diff --git a/.coveragerc b/.coveragerc
index 4bd5b63fa..74dccbfe1 100644
--- a/.coveragerc
+++ b/.coveragerc
@@ -1,6 +1,7 @@
 [run]
 omit =
     scripts/*
-    freqtrade/tests/*
+    freqtrade/templates/*
     freqtrade/vendor/*
     freqtrade/__main__.py
+    tests/*
diff --git a/.devcontainer/Dockerfile b/.devcontainer/Dockerfile
new file mode 100644
index 000000000..b333dc19d
--- /dev/null
+++ b/.devcontainer/Dockerfile
@@ -0,0 +1,18 @@
+FROM freqtradeorg/freqtrade:develop
+
+# Install dependencies
+COPY requirements-dev.txt /freqtrade/
+RUN apt-get update \
+    && apt-get -y install git sudo vim \
+    && apt-get clean \
+    && pip install autopep8 -r docs/requirements-docs.txt -r requirements-dev.txt --no-cache-dir \
+    && useradd -u 1000 -U -m ftuser \
+    && mkdir -p /home/ftuser/.vscode-server /home/ftuser/.vscode-server-insiders /home/ftuser/commandhistory \
+    && echo "export PROMPT_COMMAND='history -a'" >> /home/ftuser/.bashrc \
+    && echo "export HISTFILE=~/commandhistory/.bash_history" >> /home/ftuser/.bashrc \
+    && chown ftuser: -R /home/ftuser/
+
+USER ftuser
+
+# Empty the ENTRYPOINT to allow all commands
+ENTRYPOINT []
diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
new file mode 100644
index 000000000..1882e3bdf
--- /dev/null
+++ b/.devcontainer/devcontainer.json
@@ -0,0 +1,44 @@
+{
+    "name": "freqtrade Develop",
+
+    "dockerComposeFile": [
+        "docker-compose.yml"
+    ],
+
+    "service": "ft_vscode",
+
+    "workspaceFolder": "/freqtrade/",
+
+    "settings": {
+        "terminal.integrated.shell.linux": "/bin/bash",
+        "editor.insertSpaces": true,
+        "files.trimTrailingWhitespace": true,
+        "[markdown]": {
+            "files.trimTrailingWhitespace": false,
+        },
+        "python.pythonPath": "/usr/local/bin/python",
+    },
+
+    // Add the IDs of extensions you want installed when the container is created.
+    "extensions": [
+        "ms-python.python",
+        "ms-python.vscode-pylance",
+        "davidanson.vscode-markdownlint",
+        "ms-azuretools.vscode-docker",
+    ],
+
+    // Use 'forwardPorts' to make a list of ports inside the container available locally.
+    // "forwardPorts": [],
+
+    // Uncomment the next line if you want start specific services in your Docker Compose config.
+    // "runServices": [],
+
+    // Uncomment the next line if you want to keep your containers running after VS Code shuts down.
+    // "shutdownAction": "none",
+
+    // Uncomment the next line to run commands after the container is created - for example installing curl.
+    // "postCreateCommand": "sudo apt-get update && apt-get install -y git",
+
+    // Uncomment to connect as a non-root user if you've added one. See https://aka.ms/vscode-remote/containers/non-root.
+    "remoteUser": "ftuser"
+}
diff --git a/.devcontainer/docker-compose.yml b/.devcontainer/docker-compose.yml
new file mode 100644
index 000000000..20ec247d1
--- /dev/null
+++ b/.devcontainer/docker-compose.yml
@@ -0,0 +1,24 @@
+---
+version: '3'
+services:
+  ft_vscode:
+    build:
+      context: ..
+      dockerfile: ".devcontainer/Dockerfile"
+    volumes:
+      # Allow git usage within container
+      - "${HOME}/.ssh:/home/ftuser/.ssh:ro"
+      - "${HOME}/.gitconfig:/home/ftuser/.gitconfig:ro"
+      - ..:/freqtrade:cached
+      # Persist bash-history
+      - freqtrade-vscode-server:/home/ftuser/.vscode-server
+      - freqtrade-bashhistory:/home/ftuser/commandhistory
+    # Expose API port
+    ports:
+      - "127.0.0.1:8080:8080"
+    command: /bin/sh -c "while sleep 1000; do :; done"
+
+
+volumes:
+  freqtrade-vscode-server:
+  freqtrade-bashhistory:
diff --git a/.dockerignore b/.dockerignore
index 223b3b110..09f4c9f0c 100644
--- a/.dockerignore
+++ b/.dockerignore
@@ -13,3 +13,4 @@ CONTRIBUTING.md
 MANIFEST.in
 README.md
 freqtrade.service
+user_data
diff --git a/.github/ISSUE_TEMPLATE.md b/.github/ISSUE_TEMPLATE.md
deleted file mode 100644
index 94d998310..000000000
--- a/.github/ISSUE_TEMPLATE.md
+++ /dev/null
@@ -1,32 +0,0 @@
-## Step 1: Have you search for this issue before posting it?
-
-If you have discovered a bug in the bot, please [search our issue tracker](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue). 
-If it hasn't been reported, please create a new issue.
-
-## Step 2: Describe your environment
-
-  * Python Version: _____ (`python -V`)
-  * CCXT version: _____ (`pip freeze | grep ccxt`)
-  * Branch: Master | Develop
-  * Last Commit ID: _____ (`git log --format="%H" -n 1`)
-  
-## Step 3: Describe the problem:
-
-*Explain the problem you have encountered*
-
-### Steps to reproduce:
-
-  1. _____
-  2. _____
-  3. _____
-  
-### Observed Results:
-
-  * What happened?
-  * What did you expect to happen?
-
-### Relevant code exceptions or logs:
-
-  ```
-  // paste your log here
-  ```
diff --git a/.github/ISSUE_TEMPLATE/bug_report.md b/.github/ISSUE_TEMPLATE/bug_report.md
new file mode 100644
index 000000000..dacd9e673
--- /dev/null
+++ b/.github/ISSUE_TEMPLATE/bug_report.md
@@ -0,0 +1,48 @@
+---
+name: Bug report
+about: Create a report to help us improve
+title: ''
+labels: "Triage Needed"
+assignees: ''
+
+---
+<!-- 
+Have you searched for similar issues before posting it?
+
+If you have discovered a bug in the bot, please [search our issue tracker](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue). 
+If it hasn't been reported, please create a new issue.
+
+Please do not use bug reports to request new features.
+-->
+
+## Describe your environment
+
+  * Operating system: ____
+  * Python Version: _____ (`python -V`)
+  * CCXT version: _____ (`pip freeze | grep ccxt`)
+  * Freqtrade Version: ____ (`freqtrade -V` or `docker-compose run --rm freqtrade -V` for Freqtrade running in docker)
+  
+Note: All issues other than enhancement requests will be closed without further comment if the above template is deleted or not filled out.
+
+## Describe the problem:
+
+*Explain the problem you have encountered*
+
+### Steps to reproduce:
+
+  1. _____
+  2. _____
+  3. _____
+  
+### Observed Results:
+
+  * What happened?
+  * What did you expect to happen?
+
+### Relevant code exceptions or logs
+
+Note: Please copy/paste text of the messages, no screenshots of logs please.
+
+  ```
+  // paste your log here
+  ```
diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md
new file mode 100644
index 000000000..c32fb33c2
--- /dev/null
+++ b/.github/ISSUE_TEMPLATE/feature_request.md
@@ -0,0 +1,27 @@
+---
+name: Feature request
+about: Suggest an idea for this project
+title: ''
+labels: ''
+assignees: ''
+
+---
+
+<!-- 
+Note: this section will not show up in the issue.
+Have you search for this feature before requesting it? It's highly likely that a similar request was already filed.
+-->
+
+## Describe your environment
+(if applicable)
+
+  * Operating system: ____
+  * Python Version: _____ (`python -V`)
+  * CCXT version: _____ (`pip freeze | grep ccxt`)
+  * Freqtrade Version: ____ (`freqtrade -V` or `docker-compose run --rm freqtrade -V` for Freqtrade running in docker)
+
+
+## Describe the enhancement
+
+*Explain the enhancement you would like*
+
diff --git a/.github/ISSUE_TEMPLATE/question.md b/.github/ISSUE_TEMPLATE/question.md
new file mode 100644
index 000000000..f87b78f29
--- /dev/null
+++ b/.github/ISSUE_TEMPLATE/question.md
@@ -0,0 +1,25 @@
+---
+name: BQuestion
+about: Ask a question you could not find an answer in the docs
+title: ''
+labels: "Question"
+assignees: ''
+
+---
+<!-- 
+Have you searched for similar issues before posting it?
+Did you have a VERY good look at the [documentation](https://www.freqtrade.io/en/latest/) and are sure that the question is not explained there
+
+Please do not use the question template to report bugs or to request new features.
+-->
+
+## Describe your environment
+
+  * Operating system: ____
+  * Python Version: _____ (`python -V`)
+  * CCXT version: _____ (`pip freeze | grep ccxt`)
+  * Freqtrade Version: ____ (`freqtrade -V` or `docker-compose run --rm freqtrade -V` for Freqtrade running in docker)
+  
+## Your question
+
+*Ask the question you have not been able to find an answer in our [Documentation](https://www.freqtrade.io/en/latest/)*
diff --git a/.github/dependabot.yml b/.github/dependabot.yml
new file mode 100644
index 000000000..44ff606b4
--- /dev/null
+++ b/.github/dependabot.yml
@@ -0,0 +1,13 @@
+version: 2
+updates:
+- package-ecosystem: docker
+  directory: "/"
+  schedule:
+    interval: daily
+  open-pull-requests-limit: 10
+- package-ecosystem: pip
+  directory: "/"
+  schedule:
+    interval: weekly
+  open-pull-requests-limit: 10
+  target-branch: develop
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
new file mode 100644
index 000000000..f259129d4
--- /dev/null
+++ b/.github/workflows/ci.yml
@@ -0,0 +1,317 @@
+name: Freqtrade CI
+
+on:
+  push:
+    branches:
+      - master
+      - stable
+      - develop
+    tags:
+  release:
+    types: [published]
+  pull_request:
+  schedule:
+    - cron:  '0 5 * * 4'
+
+jobs:
+  build:
+
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [ ubuntu-18.04, ubuntu-20.04, macos-latest ]
+        python-version: [3.7, 3.8]
+
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: ${{ matrix.python-version }}
+
+    - name: Cache_dependencies
+      uses: actions/cache@v1
+      id: cache
+      with:
+        path: ~/dependencies/
+        key: ${{ runner.os }}-dependencies
+
+    - name: pip cache (linux)
+      uses: actions/cache@preview
+      if: startsWith(matrix.os, 'ubuntu')
+      with:
+        path: ~/.cache/pip
+        key: test-${{ matrix.os }}-${{ matrix.python-version }}-pip
+
+    - name: pip cache (macOS)
+      uses: actions/cache@preview
+      if: startsWith(matrix.os, 'macOS')
+      with:
+        path: ~/Library/Caches/pip
+        key: test-${{ matrix.os }}-${{ matrix.python-version }}-pip
+
+    - name: TA binary *nix
+      if: steps.cache.outputs.cache-hit != 'true'
+      run: |
+        cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies/; cd ..
+
+    - name: Installation - *nix
+      run: |
+        python -m pip install --upgrade pip
+        export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
+        export TA_LIBRARY_PATH=${HOME}/dependencies/lib
+        export TA_INCLUDE_PATH=${HOME}/dependencies/include
+        pip install -r requirements-dev.txt
+        pip install -e .
+
+    - name: Tests
+      run: |
+        pytest --random-order --cov=freqtrade --cov-config=.coveragerc
+
+    - name: Coveralls
+      if: (startsWith(matrix.os, 'ubuntu-20') && matrix.python-version == '3.8')
+      env:
+        # Coveralls token. Not used as secret due to github not providing secrets to forked repositories
+        COVERALLS_REPO_TOKEN: 6D1m0xupS3FgutfuGao8keFf9Hc0FpIXu
+      run: |
+        # Allow failure for coveralls
+        coveralls -v  || true
+
+    - name: Backtesting
+      run: |
+        cp config.json.example config.json
+        freqtrade create-userdir --userdir user_data
+        freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
+
+    - name: Hyperopt
+      run: |
+        cp config.json.example config.json
+        freqtrade create-userdir --userdir user_data
+        freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
+
+    - name: Flake8
+      run: |
+        flake8
+
+    - name: Sort imports (isort)
+      run: |
+        isort --check .
+
+    - name: Mypy
+      run: |
+        mypy freqtrade scripts
+
+    - name: Slack Notification
+      uses: homoluctus/slatify@v1.8.0
+      if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
+      with:
+        type: ${{ job.status }}
+        job_name: '*Freqtrade CI ${{ matrix.os }}*'
+        mention: 'here'
+        mention_if: 'failure'
+        channel: '#notifications'
+        url: ${{ secrets.SLACK_WEBHOOK }}
+
+  build_windows:
+
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [ windows-latest ]
+        python-version: [3.7, 3.8]
+
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: ${{ matrix.python-version }}
+
+    - name: Pip cache (Windows)
+      uses: actions/cache@preview
+      if: startsWith(runner.os, 'Windows')
+      with:
+        path: ~\AppData\Local\pip\Cache
+        key: ${{ matrix.os }}-${{ matrix.python-version }}-pip
+
+    - name: Installation
+      run: |
+        ./build_helpers/install_windows.ps1
+
+    - name: Tests
+      run: |
+        pytest --random-order --cov=freqtrade --cov-config=.coveragerc
+
+    - name: Backtesting
+      run: |
+        cp config.json.example config.json
+        freqtrade create-userdir --userdir user_data
+        freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
+
+    - name: Hyperopt
+      run: |
+        cp config.json.example config.json
+        freqtrade create-userdir --userdir user_data
+        freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
+
+    - name: Flake8
+      run: |
+        flake8
+
+    - name: Mypy
+      run: |
+        mypy freqtrade scripts
+
+    - name: Slack Notification
+      uses: homoluctus/slatify@v1.8.0
+      if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
+      with:
+        type: ${{ job.status }}
+        job_name: '*Freqtrade CI windows*'
+        mention: 'here'
+        mention_if: 'failure'
+        channel: '#notifications'
+        url: ${{ secrets.SLACK_WEBHOOK }}
+
+  docs_check:
+    runs-on: ubuntu-20.04
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Documentation syntax
+      run: |
+        ./tests/test_docs.sh
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: 3.8
+
+    - name: Documentation build
+      run: |
+        pip install -r docs/requirements-docs.txt
+        pip install mkdocs
+        mkdocs build
+
+    - name: Slack Notification
+      uses: homoluctus/slatify@v1.8.0
+      if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
+      with:
+        type: ${{ job.status }}
+        job_name: '*Freqtrade Docs*'
+        channel: '#notifications'
+        url: ${{ secrets.SLACK_WEBHOOK }}
+
+  cleanup-prior-runs:
+    runs-on: ubuntu-20.04
+    steps:
+    - name: Cleanup previous runs on this branch
+      uses: rokroskar/workflow-run-cleanup-action@v0.2.2
+      if: "!startsWith(github.ref, 'refs/tags/') && github.ref != 'refs/heads/stable' && github.repository == 'freqtrade/freqtrade'"
+      env:
+        GITHUB_TOKEN: "${{ secrets.GITHUB_TOKEN }}"
+
+  # Notify on slack only once - when CI completes (and after deploy) in case it's successfull
+  notify-complete:
+    needs: [ build, build_windows, docs_check ]
+    runs-on: ubuntu-20.04
+    steps:
+    - name: Slack Notification
+      uses: homoluctus/slatify@v1.8.0
+      if: always() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
+      with:
+        type: ${{ job.status }}
+        job_name: '*Freqtrade CI*'
+        channel: '#notifications'
+        url: ${{ secrets.SLACK_WEBHOOK }}
+
+  deploy:
+    needs: [ build, build_windows, docs_check ]
+    runs-on: ubuntu-20.04
+    if: (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'release') && github.repository == 'freqtrade/freqtrade'
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: 3.8
+
+    - name: Extract branch name
+      shell: bash
+      run: echo "##[set-output name=branch;]$(echo ${GITHUB_REF##*/})"
+      id: extract_branch
+
+    - name: Build distribution
+      run: |
+        pip install -U setuptools wheel
+        python setup.py sdist bdist_wheel
+
+    - name: Publish to PyPI (Test)
+      uses: pypa/gh-action-pypi-publish@master
+      if: (github.event_name == 'release')
+      with:
+        user: __token__
+        password: ${{ secrets.pypi_test_password }}
+        repository_url: https://test.pypi.org/legacy/
+
+    - name: Publish to PyPI
+      uses: pypa/gh-action-pypi-publish@master
+      if: (github.event_name == 'release')
+      with:
+        user: __token__
+        password: ${{ secrets.pypi_password }}
+
+    - name: Dockerhub login
+      env:
+        DOCKER_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
+        DOCKER_USERNAME: ${{ secrets.DOCKER_USERNAME }}
+      run: |
+        echo "${DOCKER_PASSWORD}" | docker login --username ${DOCKER_USERNAME} --password-stdin
+
+    - name: Build and test and push docker image
+      env:
+        IMAGE_NAME: freqtradeorg/freqtrade
+        BRANCH_NAME: ${{ steps.extract_branch.outputs.branch }}
+      run: |
+        build_helpers/publish_docker.sh
+
+    # We need docker experimental to pull the ARM image.
+    - name: Switch docker to experimental
+      run: |
+          docker version -f '{{.Server.Experimental}}'
+          echo $'{\n    "experimental": true\n}' | sudo tee /etc/docker/daemon.json
+          sudo systemctl restart docker
+          docker version -f '{{.Server.Experimental}}'
+
+    - name: Set up Docker Buildx
+      id: buildx
+      uses: crazy-max/ghaction-docker-buildx@v1
+      with:
+        buildx-version: latest
+        qemu-version: latest
+
+    - name: Available platforms
+      run: echo ${{ steps.buildx.outputs.platforms }}
+
+    - name: Build Raspberry docker image
+      env:
+        IMAGE_NAME: freqtradeorg/freqtrade
+        BRANCH_NAME: ${{ steps.extract_branch.outputs.branch }}_pi
+      run: |
+        build_helpers/publish_docker_pi.sh
+
+
+    - name: Slack Notification
+      uses: homoluctus/slatify@v1.8.0
+      if: always() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
+      with:
+        type: ${{ job.status }}
+        job_name: '*Freqtrade CI Deploy*'
+        mention: 'here'
+        mention_if: 'failure'
+        channel: '#notifications'
+        url: ${{ secrets.SLACK_WEBHOOK }}
+
diff --git a/.github/workflows/docker_update_readme.yml b/.github/workflows/docker_update_readme.yml
new file mode 100644
index 000000000..95e69be2a
--- /dev/null
+++ b/.github/workflows/docker_update_readme.yml
@@ -0,0 +1,18 @@
+name: Update Docker Hub Description
+on:
+  push:
+    branches:
+    - stable
+
+jobs:
+  dockerHubDescription:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v1
+    - name: Docker Hub Description
+      uses: peter-evans/dockerhub-description@v2.1.0
+      env:
+        DOCKERHUB_USERNAME: ${{ secrets.DOCKER_USERNAME }}
+        DOCKERHUB_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
+        DOCKERHUB_REPOSITORY: freqtradeorg/freqtrade
+
diff --git a/.gitignore b/.gitignore
index 9ed046c40..f206fce66 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,12 +1,11 @@
 # Freqtrade rules
-freqtrade/tests/testdata/*.json
-hyperopt_conf.py
 config*.json
 *.sqlite
-.hyperopt
 logfile.txt
-hyperopt_trials.pickle
-user_data/
+user_data/*
+!user_data/strategy/sample_strategy.py
+!user_data/notebooks
+user_data/notebooks/*
 freqtrade-plot.html
 freqtrade-profit-plot.html
 
@@ -80,8 +79,7 @@ docs/_build/
 target/
 
 # Jupyter Notebook
-.ipynb_checkpoints
-*.ipynb
+*.ipynb_checkpoints
 
 # pyenv
 .python-version
@@ -93,3 +91,6 @@ target/
 
 .pytest_cache/
 .mypy_cache/
+
+#exceptions
+!*.gitkeep
diff --git a/.pyup.yml b/.pyup.yml
deleted file mode 100644
index b1b721113..000000000
--- a/.pyup.yml
+++ /dev/null
@@ -1,37 +0,0 @@
-# autogenerated pyup.io config file
-# see https://pyup.io/docs/configuration/ for all available options
-
-# configure updates globally
-# default: all
-# allowed: all, insecure, False
-update: all
-
-# configure dependency pinning globally
-# default: True
-# allowed: True, False
-pin: True
-
-# update schedule
-# default: empty
-# allowed: "every day", "every week", ..
-schedule: "every week"
-
-
-search: False
-# Specify requirement files by hand, default is empty
-# default: empty
-# allowed: list
-requirements:
-  - requirements.txt
-  - requirements-dev.txt
-  - requirements-plot.txt
-  - requirements-common.txt
-
-
-# configure the branch prefix the bot is using
-# default: pyup-
-branch_prefix: pyup/
-
-# allow to close stale PRs
-# default: True
-close_prs: True
diff --git a/.travis.yml b/.travis.yml
index b44fef7a1..9b8448db5 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -1,4 +1,3 @@
-sudo: true
 os:
 - linux
 dist: xenial
@@ -10,15 +9,11 @@ services:
 env:
   global:
     - IMAGE_NAME=freqtradeorg/freqtrade
-addons:
-  apt:
-    packages:
-    - libelf-dev
-    - libdw-dev
-    - binutils-dev
 install:
-- cd build_helpers && ./install_ta-lib.sh; cd ..
-- export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
+- cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies; cd ..
+- export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
+- export TA_LIBRARY_PATH=${HOME}/dependencies/lib
+- export TA_INCLUDE_PATH=${HOME}/dependencies/include
 - pip install -r requirements-dev.txt
 - pip install -e .
 jobs:
@@ -26,28 +21,36 @@ jobs:
   include:
     - stage: tests
       script:
-      - pytest --random-order --cov=freqtrade --cov-config=.coveragerc freqtrade/tests/
+      - pytest --random-order --cov=freqtrade --cov-config=.coveragerc
       # Allow failure for coveralls
-      - coveralls || true
+      # - coveralls || true
       name: pytest
     - script:
       - cp config.json.example config.json
-      - freqtrade --datadir freqtrade/tests/testdata backtesting
+      - freqtrade create-userdir --userdir user_data
+      - freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
       name: backtest
     - script:
       - cp config.json.example config.json
-      - freqtrade --datadir freqtrade/tests/testdata hyperopt -e 5
+      - freqtrade create-userdir --userdir user_data
+      - freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily
       name: hyperopt
-    - script: flake8 freqtrade scripts
+    - script: flake8
       name: flake8
+    - script:
+      # Test Documentation boxes -
+      # !!! <TYPE>: is not allowed!
+      # !!! <TYPE> "title" - Title needs to be quoted!
+      - grep -Er '^!{3}\s\S+:|^!{3}\s\S+\s[^"]' docs/*; test $? -ne 0
+      name: doc syntax
     - script: mypy freqtrade scripts
       name: mypy
 
-    - stage: docker
-      if: branch in (master, develop, feat/improve_travis) AND (type in (push, cron))
-      script:
-        - build_helpers/publish_docker.sh
-      name: "Build and test and push docker image"
+    # - stage: docker
+    #   if: branch in (master, develop, feat/improve_travis) AND (type in (push, cron))
+    #   script:
+    #     - build_helpers/publish_docker.sh
+    #   name: "Build and test and push docker image"
 
 notifications:
   slack:
@@ -55,4 +58,4 @@ notifications:
 cache:
   pip: True
   directories:
-    - /usr/local/lib/
+    - $HOME/dependencies
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index e15059f56..6b4e8adaf 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -8,17 +8,17 @@ Issues labeled [good first issue](https://github.com/freqtrade/freqtrade/labels/
 
 Few pointers for contributions:
 
-- Create your PR against the `develop` branch, not `master`.
-- New features need to contain unit tests and must be PEP8 conformant (max-line-length = 100).
+- Create your PR against the `develop` branch, not `stable`.
+- New features need to contain unit tests, must conform to PEP8 (max-line-length = 100) and should be documented with the introduction PR.
+- PR's can be declared as `[WIP]` - which signify Work in Progress Pull Requests (which are not finished).
 
-If you are unsure, discuss the feature on our [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/enQtNjU5ODcwNjI1MDU3LWEyODBiNzkzNzcyNzU0MWYyYzE5NjIyOTQxMzBmMGUxOTIzM2YyN2Y4NWY1YTEwZDgwYTRmMzE2NmM5ZmY2MTg)
-or in a [issue](https://github.com/freqtrade/freqtrade/issues) before a PR.
+If you are unsure, discuss the feature on our [discord server](https://discord.gg/MA9v74M), on [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-jaut7r4m-Y17k4x5mcQES9a9swKuxbg) or in a [issue](https://github.com/freqtrade/freqtrade/issues) before a PR.
 
 ## Getting started
 
 Best start by reading the [documentation](https://www.freqtrade.io/) to get a feel for what is possible with the bot, or head straight to the [Developer-documentation](https://www.freqtrade.io/en/latest/developer/) (WIP) which should help you getting started.
 
-## Before sending the PR:
+## Before sending the PR
 
 ### 1. Run unit tests
 
@@ -28,19 +28,19 @@ make it pass. It means you have introduced a regression.
 #### Test the whole project
 
 ```bash
-pytest freqtrade
+pytest
 ```
 
 #### Test only one file
 
 ```bash
-pytest freqtrade/tests/test_<file_name>.py
+pytest tests/test_<file_name>.py
 ```
 
 #### Test only one method from one file
 
 ```bash
-pytest freqtrade/tests/test_<file_name>.py::test_<method_name>
+pytest tests/test_<file_name>.py::test_<method_name>
 ```
 
 ### 2. Test if your code is PEP8 compliant
@@ -48,7 +48,7 @@ pytest freqtrade/tests/test_<file_name>.py::test_<method_name>
 #### Run Flake8
 
 ```bash
-flake8 freqtrade
+flake8 freqtrade tests scripts
 ```
 
 We receive a lot of code that fails the `flake8` checks.
@@ -64,6 +64,14 @@ Guide for installing them is [here](http://flake8.pycqa.org/en/latest/user/using
 mypy freqtrade
 ```
 
+### 4. Ensure all imports are correct
+
+#### Run isort
+
+``` bash
+isort .
+```
+
 ## (Core)-Committer Guide
 
 ### Process: Pull Requests
@@ -109,11 +117,11 @@ Exceptions:
 
 Contributors may be given commit privileges. Preference will be given to those with:
 
-1. Past contributions to FreqTrade and other related open-source projects. Contributions to FreqTrade include both code (both accepted and pending) and friendly participation in the issue tracker and Pull request reviews. Quantity and quality are considered.
+1. Past contributions to Freqtrade and other related open-source projects. Contributions to Freqtrade include both code (both accepted and pending) and friendly participation in the issue tracker and Pull request reviews. Quantity and quality are considered.
 1. A coding style that the other core committers find simple, minimal, and clean.
 1. Access to resources for cross-platform development and testing.
 1. Time to devote to the project regularly.
 
-Beeing a Committer does not grant write permission on `develop` or `master` for security reasons (Users trust FreqTrade with their Exchange API keys).
+Being a Committer does not grant write permission on `develop` or `stable` for security reasons (Users trust Freqtrade with their Exchange API keys).
 
-After beeing Committer for some time, a Committer may be named Core Committer and given full repository access.
+After being Committer for some time, a Committer may be named Core Committer and given full repository access.
diff --git a/Dockerfile b/Dockerfile
index 7a0298719..2be65274e 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,7 +1,7 @@
-FROM python:3.7.3-slim-stretch
+FROM python:3.8.6-slim-buster
 
 RUN apt-get update \
-    && apt-get -y install curl build-essential libssl-dev \
+    && apt-get -y install curl build-essential libssl-dev sqlite3 \
     && apt-get clean \
     && pip install --upgrade pip
 
@@ -16,11 +16,14 @@ RUN cd /tmp && /tmp/install_ta-lib.sh && rm -r /tmp/*ta-lib*
 ENV LD_LIBRARY_PATH /usr/local/lib
 
 # Install dependencies
-COPY requirements.txt requirements-common.txt /freqtrade/
+COPY requirements.txt requirements-hyperopt.txt /freqtrade/
 RUN pip install numpy --no-cache-dir \
-  && pip install -r requirements.txt --no-cache-dir
+  && pip install -r requirements-hyperopt.txt --no-cache-dir
 
 # Install and execute
 COPY . /freqtrade/
-RUN pip install -e . --no-cache-dir
+RUN pip install -e . --no-cache-dir \
+  && mkdir /freqtrade/user_data/
 ENTRYPOINT ["freqtrade"]
+# Default to trade mode
+CMD [ "trade" ]
diff --git a/Dockerfile.armhf b/Dockerfile.armhf
new file mode 100644
index 000000000..0633008ea
--- /dev/null
+++ b/Dockerfile.armhf
@@ -0,0 +1,29 @@
+FROM --platform=linux/arm/v7 python:3.7.7-slim-buster
+
+RUN apt-get update \
+  && apt-get -y install curl build-essential libssl-dev libffi-dev libatlas3-base libgfortran5 sqlite3 \
+  && apt-get clean \
+  && pip install --upgrade pip \
+  && echo "[global]\nextra-index-url=https://www.piwheels.org/simple" > /etc/pip.conf
+
+# Prepare environment
+RUN mkdir /freqtrade
+WORKDIR /freqtrade
+
+# Install TA-lib
+COPY build_helpers/* /tmp/
+RUN cd /tmp && /tmp/install_ta-lib.sh && rm -r /tmp/*ta-lib*
+
+ENV LD_LIBRARY_PATH /usr/local/lib
+
+# Install dependencies
+COPY requirements.txt /freqtrade/
+RUN pip install numpy --no-cache-dir \
+  && pip install -r requirements.txt --no-cache-dir
+
+# Install and execute
+COPY . /freqtrade/
+RUN pip install -e . --no-cache-dir
+ENTRYPOINT ["freqtrade"]
+# Default to trade mode
+CMD [ "trade" ]
diff --git a/Dockerfile.pi b/Dockerfile.pi
deleted file mode 100644
index 1b9c4c579..000000000
--- a/Dockerfile.pi
+++ /dev/null
@@ -1,40 +0,0 @@
-FROM balenalib/raspberrypi3-debian:stretch
-
-RUN [ "cross-build-start" ]
-
-RUN apt-get update \
- && apt-get -y install wget curl build-essential libssl-dev libffi-dev \
- && apt-get clean
-
-# Prepare environment
-RUN mkdir /freqtrade
-WORKDIR /freqtrade
-
-# Install TA-lib
-COPY build_helpers/ta-lib-0.4.0-src.tar.gz /freqtrade/
-RUN tar -xzf /freqtrade/ta-lib-0.4.0-src.tar.gz \
- && cd /freqtrade/ta-lib/ \
- && ./configure \
- && make \
- && make install \
- && rm /freqtrade/ta-lib-0.4.0-src.tar.gz
-
-ENV LD_LIBRARY_PATH /usr/local/lib
-
-# Install berryconda
-RUN wget https://github.com/jjhelmus/berryconda/releases/download/v2.0.0/Berryconda3-2.0.0-Linux-armv7l.sh \
- && bash ./Berryconda3-2.0.0-Linux-armv7l.sh -b \
- && rm Berryconda3-2.0.0-Linux-armv7l.sh
-
-# Install dependencies
-COPY requirements-common.txt /freqtrade/
-RUN ~/berryconda3/bin/conda install -y numpy pandas scipy \
- && ~/berryconda3/bin/pip install -r requirements-common.txt --no-cache-dir
-
-# Install and execute
-COPY . /freqtrade/
-RUN ~/berryconda3/bin/pip install -e . --no-cache-dir
-
-RUN [ "cross-build-end" ]
-
-ENTRYPOINT ["/root/berryconda3/bin/python","./freqtrade/main.py"]
diff --git a/MANIFEST.in b/MANIFEST.in
index 63508c05d..c67f5258f 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -2,4 +2,4 @@ include LICENSE
 include README.md
 include config.json.example
 recursive-include freqtrade *.py
-include freqtrade/tests/testdata/*.json
+recursive-include freqtrade/templates/ *.j2 *.ipynb
diff --git a/README.md b/README.md
index 240b4f917..8526b5c91 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
 # Freqtrade
 
-[![Build Status](https://travis-ci.org/freqtrade/freqtrade.svg?branch=develop)](https://travis-ci.org/freqtrade/freqtrade)
+[![Freqtrade CI](https://github.com/freqtrade/freqtrade/workflows/Freqtrade%20CI/badge.svg)](https://github.com/freqtrade/freqtrade/actions/)
 [![Coverage Status](https://coveralls.io/repos/github/freqtrade/freqtrade/badge.svg?branch=develop&service=github)](https://coveralls.io/github/freqtrade/freqtrade?branch=develop)
 [![Documentation](https://readthedocs.org/projects/freqtrade/badge/)](https://www.freqtrade.io)
 [![Maintainability](https://api.codeclimate.com/v1/badges/5737e6d668200b7518ff/maintainability)](https://codeclimate.com/github/freqtrade/freqtrade/maintainability)
@@ -25,7 +25,8 @@ hesitate to read the source code and understand the mechanism of this bot.
 ## Exchange marketplaces supported
 
 - [X] [Bittrex](https://bittrex.com/)
-- [X] [Binance](https://www.binance.com/) ([*Note for binance users](#a-note-on-binance))
+- [X] [Binance](https://www.binance.com/) ([*Note for binance users](docs/exchanges.md#blacklists))
+- [X] [Kraken](https://kraken.com/)
 - [ ] [113 others to tests](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
 
 ## Documentation
@@ -54,94 +55,90 @@ Please find the complete documentation on our [website](https://www.freqtrade.io
 Freqtrade provides a Linux/macOS script to install all dependencies and help you to configure the bot.
 
 ```bash
-git clone git@github.com:freqtrade/freqtrade.git
+git clone -b develop https://github.com/freqtrade/freqtrade.git 
 cd freqtrade
-git checkout develop
 ./setup.sh --install
 ```
 
 For any other type of installation please refer to [Installation doc](https://www.freqtrade.io/en/latest/installation/).
 
-
 ## Basic Usage
 
 ### Bot commands
 
 ```
-usage: freqtrade [-h] [-v] [--logfile FILE] [--version] [-c PATH] [-d PATH]
-                 [-s NAME] [--strategy-path PATH] [--dynamic-whitelist [INT]]
-                 [--db-url PATH] [--sd-notify]
-                 {backtesting,edge,hyperopt} ...
+usage: freqtrade [-h] [-V]
+                 {trade,create-userdir,new-config,new-hyperopt,new-strategy,download-data,convert-data,convert-trade-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,plot-dataframe,plot-profit}
+                 ...
 
 Free, open source crypto trading bot
 
 positional arguments:
-  {backtesting,edge,hyperopt}
+  {trade,create-userdir,new-config,new-hyperopt,new-strategy,download-data,convert-data,convert-trade-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,plot-dataframe,plot-profit}
+    trade               Trade module.
+    create-userdir      Create user-data directory.
+    new-config          Create new config
+    new-hyperopt        Create new hyperopt
+    new-strategy        Create new strategy
+    download-data       Download backtesting data.
+    convert-data        Convert candle (OHLCV) data from one format to
+                        another.
+    convert-trade-data  Convert trade data from one format to another.
     backtesting         Backtesting module.
     edge                Edge module.
     hyperopt            Hyperopt module.
+    hyperopt-list       List Hyperopt results
+    hyperopt-show       Show details of Hyperopt results
+    list-exchanges      Print available exchanges.
+    list-hyperopts      Print available hyperopt classes.
+    list-markets        Print markets on exchange.
+    list-pairs          Print pairs on exchange.
+    list-strategies     Print available strategies.
+    list-timeframes     Print available timeframes for the exchange.
+    show-trades         Show trades.
+    test-pairlist       Test your pairlist configuration.
+    plot-dataframe      Plot candles with indicators.
+    plot-profit         Generate plot showing profits.
 
 optional arguments:
   -h, --help            show this help message and exit
-  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
-  --logfile FILE        Log to the file specified
-  --version             show program's version number and exit
-  -c PATH, --config PATH
-                        Specify configuration file (default: None). Multiple
-                        --config options may be used.
-  -d PATH, --datadir PATH
-                        Path to backtest data.
-  -s NAME, --strategy NAME
-                        Specify strategy class name (default:
-                        DefaultStrategy).
-  --strategy-path PATH  Specify additional strategy lookup path.
-  --dynamic-whitelist [INT]
-                        Dynamically generate and update whitelist based on 24h
-                        BaseVolume (default: 20). DEPRECATED.
-  --db-url PATH         Override trades database URL, this is useful if
-                        dry_run is enabled or in custom deployments (default:
-                        None).
-  --sd-notify           Notify systemd service manager.
+  -V, --version         show program's version number and exit
+
 ```
 
 ### Telegram RPC commands
 
-Telegram is not mandatory. However, this is a great way to control your bot. More details on our [documentation](https://www.freqtrade.io/en/latest/telegram-usage/)
+Telegram is not mandatory. However, this is a great way to control your bot. More details and the full command list on our [documentation](https://www.freqtrade.io/en/latest/telegram-usage/)
 
-- `/start`: Starts the trader
-- `/stop`: Stops the trader
-- `/status [table]`: Lists all open trades
-- `/count`: Displays number of open trades
+- `/start`: Starts the trader.
+- `/stop`: Stops the trader.
+- `/stopbuy`: Stop entering new trades.
+- `/status [table]`: Lists all open trades.
 - `/profit`: Lists cumulative profit from all finished trades
 - `/forcesell <trade_id>|all`: Instantly sells the given trade (Ignoring `minimum_roi`).
 - `/performance`: Show performance of each finished trade grouped by pair
-- `/balance`: Show account balance per currency
-- `/daily <n>`: Shows profit or loss per day, over the last n days
-- `/help`: Show help message
-- `/version`: Show version
-
+- `/balance`: Show account balance per currency.
+- `/daily <n>`: Shows profit or loss per day, over the last n days.
+- `/help`: Show help message.
+- `/version`: Show version.
 
 ## Development branches
 
 The project is currently setup in two main branches:
 
-- `develop` - This branch has often new features, but might also cause breaking changes.
-- `master` - This branch contains the latest stable release. The bot 'should' be stable on this branch, and is generally well tested.
+- `develop` - This branch has often new features, but might also contain breaking changes. We try hard to keep this branch as stable as possible.
+- `stable` - This branch contains the latest stable release. This branch is generally well tested.
 - `feat/*` - These are feature branches, which are being worked on heavily. Please don't use these unless you want to test a specific feature.
 
-## A note on Binance
-
-For Binance, please add `"BNB/<STAKE>"` to your blacklist to avoid issues.
-Accounts having BNB accounts use this to pay for fees - if your first trade happens to be on `BNB`, further trades will consume this position and make the initial BNB order unsellable as the expected amount is not there anymore.
-
 ## Support
 
-### Help / Slack
+### Help / Discord / Slack
 
-For any questions not covered by the documentation or for further
-information about the bot, we encourage you to join our slack channel.
+For any questions not covered by the documentation or for further information about the bot, or to simply engage with like-minded individuals, we encourage you to join our slack channel.
 
-- [Click here to join Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/enQtNjU5ODcwNjI1MDU3LWEyODBiNzkzNzcyNzU0MWYyYzE5NjIyOTQxMzBmMGUxOTIzM2YyN2Y4NWY1YTEwZDgwYTRmMzE2NmM5ZmY2MTg).
+Please check out our [discord server](https://discord.gg/MA9v74M).
+
+You can also join our [Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/zt-jaut7r4m-Y17k4x5mcQES9a9swKuxbg).
 
 ### [Bugs / Issues](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue)
 
@@ -169,18 +166,18 @@ Please read our
 [Contributing document](https://github.com/freqtrade/freqtrade/blob/develop/CONTRIBUTING.md)
 to understand the requirements before sending your pull-requests.
 
-Coding is not a neccessity to contribute - maybe start with improving our documentation?
+Coding is not a necessity to contribute - maybe start with improving our documentation?
 Issues labeled [good first issue](https://github.com/freqtrade/freqtrade/labels/good%20first%20issue) can be good first contributions, and will help get you familiar with the codebase.
 
-**Note** before starting any major new feature work, *please open an issue describing what you are planning to do* or talk to us on [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/enQtNjU5ODcwNjI1MDU3LWEyODBiNzkzNzcyNzU0MWYyYzE5NjIyOTQxMzBmMGUxOTIzM2YyN2Y4NWY1YTEwZDgwYTRmMzE2NmM5ZmY2MTg). This will ensure that interested parties can give valuable feedback on the feature, and let others know that you are working on it.
+**Note** before starting any major new feature work, *please open an issue describing what you are planning to do* or talk to us on [discord](https://discord.gg/MA9v74M) or [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-jaut7r4m-Y17k4x5mcQES9a9swKuxbg). This will ensure that interested parties can give valuable feedback on the feature, and let others know that you are working on it.
 
-**Important:** Always create your PR against the `develop` branch, not `master`.
+**Important:** Always create your PR against the `develop` branch, not `stable`.
 
 ## Requirements
 
-### Uptodate clock
+### Up-to-date clock
 
-The clock must be accurate, syncronized to a NTP server very frequently to avoid problems with communication to the exchanges.
+The clock must be accurate, synchronized to a NTP server very frequently to avoid problems with communication to the exchanges.
 
 ### Min hardware required
 
diff --git a/bin/freqtrade b/bin/freqtrade
deleted file mode 100755
index 25c94fe98..000000000
--- a/bin/freqtrade
+++ /dev/null
@@ -1,11 +0,0 @@
-#!/usr/bin/env python3
-
-import sys
-import warnings
-
-from freqtrade.main import main
-
-warnings.warn(
-    "Deprecated - To continue to run the bot like this, please run `pip install -e .` again.",
-    DeprecationWarning)
-main(sys.argv[1:])
diff --git a/build_helpers/TA_Lib-0.4.19-cp37-cp37m-win_amd64.whl b/build_helpers/TA_Lib-0.4.19-cp37-cp37m-win_amd64.whl
new file mode 100644
index 000000000..5adbda8a7
Binary files /dev/null and b/build_helpers/TA_Lib-0.4.19-cp37-cp37m-win_amd64.whl differ
diff --git a/build_helpers/TA_Lib-0.4.19-cp38-cp38-win_amd64.whl b/build_helpers/TA_Lib-0.4.19-cp38-cp38-win_amd64.whl
new file mode 100644
index 000000000..b652c7ee0
Binary files /dev/null and b/build_helpers/TA_Lib-0.4.19-cp38-cp38-win_amd64.whl differ
diff --git a/build_helpers/install_ta-lib.sh b/build_helpers/install_ta-lib.sh
index 9fe341bba..cb86e5f64 100755
--- a/build_helpers/install_ta-lib.sh
+++ b/build_helpers/install_ta-lib.sh
@@ -1,8 +1,14 @@
-if [ ! -f "/usr/local/lib/libta_lib.a" ]; then
+if [ -z "$1" ]; then
+  INSTALL_LOC=/usr/local
+else
+  INSTALL_LOC=${1}
+fi
+echo "Installing to ${INSTALL_LOC}"
+if [ ! -f "${INSTALL_LOC}/lib/libta_lib.a" ]; then
   tar zxvf ta-lib-0.4.0-src.tar.gz
   cd ta-lib \
   && sed -i.bak "s|0.00000001|0.000000000000000001 |g" src/ta_func/ta_utility.h \
-  && ./configure \
+  && ./configure --prefix=${INSTALL_LOC}/ \
   && make \
   && which sudo && sudo make install || make install \
   && cd ..
diff --git a/build_helpers/install_windows.ps1 b/build_helpers/install_windows.ps1
new file mode 100644
index 000000000..5747db335
--- /dev/null
+++ b/build_helpers/install_windows.ps1
@@ -0,0 +1,17 @@
+# Downloads don't work automatically, since the URL is regenerated via javascript.
+# Downloaded from https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib
+# Invoke-WebRequest -Uri "https://download.lfd.uci.edu/pythonlibs/xxxxxxx/TA_Lib-0.4.17-cp37-cp37m-win_amd64.whl" -OutFile "TA_Lib-0.4.17-cp37-cp37m-win_amd64.whl"
+
+python -m pip install --upgrade pip
+
+$pyv = python -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')"
+
+if ($pyv -eq '3.7') {
+    pip install build_helpers\TA_Lib-0.4.19-cp37-cp37m-win_amd64.whl
+}
+if ($pyv -eq '3.8') {
+    pip install build_helpers\TA_Lib-0.4.19-cp38-cp38-win_amd64.whl
+}
+
+pip install -r requirements-dev.txt
+pip install -e .
diff --git a/build_helpers/publish_docker.sh b/build_helpers/publish_docker.sh
index 7a8127c44..ac0cd2461 100755
--- a/build_helpers/publish_docker.sh
+++ b/build_helpers/publish_docker.sh
@@ -1,21 +1,28 @@
 #!/bin/sh
-# - export TAG=`if [ "$TRAVIS_BRANCH" == "develop" ]; then echo "latest"; else echo $TRAVIS_BRANCH ; fi`
-# Replace / with _ to create a valid tag
-TAG=$(echo "${TRAVIS_BRANCH}" | sed -e "s/\//_/")
 
+# Replace / with _ to create a valid tag
+TAG=$(echo "${BRANCH_NAME}" | sed -e "s/\//_/g")
+TAG_PLOT=${TAG}_plot
+echo "Running for ${TAG}"
 
 # Add commit and commit_message to docker container
-echo "${TRAVIS_COMMIT} ${TRAVIS_COMMIT_MESSAGE}" > freqtrade_commit
+echo "${GITHUB_SHA}" > freqtrade_commit
 
-if [ "${TRAVIS_EVENT_TYPE}" = "cron" ]; then
-    echo "event ${TRAVIS_EVENT_TYPE}: full rebuild - skipping cache"
+if [ "${GITHUB_EVENT_NAME}" = "schedule" ]; then
+    echo "event ${GITHUB_EVENT_NAME}: full rebuild - skipping cache"
     docker build -t freqtrade:${TAG} .
 else
-    echo "event ${TRAVIS_EVENT_TYPE}: building with cache"
+    echo "event ${GITHUB_EVENT_NAME}: building with cache"
     # Pull last build to avoid rebuilding the whole image
     docker pull ${IMAGE_NAME}:${TAG}
     docker build --cache-from ${IMAGE_NAME}:${TAG} -t freqtrade:${TAG} .
 fi
+# Tag image for upload and next build step
+docker tag freqtrade:$TAG ${IMAGE_NAME}:$TAG
+
+docker build --cache-from freqtrade:${TAG} --build-arg sourceimage=${TAG} -t freqtrade:${TAG_PLOT} -f docker/Dockerfile.plot .
+
+docker tag freqtrade:$TAG_PLOT ${IMAGE_NAME}:$TAG_PLOT
 
 if [ $? -ne 0 ]; then
     echo "failed building image"
@@ -23,33 +30,23 @@ if [ $? -ne 0 ]; then
 fi
 
 # Run backtest
-docker run --rm -it -v $(pwd)/config.json.example:/freqtrade/config.json:ro freqtrade:${TAG} --datadir freqtrade/tests/testdata backtesting
+docker run --rm -v $(pwd)/config.json.example:/freqtrade/config.json:ro -v $(pwd)/tests:/tests freqtrade:${TAG} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy DefaultStrategy
 
 if [ $? -ne 0 ]; then
     echo "failed running backtest"
     return 1
 fi
 
-# Tag image for upload
-docker tag freqtrade:$TAG ${IMAGE_NAME}:$TAG
 if [ $? -ne 0 ]; then
     echo "failed tagging image"
     return 1
 fi
 
 # Tag as latest for develop builds
-if [ "${TRAVIS_BRANCH}" = "develop" ]; then
+if [ "${TAG}" = "develop" ]; then
     docker tag freqtrade:$TAG ${IMAGE_NAME}:latest
 fi
 
-# Login
-echo "$DOCKER_PASS" | docker login -u $DOCKER_USER --password-stdin
-
-if [ $? -ne 0 ]; then
-    echo "failed login"
-    return 1
-fi
-
 # Show all available images
 docker images
 
diff --git a/build_helpers/publish_docker_pi.sh b/build_helpers/publish_docker_pi.sh
new file mode 100755
index 000000000..060b1deaf
--- /dev/null
+++ b/build_helpers/publish_docker_pi.sh
@@ -0,0 +1,36 @@
+#!/bin/sh
+
+# The below assumes a correctly setup docker buildx environment
+
+# Replace / with _ to create a valid tag
+TAG=$(echo "${BRANCH_NAME}" | sed -e "s/\//_/g")
+PI_PLATFORM="linux/arm/v7"
+echo "Running for ${TAG}"
+CACHE_TAG=freqtradeorg/freqtrade_cache:${TAG}_cache
+
+# Add commit and commit_message to docker container
+echo "${GITHUB_SHA}" > freqtrade_commit
+
+if [ "${GITHUB_EVENT_NAME}" = "schedule" ]; then
+    echo "event ${GITHUB_EVENT_NAME}: full rebuild - skipping cache"
+    docker buildx build \
+        --cache-to=type=registry,ref=${CACHE_TAG} \
+        -f Dockerfile.armhf \
+        --platform ${PI_PLATFORM} \
+        -t ${IMAGE_NAME}:${TAG} --push .
+else
+    echo "event ${GITHUB_EVENT_NAME}: building with cache"
+    # Pull last build to avoid rebuilding the whole image
+    # docker pull --platform ${PI_PLATFORM} ${IMAGE_NAME}:${TAG}
+    docker buildx build \
+        --cache-from=type=registry,ref=${CACHE_TAG} \
+        --cache-to=type=registry,ref=${CACHE_TAG} \
+        -f Dockerfile.armhf \
+        --platform ${PI_PLATFORM} \
+        -t ${IMAGE_NAME}:${TAG} --push .
+fi
+
+if [ $? -ne 0 ]; then
+    echo "failed building image"
+    return 1
+fi
diff --git a/config.json.example b/config.json.example
index 94084434a..af45dac74 100644
--- a/config.json.example
+++ b/config.json.example
@@ -2,17 +2,18 @@
     "max_open_trades": 3,
     "stake_currency": "BTC",
     "stake_amount": 0.05,
+    "tradable_balance_ratio": 0.99,
     "fiat_display_currency": "USD",
-    "ticker_interval" : "5m",
-    "dry_run": false,
-    "trailing_stop": false,
+    "timeframe": "5m",
+    "dry_run": true,
+    "cancel_open_orders_on_exit": false,
     "unfilledtimeout": {
         "buy": 10,
         "sell": 30
     },
     "bid_strategy": {
-        "ask_last_balance": 0.0,
         "use_order_book": false,
+        "ask_last_balance": 0.0,
         "order_book_top": 1,
         "check_depth_of_market": {
             "enabled": false,
@@ -22,7 +23,10 @@
     "ask_strategy":{
         "use_order_book": false,
         "order_book_min": 1,
-        "order_book_max": 9
+        "order_book_max": 1,
+        "use_sell_signal": true,
+        "sell_profit_only": false,
+        "ignore_roi_if_buy_signal": false
     },
     "exchange": {
         "name": "bittrex",
@@ -40,8 +44,8 @@
             "DASH/BTC",
             "ZEC/BTC",
             "XLM/BTC",
-            "NXT/BTC",
-            "POWR/BTC",
+            "XRP/BTC",
+            "TRX/BTC",
             "ADA/BTC",
             "XMR/BTC"
         ],
@@ -49,16 +53,13 @@
             "DOGE/BTC"
         ]
     },
-    "experimental": {
-        "use_sell_signal": false,
-        "sell_profit_only": false,
-        "ignore_roi_if_buy_signal": false
-    },
+    "pairlists": [
+        {"method": "StaticPairList"}
+    ],
     "edge": {
         "enabled": false,
         "process_throttle_secs": 3600,
         "calculate_since_number_of_days": 7,
-        "capital_available_percentage": 0.5,
         "allowed_risk": 0.01,
         "stoploss_range_min": -0.01,
         "stoploss_range_max": -0.1,
@@ -70,10 +71,20 @@
         "remove_pumps": false
     },
     "telegram": {
-        "enabled": true,
+        "enabled": false,
         "token": "your_telegram_token",
         "chat_id": "your_telegram_chat_id"
     },
+    "api_server": {
+        "enabled": false,
+        "listen_ip_address": "127.0.0.1",
+        "listen_port": 8080,
+        "verbosity": "info",
+        "jwt_secret_key": "somethingrandom",
+        "CORS_origins": [],
+        "username": "",
+        "password": ""
+    },
     "initial_state": "running",
     "forcebuy_enable": false,
     "internals": {
diff --git a/config_binance.json.example b/config_binance.json.example
index 1d492fc3c..f3f8eb659 100644
--- a/config_binance.json.example
+++ b/config_binance.json.example
@@ -2,10 +2,11 @@
     "max_open_trades": 3,
     "stake_currency": "BTC",
     "stake_amount": 0.05,
+    "tradable_balance_ratio": 0.99,
     "fiat_display_currency": "USD",
-    "ticker_interval" : "5m",
+    "timeframe": "5m",
     "dry_run": true,
-    "trailing_stop": false,
+    "cancel_open_orders_on_exit": false,
     "unfilledtimeout": {
         "buy": 10,
         "sell": 30
@@ -22,7 +23,10 @@
     "ask_strategy":{
         "use_order_book": false,
         "order_book_min": 1,
-        "order_book_max": 9
+        "order_book_max": 1,
+        "use_sell_signal": true,
+        "sell_profit_only": false,
+        "ignore_roi_if_buy_signal": false
     },
     "exchange": {
         "name": "binance",
@@ -34,33 +38,33 @@
             "rateLimit": 200
         },
         "pair_whitelist": [
-            "AST/BTC",
-            "ETC/BTC",
-            "ETH/BTC",
+            "ALGO/BTC",
+            "ATOM/BTC",
+            "BAT/BTC",
+            "BCH/BTC",
+            "BRD/BTC",
             "EOS/BTC",
+            "ETH/BTC",
             "IOTA/BTC",
+            "LINK/BTC",
             "LTC/BTC",
-            "MTH/BTC",
-            "NCASH/BTC",
-            "TNT/BTC",
+            "NEO/BTC",
+            "NXS/BTC",
             "XMR/BTC",
-            "XLM/BTC",
-            "XRP/BTC"
+            "XRP/BTC",
+            "XTZ/BTC"
         ],
         "pair_blacklist": [
             "BNB/BTC"
         ]
     },
-    "experimental": {
-        "use_sell_signal": false,
-        "sell_profit_only": false,
-        "ignore_roi_if_buy_signal": false
-    },
+    "pairlists": [
+        {"method": "StaticPairList"}
+    ],
     "edge": {
         "enabled": false,
         "process_throttle_secs": 3600,
         "calculate_since_number_of_days": 7,
-        "capital_available_percentage": 0.5,
         "allowed_risk": 0.01,
         "stoploss_range_min": -0.01,
         "stoploss_range_max": -0.1,
@@ -76,6 +80,16 @@
         "token": "your_telegram_token",
         "chat_id": "your_telegram_chat_id"
     },
+    "api_server": {
+        "enabled": false,
+        "listen_ip_address": "127.0.0.1",
+        "listen_port": 8080,
+        "verbosity": "info",
+        "jwt_secret_key": "somethingrandom",
+        "CORS_origins": [],
+        "username": "",
+        "password": ""
+    },
     "initial_state": "running",
     "forcebuy_enable": false,
     "internals": {
diff --git a/config_full.json.example b/config_full.json.example
index b6451859c..45c5c695c 100644
--- a/config_full.json.example
+++ b/config_full.json.example
@@ -2,10 +2,14 @@
     "max_open_trades": 3,
     "stake_currency": "BTC",
     "stake_amount": 0.05,
+    "tradable_balance_ratio": 0.99,
     "fiat_display_currency": "USD",
-    "amount_reserve_percent" : 0.05,
-    "dry_run": false,
-    "ticker_interval": "5m",
+    "amount_reserve_percent": 0.05,
+    "amend_last_stake_amount": false,
+    "last_stake_amount_min_ratio": 0.5,
+    "dry_run": true,
+    "cancel_open_orders_on_exit": false,
+    "timeframe": "5m",
     "trailing_stop": false,
     "trailing_stop_positive": 0.005,
     "trailing_stop_positive_offset": 0.0051,
@@ -22,6 +26,7 @@
         "sell": 30
     },
     "bid_strategy": {
+        "price_side": "bid",
         "use_order_book": false,
         "ask_last_balance": 0.0,
         "order_book_top": 1,
@@ -31,13 +36,18 @@
         }
     },
     "ask_strategy":{
+        "price_side": "ask",
         "use_order_book": false,
         "order_book_min": 1,
-        "order_book_max": 9
+        "order_book_max": 1,
+        "use_sell_signal": true,
+        "sell_profit_only": false,
+        "ignore_roi_if_buy_signal": false
     },
     "order_types": {
         "buy": "limit",
         "sell": "limit",
+        "emergencysell": "market",
         "stoploss": "market",
         "stoploss_on_exchange": false,
         "stoploss_on_exchange_interval": 60
@@ -46,14 +56,19 @@
         "buy": "gtc",
         "sell": "gtc"
     },
-    "pairlist": {
-        "method": "VolumePairList",
-        "config": {
+    "pairlists": [
+        {"method": "StaticPairList"},
+        {
+            "method": "VolumePairList",
             "number_assets": 20,
             "sort_key": "quoteVolume",
-            "precision_filter": false
-        }
-    },
+            "refresh_period": 1800
+        },
+        {"method": "AgeFilter", "min_days_listed": 10},
+        {"method": "PrecisionFilter"},
+        {"method": "PriceFilter", "low_price_ratio": 0.01, "min_price": 0.00000010},
+        {"method": "SpreadFilter", "max_spread_ratio": 0.005}
+    ],
     "exchange": {
         "name": "bittrex",
         "sandbox": false,
@@ -74,7 +89,7 @@
             "ZEC/BTC",
             "XLM/BTC",
             "NXT/BTC",
-            "POWR/BTC",
+            "TRX/BTC",
             "ADA/BTC",
             "XMR/BTC"
         ],
@@ -88,7 +103,6 @@
         "enabled": false,
         "process_throttle_secs": 3600,
         "calculate_since_number_of_days": 7,
-        "capital_available_percentage": 0.5,
         "allowed_risk": 0.01,
         "stoploss_range_min": -0.01,
         "stoploss_range_max": -0.1,
@@ -99,20 +113,27 @@
         "max_trade_duration_minute": 1440,
         "remove_pumps": false
     },
-    "experimental": {
-        "use_sell_signal": false,
-        "sell_profit_only": false,
-        "ignore_roi_if_buy_signal": false
-    },
     "telegram": {
         "enabled": true,
         "token": "your_telegram_token",
-        "chat_id": "your_telegram_chat_id"
+        "chat_id": "your_telegram_chat_id",
+        "notification_settings": {
+            "status": "on",
+            "warning": "on",
+            "startup": "on",
+            "buy": "on",
+            "sell": "on",
+            "buy_cancel": "on",
+            "sell_cancel": "on"
+        }
     },
     "api_server": {
         "enabled": false,
         "listen_ip_address": "127.0.0.1",
         "listen_port": 8080,
+        "verbosity": "info",
+        "jwt_secret_key": "somethingrandom",
+        "CORS_origins": [],
         "username": "freqtrader",
         "password": "SuperSecurePassword"
     },
@@ -120,8 +141,12 @@
     "initial_state": "running",
     "forcebuy_enable": false,
     "internals": {
-        "process_throttle_secs": 5
+        "process_throttle_secs": 5,
+        "heartbeat_interval": 60
     },
+    "disable_dataframe_checks": false,
     "strategy": "DefaultStrategy",
-    "strategy_path": "user_data/strategies/"
+    "strategy_path": "user_data/strategies/",
+    "dataformat_ohlcv": "json",
+    "dataformat_trades": "jsongz"
 }
diff --git a/config_kraken.json.example b/config_kraken.json.example
index ea3677b2d..5f3b57854 100644
--- a/config_kraken.json.example
+++ b/config_kraken.json.example
@@ -2,10 +2,11 @@
     "max_open_trades": 5,
     "stake_currency": "EUR",
     "stake_amount": 10,
+    "tradable_balance_ratio": 0.99,
     "fiat_display_currency": "EUR",
-    "ticker_interval" : "5m",
+    "timeframe": "5m",
     "dry_run": true,
-    "trailing_stop": false,
+    "cancel_open_orders_on_exit": false,
     "unfilledtimeout": {
         "buy": 10,
         "sell": 30
@@ -22,31 +23,53 @@
     "ask_strategy":{
         "use_order_book": false,
         "order_book_min": 1,
-        "order_book_max": 9
+        "order_book_max": 1,
+        "use_sell_signal": true,
+        "sell_profit_only": false,
+        "ignore_roi_if_buy_signal": false
     },
     "exchange": {
         "name": "kraken",
-        "key": "",
-        "secret": "",
+        "key": "your_exchange_key",
+        "secret": "your_exchange_key",
         "ccxt_config": {"enableRateLimit": true},
         "ccxt_async_config": {
             "enableRateLimit": true,
             "rateLimit": 1000
         },
         "pair_whitelist": [
-            "ETH/EUR",
+            "ADA/EUR",
+            "ATOM/EUR",
+            "BAT/EUR",
+            "BCH/EUR",
             "BTC/EUR",
-            "BCH/EUR"
+            "DAI/EUR",
+            "DASH/EUR",
+            "EOS/EUR",
+            "ETC/EUR",
+            "ETH/EUR",
+            "LINK/EUR",
+            "LTC/EUR",
+            "QTUM/EUR",
+            "REP/EUR",
+            "WAVES/EUR",
+            "XLM/EUR",
+            "XMR/EUR",
+            "XRP/EUR",
+            "XTZ/EUR",
+            "ZEC/EUR"
         ],
         "pair_blacklist": [
 
         ]
     },
+    "pairlists": [
+        {"method": "StaticPairList"}
+    ],
     "edge": {
         "enabled": false,
         "process_throttle_secs": 3600,
         "calculate_since_number_of_days": 7,
-        "capital_available_percentage": 0.5,
         "allowed_risk": 0.01,
         "stoploss_range_min": -0.01,
         "stoploss_range_max": -0.1,
@@ -62,9 +85,20 @@
         "token": "your_telegram_token",
         "chat_id": "your_telegram_chat_id"
     },
+    "api_server": {
+        "enabled": false,
+        "listen_ip_address": "127.0.0.1",
+        "listen_port": 8080,
+        "verbosity": "info",
+        "jwt_secret_key": "somethingrandom",
+        "CORS_origins": [],
+        "username": "",
+        "password": ""
+    },
     "initial_state": "running",
     "forcebuy_enable": false,
     "internals": {
         "process_throttle_secs": 5
-    }
+    },
+    "download_trades": true
 }
diff --git a/docker-compose.yml b/docker-compose.yml
new file mode 100644
index 000000000..a99aac3c7
--- /dev/null
+++ b/docker-compose.yml
@@ -0,0 +1,23 @@
+---
+version: '3'
+services:
+  freqtrade:
+    image: freqtradeorg/freqtrade:stable
+    # image: freqtradeorg/freqtrade:develop
+    # Use plotting image
+    # image: freqtradeorg/freqtrade:develop_plot
+    # Build step - only needed when additional dependencies are needed
+    # build:
+    #   context: .
+    #   dockerfile: "./Dockerfile.technical"
+    restart: unless-stopped
+    container_name: freqtrade
+    volumes:
+      - "./user_data:/freqtrade/user_data"
+    # Default command used when running `docker compose up`
+    command: >
+      trade
+      --logfile /freqtrade/user_data/logs/freqtrade.log
+      --db-url sqlite:////freqtrade/user_data/tradesv3.sqlite
+      --config /freqtrade/user_data/config.json
+      --strategy SampleStrategy
diff --git a/Dockerfile.develop b/docker/Dockerfile.develop
similarity index 99%
rename from Dockerfile.develop
rename to docker/Dockerfile.develop
index 8f6871c55..cb49984e2 100644
--- a/Dockerfile.develop
+++ b/docker/Dockerfile.develop
@@ -2,6 +2,7 @@ FROM freqtradeorg/freqtrade:develop
 
 # Install dependencies
 COPY requirements-dev.txt /freqtrade/
+
 RUN pip install numpy --no-cache-dir \
   && pip install -r requirements-dev.txt --no-cache-dir
 
diff --git a/docker/Dockerfile.jupyter b/docker/Dockerfile.jupyter
new file mode 100644
index 000000000..b7499eeef
--- /dev/null
+++ b/docker/Dockerfile.jupyter
@@ -0,0 +1,7 @@
+FROM freqtradeorg/freqtrade:develop_plot
+
+
+RUN pip install jupyterlab --no-cache-dir
+
+# Empty the ENTRYPOINT to allow all commands
+ENTRYPOINT []
diff --git a/docker/Dockerfile.plot b/docker/Dockerfile.plot
new file mode 100644
index 000000000..40bc72bc5
--- /dev/null
+++ b/docker/Dockerfile.plot
@@ -0,0 +1,7 @@
+ARG sourceimage=develop
+FROM freqtradeorg/freqtrade:${sourceimage}
+
+# Install dependencies
+COPY requirements-plot.txt /freqtrade/
+
+RUN pip install -r requirements-plot.txt --no-cache-dir
diff --git a/Dockerfile.technical b/docker/Dockerfile.technical
similarity index 100%
rename from Dockerfile.technical
rename to docker/Dockerfile.technical
diff --git a/docker/docker-compose-jupyter.yml b/docker/docker-compose-jupyter.yml
new file mode 100644
index 000000000..11a01705c
--- /dev/null
+++ b/docker/docker-compose-jupyter.yml
@@ -0,0 +1,16 @@
+---
+version: '3'
+services:
+  ft_jupyterlab:
+    build:
+      context: ..
+      dockerfile: docker/Dockerfile.jupyter
+    restart: unless-stopped
+    container_name: freqtrade
+    ports:
+      - "127.0.0.1:8888:8888"
+    volumes:
+      - "./user_data:/freqtrade/user_data"
+    # Default command used when running `docker compose up`
+    command: >
+      jupyter lab --port=8888 --ip 0.0.0.0 --allow-root
diff --git a/docs/advanced-hyperopt.md b/docs/advanced-hyperopt.md
new file mode 100644
index 000000000..59ebc16b5
--- /dev/null
+++ b/docs/advanced-hyperopt.md
@@ -0,0 +1,91 @@
+# Advanced Hyperopt
+
+This page explains some advanced Hyperopt topics that may require higher
+coding skills and Python knowledge than creation of an ordinal hyperoptimization
+class.
+
+## Derived hyperopt classes
+
+Custom hyperop classes can be derived in the same way [it can be done for strategies](strategy-customization.md#derived-strategies).
+
+Applying to hyperoptimization, as an example, you may override how dimensions are defined in your optimization hyperspace:
+
+```python
+class MyAwesomeHyperOpt(IHyperOpt):
+    ...
+    # Uses default stoploss dimension
+
+class MyAwesomeHyperOpt2(MyAwesomeHyperOpt):
+    @staticmethod
+    def stoploss_space() -> List[Dimension]:
+        # Override boundaries for stoploss
+        return [
+            Real(-0.33, -0.01, name='stoploss'),
+        ]
+```
+
+and then quickly switch between hyperopt classes, running optimization process with hyperopt class you need in each particular case:
+
+```
+$ freqtrade hyperopt --hyperopt MyAwesomeHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --strategy MyAwesomeStrategy ...
+or
+$ freqtrade hyperopt --hyperopt MyAwesomeHyperOpt2 --hyperopt-loss SharpeHyperOptLossDaily --strategy MyAwesomeStrategy ...
+```
+
+## Creating and using a custom loss function
+
+To use a custom loss function class, make sure that the function `hyperopt_loss_function` is defined in your custom hyperopt loss class.
+For the sample below, you then need to add the command line parameter `--hyperopt-loss SuperDuperHyperOptLoss` to your hyperopt call so this function is being used.
+
+A sample of this can be found below, which is identical to the Default Hyperopt loss implementation. A full sample can be found in [userdata/hyperopts](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_loss.py).
+
+``` python
+from freqtrade.optimize.hyperopt import IHyperOptLoss
+
+TARGET_TRADES = 600
+EXPECTED_MAX_PROFIT = 3.0
+MAX_ACCEPTED_TRADE_DURATION = 300
+
+class SuperDuperHyperOptLoss(IHyperOptLoss):
+    """
+    Defines the default loss function for hyperopt
+    """
+
+    @staticmethod
+    def hyperopt_loss_function(results: DataFrame, trade_count: int,
+                               min_date: datetime, max_date: datetime,
+                               *args, **kwargs) -> float:
+        """
+        Objective function, returns smaller number for better results
+        This is the legacy algorithm (used until now in freqtrade).
+        Weights are distributed as follows:
+        * 0.4 to trade duration
+        * 0.25: Avoiding trade loss
+        * 1.0 to total profit, compared to the expected value (`EXPECTED_MAX_PROFIT`) defined above
+        """
+        total_profit = results['profit_percent'].sum()
+        trade_duration = results['trade_duration'].mean()
+
+        trade_loss = 1 - 0.25 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.8)
+        profit_loss = max(0, 1 - total_profit / EXPECTED_MAX_PROFIT)
+        duration_loss = 0.4 * min(trade_duration / MAX_ACCEPTED_TRADE_DURATION, 1)
+        result = trade_loss + profit_loss + duration_loss
+        return result
+```
+
+Currently, the arguments are:
+
+* `results`: DataFrame containing the result  
+    The following columns are available in results (corresponds to the output-file of backtesting when used with `--export trades`):  
+    `pair, profit_percent, profit_abs, open_time, close_time, open_index, close_index, trade_duration, open_at_end, open_rate, close_rate, sell_reason`
+* `trade_count`: Amount of trades (identical to `len(results)`)
+* `min_date`: Start date of the hyperopting TimeFrame
+* `min_date`: End date of the hyperopting TimeFrame
+
+This function needs to return a floating point number (`float`). Smaller numbers will be interpreted as better results. The parameters and balancing for this is up to you.
+
+!!! Note
+    This function is called once per iteration - so please make sure to have this as optimized as possible to not slow hyperopt down unnecessarily.
+
+!!! Note
+    Please keep the arguments `*args` and `**kwargs` in the interface to allow us to extend this interface later.
diff --git a/docs/advanced-setup.md b/docs/advanced-setup.md
new file mode 100644
index 000000000..f03bc10c0
--- /dev/null
+++ b/docs/advanced-setup.md
@@ -0,0 +1,140 @@
+# Advanced Post-installation Tasks
+
+This page explains some advanced tasks and configuration options that can be performed after the bot installation and may be uselful in some environments.
+
+If you do not know what things mentioned here mean, you probably do not need it.
+
+## Running multiple instances of Freqtrade
+
+This section will show you how to run multiple bots at the same time, on the same machine.
+
+### Things to consider
+
+* Use different database files.
+* Use different Telegram bots (requires multiple different configuration files; applies only when Telegram is enabled).
+* Use different ports (applies only when Freqtrade REST API webserver is enabled).
+
+### Different database files
+
+In order to keep track of your trades, profits, etc., freqtrade is using a SQLite database where it stores various types of information such as the trades you performed in the past and the current position(s) you are holding at any time. This allows you to keep track of your profits, but most importantly, keep track of ongoing activity if the bot process would be restarted or would be terminated unexpectedly.
+
+Freqtrade will, by default, use separate database files for dry-run and live bots (this assumes no database-url is given in either configuration nor via command line argument).
+For live trading mode, the default database will be `tradesv3.sqlite` and for dry-run it will be `tradesv3.dryrun.sqlite`.
+
+The optional argument to the trade command used to specify the path of these files is `--db-url`, which requires a valid SQLAlchemy url.
+So when you are starting a bot with only the config and strategy arguments in dry-run mode, the following 2 commands would have the same outcome.
+
+``` bash
+freqtrade trade -c MyConfig.json -s MyStrategy
+# is equivalent to
+freqtrade trade -c MyConfig.json -s MyStrategy --db-url sqlite:///tradesv3.dryrun.sqlite
+```
+
+It means that if you are running the trade command in two different terminals, for example to test your strategy both for trades in USDT and in another instance for trades in BTC, you will have to run them with different databases.
+
+If you specify the URL of a database which does not exist, freqtrade will create one with the name you specified. So to test your custom strategy with BTC and USDT stake currencies, you could use the following commands (in 2 separate terminals):
+
+``` bash
+# Terminal 1:
+freqtrade trade -c MyConfigBTC.json -s MyCustomStrategy --db-url sqlite:///user_data/tradesBTC.dryrun.sqlite
+# Terminal 2:
+freqtrade trade -c MyConfigUSDT.json -s MyCustomStrategy --db-url sqlite:///user_data/tradesUSDT.dryrun.sqlite
+```
+
+Conversely, if you wish to do the same thing in production mode, you will also have to create at least one new database (in addition to the default one) and specify the path to the "live" databases, for example:
+
+``` bash
+# Terminal 1:
+freqtrade trade -c MyConfigBTC.json -s MyCustomStrategy --db-url sqlite:///user_data/tradesBTC.live.sqlite
+# Terminal 2:
+freqtrade trade -c MyConfigUSDT.json -s MyCustomStrategy --db-url sqlite:///user_data/tradesUSDT.live.sqlite
+```
+
+For more information regarding usage of the sqlite databases, for example to manually enter or remove trades, please refer to the [SQL Cheatsheet](sql_cheatsheet.md).
+
+## Configure the bot running as a systemd service
+
+Copy the `freqtrade.service` file to your systemd user directory (usually `~/.config/systemd/user`) and update `WorkingDirectory` and `ExecStart` to match your setup.
+
+!!! Note
+    Certain systems (like Raspbian) don't load service unit files from the user directory. In this case, copy `freqtrade.service` into `/etc/systemd/user/` (requires superuser permissions).
+
+After that you can start the daemon with:
+
+```bash
+systemctl --user start freqtrade
+```
+
+For this to be persistent (run when user is logged out) you'll need to enable `linger` for your freqtrade user.
+
+```bash
+sudo loginctl enable-linger "$USER"
+```
+
+If you run the bot as a service, you can use systemd service manager as a software watchdog monitoring freqtrade bot 
+state and restarting it in the case of failures. If the `internals.sd_notify` parameter is set to true in the 
+configuration or the `--sd-notify` command line option is used, the bot will send keep-alive ping messages to systemd 
+using the sd_notify (systemd notifications) protocol and will also tell systemd its current state (Running or Stopped) 
+when it changes. 
+
+The `freqtrade.service.watchdog` file contains an example of the service unit configuration file which uses systemd 
+as the watchdog.
+
+!!! Note
+    The sd_notify communication between the bot and the systemd service manager will not work if the bot runs in a Docker container.
+
+## Advanced Logging
+
+On many Linux systems the bot can be configured to send its log messages to `syslog` or `journald` system services. Logging to a remote `syslog` server is also available on Windows. The special values for the `--logfile` command line option can be used for this.
+
+### Logging to syslog
+
+To send Freqtrade log messages to a local or remote `syslog` service use the `--logfile` command line option with the value in the following format:
+
+* `--logfile syslog:<syslog_address>` -- send log messages to `syslog` service using the `<syslog_address>` as the syslog address.
+
+The syslog address can be either a Unix domain socket (socket filename) or a UDP socket specification, consisting of IP address and UDP port, separated by the `:` character.
+
+So, the following are the examples of possible usages:
+
+* `--logfile syslog:/dev/log` -- log to syslog (rsyslog) using the `/dev/log` socket, suitable for most systems.
+* `--logfile syslog` -- same as above, the shortcut for `/dev/log`.
+* `--logfile syslog:/var/run/syslog` -- log to syslog (rsyslog) using the `/var/run/syslog` socket. Use this on MacOS.
+* `--logfile syslog:localhost:514` -- log to local syslog using UDP socket, if it listens on port 514.
+* `--logfile syslog:<ip>:514` -- log to remote syslog at IP address and port 514. This may be used on Windows for remote logging to an external syslog server.
+
+Log messages are send to `syslog` with the `user` facility. So you can see them with the following commands:
+
+* `tail -f /var/log/user`, or 
+* install a comprehensive graphical viewer (for instance, 'Log File Viewer' for Ubuntu).
+
+On many systems `syslog` (`rsyslog`) fetches data from `journald` (and vice versa), so both `--logfile syslog` or `--logfile journald` can be used and the messages be viewed with both `journalctl` and a syslog viewer utility. You can combine this in any way which suites you better.
+
+For `rsyslog` the messages from the bot can be redirected into a separate dedicated log file. To achieve this, add
+```
+if $programname startswith "freqtrade" then -/var/log/freqtrade.log
+```
+to one of the rsyslog configuration files, for example at the end of the `/etc/rsyslog.d/50-default.conf`.
+
+For `syslog` (`rsyslog`), the reduction mode can be switched on. This will reduce the number of repeating messages. For instance, multiple bot Heartbeat messages will be reduced to a single message when nothing else happens with the bot. To achieve this, set in `/etc/rsyslog.conf`:
+```
+# Filter duplicated messages
+$RepeatedMsgReduction on
+```
+
+### Logging to journald
+
+This needs the `systemd` python package installed as the dependency, which is not available on Windows. Hence, the whole journald logging functionality is not available for a bot running on Windows.
+
+To send Freqtrade log messages to `journald` system service use the `--logfile` command line option with the value in the following format:
+
+* `--logfile journald` -- send log messages to `journald`.
+
+Log messages are send to `journald` with the `user` facility. So you can see them with the following commands:
+
+* `journalctl -f` -- shows Freqtrade log messages sent to `journald` along with other log messages fetched by `journald`.
+* `journalctl -f -u freqtrade.service` -- this command can be used when the bot is run as a `systemd` service.
+
+There are many other options in the `journalctl` utility to filter the messages, see manual pages for this utility.
+
+On many systems `syslog` (`rsyslog`) fetches data from `journald` (and vice versa), so both `--logfile syslog` or `--logfile journald` can be used and the messages be viewed with both `journalctl` and a syslog viewer utility. You can combine this in any way which suites you better.
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diff --git a/docs/backtesting.md b/docs/backtesting.md
index 179bcee15..84911568b 100644
--- a/docs/backtesting.md
+++ b/docs/backtesting.md
@@ -1,68 +1,72 @@
 # Backtesting
 
-This page explains how to validate your strategy performance by using
-Backtesting.
+This page explains how to validate your strategy performance by using Backtesting.
+
+Backtesting requires historic data to be available.
+To learn how to get data for the pairs and exchange you're interested in, head over to the [Data Downloading](data-download.md) section of the documentation.
 
 ## Test your strategy with Backtesting
 
-Now you have good Buy and Sell strategies, you want to test it against
+Now you have good Buy and Sell strategies and some historic data, you want to test it against
 real data. This is what we call
 [backtesting](https://en.wikipedia.org/wiki/Backtesting).
 
-Backtesting will use the crypto-currencies (pair) from your config file
-and load static tickers located in
-[/freqtrade/tests/testdata](https://github.com/freqtrade/freqtrade/tree/develop/freqtrade/tests/testdata).
-If the 5 min and 1 min ticker for the crypto-currencies to test is not
-already in the `testdata` directory, backtesting will download them
-automatically. Testdata files will not be updated until you specify it.
+Backtesting will use the crypto-currencies (pairs) from your config file and load historical candle (OHCLV) data from `user_data/data/<exchange>` by default.
+If no data is available for the exchange / pair / timeframe combination, backtesting will ask you to download them first using `freqtrade download-data`.
+For details on downloading, please refer to the [Data Downloading](data-download.md) section in the documentation.
 
-The result of backtesting will confirm you if your bot has better odds of making a profit than a loss.
+The result of backtesting will confirm if your bot has better odds of making a profit than a loss.
 
-The backtesting is very easy with freqtrade.
+!!! Warning "Using dynamic pairlists for backtesting"
+    Using dynamic pairlists is possible, however it relies on the current market conditions - which will not reflect the historic status of the pairlist.
+    Also, when using pairlists other than StaticPairlist, reproducability of backtesting-results cannot be guaranteed.
+    Please read the [pairlists documentation](configuration.md#pairlists) for more information.
+
+    To achieve reproducible results, best generate a pairlist via the [`test-pairlist`](utils.md#test-pairlist) command and use that as static pairlist.
 
 ### Run a backtesting against the currencies listed in your config file
-#### With 5 min tickers (Per default)
+
+#### With 5 min candle (OHLCV) data (per default)
 
 ```bash
 freqtrade backtesting
 ```
 
-#### With 1 min tickers
+#### With 1 min candle (OHLCV) data
 
 ```bash
-freqtrade backtesting --ticker-interval 1m
+freqtrade backtesting --timeframe 1m
 ```
 
-#### Update cached pairs with the latest data
+#### Using a different on-disk historical candle (OHLCV) data source
+
+Assume you downloaded the history data from the Bittrex exchange and kept it in the `user_data/data/bittrex-20180101` directory. 
+You can then use this data for backtesting as follows:
 
 ```bash
-freqtrade backtesting --refresh-pairs-cached
-```
-
-#### With live data (do not alter your testdata files)
-
-```bash
-freqtrade backtesting --live
-```
-
-#### Using a different on-disk ticker-data source
-
-```bash
-freqtrade backtesting --datadir freqtrade/tests/testdata-20180101
+freqtrade --datadir user_data/data/bittrex-20180101 backtesting
 ```
 
 #### With a (custom) strategy file
 
 ```bash
-freqtrade -s TestStrategy backtesting
+freqtrade backtesting -s SampleStrategy
 ```
 
-Where `-s TestStrategy` refers to the class name within the strategy file `test_strategy.py` found in the `freqtrade/user_data/strategies` directory
+Where `-s SampleStrategy` refers to the class name within the strategy file `sample_strategy.py` found in the `freqtrade/user_data/strategies` directory.
+
+#### Comparing multiple Strategies
+
+```bash
+freqtrade backtesting --strategy-list SampleStrategy1 AwesomeStrategy --timeframe 5m
+```
+
+Where `SampleStrategy1` and `AwesomeStrategy` refer to class names of strategies.
 
 #### Exporting trades to file
 
 ```bash
-freqtrade backtesting --export trades
+freqtrade backtesting --export trades --config config.json --strategy SampleStrategy
 ```
 
 The exported trades can be used for [further analysis](#further-backtest-result-analysis), or can be used by the plotting script `plot_dataframe.py` in the scripts directory.
@@ -70,68 +74,47 @@ The exported trades can be used for [further analysis](#further-backtest-result-
 #### Exporting trades to file specifying a custom filename
 
 ```bash
-freqtrade backtesting --export trades --export-filename=backtest_teststrategy.json
+freqtrade backtesting --export trades --export-filename=backtest_samplestrategy.json
 ```
 
-#### Running backtest with smaller testset
+Please also read about the [strategy startup period](strategy-customization.md#strategy-startup-period).
 
-Use the `--timerange` argument to change how much of the testset
-you want to use. The last N ticks/timeframes will be used.
+#### Supplying custom fee value
 
-Example:
+Sometimes your account has certain fee rebates (fee reductions starting with a certain account size or monthly volume), which are not visible to ccxt.
+To account for this in backtesting, you can use the `--fee` command line option to supply this value to backtesting.
+This fee must be a ratio, and will be applied twice (once for trade entry, and once for trade exit).
+
+For example, if the buying and selling commission fee is 0.1% (i.e., 0.001 written as ratio), then you would run backtesting as the following:
 
 ```bash
-freqtrade backtesting --timerange=-200
+freqtrade backtesting --fee 0.001
 ```
 
-#### Advanced use of timerange
+!!! Note
+    Only supply this option (or the corresponding configuration parameter) if you want to experiment with different fee values. By default, Backtesting fetches the default fee from the exchange pair/market info.
 
-Doing `--timerange=-200` will get the last 200 timeframes
-from your inputdata. You can also specify specific dates,
-or a range span indexed by start and stop.
+#### Running backtest with smaller testset by using timerange
+
+Use the `--timerange` argument to change how much of the testset you want to use.
+
+
+For example, running backtesting with the `--timerange=20190501-` option will use all available data starting with May 1st, 2019 from your inputdata.
+
+```bash
+freqtrade backtesting --timerange=20190501-
+```
+
+You can also specify particular dates or a range span indexed by start and stop.
 
 The full timerange specification:
 
-- Use last 123 tickframes of data: `--timerange=-123`
-- Use first 123 tickframes of data: `--timerange=123-`
-- Use tickframes from line 123 through 456: `--timerange=123-456`
 - Use tickframes till 2018/01/31: `--timerange=-20180131`
 - Use tickframes since 2018/01/31: `--timerange=20180131-`
 - Use tickframes since 2018/01/31 till 2018/03/01 : `--timerange=20180131-20180301`
 - Use tickframes between POSIX timestamps 1527595200 1527618600:
                                                 `--timerange=1527595200-1527618600`
 
-#### Downloading new set of ticker data
-
-To download new set of backtesting ticker data, you can use a download script.
-
-If you are using Binance for example:
-
-- create a directory `user_data/data/binance` and copy `pairs.json` in that directory.
-- update the `pairs.json` to contain the currency pairs you are interested in.
-
-```bash
-mkdir -p user_data/data/binance
-cp freqtrade/tests/testdata/pairs.json user_data/data/binance
-```
-
-Then run:
-
-```bash
-python scripts/download_backtest_data.py --exchange binance
-```
-
-This will download ticker data for all the currency pairs you defined in `pairs.json`.
-
-- To use a different directory than the exchange specific default, use `--datadir user_data/data/some_directory`.
-- To change the exchange used to download the tickers, use `--exchange`. Default is `bittrex`.
-- To use `pairs.json` from some other directory, use `--pairs-file some_other_dir/pairs.json`.
-- To download ticker data for only 10 days, use `--days 10`.
-- Use `--timeframes` to specify which tickers to download. Default is `--timeframes 1m 5m` which will download 1-minute and 5-minute tickers.
-- To use exchange, timeframe and list of pairs as defined in your configuration file, use the `-c/--config` option. With this, the script uses the whitelist defined in the config as the list of currency pairs to download data for and does not require the pairs.json file. You can combine `-c/--config` with other options.
-
-For help about backtesting usage, please refer to [Backtesting commands](#backtesting-commands).
-
 ## Understand the backtesting result
 
 The most important in the backtesting is to understand the result.
@@ -140,48 +123,65 @@ A backtesting result will look like that:
 
 ```
 ========================================================= BACKTESTING REPORT ========================================================
-| pair     |   buy count |   avg profit % |   cum profit % |   tot profit BTC |   tot profit % | avg duration   |   profit |   loss |
-|:---------|------------:|---------------:|---------------:|-----------------:|---------------:|:---------------|---------:|-------:|
-| ADA/BTC  |          35 |          -0.11 |          -3.88 |      -0.00019428 |          -1.94 | 4:35:00        |       14 |     21 |
-| ARK/BTC  |          11 |          -0.41 |          -4.52 |      -0.00022647 |          -2.26 | 2:03:00        |        3 |      8 |
-| BTS/BTC  |          32 |           0.31 |           9.78 |       0.00048938 |           4.89 | 5:05:00        |       18 |     14 |
-| DASH/BTC |          13 |          -0.08 |          -1.07 |      -0.00005343 |          -0.53 | 4:39:00        |        6 |      7 |
-| ENG/BTC  |          18 |           1.36 |          24.54 |       0.00122807 |          12.27 | 2:50:00        |        8 |     10 |
-| EOS/BTC  |          36 |           0.08 |           3.06 |       0.00015304 |           1.53 | 3:34:00        |       16 |     20 |
-| ETC/BTC  |          26 |           0.37 |           9.51 |       0.00047576 |           4.75 | 6:14:00        |       11 |     15 |
-| ETH/BTC  |          33 |           0.30 |           9.96 |       0.00049856 |           4.98 | 7:31:00        |       16 |     17 |
-| IOTA/BTC |          32 |           0.03 |           1.09 |       0.00005444 |           0.54 | 3:12:00        |       14 |     18 |
-| LSK/BTC  |          15 |           1.75 |          26.26 |       0.00131413 |          13.13 | 2:58:00        |        6 |      9 |
-| LTC/BTC  |          32 |          -0.04 |          -1.38 |      -0.00006886 |          -0.69 | 4:49:00        |       11 |     21 |
-| NANO/BTC |          17 |           1.26 |          21.39 |       0.00107058 |          10.70 | 1:55:00        |       10 |      7 |
-| NEO/BTC  |          23 |           0.82 |          18.97 |       0.00094936 |           9.48 | 2:59:00        |       10 |     13 |
-| REQ/BTC  |           9 |           1.17 |          10.54 |       0.00052734 |           5.27 | 3:47:00        |        4 |      5 |
-| XLM/BTC  |          16 |           1.22 |          19.54 |       0.00097800 |           9.77 | 3:15:00        |        7 |      9 |
-| XMR/BTC  |          23 |          -0.18 |          -4.13 |      -0.00020696 |          -2.07 | 5:30:00        |       12 |     11 |
-| XRP/BTC  |          35 |           0.66 |          22.96 |       0.00114897 |          11.48 | 3:49:00        |       12 |     23 |
-| ZEC/BTC  |          22 |          -0.46 |         -10.18 |      -0.00050971 |          -5.09 | 2:22:00        |        7 |     15 |
-| TOTAL    |         429 |           0.36 |         152.41 |       0.00762792 |          76.20 | 4:12:00        |      186 |    243 |
+| Pair     |   Buys |   Avg Profit % |   Cum Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration   |  Wins |  Draws |  Losses |
+|:---------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|--------:|
+| ADA/BTC  |     35 |          -0.11 |          -3.88 |      -0.00019428 |          -1.94 | 4:35:00        |    14 |      0 |      21 |
+| ARK/BTC  |     11 |          -0.41 |          -4.52 |      -0.00022647 |          -2.26 | 2:03:00        |     3 |      0 |       8 |
+| BTS/BTC  |     32 |           0.31 |           9.78 |       0.00048938 |           4.89 | 5:05:00        |    18 |      0 |      14 |
+| DASH/BTC |     13 |          -0.08 |          -1.07 |      -0.00005343 |          -0.53 | 4:39:00        |     6 |      0 |       7 |
+| ENG/BTC  |     18 |           1.36 |          24.54 |       0.00122807 |          12.27 | 2:50:00        |     8 |      0 |      10 |
+| EOS/BTC  |     36 |           0.08 |           3.06 |       0.00015304 |           1.53 | 3:34:00        |    16 |      0 |      20 |
+| ETC/BTC  |     26 |           0.37 |           9.51 |       0.00047576 |           4.75 | 6:14:00        |    11 |      0 |      15 |
+| ETH/BTC  |     33 |           0.30 |           9.96 |       0.00049856 |           4.98 | 7:31:00        |    16 |      0 |      17 |
+| IOTA/BTC |     32 |           0.03 |           1.09 |       0.00005444 |           0.54 | 3:12:00        |    14 |      0 |      18 |
+| LSK/BTC  |     15 |           1.75 |          26.26 |       0.00131413 |          13.13 | 2:58:00        |     6 |      0 |       9 |
+| LTC/BTC  |     32 |          -0.04 |          -1.38 |      -0.00006886 |          -0.69 | 4:49:00        |    11 |      0 |      21 |
+| NANO/BTC |     17 |           1.26 |          21.39 |       0.00107058 |          10.70 | 1:55:00        |    10 |      0 |       7 |
+| NEO/BTC  |     23 |           0.82 |          18.97 |       0.00094936 |           9.48 | 2:59:00        |    10 |      0 |      13 |
+| REQ/BTC  |      9 |           1.17 |          10.54 |       0.00052734 |           5.27 | 3:47:00        |     4 |      0 |       5 |
+| XLM/BTC  |     16 |           1.22 |          19.54 |       0.00097800 |           9.77 | 3:15:00        |     7 |      0 |       9 |
+| XMR/BTC  |     23 |          -0.18 |          -4.13 |      -0.00020696 |          -2.07 | 5:30:00        |    12 |      0 |      11 |
+| XRP/BTC  |     35 |           0.66 |          22.96 |       0.00114897 |          11.48 | 3:49:00        |    12 |      0 |      23 |
+| ZEC/BTC  |     22 |          -0.46 |         -10.18 |      -0.00050971 |          -5.09 | 2:22:00        |     7 |      0 |      15 |
+| TOTAL    |    429 |           0.36 |         152.41 |       0.00762792 |          76.20 | 4:12:00        |   186 |      0 |     243 |
 ========================================================= SELL REASON STATS =========================================================
-| Sell Reason        |   Count |
-|:-------------------|--------:|
-| trailing_stop_loss |     205 |
-| stop_loss          |     166 |
-| sell_signal        |      56 |
-| force_sell         |       2 |
+| Sell Reason        |   Sells |  Wins |  Draws |  Losses |
+|:-------------------|--------:|------:|-------:|--------:|
+| trailing_stop_loss |     205 |   150 |      0 |      55 |
+| stop_loss          |     166 |     0 |      0 |     166 |
+| sell_signal        |      56 |    36 |      0 |      20 |
+| force_sell         |       2 |     0 |      0 |       2 |
 ====================================================== LEFT OPEN TRADES REPORT ======================================================
-| pair     |   buy count |   avg profit % |   cum profit % |   tot profit BTC |   tot profit % | avg duration   |   profit |   loss |
-|:---------|------------:|---------------:|---------------:|-----------------:|---------------:|:---------------|---------:|-------:|
-| ADA/BTC  |           1 |           0.89 |           0.89 |       0.00004434 |           0.44 | 6:00:00        |        1 |      0 |
-| LTC/BTC  |           1 |           0.68 |           0.68 |       0.00003421 |           0.34 | 2:00:00        |        1 |      0 |
-| TOTAL    |           2 |           0.78 |           1.57 |       0.00007855 |           0.78 | 4:00:00        |        2 |      0 |
+| Pair     |   Buys |   Avg Profit % |   Cum Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration   |  Wins |  Draws |  Losses |
+|:---------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|--------:|
+| ADA/BTC  |      1 |           0.89 |           0.89 |       0.00004434 |           0.44 | 6:00:00        |     1 |      0 |       0 |
+| LTC/BTC  |      1 |           0.68 |           0.68 |       0.00003421 |           0.34 | 2:00:00        |     1 |      0 |       0 |
+| TOTAL    |      2 |           0.78 |           1.57 |       0.00007855 |           0.78 | 4:00:00        |     2 |      0 |       0 |
+=============== SUMMARY METRICS ===============
+| Metric                | Value               |
+|-----------------------+---------------------|
+| Backtesting from      | 2019-01-01 00:00:00 |
+| Backtesting to        | 2019-05-01 00:00:00 |
+| Total trades          | 429                 |
+| First trade           | 2019-01-01 18:30:00 |
+| First trade Pair      | EOS/USDT            |
+| Total Profit %        | 152.41%             |
+| Trades per day        | 3.575               |
+| Best day              | 25.27%              |
+| Worst day             | -30.67%             |
+| Avg. Duration Winners | 4:23:00             |
+| Avg. Duration Loser   | 6:55:00             |
+|                       |                     |
+| Max Drawdown          | 50.63%              |
+| Drawdown Start        | 2019-02-15 14:10:00 |
+| Drawdown End          | 2019-04-11 18:15:00 |
+| Market change         | -5.88%              |
+===============================================
 ```
 
-The 1st table will contain all trades the bot made.
+### Backtesting report table
 
-The 2nd table will contain a recap of sell reasons.
-
-The 3rd table will contain all trades the bot had to `forcesell` at the end of the backtest period to present a full picture.
-These trades are also included in the first table, but are extracted separately for clarity.
+The 1st table contains all trades the bot made, including "left open trades".
 
 The last line will give you the overall performance of your strategy,
 here:
@@ -190,22 +190,16 @@ here:
 | TOTAL    |         429 |           0.36 |         152.41 |       0.00762792 |          76.20 | 4:12:00        |      186 |    243 |
 ```
 
-We understand the bot has made `429` trades for an average duration of
-`4:12:00`, with a performance of `76.20%` (profit), that means it has
+The bot has made `429` trades for an average duration of `4:12:00`, with a performance of `76.20%` (profit), that means it has
 earned a total of `0.00762792 BTC` starting with a capital of 0.01 BTC.
 
-The column `avg profit %` shows the average profit for all trades made while the column `cum profit %` sums all the profits/losses. 
-The column `tot profit %` shows instead the total profit % in relation to allocated capital 
-(`max_open_trades * stake_amount`). In the above results we have `max_open_trades=2 stake_amount=0.005` in config 
-so `(76.20/100) * (0.005 * 2) =~ 0.00762792 BTC`.
+The column `avg profit %` shows the average profit for all trades made while the column `cum profit %` sums up all the profits/losses.
+The column `tot profit %` shows instead the total profit % in relation to allocated capital (`max_open_trades * stake_amount`).
+In the above results we have `max_open_trades=2` and `stake_amount=0.005` in config  so `tot_profit %` will be `(76.20/100) * (0.005 * 2) =~ 0.00762792 BTC`.
 
-As you will see your strategy performance will be influenced by your buy
-strategy, your sell strategy, and also by the `minimal_roi` and
-`stop_loss` you have set.
+Your strategy performance is influenced by your buy strategy, your sell strategy, and also by the `minimal_roi` and `stop_loss` you have set.
 
-As for an example if your minimal_roi is only `"0":  0.01`. You cannot
-expect the bot to make more profit than 1% (because it will sell every
-time a trade will reach 1%).
+For example, if your `minimal_roi` is only `"0":  0.01` you cannot expect the bot to make more profit than 1% (because it will sell every time a trade reaches 1%).
 
 ```json
 "minimal_roi": {
@@ -214,39 +208,112 @@ time a trade will reach 1%).
 ```
 
 On the other hand, if you set a too high `minimal_roi` like `"0":  0.55`
-(55%), there is a lot of chance that the bot will never reach this
-profit. Hence, keep in mind that your performance is a mix of your
-strategies, your configuration, and the crypto-currency you have set up.
+(55%), there is almost no chance that the bot will ever reach this profit.
+Hence, keep in mind that your performance is an integral mix of all different elements of the strategy, your configuration, and the crypto-currency pairs you have set up.
+
+### Sell reasons table
+
+The 2nd table contains a recap of sell reasons.
+This table can tell you which area needs some additional work (e.g. all or many of the `sell_signal` trades are losses, so you should work on improving the sell signal, or consider disabling it).
+
+### Left open trades table
+
+The 3rd table contains all trades the bot had to `forcesell` at the end of the backtesting period to present you the full picture.
+This is necessary to simulate realistic behavior, since the backtest period has to end at some point, while realistically, you could leave the bot running forever.
+These trades are also included in the first table, but are also shown separately in this table for clarity.
+
+### Summary metrics
+
+The last element of the backtest report is the summary metrics table.
+It contains some useful key metrics about performance of your strategy on backtesting data.
+
+```
+=============== SUMMARY METRICS ===============
+| Metric                | Value               |
+|-----------------------+---------------------|
+| Backtesting from      | 2019-01-01 00:00:00 |
+| Backtesting to        | 2019-05-01 00:00:00 |
+| Total trades          | 429                 |
+| First trade           | 2019-01-01 18:30:00 |
+| First trade Pair      | EOS/USDT            |
+| Total Profit %        | 152.41%             |
+| Trades per day        | 3.575               |
+| Best day              | 25.27%              |
+| Worst day             | -30.67%             |
+| Avg. Duration Winners | 4:23:00             |
+| Avg. Duration Loser   | 6:55:00             |
+|                       |                     |
+| Max Drawdown          | 50.63%              |
+| Drawdown Start        | 2019-02-15 14:10:00 |
+| Drawdown End          | 2019-04-11 18:15:00 |
+| Market change         | -5.88%              |
+===============================================
+
+```
+
+- `Total trades`: Identical to the total trades of the backtest output table.
+- `First trade`: First trade entered.
+- `First trade pair`: Which pair was part of the first trade.
+- `Backtesting from` / `Backtesting to`: Backtesting range (usually defined with the `--timerange` option).
+- `Total Profit %`: Total profit per stake amount. Aligned to the TOTAL column of the first table.
+- `Trades per day`: Total trades divided by the backtesting duration in days (this will give you information about how many trades to expect from the strategy).
+- `Best day` / `Worst day`: Best and worst day based on daily profit.
+- `Avg. Duration Winners` / `Avg. Duration Loser`: Average durations for winning and losing trades.
+- `Max Drawdown`: Maximum drawdown experienced. For example, the value of 50% means that from highest to subsequent lowest point, a 50% drop was experienced).
+- `Drawdown Start` / `Drawdown End`: Start and end datetimes for this largest drawdown (can also be visualized via the `plot-dataframe` sub-command).
+- `Market change`: Change of the market during the backtest period. Calculated as average of all pairs changes from the first to the last candle using the "close" column.
+
+### Assumptions made by backtesting
+
+Since backtesting lacks some detailed information about what happens within a candle, it needs to take a few assumptions:
+
+- Buys happen at open-price
+- Sell signal sells happen at open-price of the following candle
+- Low happens before high for stoploss, protecting capital first
+- ROI
+  - sells are compared to high - but the ROI value is used (e.g. ROI = 2%, high=5% - so the sell will be at 2%)
+  - sells are never "below the candle", so a ROI of 2% may result in a sell at 2.4% if low was at 2.4% profit
+  - Forcesells caused by `<N>=-1` ROI entries use low as sell value, unless N falls on the candle open (e.g. `120: -1` for 1h candles)
+- Stoploss sells happen exactly at stoploss price, even if low was lower
+- Trailing stoploss
+  - High happens first - adjusting stoploss
+  - Low uses the adjusted stoploss (so sells with large high-low difference are backtested correctly)
+- Sell-reason does not explain if a trade was positive or negative, just what triggered the sell (this can look odd if negative ROI values are used)
+- Stoploss (and trailing stoploss) is evaluated before ROI within one candle. So you can often see more trades with the `stoploss` and/or `trailing_stop` sell reason comparing to the results obtained with the same strategy in the Dry Run/Live Trade modes.
+
+Taking these assumptions, backtesting tries to mirror real trading as closely as possible. However, backtesting will **never** replace running a strategy in dry-run mode.
+Also, keep in mind that past results don't guarantee future success.
+
+In addition to the above assumptions, strategy authors should carefully read the [Common Mistakes](strategy-customization.md#common-mistakes-when-developing-strategies) section, to avoid using data in backtesting which is not available in real market conditions.
 
 ### Further backtest-result analysis
 
 To further analyze your backtest results, you can [export the trades](#exporting-trades-to-file).
 You can then load the trades to perform further analysis as shown in our [data analysis](data-analysis.md#backtesting) backtesting section.
 
-
 ## Backtesting multiple strategies
 
-To backtest multiple strategies, a list of Strategies can be provided.
+To compare multiple strategies, a list of Strategies can be provided to backtesting.
 
-This is limited to 1 ticker-interval per run, however, data is only loaded once from disk so if you have multiple
-strategies you'd like to compare, this should give a nice runtime boost.
+This is limited to 1 timeframe value per run. However, data is only loaded once from disk so if you have multiple
+strategies you'd like to compare, this will give a nice runtime boost.
 
 All listed Strategies need to be in the same directory.
 
 ``` bash
-freqtrade backtesting --timerange 20180401-20180410 --ticker-interval 5m --strategy-list Strategy001 Strategy002 --export trades
+freqtrade backtesting --timerange 20180401-20180410 --timeframe 5m --strategy-list Strategy001 Strategy002 --export trades
 ```
 
-This will save the results to `user_data/backtest_data/backtest-result-<strategy>.json`, injecting the strategy-name into the target filename.
+This will save the results to `user_data/backtest_results/backtest-result-<strategy>.json`, injecting the strategy-name into the target filename.
 There will be an additional table comparing win/losses of the different strategies (identical to the "Total" row in the first table).
-Detailed output for all strategies one after the other will be available, so make sure to scroll up.
+Detailed output for all strategies one after the other will be available, so make sure to scroll up to see the details per strategy.
 
 ```
-=========================================================== Strategy Summary ===========================================================
-| Strategy    |   buy count |   avg profit % |   cum profit % |   tot profit BTC |   tot profit % | avg duration   |   profit |   loss |
-|:------------|------------:|---------------:|---------------:|-----------------:|---------------:|:---------------|---------:|-------:|
-| Strategy1   |         429 |           0.36 |         152.41 |       0.00762792 |          76.20 | 4:12:00        |      186 |    243 |
-| Strategy2   |        1487 |          -0.13 |        -197.58 |      -0.00988917 |         -98.79 | 4:43:00        |      662 |    825 |
+=========================================================== STRATEGY SUMMARY ===========================================================
+| Strategy    |   Buys |   Avg Profit % |   Cum Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration   |  Wins |  Draws | Losses |
+|:------------|-------:|---------------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|-------:|
+| Strategy1   |    429 |           0.36 |         152.41 |       0.00762792 |          76.20 | 4:12:00        |   186 |      0 |    243 |
+| Strategy2   |   1487 |          -0.13 |        -197.58 |      -0.00988917 |         -98.79 | 4:43:00        |   662 |      0 |    825 |
 ```
 
 ## Next step
diff --git a/docs/bot-basics.md b/docs/bot-basics.md
new file mode 100644
index 000000000..44f493456
--- /dev/null
+++ b/docs/bot-basics.md
@@ -0,0 +1,58 @@
+# Freqtrade basics
+
+This page provides you some basic concepts on how Freqtrade works and operates.
+
+## Freqtrade terminology
+
+* Trade: Open position.
+* Open Order: Order which is currently placed on the exchange, and is not yet complete.
+* Pair: Tradable pair, usually in the format of Quote/Base (e.g. XRP/USDT).
+* Timeframe: Candle length to use (e.g. `"5m"`, `"1h"`, ...).
+* Indicators: Technical indicators (SMA, EMA, RSI, ...).
+* Limit order: Limit orders which execute at the defined limit price or better.
+* Market order: Guaranteed to fill, may move price depending on the order size.
+
+## Fee handling
+
+All profit calculations of Freqtrade include fees. For Backtesting / Hyperopt / Dry-run modes, the exchange default fee is used (lowest tier on the exchange). For live operations, fees are used as applied by the exchange (this includes BNB rebates etc.).
+
+## Bot execution logic
+
+Starting freqtrade in dry-run or live mode (using `freqtrade trade`) will start the bot and start the bot iteration loop.
+By default, loop runs every few seconds (`internals.process_throttle_secs`) and does roughly the following in the following sequence:
+
+* Fetch open trades from persistence.
+* Calculate current list of tradable pairs.
+* Download ohlcv data for the pairlist including all [informative pairs](strategy-customization.md#get-data-for-non-tradeable-pairs)  
+  This step is only executed once per Candle to avoid unnecessary network traffic.
+* Call `bot_loop_start()` strategy callback.
+* Analyze strategy per pair.
+  * Call `populate_indicators()`
+  * Call `populate_buy_trend()`
+  * Call `populate_sell_trend()`
+* Check timeouts for open orders.
+  * Calls `check_buy_timeout()` strategy callback for open buy orders.
+  * Calls `check_sell_timeout()` strategy callback for open sell orders.
+* Verifies existing positions and eventually places sell orders.
+  * Considers stoploss, ROI and sell-signal.
+  * Determine sell-price based on `ask_strategy` configuration setting.
+  * Before a sell order is placed, `confirm_trade_exit()` strategy callback is called.
+* Check if trade-slots are still available (if `max_open_trades` is reached).
+* Verifies buy signal trying to enter new positions.
+  * Determine buy-price based on `bid_strategy` configuration setting.
+  * Before a buy order is placed, `confirm_trade_entry()` strategy callback is called.
+
+This loop will be repeated again and again until the bot is stopped.
+
+## Backtesting / Hyperopt execution logic
+
+[backtesting](backtesting.md) or [hyperopt](hyperopt.md) do only part of the above logic, since most of the trading operations are fully simulated.
+
+* Load historic data for configured pairlist.
+* Calculate indicators (calls `populate_indicators()`).
+* Calls `populate_buy_trend()` and `populate_sell_trend()`
+* Loops per candle simulating entry and exit points.
+* Generate backtest report output
+
+!!! Note
+    Both Backtesting and Hyperopt include exchange default Fees in the calculation. Custom fees can be passed to backtesting / hyperopt by specifying the `--fee` argument.
diff --git a/docs/bot-usage.md b/docs/bot-usage.md
index c643ecace..4d07435c7 100644
--- a/docs/bot-usage.md
+++ b/docs/bot-usage.md
@@ -2,76 +2,130 @@
 
 This page explains the different parameters of the bot and how to run it.
 
+!!! Note
+    If you've used `setup.sh`, don't forget to activate your virtual environment (`source .env/bin/activate`) before running freqtrade commands.
+
+!!! Warning "Up-to-date clock"
+    The clock on the system running the bot must be accurate, synchronized to a NTP server frequently enough to avoid problems with communication to the exchanges.
 
 ## Bot commands
 
 ```
-usage: freqtrade [-h] [-v] [--logfile FILE] [--version] [-c PATH] [-d PATH]
-                 [-s NAME] [--strategy-path PATH] [--db-url PATH]
-                 [--sd-notify]
-                 {backtesting,edge,hyperopt} ...
+usage: freqtrade [-h] [-V]
+                 {trade,create-userdir,new-config,new-hyperopt,new-strategy,download-data,convert-data,convert-trade-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,plot-dataframe,plot-profit}
+                 ...
 
 Free, open source crypto trading bot
 
 positional arguments:
-  {backtesting,edge,hyperopt}
+  {trade,create-userdir,new-config,new-hyperopt,new-strategy,download-data,convert-data,convert-trade-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,plot-dataframe,plot-profit}
+    trade               Trade module.
+    create-userdir      Create user-data directory.
+    new-config          Create new config
+    new-hyperopt        Create new hyperopt
+    new-strategy        Create new strategy
+    download-data       Download backtesting data.
+    convert-data        Convert candle (OHLCV) data from one format to
+                        another.
+    convert-trade-data  Convert trade data from one format to another.
     backtesting         Backtesting module.
     edge                Edge module.
     hyperopt            Hyperopt module.
+    hyperopt-list       List Hyperopt results
+    hyperopt-show       Show details of Hyperopt results
+    list-exchanges      Print available exchanges.
+    list-hyperopts      Print available hyperopt classes.
+    list-markets        Print markets on exchange.
+    list-pairs          Print pairs on exchange.
+    list-strategies     Print available strategies.
+    list-timeframes     Print available timeframes for the exchange.
+    show-trades         Show trades.
+    test-pairlist       Test your pairlist configuration.
+    plot-dataframe      Plot candles with indicators.
+    plot-profit         Generate plot showing profits.
 
 optional arguments:
   -h, --help            show this help message and exit
+  -V, --version         show program's version number and exit
+
+```
+
+### Bot trading commands
+
+```
+usage: freqtrade trade [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
+                       [--userdir PATH] [-s NAME] [--strategy-path PATH]
+                       [--db-url PATH] [--sd-notify] [--dry-run]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --db-url PATH         Override trades database URL, this is useful in custom
+                        deployments (default: `sqlite:///tradesv3.sqlite` for
+                        Live Run mode, `sqlite:///tradesv3.dryrun.sqlite` for
+                        Dry Run).
+  --sd-notify           Notify systemd service manager.
+  --dry-run             Enforce dry-run for trading (removes Exchange secrets
+                        and simulates trades).
+
+Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
-  --logfile FILE        Log to the file specified
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
   -V, --version         show program's version number and exit
   -c PATH, --config PATH
-                        Specify configuration file (default: None). Multiple
-                        --config options may be used. Can be set to '-' to
-                        read config from stdin.
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
   -d PATH, --datadir PATH
-                        Path to backtest data.
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+Strategy arguments:
   -s NAME, --strategy NAME
-                        Specify strategy class name (default:
-                        DefaultStrategy).
+                        Specify strategy class name which will be used by the
+                        bot.
   --strategy-path PATH  Specify additional strategy lookup path.
-  --db-url PATH         Override trades database URL, this is useful if
-                        dry_run is enabled or in custom deployments (default:
-                        None).
-  --sd-notify           Notify systemd service manager.
+
 ```
 
-### How to use a different configuration file?
+### How to specify which configuration file be used?
 
-The bot allows you to select which configuration file you want to use. Per
-default, the bot will load the file `./config.json`
+The bot allows you to select which configuration file you want to use by means of
+the `-c/--config` command line option:
 
 ```bash
-freqtrade -c path/far/far/away/config.json
+freqtrade trade -c path/far/far/away/config.json
 ```
 
+Per default, the bot loads the `config.json` configuration file from the current
+working directory.
+
 ### How to use multiple configuration files?
 
 The bot allows you to use multiple configuration files by specifying multiple
-`-c/--config` configuration options in the command line. Configuration parameters
-defined in the last configuration file override parameters with the same name
-defined in the previous configuration file specified in the command line.
+`-c/--config` options in the command line. Configuration parameters
+defined in the latter configuration files override parameters with the same name
+defined in the previous configuration files specified in the command line earlier.
 
-For example, you can make a separate configuration file with your key and secrete
+For example, you can make a separate configuration file with your key and secret
 for the Exchange you use for trading, specify default configuration file with
-empty key and secrete values while running in the Dry Mode (which does not actually
+empty key and secret values while running in the Dry Mode (which does not actually
 require them):
 
 ```bash
-freqtrade -c ./config.json
+freqtrade trade -c ./config.json
 ```
 
 and specify both configuration files when running in the normal Live Trade Mode:
 
 ```bash
-freqtrade -c ./config.json -c path/to/secrets/keys.config.json
+freqtrade trade -c ./config.json -c path/to/secrets/keys.config.json
 ```
 
-This could help you hide your private Exchange key and Exchange secrete on you local machine
+This could help you hide your private Exchange key and Exchange secret on you local machine
 by setting appropriate file permissions for the file which contains actual secrets and, additionally,
 prevent unintended disclosure of sensitive private data when you publish examples
 of your configuration in the project issues or in the Internet.
@@ -79,13 +133,36 @@ of your configuration in the project issues or in the Internet.
 See more details on this technique with examples in the documentation page on
 [configuration](configuration.md).
 
+### Where to store custom data
+
+Freqtrade allows the creation of a user-data directory using `freqtrade create-userdir --userdir someDirectory`.
+This directory will look as follows:
+
+```
+user_data/
+├── backtest_results
+├── data
+├── hyperopts
+├── hyperopt_results
+├── plot
+└── strategies
+```
+
+You can add the entry "user_data_dir" setting to your configuration, to always point your bot to this directory.
+Alternatively, pass in `--userdir` to every command.
+The bot will fail to start if the directory does not exist, but will create necessary subdirectories.
+
+This directory should contain your custom strategies, custom hyperopts and hyperopt loss functions, backtesting historical data (downloaded using either backtesting command or the download script) and plot outputs.
+
+It is recommended to use version control to keep track of changes to your strategies.
+
 ### How to use **--strategy**?
 
 This parameter will allow you to load your custom strategy class.
-Per default without `--strategy` or `-s` the bot will load the
-`DefaultStrategy` included with the bot (`freqtrade/strategy/default_strategy.py`).
+To test the bot installation, you can use the `SampleStrategy` installed by the `create-userdir` subcommand (usually `user_data/strategy/sample_strategy.py`).
 
-The bot will search your strategy file within `user_data/strategies` and `freqtrade/strategy`.
+The bot will search your strategy file within `user_data/strategies`.
+To use other directories, please read the next section about `--strategy-path`.
 
 To load a strategy, simply pass the class name (e.g.: `CustomStrategy`) in this parameter.
 
@@ -94,7 +171,7 @@ In `user_data/strategies` you have a file `my_awesome_strategy.py` which has
 a strategy class called `AwesomeStrategy` to load it:
 
 ```bash
-freqtrade --strategy AwesomeStrategy
+freqtrade trade --strategy AwesomeStrategy
 ```
 
 If the bot does not find your strategy file, it will display in an error
@@ -107,8 +184,9 @@ Learn more about strategy file in
 
 This parameter allows you to add an additional strategy lookup path, which gets
 checked before the default locations (The passed path must be a directory!):
+
 ```bash
-freqtrade --strategy AwesomeStrategy --strategy-path /some/directory
+freqtrade trade --strategy AwesomeStrategy --strategy-path /some/directory
 ```
 
 #### How to install a strategy?
@@ -124,7 +202,7 @@ using `--db-url`. This can also be used to specify a custom database
 in production mode. Example command:
 
 ```bash
-freqtrade -c config.json --db-url sqlite:///tradesv3.dry_run.sqlite
+freqtrade trade -c config.json --db-url sqlite:///tradesv3.dry_run.sqlite
 ```
 
 ## Backtesting commands
@@ -132,27 +210,30 @@ freqtrade -c config.json --db-url sqlite:///tradesv3.dry_run.sqlite
 Backtesting also uses the config specified via `-c/--config`.
 
 ```
-usage: freqtrade backtesting [-h] [-i TICKER_INTERVAL] [--timerange TIMERANGE]
-                           [--max_open_trades MAX_OPEN_TRADES]
-                           [--stake_amount STAKE_AMOUNT] [-r] [--eps] [--dmmp]
-                           [-l]
-                           [--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]]
-                           [--export EXPORT] [--export-filename PATH]
+usage: freqtrade backtesting [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                             [-d PATH] [--userdir PATH] [-s NAME]
+                             [--strategy-path PATH] [-i TIMEFRAME]
+                             [--timerange TIMERANGE] [--max-open-trades INT]
+                             [--stake-amount STAKE_AMOUNT] [--fee FLOAT]
+                             [--eps] [--dmmp]
+                             [--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]]
+                             [--export EXPORT] [--export-filename PATH]
 
 optional arguments:
   -h, --help            show this help message and exit
-  -i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
-                        Specify ticker interval (1m, 5m, 30m, 1h, 1d).
+  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
+                        Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
+                        `1d`).
   --timerange TIMERANGE
                         Specify what timerange of data to use.
-  --max_open_trades MAX_OPEN_TRADES
-                        Specify max_open_trades to use.
-  --stake_amount STAKE_AMOUNT
-                        Specify stake_amount.
-  -r, --refresh-pairs-cached
-                        Refresh the pairs files in tests/testdata with the
-                        latest data from the exchange. Use it if you want to
-                        run your optimization commands with up-to-date data.
+  --max-open-trades INT
+                        Override the value of the `max_open_trades`
+                        configuration setting.
+  --stake-amount STAKE_AMOUNT
+                        Override the value of the `stake_amount` configuration
+                        setting.
+  --fee FLOAT           Specify fee ratio. Will be applied twice (on trade
+                        entry and exit).
   --eps, --enable-position-stacking
                         Allow buying the same pair multiple times (position
                         stacking).
@@ -160,83 +241,104 @@ optional arguments:
                         Disable applying `max_open_trades` during backtest
                         (same as setting `max_open_trades` to a very high
                         number).
-  -l, --live            Use live data.
   --strategy-list STRATEGY_LIST [STRATEGY_LIST ...]
-                        Provide a commaseparated list of strategies to
-                        backtest Please note that ticker-interval needs to be
+                        Provide a space-separated list of strategies to
+                        backtest. Please note that ticker-interval needs to be
                         set either in config or via command line. When using
-                        this together with --export trades, the strategy-name
-                        is injected into the filename (so backtest-data.json
-                        becomes backtest-data-DefaultStrategy.json
-  --export EXPORT       Export backtest results, argument are: trades. Example
-                        --export=trades
+                        this together with `--export trades`, the strategy-
+                        name is injected into the filename (so `backtest-
+                        data.json` becomes `backtest-data-
+                        DefaultStrategy.json`
+  --export EXPORT       Export backtest results, argument are: trades.
+                        Example: `--export=trades`
   --export-filename PATH
-                        Save backtest results to this filename requires
-                        --export to be set as well Example --export-
-                        filename=user_data/backtest_data/backtest_today.json
-                        (default: user_data/backtest_data/backtest-
-                        result.json)
+                        Save backtest results to the file with this filename.
+                        Requires `--export` to be set as well. Example:
+                        `--export-filename=user_data/backtest_results/backtest
+                        _today.json`
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+Strategy arguments:
+  -s NAME, --strategy NAME
+                        Specify strategy class name which will be used by the
+                        bot.
+  --strategy-path PATH  Specify additional strategy lookup path.
+
 ```
 
-### How to use **--refresh-pairs-cached** parameter?
+### Getting historic data for backtesting
 
-The first time your run Backtesting, it will take the pairs you have
-set in your config file and download data from the Exchange.
-
-If for any reason you want to update your data set, you use
-`--refresh-pairs-cached` to force Backtesting to update the data it has.
-
-!!! Note
-    Use it only if you want to update your data set. You will not be able to come back to the previous version.
-
-To test your strategy with latest data, we recommend continuing using
-the parameter `-l` or `--live`.
+The first time your run Backtesting, you will need to download some historic data first.
+This can be accomplished by using `freqtrade download-data`.  
+Check the corresponding [Data Downloading](data-download.md) section for more details
 
 ## Hyperopt commands
 
 To optimize your strategy, you can use hyperopt parameter hyperoptimization
-to find optimal parameter values for your stategy.
+to find optimal parameter values for your strategy.
 
 ```
-usage: freqtrade hyperopt [-h] [-i TICKER_INTERVAL] [--timerange TIMERANGE]
-                          [--max_open_trades INT]
-                          [--stake_amount STAKE_AMOUNT] [-r]
-                          [--customhyperopt NAME] [--eps] [-e INT]
-                          [-s {all,buy,sell,roi,stoploss} [{all,buy,sell,roi,stoploss} ...]]
-                          [--dmmp] [--print-all] [-j JOBS]
-                          [--random-state INT] [--min-trades INT] [--continue]
+usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
+                          [--userdir PATH] [-s NAME] [--strategy-path PATH]
+                          [-i TIMEFRAME] [--timerange TIMERANGE]
+                          [--max-open-trades INT]
+                          [--stake-amount STAKE_AMOUNT] [--fee FLOAT]
+                          [--hyperopt NAME] [--hyperopt-path PATH] [--eps]
+                          [-e INT]
+                          [--spaces {all,buy,sell,roi,stoploss,trailing,default} [{all,buy,sell,roi,stoploss,trailing,default} ...]]
+                          [--dmmp] [--print-all] [--no-color] [--print-json]
+                          [-j JOBS] [--random-state INT] [--min-trades INT]
                           [--hyperopt-loss NAME]
 
 optional arguments:
   -h, --help            show this help message and exit
-  -i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
+  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
                         Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
                         `1d`).
   --timerange TIMERANGE
                         Specify what timerange of data to use.
-  --max_open_trades INT
-                        Specify max_open_trades to use.
-  --stake_amount STAKE_AMOUNT
-                        Specify stake_amount.
-  -r, --refresh-pairs-cached
-                        Refresh the pairs files in tests/testdata with the
-                        latest data from the exchange. Use it if you want to
-                        run your optimization commands with up-to-date data.
-  --customhyperopt NAME
-                        Specify hyperopt class name (default:
-                        `DefaultHyperOpts`).
+  --max-open-trades INT
+                        Override the value of the `max_open_trades`
+                        configuration setting.
+  --stake-amount STAKE_AMOUNT
+                        Override the value of the `stake_amount` configuration
+                        setting.
+  --fee FLOAT           Specify fee ratio. Will be applied twice (on trade
+                        entry and exit).
+  --hyperopt NAME       Specify hyperopt class name which will be used by the
+                        bot.
+  --hyperopt-path PATH  Specify additional lookup path for Hyperopt and
+                        Hyperopt Loss functions.
   --eps, --enable-position-stacking
                         Allow buying the same pair multiple times (position
                         stacking).
   -e INT, --epochs INT  Specify number of epochs (default: 100).
-  -s {all,buy,sell,roi,stoploss} [{all,buy,sell,roi,stoploss} ...], --spaces {all,buy,sell,roi,stoploss} [{all,buy,sell,roi,stoploss} ...]
+  --spaces {all,buy,sell,roi,stoploss,trailing,default} [{all,buy,sell,roi,stoploss,trailing,default} ...]
                         Specify which parameters to hyperopt. Space-separated
-                        list. Default: `all`.
+                        list.
   --dmmp, --disable-max-market-positions
                         Disable applying `max_open_trades` during backtest
                         (same as setting `max_open_trades` to a very high
                         number).
   --print-all           Print all results, not only the best ones.
+  --no-color            Disable colorization of hyperopt results. May be
+                        useful if you are redirecting output to a file.
+  --print-json          Print output in JSON format.
   -j JOBS, --job-workers JOBS
                         The number of concurrently running jobs for
                         hyperoptimization (hyperopt worker processes). If -1
@@ -247,55 +349,97 @@ optional arguments:
                         reproducible hyperopt results.
   --min-trades INT      Set minimal desired number of trades for evaluations
                         in the hyperopt optimization path (default: 1).
-  --continue            Continue hyperopt from previous runs. By default,
-                        temporary files will be removed and hyperopt will
-                        start from scratch.
-  --hyperopt-loss       NAME
-                        Specify the class name of the hyperopt loss function
+  --hyperopt-loss NAME  Specify the class name of the hyperopt loss function
                         class (IHyperOptLoss). Different functions can
                         generate completely different results, since the
-                        target for optimization is different. (default:
-                        `DefaultHyperOptLoss`).
+                        target for optimization is different. Built-in
+                        Hyperopt-loss-functions are: ShortTradeDurHyperOptLoss,
+                        OnlyProfitHyperOptLoss, SharpeHyperOptLoss,
+                        SharpeHyperOptLossDaily, SortinoHyperOptLoss,
+                        SortinoHyperOptLossDaily.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+Strategy arguments:
+  -s NAME, --strategy NAME
+                        Specify strategy class name which will be used by the
+                        bot.
+  --strategy-path PATH  Specify additional strategy lookup path.
+
 ```
 
 ## Edge commands
 
-To know your trade expectacny and winrate against historical data, you can use Edge.
+To know your trade expectancy and winrate against historical data, you can use Edge.
 
 ```
-usage: freqtrade edge [-h] [-i TICKER_INTERVAL] [--timerange TIMERANGE]
-                    [--max_open_trades MAX_OPEN_TRADES]
-                    [--stake_amount STAKE_AMOUNT] [-r]
-                    [--stoplosses STOPLOSS_RANGE]
+usage: freqtrade edge [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
+                      [--userdir PATH] [-s NAME] [--strategy-path PATH]
+                      [-i TIMEFRAME] [--timerange TIMERANGE]
+                      [--max-open-trades INT] [--stake-amount STAKE_AMOUNT]
+                      [--fee FLOAT] [--stoplosses STOPLOSS_RANGE]
 
 optional arguments:
   -h, --help            show this help message and exit
-  -i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
-                        Specify ticker interval (1m, 5m, 30m, 1h, 1d).
+  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
+                        Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
+                        `1d`).
   --timerange TIMERANGE
                         Specify what timerange of data to use.
-  --max_open_trades MAX_OPEN_TRADES
-                        Specify max_open_trades to use.
-  --stake_amount STAKE_AMOUNT
-                        Specify stake_amount.
-  -r, --refresh-pairs-cached
-                        Refresh the pairs files in tests/testdata with the
-                        latest data from the exchange. Use it if you want to
-                        run your optimization commands with up-to-date data.
+  --max-open-trades INT
+                        Override the value of the `max_open_trades`
+                        configuration setting.
+  --stake-amount STAKE_AMOUNT
+                        Override the value of the `stake_amount` configuration
+                        setting.
+  --fee FLOAT           Specify fee ratio. Will be applied twice (on trade
+                        entry and exit).
   --stoplosses STOPLOSS_RANGE
-                        Defines a range of stoploss against which edge will
-                        assess the strategy the format is "min,max,step"
-                        (without any space).example:
-                        --stoplosses=-0.01,-0.1,-0.001
+                        Defines a range of stoploss values against which edge
+                        will assess the strategy. The format is "min,max,step"
+                        (without any space). Example:
+                        `--stoplosses=-0.01,-0.1,-0.001`
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+Strategy arguments:
+  -s NAME, --strategy NAME
+                        Specify strategy class name which will be used by the
+                        bot.
+  --strategy-path PATH  Specify additional strategy lookup path.
+
 ```
 
 To understand edge and how to read the results, please read the [edge documentation](edge.md).
 
-## A parameter missing in the configuration?
-
-All parameters for `main.py`, `backtesting`, `hyperopt` are referenced
-in [misc.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/misc.py#L84)
-
 ## Next step
 
 The optimal strategy of the bot will change with time depending of the market trends. The next step is to
diff --git a/docs/configuration.md b/docs/configuration.md
index f8dbbbbbb..56ba13414 100644
--- a/docs/configuration.md
+++ b/docs/configuration.md
@@ -1,118 +1,225 @@
 # Configure the bot
 
-This page explains how to configure your `config.json` file.
+Freqtrade has many configurable features and possibilities.
+By default, these settings are configured via the configuration file (see below).
 
-## Setup config.json
+## The Freqtrade configuration file
 
-We recommend to copy and use the `config.json.example` as a template
+The bot uses a set of configuration parameters during its operation that all together conform the bot configuration. It normally reads its configuration from a file (Freqtrade configuration file).
+
+Per default, the bot loads the configuration from the `config.json` file, located in the current working directory.
+
+You can specify a different configuration file used by the bot with the `-c/--config` command line option.
+
+In some advanced use cases, multiple configuration files can be specified and used by the bot or the bot can read its configuration parameters from the process standard input stream.
+
+If you used the [Quick start](installation.md/#quick-start) method for installing 
+the bot, the installation script should have already created the default configuration file (`config.json`) for you.
+
+If default configuration file is not created we recommend you to copy and use the `config.json.example` as a template
 for your bot configuration.
 
-The table below will list all configuration parameters.
+The Freqtrade configuration file is to be written in the JSON format.
 
-Mandatory Parameters are marked as **Required**.
+Additionally to the standard JSON syntax, you may use one-line `// ...` and multi-line `/* ... */` comments in your configuration files and trailing commas in the lists of parameters.
 
-|  Command | Default | Description |
-|----------|---------|-------------|
-| `max_open_trades` | 3 | **Required.** Number of trades open your bot will have. If -1 then it is ignored (i.e. potentially unlimited open trades)
-| `stake_currency` | BTC | **Required.** Crypto-currency used for trading. [Strategy Override](#parameters-in-the-strategy).
-| `stake_amount` | 0.05 | **Required.** Amount of crypto-currency your bot will use for each trade. Per default, the bot will use (0.05 BTC x 3) = 0.15 BTC in total will be always engaged. Set it to `"unlimited"` to allow the bot to use all available balance. [Strategy Override](#parameters-in-the-strategy).
-| `amount_reserve_percent` | 0.05 | Reserve some amount in min pair stake amount. Default is 5%. The bot will reserve `amount_reserve_percent` + stop-loss value when calculating min pair stake amount in order to avoid possible trade refusals.
-| `ticker_interval` | [1m, 5m, 15m, 30m, 1h, 1d, ...] | The ticker interval to use (1min, 5 min, 15 min, 30 min, 1 hour or 1 day). Default is 5 minutes. [Strategy Override](#parameters-in-the-strategy).
-| `fiat_display_currency` | USD | **Required.** Fiat currency used to show your profits. More information below.
-| `dry_run` | true | **Required.** Define if the bot must be in Dry-run or production mode.
-| `dry_run_wallet` | 999.9 | Overrides the default amount of 999.9 stake currency units in the wallet used by the bot running in the Dry Run mode if you need it for any reason.
-| `process_only_new_candles` | false | If set to true indicators are processed only once a new candle arrives. If false each loop populates the indicators, this will mean the same candle is processed many times creating system load but can be useful of your strategy depends on tick data not only candle. [Strategy Override](#parameters-in-the-strategy).
-| `minimal_roi` | See below | Set the threshold in percent the bot will use to sell a trade. More information below. [Strategy Override](#parameters-in-the-strategy).
-| `stoploss` | -0.10 | Value of the stoploss in percent used by the bot. More information below. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).
-| `trailing_stop` | false | Enables trailing stop-loss (based on `stoploss` in either configuration or strategy file). More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).
-| `trailing_stop_positive` | 0 | Changes stop-loss once profit has been reached. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).
-| `trailing_stop_positive_offset` | 0 | Offset on when to apply `trailing_stop_positive`. Percentage value which should be positive. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).
-| `trailing_only_offset_is_reached` | false | Only apply trailing stoploss when the offset is reached. [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).
-| `unfilledtimeout.buy` | 10 | **Required.** How long (in minutes) the bot will wait for an unfilled buy order to complete, after which the order will be cancelled.
-| `unfilledtimeout.sell` | 10 | **Required.** How long (in minutes) the bot will wait for an unfilled sell order to complete, after which the order will be cancelled.
-| `bid_strategy.ask_last_balance` | 0.0 | **Required.** Set the bidding price. More information [below](#understand-ask_last_balance).
-| `bid_strategy.use_order_book` | false | Allows buying of pair using the rates in Order Book Bids.
-| `bid_strategy.order_book_top` | 0 | Bot will use the top N rate in Order Book Bids. Ie. a value of 2 will allow the bot to pick the 2nd bid rate in Order Book Bids.
-| `bid_strategy. check_depth_of_market.enabled` | false | Does not buy if the % difference of buy orders and sell orders is met in Order Book.
-| `bid_strategy. check_depth_of_market.bids_to_ask_delta` | 0 | The % difference of buy orders and sell orders found in Order Book. A value lesser than 1 means sell orders is greater, while value greater than 1 means buy orders is higher.
-| `ask_strategy.use_order_book` | false | Allows selling of open traded pair using the rates in Order Book Asks.
-| `ask_strategy.order_book_min` | 0 | Bot will scan from the top min to max Order Book Asks searching for a profitable rate.
-| `ask_strategy.order_book_max` | 0 | Bot will scan from the top min to max Order Book Asks searching for a profitable rate.
-| `order_types` | None | Configure order-types depending on the action (`"buy"`, `"sell"`, `"stoploss"`, `"stoploss_on_exchange"`). [More information below](#understand-order_types). [Strategy Override](#parameters-in-the-strategy).
-| `order_time_in_force` | None | Configure time in force for buy and sell orders. [More information below](#understand-order_time_in_force). [Strategy Override](#parameters-in-the-strategy).
-| `exchange.name` |  | **Required.** Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename).
-| `exchange.sandbox` | false | Use the 'sandbox' version of the exchange, where the exchange provides a sandbox for risk-free integration. See [here](sandbox-testing.md) in more details.
-| `exchange.key` | '' | API key to use for the exchange. Only required when you are in production mode.
-| `exchange.secret` | '' | API secret to use for the exchange. Only required when you are in production mode.
-| `exchange.pair_whitelist` | [] | List of pairs to use by the bot for trading and to check for potential trades during backtesting. Can be overriden by dynamic pairlists (see [below](#dynamic-pairlists)).
-| `exchange.pair_blacklist` | [] | List of pairs the bot must absolutely avoid for trading and backtesting. Can be overriden by dynamic pairlists (see [below](#dynamic-pairlists)).
-| `exchange.ccxt_config` | None | Additional CCXT parameters passed to the regular ccxt instance. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation)
-| `exchange.ccxt_async_config` | None | Additional CCXT parameters passed to the async ccxt instance. Parameters may differ from exchange to exchange  and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation)
-| `exchange.markets_refresh_interval` | 60 | The interval in minutes in which markets are reloaded.
-| `edge` | false | Please refer to [edge configuration document](edge.md) for detailed explanation.
-| `experimental.use_sell_signal` | false | Use your sell strategy in addition of the `minimal_roi`. [Strategy Override](#parameters-in-the-strategy).
-| `experimental.sell_profit_only` | false | Waits until you have made a positive profit before taking a sell decision. [Strategy Override](#parameters-in-the-strategy).
-| `experimental.ignore_roi_if_buy_signal` | false | Does not sell if the buy-signal is still active. Takes preference over `minimal_roi` and `use_sell_signal`. [Strategy Override](#parameters-in-the-strategy).
-| `pairlist.method` | StaticPairList | Use static or dynamic volume-based pairlist. [More information below](#dynamic-pairlists).
-| `pairlist.config` | None | Additional configuration for dynamic pairlists. [More information below](#dynamic-pairlists).
-| `telegram.enabled` | true | **Required.** Enable or not the usage of Telegram.
-| `telegram.token` | token | Your Telegram bot token. Only required if `telegram.enabled` is `true`.
-| `telegram.chat_id` | chat_id | Your personal Telegram account id. Only required if `telegram.enabled` is `true`.
-| `webhook.enabled` | false | Enable usage of Webhook notifications
-| `webhook.url` | false | URL for the webhook. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details.
-| `webhook.webhookbuy` | false | Payload to send on buy. Only required if `webhook.enabled` is `true`. See the [webhook documentationV](webhook-config.md) for more details.
-| `webhook.webhooksell` | false | Payload to send on sell. Only required if `webhook.enabled` is `true`. See the [webhook documentationV](webhook-config.md) for more details.
-| `webhook.webhookstatus` | false | Payload to send on status calls. Only required if `webhook.enabled` is `true`. See the [webhook documentationV](webhook-config.md) for more details.
-| `db_url` | `sqlite:///tradesv3.sqlite`| Declares database URL to use. NOTE: This defaults to `sqlite://` if `dry_run` is `True`.
-| `initial_state` | running | Defines the initial application state. More information below.
-| `forcebuy_enable` | false | Enables the RPC Commands to force a buy. More information below.
-| `strategy` | DefaultStrategy | Defines Strategy class to use.
-| `strategy_path` | null | Adds an additional strategy lookup path (must be a directory).
-| `internals.process_throttle_secs` | 5 | **Required.** Set the process throttle. Value in second.
-| `internals.sd_notify` | false | Enables use of the sd_notify protocol to tell systemd service manager about changes in the bot state and issue keep-alive pings. See [here](installation.md#7-optional-configure-freqtrade-as-a-systemd-service) for more details.
-| `logfile` | | Specify Logfile. Uses a rolling strategy of 10 files, with 1Mb per file.
+Do not worry if you are not familiar with JSON format -- simply open the configuration file with an editor of your choice, make some changes to the parameters you need, save your changes and, finally, restart the bot or, if it was previously stopped, run it again with the changes you made to the configuration. The bot validates syntax of the configuration file at startup and will warn you if you made any errors editing it, pointing out problematic lines.
+
+## Configuration parameters
+
+The table below will list all configuration parameters available.
+
+Freqtrade can also load many options via command line (CLI) arguments (check out the commands `--help` output for details).
+The prevelance for all Options is as follows:
+
+- CLI arguments override any other option
+- Configuration files are used in sequence (last file wins), and override Strategy configurations.
+- Strategy configurations are only used if they are not set via configuration or via command line arguments. These options are marked with [Strategy Override](#parameters-in-the-strategy) in the below table.
+
+Mandatory parameters are marked as **Required**, which means that they are required to be set in one of the possible ways.
+
+|  Parameter | Description |
+|------------|-------------|
+| `max_open_trades` | **Required.** Number of open trades your bot is allowed to have. Only one open trade per pair is possible, so the length of your pairlist is another limitation which can apply. If -1 then it is ignored (i.e. potentially unlimited open trades, limited by the pairlist). [More information below](#configuring-amount-per-trade).<br> **Datatype:** Positive integer or -1.
+| `stake_currency` | **Required.** Crypto-currency used for trading. [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** String
+| `stake_amount` | **Required.** Amount of crypto-currency your bot will use for each trade. Set it to `"unlimited"` to allow the bot to use all available balance. [More information below](#configuring-amount-per-trade). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Positive float or `"unlimited"`.
+| `tradable_balance_ratio` | Ratio of the total account balance the bot is allowed to trade. [More information below](#configuring-amount-per-trade). <br>*Defaults to `0.99` 99%).*<br> **Datatype:** Positive float between `0.1` and `1.0`.
+| `amend_last_stake_amount` | Use reduced last stake amount if necessary. [More information below](#configuring-amount-per-trade). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
+| `last_stake_amount_min_ratio` | Defines minimum stake amount that has to be left and executed. Applies only to the last stake amount when it's amended to a reduced value (i.e. if `amend_last_stake_amount` is set to `true`). [More information below](#configuring-amount-per-trade). <br>*Defaults to `0.5`.* <br> **Datatype:** Float (as ratio)
+| `amount_reserve_percent` | Reserve some amount in min pair stake amount. The bot will reserve `amount_reserve_percent` + stoploss value when calculating min pair stake amount in order to avoid possible trade refusals. <br>*Defaults to `0.05` (5%).* <br> **Datatype:** Positive Float as ratio.
+| `timeframe` | The timeframe (former ticker interval) to use (e.g `1m`, `5m`, `15m`, `30m`, `1h` ...). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** String
+| `fiat_display_currency` | Fiat currency used to show your profits. [More information below](#what-values-can-be-used-for-fiat_display_currency). <br> **Datatype:** String
+| `dry_run` | **Required.** Define if the bot must be in Dry Run or production mode. <br>*Defaults to `true`.* <br> **Datatype:** Boolean
+| `dry_run_wallet` | Define the starting amount in stake currency for the simulated wallet used by the bot running in the Dry Run mode.<br>*Defaults to `1000`.* <br> **Datatype:** Float
+| `cancel_open_orders_on_exit` | Cancel open orders when the `/stop` RPC command is issued, `Ctrl+C` is pressed or the bot dies unexpectedly. When set to `true`, this allows you to use `/stop` to cancel unfilled and partially filled orders in the event of a market crash. It does not impact open positions. <br>*Defaults to `false`.* <br> **Datatype:** Boolean
+| `process_only_new_candles` | Enable processing of indicators only when new candles arrive. If false each loop populates the indicators, this will mean the same candle is processed many times creating system load but can be useful of your strategy depends on tick data not only candle. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.*  <br> **Datatype:** Boolean
+| `minimal_roi` | **Required.** Set the threshold as ratio the bot will use to sell a trade. [More information below](#understand-minimal_roi). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Dict
+| `stoploss` |  **Required.** Value as ratio of the stoploss used by the bot. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).  <br> **Datatype:** Float (as ratio)
+| `trailing_stop` | Enables trailing stoploss (based on `stoploss` in either configuration or strategy file). More details in the [stoploss documentation](stoploss.md#trailing-stop-loss). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Boolean
+| `trailing_stop_positive` | Changes stoploss once profit has been reached. More details in the [stoploss documentation](stoploss.md#trailing-stop-loss-custom-positive-loss). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Float
+| `trailing_stop_positive_offset` | Offset on when to apply `trailing_stop_positive`. Percentage value which should be positive. More details in the [stoploss documentation](stoploss.md#trailing-stop-loss-only-once-the-trade-has-reached-a-certain-offset). [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `0.0` (no offset).* <br> **Datatype:** Float
+| `trailing_only_offset_is_reached` | Only apply trailing stoploss when the offset is reached. [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.*  <br> **Datatype:** Boolean
+| `unfilledtimeout.buy` | **Required.** How long (in minutes) the bot will wait for an unfilled buy order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
+| `unfilledtimeout.sell` | **Required.** How long (in minutes) the bot will wait for an unfilled sell order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
+| `bid_strategy.price_side` | Select the side of the spread the bot should look at to get the buy rate. [More information below](#buy-price-side).<br> *Defaults to `bid`.* <br> **Datatype:** String (either `ask` or `bid`).
+| `bid_strategy.ask_last_balance` | **Required.** Set the bidding price. More information [below](#buy-price-without-orderbook-enabled).
+| `bid_strategy.use_order_book` | Enable buying using the rates in [Order Book Bids](#buy-price-with-orderbook-enabled). <br> **Datatype:** Boolean
+| `bid_strategy.order_book_top` | Bot will use the top N rate in Order Book Bids to buy. I.e. a value of 2 will allow the bot to pick the 2nd bid rate in [Order Book Bids](#buy-price-with-orderbook-enabled). <br>*Defaults to `1`.*  <br> **Datatype:** Positive Integer
+| `bid_strategy. check_depth_of_market.enabled` | Do not buy if the difference of buy orders and sell orders is met in Order Book. [Check market depth](#check-depth-of-market). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
+| `bid_strategy. check_depth_of_market.bids_to_ask_delta` | The difference ratio of buy orders and sell orders found in Order Book. A value below 1 means sell order size is greater, while value greater than 1 means buy order size is higher. [Check market depth](#check-depth-of-market) <br> *Defaults to `0`.*  <br> **Datatype:** Float (as ratio)
+| `ask_strategy.price_side` | Select the side of the spread the bot should look at to get the sell rate. [More information below](#sell-price-side).<br> *Defaults to `ask`.* <br> **Datatype:** String (either `ask` or `bid`).
+| `ask_strategy.use_order_book` | Enable selling of open trades using [Order Book Asks](#sell-price-with-orderbook-enabled). <br> **Datatype:** Boolean
+| `ask_strategy.order_book_min` | Bot will scan from the top min to max Order Book Asks searching for a profitable rate. <br>*Defaults to `1`.* <br> **Datatype:** Positive Integer
+| `ask_strategy.order_book_max` | Bot will scan from the top min to max Order Book Asks searching for a profitable rate. <br>*Defaults to `1`.* <br> **Datatype:** Positive Integer
+| `ask_strategy.use_sell_signal` | Use sell signals produced by the strategy in addition to the `minimal_roi`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `true`.* <br> **Datatype:** Boolean
+| `ask_strategy.sell_profit_only` | Wait until the bot makes a positive profit before taking a sell decision. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
+| `ask_strategy.ignore_roi_if_buy_signal` | Do not sell if the buy signal is still active. This setting takes preference over `minimal_roi` and `use_sell_signal`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
+| `order_types` | Configure order-types depending on the action (`"buy"`, `"sell"`, `"stoploss"`, `"stoploss_on_exchange"`). [More information below](#understand-order_types). [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Dict
+| `order_time_in_force` | Configure time in force for buy and sell orders. [More information below](#understand-order_time_in_force). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Dict
+| `exchange.name` | **Required.** Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename). <br> **Datatype:** String
+| `exchange.sandbox` | Use the 'sandbox' version of the exchange, where the exchange provides a sandbox for risk-free integration. See [here](sandbox-testing.md) in more details.<br> **Datatype:** Boolean
+| `exchange.key` | API key to use for the exchange. Only required when you are in production mode.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
+| `exchange.secret` | API secret to use for the exchange. Only required when you are in production mode.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
+| `exchange.password` | API password to use for the exchange. Only required when you are in production mode and for exchanges that use password for API requests.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
+| `exchange.pair_whitelist` | List of pairs to use by the bot for trading and to check for potential trades during backtesting. Not used by VolumePairList (see [below](#pairlists-and-pairlist-handlers)). <br> **Datatype:** List
+| `exchange.pair_blacklist` | List of pairs the bot must absolutely avoid for trading and backtesting (see [below](#pairlists-and-pairlist-handlers)). <br> **Datatype:** List
+| `exchange.ccxt_config` | Additional CCXT parameters passed to both ccxt instances (sync and async). This is usually the correct place for ccxt configurations. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation) <br> **Datatype:** Dict
+| `exchange.ccxt_sync_config` | Additional CCXT parameters passed to the regular (sync) ccxt instance. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation) <br> **Datatype:** Dict
+| `exchange.ccxt_async_config` | Additional CCXT parameters passed to the async ccxt instance. Parameters may differ from exchange to exchange  and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation) <br> **Datatype:** Dict
+| `exchange.markets_refresh_interval` | The interval in minutes in which markets are reloaded. <br>*Defaults to `60` minutes.* <br> **Datatype:** Positive Integer
+| `exchange.skip_pair_validation` | Skip pairlist validation on startup.<br>*Defaults to `false`<br> **Datatype:** Boolean
+| `edge.*` | Please refer to [edge configuration document](edge.md) for detailed explanation.
+| `experimental.block_bad_exchanges` | Block exchanges known to not work with freqtrade. Leave on default unless you want to test if that exchange works now. <br>*Defaults to `true`.* <br> **Datatype:** Boolean
+| `pairlists` | Define one or more pairlists to be used. [More information below](#pairlists-and-pairlist-handlers). <br>*Defaults to `StaticPairList`.*  <br> **Datatype:** List of Dicts
+| `telegram.enabled` | Enable the usage of Telegram. <br> **Datatype:** Boolean
+| `telegram.token` | Your Telegram bot token. Only required if `telegram.enabled` is `true`. <br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
+| `telegram.chat_id` | Your personal Telegram account id. Only required if `telegram.enabled` is `true`. <br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
+| `webhook.enabled` | Enable usage of Webhook notifications <br> **Datatype:** Boolean
+| `webhook.url` | URL for the webhook. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
+| `webhook.webhookbuy` | Payload to send on buy. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
+| `webhook.webhookbuycancel` | Payload to send on buy order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
+| `webhook.webhooksell` | Payload to send on sell. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
+| `webhook.webhooksellcancel` | Payload to send on sell order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
+| `webhook.webhookstatus` | Payload to send on status calls. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
+| `api_server.enabled` | Enable usage of API Server. See the [API Server documentation](rest-api.md) for more details. <br> **Datatype:** Boolean
+| `api_server.listen_ip_address` | Bind IP address. See the [API Server documentation](rest-api.md) for more details. <br> **Datatype:** IPv4
+| `api_server.listen_port` | Bind Port. See the [API Server documentation](rest-api.md) for more details. <br>**Datatype:** Integer between 1024 and 65535
+| `api_server.verbosity` | Logging verbosity. `info` will print all RPC Calls, while "error" will only display errors. <br>**Datatype:** Enum, either `info` or `error`. Defaults to `info`.
+| `api_server.username` | Username for API server. See the [API Server documentation](rest-api.md) for more details. <br>**Keep it in secret, do not disclose publicly.**<br> **Datatype:** String
+| `api_server.password` | Password for API server. See the [API Server documentation](rest-api.md) for more details. <br>**Keep it in secret, do not disclose publicly.**<br> **Datatype:** String
+| `db_url` | Declares database URL to use. NOTE: This defaults to `sqlite:///tradesv3.dryrun.sqlite` if `dry_run` is `true`, and to `sqlite:///tradesv3.sqlite` for production instances. <br> **Datatype:** String, SQLAlchemy connect string
+| `initial_state` | Defines the initial application state. More information below. <br>*Defaults to `stopped`.* <br> **Datatype:** Enum, either `stopped` or `running`
+| `forcebuy_enable` | Enables the RPC Commands to force a buy. More information below. <br> **Datatype:** Boolean
+| `disable_dataframe_checks` | Disable checking the OHLCV dataframe returned from the strategy methods for correctness. Only use when intentionally changing the dataframe and understand what you are doing. [Strategy Override](#parameters-in-the-strategy).<br> *Defaults to `False`*. <br> **Datatype:** Boolean
+| `strategy` | **Required** Defines Strategy class to use. Recommended to be set via `--strategy NAME`. <br> **Datatype:** ClassName
+| `strategy_path` | Adds an additional strategy lookup path (must be a directory). <br> **Datatype:** String
+| `internals.process_throttle_secs` | Set the process throttle. Value in second. <br>*Defaults to `5` seconds.* <br> **Datatype:** Positive Integer
+| `internals.heartbeat_interval` | Print heartbeat message every N seconds. Set to 0 to disable heartbeat messages. <br>*Defaults to `60` seconds.* <br> **Datatype:** Positive Integer or 0
+| `internals.sd_notify` | Enables use of the sd_notify protocol to tell systemd service manager about changes in the bot state and issue keep-alive pings. See [here](installation.md#7-optional-configure-freqtrade-as-a-systemd-service) for more details. <br> **Datatype:** Boolean
+| `logfile` | Specifies logfile name. Uses a rolling strategy for log file rotation for 10 files with the 1MB limit per file. <br> **Datatype:** String
+| `user_data_dir` | Directory containing user data. <br> *Defaults to `./user_data/`*. <br> **Datatype:** String
+| `dataformat_ohlcv` | Data format to use to store historical candle (OHLCV) data. <br> *Defaults to `json`*. <br> **Datatype:** String
+| `dataformat_trades` | Data format to use to store historical trades data. <br> *Defaults to `jsongz`*. <br> **Datatype:** String
 
 ### Parameters in the strategy
 
 The following parameters can be set in either configuration file or strategy.
 Values set in the configuration file always overwrite values set in the strategy.
 
-* `stake_currency`
-* `stake_amount`
-* `ticker_interval`
 * `minimal_roi`
+* `timeframe`
 * `stoploss`
 * `trailing_stop`
 * `trailing_stop_positive`
 * `trailing_stop_positive_offset`
+* `trailing_only_offset_is_reached`
 * `process_only_new_candles`
 * `order_types`
 * `order_time_in_force`
-* `use_sell_signal` (experimental)
-* `sell_profit_only` (experimental)
-* `ignore_roi_if_buy_signal` (experimental)
+* `stake_currency`
+* `stake_amount`
+* `unfilledtimeout`
+* `disable_dataframe_checks`
+* `use_sell_signal` (ask_strategy)
+* `sell_profit_only` (ask_strategy)
+* `ignore_roi_if_buy_signal` (ask_strategy)
 
-### Understand stake_amount
+### Configuring amount per trade
 
-The `stake_amount` configuration parameter is an amount of crypto-currency your bot will use for each trade.
-The minimal value is 0.0005. If there is not enough crypto-currency in
-the account an exception is generated.
-To allow the bot to trade all the available `stake_currency` in your account set
+There are several methods to configure how much of the stake currency the bot will use to enter a trade. All methods respect the [available balance configuration](#available-balance) as explained below.
+
+#### Available balance
+
+By default, the bot assumes that the `complete amount - 1%` is at it's disposal, and when using [dynamic stake amount](#dynamic-stake-amount), it will split the complete balance into `max_open_trades` buckets per trade.
+Freqtrade will reserve 1% for eventual fees when entering a trade and will therefore not touch that by default.
+
+You can configure the "untouched" amount by using the `tradable_balance_ratio` setting.
+
+For example, if you have 10 ETH available in your wallet on the exchange and `tradable_balance_ratio=0.5` (which is 50%), then the bot will use a maximum amount of 5 ETH for trading and considers this as available balance. The rest of the wallet is untouched by the trades.
+
+!!! Warning
+    The `tradable_balance_ratio` setting applies to the current balance (free balance + tied up in trades). Therefore, assuming the starting balance of 1000, a configuration with `tradable_balance_ratio=0.99` will not guarantee that 10 currency units will always remain available on the exchange. For example, the free amount may reduce to 5 units if the total balance is reduced to 500 (either by a losing streak, or by withdrawing balance).
+
+#### Amend last stake amount
+
+Assuming we have the tradable balance of 1000 USDT, `stake_amount=400`, and `max_open_trades=3`.
+The bot would open 2 trades, and will be unable to fill the last trading slot, since the requested 400 USDT are no longer available, since 800 USDT are already tied in other trades.
+
+To overcome this, the option `amend_last_stake_amount` can be set to `True`, which will enable the bot to reduce stake_amount to the available balance in order to fill the last trade slot.
+
+In the example above this would mean:
+
+- Trade1: 400 USDT
+- Trade2: 400 USDT
+- Trade3: 200 USDT
+
+!!! Note
+    This option only applies with [Static stake amount](#static-stake-amount) - since [Dynamic stake amount](#dynamic-stake-amount) divides the balances evenly.
+
+!!! Note
+    The minimum last stake amount can be configured using `amend_last_stake_amount` - which defaults to 0.5 (50%). This means that the minimum stake amount that's ever used is `stake_amount * 0.5`. This avoids very low stake amounts, that are close to the minimum tradable amount for the pair and can be refused by the exchange.
+
+#### Static stake amount
+
+The `stake_amount` configuration statically configures the amount of stake-currency your bot will use for each trade.
+
+The minimal configuration value is 0.0001, however, please check your exchange's trading minimums for the stake currency you're using to avoid problems.
+
+This setting works in combination with `max_open_trades`. The maximum capital engaged in trades is `stake_amount * max_open_trades`.
+For example, the bot will at most use (0.05 BTC x 3) = 0.15 BTC, assuming a configuration of `max_open_trades=3` and `stake_amount=0.05`.
+
+!!! Note
+    This setting respects the [available balance configuration](#available-balance).
+
+#### Dynamic stake amount
+
+Alternatively, you can use a dynamic stake amount, which will use the available balance on the exchange, and divide that equally by the amount of allowed trades (`max_open_trades`).
+
+To configure this, set `stake_amount="unlimited"`. We also recommend to set `tradable_balance_ratio=0.99` (99%) - to keep a minimum balance for eventual fees.
+
+In this case a trade amount is calculated as:
+
+```python
+currency_balance / (max_open_trades - current_open_trades)
+```
+
+To allow the bot to trade all the available `stake_currency` in your account (minus `tradable_balance_ratio`) set
 
 ```json
 "stake_amount" : "unlimited",
+"tradable_balance_ratio": 0.99,
 ```
 
-In this case a trade amount is calclulated as:
+!!! Note
+    This configuration will allow increasing / decreasing stakes depending on the performance of the bot (lower stake if bot is loosing, higher stakes if the bot has a winning record, since higher balances are available).
 
-```python
-currency_balanse / (max_open_trades - current_open_trades)
-```
+!!! Note "When using Dry-Run Mode"
+    When using `"stake_amount" : "unlimited",` in combination with Dry-Run, the balance will be simulated starting with a stake of `dry_run_wallet` which will evolve over time. It is therefore important to set `dry_run_wallet` to a sensible value (like 0.05 or 0.01 for BTC and 1000 or 100 for USDT, for example), otherwise it may simulate trades with 100 BTC (or more) or 0.05 USDT (or less) at once - which may not correspond to your real available balance or is less than the exchange minimal limit for the order amount for the stake currency.
 
 ### Understand minimal_roi
 
 The `minimal_roi` configuration parameter is a JSON object where the key is a duration
-in minutes and the value is the minimum ROI in percent.
+in minutes and the value is the minimum ROI as ratio.
 See the example below:
 
 ```json
@@ -129,6 +236,9 @@ This parameter can be set in either Strategy or Configuration file. If you use i
 `minimal_roi` value from the strategy file.
 If it is not set in either Strategy or Configuration, a default of 1000% `{"0": 10}` is used, and minimal roi is disabled unless your trade generates 1000% profit.
 
+!!! Note "Special case to forcesell after a specific time"
+    A special case presents using `"<N>": -1` as ROI. This forces the bot to sell a trade after N Minutes, no matter if it's positive or negative, so represents a time-limited force-sell.
+
 ### Understand stoploss
 
 Go to the [stoploss documentation](stoploss.md) for more details.
@@ -161,29 +271,21 @@ before asking the strategy if we should buy or a sell an asset. After each wait
 every opened trade wether or not we should sell, and for all the remaining pairs (either the dynamic list of pairs or
 the static list of pairs) if we should buy.
 
-### Understand ask_last_balance
-
-The `ask_last_balance` configuration parameter sets the bidding price. Value `0.0` will use `ask` price, `1.0` will
-use the `last` price and values between those interpolate between ask and last
-price. Using `ask` price will guarantee quick success in bid, but bot will also
-end up paying more then would probably have been necessary.
-
 ### Understand order_types
 
-The `order_types` configuration parameter contains a dict mapping order-types to
-market-types as well as stoploss on or off exchange type and stoploss on exchange
-update interval in seconds. This allows to buy using limit orders, sell using
-limit-orders, and create stoploss orders using market. It also allows to set the
-stoploss "on exchange" which means stoploss order would be placed immediately once
-the buy order is fulfilled. In case stoploss on exchange and `trailing_stop` are
-both set, then the bot will use `stoploss_on_exchange_interval` to check it periodically
-and update it if necessary (e.x. in case of trailing stoploss).
-This can be set in the configuration file or in the strategy.
-Values set in the configuration file  overwrites values set in the strategy.
+The `order_types` configuration parameter maps actions (`buy`, `sell`, `stoploss`, `emergencysell`) to order-types (`market`, `limit`, ...) as well as configures stoploss to be on the exchange and defines stoploss on exchange update interval in seconds.
 
-If this is configured, all 4 values (`buy`, `sell`, `stoploss` and
-`stoploss_on_exchange`) need to be present, otherwise the bot will warn about it and fail to start.
-The below is the default which is used if this is not configured in either strategy or configuration file.
+This allows to buy using limit orders, sell using
+limit-orders, and create stoplosses using market orders. It also allows to set the
+stoploss "on exchange" which means stoploss order would be placed immediately once
+the buy order is fulfilled.
+    
+`order_types` set in the configuration file overwrites values set in the strategy as a whole, so you need to configure the whole `order_types` dictionary in one place.
+
+If this is configured, the following 4 values (`buy`, `sell`, `stoploss` and
+`stoploss_on_exchange`) need to be present, otherwise the bot will fail to start.
+
+For information on (`emergencysell`,`stoploss_on_exchange`,`stoploss_on_exchange_interval`,`stoploss_on_exchange_limit_ratio`) please see stop loss documentation [stop loss on exchange](stoploss.md)
 
 Syntax for Strategy:
 
@@ -191,9 +293,11 @@ Syntax for Strategy:
 order_types = {
     "buy": "limit",
     "sell": "limit",
+    "emergencysell": "market",
     "stoploss": "market",
     "stoploss_on_exchange": False,
-    "stoploss_on_exchange_interval": 60
+    "stoploss_on_exchange_interval": 60,
+    "stoploss_on_exchange_limit_ratio": 0.99,
 }
 ```
 
@@ -203,25 +307,30 @@ Configuration:
 "order_types": {
     "buy": "limit",
     "sell": "limit",
+    "emergencysell": "market",
     "stoploss": "market",
     "stoploss_on_exchange": false,
     "stoploss_on_exchange_interval": 60
 }
 ```
 
-!!! Note
+!!! Note "Market order support"
     Not all exchanges support "market" orders.
     The following message will be shown if your exchange does not support market orders:
-    `"Exchange <yourexchange>  does not support market orders."`
+    `"Exchange <yourexchange> does not support market orders."` and the bot will refuse to start.
 
-!!! Note
-    Stoploss on exchange interval is not mandatory. Do not change its value if you are
+!!! Warning "Using market orders"
+    Please carefully read the section [Market order pricing](#market-order-pricing) section when using market orders.
+
+!!! Note "Stoploss on exchange"
+    `stoploss_on_exchange_interval` is not mandatory. Do not change its value if you are
     unsure of what you are doing. For more information about how stoploss works please
-    read [the stoploss documentation](stoploss.md).
+    refer to [the stoploss documentation](stoploss.md).
 
-!!! Note
-    In case of stoploss on exchange if the stoploss is cancelled manually then
-    the bot would recreate one.
+    If `stoploss_on_exchange` is enabled and the stoploss is cancelled manually on the exchange, then the bot will create a new stoploss order.
+
+!!! Warning "Warning: stoploss_on_exchange failures"
+    If stoploss on exchange creation fails for some reason, then an "emergency sell" is initiated. By default, this will sell the asset using a market order. The order-type for the emergency-sell can be changed by setting the `emergencysell` value in the `order_types` dictionary - however this is not advised.
 
 ### Understand order_time_in_force
 
@@ -234,7 +343,7 @@ This is most of the time the default time in force. It means the order will rema
 on exchange till it is canceled by user. It can be fully or partially fulfilled.
 If partially fulfilled, the remaining will stay on the exchange till cancelled.
 
-**FOK (Full Or Kill):**
+**FOK (Fill Or Kill):**
 
 It means if the order is not executed immediately AND fully then it is canceled by the exchange.
 
@@ -264,16 +373,18 @@ The possible values are: `gtc` (default), `fok` or `ioc`.
 
 Freqtrade is based on [CCXT library](https://github.com/ccxt/ccxt) that supports over 100 cryptocurrency
 exchange markets and trading APIs. The complete up-to-date list can be found in the
-[CCXT repo homepage](https://github.com/ccxt/ccxt/tree/master/python). However, the bot was tested
-with only Bittrex and Binance.
-
-The bot was tested with the following exchanges:
+[CCXT repo homepage](https://github.com/ccxt/ccxt/tree/master/python).
+ However, the bot was tested by the development team with only Bittrex, Binance and Kraken,
+ so the these are the only officially supported exchanges:
 
 - [Bittrex](https://bittrex.com/): "bittrex"
 - [Binance](https://www.binance.com/): "binance"
+- [Kraken](https://kraken.com/): "kraken"
 
 Feel free to test other exchanges and submit your PR to improve the bot.
 
+Some exchanges require special configuration, which can be found on the [Exchange-specific Notes](exchanges.md) documentation page.
+
 #### Sample exchange configuration
 
 A exchange configuration for "binance" would look as follows:
@@ -297,13 +408,13 @@ This configuration enables binance, as well as rate limiting to avoid bans from
     Optimal settings for rate limiting depend on the exchange and the size of the whitelist, so an ideal parameter will vary on many other settings.
     We try to provide sensible defaults per exchange where possible, if you encounter bans please make sure that `"enableRateLimit"` is enabled and increase the `"rateLimit"` parameter step by step.
 
-#### Advanced FreqTrade Exchange configuration
+#### Advanced Freqtrade Exchange configuration
 
 Advanced options can be configured using the `_ft_has_params` setting, which will override Defaults and exchange-specific behaviours.
 
 Available options are listed in the exchange-class as `_ft_has_default`.
 
-For example, to test the order type `FOK` with Kraken, and modify candle_limit to 200 (so you only get 200 candles per call):
+For example, to test the order type `FOK` with Kraken, and modify candle limit to 200 (so you only get 200 candles per API call):
 
 ```json
 "exchange": {
@@ -336,6 +447,135 @@ The valid values are:
 "BTC", "ETH", "XRP", "LTC", "BCH", "USDT"
 ```
 
+## Prices used for orders
+
+Prices for regular orders can be controlled via the parameter structures `bid_strategy` for buying and `ask_strategy` for selling.
+Prices are always retrieved right before an order is placed, either by querying the exchange tickers or by using the orderbook data.
+
+!!! Note
+    Orderbook data used by Freqtrade are the data retrieved from exchange by the ccxt's function `fetch_order_book()`, i.e. are usually data from the L2-aggregated orderbook, while the ticker data are the structures returned by the ccxt's `fetch_ticker()`/`fetch_tickers()` functions. Refer to the ccxt library [documentation](https://github.com/ccxt/ccxt/wiki/Manual#market-data) for more details.
+
+!!! Warning "Using market orders"
+    Please read the section [Market order pricing](#market-order-pricing) section when using market orders.
+
+### Buy price
+
+#### Check depth of market
+
+When check depth of market is enabled (`bid_strategy.check_depth_of_market.enabled=True`), the buy signals are filtered based on the orderbook depth (sum of all amounts) for each orderbook side.
+
+Orderbook `bid` (buy) side depth is then divided by the orderbook `ask` (sell) side depth and the resulting delta is compared to the value of the `bid_strategy.check_depth_of_market.bids_to_ask_delta` parameter. The buy order is only executed if the orderbook delta is greater than or equal to the configured delta value.
+
+!!! Note
+    A delta value below 1 means that `ask` (sell) orderbook side depth is greater than the depth of the `bid` (buy) orderbook side, while a value greater than 1 means opposite (depth of the buy side is higher than the depth of the sell side).
+
+#### Buy price side
+
+The configuration setting `bid_strategy.price_side` defines the side of the spread the bot looks for when buying.
+
+The following displays an orderbook.
+
+``` explanation
+...
+103
+102
+101  # ask
+-------------Current spread
+99   # bid
+98
+97
+...
+```
+
+If `bid_strategy.price_side` is set to `"bid"`, then the bot will use 99 as buying price.  
+In line with that, if `bid_strategy.price_side` is set to `"ask"`, then the bot will use 101 as buying price.
+
+Using `ask` price often guarantees quicker filled orders, but the bot can also end up paying more than what would have been necessary.
+Taker fees instead of maker fees will most likely apply even when using limit buy orders.
+Also, prices at the "ask" side of the spread are higher than prices at the "bid" side in the orderbook, so the order behaves similar to a market order (however with a maximum price).
+
+#### Buy price with Orderbook enabled
+
+When buying with the orderbook enabled (`bid_strategy.use_order_book=True`), Freqtrade fetches the `bid_strategy.order_book_top` entries from the orderbook and then uses the entry specified as `bid_strategy.order_book_top` on the configured side (`bid_strategy.price_side`) of the orderbook. 1 specifies the topmost entry in the orderbook, while 2 would use the 2nd entry in the orderbook, and so on.
+
+#### Buy price without Orderbook enabled
+
+The following section uses `side` as the configured `bid_strategy.price_side`.
+
+When not using orderbook (`bid_strategy.use_order_book=False`), Freqtrade uses the best `side` price from the ticker if it's below the `last` traded price from the ticker. Otherwise (when the `side` price is above the `last` price), it calculates a rate between `side` and `last` price.
+
+The `bid_strategy.ask_last_balance` configuration parameter controls this. A value of `0.0` will use `side` price, while `1.0` will use the `last` price and values between those interpolate between ask and last price.
+
+### Sell price
+
+#### Sell price side
+
+The configuration setting `ask_strategy.price_side` defines the side of the spread the bot looks for when selling.
+
+The following displays an orderbook:
+
+``` explanation
+...
+103
+102
+101  # ask
+-------------Current spread
+99   # bid
+98
+97
+...
+```
+
+If `ask_strategy.price_side` is set to `"ask"`, then the bot will use 101 as selling price.  
+In line with that, if `ask_strategy.price_side` is set to `"bid"`, then the bot will use 99 as selling price.
+
+#### Sell price with Orderbook enabled
+
+When selling with the orderbook enabled (`ask_strategy.use_order_book=True`), Freqtrade fetches the `ask_strategy.order_book_max` entries in the orderbook. Then each of the orderbook steps between `ask_strategy.order_book_min` and `ask_strategy.order_book_max` on the configured orderbook side are validated for a profitable sell-possibility based on the strategy configuration (`minimal_roi` conditions) and the sell order is placed at the first profitable spot.
+
+!!! Note
+    Using `order_book_max` higher than `order_book_min` only makes sense when ask_strategy.price_side is set to `"ask"`.
+
+The idea here is to place the sell order early, to be ahead in the queue.
+
+A fixed slot (mirroring `bid_strategy.order_book_top`) can be defined by setting `ask_strategy.order_book_min` and `ask_strategy.order_book_max` to the same number.
+
+!!! Warning "Order_book_max > 1 - increased risks for stoplosses!"
+    Using `ask_strategy.order_book_max` higher than 1 will increase the risk the stoploss on exchange is cancelled too early, since an eventual [stoploss on exchange](#understand-order_types) will be cancelled as soon as the order is placed.
+    Also, the sell order will remain on the exchange for `unfilledtimeout.sell` (or until it's filled) - which can lead to missed stoplosses (with or without using stoploss on exchange).
+
+!!! Warning "Order_book_max > 1 in dry-run"
+    Using `ask_strategy.order_book_max` higher than 1 will result in improper dry-run results (significantly better than real orders executed on exchange), since dry-run assumes orders to be filled almost instantly.
+    It is therefore advised to not use this setting for dry-runs.
+
+#### Sell price without Orderbook enabled
+
+When not using orderbook (`ask_strategy.use_order_book=False`), the price at the `ask_strategy.price_side` side (defaults to `"ask"`) from the ticker will be used as the sell price.
+
+### Market order pricing
+
+When using market orders, prices should be configured to use the "correct" side of the orderbook to allow realistic pricing detection.
+Assuming both buy and sell are using market orders, a configuration similar to the following might be used
+
+``` jsonc
+  "order_types": {
+    "buy": "market",
+    "sell": "market"
+    // ...
+  },
+  "bid_strategy": {
+    "price_side": "ask",
+    // ...
+  },
+  "ask_strategy":{
+    "price_side": "bid",
+    // ...
+  },
+```
+
+Obviously, if only one side is using limit orders, different pricing combinations can be used.
+--8<-- "includes/pairlists.md"
+
 ## Switch to Dry-run mode
 
 We recommend starting the bot in the Dry-run mode to see how your bot will
@@ -351,7 +591,7 @@ creating trades on the exchange.
 "db_url": "sqlite:///tradesv3.dryrun.sqlite",
 ```
 
-3. Remove your Exchange API key and secrete (change them by empty values or fake credentials):
+3. Remove your Exchange API key and secret (change them by empty values or fake credentials):
 
 ```json
 "exchange": {
@@ -362,41 +602,18 @@ creating trades on the exchange.
 }
 ```
 
-Once you will be happy with your bot performance running in the Dry-run mode,
-you can switch it to production mode.
+Once you will be happy with your bot performance running in the Dry-run mode, you can switch it to production mode.
 
-### Dynamic Pairlists
+!!! Note
+    A simulated wallet is available during dry-run mode, and will assume a starting capital of `dry_run_wallet` (defaults to 1000).
 
-Dynamic pairlists select pairs for you based on the logic configured.
-The bot runs against all pairs (with that stake) on the exchange, and a number of assets
-(`number_assets`) is selected based on the selected criteria.
+### Considerations for dry-run
 
-By default, the `StaticPairList` method is used.
-The Pairlist method is configured as `pair_whitelist` parameter under the `exchange`
-section of the configuration.
-
-**Available Pairlist methods:**
-
-* `StaticPairList`
-  * It uses configuration from `exchange.pair_whitelist` and `exchange.pair_blacklist`.
-* `VolumePairList`
-  * It selects `number_assets` top pairs based on `sort_key`, which can be one of
-`askVolume`, `bidVolume` and `quoteVolume`, defaults to `quoteVolume`.
-  * There is a possibility to filter low-value coins that would not allow setting a stop loss
-(set `precision_filter` parameter to `true` for this).
-
-Example:
-
-```json
-"pairlist": {
-        "method": "VolumePairList",
-        "config": {
-            "number_assets": 20,
-            "sort_key": "quoteVolume",
-            "precision_filter": false
-        }
-    },
-```
+* API-keys may or may not be provided. Only Read-Only operations (i.e. operations that do not alter account state) on the exchange are performed in the dry-run mode.
+* Wallets (`/balance`) are simulated.
+* Orders are simulated, and will not be posted to the exchange.
+* In combination with `stoploss_on_exchange`, the stop_loss price is assumed to be filled.
+* Open orders (not trades, which are stored in the database) are reset on bot restart.
 
 ## Switch to production mode
 
@@ -404,6 +621,11 @@ In production mode, the bot will engage your money. Be careful, since a wrong
 strategy can lose all your money. Be aware of what you are doing when
 you run it in production mode.
 
+### Setup your exchange account
+
+You will need to create API Keys (usually you get `key` and `secret`, some exchanges require an additional `password`) from the Exchange website and you'll need to insert this into the appropriate fields in the configuration or when asked by the `freqtrade new-config` command.
+API Keys are usually only required for live trading (trading for real money, bot running in "production mode", executing real orders on the exchange) and are not required for the bot running in dry-run (trade simulation) mode. When you setup the bot in dry-run mode, you may fill these fields with empty values.
+
 ### To switch your bot in production mode
 
 **Edit your `config.json`  file.**
@@ -423,12 +645,11 @@ you run it in production mode.
         "secret": "08a9dc6db3d7b53e1acebd9275677f4b0a04f1a5",
         ...
 }
-
 ```
-!!! Note
-    If you have an exchange API key yet, [see our tutorial](/pre-requisite).
 
-### Using proxy with FreqTrade
+You should also make sure to read the [Exchanges](exchanges.md) section of the documentation to be aware of potential configuration details specific to your exchange.
+
+### Using proxy with Freqtrade
 
 To use a proxy with freqtrade, add the kwarg `"aiohttp_trust_env"=true` to the `"ccxt_async_kwargs"` dict in the exchange section of the configuration.
 
@@ -448,14 +669,13 @@ export HTTPS_PROXY="http://addr:port"
 freqtrade
 ```
 
+## Embedding Strategies
 
-### Embedding Strategies
-
-FreqTrade provides you with with an easy way to embed the strategy into your configuration file.
+Freqtrade provides you with with an easy way to embed the strategy into your configuration file.
 This is done by utilizing BASE64 encoding and providing this string at the strategy configuration field,
 in your chosen config file.
 
-#### Encoding a string as BASE64
+### Encoding a string as BASE64
 
 This is a quick example, how to generate the BASE64 string in python
 
diff --git a/docs/data-analysis.md b/docs/data-analysis.md
index 1940fa3e6..17da98935 100644
--- a/docs/data-analysis.md
+++ b/docs/data-analysis.md
@@ -1,42 +1,123 @@
-# Analyzing bot data
+# Analyzing bot data with Jupyter notebooks  
 
-After performing backtests, or after running the bot for some time, it will be interesting to analyze the results your bot generated.
+You can analyze the results of backtests and trading history easily using Jupyter notebooks. Sample notebooks are located at `user_data/notebooks/` after initializing the user directory with `freqtrade create-userdir --userdir user_data`.  
 
-A good way for this is using Jupyter (notebook or lab) - which provides an interactive environment to analyze the data.
+## Quick start with docker
 
-The following helpers will help you loading the data into Pandas DataFrames, and may also give you some starting points in analyzing the results.
+Freqtrade provides a docker-compose file which starts up a jupyter lab server.
+You can run this server using the following command: `docker-compose -f docker/docker-compose-jupyter.yml up`
 
-## Backtesting
+This will create a dockercontainer running jupyter lab, which will be accessible using `https://127.0.0.1:8888/lab`.
+Please use the link that's printed in the console after startup for simplified login.
 
-To analyze your backtest results, you can [export the trades](#exporting-trades-to-file).
-You can then load the trades to perform further analysis.
+For more information, Please visit the [Data analysis with Docker](docker_quickstart.md#data-analayis-using-docker-compose) section.
 
-Freqtrade provides the `load_backtest_data()` helper function to easily load the backtest results, which takes the path to the the backtest-results file as parameter.
+### Pro tips
 
-``` python
-from freqtrade.data.btanalysis import load_backtest_data
-df = load_backtest_data("user_data/backtest-result.json")
+* See [jupyter.org](https://jupyter.org/documentation) for usage instructions.
+* Don't forget to start a Jupyter notebook server from within your conda or venv environment or use [nb_conda_kernels](https://github.com/Anaconda-Platform/nb_conda_kernels)*
+* Copy the example notebook before use so your changes don't get overwritten with the next freqtrade update.
 
-# Show value-counts per pair
-df.groupby("pair")["sell_reason"].value_counts()
+### Using virtual environment with system-wide Jupyter installation
 
+Sometimes it can be desired to use a system-wide installation of Jupyter notebook, and use a jupyter kernel from the virtual environment.
+This prevents you from installing the full jupyter suite multiple times per system, and provides an easy way to switch between tasks (freqtrade / other analytics tasks).
+
+For this to work, first activate your virtual environment and run the following commands:
+
+``` bash
+# Activate virtual environment
+source .env/bin/activate
+
+pip install ipykernel
+ipython kernel install --user --name=freqtrade
+# Restart jupyter (lab / notebook)
+# select kernel "freqtrade" in the notebook
 ```
 
-This will allow you to drill deeper into your backtest results, and perform analysis which otherwise would make the regular backtest-output very difficult to digest due to information overload.
+!!! Note
+    This section is provided for completeness, the Freqtrade Team won't provide full support for problems with this setup and will recommend to install Jupyter in the virtual environment directly, as that is the easiest way to get jupyter notebooks up and running. For help with this setup please refer to the [Project Jupyter](https://jupyter.org/) [documentation](https://jupyter.org/documentation) or [help channels](https://jupyter.org/community).
 
-If you have some ideas for interesting / helpful backtest data analysis ideas, please submit a Pull Request so the community can benefit from it.
+!!! Warning
+    Some tasks don't work especially well in notebooks. For example, anything using asynchronous execution is a problem for Jupyter. Also, freqtrade's primary entry point is the shell cli, so using pure python in a notebook bypasses arguments that provide required objects and parameters to helper functions. You may need to set those values or create expected objects manually.
 
-## Live data
+## Recommended workflow  
 
-To analyze the trades your bot generated, you can load them to a DataFrame as follows:
+| Task | Tool |  
+  --- | ---  
+Bot operations | CLI  
+Repetitive tasks | Shell scripts
+Data analysis & visualization | Notebook  
+
+1. Use the CLI to
+    * download historical data
+    * run a backtest
+    * run with real-time data
+    * export results  
+
+1. Collect these actions in shell scripts
+    * save complicated commands with arguments
+    * execute multi-step operations  
+    * automate testing strategies and preparing data for analysis
+
+1. Use a notebook to
+    * visualize data
+    * munge and plot to generate insights
+
+## Example utility snippets  
+
+### Change directory to root  
+
+Jupyter notebooks execute from the notebook directory. The following snippet searches for the project root, so relative paths remain consistent.
+
+```python
+import os
+from pathlib import Path
+
+# Change directory
+# Modify this cell to insure that the output shows the correct path.
+# Define all paths relative to the project root shown in the cell output
+project_root = "somedir/freqtrade"
+i=0
+try:
+    os.chdirdir(project_root)
+    assert Path('LICENSE').is_file()
+except:
+    while i<4 and (not Path('LICENSE').is_file()):
+        os.chdir(Path(Path.cwd(), '../'))
+        i+=1
+    project_root = Path.cwd()
+print(Path.cwd())
+```
+
+### Load multiple configuration files
+
+This option can be useful to inspect the results of passing in multiple configs.
+This will also run through the whole Configuration initialization, so the configuration is completely initialized to be passed to other methods.
 
 ``` python
-from freqtrade.data.btanalysis import load_trades_from_db
+import json
+from freqtrade.configuration import Configuration
 
-df = load_trades_from_db("sqlite:///tradesv3.sqlite")
-
-df.groupby("pair")["sell_reason"].value_counts()
+# Load config from multiple files
+config = Configuration.from_files(["config1.json", "config2.json"])
 
+# Show the config in memory
+print(json.dumps(config['original_config'], indent=2))
 ```
 
+For Interactive environments, have an additional configuration specifying `user_data_dir` and pass this in last, so you don't have to change directories while running the bot.
+Best avoid relative paths, since this starts at the storage location of the jupyter notebook, unless the directory is changed.
+
+``` json
+{
+    "user_data_dir": "~/.freqtrade/"
+}
+```
+
+### Further Data analysis documentation
+
+* [Strategy debugging](strategy_analysis_example.md) - also available as Jupyter notebook (`user_data/notebooks/strategy_analysis_example.ipynb`)
+* [Plotting](plotting.md)
+
 Feel free to submit an issue or Pull Request enhancing this document if you would like to share ideas on how to best analyze the data.
diff --git a/docs/data-download.md b/docs/data-download.md
new file mode 100644
index 000000000..e9c5c1865
--- /dev/null
+++ b/docs/data-download.md
@@ -0,0 +1,328 @@
+# Data Downloading
+
+## Getting data for backtesting and hyperopt
+
+To download data (candles / OHLCV) needed for backtesting and hyperoptimization use the `freqtrade download-data` command.
+
+If no additional parameter is specified, freqtrade will download data for `"1m"` and `"5m"` timeframes for the last 30 days.
+Exchange and pairs will come from `config.json` (if specified using `-c/--config`).
+Otherwise `--exchange` becomes mandatory.
+
+You can use a relative timerange (`--days 20`) or an absolute starting point (`--timerange 20200101`). For incremental downloads, the relative approach should be used.
+
+!!! Tip "Tip: Updating existing data"
+    If you already have backtesting data available in your data-directory and would like to refresh this data up to today, use `--days xx` with a number slightly higher than the missing number of days. Freqtrade will keep the available data and only download the missing data.
+    Be careful though: If the number is too small (which would result in a few missing days), the whole dataset will be removed and only xx days will be downloaded.
+
+### Usage
+
+```
+usage: freqtrade download-data [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                               [-d PATH] [--userdir PATH]
+                               [-p PAIRS [PAIRS ...]] [--pairs-file FILE]
+                               [--days INT] [--timerange TIMERANGE]
+                               [--dl-trades] [--exchange EXCHANGE]
+                               [-t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]]
+                               [--erase]
+                               [--data-format-ohlcv {json,jsongz,hdf5}]
+                               [--data-format-trades {json,jsongz,hdf5}]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
+                        Show profits for only these pairs. Pairs are space-
+                        separated.
+  --pairs-file FILE     File containing a list of pairs to download.
+  --days INT            Download data for given number of days.
+  --timerange TIMERANGE
+                        Specify what timerange of data to use.
+  --dl-trades           Download trades instead of OHLCV data. The bot will
+                        resample trades to the desired timeframe as specified
+                        as --timeframes/-t.
+  --exchange EXCHANGE   Exchange name (default: `bittrex`). Only valid if no
+                        config is provided.
+  -t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...], --timeframes {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]
+                        Specify which tickers to download. Space-separated
+                        list. Default: `1m 5m`.
+  --erase               Clean all existing data for the selected
+                        exchange/pairs/timeframes.
+  --data-format-ohlcv {json,jsongz,hdf5}
+                        Storage format for downloaded candle (OHLCV) data.
+                        (default: `json`).
+  --data-format-trades {json,jsongz,hdf5}
+                        Storage format for downloaded trades data. (default:
+                        `jsongz`).
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+```
+
+!!! Note "Startup period"
+    `download-data` is a strategy-independent command. The idea is to download a big chunk of data once, and then iteratively increase the amount of data stored.
+
+    For that reason, `download-data` does not care about the "startup-period" defined in a strategy. It's up to the user to download additional days if the backtest should start at a specific point in time (while respecting startup period).
+
+### Data format
+
+Freqtrade currently supports 3 data-formats for both OHLCV and trades data:
+
+* `json` (plain "text" json files)
+* `jsongz` (a gzip-zipped version of json files)
+* `hdf5` (a high performance datastore)
+
+By default, OHLCV data is stored as `json` data, while trades data is stored as `jsongz` data.
+
+This can be changed via the `--data-format-ohlcv` and `--data-format-trades` command line arguments respectively.
+To persist this change, you can should also add the following snippet to your configuration, so you don't have to insert the above arguments each time:
+
+``` jsonc
+    // ...
+    "dataformat_ohlcv": "hdf5",
+    "dataformat_trades": "hdf5",
+    // ...
+```
+
+If the default data-format has been changed during download, then the keys `dataformat_ohlcv` and `dataformat_trades` in the configuration file need to be adjusted to the selected dataformat as well.
+
+!!! Note
+    You can convert between data-formats using the [convert-data](#sub-command-convert-data) and [convert-trade-data](#sub-command-convert-trade-data) methods.
+
+#### Sub-command convert data
+
+```
+usage: freqtrade convert-data [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                              [-d PATH] [--userdir PATH]
+                              [-p PAIRS [PAIRS ...]] --format-from
+                              {json,jsongz,hdf5} --format-to
+                              {json,jsongz,hdf5} [--erase]
+                              [-t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
+                        Show profits for only these pairs. Pairs are space-
+                        separated.
+  --format-from {json,jsongz,hdf5}
+                        Source format for data conversion.
+  --format-to {json,jsongz,hdf5}
+                        Destination format for data conversion.
+  --erase               Clean all existing data for the selected
+                        exchange/pairs/timeframes.
+  -t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...], --timeframes {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]
+                        Specify which tickers to download. Space-separated
+                        list. Default: `1m 5m`.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+```
+
+##### Example converting data
+
+The following command will convert all candle (OHLCV) data available in `~/.freqtrade/data/binance` from json to jsongz, saving diskspace in the process.
+It'll also remove original json data files (`--erase` parameter).
+
+``` bash
+freqtrade convert-data --format-from json --format-to jsongz --datadir ~/.freqtrade/data/binance -t 5m 15m --erase
+```
+
+#### Sub-command convert trade data
+
+```
+usage: freqtrade convert-trade-data [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                                    [-d PATH] [--userdir PATH]
+                                    [-p PAIRS [PAIRS ...]] --format-from
+                                    {json,jsongz,hdf5} --format-to
+                                    {json,jsongz,hdf5} [--erase]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
+                        Show profits for only these pairs. Pairs are space-
+                        separated.
+  --format-from {json,jsongz,hdf5}
+                        Source format for data conversion.
+  --format-to {json,jsongz,hdf5}
+                        Destination format for data conversion.
+  --erase               Clean all existing data for the selected
+                        exchange/pairs/timeframes.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+```
+
+##### Example converting trades
+
+The following command will convert all available trade-data in `~/.freqtrade/data/kraken` from jsongz to json.
+It'll also remove original jsongz data files (`--erase` parameter).
+
+``` bash
+freqtrade convert-trade-data --format-from jsongz --format-to json --datadir ~/.freqtrade/data/kraken --erase
+```
+
+### Sub-command list-data
+
+You can get a list of downloaded data using the `list-data` sub-command.
+
+```
+usage: freqtrade list-data [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
+                           [--userdir PATH] [--exchange EXCHANGE]
+                           [--data-format-ohlcv {json,jsongz,hdf5}]
+                           [-p PAIRS [PAIRS ...]]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --exchange EXCHANGE   Exchange name (default: `bittrex`). Only valid if no
+                        config is provided.
+  --data-format-ohlcv {json,jsongz,hdf5}
+                        Storage format for downloaded candle (OHLCV) data.
+                        (default: `json`).
+  -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
+                        Show profits for only these pairs. Pairs are space-
+                        separated.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+```
+
+#### Example list-data
+
+```bash
+> freqtrade list-data --userdir ~/.freqtrade/user_data/
+
+Found 33 pair / timeframe combinations.
+pairs       timeframe
+----------  -----------------------------------------
+ADA/BTC     5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d
+ADA/ETH     5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d
+ETH/BTC     5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d
+ETH/USDT    5m, 15m, 30m, 1h, 2h, 4h
+```
+
+### Pairs file
+
+In alternative to the whitelist from `config.json`, a `pairs.json` file can be used.
+
+If you are using Binance for example:
+
+- create a directory `user_data/data/binance` and copy or create the `pairs.json` file in that directory.
+- update the `pairs.json` file to contain the currency pairs you are interested in.
+
+```bash
+mkdir -p user_data/data/binance
+cp freqtrade/tests/testdata/pairs.json user_data/data/binance
+```
+
+The format of the `pairs.json` file is a simple json list.
+Mixing different stake-currencies is allowed for this file, since it's only used for downloading.
+
+``` json
+[
+    "ETH/BTC",
+    "ETH/USDT",
+    "BTC/USDT",
+    "XRP/ETH"
+]
+```
+
+### Start download
+
+Then run:
+
+```bash
+freqtrade download-data --exchange binance
+```
+
+This will download historical candle (OHLCV) data for all the currency pairs you defined in `pairs.json`.
+
+### Other Notes
+
+- To use a different directory than the exchange specific default, use `--datadir user_data/data/some_directory`.
+- To change the exchange used to download the historical data from, please use a different configuration file (you'll probably need to adjust rate limits etc.)
+- To use `pairs.json` from some other directory, use `--pairs-file some_other_dir/pairs.json`.
+- To download historical candle (OHLCV) data for only 10 days, use `--days 10` (defaults to 30 days).
+- To download historical candle (OHLCV) data from a fixed starting point, use `--timerange 20200101-` - which will download all data from January 1st, 2020. Eventually set end dates are ignored.
+- Use `--timeframes` to specify what timeframe download the historical candle (OHLCV) data for. Default is `--timeframes 1m 5m` which will download 1-minute and 5-minute data.
+- To use exchange, timeframe and list of pairs as defined in your configuration file, use the `-c/--config` option. With this, the script uses the whitelist defined in the config as the list of currency pairs to download data for and does not require the pairs.json file. You can combine `-c/--config` with most other options.
+
+### Trades (tick) data
+
+By default, `download-data` sub-command downloads Candles (OHLCV) data. Some exchanges also provide historic trade-data via their API.
+This data can be useful if you need many different timeframes, since it is only downloaded once, and then resampled locally to the desired timeframes.
+
+Since this data is large by default, the files use gzip by default. They are stored in your data-directory with the naming convention of `<pair>-trades.json.gz` (`ETH_BTC-trades.json.gz`). Incremental mode is also supported, as for historic OHLCV data, so downloading the data once per week with `--days 8` will create an incremental data-repository.
+
+To use this mode, simply add `--dl-trades` to your call. This will swap the download method to download trades, and resamples the data locally.
+
+Example call:
+
+```bash
+freqtrade download-data --exchange binance --pairs XRP/ETH ETH/BTC --days 20 --dl-trades
+```
+
+!!! Note
+    While this method uses async calls, it will be slow, since it requires the result of the previous call to generate the next request to the exchange.
+
+!!! Warning
+    The historic trades are not available during Freqtrade dry-run and live trade modes because all exchanges tested provide this data with a delay of few 100 candles, so it's not suitable for real-time trading.
+
+!!! Note "Kraken user"
+    Kraken users should read [this](exchanges.md#historic-kraken-data) before starting to download data.
+
+## Next step
+
+Great, you now have backtest data downloaded, so you can now start [backtesting](backtesting.md) your strategy.
diff --git a/docs/deprecated.md b/docs/deprecated.md
index c1582ce31..312f2c74f 100644
--- a/docs/deprecated.md
+++ b/docs/deprecated.md
@@ -4,31 +4,32 @@ This page contains description of the command line arguments, configuration para
 and the bot features that were declared as DEPRECATED by the bot development team
 and are no longer supported. Please avoid their usage in your configuration.
 
+## Removed features
+
+### the `--refresh-pairs-cached` command line option
+
+`--refresh-pairs-cached` in the context of backtesting, hyperopt and edge allows to refresh candle data for backtesting.
+Since this leads to much confusion, and slows down backtesting (while not being part of backtesting) this has been singled out as a separate freqtrade sub-command `freqtrade download-data`.
+
+This command line option was deprecated in 2019.7-dev (develop branch) and removed in 2019.9.
+
 ### The **--dynamic-whitelist** command line option
 
 This command line option was deprecated in 2018 and removed freqtrade 2019.6-dev (develop branch)
-and in freqtrade 2019.7 (master branch).
+and in freqtrade 2019.7.
 
-Per default `--dynamic-whitelist` will retrieve the 20 currencies based
-on BaseVolume. This value can be changed when you run the script.
+### the `--live` command line option
 
-**By Default**
-Get the 20 currencies based on BaseVolume.
+`--live` in the context of backtesting allowed to download the latest tick data for backtesting.
+Did only download the latest 500 candles, so was ineffective in getting good backtest data.
+Removed in 2019-7-dev (develop branch) and in freqtrade 2019.8.
 
-```bash
-freqtrade --dynamic-whitelist
-```
+### Allow running multiple pairlists in sequence
 
-**Customize the number of currencies to retrieve**
-Get the 30 currencies based on BaseVolume.
+The former `"pairlist"` section in the configuration has been removed, and is replaced by `"pairlists"` - being a list to specify a sequence of pairlists.
 
-```bash
-freqtrade --dynamic-whitelist 30
-```
-
-**Exception**
-`--dynamic-whitelist` must be greater than 0. If you enter 0 or a
-negative value (e.g -2), `--dynamic-whitelist` will use the default
-value (20).
+The old section of configuration parameters (`"pairlist"`) has been deprecated in 2019.11 and has been removed in 2020.4.
 
+### deprecation of bidVolume and askVolume from volume-pairlist
 
+Since only quoteVolume can be compared between assets, the other options (bidVolume, askVolume) have been deprecated in 2020.4, and have been removed in 2020.9.
diff --git a/docs/developer.md b/docs/developer.md
index f58e0597d..c253f4460 100644
--- a/docs/developer.md
+++ b/docs/developer.md
@@ -1,8 +1,8 @@
 # Development Help
 
-This page is intended for developers of FreqTrade, people who want to contribute to the FreqTrade codebase or documentation, or people who want to understand the source code of the application they're running.
+This page is intended for developers of Freqtrade, people who want to contribute to the Freqtrade codebase or documentation, or people who want to understand the source code of the application they're running.
 
-All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome. We [track issues](https://github.com/freqtrade/freqtrade/issues) on [GitHub](https://github.com) and also have a dev channel in [slack](https://join.slack.com/t/highfrequencybot/shared_invite/enQtNjU5ODcwNjI1MDU3LWEyODBiNzkzNzcyNzU0MWYyYzE5NjIyOTQxMzBmMGUxOTIzM2YyN2Y4NWY1YTEwZDgwYTRmMzE2NmM5ZmY2MTg) where you can ask questions.
+All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome. We [track issues](https://github.com/freqtrade/freqtrade/issues) on [GitHub](https://github.com) and also have a dev channel on [discord](https://discord.gg/MA9v74M) or [slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-jaut7r4m-Y17k4x5mcQES9a9swKuxbg) where you can ask questions.
 
 ## Documentation
 
@@ -10,81 +10,170 @@ Documentation is available at [https://freqtrade.io](https://www.freqtrade.io/)
 
 Special fields for the documentation (like Note boxes, ...) can be found [here](https://squidfunk.github.io/mkdocs-material/extensions/admonition/).
 
+To test the documentation locally use the following commands.
+
+``` bash
+pip install -r docs/requirements-docs.txt
+mkdocs serve
+```
+
+This will spin up a local server (usually on port 8000) so you can see if everything looks as you'd like it to.
+
 ## Developer setup
 
-To configure a development environment, use best use the `setup.sh` script and answer "y" when asked "Do you want to install dependencies for dev [y/N]? ".
-Alternatively (if your system is not supported by the setup.sh script), follow the manual installation process and run `pip3 install -r requirements-dev.txt`.
+To configure a development environment, you can either use the provided [DevContainer](#devcontainer-setup), or use the `setup.sh` script and answer "y" when asked "Do you want to install dependencies for dev [y/N]? ".
+Alternatively (e.g. if your system is not supported by the setup.sh script), follow the manual installation process and run `pip3 install -e .[all]`.
 
 This will install all required tools for development, including `pytest`, `flake8`, `mypy`, and `coveralls`.
 
+### Devcontainer setup
+
+The fastest and easiest way to get started is to use [VSCode](https://code.visualstudio.com/) with the Remote container extension.
+This gives developers the ability to start the bot with all required dependencies *without* needing to install any freqtrade specific dependencies on your local machine.
+
+#### Devcontainer dependencies
+
+* [VSCode](https://code.visualstudio.com/)
+* [docker](https://docs.docker.com/install/)
+* [Remote container extension documentation](https://code.visualstudio.com/docs/remote)
+
+For more information about the [Remote container extension](https://code.visualstudio.com/docs/remote), best consult the documentation.
+
+### Tests
+
+New code should be covered by basic unittests. Depending on the complexity of the feature, Reviewers may request more in-depth unittests.
+If necessary, the Freqtrade team can assist and give guidance with writing good tests (however please don't expect anyone to write the tests for you).
+
+#### Checking log content in tests
+
+Freqtrade uses 2 main methods to check log content in tests, `log_has()` and `log_has_re()` (to check using regex, in case of dynamic log-messages).
+These are available from `conftest.py` and can be imported in any test module.
+
+A sample check looks as follows:
+
+``` python
+from tests.conftest import log_has, log_has_re
+
+def test_method_to_test(caplog):
+    method_to_test()
+
+    assert log_has("This event happened", caplog)
+    # Check regex with trailing number ...
+    assert log_has_re(r"This dynamic event happened and produced \d+", caplog)
+
+```
+
+## ErrorHandling
+
+Freqtrade Exceptions all inherit from `FreqtradeException`.
+This general class of error should however not be used directly. Instead, multiple specialized sub-Exceptions exist.
+
+Below is an outline of exception inheritance hierarchy:
+
+```
++ FreqtradeException
+|
++---+ OperationalException
+|
++---+ DependencyException
+|   |
+|   +---+ PricingError
+|   |
+|   +---+ ExchangeError
+|       |
+|       +---+ TemporaryError
+|       |
+|       +---+ DDosProtection
+|       |
+|       +---+ InvalidOrderException
+|           |
+|           +---+ RetryableOrderError
+|           |
+|           +---+ InsufficientFundsError
+|
++---+ StrategyError
+```
+
 ## Modules
 
-### Dynamic Pairlist
+### Pairlists
 
 You have a great idea for a new pair selection algorithm you would like to try out? Great.
 Hopefully you also want to contribute this back upstream.
 
-Whatever your motivations are - This should get you off the ground in trying to develop a new Pairlist provider.
+Whatever your motivations are - This should get you off the ground in trying to develop a new Pairlist Handler.
 
-First of all, have a look at the [VolumePairList](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/pairlist/VolumePairList.py) provider, and best copy this file with a name of your new Pairlist Provider.
+First of all, have a look at the [VolumePairList](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/pairlist/VolumePairList.py) Handler, and best copy this file with a name of your new Pairlist Handler.
 
-This is a simple provider, which however serves as a good example on how to start developing.
+This is a simple Handler, which however serves as a good example on how to start developing.
 
-Next, modify the classname of the provider (ideally align this with the Filename).
+Next, modify the class-name of the Handler (ideally align this with the module filename).
 
-The base-class provides the an instance of the bot (`self._freqtrade`), as well as the configuration (`self._config`), and initiates both `_blacklist` and `_whitelist`.
+The base-class provides an instance of the exchange (`self._exchange`) the pairlist manager (`self._pairlistmanager`), as well as the main configuration (`self._config`), the pairlist dedicated configuration (`self._pairlistconfig`) and the absolute position within the list of pairlists.
 
 ```python
-        self._freqtrade = freqtrade
+        self._exchange = exchange
+        self._pairlistmanager = pairlistmanager
         self._config = config
-        self._whitelist = self._config['exchange']['pair_whitelist']
-        self._blacklist = self._config['exchange'].get('pair_blacklist', [])
+        self._pairlistconfig = pairlistconfig
+        self._pairlist_pos = pairlist_pos
 ```
 
-
 Now, let's step through the methods which require actions:
 
-#### configuration
+#### Pairlist configuration
 
-Configuration for PairListProvider is done in the bot configuration file in the element `"pairlist"`.
-This Pairlist-object may contain a `"config"` dict with additional configurations for the configured pairlist.
-By convention, `"number_assets"` is used to specify the maximum number of pairs to keep in the whitelist. Please follow this to ensure a consistent user experience.
+Configuration for the chain of Pairlist Handlers is done in the bot configuration file in the element `"pairlists"`, an array of configuration parameters for each Pairlist Handlers in the chain.
 
-Additional elements can be configured as needed. `VolumePairList` uses `"sort_key"` to specify the sorting value - however feel free to specify whatever is necessary for your great algorithm to be successfull and dynamic.
+By convention, `"number_assets"` is used to specify the maximum number of pairs to keep in the pairlist. Please follow this to ensure a consistent user experience.
+
+Additional parameters can be configured as needed. For instance, `VolumePairList` uses `"sort_key"` to specify the sorting value - however feel free to specify whatever is necessary for your great algorithm to be successful and dynamic.
 
 #### short_desc
 
 Returns a description used for Telegram messages.
-This should contain the name of the Provider, as well as a short description containing the number of assets. Please follow the format `"PairlistName - top/bottom X pairs"`.
 
-#### refresh_pairlist
+This should contain the name of the Pairlist Handler, as well as a short description containing the number of assets. Please follow the format `"PairlistName - top/bottom X pairs"`.
+
+#### gen_pairlist
+
+Override this method if the Pairlist Handler can be used as the leading Pairlist Handler in the chain, defining the initial pairlist which is then handled by all Pairlist Handlers in the chain. Examples are `StaticPairList` and `VolumePairList`.
+
+This is called with each iteration of the bot (only if the Pairlist Handler is at the first location) - so consider implementing caching for compute/network heavy calculations.
+
+It must return the resulting pairlist (which may then be passed into the chain of Pairlist Handlers).
+
+Validations are optional, the parent class exposes a `_verify_blacklist(pairlist)` and `_whitelist_for_active_markets(pairlist)` to do default filtering. Use this if you limit your result to a certain number of pairs - so the end-result is not shorter than expected.
+
+#### filter_pairlist
+
+This method is called for each Pairlist Handler in the chain by the pairlist manager.
 
-Override this method and run all calculations needed in this method.
 This is called with each iteration of the bot - so consider implementing caching for compute/network heavy calculations.
 
-Assign the resulting whiteslist to `self._whitelist` and `self._blacklist` respectively. These will then be used to run the bot in this iteration. Pairs with open trades will be added to the whitelist to have the sell-methods run correctly.
+It gets passed a pairlist (which can be the result of previous pairlists) as well as `tickers`, a pre-fetched version of `get_tickers()`.
 
-Please also run `self._validate_whitelist(pairs)` and to check and remove pairs with inactive markets. This function is available in the Parent class (`StaticPairList`) and should ideally not be overwritten.
+The default implementation in the base class simply calls the `_validate_pair()` method for each pair in the pairlist, but you may override it. So you should either implement the `_validate_pair()` in your Pairlist Handler or override `filter_pairlist()` to do something else.
+
+If overridden, it must return the resulting pairlist (which may then be passed into the next Pairlist Handler in the chain).
+
+Validations are optional, the parent class exposes a `_verify_blacklist(pairlist)` and `_whitelist_for_active_markets(pairlist)` to do default filters. Use this if you limit your result to a certain number of pairs - so the end result is not shorter than expected.
+
+In `VolumePairList`, this implements different methods of sorting, does early validation so only the expected number of pairs is returned.
 
 ##### sample
 
 ``` python
-    def refresh_pairlist(self) -> None:
+    def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
         # Generate dynamic whitelist
-        pairs = self._gen_pair_whitelist(self._config['stake_currency'], self._sort_key)
-        # Validate whitelist to only have active market pairs
-        self._whitelist = self._validate_whitelist(pairs)[:self._number_pairs]
+        pairs = self._calculate_pairlist(pairlist, tickers)
+        return pairs
 ```
 
-#### _gen_pair_whitelist
-
-This is a simple method used by `VolumePairList` - however serves as a good example.
-It implements caching (`@cached(TTLCache(maxsize=1, ttl=1800))`) as well as a configuration option to allow different (but similar) strategies to work with the same PairListProvider.
-
 ## Implement a new Exchange (WIP)
 
 !!! Note
-    This section is a Work in Progress and is not a complete guide on how to test a new exchange with FreqTrade.
+    This section is a Work in Progress and is not a complete guide on how to test a new exchange with Freqtrade.
 
 Most exchanges supported by CCXT should work out of the box.
 
@@ -92,11 +181,11 @@ Most exchanges supported by CCXT should work out of the box.
 
 Check if the new exchange supports Stoploss on Exchange orders through their API.
 
-Since CCXT does not provide unification for Stoploss On Exchange yet, we'll need to implement the exchange-specific parameters ourselfs. Best look at `binance.py` for an example implementation of this. You'll need to dig through the documentation of the Exchange's API on how exactly this can be done. [CCXT Issues](https://github.com/ccxt/ccxt/issues) may also provide great help, since others may have implemented something similar for their projects.
+Since CCXT does not provide unification for Stoploss On Exchange yet, we'll need to implement the exchange-specific parameters ourselves. Best look at `binance.py` for an example implementation of this. You'll need to dig through the documentation of the Exchange's API on how exactly this can be done. [CCXT Issues](https://github.com/ccxt/ccxt/issues) may also provide great help, since others may have implemented something similar for their projects.
 
 ### Incomplete candles
 
-While fetching OHLCV data, we're may end up getting incomplete candles (Depending on the exchange).
+While fetching candle (OHLCV) data, we may end up getting incomplete candles (depending on the exchange).
 To demonstrate this, we'll use daily candles (`"1d"`) to keep things simple.
 We query the api (`ct.fetch_ohlcv()`) for the timeframe and look at the date of the last entry. If this entry changes or shows the date of a "incomplete" candle, then we should drop this since having incomplete candles is problematic because indicators assume that only complete candles are passed to them, and will generate a lot of false buy signals. By default, we're therefore removing the last candle assuming it's incomplete.
 
@@ -105,26 +194,51 @@ To check how the new exchange behaves, you can use the following snippet:
 ``` python
 import ccxt
 from datetime import datetime
-from freqtrade.data.converter import parse_ticker_dataframe
+from freqtrade.data.converter import ohlcv_to_dataframe
 ct = ccxt.binance()
 timeframe = "1d"
 pair = "XLM/BTC"  # Make sure to use a pair that exists on that exchange!
 raw = ct.fetch_ohlcv(pair, timeframe=timeframe)
 
 # convert to dataframe
-df1 = parse_ticker_dataframe(raw, timeframe, pair=pair, drop_incomplete=False)
+df1 = ohlcv_to_dataframe(raw, timeframe, pair=pair, drop_incomplete=False)
 
-print(df1["date"].tail(1))
+print(df1.tail(1))
 print(datetime.utcnow())
 ```
 
 ``` output
-19   2019-06-08 00:00:00+00:00
+                         date      open      high       low     close  volume  
+499 2019-06-08 00:00:00+00:00  0.000007  0.000007  0.000007  0.000007   26264344.0  
 2019-06-09 12:30:27.873327
 ```
 
 The output will show the last entry from the Exchange as well as the current UTC date.
 If the day shows the same day, then the last candle can be assumed as incomplete and should be dropped (leave the setting `"ohlcv_partial_candle"` from the exchange-class untouched / True). Otherwise, set `"ohlcv_partial_candle"` to `False` to not drop Candles (shown in the example above).
+Another way is to run this command multiple times in a row and observe if the volume is changing (while the date remains the same).
+
+## Updating example notebooks
+
+To keep the jupyter notebooks aligned with the documentation, the following should be ran after updating a example notebook.
+
+``` bash
+jupyter nbconvert --ClearOutputPreprocessor.enabled=True --inplace freqtrade/templates/strategy_analysis_example.ipynb
+jupyter nbconvert --ClearOutputPreprocessor.enabled=True --to markdown freqtrade/templates/strategy_analysis_example.ipynb --stdout > docs/strategy_analysis_example.md
+```
+
+## Continuous integration
+
+This documents some decisions taken for the CI Pipeline.
+
+* CI runs on all OS variants, Linux (ubuntu), macOS and Windows.
+* Docker images are build for the branches `stable` and `develop`.
+* Docker images containing Plot dependencies are also available as `stable_plot` and `develop_plot`.
+* Raspberry PI Docker images are postfixed with `_pi` - so tags will be `:stable_pi` and `develop_pi`.
+* Docker images contain a file, `/freqtrade/freqtrade_commit` containing the commit this image is based of.
+* Full docker image rebuilds are run once a week via schedule.
+* Deployments run on ubuntu.
+* ta-lib binaries are contained in the build_helpers directory to avoid fails related to external unavailability.
+* All tests must pass for a PR to be merged to `stable` or `develop`.
 
 ## Creating a release
 
@@ -132,36 +246,69 @@ This part of the documentation is aimed at maintainers, and shows how to create
 
 ### Create release branch
 
-``` bash
-# make sure you're in develop branch
-git checkout develop
+First, pick a commit that's about one week old (to not include latest additions to releases).
 
+``` bash
 # create new branch
-git checkout -b new_release
+git checkout -b new_release <commitid>
 ```
 
-* Edit `freqtrade/__init__.py` and add the version matching the current date (for example `2019.7` for July 2019). Minor versions can be `2019.7-1` should we need to do a second release that month.
+Determine if crucial bugfixes have been made between this commit and the current state, and eventually cherry-pick these.
+
+* Merge the release branch (stable) into this branch.
+* Edit `freqtrade/__init__.py` and add the version matching the current date (for example `2019.7` for July 2019). Minor versions can be `2019.7.1` should we need to do a second release that month. Version numbers must follow allowed versions from PEP0440 to avoid failures pushing to pypi.
 * Commit this part
-* push that branch to the remote and create a PR against the master branch
+* push that branch to the remote and create a PR against the stable branch
 
 ### Create changelog from git commits
 
 !!! Note
-    Make sure that both master and develop are up-todate!.
+    Make sure that the `stable` branch is up-to-date!
 
 ``` bash
 # Needs to be done before merging / pulling that branch.
-git log --oneline --no-decorate --no-merges master..develop
+git log --oneline --no-decorate --no-merges stable..new_release
+```
+
+To keep the release-log short, best wrap the full git changelog into a collapsible details section.
+
+```markdown
+<details>
+<summary>Expand full changelog</summary>
+
+... Full git changelog
+
+</details>
 ```
 
 ### Create github release / tag
 
-* Use the button "Draft a new release" in the Github UI (subsection releases)
-* Use the version-number specified as tag. 
-* Use "master" as reference (this step comes after the above PR is merged).
+Once the PR against stable is merged (best right after merging):
+
+* Use the button "Draft a new release" in the Github UI (subsection releases).
+* Use the version-number specified as tag.
+* Use "stable" as reference (this step comes after the above PR is merged).
 * Use the above changelog as release comment (as codeblock)
 
-### After-release
+## Releases
 
-* Update version in develop by postfixing that with `-dev` (`2019.6 -> 2019.6-dev`).
-* Create a PR against develop to update that branch.
+### pypi
+
+!!! Note
+    This process is now automated as part of Github Actions.
+
+To create a pypi release, please run the following commands:
+
+Additional requirement: `wheel`, `twine` (for uploading), account on pypi with proper permissions.
+
+``` bash
+python setup.py sdist bdist_wheel
+
+# For pypi test (to check if some change to the installation did work)
+twine upload --repository-url https://test.pypi.org/legacy/ dist/*
+
+# For production:
+twine upload dist/*
+```
+
+Please don't push non-releases to the productive / real pypi instance.
diff --git a/docs/docker.md b/docs/docker.md
index 615d31796..f4699cf4c 100644
--- a/docs/docker.md
+++ b/docs/docker.md
@@ -1,31 +1,28 @@
-# Using FreqTrade with Docker
+## Freqtrade with docker without docker-compose
 
-## Install Docker
+!!! Warning
+    The below documentation is provided for completeness and assumes that you are familiar with running docker containers. If you're just starting out with Docker, we recommend to follow the [Quickstart](docker.md) instructions.
 
-Start by downloading and installing Docker CE for your platform:
-
-* [Mac](https://docs.docker.com/docker-for-mac/install/)
-* [Windows](https://docs.docker.com/docker-for-windows/install/)
-* [Linux](https://docs.docker.com/install/)
-
-Once you have Docker installed, simply prepare the config file (e.g. `config.json`) and run the image for `freqtrade` as explained below.
-
-## Download the official FreqTrade docker image
+### Download the official Freqtrade docker image
 
 Pull the image from docker hub.
 
-Branches / tags available can be checked out on [Dockerhub](https://hub.docker.com/r/freqtradeorg/freqtrade/tags/).
+Branches / tags available can be checked out on [Dockerhub tags page](https://hub.docker.com/r/freqtradeorg/freqtrade/tags/).
 
 ```bash
-docker pull freqtradeorg/freqtrade:develop
+docker pull freqtradeorg/freqtrade:stable
 # Optionally tag the repository so the run-commands remain shorter
-docker tag freqtradeorg/freqtrade:develop freqtrade
+docker tag freqtradeorg/freqtrade:stable freqtrade
 ```
 
 To update the image, simply run the above commands again and restart your running container.
 
 Should you require additional libraries, please [build the image yourself](#build-your-own-docker-image).
 
+!!! Note "Docker image update frequency"
+    The official docker images with tags `stable`, `develop` and `latest` are automatically rebuild once a week to keep the base image up-to-date.
+    In addition to that, every merge to `develop` will trigger a rebuild for `develop` and `latest`.
+
 ### Prepare the configuration files
 
 Even though you will use docker, you'll still need some files from the github repository.
@@ -55,39 +52,38 @@ cp -n config.json.example config.json
 
 #### Create your database file
 
-Production
+=== "Dry-Run"
+    ``` bash
+    touch tradesv3.dryrun.sqlite
+    ```
 
-```bash
-touch tradesv3.sqlite
-````
+=== "Production"
+    ``` bash
+    touch tradesv3.sqlite
+    ```
 
-Dry-Run
 
-```bash
-touch tradesv3.dryrun.sqlite
-```
-
-!!! Note
-    Make sure to use the path to this file when starting the bot in docker.
+!!! Warning "Database File Path"
+    Make sure to use the path to the correct database file when starting the bot in Docker.
 
 ### Build your own Docker image
 
 Best start by pulling the official docker image from dockerhub as explained [here](#download-the-official-docker-image) to speed up building.
 
-To add additional libraries to your docker image, best check out [Dockerfile.technical](https://github.com/freqtrade/freqtrade/blob/develop/Dockerfile.technical) which adds the [technical](https://github.com/freqtrade/technical) module to the image.
+To add additional libraries to your docker image, best check out [Dockerfile.technical](https://github.com/freqtrade/freqtrade/blob/develop/docker/Dockerfile.technical) which adds the [technical](https://github.com/freqtrade/technical) module to the image.
 
 ```bash
-docker build -t freqtrade -f Dockerfile.technical .
+docker build -t freqtrade -f docker/Dockerfile.technical .
 ```
 
-If you are developing using Docker, use `Dockerfile.develop` to build a dev Docker image, which will also set up develop dependencies:
+If you are developing using Docker, use `docker/Dockerfile.develop` to build a dev Docker image, which will also set up develop dependencies:
 
 ```bash
-docker build -f Dockerfile.develop -t freqtrade-dev .
+docker build -f docker/Dockerfile.develop -t freqtrade-dev .
 ```
 
-!!! Note
-    For security reasons, your configuration file will not be included in the image, you will need to bind mount it. It is also advised to bind mount an SQLite database file (see the "5. Run a restartable docker image" section) to keep it between  updates.
+!!! Warning "Include your config file manually"
+    For security reasons, your configuration file will not be included in the image, you will need to bind mount it. It is also advised to bind mount an SQLite database file (see [5. Run a restartable docker image](#run-a-restartable-docker-image)") to keep it between  updates.
 
 #### Verify the Docker image
 
@@ -108,37 +104,36 @@ docker run --rm -v `pwd`/config.json:/freqtrade/config.json -it freqtrade
 ```
 
 !!! Warning
-    In this example, the database will be created inside the docker instance and will be lost when you will refresh your image.
+    In this example, the database will be created inside the docker instance and will be lost when you refresh your image.
 
 #### Adjust timezone
 
 By default, the container will use UTC timezone.
-Should you find this irritating please add the following to your docker commands:
+If you would like to change the timezone use the following commands:
 
-##### Linux
+=== "Linux"
+    ``` bash
+    -v /etc/timezone:/etc/timezone:ro
 
-``` bash
--v /etc/timezone:/etc/timezone:ro
+    # Complete command:
+    docker run --rm -v /etc/timezone:/etc/timezone:ro -v `pwd`/config.json:/freqtrade/config.json -it freqtrade
+    ```
 
-# Complete command:
-docker run --rm -v /etc/timezone:/etc/timezone:ro -v `pwd`/config.json:/freqtrade/config.json -it freqtrade
-```
+=== "MacOS"
+    ```bash
+    docker run --rm -e TZ=`ls -la /etc/localtime | cut -d/ -f8-9` -v `pwd`/config.json:/freqtrade/config.json -it freqtrade
+    ```
 
-##### MacOS
-
-There is known issue in OSX Docker versions after 17.09.1, whereby `/etc/localtime` cannot be shared causing Docker to not start. A work-around for this is to start with the following cmd.
-
-```bash
-docker run --rm -e TZ=`ls -la /etc/localtime | cut -d/ -f8-9` -v `pwd`/config.json:/freqtrade/config.json -it freqtrade
-```
-
-More information on this docker issue and work-around can be read [here](https://github.com/docker/for-mac/issues/2396).
+!!! Note "MacOS Issues"
+    The OSX Docker versions after 17.09.1 have a known issue whereby `/etc/localtime` cannot be shared causing Docker to not start.<br>
+    A work-around for this is to start with the MacOS command above
+    More information on this docker issue and work-around can be read [here](https://github.com/docker/for-mac/issues/2396).
 
 ### Run a restartable docker image
 
 To run a restartable instance in the background (feel free to place your configuration and database files wherever it feels comfortable on your filesystem).
 
-#### Move your config file and database
+#### 1. Move your config file and database
 
 The following will assume that you place your configuration / database files to `~/.freqtrade`, which is a hidden directory in your home directory. Feel free to use a different directory and replace the directory in the upcomming commands.
 
@@ -148,7 +143,7 @@ mv config.json ~/.freqtrade
 mv tradesv3.sqlite ~/.freqtrade
 ```
 
-#### Run the docker image
+#### 2. Run the docker image
 
 ```bash
 docker run -d \
@@ -156,16 +151,18 @@ docker run -d \
   -v ~/.freqtrade/config.json:/freqtrade/config.json \
   -v ~/.freqtrade/user_data/:/freqtrade/user_data \
   -v ~/.freqtrade/tradesv3.sqlite:/freqtrade/tradesv3.sqlite \
-  freqtrade --db-url sqlite:///tradesv3.sqlite --strategy MyAwesomeStrategy
+  freqtrade trade --db-url sqlite:///tradesv3.sqlite --strategy MyAwesomeStrategy
 ```
 
 !!! Note
-    db-url defaults to `sqlite:///tradesv3.sqlite` but it defaults to `sqlite://` if `dry_run=True` is being used.
-    To override this behaviour use a custom db-url value: i.e.: `--db-url sqlite:///tradesv3.dryrun.sqlite`
+    When using docker, it's best to specify `--db-url` explicitly to ensure that the database URL and the mounted database file match.
 
 !!! Note
     All available bot command line parameters can be added to the end of the `docker run` command.
 
+!!! Note
+    You can define a [restart policy](https://docs.docker.com/config/containers/start-containers-automatically/) in docker. It can be useful in some cases to use the `--restart unless-stopped` flag (crash of freqtrade or reboot of your system).
+
 ### Monitor your Docker instance
 
 You can use the following commands to monitor and manage your container:
@@ -195,7 +192,7 @@ docker run -d \
   -v ~/.freqtrade/config.json:/freqtrade/config.json \
   -v ~/.freqtrade/tradesv3.sqlite:/freqtrade/tradesv3.sqlite \
   -v ~/.freqtrade/user_data/:/freqtrade/user_data/ \
-  freqtrade --strategy AwsomelyProfitableStrategy backtesting
+  freqtrade backtesting --strategy AwsomelyProfitableStrategy
 ```
 
 Head over to the [Backtesting Documentation](backtesting.md) for more details.
diff --git a/docs/docker_quickstart.md b/docs/docker_quickstart.md
new file mode 100644
index 000000000..48ee34954
--- /dev/null
+++ b/docs/docker_quickstart.md
@@ -0,0 +1,191 @@
+# Using Freqtrade with Docker
+
+## Install Docker
+
+Start by downloading and installing Docker CE for your platform:
+
+* [Mac](https://docs.docker.com/docker-for-mac/install/)
+* [Windows](https://docs.docker.com/docker-for-windows/install/)
+* [Linux](https://docs.docker.com/install/)
+
+Optionally, [`docker-compose`](https://docs.docker.com/compose/install/) should be installed and available to follow the [docker quick start guide](#docker-quick-start).
+
+Once you have Docker installed, simply prepare the config file (e.g. `config.json`) and run the image for `freqtrade` as explained below.
+
+## Freqtrade with docker-compose
+
+Freqtrade provides an official Docker image on [Dockerhub](https://hub.docker.com/r/freqtradeorg/freqtrade/), as well as a [docker-compose file](https://github.com/freqtrade/freqtrade/blob/develop/docker-compose.yml) ready for usage.
+
+!!! Note
+    - The following section assumes that `docker` and `docker-compose` are installed and available to the logged in user.
+    - All below commands use relative directories and will have to be executed from the directory containing the `docker-compose.yml` file.
+
+### Docker quick start
+
+Create a new directory and place the [docker-compose file](https://github.com/freqtrade/freqtrade/blob/develop/docker-compose.yml) in this directory.
+
+=== "PC/MAC/Linux"
+    ``` bash
+    mkdir ft_userdata
+    cd ft_userdata/
+    # Download the docker-compose file from the repository
+    curl https://raw.githubusercontent.com/freqtrade/freqtrade/stable/docker-compose.yml -o docker-compose.yml
+
+    # Pull the freqtrade image
+    docker-compose pull
+
+    # Create user directory structure
+    docker-compose run --rm freqtrade create-userdir --userdir user_data
+
+    # Create configuration - Requires answering interactive questions
+    docker-compose run --rm freqtrade new-config --config user_data/config.json
+    ```
+
+=== "RaspberryPi"
+    ``` bash
+    mkdir ft_userdata
+    cd ft_userdata/
+    # Download the docker-compose file from the repository
+    curl https://raw.githubusercontent.com/freqtrade/freqtrade/stable/docker-compose.yml -o docker-compose.yml
+
+    # Pull the freqtrade image
+    docker-compose pull
+
+    # Create user directory structure
+    docker-compose run --rm freqtrade create-userdir --userdir user_data
+
+    # Create configuration - Requires answering interactive questions
+    docker-compose run --rm freqtrade new-config --config user_data/config.json
+    ```
+
+    !!! Note "Change your docker Image"
+        You have to change the docker image in the docker-compose file for your Raspberry build to work properly.
+        ``` yml
+        image: freqtradeorg/freqtrade:stable_pi
+        # image: freqtradeorg/freqtrade:develop_pi
+        ```
+
+The above snippet creates a new directory called `ft_userdata`, downloads the latest compose file and pulls the freqtrade image.
+The last 2 steps in the snippet create the directory with `user_data`, as well as (interactively) the default configuration based on your selections.
+
+!!! Question "How to edit the bot configuration?"
+    You can edit the configuration at any time, which is available as `user_data/config.json` (within the directory `ft_userdata`) when using the above configuration.
+
+    You can also change the both Strategy and commands by editing the `docker-compose.yml` file.
+
+#### Adding a custom strategy
+
+1. The configuration is now available as `user_data/config.json`
+2. Copy a custom strategy to the directory `user_data/strategies/`
+3. add the Strategy' class name to the `docker-compose.yml` file
+
+The `SampleStrategy` is run by default.
+
+!!! Warning "`SampleStrategy` is just a demo!"
+    The `SampleStrategy` is there for your reference and give you ideas for your own strategy.
+    Please always backtest the strategy and use dry-run for some time before risking real money!
+
+Once this is done, you're ready to launch the bot in trading mode (Dry-run or Live-trading, depending on your answer to the corresponding question you made above).
+
+``` bash
+docker-compose up -d
+```
+
+#### Docker-compose logs
+
+Logs will be located at: `user_data/logs/freqtrade.log`. 
+You can check the latest log with the command `docker-compose logs -f`.
+
+#### Database
+
+The database will be at: `user_data/tradesv3.sqlite`
+
+#### Updating freqtrade with docker-compose
+
+To update freqtrade when using `docker-compose` is as simple as running the following 2 commands:
+
+``` bash
+# Download the latest image
+docker-compose pull
+# Restart the image
+docker-compose up -d
+```
+
+This will first pull the latest image, and will then restart the container with the just pulled version.
+
+!!! Warning "Check the Changelog"
+    You should always check the changelog for breaking changes / manual interventions required and make sure the bot starts correctly after the update.
+
+### Editing the docker-compose file
+
+Advanced users may edit the docker-compose file further to include all possible options or arguments.
+
+All possible freqtrade arguments will be available by running `docker-compose run --rm freqtrade <command> <optional arguments>`.
+
+!!! Note "`docker-compose run --rm`"
+    Including `--rm` will clean up the container after completion, and is highly recommended for all modes except trading mode (running with `freqtrade trade` command).
+
+#### Example: Download data with docker-compose
+
+Download backtesting data for 5 days for the pair ETH/BTC and 1h timeframe from Binance. The data will be stored in the directory `user_data/data/` on the host.
+
+``` bash
+docker-compose run --rm freqtrade download-data --pairs ETH/BTC --exchange binance --days 5 -t 1h
+```
+
+Head over to the [Data Downloading Documentation](data-download.md) for more details on downloading data.
+
+#### Example: Backtest with docker-compose
+
+Run backtesting in docker-containers for SampleStrategy and specified timerange of historical data, on 5m timeframe:
+
+``` bash
+docker-compose run --rm freqtrade backtesting --config user_data/config.json --strategy SampleStrategy --timerange 20190801-20191001 -i 5m
+```
+
+Head over to the [Backtesting Documentation](backtesting.md) to learn more.
+
+### Additional dependencies with docker-compose
+
+If your strategy requires dependencies not included in the default image (like [technical](https://github.com/freqtrade/technical)) - it will be necessary to build the image on your host.
+For this, please create a Dockerfile containing installation steps for the additional dependencies (have a look at [docker/Dockerfile.technical](https://github.com/freqtrade/freqtrade/blob/develop/docker/Dockerfile.technical) for an example).
+
+You'll then also need to modify the `docker-compose.yml` file and uncomment the build step, as well as rename the image to avoid naming collisions.
+
+``` yaml
+    image: freqtrade_custom
+    build:
+      context: .
+      dockerfile: "./Dockerfile.<yourextension>"
+```
+
+You can then run `docker-compose build` to build the docker image, and run it using the commands described above.
+
+## Plotting with docker-compose
+
+Commands `freqtrade plot-profit` and `freqtrade plot-dataframe` ([Documentation](plotting.md)) are available by changing the image to `*_plot` in your docker-compose.yml file.
+You can then use these commands as follows:
+
+``` bash
+docker-compose run --rm freqtrade plot-dataframe --strategy AwesomeStrategy -p BTC/ETH --timerange=20180801-20180805
+```
+
+The output will be stored in the `user_data/plot` directory, and can be opened with any modern browser.
+
+## Data analayis using docker compose
+
+Freqtrade provides a docker-compose file which starts up a jupyter lab server.
+You can run this server using the following command:
+
+``` bash
+docker-compose --rm -f docker/docker-compose-jupyter.yml up
+```
+
+This will create a dockercontainer running jupyter lab, which will be accessible using `https://127.0.0.1:8888/lab`.
+Please use the link that's printed in the console after startup for simplified login.
+
+Since part of this image is built on your machine, it is recommended to rebuild the image from time to time to keep freqtrade (and dependencies) uptodate.
+
+``` bash
+docker-compose -f docker/docker-compose-jupyter.yml build --no-cache
+```
diff --git a/docs/edge.md b/docs/edge.md
index 9047758f4..7442f1927 100644
--- a/docs/edge.md
+++ b/docs/edge.md
@@ -1,75 +1,160 @@
-#  Edge positioning
+# Edge positioning
 
-This page explains how to use Edge Positioning module in your bot in order to enter into a trade only if the trade has a reasonable win rate and risk reward ratio, and consequently adjust your position size and stoploss.
+The `Edge Positioning` module uses probability to calculate your win rate and risk reward ration. It will use these statistics to control your strategy trade entry points, position side and, stoploss. 
 
 !!! Warning
-    Edge positioning is not compatible with dynamic (volume-based) whitelist.
+    `Edge positioning` is not compatible with dynamic (volume-based) whitelist.
 
 !!! Note
-    Edge does not consider anything else than buy/sell/stoploss signals. So trailing stoploss, ROI, and everything else are ignored in its calculation.
+    `Edge Positioning` only considers *its own* buy/sell/stoploss signals. It ignores the stoploss, trailing stoploss, and ROI settings in the strategy configuration file.
+    `Edge Positioning` improves the performance of some trading strategies and *decreases* the performance of others.
 
 ## Introduction
-Trading is all about probability. No one can claim that he has a strategy working all the time. You have to assume that sometimes you lose.
 
-But it doesn't mean there is no rule, it only means rules should work "most of the time". Let's play a game: we toss a coin, heads: I give you 10$, tails: you give me 10$. Is it an interesting game? No, it's quite boring, isn't it?
+Trading strategies are not perfect. They are frameworks that are susceptible to the market and its indicators. Because the market is not at all predictable, sometimes a strategy will win and sometimes the same strategy will lose.
 
-But let's say the probability that we have heads is 80% (because our coin has the displaced distribution of mass or other defect), and the probability that we have tails is 20%. Now it is becoming interesting...
+To obtain an edge in the market, a strategy has to make more money than it loses. Making money in trading is not only about *how often* the strategy makes or loses money. 
 
-That means 10$ X 80% versus 10$ X 20%. 8$ versus 2$. That means over time you will win 8$ risking only 2$ on each toss of coin.
+!!! tip "It doesn't matter how often, but how much!"
+    A bad strategy might make 1 penny in *ten* transactions but lose 1 dollar in *one* transaction. If one only checks the number of winning trades, it would be misleading to think that the strategy is actually making a profit.
 
-Let's complicate it more: you win 80% of the time but only 2$, I win 20% of the time but 8$. The calculation is: 80% X 2$ versus 20% X 8$. It is becoming boring again because overtime you win $1.6$ (80% X 2$) and me $1.6 (20% X 8$) too.
+The Edge Positioning module seeks to improve a strategy's winning probability and the money that the strategy will make *on the long run*. 
 
-The question is: How do you calculate that? How do you know if you wanna play?
+We raise the following question[^1]:
 
-The answer comes to two factors:
-- Win Rate
-- Risk Reward Ratio
+!!! Question "Which trade is a better option?"
+    a) A trade with 80% of chance of losing $100 and 20% chance of winning $200<br/>
+    b) A trade with 100% of chance of losing $30
 
-### Win Rate
-Win Rate (*W*) is is the mean over some amount of trades (*N*) what is the percentage of winning trades to total number of trades (note that we don't consider how much you gained but only if you won or not).
+???+ Info "Answer"
+    The expected value of *a)* is smaller than the expected value of *b)*.<br/>
+    Hence, *b*) represents a smaller loss in the long run.<br/>
+    However, the answer is: *it depends*
 
-    W = (Number of winning trades) / (Total number of trades) = (Number of winning trades) / N
+Another way to look at it is to ask a similar question:
 
-Complementary Loss Rate (*L*) is defined as
+!!! Question "Which trade is a better option?"
+    a) A trade with 80% of chance of winning 100 and 20% chance of losing $200<br/>
+    b) A trade with 100% of chance of winning $30
 
-    L = (Number of losing trades) / (Total number of trades) = (Number of losing trades) / N
+Edge positioning tries to answer the hard questions about risk/reward and position size automatically, seeking to minimizes the chances of losing of a given strategy.
 
-or, which is the same, as
+### Trading, winning and losing
 
-    L = 1 – W
+Let's call $o$ the return of a single transaction $o$ where $o \in \mathbb{R}$. The collection $O = \{o_1, o_2, ..., o_N\}$ is the set of all returns of transactions made during a trading session. We say that $N$ is the cardinality of $O$, or, in lay terms, it is the number of transactions made in a trading session.
+
+!!! Example
+    In a session where a strategy made three transactions we can say that $O = \{3.5, -1, 15\}$. That means that $N = 3$ and $o_1 = 3.5$, $o_2 = -1$, $o_3 = 15$.
+
+A winning trade is a trade where a strategy *made* money. Making money means that the strategy closed the position in a value that returned a profit, after all deducted fees. Formally, a winning trade will have a return $o_i > 0$. Similarly, a losing trade will have a return $o_j \leq 0$. With that, we can discover the set of all winning trades, $T_{win}$, as follows:
+
+$$ T_{win} = \{ o \in O | o > 0 \} $$
+
+Similarly, we can discover the set of losing trades $T_{lose}$ as follows:
+
+$$ T_{lose} = \{o \in O | o \leq 0\} $$
+
+!!! Example
+    In a section where a strategy made three transactions $O = \{3.5, -1, 15, 0\}$:<br>
+    $T_{win} = \{3.5, 15\}$<br>
+    $T_{lose} = \{-1, 0\}$<br>
+
+### Win Rate and Lose Rate
+
+The win rate $W$ is the proportion of winning trades with respect to all the trades made by a strategy. We use the following function to compute the win rate:
+
+$$W = \frac{|T_{win}|}{N}$$
+
+Where $W$ is the win rate, $N$ is the number of trades and, $T_{win}$ is the set of all trades where the strategy made money.
+
+Similarly, we can compute the rate of losing trades:
+
+$$ 
+    L = \frac{|T_{lose}|}{N} 
+$$
+
+Where $L$ is the lose rate, $N$ is the amount of trades made and, $T_{lose}$ is the set of all trades where the strategy lost money. Note that the above formula is the same as calculating $L = 1 – W$ or $W = 1 – L$
 
 ### Risk Reward Ratio
-Risk Reward Ratio (*R*) is a formula used to measure the expected gains of a given investment against the risk of loss. It is basically what you potentially win divided by what you potentially lose:
 
-    R = Profit / Loss
+Risk Reward Ratio ($R$) is a formula used to measure the expected gains of a given investment against the risk of loss. It is basically what you potentially win divided by what you potentially lose. Formally:
 
-Over time, on many trades, you can calculate your risk reward by dividing your average profit on winning trades by your average loss on losing trades:
+$$ R = \frac{\text{potential_profit}}{\text{potential_loss}} $$
 
-    Average profit = (Sum of profits) / (Number of winning trades)
+???+ Example "Worked example of $R$ calculation"
+    Let's say that you think that the price of *stonecoin* today is $10.0. You believe that, because they will start mining stonecoin, it will go up to $15.0 tomorrow. There is the risk that the stone is too hard, and the GPUs can't mine it, so the price might go to $0 tomorrow. You are planning to invest $100, which will give you 10 shares (100 / 10).
 
-    Average loss = (Sum of losses) / (Number of losing trades)
+    Your potential profit is calculated as:
 
-    R = (Average profit) / (Average loss)
+    $\begin{aligned} 
+        \text{potential_profit} &= (\text{potential_price} - \text{entry_price}) * \frac{\text{investment}}{\text{entry_price}} \\
+                                &= (15 - 10) * (100 / 10) \\
+                                &= 50
+    \end{aligned}$
+
+    Since the price might go to $0, the $100 dollars invested could turn into 0.
+
+    We do however use a stoploss of 15% - so in the worst case, we'll sell 15% below entry price (or at 8.5$).
+
+    $\begin{aligned}
+        \text{potential_loss} &= (\text{entry_price} - \text{stoploss}) * \frac{\text{investment}}{\text{entry_price}} \\
+                                &= (10 - 8.5) * (100 / 10)\\
+                                &= 15
+    \end{aligned}$
+
+    We can compute the Risk Reward Ratio as follows:
+
+    $\begin{aligned}
+        R   &= \frac{\text{potential_profit}}{\text{potential_loss}}\\
+            &= \frac{50}{15}\\
+            &= 3.33
+    \end{aligned}$<br>
+    What it effectively means is that the strategy have the potential to make 3.33$ for each $1 invested.
+
+On a long horizon, that is, on many trades, we can calculate the risk reward by dividing the strategy' average profit on winning trades by the strategy' average loss on losing trades. We can calculate the average profit, $\mu_{win}$, as follows:
+
+$$ \text{average_profit} = \mu_{win} = \frac{\text{sum_of_profits}}{\text{count_winning_trades}} = \frac{\sum^{o \in T_{win}} o}{|T_{win}|} $$
+
+Similarly, we can calculate the average loss, $\mu_{lose}$, as follows:
+
+$$ \text{average_loss} = \mu_{lose} = \frac{\text{sum_of_losses}}{\text{count_losing_trades}} = \frac{\sum^{o \in T_{lose}} o}{|T_{lose}|} $$
+
+Finally, we can calculate the Risk Reward ratio, $R$, as follows:
+
+$$ R = \frac{\text{average_profit}}{\text{average_loss}} = \frac{\mu_{win}}{\mu_{lose}}\\ $$
+
+
+???+ Example "Worked example of $R$ calculation using mean profit/loss"
+    Let's say the strategy that we are using makes an average win $\mu_{win} = 2.06$ and an average loss $\mu_{loss} = 4.11$.<br>
+    We calculate the risk reward ratio as follows:<br>
+    $R = \frac{\mu_{win}}{\mu_{loss}} = \frac{2.06}{4.11} = 0.5012...$
+    
 
 ### Expectancy
-At this point we can combine *W* and *R* to create an expectancy ratio. This is a simple process of multiplying the risk reward ratio by the percentage of winning trades and subtracting the percentage of losing trades, which is calculated as follows:
 
-    Expectancy Ratio = (Risk Reward Ratio X Win Rate) – Loss Rate = (R X W) – L
+By combining the Win Rate $W$ and and the Risk Reward ratio $R$ to create an expectancy ratio $E$. A expectance ratio is the expected return of the investment made in a trade. We can compute the value of $E$ as follows:
 
-So lets say your Win rate is 28% and your Risk Reward Ratio is 5:
+$$E = R * W - L$$
 
-    Expectancy = (5 X 0.28) – 0.72 = 0.68
+!!! Example "Calculating $E$"
+    Let's say that a strategy has a win rate $W = 0.28$ and a risk reward ratio $R = 5$. What this means is that the strategy is expected to make 5 times the investment around on 28% of the trades it makes. Working out the example:<br>
+    $E = R * W - L = 5 * 0.28 - 0.72 = 0.68$
+    <br>
 
-Superficially, this means that on average you expect this strategy’s trades to return .68 times the size of your loses. This is important for two reasons: First, it may seem obvious, but you know right away that you have a positive return. Second, you now have a number you can compare to other candidate systems to make decisions about which ones you employ.
+The expectancy worked out in the example above means that, on average, this strategy' trades will return 1.68 times the size of its losses. Said another way, the strategy makes $1.68 for every $1 it loses, on average. 
+
+This is important for two reasons: First, it may seem obvious, but you know right away that you have a positive return. Second, you now have a number you can compare to other candidate systems to make decisions about which ones you employ.
 
 It is important to remember that any system with an expectancy greater than 0 is profitable using past data. The key is finding one that will be profitable in the future.
 
 You can also use this value to evaluate the effectiveness of modifications to this system.
 
-**NOTICE:** It's important to keep in mind that Edge is testing your expectancy using historical data, there's no guarantee that you will have a similar edge in the future. It's still vital to do this testing in order to build confidence in your methodology, but be wary of "curve-fitting" your approach to the historical data as things are unlikely to play out the exact same way for future trades.
+!!! Note
+    It's important to keep in mind that Edge is testing your expectancy using historical data, there's no guarantee that you will have a similar edge in the future. It's still vital to do this testing in order to build confidence in your methodology but be wary of "curve-fitting" your approach to the historical data as things are unlikely to play out the exact same way for future trades.
 
 ## How does it work?
-If enabled in config, Edge will go through historical data with a range of stoplosses in order to find buy and sell/stoploss signals. It then calculates win rate and expectancy over *N* trades for each stoploss. Here is an example:
+
+Edge combines dynamic stoploss, dynamic positions, and whitelist generation into one isolated module which is then applied to the trading strategy. If enabled in config, Edge will go through historical data with a range of stoplosses in order to find buy and sell/stoploss signals. It then calculates win rate and expectancy over *N* trades for each stoploss. Here is an example:
 
 | Pair   |      Stoploss      |  Win Rate | Risk Reward Ratio | Expectancy |
 |----------|:-------------:|-------------:|------------------:|-----------:|
@@ -78,165 +163,108 @@ If enabled in config, Edge will go through historical data with a range of stopl
 | XZC/ETH  |  -0.03        |   0.52       |1.359670           | 0.228      |
 | XZC/ETH  |  -0.04        |   0.51       |1.234539           | 0.117      |
 
-The goal here is to find the best stoploss for the strategy in order to have the maximum expectancy. In the above example stoploss at 3% leads to the maximum expectancy according to historical data.
+The goal here is to find the best stoploss for the strategy in order to have the maximum expectancy. In the above example stoploss at $3%$ leads to the maximum expectancy according to historical data.
 
 Edge module then forces stoploss value it evaluated to your strategy dynamically.
 
 ### Position size
-Edge also dictates the stake amount for each trade to the bot according to the following factors:
+
+Edge dictates the amount at stake for each trade to the bot according to the following factors:
 
 - Allowed capital at risk
 - Stoploss
 
 Allowed capital at risk is calculated as follows:
 
-    Allowed capital at risk = (Capital available_percentage) X (Allowed risk per trade)
+```
+Allowed capital at risk = (Capital available_percentage) X (Allowed risk per trade)
+```
 
-Stoploss is calculated as described above against historical data.
+Stoploss is calculated as described above with respect to historical data.
 
-Your position size then will be:
+The position size is calculated as follows:
 
-    Position size = (Allowed capital at risk) / Stoploss
+```
+Position size = (Allowed capital at risk) / Stoploss
+```
 
 Example:
 
-Let's say the stake currency is ETH and you have 10 ETH on the exchange, your capital available percentage is 50% and you would allow 1% of risk for each trade. thus your available capital for trading is **10 x 0.5 = 5 ETH** and allowed capital at risk would be **5 x 0.01 = 0.05 ETH**.
+Let's say the stake currency is **ETH** and there is $10$ **ETH** on the wallet. The capital available percentage is $50%$ and the allowed risk per trade is $1\%$. Thus, the available capital for trading is $10 * 0.5 = 5$ **ETH** and the allowed capital at risk would be $5 * 0.01 = 0.05$ **ETH**.
 
-Let's assume Edge has calculated that for **XLM/ETH** market your stoploss should be at 2%. So your position size will be **0.05 / 0.02 = 2.5 ETH**.
+-   **Trade 1:** The strategy detects a new buy signal in the **XLM/ETH** market. `Edge Positioning` calculates a stoploss of $2\%$ and a position of $0.05 / 0.02 = 2.5$ **ETH**. The bot takes a position of $2.5$ **ETH** in the **XLM/ETH** market.
 
-Bot takes a position of 2.5 ETH on XLM/ETH (call it trade 1). Up next, you receive another buy signal while trade 1 is still open. This time on **BTC/ETH** market. Edge calculated stoploss for this market at 4%. So your position size would be 0.05 / 0.04 = 1.25 ETH (call it trade 2).
+-   **Trade 2:** The strategy detects a buy signal on the **BTC/ETH** market while **Trade 1** is still open. `Edge Positioning` calculates the stoploss of $4\%$ on this market. Thus, **Trade 2** position size is $0.05 / 0.04 = 1.25$ **ETH**.
 
-Note that available capital for trading didn’t change for trade 2 even if you had already trade 1. The available capital doesn’t mean the free amount on your wallet.
+!!! Tip "Available Capital $\neq$ Available in wallet"
+    The available capital for trading didn't change in **Trade 2** even with **Trade 1** still open. The available capital **is not** the free amount in the wallet.
 
-Now you have two trades open. The bot receives yet another buy signal for another market: **ADA/ETH**. This time the stoploss is calculated at 1%. So your position size is **0.05 / 0.01 = 5 ETH**. But there are already 3.75 ETH blocked in two previous trades. So the position size for this third trade would be **5 – 3.75 = 1.25 ETH**.
+-   **Trade 3:** The strategy detects a buy signal in the **ADA/ETH** market. `Edge Positioning` calculates a stoploss of $1\%$ and a position of $0.05 / 0.01 = 5$ **ETH**. Since **Trade 1** has $2.5$ **ETH** blocked and **Trade 2** has $1.25$ **ETH** blocked, there is only $5 - 1.25 - 2.5 = 1.25$ **ETH** available. Hence, the position size of **Trade 3** is $1.25$ **ETH**. 
 
-Available capital doesn’t change before a position is sold. Let’s assume that trade 1 receives a sell signal and it is sold with a profit of 1 ETH. Your total capital on exchange would be 11 ETH and the available capital for trading becomes 5.5 ETH.
+!!! Tip "Available Capital Updates"
+    The available capital does not change before a position is sold. After a trade is closed the Available Capital goes up if the trade was profitable or goes down if the trade was a loss.
 
-So the Bot receives another buy signal for trade 4 with a stoploss at 2% then your position size would be **0.055 / 0.02 = 2.75 ETH**.
+-   The strategy detects a sell signal in the **XLM/ETH** market. The bot exits **Trade 1** for a profit of $1$ **ETH**. The total capital in the wallet becomes $11$ **ETH** and the available capital for trading becomes $5.5$ **ETH**.
+
+-   **Trade 4** The strategy detects a new buy signal int the **XLM/ETH** market. `Edge Positioning` calculates the stoploss of $2%$, and the position size of $0.055 / 0.02 = 2.75$ **ETH**.
 
 ## Configurations
+
 Edge module has following configuration options:
 
-#### enabled
-If true, then Edge will run periodically.
-
-(defaults to false)
-
-#### process_throttle_secs
-How often should Edge run in seconds?
-
-(defaults to 3600 so one hour)
-
-#### calculate_since_number_of_days
-Number of days of data against which Edge calculates Win Rate, Risk Reward and Expectancy
-Note that it downloads historical data so increasing this number would lead to slowing down the bot.
-
-(defaults to 7)
-
-#### capital_available_percentage
-This is the percentage of the total capital on exchange in stake currency.
-
-As an example if you have 10 ETH available in your wallet on the exchange and this value is 0.5 (which is 50%), then the bot will use a maximum amount of 5 ETH for trading and considers it as available capital.
-
-(defaults to 0.5)
-
-#### allowed_risk
-Percentage of allowed risk per trade.
-
-(defaults to 0.01 so 1%)
-
-#### stoploss_range_min
-
-Minimum stoploss.
-
-(defaults to -0.01)
-
-#### stoploss_range_max
-
-Maximum stoploss.
-
-(defaults to -0.10)
-
-#### stoploss_range_step
-
-As an example if this is set to -0.01 then Edge will test the strategy for \[-0.01, -0,02, -0,03 ..., -0.09, -0.10\] ranges.
-Note than having a smaller step means having a bigger range which could lead to slow calculation.
-
-If you set this parameter to -0.001, you then slow down the Edge calculation by a factor of 10.
-
-(defaults to -0.01)
-
-#### minimum_winrate
-
-It filters out pairs which don't have at least minimum_winrate.
-
-This comes handy if you want to be conservative and don't comprise win rate in favour of risk reward ratio.
-
-(defaults to 0.60)
-
-#### minimum_expectancy
-
-It filters out pairs which have the expectancy lower than this number.
-
-Having an expectancy of 0.20 means if you put 10$ on a trade you expect a 12$ return.
-
-(defaults to 0.20)
-
-#### min_trade_number
-
-When calculating *W*, *R* and *E* (expectancy) against historical data, you always want to have a minimum number of trades. The more this number is the more Edge is reliable.
-
-Having a win rate of 100% on a single trade doesn't mean anything at all. But having a win rate of 70% over past 100 trades means clearly something.
-
-(defaults to 10, it is highly recommended not to decrease this number)
-
-#### max_trade_duration_minute
-
-Edge will filter out trades with long duration. If a trade is profitable after 1 month, it is hard to evaluate the strategy based on it. But if most of trades are profitable and they have maximum duration of 30 minutes, then it is clearly a good sign.
-
-**NOTICE:** While configuring this value, you should take into consideration your ticker interval. As an example filtering out trades having duration less than one day for a strategy which has 4h interval does not make sense. Default value is set assuming your strategy interval is relatively small (1m or 5m, etc.).
-
-(defaults to 1 day, i.e. to 60 * 24 = 1440 minutes)
-
-#### remove_pumps
-
-Edge will remove sudden pumps in a given market while going through historical data. However, given that pumps happen very often in crypto markets, we recommend you keep this off.
-
-(defaults to false)
+|  Parameter | Description |
+|------------|-------------|
+| `enabled` | If true, then Edge will run periodically. <br>*Defaults to `false`.* <br> **Datatype:** Boolean
+| `process_throttle_secs` | How often should Edge run in seconds. <br>*Defaults to `3600` (once per hour).* <br> **Datatype:** Integer
+| `calculate_since_number_of_days` | Number of days of data against which Edge calculates Win Rate, Risk Reward and Expectancy. <br> **Note** that it downloads historical data so increasing this number would lead to slowing down the bot. <br>*Defaults to `7`.* <br> **Datatype:** Integer
+| `allowed_risk` | Ratio of allowed risk per trade. <br>*Defaults to `0.01` (1%)).* <br> **Datatype:** Float
+| `stoploss_range_min` | Minimum stoploss. <br>*Defaults to `-0.01`.* <br> **Datatype:** Float
+| `stoploss_range_max` | Maximum stoploss. <br>*Defaults to `-0.10`.* <br> **Datatype:** Float
+| `stoploss_range_step` | As an example if this is set to -0.01 then Edge will test the strategy for `[-0.01, -0,02, -0,03 ..., -0.09, -0.10]` ranges. <br> **Note** than having a smaller step means having a bigger range which could lead to slow calculation. <br> If you set this parameter to -0.001, you then slow down the Edge calculation by a factor of 10. <br>*Defaults to `-0.001`.* <br> **Datatype:** Float
+| `minimum_winrate` | It filters out pairs which don't have at least minimum_winrate. <br>This comes handy if you want to be conservative and don't comprise win rate in favour of risk reward ratio. <br>*Defaults to `0.60`.* <br> **Datatype:** Float
+| `minimum_expectancy` | It filters out pairs which have the expectancy lower than this number. <br>Having an expectancy of 0.20 means if you put 10$ on a trade you expect a 12$ return. <br>*Defaults to `0.20`.* <br> **Datatype:** Float
+| `min_trade_number` | When calculating *W*, *R* and *E* (expectancy) against historical data, you always want to have a minimum number of trades. The more this number is the more Edge is reliable. <br>Having a win rate of 100% on a single trade doesn't mean anything at all. But having a win rate of 70% over past 100 trades means clearly something. <br>*Defaults to `10` (it is highly recommended not to decrease this number).* <br> **Datatype:** Integer
+| `max_trade_duration_minute` | Edge will filter out trades with long duration. If a trade is profitable after 1 month, it is hard to evaluate the strategy based on it. But if most of trades are profitable and they have maximum duration of 30 minutes, then it is clearly a good sign.<br>**NOTICE:** While configuring this value, you should take into consideration your timeframe. As an example filtering out trades having duration less than one day for a strategy which has 4h interval does not make sense. Default value is set assuming your strategy interval is relatively small (1m or 5m, etc.).<br>*Defaults to `1440` (one day).* <br> **Datatype:** Integer
+| `remove_pumps` | Edge will remove sudden pumps in a given market while going through historical data. However, given that pumps happen very often in crypto markets, we recommend you keep this off.<br>*Defaults to `false`.* <br> **Datatype:** Boolean
 
 ## Running Edge independently
 
 You can run Edge independently in order to see in details the result. Here is an example:
 
-```bash
+``` bash
 freqtrade edge
 ```
 
 An example of its output:
 
-| pair      |   stoploss |   win rate |   risk reward ratio |   required risk reward |   expectancy |   total number of trades |   average duration (min) |
-|:----------|-----------:|-----------:|--------------------:|-----------------------:|-------------:|-------------------------:|-------------------------:|
-| AGI/BTC   |      -0.02 |       0.64 |                5.86 |                   0.56 |         3.41 |                       14 |                       54 |
-| NXS/BTC   |      -0.03 |       0.64 |                2.99 |                   0.57 |         1.54 |                       11 |                       26 |
-| LEND/BTC  |      -0.02 |       0.82 |                2.05 |                   0.22 |         1.50 |                       11 |                       36 |
-| VIA/BTC   |      -0.01 |       0.55 |                3.01 |                   0.83 |         1.19 |                       11 |                       48 |
-| MTH/BTC   |      -0.09 |       0.56 |                2.82 |                   0.80 |         1.12 |                       18 |                       52 |
-| ARDR/BTC  |      -0.04 |       0.42 |                3.14 |                   1.40 |         0.73 |                       12 |                       42 |
-| BCPT/BTC  |      -0.01 |       0.71 |                1.34 |                   0.40 |         0.67 |                       14 |                       30 |
-| WINGS/BTC |      -0.02 |       0.56 |                1.97 |                   0.80 |         0.65 |                       27 |                       42 |
-| VIBE/BTC  |      -0.02 |       0.83 |                0.91 |                   0.20 |         0.59 |                       12 |                       35 |
-| MCO/BTC   |      -0.02 |       0.79 |                0.97 |                   0.27 |         0.55 |                       14 |                       31 |
-| GNT/BTC   |      -0.02 |       0.50 |                2.06 |                   1.00 |         0.53 |                       18 |                       24 |
-| HOT/BTC   |      -0.01 |       0.17 |                7.72 |                   4.81 |         0.50 |                      209 |                        7 |
-| SNM/BTC   |      -0.03 |       0.71 |                1.06 |                   0.42 |         0.45 |                       17 |                       38 |
-| APPC/BTC  |      -0.02 |       0.44 |                2.28 |                   1.27 |         0.44 |                       25 |                       43 |
-| NEBL/BTC  |      -0.03 |       0.63 |                1.29 |                   0.58 |         0.44 |                       19 |                       59 |
+| **pair**     |   **stoploss** |   **win rate** |   **risk reward ratio** |   **required risk reward** |   **expectancy** |   **total number of trades** |   **average duration (min)** |
+|:----------|-----------:|-----------:|--------------------:|-----------------------:|-------------:|-----------------:|---------------:|
+| **AGI/BTC**   |      -0.02 |       0.64 |                5.86 |                   0.56 |         3.41 |                       14 |                       54 |
+| **NXS/BTC**   |      -0.03 |       0.64 |                2.99 |                   0.57 |         1.54 |                       11 |                       26 |
+| **LEND/BTC**  |      -0.02 |       0.82 |                2.05 |                   0.22 |         1.50 |                       11 |                       36 |
+| **VIA/BTC**   |      -0.01 |       0.55 |                3.01 |                   0.83 |         1.19 |                       11 |                       48 |
+| **MTH/BTC**   |      -0.09 |       0.56 |                2.82 |                   0.80 |         1.12 |                       18 |                       52 |
+| **ARDR/BTC**  |      -0.04 |       0.42 |                3.14 |                   1.40 |         0.73 |                       12 |                       42 |
+| **BCPT/BTC**  |      -0.01 |       0.71 |                1.34 |                   0.40 |         0.67 |                       14 |                       30 |
+| **WINGS/BTC** |      -0.02 |       0.56 |                1.97 |                   0.80 |         0.65 |                       27 |                       42 |
+| **VIBE/BTC**  |      -0.02 |       0.83 |                0.91 |                   0.20 |         0.59 |                       12 |                       35 |
+| **MCO/BTC**   |      -0.02 |       0.79 |                0.97 |                   0.27 |         0.55 |                       14 |                       31 |
+| **GNT/BTC**   |      -0.02 |       0.50 |                2.06 |                   1.00 |         0.53 |                       18 |                       24 |
+| **HOT/BTC**   |      -0.01 |       0.17 |                7.72 |                   4.81 |         0.50 |                      209 |                        7 |
+| **SNM/BTC**   |      -0.03 |       0.71 |                1.06 |                   0.42 |         0.45 |                       17 |                       38 |
+| **APPC/BTC**  |      -0.02 |       0.44 |                2.28 |                   1.27 |         0.44 |                       25 |                       43 |
+| **NEBL/BTC**  |      -0.03 |       0.63 |                1.29 |                   0.58 |         0.44 |                       19 |                       59 |
+
+Edge produced the above table by comparing `calculate_since_number_of_days` to `minimum_expectancy` to find `min_trade_number` historical information based on the config file. The timerange Edge uses for its comparisons can be further limited by using the `--timerange` switch.
+
+In live and dry-run modes, after the `process_throttle_secs` has passed, Edge will again process `calculate_since_number_of_days` against `minimum_expectancy` to find `min_trade_number`. If no `min_trade_number` is found, the bot will return "whitelist empty". Depending on the trade strategy being deployed, "whitelist empty" may be return much of the time - or *all* of the time. The use of Edge may also cause trading to occur in bursts, though this is rare.
+
+If you encounter "whitelist empty" a lot, condsider tuning `calculate_since_number_of_days`, `minimum_expectancy`  and `min_trade_number` to align to the trading frequency of your strategy.
 
 ### Update cached pairs with the latest data
 
-```bash
-freqtrade edge --refresh-pairs-cached
-```
+Edge requires historic data the same way as backtesting does.
+Please refer to the [Data Downloading](data-download.md) section of the documentation for details.
 
 ### Precising stoploss range
 
@@ -250,14 +278,14 @@ freqtrade edge --stoplosses=-0.01,-0.1,-0.001 #min,max,step
 freqtrade edge --timerange=20181110-20181113
 ```
 
-Doing `--timerange=-200` will get the last 200 timeframes from your inputdata. You can also specify specific dates, or a range span indexed by start and stop.
+Doing `--timerange=-20190901` will get all available data until September 1st (excluding September 1st 2019).
 
 The full timerange specification:
 
-* Use last 123 tickframes of data: `--timerange=-123`
-* Use first 123 tickframes of data: `--timerange=123-`
-* Use tickframes from line 123 through 456: `--timerange=123-456`
 * Use tickframes till 2018/01/31: `--timerange=-20180131`
 * Use tickframes since 2018/01/31: `--timerange=20180131-`
 * Use tickframes since 2018/01/31 till 2018/03/01 : `--timerange=20180131-20180301`
 * Use tickframes between POSIX timestamps 1527595200 1527618600: `--timerange=1527595200-1527618600`
+
+
+[^1]: Question extracted from MIT Opencourseware S096 - Mathematics with applications in Finance: https://ocw.mit.edu/courses/mathematics/18-s096-topics-in-mathematics-with-applications-in-finance-fall-2013/
diff --git a/docs/exchanges.md b/docs/exchanges.md
new file mode 100644
index 000000000..fcf7c1cad
--- /dev/null
+++ b/docs/exchanges.md
@@ -0,0 +1,119 @@
+# Exchange-specific Notes
+
+This page combines common gotchas and informations which are exchange-specific and most likely don't apply to other exchanges.
+
+## Binance
+
+!!! Tip "Stoploss on Exchange"
+    Binance supports `stoploss_on_exchange` and uses stop-loss-limit orders. It provides great advantages, so we recommend to benefit from it.
+
+### Blacklists
+
+For Binance, please add `"BNB/<STAKE>"` to your blacklist to avoid issues.
+Accounts having BNB accounts use this to pay for fees - if your first trade happens to be on `BNB`, further trades will consume this position and make the initial BNB order unsellable as the expected amount is not there anymore.
+
+### Binance sites
+
+Binance has been split into 3, and users must use the correct ccxt exchange ID for their exchange, otherwise API keys are not recognized.
+
+* [binance.com](https://www.binance.com/) - International users. Use exchange id: `binance`.
+* [binance.us](https://www.binance.us/) - US based users. Use exchange id: `binanceus`.
+* [binance.je](https://www.binance.je/) - Binance Jersey, trading fiat currencies. Use exchange id: `binanceje`.
+
+## Kraken
+
+!!! Tip "Stoploss on Exchange"
+    Kraken supports `stoploss_on_exchange` and uses stop-loss-market orders. It provides great advantages, so we recommend to benefit from it, however since the resulting order is a stoploss-market order, sell-rates are not guaranteed, which makes this feature less secure than on other exchanges. This limitation is based on kraken's policy [source](https://blog.kraken.com/post/1234/announcement-delisting-pairs-and-temporary-suspension-of-advanced-order-types/) and [source2](https://blog.kraken.com/post/1494/kraken-enables-advanced-orders-and-adds-10-currency-pairs/) - which has stoploss-limit orders disabled.
+
+### Historic Kraken data
+
+The Kraken API does only provide 720 historic candles, which is sufficient for Freqtrade dry-run and live trade modes, but is a problem for backtesting.
+To download data for the Kraken exchange, using `--dl-trades` is mandatory, otherwise the bot will download the same 720 candles over and over, and you'll not have enough backtest data.
+
+Due to the heavy rate-limiting applied by Kraken, the following configuration section should be used to download data:
+
+``` json
+    "ccxt_async_config": {
+        "enableRateLimit": true,
+        "rateLimit": 3100
+    },
+```
+
+## Bittrex
+
+### Order types
+
+Bittrex does not support market orders. If you have a message at the bot startup about this, you should change order type values set in your configuration and/or in the strategy from `"market"` to `"limit"`. See some more details on this [here in the FAQ](faq.md#im-getting-the-exchange-bittrex-does-not-support-market-orders-message-and-cannot-run-my-strategy).
+
+### Restricted markets
+
+Bittrex split its exchange into US and International versions.
+The International version has more pairs available, however the API always returns all pairs, so there is currently no automated way to detect if you're affected by the restriction.
+
+If you have restricted pairs in your whitelist, you'll get a warning message in the log on Freqtrade startup for each restricted pair.
+
+The warning message will look similar to the following:
+
+``` output
+[...] Message: bittrex {"success":false,"message":"RESTRICTED_MARKET","result":null,"explanation":null}"
+```
+
+If you're an "International" customer on the Bittrex exchange, then this warning will probably not impact you.
+If you're a US customer, the bot will fail to create orders for these pairs, and you should remove them from your whitelist.
+
+You can get a list of restricted markets by using the following snippet:
+
+``` python
+import ccxt
+ct = ccxt.bittrex()
+_ = ct.load_markets()
+res = [ f"{x['MarketCurrency']}/{x['BaseCurrency']}" for x in ct.publicGetMarkets()['result'] if x['IsRestricted']]
+print(res)
+```
+
+## FTX
+
+!!! Tip "Stoploss on Exchange"
+    FTX supports `stoploss_on_exchange` and can use both stop-loss-market and stop-loss-limit orders. It provides great advantages, so we recommend to benefit from it.
+    You can use either `"limit"` or `"market"` in the `order_types.stoploss` configuration setting to decide.
+
+
+### Using subaccounts
+
+To use subaccounts with FTX, you need to edit the configuration and add the following:
+
+``` json
+"exchange": {
+    "ccxt_config": {
+        "headers": {
+            "FTX-SUBACCOUNT": "name"
+        }
+    },
+}
+```
+
+!!! Note
+    Older versions of freqtrade may require this key to be added to `"ccxt_async_config"` as well.
+
+## All exchanges
+
+Should you experience constant errors with Nonce (like `InvalidNonce`), it is best to regenerate the API keys. Resetting Nonce is difficult and it's usually easier to regenerate the API keys.
+
+
+## Random notes for other exchanges
+
+* The Ocean (exchange id: `theocean`) exchange uses Web3 functionality and requires `web3` python package to be installed:
+```shell
+$ pip3 install web3
+```
+
+### Getting latest price / Incomplete candles
+
+Most exchanges return current incomplete candle via their OHLCV/klines API interface.
+By default, Freqtrade assumes that incomplete candle is fetched from the exchange and removes the last candle assuming it's the incomplete candle.
+
+Whether your exchange returns incomplete candles or not can be checked using [the helper script](developer.md#Incomplete-candles) from the Contributor documentation.
+
+Due to the danger of repainting, Freqtrade does not allow you to use this incomplete candle.
+
+However, if it is based on the need for the latest price for your strategy - then this requirement can be acquired using the [data provider](strategy-customization.md#possible-options-for-dataprovider) from within the strategy.
diff --git a/docs/faq.md b/docs/faq.md
index 83576af4d..aa33218fb 100644
--- a/docs/faq.md
+++ b/docs/faq.md
@@ -1,10 +1,14 @@
 # Freqtrade FAQ
 
+## Beginner Tips & Tricks
+
+* When you work with your strategy & hyperopt file you should use a proper code editor like vscode or Pycharm. A good code editor will provide syntax highlighting as well as line numbers, making it easy to find syntax errors (most likely, pointed out by Freqtrade during startup).
+
 ## Freqtrade common issues
 
 ### The bot does not start
 
-Running the bot with `freqtrade --config config.json` does show the output `freqtrade: command not found`.
+Running the bot with `freqtrade trade --config config.json` does show the output `freqtrade: command not found`.
 
 This could have the following reasons:
 
@@ -15,10 +19,12 @@ This could have the following reasons:
 
 ### I have waited 5 minutes, why hasn't the bot made any trades yet?!
 
-Depending on the buy strategy, the amount of whitelisted coins, the
+* Depending on the buy strategy, the amount of whitelisted coins, the
 situation of the market etc, it can take up to hours to find good entry
 position for a trade. Be patient!
 
+* Or it may because of a configuration error? Best check the logs, it's usually telling you if the bot is simply not getting buy signals (only heartbeat messages), or if there is something wrong (errors / exceptions in the log).
+
 ### I have made 12 trades already, why is my total profit negative?!
 
 I understand your disappointment but unfortunately 12 trades is just
@@ -38,42 +44,112 @@ like pauses. You can stop your bot, adjust settings and start it again.
 
 ### I want to improve the bot with a new strategy
 
-That's great. We have a nice backtesting and hyperoptimizing setup. See
+That's great. We have a nice backtesting and hyperoptimization setup. See
 the tutorial [here|Testing-new-strategies-with-Hyperopt](bot-usage.md#hyperopt-commands).
 
 ### Is there a setting to only SELL the coins being held and not perform anymore BUYS?
 
 You can use the `/forcesell all` command from Telegram.
 
+### I want to run multiple bots on the same machine
+
+Please look at the [advanced setup documentation Page](advanced-setup.md#running-multiple-instances-of-freqtrade).
+
+### I'm getting "Missing data fillup" messages in the log
+
+This message is just a warning that the latest candles had missing candles in them.
+Depending on the exchange, this can indicate that the pair didn't have a trade for the timeframe you are using - and the exchange does only return candles with volume.
+On low volume pairs, this is a rather common occurance.
+
+If this happens for all pairs in the pairlist, this might indicate a recent exchange downtime. Please check your exchange's public channels for details.
+
+Irrespectively of the reason, Freqtrade will fill up these candles with "empty" candles, where open, high, low and close are set to the previous candle close - and volume is empty. In a chart, this will look like a `_` - and is aligned with how exchanges usually represent 0 volume candles.
+
+### I'm getting the "RESTRICTED_MARKET" message in the log
+
+Currently known to happen for US Bittrex users.  
+
+Read [the Bittrex section about restricted markets](exchanges.md#restricted-markets) for more information.
+
+### I'm getting the "Exchange Bittrex does not support market orders." message and cannot run my strategy
+
+As the message says, Bittrex does not support market orders and you have one of the [order types](configuration.md/#understand-order_types) set to "market". Probably your strategy was written with other exchanges in mind and sets "market" orders for "stoploss" orders, which is correct and preferable for most of the exchanges supporting market orders (but not for Bittrex).
+
+To fix it for Bittrex, redefine order types in the strategy to use "limit" instead of "market":
+
+```
+    order_types = {
+        ...
+        'stoploss': 'limit',
+        ...
+    }
+```
+
+Same fix should be done in the configuration file, if order types are defined in your custom config rather than in the strategy.
+
+### How do I search the bot logs for something?
+
+By default, the bot writes its log into stderr stream. This is implemented this way so that you can easily separate the bot's diagnostics messages from Backtesting, Edge and Hyperopt results, output from other various Freqtrade utility sub-commands, as well as from the output of your custom `print()`'s you may have inserted into your strategy. So if you need to search the log messages with the grep utility, you need to redirect stderr to stdout and disregard stdout.
+
+* In unix shells, this normally can be done as simple as:
+```shell
+$ freqtrade --some-options 2>&1 >/dev/null | grep 'something'
+```
+(note, `2>&1` and `>/dev/null` should be written in this order)
+
+* Bash interpreter also supports so called process substitution syntax, you can grep the log for a string with it as:
+```shell
+$ freqtrade --some-options 2> >(grep 'something') >/dev/null
+```
+or
+```shell
+$ freqtrade --some-options 2> >(grep -v 'something' 1>&2)
+```
+
+* You can also write the copy of Freqtrade log messages to a file with the `--logfile` option:
+```shell
+$ freqtrade --logfile /path/to/mylogfile.log --some-options
+```
+and then grep it as:
+```shell
+$ cat /path/to/mylogfile.log | grep 'something'
+```
+or even on the fly, as the bot works and the log file grows:
+```shell
+$ tail -f /path/to/mylogfile.log | grep 'something'
+```
+from a separate terminal window.
+
+On Windows, the `--logfile` option is also supported by Freqtrade and you can use the `findstr` command to search the log for the string of interest:
+```
+> type \path\to\mylogfile.log | findstr "something"
+```
+
 ## Hyperopt module
 
 ### How many epoch do I need to get a good Hyperopt result?
 
-Per default Hyperopts without `-e` or `--epochs` parameter will only
+Per default Hyperopt called without the `-e`/`--epochs` command line option will only
 run 100 epochs, means 100 evals of your triggers, guards, ... Too few
 to find a great result (unless if you are very lucky), so you probably
 have to run it for 10.000 or more. But it will take an eternity to
 compute.
 
-We recommend you to run it at least 10.000 epochs:
+Since hyperopt uses Bayesian search, running for too many epochs may not produce greater results.
+
+It's therefore recommended to run between 500-1000 epochs over and over until you hit at least 10.000 epochs in total (or are satisfied with the result). You can best judge by looking at the results - if the bot keeps discovering better strategies, it's best to keep on going.
 
 ```bash
-freqtrade hyperopt -e 10000
+freqtrade hyperopt --hyperop SampleHyperopt --hyperopt-loss SharpeHyperOptLossDaily --strategy SampleStrategy -e 1000
 ```
 
-or if you want intermediate result to see
+### Why does it take a long time to run hyperopt?
 
-```bash
-for i in {1..100}; do freqtrade hyperopt -e 100; done
-```
+* Discovering a great strategy with Hyperopt takes time. Study www.freqtrade.io, the Freqtrade Documentation page, join the Freqtrade [Slack community](https://join.slack.com/t/highfrequencybot/shared_invite/zt-jaut7r4m-Y17k4x5mcQES9a9swKuxbg) - or the Freqtrade [discord community](https://discord.gg/X89cVG). While you patiently wait for the most advanced, free crypto bot in the world, to hand you a possible golden strategy specially designed just for you.
 
-### Why it is so long to run hyperopt?
+* If you wonder why it can take from 20 minutes to days to do 1000 epochs here are some answers:
 
-Finding a great Hyperopt results takes time.
-
-If you wonder why it takes a while to find great hyperopt results
-
-This answer was written during the under the release 0.15.1, when we had:
+This answer was written during the release 0.15.1, when we had:
 
 - 8 triggers
 - 9 guards: let's say we evaluate even 10 values from each
@@ -83,7 +159,14 @@ The following calculation is still very rough and not very precise
 but it will give the idea. With only these triggers and guards there is
 already 8\*10^9\*10 evaluations. A roughly total of 80 billion evals.
 Did you run 100 000 evals? Congrats, you've done roughly 1 / 100 000 th
-of the search space.
+of the search space, assuming that the bot never tests the same parameters more than once.
+
+* The time it takes to run 1000 hyperopt epochs depends on things like: The available cpu, hard-disk, ram, timeframe, timerange, indicator settings, indicator count, amount of coins that hyperopt test strategies on and the resulting trade count - which can be 650 trades in a year or 10.0000 trades depending if the strategy aims for big profits by trading rarely or for many low profit trades. 
+
+Example: 4% profit 650 times vs 0,3% profit a trade 10.000 times in a year. If we assume you set the --timerange to 365 days. 
+
+Example: 
+`freqtrade --config config.json --strategy SampleStrategy --hyperopt SampleHyperopt -e 1000 --timerange 20190601-20200601`
 
 ## Edge module
 
@@ -91,7 +174,7 @@ of the search space.
 
 The Edge module is mostly a result of brainstorming of [@mishaker](https://github.com/mishaker) and [@creslinux](https://github.com/creslinux) freqtrade team members.
 
-You can find further info on expectancy, winrate, risk management and position size in the following sources:
+You can find further info on expectancy, win rate, risk management and position size in the following sources:
 
 - https://www.tradeciety.com/ultimate-math-guide-for-traders/
 - http://www.vantharp.com/tharp-concepts/expectancy.asp
diff --git a/docs/hyperopt.md b/docs/hyperopt.md
index ef3d28188..fc7a0dd93 100644
--- a/docs/hyperopt.md
+++ b/docs/hyperopt.md
@@ -6,59 +6,121 @@ algorithms included in the `scikit-optimize` package to accomplish this. The
 search will burn all your CPU cores, make your laptop sound like a fighter jet
 and still take a long time.
 
+In general, the search for best parameters starts with a few random combinations (see [below](#reproducible-results) for more details) and then uses Bayesian search with a ML regressor algorithm (currently ExtraTreesRegressor) to quickly find a combination of parameters in the search hyperspace that minimizes the value of the [loss function](#loss-functions).
+
+Hyperopt requires historic data to be available, just as backtesting does.
+To learn how to get data for the pairs and exchange you're interested in, head over to the [Data Downloading](data-download.md) section of the documentation.
+
 !!! Bug
-    Hyperopt will crash when used with only 1 CPU Core as found out in [Issue #1133](https://github.com/freqtrade/freqtrade/issues/1133)
+    Hyperopt can crash when used with only 1 CPU Core as found out in [Issue #1133](https://github.com/freqtrade/freqtrade/issues/1133)
+
+## Install hyperopt dependencies
+
+Since Hyperopt dependencies are not needed to run the bot itself, are heavy, can not be easily built on some platforms (like Raspberry PI), they are not installed by default. Before you run Hyperopt, you need to install the corresponding dependencies, as described in this section below.
+
+!!! Note
+    Since Hyperopt is a resource intensive process, running it on a Raspberry Pi is not recommended nor supported.
+
+### Docker
+
+The docker-image includes hyperopt dependencies, no further action needed.
+
+### Easy installation script (setup.sh) / Manual installation
+
+```bash
+source .env/bin/activate
+pip install -r requirements-hyperopt.txt
+```
 
 ## Prepare Hyperopting
 
 Before we start digging into Hyperopt, we recommend you to take a look at
-an example hyperopt file located into [user_data/hyperopts/](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt.py)
+the sample hyperopt file located in [user_data/hyperopts/](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt.py).
 
-Configuring hyperopt is similar to writing your own strategy, and many tasks will be similar and a lot of code can be copied across from the strategy.
+Configuring hyperopt is similar to writing your own strategy, and many tasks will be similar.
 
-### Checklist on all tasks / possibilities in hyperopt
+!!! Tip "About this page"
+    For this page, we will be using a fictional strategy called `AwesomeStrategy` - which will be optimized using the `AwesomeHyperopt` class.
 
-Depending on the space you want to optimize, only some of the below are required.
+The simplest way to get started is to use the following, command, which will create a new hyperopt file from a template, which will be located under `user_data/hyperopts/AwesomeHyperopt.py`.
+
+``` bash
+freqtrade new-hyperopt --hyperopt AwesomeHyperopt
+```
+
+### Hyperopt checklist
+
+Checklist on all tasks / possibilities in hyperopt
+
+Depending on the space you want to optimize, only some of the below are required:
 
-* fill `populate_indicators` - probably a copy from your strategy
 * fill `buy_strategy_generator` - for buy signal optimization
-* fill `indicator_space` - for buy signal optimzation
+* fill `indicator_space` - for buy signal optimization
 * fill `sell_strategy_generator` - for sell signal optimization
-* fill `sell_indicator_space` - for sell signal optimzation
-* fill `roi_space` - for ROI optimization
-* fill `generate_roi_table` - for ROI optimization (if you need more than 3 entries)
-* fill `stoploss_space` - stoploss optimization
-* Optional but recommended
-  * copy `populate_buy_trend` from your strategy - otherwise default-strategy will be used
-  * copy `populate_sell_trend` from your strategy - otherwise default-strategy will be used
+* fill `sell_indicator_space` - for sell signal optimization
 
-### 1. Install a Custom Hyperopt File
+!!! Note
+    `populate_indicators` needs to create all indicators any of thee spaces may use, otherwise hyperopt will not work.
 
-Put your hyperopt file into the directory `user_data/hyperopts`.
+Optional in hyperopt - can also be loaded from a strategy (recommended):
 
-Let assume you want a hyperopt file `awesome_hyperopt.py`:  
-Copy the file `user_data/hyperopts/sample_hyperopt.py` into `user_data/hyperopts/awesome_hyperopt.py`
+* copy `populate_indicators` from your strategy - otherwise default-strategy will be used
+* copy `populate_buy_trend` from your strategy - otherwise default-strategy will be used
+* copy `populate_sell_trend` from your strategy - otherwise default-strategy will be used
 
-### 2. Configure your Guards and Triggers
+!!! Note
+    You always have to provide a strategy to Hyperopt, even if your custom Hyperopt class contains all methods.
+    Assuming the optional methods are not in your hyperopt file, please use `--strategy AweSomeStrategy` which contains these methods so hyperopt can use these methods instead.
+
+Rarely you may also need to override:
+
+* `roi_space` - for custom ROI optimization (if you need the ranges for the ROI parameters in the optimization hyperspace that differ from default)
+* `generate_roi_table` - for custom ROI optimization (if you need the ranges for the values in the ROI table that differ from default or the number of entries (steps) in the ROI table which differs from the default 4 steps)
+* `stoploss_space` - for custom stoploss optimization (if you need the range for the stoploss parameter in the optimization hyperspace that differs from default)
+* `trailing_space` - for custom trailing stop optimization (if you need the ranges for the trailing stop parameters in the optimization hyperspace that differ from default)
+
+!!! Tip "Quickly optimize ROI, stoploss and trailing stoploss"
+    You can quickly optimize the spaces `roi`, `stoploss` and `trailing` without changing anything (i.e. without creation of a "complete" Hyperopt class with dimensions, parameters, triggers and guards, as described in this document) from the default hyperopt template by relying on your strategy to do most of the calculations.
+
+    ```python
+    # Have a working strategy at hand.
+    freqtrade new-hyperopt --hyperopt EmptyHyperopt
+
+    freqtrade hyperopt --hyperopt EmptyHyperopt --hyperopt-loss SharpeHyperOptLossDaily --spaces roi stoploss trailing --strategy MyWorkingStrategy --config config.json -e 100
+    ```
+
+### Create a Custom Hyperopt File
+
+Let assume you want a hyperopt file `AwesomeHyperopt.py`:  
+
+``` bash
+freqtrade new-hyperopt --hyperopt AwesomeHyperopt
+```
+
+This command will create a new hyperopt file from a template, allowing you to get started quickly.
+
+### Configure your Guards and Triggers
 
 There are two places you need to change in your hyperopt file to add a new buy hyperopt for testing:
 
-- Inside `indicator_space()` - the parameters hyperopt shall be optimizing.
-- Inside `populate_buy_trend()` - applying the parameters.
+* Inside `indicator_space()` - the parameters hyperopt shall be optimizing.
+* Inside `populate_buy_trend()` - applying the parameters.
 
 There you have two different types of indicators: 1. `guards` and 2. `triggers`.
 
 1. Guards are conditions like "never buy if ADX < 10", or never buy if current price is over EMA10.
-2. Triggers are ones that actually trigger buy in specific moment, like "buy when EMA5 crosses over EMA10" or "buy when close price touches lower bollinger band".
+2. Triggers are ones that actually trigger buy in specific moment, like "buy when EMA5 crosses over EMA10" or "buy when close price touches lower Bollinger band".
 
-Hyperoptimization will, for each eval round, pick one trigger and possibly
-multiple guards. The constructed strategy will be something like
-"*buy exactly when close price touches lower bollinger band, BUT only if
+!!! Hint "Guards and Triggers"
+    Technically, there is no difference between Guards and Triggers.  
+    However, this guide will make this distinction to make it clear that signals should not be "sticking".
+    Sticking signals are signals that are active for multiple candles. This can lead into buying a signal late (right before the signal disappears - which means that the chance of success is a lot lower than right at the beginning).
+
+Hyper-optimization will, for each epoch round, pick one trigger and possibly
+multiple guards. The constructed strategy will be something like "*buy exactly when close price touches lower Bollinger band, BUT only if
 ADX > 10*".
 
-If you have updated the buy strategy, ie. changed the contents of
-`populate_buy_trend()` method you have to update the `guards` and
-`triggers` hyperopts must use.
+If you have updated the buy strategy, i.e. changed the contents of `populate_buy_trend()` method, you have to update the `guards` and `triggers` your hyperopt must use correspondingly.
 
 #### Sell optimization
 
@@ -71,10 +133,11 @@ Place the corresponding settings into the following methods
 The configuration and rules are the same than for buy signals.
 To avoid naming collisions in the search-space, please prefix all sell-spaces with `sell-`.
 
-#### Using ticker-interval as part of the Strategy
+#### Using timeframe as a part of the Strategy
 
-The Strategy exposes the ticker-interval as `self.ticker_interval`. The same value is available as class-attribute `HyperoptName.ticker_interval`.
-In the case of the linked sample-value this would be `SampleHyperOpts.ticker_interval`.
+The Strategy class exposes the timeframe value as the `self.timeframe` attribute.
+The same value is available as class-attribute `HyperoptName.timeframe`.
+In the case of the linked sample-value this would be `AwesomeHyperopt.timeframe`.
 
 ## Solving a Mystery
 
@@ -102,14 +165,14 @@ We will start by defining a search space:
 
 Above definition says: I have five parameters I want you to randomly combine
 to find the best combination. Two of them are integer values (`adx-value`
-and `rsi-value`) and I want you test in the range of values 20 to 40.
+and `rsi-value`) and I want you test in the range of values 20 to 40.  
 Then we have three category variables. First two are either `True` or `False`.
 We use these to either enable or disable the ADX and RSI guards. The last
 one we call `trigger` and use it to decide which buy trigger we want to use.
 
 So let's write the buy strategy using these values:
 
-``` python
+```python
         def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
             conditions = []
             # GUARDS AND TRENDS
@@ -127,6 +190,9 @@ So let's write the buy strategy using these values:
                         dataframe['macd'], dataframe['macdsignal']
                     ))
 
+            # Check that volume is not 0
+            conditions.append(dataframe['volume'] > 0)
+
             if conditions:
                 dataframe.loc[
                     reduce(lambda x, y: x & y, conditions),
@@ -137,87 +203,32 @@ So let's write the buy strategy using these values:
         return populate_buy_trend
 ```
 
-Hyperopting will now call this `populate_buy_trend` as many times you ask it (`epochs`)
-with different value combinations. It will then use the given historical data and make
-buys based on the buy signals generated with the above function and based on the results
-it will end with telling you which paramter combination produced the best profits.
+Hyperopt will now call `populate_buy_trend()` many times (`epochs`) with different value combinations.  
+It will use the given historical data and make buys based on the buy signals generated with the above function.  
+Based on the results, hyperopt will tell you which parameter combination produced the best results (based on the configured [loss function](#loss-functions)).
 
-The search for best parameters starts with a few random combinations and then uses a
-regressor algorithm (currently ExtraTreesRegressor) to quickly find a parameter combination
-that minimizes the value of the [loss function](#loss-functions).
-
-The above setup expects to find ADX, RSI and Bollinger Bands in the populated indicators.
-When you want to test an indicator that isn't used by the bot currently, remember to
-add it to the `populate_indicators()` method in `hyperopt.py`.
+!!! Note
+    The above setup expects to find ADX, RSI and Bollinger Bands in the populated indicators.
+    When you want to test an indicator that isn't used by the bot currently, remember to
+    add it to the `populate_indicators()` method in your strategy or hyperopt file.
 
 ## Loss-functions
 
 Each hyperparameter tuning requires a target. This is usually defined as a loss function (sometimes also called objective function), which should decrease for more desirable results, and increase for bad results.
 
-By default, FreqTrade uses a loss function, which has been with freqtrade since the beginning and optimizes mostly for short trade duration and avoiding losses.
+A loss function must be specified via the `--hyperopt-loss <Class-name>` argument (or optionally via the configuration under the `"hyperopt_loss"` key).
+This class should be in its own file within the `user_data/hyperopts/` directory.
 
-A different version this can be used by using the `--hyperopt-loss <Class-name>` argument.
-This class should be in it's own file within the `user_data/hyperopts/` directory.
+Currently, the following loss functions are builtin:
 
-Currently, the following loss functions are builtin: `SharpeHyperOptLoss` and `DefaultHyperOptLoss`.
+* `ShortTradeDurHyperOptLoss` (default legacy Freqtrade hyperoptimization loss function) - Mostly for short trade duration and avoiding losses.
+* `OnlyProfitHyperOptLoss` (which takes only amount of profit into consideration)
+* `SharpeHyperOptLoss` (optimizes Sharpe Ratio calculated on trade returns relative to standard deviation)
+* `SharpeHyperOptLossDaily` (optimizes Sharpe Ratio calculated on **daily** trade returns relative to standard deviation)
+* `SortinoHyperOptLoss` (optimizes Sortino Ratio calculated on trade returns relative to **downside** standard deviation)
+* `SortinoHyperOptLossDaily` (optimizes Sortino Ratio calculated on **daily** trade returns relative to **downside** standard deviation)
 
-### Creating and using a custom loss function
-
-To use a custom loss function class, make sure that the function `hyperopt_loss_function` is defined in your custom hyperopt loss class.
-For the sample below, you then need to add the command line parameter `--hyperopt-loss SuperDuperHyperOptLoss` to your hyperopt call so this fuction is being used.
-
-A sample of this can be found below, which is identical to the Default Hyperopt loss implementation. A full sample can be found [user_data/hyperopts/](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt_loss.py)
-
-``` python
-from freqtrade.optimize.hyperopt import IHyperOptLoss
-
-TARGET_TRADES = 600
-EXPECTED_MAX_PROFIT = 3.0
-MAX_ACCEPTED_TRADE_DURATION = 300
-
-class SuperDuperHyperOptLoss(IHyperOptLoss):
-    """
-    Defines the default loss function for hyperopt
-    """
-
-    @staticmethod
-    def hyperopt_loss_function(results: DataFrame, trade_count: int,
-                               min_date: datetime, max_date: datetime,
-                               *args, **kwargs) -> float:
-        """
-        Objective function, returns smaller number for better results
-        This is the legacy algorithm (used until now in freqtrade).
-        Weights are distributed as follows:
-        * 0.4 to trade duration
-        * 0.25: Avoiding trade loss
-        * 1.0 to total profit, compared to the expected value (`EXPECTED_MAX_PROFIT`) defined above
-        """
-        total_profit = results.profit_percent.sum()
-        trade_duration = results.trade_duration.mean()
-
-        trade_loss = 1 - 0.25 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.8)
-        profit_loss = max(0, 1 - total_profit / EXPECTED_MAX_PROFIT)
-        duration_loss = 0.4 * min(trade_duration / MAX_ACCEPTED_TRADE_DURATION, 1)
-        result = trade_loss + profit_loss + duration_loss
-        return result
-```
-
-Currently, the arguments are:
-
-* `results`: DataFrame containing the result  
-    The following columns are available in results (corresponds to the output-file of backtesting when used with `--export trades`):  
-    `pair, profit_percent, profit_abs, open_time, close_time, open_index, close_index, trade_duration, open_at_end, open_rate, close_rate, sell_reason`
-* `trade_count`: Amount of trades (identical to `len(results)`)
-* `min_date`: Start date of the hyperopting TimeFrame
-* `min_date`: End date of the hyperopting TimeFrame
-
-This function needs to return a floating point number (`float`). Smaller numbers will be interpreted as better results. The parameters and balancing for this is up to you.
-
-!!! Note
-    This function is called once per iteration - so please make sure to have this as optimized as possible to not slow hyperopt down unnecessarily.
-
-!!! Note
-    Please keep the arguments `*args` and `**kwargs` in the interface to allow us to extend this interface later.
+Creation of a custom loss function is covered in the [Advanced Hyperopt](advanced-hyperopt.md) part of the documentation.
 
 ## Execute Hyperopt
 
@@ -227,44 +238,50 @@ Because hyperopt tries a lot of combinations to find the best parameters it will
 We strongly recommend to use `screen` or `tmux` to prevent any connection loss.
 
 ```bash
-freqtrade -c config.json hyperopt --customhyperopt <hyperoptname> -e 5000 --spaces all
+freqtrade hyperopt --config config.json --hyperopt <hyperoptname> --hyperopt-loss <hyperoptlossname> --strategy <strategyname> -e 500 --spaces all
 ```
 
-Use  `<hyperoptname>` as the name of the custom hyperopt used.
+Use `<hyperoptname>` as the name of the custom hyperopt used.
 
-The `-e` flag will set how many evaluations hyperopt will do. We recommend
-running at least several thousand evaluations.
+The `-e` option will set how many evaluations hyperopt will do. Since hyperopt uses Bayesian search, running too many epochs at once may not produce greater results. Experience has shown that best results are usually not improving much after 500-1000 epochs.  
+Doing multiple runs (executions) with a few 1000 epochs and different random state will most likely produce different results.
 
-The `--spaces all` flag determines that all possible parameters should be optimized. Possibilities are listed below.
+The `--spaces all` option determines that all possible parameters should be optimized. Possibilities are listed below.
 
 !!! Note
-    By default, hyperopt will erase previous results and start from scratch. Continuation can be archived by using `--continue`.
+    Hyperopt will store hyperopt results with the timestamp of the hyperopt start time.
+    Reading commands (`hyperopt-list`, `hyperopt-show`) can use `--hyperopt-filename <filename>` to read and display older hyperopt results.
+    You can find a list of filenames with `ls -l user_data/hyperopt_results/`.
 
-!!! Warning
-    When switching parameters or changing configuration options, make sure to not use the argument `--continue` so temporary results can be removed.
+### Execute Hyperopt with different historical data source
 
-### Execute Hyperopt with Different Ticker-Data Source
+If you would like to hyperopt parameters using an alternate historical data set that
+you have on-disk, use the `--datadir PATH` option. By default, hyperopt
+uses data from directory `user_data/data`.
 
-If you would like to hyperopt parameters using an alternate ticker data that
-you have on-disk, use the `--datadir PATH` option. Default hyperopt will
-use data from directory `user_data/data`.
+### Running Hyperopt with a smaller test-set
 
-### Running Hyperopt with Smaller Testset
-
-Use the `--timerange` argument to change how much of the testset you want to use.
+Use the `--timerange` argument to change how much of the test-set you want to use.
 For example, to use one month of data, pass the following parameter to the hyperopt call:
 
 ```bash
-freqtrade hyperopt --timerange 20180401-20180501
+freqtrade hyperopt --hyperopt <hyperoptname> --strategy <strategyname> --timerange 20180401-20180501
+```
+
+### Running Hyperopt using methods from a strategy
+
+Hyperopt can reuse `populate_indicators`, `populate_buy_trend`, `populate_sell_trend` from your strategy, assuming these methods are **not** in your custom hyperopt file, and a strategy is provided.
+
+```bash
+freqtrade hyperopt --hyperopt AwesomeHyperopt --hyperopt-loss SharpeHyperOptLossDaily --strategy AwesomeStrategy
 ```
 
 ### Running Hyperopt with Smaller Search Space
 
-Use the `--spaces` argument to limit the search space used by hyperopt.
-Letting Hyperopt optimize everything is a huuuuge search space. Often it
-might make more sense to start by just searching for initial buy algorithm.
-Or maybe you just want to optimize your stoploss or roi table for that awesome
-new buy strategy you have.
+Use the `--spaces` option to limit the search space used by hyperopt.
+Letting Hyperopt optimize everything is a huuuuge search space. 
+Often it might make more sense to start by just searching for initial buy algorithm.
+Or maybe you just want to optimize your stoploss or roi table for that awesome new buy strategy you have.
 
 Legal values are:
 
@@ -273,29 +290,43 @@ Legal values are:
 * `sell`: just search for a new sell strategy
 * `roi`: just optimize the minimal profit table for your strategy
 * `stoploss`: search for the best stoploss value
+* `trailing`: search for the best trailing stop values
+* `default`: `all` except `trailing`
 * space-separated list of any of the above values for example `--spaces roi stoploss`
 
+The default Hyperopt Search Space, used when no `--space` command line option is specified, does not include the `trailing` hyperspace. We recommend you to run optimization for the `trailing` hyperspace separately, when the best parameters for other hyperspaces were found, validated and pasted into your custom strategy.
+
 ### Position stacking and disabling max market positions
 
-In some situations, you may need to run Hyperopt (and Backtesting) with the 
+In some situations, you may need to run Hyperopt (and Backtesting) with the
 `--eps`/`--enable-position-staking` and `--dmmp`/`--disable-max-market-positions` arguments.
 
 By default, hyperopt emulates the behavior of the Freqtrade Live Run/Dry Run, where only one
-open trade is allowed for every traded pair. The total number of trades open for all pairs 
+open trade is allowed for every traded pair. The total number of trades open for all pairs
 is also limited by the `max_open_trades` setting. During Hyperopt/Backtesting this may lead to
-some potential trades to be hidden (or masked) by previosly open trades.
+some potential trades to be hidden (or masked) by previously open trades.
 
 The `--eps`/`--enable-position-stacking` argument allows emulation of buying the same pair multiple times,
-while `--dmmp`/`--disable-max-market-positions` disables applying `max_open_trades` 
+while `--dmmp`/`--disable-max-market-positions` disables applying `max_open_trades`
 during Hyperopt/Backtesting (which is equal to setting `max_open_trades` to a very high
 number).
 
 !!! Note
     Dry/live runs will **NOT** use position stacking - therefore it does make sense to also validate the strategy without this as it's closer to reality.
 
-You can also enable position stacking in the configuration file by explicitly setting 
+You can also enable position stacking in the configuration file by explicitly setting
 `"position_stacking"=true`.
 
+### Reproducible results
+
+The search for optimal parameters starts with a few (currently 30) random combinations in the hyperspace of parameters, random Hyperopt epochs. These random epochs are marked with an asterisk character (`*`) in the first column in the Hyperopt output.
+
+The initial state for generation of these random values (random state) is controlled by the value of the `--random-state` command line option. You can set it to some arbitrary value of your choice to obtain reproducible results.
+
+If you have not set this value explicitly in the command line options, Hyperopt seeds the random state with some random value for you. The random state value for each Hyperopt run is shown in the log, so you can copy and paste it into the `--random-state` command line option to repeat the set of the initial random epochs used.
+
+If you have not changed anything in the command line options, configuration, timerange, Strategy and Hyperopt classes, historical data and the Loss Function -- you should obtain same hyper-optimization results with same random state value used.
+
 ## Understand the Hyperopt Result
 
 Once Hyperopt is completed you can use the result to create a new strategy.
@@ -303,8 +334,10 @@ Given the following result from hyperopt:
 
 ```
 Best result:
-   135 trades. Avg profit  0.57%. Total profit  0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins.
-with values:
+
+    44/100:    135 trades. Avg profit  0.57%. Total profit  0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367
+
+Buy hyperspace params:
 {    'adx-value': 44,
      'rsi-value': 29,
      'adx-enabled': False,
@@ -323,12 +356,11 @@ method, what those values match to.
 
 So for example you had `rsi-value: 29.0` so we would look at `rsi`-block, that translates to the following code block:
 
-``` python
+```python
 (dataframe['rsi'] < 29.0)
 ```
 
-Translating your whole hyperopt result as the new buy-signal
-would then look like:
+Translating your whole hyperopt result as the new buy-signal would then look like:
 
 ```python
 def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
@@ -341,52 +373,144 @@ def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
     return dataframe
 ```
 
+By default, hyperopt prints colorized results -- epochs with positive profit are printed in the green color. This highlighting helps you find epochs that can be interesting for later analysis. Epochs with zero total profit or with negative profits (losses) are printed in the normal color. If you do not need colorization of results (for instance, when you are redirecting hyperopt output to a file) you can switch colorization off by specifying the `--no-color` option in the command line.
+
+You can use the `--print-all` command line option if you would like to see all results in the hyperopt output, not only the best ones. When `--print-all` is used, current best results are also colorized by default -- they are printed in bold (bright) style. This can also be switched off with the `--no-color` command line option.
+
+!!! Note "Windows and color output"
+    Windows does not support color-output natively, therefore it is automatically disabled. To have color-output for hyperopt running under windows, please consider using WSL.
+
 ### Understand Hyperopt ROI results
 
-If you are optimizing ROI, you're result will look as follows and include a ROI table.
+If you are optimizing ROI (i.e. if optimization search-space contains 'all', 'default' or 'roi'), your result will look as follows and include a ROI table:
 
 ```
 Best result:
-   135 trades. Avg profit  0.57%. Total profit  0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins.
-with values:
-{   'adx-value': 44,
-    'rsi-value': 29,
-    'adx-enabled': false,
-    'rsi-enabled': True,
-    'trigger': 'bb_lower',
-    'roi_t1': 40,
-    'roi_t2': 57,
-    'roi_t3': 21,
-    'roi_p1': 0.03634636907306948,
-    'roi_p2': 0.055237357937802885,
-    'roi_p3': 0.015163796015548354,
-    'stoploss': -0.37996664668703606
-}
+
+    44/100:    135 trades. Avg profit  0.57%. Total profit  0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367
+
 ROI table:
-{   0: 0.10674752302642071,
-    21: 0.09158372701087236,
-    78: 0.03634636907306948,
+{   0: 0.10674,
+    21: 0.09158,
+    78: 0.03634,
     118: 0}
 ```
 
-This would translate to the following ROI table:
+In order to use this best ROI table found by Hyperopt in backtesting and for live trades/dry-run, copy-paste it as the value of the `minimal_roi` attribute of your custom strategy:
 
-``` python
- minimal_roi = {
-        "118": 0,
-        "78": 0.0363463,
-        "21": 0.0915,
-        "0": 0.106
+```
+    # Minimal ROI designed for the strategy.
+    # This attribute will be overridden if the config file contains "minimal_roi"
+    minimal_roi = {
+        0: 0.10674,
+        21: 0.09158,
+        78: 0.03634,
+        118: 0
     }
 ```
 
-### Validate backtesting results
+As stated in the comment, you can also use it as the value of the `minimal_roi` setting in the configuration file.
+
+#### Default ROI Search Space
+
+If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace for you -- it's the hyperspace of components for the ROI tables. By default, each ROI table generated by the Freqtrade consists of 4 rows (steps). Hyperopt implements adaptive ranges for ROI tables with ranges for values in the ROI steps that depend on the timeframe used. By default the values vary in the following ranges (for some of the most used timeframes, values are rounded to 5 digits after the decimal point):
+
+| # step | 1m     |                   | 5m       |             | 1h         |                   | 1d           |                   |
+| ------ | ------ | ----------------- | -------- | ----------- | ---------- | ----------------- | ------------ | ----------------- |
+| 1      | 0      | 0.01161...0.11992 | 0        | 0.03...0.31 | 0          | 0.06883...0.71124 | 0            | 0.12178...1.25835 |
+| 2      | 2...8  | 0.00774...0.04255 | 10...40  | 0.02...0.11 | 120...480  | 0.04589...0.25238 | 2880...11520 | 0.08118...0.44651 |
+| 3      | 4...20 | 0.00387...0.01547 | 20...100 | 0.01...0.04 | 240...1200 | 0.02294...0.09177 | 5760...28800 | 0.04059...0.16237 |
+| 4      | 6...44 | 0.0               | 30...220 | 0.0         | 360...2640 | 0.0               | 8640...63360 | 0.0               |
+
+These ranges should be sufficient in most cases. The minutes in the steps (ROI dict keys) are scaled linearly depending on the timeframe used. The ROI values in the steps (ROI dict values) are scaled logarithmically depending on the timeframe used.
+
+If you have the `generate_roi_table()` and `roi_space()` methods in your custom hyperopt file, remove them in order to utilize these adaptive ROI tables and the ROI hyperoptimization space generated by Freqtrade by default.
+
+Override the `roi_space()` method if you need components of the ROI tables to vary in other ranges. Override the `generate_roi_table()` and `roi_space()` methods and implement your own custom approach for generation of the ROI tables during hyperoptimization if you need a different structure of the ROI tables or other amount of rows (steps). 
+
+A sample for these methods can be found in [sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py).
+
+### Understand Hyperopt Stoploss results
+
+If you are optimizing stoploss values (i.e. if optimization search-space contains 'all', 'default' or 'stoploss'), your result will look as follows and include stoploss:
+
+```
+Best result:
+
+    44/100:    135 trades. Avg profit  0.57%. Total profit  0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367
+
+Buy hyperspace params:
+{   'adx-value': 44,
+    'rsi-value': 29,
+    'adx-enabled': False,
+    'rsi-enabled': True,
+    'trigger': 'bb_lower'}
+Stoploss: -0.27996
+```
+
+In order to use this best stoploss value found by Hyperopt in backtesting and for live trades/dry-run, copy-paste it as the value of the `stoploss` attribute of your custom strategy:
+
+``` python
+    # Optimal stoploss designed for the strategy
+    # This attribute will be overridden if the config file contains "stoploss"
+    stoploss = -0.27996
+```
+
+As stated in the comment, you can also use it as the value of the `stoploss` setting in the configuration file.
+
+#### Default Stoploss Search Space
+
+If you are optimizing stoploss values, Freqtrade creates the 'stoploss' optimization hyperspace for you. By default, the stoploss values in that hyperspace vary in the range -0.35...-0.02, which is sufficient in most cases.
+
+If you have the `stoploss_space()` method in your custom hyperopt file, remove it in order to utilize Stoploss hyperoptimization space generated by Freqtrade by default.
+
+Override the `stoploss_space()` method and define the desired range in it if you need stoploss values to vary in other range during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py).
+
+### Understand Hyperopt Trailing Stop results
+
+If you are optimizing trailing stop values (i.e. if optimization search-space contains 'all' or 'trailing'), your result will look as follows and include trailing stop parameters:
+
+```
+Best result:
+
+    45/100:    606 trades. Avg profit  1.04%. Total profit  0.31555614 BTC ( 630.48Σ%). Avg duration 150.3 mins. Objective: -1.10161
+
+Trailing stop:
+{   'trailing_only_offset_is_reached': True,
+    'trailing_stop': True,
+    'trailing_stop_positive': 0.02001,
+    'trailing_stop_positive_offset': 0.06038}
+```
+
+In order to use these best trailing stop parameters found by Hyperopt in backtesting and for live trades/dry-run, copy-paste them as the values of the corresponding attributes of your custom strategy:
+
+``` python
+    # Trailing stop
+    # These attributes will be overridden if the config file contains corresponding values.
+    trailing_stop = True
+    trailing_stop_positive = 0.02001
+    trailing_stop_positive_offset = 0.06038
+    trailing_only_offset_is_reached = True
+```
+
+As stated in the comment, you can also use it as the values of the corresponding settings in the configuration file.
+
+#### Default Trailing Stop Search Space
+
+If you are optimizing trailing stop values, Freqtrade creates the 'trailing' optimization hyperspace for you. By default, the `trailing_stop` parameter is always set to True in that hyperspace, the value of the `trailing_only_offset_is_reached` vary between True and False, the values of the `trailing_stop_positive` and `trailing_stop_positive_offset` parameters vary in the ranges 0.02...0.35 and 0.01...0.1 correspondingly, which is sufficient in most cases.
+
+Override the `trailing_space()` method and define the desired range in it if you need values of the trailing stop parameters to vary in other ranges during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py).
+
+## Show details of Hyperopt results
+
+After you run Hyperopt for the desired amount of epochs, you can later list all results for analysis, select only best or profitable once, and show the details for any of the epochs previously evaluated. This can be done with the `hyperopt-list` and `hyperopt-show` sub-commands. The usage of these sub-commands is described in the [Utils](utils.md#list-hyperopt-results) chapter.
+
+## Validate backtesting results
 
 Once the optimized strategy has been implemented into your strategy, you should backtest this strategy to make sure everything is working as expected.
 
-To achieve same results (number of trades, their durations, profit, etc.) than during Hyperopt, please use same set of arguments `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
+To achieve same results (number of trades, their durations, profit, etc.) than during Hyperopt, please use same configuration and parameters (timerange, timeframe, ...) used for hyperopt `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
 
-## Next Step
-
-Now you have a perfect bot and want to control it from Telegram. Your
-next step is to learn the [Telegram usage](telegram-usage.md).
+Should results don't match, please double-check to make sure you transferred all conditions correctly.
+Pay special care to the stoploss (and trailing stoploss) parameters, as these are often set in configuration files, which override changes to the strategy.
+You should also carefully review the log of your backtest to ensure that there were no parameters inadvertently set by the configuration (like `stoploss` or `trailing_stop`).
diff --git a/docs/includes/pairlists.md b/docs/includes/pairlists.md
new file mode 100644
index 000000000..e6a9fc1a8
--- /dev/null
+++ b/docs/includes/pairlists.md
@@ -0,0 +1,142 @@
+## Pairlists and Pairlist Handlers
+
+Pairlist Handlers define the list of pairs (pairlist) that the bot should trade. They are configured in the `pairlists` section of the configuration settings.
+
+In your configuration, you can use Static Pairlist (defined by the [`StaticPairList`](#static-pair-list) Pairlist Handler) and Dynamic Pairlist (defined by the [`VolumePairList`](#volume-pair-list) Pairlist Handler).
+
+Additionally, [`AgeFilter`](#agefilter), [`PrecisionFilter`](#precisionfilter), [`PriceFilter`](#pricefilter), [`ShuffleFilter`](#shufflefilter) and [`SpreadFilter`](#spreadfilter) act as Pairlist Filters, removing certain pairs and/or moving their positions in the pairlist.
+
+If multiple Pairlist Handlers are used, they are chained and a combination of all Pairlist Handlers forms the resulting pairlist the bot uses for trading and backtesting. Pairlist Handlers are executed in the sequence they are configured. You should always configure either `StaticPairList` or `VolumePairList` as the starting Pairlist Handler.
+
+Inactive markets are always removed from the resulting pairlist. Explicitly blacklisted pairs (those in the `pair_blacklist` configuration setting) are also always removed from the resulting pairlist.
+
+### Available Pairlist Handlers
+
+* [`StaticPairList`](#static-pair-list) (default, if not configured differently)
+* [`VolumePairList`](#volume-pair-list)
+* [`AgeFilter`](#agefilter)
+* [`PrecisionFilter`](#precisionfilter)
+* [`PriceFilter`](#pricefilter)
+* [`ShuffleFilter`](#shufflefilter)
+* [`SpreadFilter`](#spreadfilter)
+
+!!! Tip "Testing pairlists"
+    Pairlist configurations can be quite tricky to get right. Best use the [`test-pairlist`](utils.md#test-pairlist) utility sub-command to test your configuration quickly.
+
+#### Static Pair List
+
+By default, the `StaticPairList` method is used, which uses a statically defined pair whitelist from the configuration.
+
+It uses configuration from `exchange.pair_whitelist` and `exchange.pair_blacklist`.
+
+```json
+"pairlists": [
+    {"method": "StaticPairList"}
+    ],
+```
+
+By default, only currently enabled pairs are allowed.
+To skip pair validation against active markets, set `"allow_inactive": true` within the `StaticPairList` configuration.
+This can be useful for backtesting expired pairs (like quarterly spot-markets).
+This option must be configured along with `exchange.skip_pair_validation` in the exchange configuration.
+
+#### Volume Pair List
+
+`VolumePairList` employs sorting/filtering of pairs by their trading volume. It selects `number_assets` top pairs with sorting based on the `sort_key` (which can only be `quoteVolume`).
+
+When used in the chain of Pairlist Handlers in a non-leading position (after StaticPairList and other Pairlist Filters), `VolumePairList` considers outputs of previous Pairlist Handlers, adding its sorting/selection of the pairs by the trading volume.
+
+When used on the leading position of the chain of Pairlist Handlers, it does not consider `pair_whitelist` configuration setting, but selects the top assets from all available markets (with matching stake-currency) on the exchange.
+
+The `refresh_period` setting allows to define the period (in seconds), at which the pairlist will be refreshed. Defaults to 1800s (30 minutes).
+
+`VolumePairList` is based on the ticker data from exchange, as reported by the ccxt library:
+
+* The `quoteVolume` is the amount of quote (stake) currency traded (bought or sold) in last 24 hours.
+
+```json
+"pairlists": [{
+        "method": "VolumePairList",
+        "number_assets": 20,
+        "sort_key": "quoteVolume",
+        "refresh_period": 1800,
+}],
+```
+
+#### AgeFilter
+
+Removes pairs that have been listed on the exchange for less than `min_days_listed` days (defaults to `10`).
+
+When pairs are first listed on an exchange they can suffer huge price drops and volatility
+in the first few days while the pair goes through its price-discovery period. Bots can often
+be caught out buying before the pair has finished dropping in price.
+
+This filter allows freqtrade to ignore pairs until they have been listed for at least `min_days_listed` days.
+
+#### PrecisionFilter
+
+Filters low-value coins which would not allow setting stoplosses.
+
+#### PriceFilter
+
+The `PriceFilter` allows filtering of pairs by price. Currently the following price filters are supported:
+
+* `min_price`
+* `max_price`
+* `low_price_ratio`
+
+The `min_price` setting removes pairs where the price is below the specified price. This is useful if you wish to avoid trading very low-priced pairs.
+This option is disabled by default, and will only apply if set to > 0.
+
+The `max_price` setting removes pairs where the price is above the specified price. This is useful if you wish to trade only low-priced pairs.
+This option is disabled by default, and will only apply if set to > 0.
+
+The `low_price_ratio` setting removes pairs where a raise of 1 price unit (pip) is above the `low_price_ratio` ratio.
+This option is disabled by default, and will only apply if set to > 0.
+
+For `PriceFiler` at least one of its `min_price`, `max_price` or `low_price_ratio` settings must be applied.
+
+Calculation example:
+
+Min price precision for SHITCOIN/BTC is 8 decimals. If its price is 0.00000011 - one price step above would be 0.00000012, which is ~9% higher than the previous price value. You may filter out this pair by using PriceFilter with `low_price_ratio` set to 0.09 (9%) or with `min_price` set to 0.00000011, correspondingly.
+
+!!! Warning "Low priced pairs"
+    Low priced pairs with high "1 pip movements" are dangerous since they are often illiquid and it may also be impossible to place the desired stoploss, which can often result in high losses since price needs to be rounded to the next tradable price - so instead of having a stoploss of -5%, you could end up with a stoploss of -9% simply due to price rounding.
+
+#### ShuffleFilter
+
+Shuffles (randomizes) pairs in the pairlist. It can be used for preventing the bot from trading some of the pairs more frequently then others when you want all pairs be treated with the same priority.
+
+!!! Tip
+    You may set the `seed` value for this Pairlist to obtain reproducible results, which can be useful for repeated backtesting sessions. If `seed` is not set, the pairs are shuffled in the non-repeatable random order.
+
+#### SpreadFilter
+
+Removes pairs that have a difference between asks and bids above the specified ratio, `max_spread_ratio` (defaults to `0.005`).
+
+Example:
+
+If `DOGE/BTC` maximum bid is 0.00000026 and minimum ask is 0.00000027, the ratio is calculated as: `1 - bid/ask ~= 0.037` which is `> 0.005` and this pair will be filtered out.
+
+### Full example of Pairlist Handlers
+
+The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets, sorting pairs by `quoteVolume` and applies both [`PrecisionFilter`](#precisionfilter) and [`PriceFilter`](#price-filter), filtering all assets where 1 price unit is > 1%. Then the `SpreadFilter` is applied and pairs are finally shuffled with the random seed set to some predefined value.
+
+```json
+"exchange": {
+    "pair_whitelist": [],
+    "pair_blacklist": ["BNB/BTC"]
+},
+"pairlists": [
+    {
+        "method": "VolumePairList",
+        "number_assets": 20,
+        "sort_key": "quoteVolume",
+    },
+    {"method": "AgeFilter", "min_days_listed": 10},
+    {"method": "PrecisionFilter"},
+    {"method": "PriceFilter", "low_price_ratio": 0.01},
+    {"method": "SpreadFilter", "max_spread_ratio": 0.005},
+    {"method": "ShuffleFilter", "seed": 42}
+    ],
+```
diff --git a/docs/index.md b/docs/index.md
index 63d6be75e..f63aeb6b8 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -1,5 +1,5 @@
 # Freqtrade
-[![Build Status](https://travis-ci.org/freqtrade/freqtrade.svg?branch=develop)](https://travis-ci.org/freqtrade/freqtrade)
+[![Freqtrade CI](https://github.com/freqtrade/freqtrade/workflows/Freqtrade%20CI/badge.svg)](https://github.com/freqtrade/freqtrade/actions/)
 [![Coverage Status](https://coveralls.io/repos/github/freqtrade/freqtrade/badge.svg?branch=develop&service=github)](https://coveralls.io/github/freqtrade/freqtrade?branch=develop)
 [![Maintainability](https://api.codeclimate.com/v1/badges/5737e6d668200b7518ff/maintainability)](https://codeclimate.com/github/freqtrade/freqtrade/maintainability)
 
@@ -8,11 +8,13 @@
 <!-- Place this tag where you want the button to render. -->
 <a class="github-button" href="https://github.com/freqtrade/freqtrade/fork" data-icon="octicon-repo-forked" data-size="large" aria-label="Fork freqtrade/freqtrade on GitHub">Fork</a>
 <!-- Place this tag where you want the button to render. -->
-<a class="github-button" href="https://github.com/freqtrade/freqtrade/archive/master.zip" data-icon="octicon-cloud-download" data-size="large" aria-label="Download freqtrade/freqtrade on GitHub">Download</a>
+<a class="github-button" href="https://github.com/freqtrade/freqtrade/archive/stable.zip" data-icon="octicon-cloud-download" data-size="large" aria-label="Download freqtrade/freqtrade on GitHub">Download</a>
 <!-- Place this tag where you want the button to render. -->
 <a class="github-button" href="https://github.com/freqtrade" data-size="large" aria-label="Follow @freqtrade on GitHub">Follow @freqtrade</a>
+
 ## Introduction
-Freqtrade is a cryptocurrency trading bot written in Python.
+
+Freqtrade is a crypto-currency algorithmic trading software developed in python (3.6+) and supported on Windows, macOS and Linux.
 
 !!! Danger "DISCLAIMER"
     This software is for educational purposes only. Do not risk money which you are afraid to lose. USE THE SOFTWARE AT YOUR OWN RISK. THE AUTHORS AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR TRADING RESULTS.
@@ -23,28 +25,21 @@ Freqtrade is a cryptocurrency trading bot written in Python.
 
 ## Features
 
- - Based on Python 3.6+: For botting on any operating system — Windows, macOS and Linux.
- - Persistence: Persistence is achieved through sqlite database.
- - Dry-run mode: Run the bot without playing money.
- - Backtesting: Run a simulation of your buy/sell strategy with historical data.
- - Strategy Optimization by machine learning: Use machine learning to optimize your buy/sell strategy parameters with real exchange data.
- - Edge position sizing: Calculate your win rate, risk reward ratio, the best stoploss and adjust your position size before taking a position for each specific market.
- - Whitelist crypto-currencies: Select which crypto-currency you want to trade or use dynamic whitelists based on market (pair) trade volume.
- - Blacklist crypto-currencies: Select which crypto-currency you want to avoid.
- - Manageable via Telegram or REST APi: Manage the bot with Telegram or via the builtin REST API.
- - Display profit/loss in fiat: Display your profit/loss in any of 33 fiat currencies supported.
- - Daily summary of profit/loss: Receive the daily summary of your profit/loss.
- - Performance status report: Receive the performance status of your current trades.
+- Develop your Strategy: Write your strategy in python, using [pandas](https://pandas.pydata.org/). Example strategies to inspire you are available in the [strategy repository](https://github.com/freqtrade/freqtrade-strategies).
+- Download market data: Download historical data of the exchange and the markets your may want to trade with.
+- Backtest: Test your strategy on downloaded historical data.
+- Optimize: Find the best parameters for your strategy using hyperoptimization which employs machining learning methods. You can optimize buy, sell, take profit (ROI), stop-loss and trailing stop-loss parameters for your strategy.
+- Select markets: Create your static list or use an automatic one based on top traded volumes and/or prices (not available during backtesting). You can also explicitly blacklist markets you don't want to trade.
+- Run: Test your strategy with simulated money (Dry-Run mode) or deploy it with real money (Live-Trade mode).
+- Run using Edge (optional module): The concept is to find the best historical [trade expectancy](edge.md#expectancy) by markets based on variation of the stop-loss and then allow/reject markets to trade. The sizing of the trade is based on a risk of a percentage of your capital.
+- Control/Monitor: Use Telegram or a REST API (start/stop the bot, show profit/loss, daily summary, current open trades results, etc.).
+- Analyse: Further analysis can be performed on either Backtesting data or Freqtrade trading history (SQL database), including automated standard plots, and methods to load the data into [interactive environments](data-analysis.md).
 
 ## Requirements
 
-### Up to date clock
-
-The clock on the system running the bot must be accurate, synchronized to a NTP server frequently enough to avoid problems with communication to the exchanges.
-
 ### Hardware requirements
 
-To run this bot we recommend you a cloud instance with a minimum of:
+To run this bot we recommend you a linux cloud instance with a minimum of:
 
 - 2GB RAM
 - 1GB disk space
@@ -52,20 +47,26 @@ To run this bot we recommend you a cloud instance with a minimum of:
 
 ### Software requirements
 
+- Docker (Recommended)
+
+Alternatively
+
 - Python 3.6.x
 - pip (pip3)
 - git
 - TA-Lib
 - virtualenv (Recommended)
-- Docker (Recommended)
 
 ## Support
 
-Help / Slack
-For any questions not covered by the documentation or for further information about the bot, we encourage you to join our Slack channel.
+### Help / Discord / Slack
 
-Click [here](https://join.slack.com/t/highfrequencybot/shared_invite/enQtNjU5ODcwNjI1MDU3LWEyODBiNzkzNzcyNzU0MWYyYzE5NjIyOTQxMzBmMGUxOTIzM2YyN2Y4NWY1YTEwZDgwYTRmMzE2NmM5ZmY2MTg) to join Slack channel.
+For any questions not covered by the documentation or for further information about the bot, or to simply engage with like-minded individuals, we encourage you to join our slack channel.
+
+Please check out our [discord server](https://discord.gg/MA9v74M).
+
+You can also join our [Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/zt-jaut7r4m-Y17k4x5mcQES9a9swKuxbg).
 
 ## Ready to try?
 
-Begin by reading our installation guide [here](installation).
+Begin by reading our installation guide [for docker](docker_quickstart.md) (recommended), or for [installation without docker](installation.md).
diff --git a/docs/javascripts/config.js b/docs/javascripts/config.js
new file mode 100644
index 000000000..95d619efc
--- /dev/null
+++ b/docs/javascripts/config.js
@@ -0,0 +1,12 @@
+window.MathJax = {
+  tex: {
+    inlineMath: [["\\(", "\\)"]],
+    displayMath: [["\\[", "\\]"]],
+    processEscapes: true,
+    processEnvironments: true
+  },
+  options: {
+    ignoreHtmlClass: ".*|",
+    processHtmlClass: "arithmatex"
+  }
+};
\ No newline at end of file
diff --git a/docs/partials/header.html b/docs/partials/header.html
index 84c254b5a..32202bccc 100644
--- a/docs/partials/header.html
+++ b/docs/partials/header.html
@@ -49,4 +49,6 @@
     </nav>
     <!-- Place this tag in your head or just before your close body tag. -->
     <script async defer src="https://buttons.github.io/buttons.js"></script>
-</header>
\ No newline at end of file
+    <script src="https://code.jquery.com/jquery-3.4.1.min.js"
+        integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
+</header>
diff --git a/docs/plotting.md b/docs/plotting.md
index b8e041d61..09eb6ddb5 100644
--- a/docs/plotting.md
+++ b/docs/plotting.md
@@ -2,9 +2,9 @@
 
 This page explains how to plot prices, indicators and profits.
 
-## Installation
+## Installation / Setup
 
-Plotting scripts use Plotly library. Install/upgrade it with:
+Plotting modules use the Plotly library. You can install / upgrade this by running the following command:
 
 ``` bash
 pip install -U -r requirements-plot.txt
@@ -12,98 +12,288 @@ pip install -U -r requirements-plot.txt
 
 ## Plot price and indicators
 
-Usage for the price plotter:
+The `freqtrade plot-dataframe` subcommand shows an interactive graph with three subplots:
 
-``` bash
-python3 script/plot_dataframe.py [-h] [-p pairs] [--live]
+* Main plot with candlestics and indicators following price (sma/ema)
+* Volume bars
+* Additional indicators as specified by `--indicators2`
+
+![plot-dataframe](assets/plot-dataframe.png)
+
+Possible arguments:
+
+```
+usage: freqtrade plot-dataframe [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                                [-d PATH] [--userdir PATH] [-s NAME]
+                                [--strategy-path PATH] [-p PAIRS [PAIRS ...]]
+                                [--indicators1 INDICATORS1 [INDICATORS1 ...]]
+                                [--indicators2 INDICATORS2 [INDICATORS2 ...]]
+                                [--plot-limit INT] [--db-url PATH]
+                                [--trade-source {DB,file}] [--export EXPORT]
+                                [--export-filename PATH]
+                                [--timerange TIMERANGE] [-i TIMEFRAME]
+                                [--no-trades]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
+                        Show profits for only these pairs. Pairs are space-
+                        separated.
+  --indicators1 INDICATORS1 [INDICATORS1 ...]
+                        Set indicators from your strategy you want in the
+                        first row of the graph. Space-separated list. Example:
+                        `ema3 ema5`. Default: `['sma', 'ema3', 'ema5']`.
+  --indicators2 INDICATORS2 [INDICATORS2 ...]
+                        Set indicators from your strategy you want in the
+                        third row of the graph. Space-separated list. Example:
+                        `fastd fastk`. Default: `['macd', 'macdsignal']`.
+  --plot-limit INT      Specify tick limit for plotting. Notice: too high
+                        values cause huge files. Default: 750.
+  --db-url PATH         Override trades database URL, this is useful in custom
+                        deployments (default: `sqlite:///tradesv3.sqlite` for
+                        Live Run mode, `sqlite:///tradesv3.dryrun.sqlite` for
+                        Dry Run).
+  --trade-source {DB,file}
+                        Specify the source for trades (Can be DB or file
+                        (backtest file)) Default: file
+  --export EXPORT       Export backtest results, argument are: trades.
+                        Example: `--export=trades`
+  --export-filename PATH
+                        Save backtest results to the file with this filename.
+                        Requires `--export` to be set as well. Example:
+                        `--export-filename=user_data/backtest_results/backtest
+                        _today.json`
+  --timerange TIMERANGE
+                        Specify what timerange of data to use.
+  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
+                        Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
+                        `1d`).
+  --no-trades           Skip using trades from backtesting file and DB.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+Strategy arguments:
+  -s NAME, --strategy NAME
+                        Specify strategy class name which will be used by the
+                        bot.
+  --strategy-path PATH  Specify additional strategy lookup path.
 ```
 
-Example
+Example:
 
 ``` bash
-python3 scripts/plot_dataframe.py -p BTC/ETH
+freqtrade plot-dataframe -p BTC/ETH
 ```
 
-The `-p` pairs argument can be used to specify pairs you would like to plot.
+The `-p/--pairs` argument can be used to specify pairs you would like to plot.
+
+!!! Note
+    The `freqtrade plot-dataframe` subcommand generates one plot-file per pair.
 
 Specify custom indicators.
 Use `--indicators1` for the main plot and `--indicators2` for the subplot below (if values are in a different range than prices).
 
+!!! Tip
+    You will almost certainly want to specify a custom strategy! This can be done by adding `-s Classname` / `--strategy ClassName` to the command.
+
 ``` bash
-python3 scripts/plot_dataframe.py -p BTC/ETH --indicators1 sma,ema --indicators2 macd
+freqtrade plot-dataframe --strategy AwesomeStrategy -p BTC/ETH --indicators1 sma ema --indicators2 macd
 ```
 
-### Advanced use
+### Further usage examples
 
-To plot multiple pairs, separate them with a comma:
+To plot multiple pairs, separate them with a space:
 
 ``` bash
-python3 scripts/plot_dataframe.py -p BTC/ETH,XRP/ETH
+freqtrade plot-dataframe --strategy AwesomeStrategy -p BTC/ETH XRP/ETH
 ```
 
-To plot the current live price use the `--live` flag:
+To plot a timerange (to zoom in)
 
 ``` bash
-python3 scripts/plot_dataframe.py -p BTC/ETH --live
+freqtrade plot-dataframe --strategy AwesomeStrategy -p BTC/ETH --timerange=20180801-20180805
 ```
 
-To plot a timerange (to zoom in):
+To plot trades stored in a database use `--db-url` in combination with `--trade-source DB`:
 
 ``` bash
-python3 scripts/plot_dataframe.py -p BTC/ETH --timerange=100-200
-```
-
-Timerange doesn't work with live data.
-
-To plot trades stored in a database use `--db-url` argument:
-
-``` bash
-python3 scripts/plot_dataframe.py --db-url sqlite:///tradesv3.dry_run.sqlite -p BTC/ETH --trade-source DB
+freqtrade plot-dataframe --strategy AwesomeStrategy --db-url sqlite:///tradesv3.dry_run.sqlite -p BTC/ETH --trade-source DB
 ```
 
 To plot trades from a backtesting result, use `--export-filename <filename>`
 
 ``` bash
-python3 scripts/plot_dataframe.py --export-filename user_data/backtest_data/backtest-result.json -p BTC/ETH
+freqtrade plot-dataframe --strategy AwesomeStrategy --export-filename user_data/backtest_results/backtest-result.json -p BTC/ETH
 ```
 
-To plot a custom strategy the strategy should have first be backtested.
-The results may then be plotted with the -s argument:
+### Plot dataframe basics
 
-``` bash
-python3 scripts/plot_dataframe.py -s Strategy_Name -p BTC/ETH --datadir user_data/data/<exchange_name>/
+![plot-dataframe2](assets/plot-dataframe2.png)
+
+The `plot-dataframe` subcommand requires backtesting data, a strategy and either a backtesting-results file or a database, containing trades corresponding to the strategy.
+
+The resulting plot will have the following elements:
+
+* Green triangles: Buy signals from the strategy. (Note: not every buy signal generates a trade, compare to cyan circles.)
+* Red triangles: Sell signals from the strategy. (Also, not every sell signal terminates a trade, compare to red and green squares.)
+* Cyan circles: Trade entry points.
+* Red squares: Trade exit points for trades with loss or 0% profit.
+* Green squares: Trade exit points for profitable trades.
+* Indicators with values corresponding to the candle scale (e.g. SMA/EMA), as specified with `--indicators1`.
+* Volume (bar chart at the bottom of the main chart).
+* Indicators with values in different scales (e.g. MACD, RSI) below the volume bars, as specified with `--indicators2`.
+
+!!! Note "Bollinger Bands"
+    Bollinger bands are automatically added to the plot if the columns `bb_lowerband` and `bb_upperband` exist, and are painted as a light blue area spanning from the lower band to the upper band.
+
+#### Advanced plot configuration
+
+An advanced plot configuration can be specified in the strategy in the `plot_config` parameter.
+
+Additional features when using plot_config include:
+
+* Specify colors per indicator
+* Specify additional subplots
+
+The sample plot configuration below specifies fixed colors for the indicators. Otherwise consecutive plots may produce different colorschemes each time, making comparisons difficult.
+It also allows multiple subplots to display both MACD and RSI at the same time.
+
+Sample configuration with inline comments explaining the process:
+
+``` python
+    plot_config = {
+        'main_plot': {
+            # Configuration for main plot indicators.
+            # Specifies `ema10` to be red, and `ema50` to be a shade of gray
+            'ema10': {'color': 'red'},
+            'ema50': {'color': '#CCCCCC'},
+            # By omitting color, a random color is selected.
+            'sar': {},
+        },
+        'subplots': {
+            # Create subplot MACD
+            "MACD": {
+                'macd': {'color': 'blue'},
+                'macdsignal': {'color': 'orange'},
+            },
+            # Additional subplot RSI
+            "RSI": {
+                'rsi': {'color': 'red'},
+            }
+        }
+    }
 ```
 
+!!! Note
+    The above configuration assumes that `ema10`, `ema50`, `macd`, `macdsignal` and `rsi` are columns in the DataFrame created by the strategy.
+
 ## Plot profit
 
-The profit plotter shows a picture with three plots:
+![plot-profit](assets/plot-profit.png)
 
-1) Average closing price for all pairs
-2) The summarized profit made by backtesting.
-   Note that this is not the real-world profit, but
-   more of an estimate.
-3) Each pair individually profit
+The `plot-profit` subcommand shows an interactive graph with three plots:
 
-The first graph is good to get a grip of how the overall market
-progresses.
+* Average closing price for all pairs.
+* The summarized profit made by backtesting.
+Note that this is not the real-world profit, but more of an estimate.
+* Profit for each individual pair.
 
-The second graph will show how your algorithm works or doesn't.
-Perhaps you want an algorithm that steadily makes small profits,
-or one that acts less seldom, but makes big swings.
+The first graph is good to get a grip of how the overall market progresses.
 
-The third graph can be useful to spot outliers, events in pairs
-that makes profit spikes.
+The second graph will show if your algorithm works or doesn't.
+Perhaps you want an algorithm that steadily makes small profits, or one that acts less often, but makes big swings.
+This graph will also highlight the start (and end) of the Max drawdown period.
 
-Usage for the profit plotter:
+The third graph can be useful to spot outliers, events in pairs that cause profit spikes.
 
-``` bash
-python3 script/plot_profit.py [-h] [-p pair] [--datadir directory] [--ticker_interval num]
+Possible options for the `freqtrade plot-profit` subcommand:
+
+```
+usage: freqtrade plot-profit [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                             [-d PATH] [--userdir PATH] [-s NAME]
+                             [--strategy-path PATH] [-p PAIRS [PAIRS ...]]
+                             [--timerange TIMERANGE] [--export EXPORT]
+                             [--export-filename PATH] [--db-url PATH]
+                             [--trade-source {DB,file}] [-i TIMEFRAME]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
+                        Show profits for only these pairs. Pairs are space-
+                        separated.
+  --timerange TIMERANGE
+                        Specify what timerange of data to use.
+  --export EXPORT       Export backtest results, argument are: trades.
+                        Example: `--export=trades`
+  --export-filename PATH
+                        Save backtest results to the file with this filename.
+                        Requires `--export` to be set as well. Example:
+                        `--export-filename=user_data/backtest_results/backtest
+                        _today.json`
+  --db-url PATH         Override trades database URL, this is useful in custom
+                        deployments (default: `sqlite:///tradesv3.sqlite` for
+                        Live Run mode, `sqlite:///tradesv3.dryrun.sqlite` for
+                        Dry Run).
+  --trade-source {DB,file}
+                        Specify the source for trades (Can be DB or file
+                        (backtest file)) Default: file
+  -i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
+                        Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
+                        `1d`).
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+Strategy arguments:
+  -s NAME, --strategy NAME
+                        Specify strategy class name which will be used by the
+                        bot.
+  --strategy-path PATH  Specify additional strategy lookup path.
 ```
 
-The `-p` pair argument, can be used to plot a single pair
+The `-p/--pairs`  argument, can be used to limit the pairs that are considered for this calculation.
 
-Example
+Examples:
+
+Use custom backtest-export file
 
 ``` bash
-python3 scripts/plot_profit.py --datadir ../freqtrade/freqtrade/tests/testdata-20171221/ -p LTC/BTC
+freqtrade plot-profit  -p LTC/BTC --export-filename user_data/backtest_results/backtest-result.json
+```
+
+Use custom database
+
+``` bash
+freqtrade plot-profit  -p LTC/BTC --db-url sqlite:///tradesv3.sqlite --trade-source DB
+```
+
+``` bash
+freqtrade --datadir user_data/data/binance_save/ plot-profit -p LTC/BTC
 ```
diff --git a/docs/requirements-docs.txt b/docs/requirements-docs.txt
index c4d8c2cae..87bc6dfdd 100644
--- a/docs/requirements-docs.txt
+++ b/docs/requirements-docs.txt
@@ -1 +1,3 @@
-mkdocs-material==3.1.0
\ No newline at end of file
+mkdocs-material==6.1.6
+mdx_truly_sane_lists==1.2
+pymdown-extensions==8.0.1
diff --git a/docs/rest-api.md b/docs/rest-api.md
index afecc1d80..7726ab875 100644
--- a/docs/rest-api.md
+++ b/docs/rest-api.md
@@ -11,18 +11,28 @@ Sample configuration:
         "enabled": true,
         "listen_ip_address": "127.0.0.1",
         "listen_port": 8080,
+        "verbosity": "info",
+        "jwt_secret_key": "somethingrandom",
+        "CORS_origins": [],
         "username": "Freqtrader",
         "password": "SuperSecret1!"
     },
 ```
 
-!!! Danger Security warning
-  By default, the configuration listens on localhost only (so it's not reachable from other systems). We strongly recommend to not expose this API to the internet and choose a strong, unique password, since others will potentially be able to control your bot.
+!!! Danger "Security warning"
+    By default, the configuration listens on localhost only (so it's not reachable from other systems). We strongly recommend to not expose this API to the internet and choose a strong, unique password, since others will potentially be able to control your bot.
 
-!!! Danger Password selection
-  Please make sure to select a very strong, unique password to protect your bot from unauthorized access.
+!!! Danger "Password selection"
+    Please make sure to select a very strong, unique password to protect your bot from unauthorized access.
 
-You can then access the API by going to `http://127.0.0.1:8080/api/v1/version` to check if the API is running correctly.
+You can then access the API by going to `http://127.0.0.1:8080/api/v1/ping` in a browser to check if the API is running correctly.
+This should return the response:
+
+``` output
+{"status":"pong"}
+```
+
+All other endpoints return sensitive info and require authentication and are therefore not available through a web browser.
 
 To generate a secure password, either use a password manager, or use the below code snipped.
 
@@ -31,9 +41,12 @@ import secrets
 secrets.token_hex()
 ```
 
+!!! Hint
+    Use the same method to also generate a JWT secret key (`jwt_secret_key`).
+
 ### Configuration with docker
 
-If you run your bot using docker, you'll need to have the bot listen to incomming connections. The security is then handled by docker.
+If you run your bot using docker, you'll need to have the bot listen to incoming connections. The security is then handled by docker.
 
 ``` json
     "api_server": {
@@ -58,7 +71,7 @@ docker run -d \
   -v ~/.freqtrade/user_data/:/freqtrade/user_data \
   -v ~/.freqtrade/tradesv3.sqlite:/freqtrade/tradesv3.sqlite \
   -p 127.0.0.1:8080:8080 \
-  freqtrade --db-url sqlite:///tradesv3.sqlite --strategy MyAwesomeStrategy
+  freqtrade trade --db-url sqlite:///tradesv3.sqlite --strategy MyAwesomeStrategy
 ```
 
 !!! Danger "Security warning"
@@ -67,7 +80,7 @@ docker run -d \
 ## Consuming the API
 
 You can consume the API by using the script `scripts/rest_client.py`.
-The client script only requires the `requests` module, so FreqTrade does not need to be installed on the system.
+The client script only requires the `requests` module, so Freqtrade does not need to be installed on the system.
 
 ``` bash
 python3 scripts/rest_client.py <command> [optional parameters]
@@ -91,28 +104,42 @@ By default, the script assumes `127.0.0.1` (localhost) and port `8080` to be use
 python3 scripts/rest_client.py --config rest_config.json <command> [optional parameters]
 ```
 
-## Available commands
+## Available endpoints
 
-|  Command | Default | Description |
-|----------|---------|-------------|
-| `start` | | Starts the trader
-| `stop` | | Stops the trader
-| `stopbuy` | | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
-| `reload_conf` | | Reloads the configuration file
-| `status` | | Lists all open trades
-| `status table` | | List all open trades in a table format
-| `count` | | Displays number of trades used and available
-| `profit` | | Display a summary of your profit/loss from close trades and some stats about your performance
-| `forcesell <trade_id>` | | Instantly sells the given trade  (Ignoring `minimum_roi`).
-| `forcesell all` | | Instantly sells all open trades (Ignoring `minimum_roi`).
-| `forcebuy <pair> [rate]` | | Instantly buys the given pair. Rate is optional. (`forcebuy_enable` must be set to True)
-| `performance` | | Show performance of each finished trade grouped by pair
-| `balance` | | Show account balance per currency
-| `daily <n>` | 7 | Shows profit or loss per day, over the last n days
-| `whitelist` | | Show the current whitelist
-| `blacklist [pair]` | | Show the current blacklist, or adds a pair to the blacklist.
-| `edge` | | Show validated pairs by Edge if it is enabled.
-| `version` | | Show version
+|  Command | Description |
+|----------|-------------|
+| `ping` | Simple command testing the API Readiness - requires no authentication.
+| `start` | Starts the trader.
+| `stop` | Stops the trader.
+| `stopbuy` | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
+| `reload_config` | Reloads the configuration file.
+| `trades` | List last trades.
+| `delete_trade <trade_id>` | Remove trade from the database. Tries to close open orders. Requires manual handling of this trade on the exchange.
+| `show_config` | Shows part of the current configuration with relevant settings to operation.
+| `logs` | Shows last log messages.
+| `status` | Lists all open trades.
+| `count` | Displays number of trades used and available.
+| `locks` | Displays currently locked pairs.
+| `profit` | Display a summary of your profit/loss from close trades and some stats about your performance.
+| `forcesell <trade_id>` | Instantly sells the given trade  (Ignoring `minimum_roi`).
+| `forcesell all` | Instantly sells all open trades (Ignoring `minimum_roi`).
+| `forcebuy <pair> [rate]` | Instantly buys the given pair. Rate is optional. (`forcebuy_enable` must be set to True)
+| `performance` | Show performance of each finished trade grouped by pair.
+| `balance` | Show account balance per currency.
+| `daily <n>` | Shows profit or loss per day, over the last n days (n defaults to 7).
+| `whitelist` | Show the current whitelist.
+| `blacklist [pair]` | Show the current blacklist, or adds a pair to the blacklist.
+| `edge` | Show validated pairs by Edge if it is enabled.
+| `pair_candles` | Returns dataframe for a pair / timeframe combination while the bot is running. **Alpha**
+| `pair_history` | Returns an analyzed dataframe for a given timerange, analyzed by a given strategy. **Alpha**
+| `plot_config` | Get plot config from the strategy (or nothing if not configured). **Alpha**
+| `strategies` | List strategies in strategy directory. **Alpha**
+| `strategy <strategy>` | Get specific Strategy content. **Alpha**
+| `available_pairs` | List available backtest data. **Alpha**
+| `version` | Show version.
+
+!!! Warning "Alpha status"
+    Endpoints labeled with *Alpha status* above may change at any time without notice.
 
 Possible commands can be listed from the rest-client script using the `help` command.
 
@@ -122,72 +149,160 @@ python3 scripts/rest_client.py help
 
 ``` output
 Possible commands:
+
+available_pairs
+	Return available pair (backtest data) based on timeframe / stake_currency selection
+
+        :param timeframe: Only pairs with this timeframe available.
+        :param stake_currency: Only pairs that include this timeframe
+
 balance
-        Get the account balance
-        :returns: json object
+	Get the account balance.
 
 blacklist
-        Show the current blacklist
+	Show the current blacklist.
+
         :param add: List of coins to add (example: "BNB/BTC")
-        :returns: json object
 
 count
-        Returns the amount of open trades
-        :returns: json object
+	Return the amount of open trades.
 
 daily
-        Returns the amount of open trades
-        :returns: json object
+	Return the amount of open trades.
+
+delete_trade
+	Delete trade from the database.
+        Tries to close open orders. Requires manual handling of this asset on the exchange.
+
+        :param trade_id: Deletes the trade with this ID from the database.
 
 edge
-        Returns information about edge
-        :returns: json object
+	Return information about edge.
 
 forcebuy
-        Buy an asset
+	Buy an asset.
+
         :param pair: Pair to buy (ETH/BTC)
         :param price: Optional - price to buy
-        :returns: json object of the trade
 
 forcesell
-        Force-sell a trade
+	Force-sell a trade.
+
         :param tradeid: Id of the trade (can be received via status command)
-        :returns: json object
+
+logs
+	Show latest logs.
+
+        :param limit: Limits log messages to the last <limit> logs. No limit to get all the trades.
+
+pair_candles
+	Return live dataframe for <pair><timeframe>.
+
+        :param pair: Pair to get data for
+        :param timeframe: Only pairs with this timeframe available.
+        :param limit: Limit result to the last n candles.
+
+pair_history
+	Return historic, analyzed dataframe
+
+        :param pair: Pair to get data for
+        :param timeframe: Only pairs with this timeframe available.
+        :param strategy: Strategy to analyze and get values for
+        :param timerange: Timerange to get data for (same format than --timerange endpoints)
 
 performance
-        Returns the performance of the different coins
-        :returns: json object
+	Return the performance of the different coins.
+
+plot_config
+	Return plot configuration if the strategy defines one.
 
 profit
-        Returns the profit summary
-        :returns: json object
+	Return the profit summary.
 
-reload_conf
-        Reload configuration
-        :returns: json object
+reload_config
+	Reload configuration.
+
+show_config
+	
+        Returns part of the configuration, relevant for trading operations.
 
 start
-        Start the bot if it's in stopped state.
-        :returns: json object
+	Start the bot if it's in the stopped state.
 
 status
-        Get the status of open trades
-        :returns: json object
+	Get the status of open trades.
 
 stop
-        Stop the bot. Use start to restart
-        :returns: json object
+	Stop the bot. Use `start` to restart.
 
 stopbuy
-        Stop buying (but handle sells gracefully).
-        use reload_conf to reset
-        :returns: json object
+	Stop buying (but handle sells gracefully). Use `reload_config` to reset.
+
+strategies
+	Lists available strategies
+
+strategy
+	Get strategy details
+
+        :param strategy: Strategy class name
+
+trades
+	Return trades history.
+
+        :param limit: Limits trades to the X last trades. No limit to get all the trades.
 
 version
-        Returns the version of the bot
-        :returns: json object containing the version
+	Return the version of the bot.
 
 whitelist
-        Show the current whitelist
-        :returns: json object
+	Show the current whitelist.
+
 ```
+
+## Advanced API usage using JWT tokens
+
+!!! Note
+    The below should be done in an application (a Freqtrade REST API client, which fetches info via API), and is not intended to be used on a regular basis.
+
+Freqtrade's REST API also offers JWT (JSON Web Tokens).
+You can login using the following command, and subsequently use the resulting access_token.
+
+``` bash
+> curl -X POST --user Freqtrader http://localhost:8080/api/v1/token/login
+{"access_token":"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE1ODkxMTk2ODEsIm5iZiI6MTU4OTExOTY4MSwianRpIjoiMmEwYmY0NWUtMjhmOS00YTUzLTlmNzItMmM5ZWVlYThkNzc2IiwiZXhwIjoxNTg5MTIwNTgxLCJpZGVudGl0eSI6eyJ1IjoiRnJlcXRyYWRlciJ9LCJmcmVzaCI6ZmFsc2UsInR5cGUiOiJhY2Nlc3MifQ.qt6MAXYIa-l556OM7arBvYJ0SDI9J8bIk3_glDujF5g","refresh_token":"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE1ODkxMTk2ODEsIm5iZiI6MTU4OTExOTY4MSwianRpIjoiZWQ1ZWI3YjAtYjMwMy00YzAyLTg2N2MtNWViMjIxNWQ2YTMxIiwiZXhwIjoxNTkxNzExNjgxLCJpZGVudGl0eSI6eyJ1IjoiRnJlcXRyYWRlciJ9LCJ0eXBlIjoicmVmcmVzaCJ9.d1AT_jYICyTAjD0fiQAr52rkRqtxCjUGEMwlNuuzgNQ"}
+
+> access_token="eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE1ODkxMTk2ODEsIm5iZiI6MTU4OTExOTY4MSwianRpIjoiMmEwYmY0NWUtMjhmOS00YTUzLTlmNzItMmM5ZWVlYThkNzc2IiwiZXhwIjoxNTg5MTIwNTgxLCJpZGVudGl0eSI6eyJ1IjoiRnJlcXRyYWRlciJ9LCJmcmVzaCI6ZmFsc2UsInR5cGUiOiJhY2Nlc3MifQ.qt6MAXYIa-l556OM7arBvYJ0SDI9J8bIk3_glDujF5g"
+# Use access_token for authentication
+> curl -X GET --header "Authorization: Bearer ${access_token}" http://localhost:8080/api/v1/count
+
+```
+
+Since the access token has a short timeout (15 min) - the `token/refresh` request should be used periodically to get a fresh access token:
+
+``` bash
+> curl -X POST --header "Authorization: Bearer ${refresh_token}"http://localhost:8080/api/v1/token/refresh
+{"access_token":"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE1ODkxMTk5NzQsIm5iZiI6MTU4OTExOTk3NCwianRpIjoiMDBjNTlhMWUtMjBmYS00ZTk0LTliZjAtNWQwNTg2MTdiZDIyIiwiZXhwIjoxNTg5MTIwODc0LCJpZGVudGl0eSI6eyJ1IjoiRnJlcXRyYWRlciJ9LCJmcmVzaCI6ZmFsc2UsInR5cGUiOiJhY2Nlc3MifQ.1seHlII3WprjjclY6DpRhen0rqdF4j6jbvxIhUFaSbs"}
+```
+
+## CORS
+
+All web-based frontends are subject to [CORS](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) - Cross-Origin Resource Sharing.
+Since most of the requests to the Freqtrade API must be authenticated, a proper CORS policy is key to avoid security problems.
+Also, the standard disallows `*` CORS policies for requests with credentials, so this setting must be set appropriately.
+
+Users can configure this themselves via the `CORS_origins` configuration setting.
+It consists of a list of allowed sites that are allowed to consume resources from the bot's API.
+
+Assuming your application is deployed as `https://frequi.freqtrade.io/home/` - this would mean that the following configuration becomes necessary:
+
+```jsonc
+{
+    //...
+    "jwt_secret_key": "somethingrandom",
+    "CORS_origins": ["https://frequi.freqtrade.io"],
+    //...
+}
+```
+
+!!! Note
+    We strongly recommend to also set `jwt_secret_key` to something random and known only to yourself to avoid unauthorized access to your bot.
diff --git a/docs/sandbox-testing.md b/docs/sandbox-testing.md
index 7f3457d15..9c14412de 100644
--- a/docs/sandbox-testing.md
+++ b/docs/sandbox-testing.md
@@ -1,104 +1,59 @@
 # Sandbox API testing
 
-Where an exchange provides a sandbox for risk-free integration, or end-to-end, testing CCXT provides access to these.
+Some exchanges provide sandboxes or testbeds for risk-free testing, while running the bot against a real exchange.
+With some configuration, freqtrade (in combination with ccxt) provides access to these.
 
-This document is a *light overview of configuring Freqtrade and GDAX sandbox.
-This can be useful to developers and trader alike as Freqtrade is quite customisable.
+This document is an overview to configure Freqtrade to be used with sandboxes.
+This can be useful to developers and trader alike.
 
-When testing your API connectivity, make sure to use the following URLs.
-***Website**
-https://public.sandbox.gdax.com
-***REST API**
-https://api-public.sandbox.gdax.com
+## Exchanges known to have a sandbox / testnet
+
+* [binance](https://testnet.binance.vision/)
+* [coinbasepro](https://public.sandbox.pro.coinbase.com)
+* [gemini](https://exchange.sandbox.gemini.com/)
+* [huobipro](https://www.testnet.huobi.pro/)
+* [kucoin](https://sandbox.kucoin.com/)
+* [phemex](https://testnet.phemex.com/) 
+
+!!! Note
+    We did not test correct functioning of all of the above testnets. Please report your experiences with each sandbox.
 
 ---
 
-# Configure a Sandbox account on Gdax
+## Configure a Sandbox account
 
-Aim of this document section
+When testing your API connectivity, make sure to use the appropriate sandbox / testnet URL.
 
-- An sanbox account
-- create 2FA (needed to create an API)
-- Add test 50BTC to account 
-- Create :
-- - API-KEY
-- - API-Secret
-- - API Password
+In general, you should follow these steps to enable an exchange's sandbox:
 
-## Acccount
+* Figure out if an exchange has a sandbox (most likely by using google or the exchange's support documents)
+* Create a sandbox account (often the sandbox-account requires separate registration)
+* [Add some test assets to account](#add-test-funds)
+* Create API keys
 
-This link will redirect to the sandbox main page to login / create account dialogues:
-https://public.sandbox.pro.coinbase.com/orders/
+### Add test funds
 
-After registration and Email confimation you wil be redirected into your sanbox account.  It is easy to verify you're in sandbox by checking the URL bar.
-> https://public.sandbox.pro.coinbase.com/
+Usually, sandbox exchanges allow depositing funds directly via web-interface.
+You should make sure to have a realistic amount of funds available to your test-account, so results are representable of your real account funds.
 
-## Enable 2Fa (a prerequisite to creating sandbox API Keys)
+!!! Warning
+    Test exchanges will **NEVER** require your real credit card or banking details!
 
-From within sand box site select your profile, top right.
->Or as a direct link: https://public.sandbox.pro.coinbase.com/profile
+## Configure freqtrade to use a exchange's sandbox
 
-From the menu panel to the left of the screen select
-
-> Security: "*View or Update*"
-
-In the new site select "enable authenticator" as typical google Authenticator.
-
-- open Google Authenticator on your phone
-- scan barcode
-- enter your generated 2fa
-
-## Enable API Access
-
-From within sandbox select profile>api>create api-keys
->or as a direct link: https://public.sandbox.pro.coinbase.com/profile/api
-
-Click on "create one" and ensure  **view** and **trade**  are "checked" and sumbit your 2FA
-
-- **Copy and paste the Passphase** into a notepade this will be needed later
-- **Copy and paste the API Secret** popup into a notepad this will needed later
-- **Copy and paste the API Key** into a notepad this will needed later
-
-## Add 50 BTC test funds
-
-To add funds, use the web interface deposit and withdraw buttons.
-
-To begin select 'Wallets' from the top menu.
-> Or as a direct link: https://public.sandbox.pro.coinbase.com/wallets
-
-- Deposits (bottom left of screen)
-- - Deposit Funds Bitcoin
-- - - Coinbase BTC Wallet
-- - - - Max (50 BTC)
-- - - - - Deposit
-
-*This process may be repeated for other currencies, ETH as example*
-
----
-
-# Configure Freqtrade to use Gax Sandbox 
-
-The aim of this document section
-
-- Enable sandbox URLs in Freqtrade
-- Configure API
-- - secret
-- - key
-- - passphrase
- 
-## Sandbox URLs
+### Sandbox URLs
 
 Freqtrade makes use of CCXT which in turn provides a list of URLs to Freqtrade.
 These include `['test']` and `['api']`.
 
-- `[Test]` if available will point to an Exchanges sandbox. 
-- `[Api]` normally used, and resolves to live API target on the exchange 
+* `[Test]` if available will point to an Exchanges sandbox.
+* `[Api]` normally used, and resolves to live API target on the exchange.
 
 To make use of sandbox / test add "sandbox": true, to your config.json
 
 ```json
   "exchange": {
-        "name": "gdax",
+        "name": "coinbasepro",
         "sandbox": true,
         "key": "5wowfxemogxeowo;heiohgmd",
         "secret": "/ZMH1P62rCVmwefewrgcewX8nh4gob+lywxfwfxwwfxwfNsH1ySgvWCUR/w==",
@@ -106,36 +61,57 @@ To make use of sandbox / test add "sandbox": true, to your config.json
         "outdated_offset": 5
         "pair_whitelist": [
             "BTC/USD"
+        ]
+  },
+  "datadir": "user_data/data/coinbasepro_sandbox"
 ```
 
-Also insert your 
+Also the following information:
 
-- api-key  (noted earlier)
-- api-secret (noted earlier)
-- password (the passphrase - noted earlier)
+* api-key (created for the sandbox webpage)
+* api-secret (noted earlier)
+* password (the passphrase - noted earlier)
+
+!!! Tip "Different data directory"
+    We also recommend to set `datadir` to something identifying downloaded data as sandbox data, to avoid having sandbox data mixed with data from the real exchange.
+    This can be done by adding the `"datadir"` key to the configuration.
+    Now, whenever you use this configuration, your data directory will be set to this directory.
 
 ---
 
 ## You should now be ready to test your sandbox
 
-Ensure Freqtrade logs show the sandbox URL, and trades made are shown in sandbox.
-** Typically the  BTC/USD has the most activity in sandbox to test against.
+Ensure Freqtrade logs show the sandbox URL, and trades made are shown in sandbox. Also make sure to select a pair which shows at least some decent value (which very often is BTC/<somestablecoin>).
 
-## GDAX - Old Candles problem
+## Common problems with sandbox exchanges
 
-It is my experience that GDAX sandbox candles may be 20+- minutes out of date. This can cause trades to fail as one of Freqtrades safety checks.
+Sandbox exchange instances often have very low volume, which can cause some problems which usually are not seen on a real exchange instance.
 
-To disable this check, add / change the `"outdated_offset"` parameter in the exchange section of your configuration to adjust for this delay.
-Example based on the above configuration:
+### Old Candles problem
 
-```json
-  "exchange": {
-        "name": "gdax",
-        "sandbox": true,
-        "key": "5wowfxemogxeowo;heiohgmd",
-        "secret": "/ZMH1P62rCVmwefewrgcewX8nh4gob+lywxfwfxwwfxwfNsH1ySgvWCUR/w==",
-        "password": "1bkjfkhfhfu6sr",
-        "outdated_offset": 30
-        "pair_whitelist": [
-            "BTC/USD"
-```
+Since Sandboxes often have low volume, candles can be quite old and show no volume.
+To disable the error "Outdated history for pair ...", best increase the parameter `"outdated_offset"` to a number that seems realistic for the sandbox you're using.
+
+### Unfilled orders
+
+Sandboxes often have very low volumes - which means that many trades can go unfilled, or can go unfilled for a very long time.
+
+To mitigate this, you can try to match the first order on the opposite orderbook side using the following configuration:
+
+``` jsonc
+  "order_types": {
+    "buy": "limit",
+    "sell": "limit"
+    // ...
+  },
+  "bid_strategy": {
+    "price_side": "ask",
+    // ...
+  },
+  "ask_strategy":{
+    "price_side": "bid",
+    // ...
+  },
+  ```
+
+  The configuration is similar to the suggested configuration for market orders - however by using limit-orders you can avoid moving the price too much, and you can set the worst price you might get.
diff --git a/docs/sql_cheatsheet.md b/docs/sql_cheatsheet.md
index f41520bd9..569af33ff 100644
--- a/docs/sql_cheatsheet.md
+++ b/docs/sql_cheatsheet.md
@@ -1,13 +1,29 @@
 # SQL Helper
+
 This page contains some help if you want to edit your sqlite db.
 
 ## Install sqlite3
-**Ubuntu/Debian installation**
+
+Sqlite3 is a terminal based sqlite application.
+Feel free to use a visual Database editor like SqliteBrowser if you feel more comfortable with that.
+
+### Ubuntu/Debian installation
+
 ```bash
 sudo apt-get install sqlite3
 ```
 
+### Using sqlite3 via docker-compose
+
+The freqtrade docker image does contain sqlite3, so you can edit the database without having to install anything on the host system.
+
+``` bash
+docker-compose exec freqtrade /bin/bash
+sqlite3 <databasefile>.sqlite
+```
+
 ## Open the DB
+
 ```bash
 sqlite3
 .open <filepath>
@@ -16,47 +32,17 @@ sqlite3
 ## Table structure
 
 ### List tables
+
 ```bash
 .tables
 ```
 
 ### Display table structure
+
 ```bash
 .schema <table_name>
 ```
 
-### Trade table structure
-```sql
-CREATE TABLE trades (
-	id INTEGER NOT NULL,
-	exchange VARCHAR NOT NULL,
-	pair VARCHAR NOT NULL,
-	is_open BOOLEAN NOT NULL,
-	fee_open FLOAT NOT NULL,
-	fee_close FLOAT NOT NULL,
-	open_rate FLOAT,
-	open_rate_requested FLOAT,
-	close_rate FLOAT,
-	close_rate_requested FLOAT,
-	close_profit FLOAT,
-	stake_amount FLOAT NOT NULL,
-	amount FLOAT,
-	open_date DATETIME NOT NULL,
-	close_date DATETIME,
-	open_order_id VARCHAR,
-	stop_loss FLOAT,
-	initial_stop_loss FLOAT,
-	stoploss_order_id VARCHAR,
-	stoploss_last_update DATETIME,
-	max_rate FLOAT,
-	sell_reason VARCHAR,
-	strategy VARCHAR,
-	ticker_interval INTEGER,
-	PRIMARY KEY (id),
-	CHECK (is_open IN (0, 1))
-);
-```
-
 ## Get all trades in the table
 
 ```sql
@@ -66,43 +52,50 @@ SELECT * FROM trades;
 ## Fix trade still open after a manual sell on the exchange
 
 !!! Warning
-  	Manually selling a pair on the exchange will not be detected by the bot and it will try to sell anyway. Whenever possible, forcesell <tradeid> should be used to accomplish the same thing.  
-		It is strongly advised to backup your database file before making any manual changes.
+    Manually selling a pair on the exchange will not be detected by the bot and it will try to sell anyway. Whenever possible, forcesell <tradeid> should be used to accomplish the same thing.  
+    It is strongly advised to backup your database file before making any manual changes.
 
 !!! Note
-  	This should not be necessary after /forcesell, as forcesell orders are closed automatically by the bot on the next iteration.
+    This should not be necessary after /forcesell, as forcesell orders are closed automatically by the bot on the next iteration.
 
 ```sql
 UPDATE trades
-SET is_open=0, close_date=<close_date>, close_rate=<close_rate>, close_profit=close_rate/open_rate-1, sell_reason=<sell_reason>  
+SET is_open=0,
+  close_date=<close_date>,
+  close_rate=<close_rate>,
+  close_profit = close_rate / open_rate - 1,
+  close_profit_abs = (amount * <close_rate> * (1 - fee_close) - (amount * (open_rate * (1 - fee_open)))),
+  sell_reason=<sell_reason>
 WHERE id=<trade_ID_to_update>;
 ```
 
-##### Example
+### Example
 
 ```sql
 UPDATE trades
-SET is_open=0, close_date='2017-12-20 03:08:45.103418', close_rate=0.19638016, close_profit=0.0496, sell_reason='force_sell'  
+SET is_open=0,
+  close_date='2020-06-20 03:08:45.103418',
+  close_rate=0.19638016,
+  close_profit=0.0496,
+  close_profit_abs = (amount * 0.19638016 * (1 - fee_close) - (amount * (open_rate * (1 - fee_open)))),
+  sell_reason='force_sell'  
 WHERE id=31;
 ```
 
-## Insert manually a new trade
+## Remove trade from the database
+
+!!! Tip "Use RPC Methods to delete trades"
+    Consider using `/delete <tradeid>` via telegram or rest API. That's the recommended way to deleting trades.
+
+If you'd still like to remove a trade from the database directly, you can use the below query.
 
 ```sql
-INSERT INTO trades (exchange, pair, is_open, fee_open, fee_close, open_rate, stake_amount, amount, open_date)
-VALUES ('bittrex', 'ETH/BTC', 1, 0.0025, 0.0025, <open_rate>, <stake_amount>, <amount>, '<datetime>')
+DELETE FROM trades WHERE id = <tradeid>;
 ```
 
-##### Example:
-
 ```sql
-INSERT INTO trades (exchange, pair, is_open, fee_open, fee_close, open_rate, stake_amount, amount, open_date)
-VALUES ('bittrex', 'ETH/BTC', 1, 0.0025, 0.0025, 0.00258580, 0.002, 0.7715262081, '2017-11-28 12:44:24.000000')
+DELETE FROM trades WHERE id = 31;
 ```
 
-## Fix wrong fees in the table
-If your DB was created before [PR#200](https://github.com/freqtrade/freqtrade/pull/200) was merged (before 12/23/17).
-
-```sql
-UPDATE trades SET fee=0.0025 WHERE fee=0.005;
-```
+!!! Warning
+    This will remove this trade from the database. Please make sure you got the correct id and **NEVER** run this query without the `where` clause.
diff --git a/docs/stoploss.md b/docs/stoploss.md
index f5e2f8df6..fa888cd47 100644
--- a/docs/stoploss.md
+++ b/docs/stoploss.md
@@ -1,80 +1,182 @@
 # Stop Loss
 
-The `stoploss` configuration parameter is loss in percentage that should trigger a sale.
+The `stoploss` configuration parameter is loss as ratio that should trigger a sale.
 For example, value `-0.10` will cause immediate sell if the profit dips below -10% for a given trade. This parameter is optional.
 
-Most of the strategy files already include the optimal `stoploss`
-value. This parameter is optional. If you use it in the configuration file, it will take over the
-`stoploss` value from the strategy file.
+Most of the strategy files already include the optimal `stoploss` value.
 
-## Stop Loss support
+!!! Info
+    All stoploss properties mentioned in this file can be set in the Strategy, or in the configuration.  
+    <ins>Configuration values will override the strategy values.</ins>
+
+## Stop Loss On-Exchange/Freqtrade
+
+Those stoploss modes can be *on exchange* or *off exchange*.
+
+These modes can be configured with these values:
+
+``` python
+    'emergencysell': 'market',
+    'stoploss_on_exchange': False
+    'stoploss_on_exchange_interval': 60,
+    'stoploss_on_exchange_limit_ratio': 0.99
+```
+
+!!! Note
+    Stoploss on exchange is only supported for Binance (stop-loss-limit), Kraken (stop-loss-market) and FTX (stop limit and stop-market) as of now.  
+    <ins>Do not set too low stoploss value if using stop loss on exchange!</ins>  
+    If set to low/tight then you have greater risk of missing fill on the order and stoploss will not work
+
+### stoploss_on_exchange and stoploss_on_exchange_limit_ratio
+Enable or Disable stop loss on exchange.
+If the stoploss is *on exchange* it means a stoploss limit order is placed on the exchange immediately after buy order happens successfully. This will protect you against sudden crashes in market as the order will be in the queue immediately and if market goes down then the order has more chance of being fulfilled.
+
+If `stoploss_on_exchange` uses limit orders, the exchange needs 2 prices, the stoploss_price and the Limit price.  
+`stoploss` defines the stop-price where the limit order is placed - and limit should be slightly below this.  
+If an exchange supports both limit and market stoploss orders, then the value of `stoploss` will be used to determine the stoploss type.  
+
+Calculation example: we bought the asset at 100$.  
+Stop-price is 95$, then limit would be `95 * 0.99 = 94.05$` - so the limit order fill can happen between 95$ and 94.05$.  
+
+For example, assuming the stoploss is on exchange, and trailing stoploss is enabled, and the market is going up, then the bot automatically cancels the previous stoploss order and puts a new one with a stop value higher than the previous stoploss order.
+
+### stoploss_on_exchange_interval
+In case of stoploss on exchange there is another parameter called `stoploss_on_exchange_interval`. This configures the interval in seconds at which the bot will check the stoploss and update it if necessary.  
+The bot cannot do these every 5 seconds (at each iteration), otherwise it would get banned by the exchange.
+So this parameter will tell the bot how often it should update the stoploss order. The default value is 60 (1 minute).
+This same logic will reapply a stoploss order on the exchange should you cancel it accidentally.
+
+### emergencysell
+`emergencysell` is an optional value, which defaults to `market` and is used when creating stop loss on exchange orders fails.
+The below is the default which is used if not changed in strategy or configuration file.
+
+Example from strategy file:
+
+``` python
+order_types = {
+    'buy': 'limit',
+    'sell': 'limit',
+    'emergencysell': 'market',
+    'stoploss': 'market',
+    'stoploss_on_exchange': True,
+    'stoploss_on_exchange_interval': 60,
+    'stoploss_on_exchange_limit_ratio': 0.99
+}
+```
+
+## Stop Loss Types
 
 At this stage the bot contains the following stoploss support modes:
 
-1. static stop loss, defined in either the strategy or configuration.
-2. trailing stop loss, defined in the configuration.
-3. trailing stop loss, custom positive loss, defined in configuration.
+1. Static stop loss.
+2. Trailing stop loss.
+3. Trailing stop loss, custom positive loss.
+4. Trailing stop loss only once the trade has reached a certain offset.
 
-!!! Note
-    All stoploss properties can be configured in either Strategy or configuration. Configuration values override strategy values.
+### Static Stop Loss
 
-Those stoploss modes can be *on exchange* or *off exchange*. If the stoploss is *on exchange* it means a stoploss limit order is placed on the exchange immediately after buy order happens successfuly. This will protect you against sudden crashes in market as the order will be in the queue immediately and if market goes down then the order has more chance of being fulfilled.
+This is very simple, you define a stop loss of x (as a ratio of price, i.e. x * 100% of price). This will try to sell the asset once the loss exceeds the defined loss.
 
-In case of stoploss on exchange there is another parameter called `stoploss_on_exchange_interval`. This configures the interval in seconds at which the bot will check the stoploss and update it if necessary. As an example in case of trailing stoploss if the order is on the exchange and the market is going up then the bot automatically cancels the previous stoploss order and put a new one with a stop value higher than previous one. It is clear that the bot cannot do it every 5 seconds otherwise it gets banned. So this parameter will tell the bot how often it should update the stoploss order. The default value is 60 (1 minute).
+Example of stop loss:
 
-!!! Note
-    Stoploss on exchange is only supported for Binance as of now.
-
-## Static Stop Loss
-
-This is very simple, basically you define a stop loss of x in your strategy file or alternative in the configuration, which
-will overwrite the strategy definition. This will basically try to sell your asset, the second the loss exceeds the defined loss.
-
-## Trailing Stop Loss
-
-The initial value for this stop loss, is defined in your strategy or configuration. Just as you would define your Stop Loss normally.
-To enable this Feauture all you have to do is to define the configuration element:
-
-``` json
-"trailing_stop" : True
+``` python
+    stoploss = -0.10
 ```
 
-This will now activate an algorithm, which automatically moves your stop loss up every time the price of your asset increases.
+For example, simplified math:
+* the bot buys an asset at a price of 100$
+* the stop loss is defined at -10%
+* the stop loss would get triggered once the asset drops below 90$
 
-For example, simplified math,
+### Trailing Stop Loss
 
-* you buy an asset at a price of 100$
-* your stop loss is defined at 2%
-* which means your stop loss, gets triggered once your asset dropped below 98$
-* assuming your asset now increases to 102$
-* your stop loss, will now be 2% of 102$ or 99.96$
-* now your asset drops in value to 101$, your stop loss, will still be 99.96$
+The initial value for this is `stoploss`, just as you would define your static Stop loss.
+To enable trailing stoploss:
 
-basically what this means is that your stop loss will be adjusted to be always be 2% of the highest observed price
-
-### Custom positive loss
-
-Due to demand, it is possible to have a default stop loss, when you are in the red with your buy, but once your profit surpasses a certain percentage,
-the system will utilize a new stop loss, which can be a different value. For example your default stop loss is 5%, but once you have 1.1% profit,
-it will be changed to be only a 1% stop loss, which trails the green candles until it goes below them.
-
-Both values can be configured in the main configuration file and requires `"trailing_stop": true` to be set to true.
-
-``` json
-    "trailing_stop_positive":  0.01,
-    "trailing_stop_positive_offset":  0.011,
-    "trailing_only_offset_is_reached": false
+``` python
+    stoploss = -0.10
+    trailing_stop = True
 ```
 
-The 0.01 would translate to a 1% stop loss, once you hit 1.1% profit.
+This will now activate an algorithm, which automatically moves the stop loss up every time the price of your asset increases.
 
-You should also make sure to have this value (`trailing_stop_positive_offset`) lower than your minimal ROI, otherwise minimal ROI will apply first and sell your trade.
+For example, simplified math:
 
-If `"trailing_only_offset_is_reached": true` then the trailing stoploss is only activated once the offset is reached. Until then, the stoploss remains at the configured`stoploss`.
+* the bot buys an asset at a price of 100$
+* the stop loss is defined at -10%
+* the stop loss would get triggered once the asset drops below 90$
+* assuming the asset now increases to 102$
+* the stop loss will now be -10% of 102$ = 91.8$
+* now the asset drops in value to 101$, the stop loss will still be 91.8$ and would trigger at 91.8$.
+
+In summary: The stoploss will be adjusted to be always be -10% of the highest observed price.
+
+### Trailing stop loss, custom positive loss
+
+It is also possible to have a default stop loss, when you are in the red with your buy (buy - fee), but once you hit positive result the system will utilize a new stop loss, which can have a different value.
+For example, your default stop loss is -10%, but once you have more than 0% profit (example 0.1%) a different trailing stoploss will be used.
+
+!!! Note
+    If you want the stoploss to only be changed when you break even of making a profit (what most users want) please refer to next section with [offset enabled](#Trailing-stop-loss-only-once-the-trade-has-reached-a-certain-offset).
+
+Both values require `trailing_stop` to be set to true and `trailing_stop_positive` with a value.
+
+``` python
+    stoploss = -0.10
+    trailing_stop = True
+    trailing_stop_positive = 0.02
+```
+
+For example, simplified math:
+
+* the bot buys an asset at a price of 100$
+* the stop loss is defined at -10%
+* the stop loss would get triggered once the asset drops below 90$
+* assuming the asset now increases to 102$
+* the stop loss will now be -2% of 102$ = 99.96$ (99.96$ stop loss will be locked in and will follow asset price increasements with -2%)
+* now the asset drops in value to 101$, the stop loss will still be 99.96$ and would trigger at 99.96$
+
+The 0.02 would translate to a -2% stop loss.
+Before this, `stoploss` is used for the trailing stoploss.
+
+### Trailing stop loss only once the trade has reached a certain offset
+
+It is also possible to use a static stoploss until the offset is reached, and then trail the trade to take profits once the market turns.
+
+If `"trailing_only_offset_is_reached": true` then the trailing stoploss is only activated once the offset is reached. Until then, the stoploss remains at the configured `stoploss`.
+This option can be used with or without `trailing_stop_positive`, but uses `trailing_stop_positive_offset` as offset.
+
+``` python
+    trailing_stop_positive_offset = 0.011
+    trailing_only_offset_is_reached = True
+```
+
+Configuration (offset is buyprice + 3%):
+
+``` python
+    stoploss = -0.10
+    trailing_stop = True
+    trailing_stop_positive = 0.02
+    trailing_stop_positive_offset = 0.03
+    trailing_only_offset_is_reached = True
+```
+
+For example, simplified math:
+
+* the bot buys an asset at a price of 100$
+* the stop loss is defined at -10%
+* the stop loss would get triggered once the asset drops below 90$
+* stoploss will remain at 90$ unless asset increases to or above our configured offset
+* assuming the asset now increases to 103$ (where we have the offset configured)
+* the stop loss will now be -2% of 103$ = 100.94$
+* now the asset drops in value to 101$, the stop loss will still be 100.94$ and would trigger at 100.94$
+
+!!! Tip
+    Make sure to have this value (`trailing_stop_positive_offset`) lower than minimal ROI, otherwise minimal ROI will apply first and sell the trade.
 
 ## Changing stoploss on open trades
 
-A stoploss on an open trade can be changed by changing the value in the configuration or strategy and use the `/reload_conf` command (alternatively, completely stopping and restarting the bot also works).
+A stoploss on an open trade can be changed by changing the value in the configuration or strategy and use the `/reload_config` command (alternatively, completely stopping and restarting the bot also works).
 
 The new stoploss value will be applied to open trades (and corresponding log-messages will be generated).
 
diff --git a/docs/strategy-advanced.md b/docs/strategy-advanced.md
new file mode 100644
index 000000000..359280694
--- /dev/null
+++ b/docs/strategy-advanced.md
@@ -0,0 +1,222 @@
+# Advanced Strategies
+
+This page explains some advanced concepts available for strategies.
+If you're just getting started, please be familiar with the methods described in the [Strategy Customization](strategy-customization.md) documentation and with the [Freqtrade basics](bot-basics.md) first.
+
+[Freqtrade basics](bot-basics.md) describes in which sequence each method described below is called, which can be helpful to understand which method to use for your custom needs.
+
+!!! Note
+    All callback methods described below should only be implemented in a strategy if they are actually used.
+
+## Custom order timeout rules
+
+Simple, timebased order-timeouts can be configured either via strategy or in the configuration in the `unfilledtimeout` section.
+
+However, freqtrade also offers a custom callback for both ordertypes, which allows you to decide based on custom criteria if a order did time out or not.
+
+!!! Note
+    Unfilled order timeouts are not relevant during backtesting or hyperopt, and are only relevant during real (live) trading. Therefore these methods are only called in these circumstances.
+
+### Custom order timeout example
+
+A simple example, which applies different unfilled-timeouts depending on the price of the asset can be seen below.
+It applies a tight timeout for higher priced assets, while allowing more time to fill on cheap coins.
+
+The function must return either `True` (cancel order) or `False` (keep order alive).
+
+``` python
+from datetime import datetime, timedelta
+from freqtrade.persistence import Trade
+
+class Awesomestrategy(IStrategy):
+
+    # ... populate_* methods
+
+    # Set unfilledtimeout to 25 hours, since our maximum timeout from below is 24 hours.
+    unfilledtimeout = {
+        'buy': 60 * 25,
+        'sell': 60 * 25
+    }
+
+    def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool:
+        if trade.open_rate > 100 and trade.open_date < datetime.utcnow() - timedelta(minutes=5):
+            return True
+        elif trade.open_rate > 10 and trade.open_date < datetime.utcnow() - timedelta(minutes=3):
+            return True
+        elif trade.open_rate < 1 and trade.open_date < datetime.utcnow() - timedelta(hours=24):
+           return True
+        return False
+
+
+    def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool:
+        if trade.open_rate > 100 and trade.open_date < datetime.utcnow() - timedelta(minutes=5):
+            return True
+        elif trade.open_rate > 10 and trade.open_date < datetime.utcnow() - timedelta(minutes=3):
+            return True
+        elif trade.open_rate < 1 and trade.open_date < datetime.utcnow() - timedelta(hours=24):
+           return True
+        return False
+```
+
+!!! Note
+    For the above example, `unfilledtimeout` must be set to something bigger than 24h, otherwise that type of timeout will apply first.
+
+### Custom order timeout example (using additional data)
+
+``` python
+from datetime import datetime
+from freqtrade.persistence import Trade
+
+class Awesomestrategy(IStrategy):
+
+    # ... populate_* methods
+
+    # Set unfilledtimeout to 25 hours, since our maximum timeout from below is 24 hours.
+    unfilledtimeout = {
+        'buy': 60 * 25,
+        'sell': 60 * 25
+    }
+
+    def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
+        ob = self.dp.orderbook(pair, 1)
+        current_price = ob['bids'][0][0]
+        # Cancel buy order if price is more than 2% above the order.
+        if current_price > order['price'] * 1.02:
+            return True
+        return False
+
+
+    def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
+        ob = self.dp.orderbook(pair, 1)
+        current_price = ob['asks'][0][0]
+        # Cancel sell order if price is more than 2% below the order.
+        if current_price < order['price'] * 0.98:
+            return True
+        return False
+```
+
+## Bot loop start callback
+
+A simple callback which is called once at the start of every bot throttling iteration.
+This can be used to perform calculations which are pair independent (apply to all pairs), loading of external data, etc.
+
+``` python
+import requests
+
+class Awesomestrategy(IStrategy):
+
+    # ... populate_* methods
+
+    def bot_loop_start(self, **kwargs) -> None:
+        """
+        Called at the start of the bot iteration (one loop).
+        Might be used to perform pair-independent tasks
+        (e.g. gather some remote resource for comparison)
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        """
+        if self.config['runmode'].value in ('live', 'dry_run'):
+            # Assign this to the class by using self.*
+            # can then be used by populate_* methods
+            self.remote_data = requests.get('https://some_remote_source.example.com')
+
+```
+
+## Bot order confirmation
+
+### Trade entry (buy order) confirmation
+
+`confirm_trade_entry()` can be used to abort a trade entry at the latest second (maybe because the price is not what we expect).
+
+``` python
+class Awesomestrategy(IStrategy):
+
+    # ... populate_* methods
+
+    def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
+                            time_in_force: str, **kwargs) -> bool:
+        """
+        Called right before placing a buy order.
+        Timing for this function is critical, so avoid doing heavy computations or
+        network requests in this method.
+
+        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+        When not implemented by a strategy, returns True (always confirming).
+
+        :param pair: Pair that's about to be bought.
+        :param order_type: Order type (as configured in order_types). usually limit or market.
+        :param amount: Amount in target (quote) currency that's going to be traded.
+        :param rate: Rate that's going to be used when using limit orders
+        :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return bool: When True is returned, then the buy-order is placed on the exchange.
+            False aborts the process
+        """
+        return True
+
+```
+
+### Trade exit (sell order) confirmation
+
+`confirm_trade_exit()` can be used to abort a trade exit (sell) at the latest second (maybe because the price is not what we expect).
+
+``` python
+from freqtrade.persistence import Trade
+
+
+class Awesomestrategy(IStrategy):
+
+    # ... populate_* methods
+
+    def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
+                           rate: float, time_in_force: str, sell_reason: str, **kwargs) -> bool:
+        """
+        Called right before placing a regular sell order.
+        Timing for this function is critical, so avoid doing heavy computations or
+        network requests in this method.
+
+        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+        When not implemented by a strategy, returns True (always confirming).
+
+        :param pair: Pair that's about to be sold.
+        :param order_type: Order type (as configured in order_types). usually limit or market.
+        :param amount: Amount in quote currency.
+        :param rate: Rate that's going to be used when using limit orders
+        :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
+        :param sell_reason: Sell reason.
+            Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
+                           'sell_signal', 'force_sell', 'emergency_sell']
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return bool: When True is returned, then the sell-order is placed on the exchange.
+            False aborts the process
+        """
+        if sell_reason == 'force_sell' and trade.calc_profit_ratio(rate) < 0:
+            # Reject force-sells with negative profit
+            # This is just a sample, please adjust to your needs
+            # (this does not necessarily make sense, assuming you know when you're force-selling)
+            return False
+        return True
+
+```
+
+## Derived strategies
+
+The strategies can be derived from other strategies. This avoids duplication of your custom strategy code. You can use this technique to override small parts of your main strategy, leaving the rest untouched:
+
+``` python
+class MyAwesomeStrategy(IStrategy):
+    ...
+    stoploss = 0.13
+    trailing_stop = False
+    # All other attributes and methods are here as they
+    # should be in any custom strategy...
+    ...
+
+class MyAwesomeStrategy2(MyAwesomeStrategy):
+    # Override something
+    stoploss = 0.08
+    trailing_stop = True
+```
+
+Both attributes and methods may be overriden, altering behavior of the original strategy in a way you need.
diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md
index 15f44955b..db007985f 100644
--- a/docs/strategy-customization.md
+++ b/docs/strategy-customization.md
@@ -1,30 +1,35 @@
-# Optimization
+# Strategy Customization
 
-This page explains where to customize your strategies, and add new
-indicators.
+This page explains how to customize your strategies, add new indicators and set up trading rules.
+
+Please familiarize yourself with [Freqtrade basics](bot-basics.md) first, which provides overall info on how the bot operates.
 
 ## Install a custom strategy file
 
 This is very simple. Copy paste your strategy file into the directory `user_data/strategies`.
 
-Let assume you have a class called `AwesomeStrategy` in the file `awesome-strategy.py`:
+Let assume you have a class called `AwesomeStrategy` in the file `AwesomeStrategy.py`:
 
-1. Move your file into `user_data/strategies` (you should have `user_data/strategies/awesome-strategy.py`
+1. Move your file into `user_data/strategies` (you should have `user_data/strategies/AwesomeStrategy.py`
 2. Start the bot with the param `--strategy AwesomeStrategy` (the parameter is the class name)
 
 ```bash
-freqtrade --strategy AwesomeStrategy
+freqtrade trade --strategy AwesomeStrategy
 ```
 
-## Change your strategy
+## Develop your own strategy
 
-The bot includes a default strategy file. However, we recommend you to
-use your own file to not have to lose your parameters every time the default
-strategy file will be updated on Github. Put your custom strategy file
-into the directory `user_data/strategies`.
+The bot includes a default strategy file.
+Also, several other strategies are available in the [strategy repository](https://github.com/freqtrade/freqtrade-strategies).
 
-Best copy the test-strategy and modify this copy to avoid having bot-updates override your changes.
-`cp  user_data/strategies/test_strategy.py user_data/strategies/awesome-strategy.py`
+You will however most likely have your own idea for a strategy.
+This document intends to help you develop one for yourself.
+
+To get started, use `freqtrade new-strategy --strategy AwesomeStrategy`.
+This will create a new strategy file from a template, which will be located under `user_data/strategies/AwesomeStrategy.py`.
+
+!!! Note
+    This is just a template file, which will most likely not be profitable out of the box.
 
 ### Anatomy of a strategy
 
@@ -36,27 +41,31 @@ A strategy file contains all the information needed to build a good strategy:
 - Minimal ROI recommended
 - Stoploss strongly recommended
 
-The bot also include a sample strategy called `TestStrategy` you can update: `user_data/strategies/test_strategy.py`.
-You can test it with the parameter: `--strategy TestStrategy`
+The bot also include a sample strategy called `SampleStrategy` you can update: `user_data/strategies/sample_strategy.py`.
+You can test it with the parameter: `--strategy SampleStrategy`
+
+Additionally, there is an attribute called `INTERFACE_VERSION`, which defines the version of the strategy interface the bot should use.
+The current version is 2 - which is also the default when it's not set explicitly in the strategy.
+
+Future versions will require this to be set.
 
 ```bash
-freqtrade --strategy AwesomeStrategy
+freqtrade trade --strategy AwesomeStrategy
 ```
 
-**For the following section we will use the [user_data/strategies/test_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/test_strategy.py)
+**For the following section we will use the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_strategy.py)
 file as reference.**
 
-!!! Note Strategies and Backtesting
+!!! Note "Strategies and Backtesting"
     To avoid problems and unexpected differences between Backtesting and dry/live modes, please be aware
-    that during backtesting the full time-interval is passed to the `populate_*()` methods at once.
+    that during backtesting the full time range is passed to the `populate_*()` methods at once.
     It is therefore best to use vectorized operations (across the whole dataframe, not loops) and
     avoid index referencing (`df.iloc[-1]`), but instead use `df.shift()` to get to the previous candle.
 
-!!! Warning Using future data
-    Since backtesting passes the full time interval to the `populate_*()` methods, the strategy author
+!!! Warning "Warning: Using future data"
+    Since backtesting passes the full time range to the `populate_*()` methods, the strategy author
     needs to take care to avoid having the strategy utilize data from the future.
-    Samples for usage of future data are `dataframe.shift(-1)`, `dataframe.resample("1h")` (this uses the left border of the interval, so moves data from an hour to the start of the hour).
-    They all use data which is not available during regular operations, so these strategies will perform well during backtesting, but will fail / perform badly in dry-runs.
+    Some common patterns for this are listed in the [Common Mistakes](#common-mistakes-when-developing-strategies) section of this document.
 
 ### Customize Indicators
 
@@ -76,7 +85,7 @@ def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame
     Performance Note: For the best performance be frugal on the number of indicators
     you are using. Let uncomment only the indicator you are using in your strategies
     or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
-    :param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
+    :param dataframe: Dataframe with data from the exchange
     :param metadata: Additional information, like the currently traded pair
     :return: a Dataframe with all mandatory indicators for the strategies
     """
@@ -109,11 +118,41 @@ def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame
     return dataframe
 ```
 
-
 !!! Note "Want more indicator examples?"
-    Look into the [user_data/strategies/test_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/test_strategy.py).<br/>
+    Look into the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_strategy.py).
     Then uncomment indicators you need.
 
+### Strategy startup period
+
+Most indicators have an instable startup period, in which they are either not available, or the calculation is incorrect. This can lead to inconsistencies, since Freqtrade does not know how long this instable period should be.
+To account for this, the strategy can be assigned the `startup_candle_count` attribute.
+This should be set to the maximum number of candles that the strategy requires to calculate stable indicators.
+
+In this example strategy, this should be set to 100 (`startup_candle_count = 100`), since the longest needed history is 100 candles.
+
+``` python
+    dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
+```
+
+By letting the bot know how much history is needed, backtest trades can start at the specified timerange during backtesting and hyperopt.
+
+!!! Warning
+    `startup_candle_count` should be below `ohlcv_candle_limit` (which is 500 for most exchanges) - since only this amount of candles will be available during Dry-Run/Live Trade operations.
+
+#### Example
+
+Let's try to backtest 1 month (January 2019) of 5m candles using an example strategy with EMA100, as above.
+
+``` bash
+freqtrade backtesting --timerange 20190101-20190201 --timeframe 5m
+```
+
+Assuming `startup_candle_count` is set to 100, backtesting knows it needs 100 candles to generate valid buy signals. It will load data from `20190101 - (100 * 5m)` - which is ~2019-12-31 15:30:00.
+If this data is available, indicators will be calculated with this extended timerange. The instable startup period (up to 2019-01-01 00:00:00) will then be removed before starting backtesting.
+
+!!! Note
+    If data for the startup period is not available, then the timerange will be adjusted to account for this startup period - so Backtesting would start at 2019-01-01 08:30:00.
+
 ### Buy signal rules
 
 Edit the method `populate_buy_trend()` in your strategy file to update your buy strategy.
@@ -122,7 +161,7 @@ It's important to always return the dataframe without removing/modifying the col
 
 This will method will also define a new column, `"buy"`, which needs to contain 1 for buys, and 0 for "no action".
 
-Sample from `user_data/strategies/test_strategy.py`:
+Sample from `user_data/strategies/sample_strategy.py`:
 
 ```python
 def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -134,15 +173,19 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
     """
     dataframe.loc[
         (
-            (dataframe['adx'] > 30) &
-            (dataframe['tema'] <= dataframe['bb_middleband']) &
-            (dataframe['tema'] > dataframe['tema'].shift(1))
+            (qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
+            (dataframe['tema'] <= dataframe['bb_middleband']) &  # Guard
+            (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard
+            (dataframe['volume'] > 0)  # Make sure Volume is not 0
         ),
         'buy'] = 1
 
     return dataframe
 ```
 
+!!! Note
+    Buying requires sellers to buy from - therefore volume needs to be > 0 (`dataframe['volume'] > 0`) to make sure that the bot does not buy/sell in no-activity periods.
+
 ### Sell signal rules
 
 Edit the method `populate_sell_trend()` into your strategy file to update your sell strategy.
@@ -152,7 +195,7 @@ It's important to always return the dataframe without removing/modifying the col
 
 This will method will also define a new column, `"sell"`, which needs to contain 1 for sells, and 0 for "no action".
 
-Sample from `user_data/strategies/test_strategy.py`:
+Sample from `user_data/strategies/sample_strategy.py`:
 
 ```python
 def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -164,9 +207,10 @@ def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame
     """
     dataframe.loc[
         (
-            (dataframe['adx'] > 70) &
-            (dataframe['tema'] > dataframe['bb_middleband']) &
-            (dataframe['tema'] < dataframe['tema'].shift(1))
+            (qtpylib.crossed_above(dataframe['rsi'], 70)) &  # Signal: RSI crosses above 70
+            (dataframe['tema'] > dataframe['bb_middleband']) &  # Guard
+            (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard
+            (dataframe['volume'] > 0)  # Make sure Volume is not 0
         ),
         'sell'] = 1
     return dataframe
@@ -206,6 +250,23 @@ minimal_roi = {
 
 While technically not completely disabled, this would sell once the trade reaches 10000% Profit.
 
+To use times based on candle duration (timeframe), the following snippet can be handy.
+This will allow you to change the timeframe for the strategy, and ROI times will still be set as candles (e.g. after 3 candles ...)
+
+``` python
+from freqtrade.exchange import timeframe_to_minutes
+
+class AwesomeStrategy(IStrategy):
+
+    timeframe = "1d"
+    timeframe_mins = timeframe_to_minutes(timeframe)
+    minimal_roi = {
+        "0": 0.05,                             # 5% for the first 3 candles
+        str(timeframe_mins * 3)): 0.02,  # 2% after 3 candles
+        str(timeframe_mins * 6)): 0.01,  # 1% After 6 candles
+    }
+```
+
 ### Stoploss
 
 Setting a stoploss is highly recommended to protect your capital from strong moves against you.
@@ -220,17 +281,18 @@ This would signify a stoploss of -10%.
 
 For the full documentation on stoploss features, look at the dedicated [stoploss page](stoploss.md).
 
-If your exchange supports it, it's recommended to also set `"stoploss_on_exchange"` in the order dict, so your stoploss is on the exchange and cannot be missed for network-problems (or other problems).
+If your exchange supports it, it's recommended to also set `"stoploss_on_exchange"` in the order_types dictionary, so your stoploss is on the exchange and cannot be missed due to network problems, high load or other reasons.
 
 For more information on order_types please look [here](configuration.md#understand-order_types).
 
-### Ticker interval
+### Timeframe (formerly ticker interval)
 
 This is the set of candles the bot should download and use for the analysis.
 Common values are `"1m"`, `"5m"`, `"15m"`, `"1h"`, however all values supported by your exchange should work.
 
-Please note that the same buy/sell signals may work with one interval, but not the other.
-This setting is accessible within the strategy by using `self.ticker_interval`.
+Please note that the same buy/sell signals may work well with one timeframe, but not with the others.
+
+This setting is accessible within the strategy methods as the `self.timeframe` attribute.
 
 ### Metadata dict
 
@@ -242,92 +304,44 @@ Instead, have a look at the section [Storing information](#Storing-information)
 
 ### Storing information
 
-Storing information can be accomplished by crating a new dictionary within the strategy class.
+Storing information can be accomplished by creating a new dictionary within the strategy class.
 
-The name of the variable can be choosen at will, but should be prefixed with `cust_` to avoid naming collisions with predefined strategy variables.
+The name of the variable can be chosen at will, but should be prefixed with `cust_` to avoid naming collisions with predefined strategy variables.
 
 ```python
 class Awesomestrategy(IStrategy):
     # Create custom dictionary
     cust_info = {}
+
     def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         # Check if the entry already exists
+        if not metadata["pair"] in self._cust_info:
+            # Create empty entry for this pair
+            self._cust_info[metadata["pair"]] = {}
+
         if "crosstime" in self.cust_info[metadata["pair"]:
-            self.cust_info[metadata["pair"]["crosstime"] += 1
+            self.cust_info[metadata["pair"]]["crosstime"] += 1
         else:
-            self.cust_info[metadata["pair"]["crosstime"] = 1
+            self.cust_info[metadata["pair"]]["crosstime"] = 1
 ```
 
 !!! Warning
-  The data is not persisted after a bot-restart (or config-reload). Also, the amount of data should be kept smallish (no DataFrames and such), otherwise the bot will start to consume a lot of memory and eventually run out of memory and crash.
+    The data is not persisted after a bot-restart (or config-reload). Also, the amount of data should be kept smallish (no DataFrames and such), otherwise the bot will start to consume a lot of memory and eventually run out of memory and crash.
 
 !!! Note
-  If the data is pair-specific, make sure to use pair as one of the keys in the dictionary.
+    If the data is pair-specific, make sure to use pair as one of the keys in the dictionary.
 
-### Additional data (DataProvider)
+***
 
-The strategy provides access to the `DataProvider`. This allows you to get additional data to use in your strategy.
+## Additional data (informative_pairs)
 
-All methods return `None` in case of failure (do not raise an exception).
-
-Please always check the mode of operation to select the correct method to get data (samples see below).
-
-#### Possible options for DataProvider
-
-- `available_pairs` - Property with tuples listing cached pairs with their intervals. (pair, interval)
-- `ohlcv(pair, ticker_interval)` - Currently cached ticker data for all pairs in the whitelist, returns DataFrame or empty DataFrame
-- `historic_ohlcv(pair, ticker_interval)` - Data stored on disk
-- `runmode` - Property containing the current runmode.
-
-#### ohlcv / historic_ohlcv
-
-``` python
-if self.dp:
-    if self.dp.runmode in ('live', 'dry_run'):
-        if (f'{self.stake_currency}/BTC', self.ticker_interval) in self.dp.available_pairs:
-            data_eth = self.dp.ohlcv(pair='{self.stake_currency}/BTC',
-                                     ticker_interval=self.ticker_interval)
-    else:
-        # Get historic ohlcv data (cached on disk).
-        history_eth = self.dp.historic_ohlcv(pair='{self.stake_currency}/BTC',
-                                             ticker_interval='1h')
-```
-
-!!! Warning Warning about backtesting
-    Be carefull when using dataprovider in backtesting. `historic_ohlcv()` provides the full time-range in one go,
-    so please be aware of it and make sure to not "look into the future" to avoid surprises when running in dry/live mode).
-
-!!! Warning Warning in hyperopt
-    This option cannot currently be used during hyperopt.
-
-#### Orderbook
-
-``` python
-if self.dp:
-    if self.dp.runmode in ('live', 'dry_run'):
-        ob = self.dp.orderbook(metadata['pair'], 1)
-        dataframe['best_bid'] = ob['bids'][0][0]
-        dataframe['best_ask'] = ob['asks'][0][0]
-```
-!Warning The order book is not part of the historic data which means backtesting and hyperopt will not work if this
- method is used.
-
-#### Available Pairs
-
-``` python
-if self.dp:
-    for pair, ticker in self.dp.available_pairs:
-        print(f"available {pair}, {ticker}")
-```
-
-
-#### Get data for non-tradeable pairs
+### Get data for non-tradeable pairs
 
 Data for additional, informative pairs (reference pairs) can be beneficial for some strategies.
-Ohlcv data for these pairs will be downloaded as part of the regular whitelist refresh process and is available via `DataProvider` just as other pairs (see above).
+OHLCV data for these pairs will be downloaded as part of the regular whitelist refresh process and is available via `DataProvider` just as other pairs (see below).
 These parts will **not** be traded unless they are also specified in the pair whitelist, or have been selected by Dynamic Whitelisting.
 
-The pairs need to be specified as tuples in the format `("pair", "interval")`, with pair as the first and time interval as the second argument.
+The pairs need to be specified as tuples in the format `("pair", "timeframe")`, with pair as the first and timeframe as the second argument.
 
 Sample:
 
@@ -338,13 +352,268 @@ def informative_pairs(self):
             ]
 ```
 
+A full sample can be found [in the DataProvider section](#complete-data-provider-sample).
+
 !!! Warning
     As these pairs will be refreshed as part of the regular whitelist refresh, it's best to keep this list short.
-    All intervals and all pairs can be specified as long as they are available (and active) on the used exchange.
-    It is however better to use resampling to longer time-intervals when possible
-    to avoid hammering the exchange with too many requests and risk beeing blocked.
+    All timeframes and all pairs can be specified as long as they are available (and active) on the used exchange.
+    It is however better to use resampling to longer timeframes whenever possible
+    to avoid hammering the exchange with too many requests and risk being blocked.
 
-### Additional data - Wallets
+***
+
+## Additional data (DataProvider)
+
+The strategy provides access to the `DataProvider`. This allows you to get additional data to use in your strategy.
+
+All methods return `None` in case of failure (do not raise an exception).
+
+Please always check the mode of operation to select the correct method to get data (samples see below).
+
+!!! Warning "Hyperopt"
+    Dataprovider is available during hyperopt, however it can only be used in `populate_indicators()` within a strategy.
+    It is not available in `populate_buy()` and `populate_sell()` methods, nor in `populate_indicators()`, if this method located in the hyperopt file.
+
+### Possible options for DataProvider
+
+- [`available_pairs`](#available_pairs) - Property with tuples listing cached pairs with their timeframe (pair, timeframe).
+- [`current_whitelist()`](#current_whitelist) - Returns a current list of whitelisted pairs. Useful for accessing dynamic whitelists (i.e. VolumePairlist)
+- [`get_pair_dataframe(pair, timeframe)`](#get_pair_dataframepair-timeframe) - This is a universal method, which returns either historical data (for backtesting) or cached live data (for the Dry-Run and Live-Run modes).
+- [`get_analyzed_dataframe(pair, timeframe)`](#get_analyzed_dataframepair-timeframe) - Returns the analyzed dataframe (after calling `populate_indicators()`, `populate_buy()`, `populate_sell()`) and the time of the latest analysis.
+- `historic_ohlcv(pair, timeframe)` - Returns historical data stored on disk.
+- `market(pair)` - Returns market data for the pair: fees, limits, precisions, activity flag, etc. See [ccxt documentation](https://github.com/ccxt/ccxt/wiki/Manual#markets) for more details on the Market data structure.
+- `ohlcv(pair, timeframe)` - Currently cached candle (OHLCV) data for the pair, returns DataFrame or empty DataFrame.
+- [`orderbook(pair, maximum)`](#orderbookpair-maximum) - Returns latest orderbook data for the pair, a dict with bids/asks with a total of `maximum` entries.
+- [`ticker(pair)`](#tickerpair) - Returns current ticker data for the pair. See [ccxt documentation](https://github.com/ccxt/ccxt/wiki/Manual#price-tickers) for more details on the Ticker data structure.
+- `runmode` - Property containing the current runmode.
+
+### Example Usages
+
+### *available_pairs*
+
+``` python
+if self.dp:
+    for pair, timeframe in self.dp.available_pairs:
+        print(f"available {pair}, {timeframe}")
+```
+
+### *current_whitelist()*
+
+Imagine you've developed a strategy that trades the `5m` timeframe using signals generated from a `1d` timeframe on the top 10 volume pairs by volume. 
+
+The strategy might look something like this:
+
+*Scan through the top 10 pairs by volume using the `VolumePairList` every 5 minutes and use a 14 day RSI to buy and sell.*
+
+Due to the limited available data, it's very difficult to resample our `5m` candles into daily candles for use in a 14 day RSI. Most exchanges limit us to just 500 candles which effectively gives us around 1.74 daily candles. We need 14 days at least!
+
+Since we can't resample our data we will have to use an informative pair; and since our whitelist will be dynamic we don't know which pair(s) to use.
+
+This is where calling `self.dp.current_whitelist()` comes in handy.
+
+```python
+    def informative_pairs(self):
+
+        # get access to all pairs available in whitelist.
+        pairs = self.dp.current_whitelist()
+        # Assign tf to each pair so they can be downloaded and cached for strategy.
+        informative_pairs = [(pair, '1d') for pair in pairs]
+        return informative_pairs   
+```
+
+### *get_pair_dataframe(pair, timeframe)*
+
+``` python
+# fetch live / historical candle (OHLCV) data for the first informative pair
+if self.dp:
+    inf_pair, inf_timeframe = self.informative_pairs()[0]
+    informative = self.dp.get_pair_dataframe(pair=inf_pair,
+                                             timeframe=inf_timeframe)
+```
+
+!!! Warning "Warning about backtesting"
+    Be careful when using dataprovider in backtesting. `historic_ohlcv()` (and `get_pair_dataframe()`
+    for the backtesting runmode) provides the full time-range in one go,
+    so please be aware of it and make sure to not "look into the future" to avoid surprises when running in dry/live mode.
+
+### *get_analyzed_dataframe(pair, timeframe)*
+
+This method is used by freqtrade internally to determine the last signal.
+It can also be used in specific callbacks to get the signal that caused the action (see [Advanced Strategy Documentation](strategy-advanced.md) for more details on available callbacks).
+
+``` python
+# fetch current dataframe
+if self.dp:
+    dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=metadata['pair'],
+                                                             timeframe=self.timeframe)
+```
+
+!!! Note "No data available"
+    Returns an empty dataframe if the requested pair was not cached.
+    This should not happen when using whitelisted pairs.
+
+### *orderbook(pair, maximum)*
+
+``` python
+if self.dp:
+    if self.dp.runmode.value in ('live', 'dry_run'):
+        ob = self.dp.orderbook(metadata['pair'], 1)
+        dataframe['best_bid'] = ob['bids'][0][0]
+        dataframe['best_ask'] = ob['asks'][0][0]
+```
+
+!!! Warning
+    The order book is not part of the historic data which means backtesting and hyperopt will not work correctly if this method is used.
+
+### *ticker(pair)*
+
+``` python
+if self.dp:
+    if self.dp.runmode.value in ('live', 'dry_run'):
+        ticker = self.dp.ticker(metadata['pair'])
+        dataframe['last_price'] = ticker['last']
+        dataframe['volume24h'] = ticker['quoteVolume']
+        dataframe['vwap'] = ticker['vwap']
+```
+
+!!! Warning
+    Although the ticker data structure is a part of the ccxt Unified Interface, the values returned by this method can
+    vary for different exchanges. For instance, many exchanges do not return `vwap` values, the FTX exchange
+    does not always fills in the `last` field (so it can be None), etc. So you need to carefully verify the ticker
+    data returned from the exchange and add appropriate error handling / defaults.
+
+!!! Warning "Warning about backtesting"
+    This method will always return up-to-date values - so usage during backtesting / hyperopt will lead to wrong results.
+
+### Complete Data-provider sample
+
+```python
+from freqtrade.strategy import IStrategy, merge_informative_pair
+from pandas import DataFrame
+
+class SampleStrategy(IStrategy):
+    # strategy init stuff...
+
+    timeframe = '5m'
+
+    # more strategy init stuff..
+
+    def informative_pairs(self):
+
+        # get access to all pairs available in whitelist.
+        pairs = self.dp.current_whitelist()
+        # Assign tf to each pair so they can be downloaded and cached for strategy.
+        informative_pairs = [(pair, '1d') for pair in pairs]
+        # Optionally Add additional "static" pairs
+        informative_pairs += [("ETH/USDT", "5m"),
+                              ("BTC/TUSD", "15m"),
+                            ]
+        return informative_pairs
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        if not self.dp:
+            # Don't do anything if DataProvider is not available.
+            return dataframe
+
+        inf_tf = '1d'
+        # Get the informative pair
+        informative = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe=inf_tf)
+        # Get the 14 day rsi
+        informative['rsi'] = ta.RSI(informative, timeperiod=14)
+
+        # Use the helper function merge_informative_pair to safely merge the pair
+        # Automatically renames the columns and merges a shorter timeframe dataframe and a longer timeframe informative pair
+        # use ffill to have the 1d value available in every row throughout the day.
+        # Without this, comparisons between columns of the original and the informative pair would only work once per day.
+        # Full documentation of this method, see below
+        dataframe = merge_informative_pair(dataframe, informative, self.timeframe, inf_tf, ffill=True)
+
+        # Calculate rsi of the original dataframe (5m timeframe)
+        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+
+        # Do other stuff
+        # ...
+
+        return dataframe
+
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+
+        dataframe.loc[
+            (
+                (qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
+                (dataframe['rsi_1d'] < 30) &                     # Ensure daily RSI is < 30
+                (dataframe['volume'] > 0)                        # Ensure this candle had volume (important for backtesting)
+            ),
+            'buy'] = 1
+
+```
+
+***
+
+## Helper functions
+
+### *merge_informative_pair()*
+
+This method helps you merge an informative pair to a regular dataframe without lookahead bias.
+It's there to help you merge the dataframe in a safe and consistent way.
+
+Options:
+
+- Rename the columns for you to create unique columns
+- Merge the dataframe without lookahead bias
+- Forward-fill (optional)
+
+All columns of the informative dataframe will be available on the returning dataframe in a renamed fashion:
+
+!!! Example "Column renaming"
+    Assuming `inf_tf = '1d'` the resulting columns will be:
+
+    ``` python
+    'date', 'open', 'high', 'low', 'close', 'rsi'                     # from the original dataframe
+    'date_1d', 'open_1d', 'high_1d', 'low_1d', 'close_1d', 'rsi_1d'   # from the informative dataframe
+    ```
+
+??? Example "Column renaming - 1h"
+    Assuming `inf_tf = '1h'` the resulting columns will be:
+
+    ``` python
+    'date', 'open', 'high', 'low', 'close', 'rsi'                     # from the original dataframe
+    'date_1h', 'open_1h', 'high_1h', 'low_1h', 'close_1h', 'rsi_1h'   # from the informative dataframe 
+    ```
+
+??? Example "Custom implementation"
+    A custom implementation for this is possible, and can be done as follows:
+
+    ``` python
+
+    # Shift date by 1 candle
+    # This is necessary since the data is always the "open date"
+    # and a 15m candle starting at 12:15 should not know the close of the 1h candle from 12:00 to 13:00
+    minutes = timeframe_to_minutes(inf_tf)
+    # Only do this if the timeframes are different:
+    informative['date_merge'] = informative["date"] + pd.to_timedelta(minutes, 'm')
+
+    # Rename columns to be unique
+    informative.columns = [f"{col}_{inf_tf}" for col in informative.columns]
+    # Assuming inf_tf = '1d' - then the columns will now be:
+    # date_1d, open_1d, high_1d, low_1d, close_1d, rsi_1d
+
+    # Combine the 2 dataframes
+    # all indicators on the informative sample MUST be calculated before this point
+    dataframe = pd.merge(dataframe, informative, left_on='date', right_on=f'date_merge_{inf_tf}', how='left')
+    # FFill to have the 1d value available in every row throughout the day.
+    # Without this, comparisons would only work once per day.
+    dataframe = dataframe.ffill()
+
+    ```
+
+!!! Warning "Informative timeframe < timeframe"
+    Using informative timeframes smaller than the dataframe timeframe is not recommended with this method, as it will not use any of the additional information this would provide.
+    To use the more detailed information properly, more advanced methods should be applied (which are out of scope for freqtrade documentation, as it'll depend on the respective need).
+
+***
+
+## Additional data (Wallets)
 
 The strategy provides access to the `Wallets` object. This contains the current balances on the exchange.
 
@@ -360,13 +629,106 @@ if self.wallets:
     total_eth = self.wallets.get_total('ETH')
 ```
 
-#### Possible options for Wallets
+### Possible options for Wallets
 
 - `get_free(asset)` - currently available balance to trade
 - `get_used(asset)` - currently tied up balance (open orders)
 - `get_total(asset)` - total available balance - sum of the 2 above
 
-### Print created dataframe
+***
+
+## Additional data (Trades)
+
+A history of Trades can be retrieved in the strategy by querying the database.
+
+At the top of the file, import Trade.
+
+```python
+from freqtrade.persistence import Trade
+```
+
+The following example queries for the current pair and trades from today, however other filters can easily be added.
+
+``` python
+if self.config['runmode'].value in ('live', 'dry_run'):
+    trades = Trade.get_trades([Trade.pair == metadata['pair'],
+                               Trade.open_date > datetime.utcnow() - timedelta(days=1),
+                               Trade.is_open == False,
+                ]).order_by(Trade.close_date).all()
+    # Summarize profit for this pair.
+    curdayprofit = sum(trade.close_profit for trade in trades)
+```
+
+Get amount of stake_currency currently invested in Trades:
+
+``` python
+if self.config['runmode'].value in ('live', 'dry_run'):
+    total_stakes = Trade.total_open_trades_stakes()
+```
+
+Retrieve performance per pair.
+Returns a List of dicts per pair.
+
+``` python
+if self.config['runmode'].value in ('live', 'dry_run'):
+    performance = Trade.get_overall_performance()
+```
+
+Sample return value: ETH/BTC had 5 trades, with a total profit of 1.5% (ratio of 0.015).
+
+``` json
+{'pair': "ETH/BTC", 'profit': 0.015, 'count': 5}
+```
+
+!!! Warning
+    Trade history is not available during backtesting or hyperopt.
+
+## Prevent trades from happening for a specific pair
+
+Freqtrade locks pairs automatically for the current candle (until that candle is over) when a pair is sold, preventing an immediate re-buy of that pair.
+
+Locked pairs will show the message `Pair <pair> is currently locked.`.
+
+### Locking pairs from within the strategy
+
+Sometimes it may be desired to lock a pair after certain events happen (e.g. multiple losing trades in a row).
+
+Freqtrade has an easy method to do this from within the strategy, by calling `self.lock_pair(pair, until, [reason])`.
+`until` must be a datetime object in the future, after which trading will be re-enabled for that pair, while `reason` is an optional string detailing why the pair was locked.
+
+Locks can also be lifted manually, by calling `self.unlock_pair(pair)`.
+
+To verify if a pair is currently locked, use `self.is_pair_locked(pair)`.
+
+!!! Note
+    Locked pairs will always be rounded up to the next candle. So assuming a `5m` timeframe, a lock with `until` set to 10:18 will lock the pair until the candle from 10:15-10:20 will be finished.
+
+!!! Warning
+    Locking pairs is not available during backtesting.
+
+#### Pair locking example
+
+``` python
+from freqtrade.persistence import Trade
+from datetime import timedelta, datetime, timezone
+# Put the above lines a the top of the strategy file, next to all the other imports
+# --------
+
+# Within populate indicators (or populate_buy):
+if self.config['runmode'].value in ('live', 'dry_run'):
+   # fetch closed trades for the last 2 days
+    trades = Trade.get_trades([Trade.pair == metadata['pair'],
+                               Trade.open_date > datetime.utcnow() - timedelta(days=2),
+                               Trade.is_open == False,
+                ]).all()
+    # Analyze the conditions you'd like to lock the pair .... will probably be different for every strategy
+    sumprofit = sum(trade.close_profit for trade in trades)
+    if sumprofit < 0:
+        # Lock pair for 12 hours
+        self.lock_pair(metadata['pair'], until=datetime.now(timezone.utc) + timedelta(hours=12))
+```
+
+## Print created dataframe
 
 To inspect the created dataframe, you can issue a print-statement in either `populate_buy_trend()` or `populate_sell_trend()`.
 You may also want to print the pair so it's clear what data is currently shown.
@@ -390,27 +752,24 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 
 Printing more than a few rows is also possible (simply use  `print(dataframe)` instead of `print(dataframe.tail())`), however not recommended, as that will be very verbose (~500 lines per pair every 5 seconds).
 
-### Where is the default strategy?
+## Common mistakes when developing strategies
 
-The default buy strategy is located in the file
-[freqtrade/default_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/strategy/default_strategy.py).
+Backtesting analyzes the whole time-range at once for performance reasons. Because of this, strategy authors need to make sure that strategies do not look-ahead into the future.
+This is a common pain-point, which can cause huge differences between backtesting and dry/live run methods, since they all use data which is not available during dry/live runs, so these strategies will perform well during backtesting, but will fail / perform badly in real conditions.
 
-### Specify custom strategy location
+The following lists some common patterns which should be avoided to prevent frustration:
 
-If you want to use a strategy from a different directory you can pass `--strategy-path`
+- don't use `shift(-1)`. This uses data from the future, which is not available.
+- don't use `.iloc[-1]` or any other absolute position in the dataframe, this will be different between dry-run and backtesting.
+- don't use `dataframe['volume'].mean()`. This uses the full DataFrame for backtesting, including data from the future. Use `dataframe['volume'].rolling(<window>).mean()` instead
+- don't use `.resample('1h')`. This uses the left border of the interval, so moves data from an hour to the start of the hour. Use `.resample('1h', label='right')` instead.
 
-```bash
-freqtrade --strategy AwesomeStrategy --strategy-path /some/directory
-```
-
-### Further strategy ideas
+## Further strategy ideas
 
 To get additional Ideas for strategies, head over to our [strategy repository](https://github.com/freqtrade/freqtrade-strategies). Feel free to use them as they are - but results will depend on the current market situation, pairs used etc. - therefore please backtest the strategy for your exchange/desired pairs first, evaluate carefully, use at your own risk.
 Feel free to use any of them as inspiration for your own strategies.
 We're happy to accept Pull Requests containing new Strategies to that repo.
 
-We also got a *strategy-sharing* channel in our [Slack community](https://join.slack.com/t/highfrequencybot/shared_invite/enQtNjU5ODcwNjI1MDU3LWEyODBiNzkzNzcyNzU0MWYyYzE5NjIyOTQxMzBmMGUxOTIzM2YyN2Y4NWY1YTEwZDgwYTRmMzE2NmM5ZmY2MTg) which is a great place to get and/or share ideas.
-
 ## Next step
 
 Now you have a perfect strategy you probably want to backtest it.
diff --git a/docs/strategy_analysis_example.md b/docs/strategy_analysis_example.md
new file mode 100644
index 000000000..90e39fd76
--- /dev/null
+++ b/docs/strategy_analysis_example.md
@@ -0,0 +1,196 @@
+# Strategy analysis example
+
+Debugging a strategy can be time-consuming. Freqtrade offers helper functions to visualize raw data.
+The following assumes you work with SampleStrategy, data for 5m timeframe from Binance and have downloaded them into the data directory in the default location.
+
+## Setup
+
+
+```python
+from pathlib import Path
+from freqtrade.configuration import Configuration
+
+# Customize these according to your needs.
+
+# Initialize empty configuration object
+config = Configuration.from_files([])
+# Optionally, use existing configuration file
+# config = Configuration.from_files(["config.json"])
+
+# Define some constants
+config["timeframe"] = "5m"
+# Name of the strategy class
+config["strategy"] = "SampleStrategy"
+# Location of the data
+data_location = Path(config['user_data_dir'], 'data', 'binance')
+# Pair to analyze - Only use one pair here
+pair = "BTC_USDT"
+```
+
+
+```python
+# Load data using values set above
+from freqtrade.data.history import load_pair_history
+
+candles = load_pair_history(datadir=data_location,
+                            timeframe=config["timeframe"],
+                            pair=pair)
+
+# Confirm success
+print("Loaded " + str(len(candles)) + f" rows of data for {pair} from {data_location}")
+candles.head()
+```
+
+## Load and run strategy
+* Rerun each time the strategy file is changed
+
+
+```python
+# Load strategy using values set above
+from freqtrade.resolvers import StrategyResolver
+strategy = StrategyResolver.load_strategy(config)
+
+# Generate buy/sell signals using strategy
+df = strategy.analyze_ticker(candles, {'pair': pair})
+df.tail()
+```
+
+### Display the trade details
+
+* Note that using `data.head()` would also work, however most indicators have some "startup" data at the top of the dataframe.
+* Some possible problems
+    * Columns with NaN values at the end of the dataframe
+    * Columns used in `crossed*()` functions with completely different units
+* Comparison with full backtest
+    * having 200 buy signals as output for one pair from `analyze_ticker()` does not necessarily mean that 200 trades will be made during backtesting.
+    * Assuming you use only one condition such as, `df['rsi'] < 30` as buy condition, this will generate multiple "buy" signals for each pair in sequence (until rsi returns > 29). The bot will only buy on the first of these signals (and also only if a trade-slot ("max_open_trades") is still available), or on one of the middle signals, as soon as a "slot" becomes available.  
+
+
+
+```python
+# Report results
+print(f"Generated {df['buy'].sum()} buy signals")
+data = df.set_index('date', drop=False)
+data.tail()
+```
+
+## Load existing objects into a Jupyter notebook
+
+The following cells assume that you have already generated data using the cli.  
+They will allow you to drill deeper into your results, and perform analysis which otherwise would make the output very difficult to digest due to information overload.
+
+### Load backtest results to pandas dataframe
+
+Analyze a trades dataframe (also used below for plotting)
+
+
+```python
+from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats
+
+# if backtest_dir points to a directory, it'll automatically load the last backtest file.
+backtest_dir = config["user_data_dir"] / "backtest_results"
+# backtest_dir can also point to a specific file 
+# backtest_dir = config["user_data_dir"] / "backtest_results/backtest-result-2020-07-01_20-04-22.json"
+```
+
+
+```python
+# You can get the full backtest statistics by using the following command.
+# This contains all information used to generate the backtest result.
+stats = load_backtest_stats(backtest_dir)
+
+strategy = 'SampleStrategy'
+# All statistics are available per strategy, so if `--strategy-list` was used during backtest, this will be reflected here as well.
+# Example usages:
+print(stats['strategy'][strategy]['results_per_pair'])
+# Get pairlist used for this backtest
+print(stats['strategy'][strategy]['pairlist'])
+# Get market change (average change of all pairs from start to end of the backtest period)
+print(stats['strategy'][strategy]['market_change'])
+# Maximum drawdown ()
+print(stats['strategy'][strategy]['max_drawdown'])
+# Maximum drawdown start and end
+print(stats['strategy'][strategy]['drawdown_start'])
+print(stats['strategy'][strategy]['drawdown_end'])
+
+
+# Get strategy comparison (only relevant if multiple strategies were compared)
+print(stats['strategy_comparison'])
+
+```
+
+
+```python
+# Load backtested trades as dataframe
+trades = load_backtest_data(backtest_dir)
+
+# Show value-counts per pair
+trades.groupby("pair")["sell_reason"].value_counts()
+```
+
+### Load live trading results into a pandas dataframe
+
+In case you did already some trading and want to analyze your performance
+
+
+```python
+from freqtrade.data.btanalysis import load_trades_from_db
+
+# Fetch trades from database
+trades = load_trades_from_db("sqlite:///tradesv3.sqlite")
+
+# Display results
+trades.groupby("pair")["sell_reason"].value_counts()
+```
+
+## Analyze the loaded trades for trade parallelism
+This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with `--disable-max-market-positions`.
+
+`analyze_trade_parallelism()` returns a timeseries dataframe with an "open_trades" column, specifying the number of open trades for each candle.
+
+
+```python
+from freqtrade.data.btanalysis import analyze_trade_parallelism
+
+# Analyze the above
+parallel_trades = analyze_trade_parallelism(trades, '5m')
+
+parallel_trades.plot()
+```
+
+## Plot results
+
+Freqtrade offers interactive plotting capabilities based on plotly.
+
+
+```python
+from freqtrade.plot.plotting import  generate_candlestick_graph
+# Limit graph period to keep plotly quick and reactive
+
+# Filter trades to one pair
+trades_red = trades.loc[trades['pair'] == pair]
+
+data_red = data['2019-06-01':'2019-06-10']
+# Generate candlestick graph
+graph = generate_candlestick_graph(pair=pair,
+                                   data=data_red,
+                                   trades=trades_red,
+                                   indicators1=['sma20', 'ema50', 'ema55'],
+                                   indicators2=['rsi', 'macd', 'macdsignal', 'macdhist']
+                                  )
+
+
+
+```
+
+
+```python
+# Show graph inline
+# graph.show()
+
+# Render graph in a seperate window
+graph.show(renderer="browser")
+
+```
+
+Feel free to submit an issue or Pull Request enhancing this document if you would like to share ideas on how to best analyze the data.
diff --git a/docs/stylesheets/ft.extra.css b/docs/stylesheets/ft.extra.css
new file mode 100644
index 000000000..3369fa177
--- /dev/null
+++ b/docs/stylesheets/ft.extra.css
@@ -0,0 +1,13 @@
+.rst-versions  {
+    font-size: .7rem;
+    color: white;
+}
+
+.rst-versions.rst-badge .rst-current-version {
+    font-size: .7rem;
+    color: white;
+}
+
+.rst-versions .rst-other-versions {
+    color: white;
+}
diff --git a/docs/telegram-usage.md b/docs/telegram-usage.md
index e06d4fdfc..09cf21223 100644
--- a/docs/telegram-usage.md
+++ b/docs/telegram-usage.md
@@ -9,7 +9,7 @@ Telegram user id.
 
 Start a chat with the [Telegram BotFather](https://telegram.me/BotFather)
 
-Send the message `/newbot`. 
+Send the message `/newbot`.
 
 *BotFather response:*
 
@@ -35,39 +35,89 @@ Copy the API Token (`22222222:APITOKEN` in the above example) and keep use it fo
 
 Don't forget to start the conversation with your bot, by clicking `/START` button
 
-### 2. Get your user id
+### 2. Telegram user_id
+
+#### Get your user id
 
 Talk to the [userinfobot](https://telegram.me/userinfobot)
 
 Get your "Id", you will use it for the config parameter `chat_id`.
 
+#### Use Group id
+
+You can use bots in telegram groups by just adding them to the group. You can find the group id by first adding a [RawDataBot](https://telegram.me/rawdatabot) to your group. The Group id is shown as id in the `"chat"` section, which the RawDataBot will send to you:
+
+``` json
+"chat":{
+   "id":-1001332619709
+}
+```
+
+For the Freqtrade configuration, you can then use the the full value (including `-` if it's there) as string:
+
+```json
+   "chat_id": "-1001332619709"
+```
+
+## Control telegram noise
+
+Freqtrade provides means to control the verbosity of your telegram bot.
+Each setting has the following possible values:
+
+* `on` - Messages will be sent, and user will be notified.
+* `silent` - Message will be sent, Notification will be without sound / vibration.
+* `off` - Skip sending a message-type all together.
+
+Example configuration showing the different settings:
+
+``` json
+"telegram": {
+      "enabled": true,
+      "token": "your_telegram_token",
+      "chat_id": "your_telegram_chat_id",
+      "notification_settings": {
+         "status": "silent",
+         "warning": "on",
+         "startup": "off",
+         "buy": "silent",
+         "sell": "on",
+         "buy_cancel": "silent",
+         "sell_cancel": "on"
+      }
+   },
+```
+
 ## Telegram commands
 
 Per default, the Telegram bot shows predefined commands. Some commands
 are only available by sending them to the bot. The table below list the
 official commands. You can ask at any moment for help with `/help`.
 
-|  Command | Default | Description |
-|----------|---------|-------------|
-| `/start` | | Starts the trader
-| `/stop` | | Stops the trader
-| `/stopbuy` | | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
-| `/reload_conf` | | Reloads the configuration file
-| `/status` | | Lists all open trades
-| `/status table` | | List all open trades in a table format
-| `/count` | | Displays number of trades used and available
-| `/profit` | | Display a summary of your profit/loss from close trades and some stats about your performance
-| `/forcesell <trade_id>` | | Instantly sells the given trade  (Ignoring `minimum_roi`).
-| `/forcesell all` | | Instantly sells all open trades (Ignoring `minimum_roi`).
-| `/forcebuy <pair> [rate]` | | Instantly buys the given pair. Rate is optional. (`forcebuy_enable` must be set to True)
-| `/performance` | | Show performance of each finished trade grouped by pair
-| `/balance` | | Show account balance per currency
-| `/daily <n>` | 7 | Shows profit or loss per day, over the last n days
-| `/whitelist` | | Show the current whitelist
-| `/blacklist [pair]` | | Show the current blacklist, or adds a pair to the blacklist.
-| `/edge` | | Show validated pairs by Edge if it is enabled.
-| `/help` | | Show help message
-| `/version` | | Show version
+|  Command | Description |
+|----------|-------------|
+| `/start` | Starts the trader
+| `/stop` | Stops the trader
+| `/stopbuy` | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
+| `/reload_config` | Reloads the configuration file
+| `/show_config` | Shows part of the current configuration with relevant settings to operation
+| `/logs [limit]` | Show last log messages.
+| `/status` | Lists all open trades
+| `/status table` | List all open trades in a table format. Pending buy orders are marked with an asterisk (*) Pending sell orders are marked with a double asterisk (**)
+| `/trades [limit]` | List all recently closed trades in a table format.
+| `/delete <trade_id>` | Delete a specific trade from the Database. Tries to close open orders. Requires manual handling of this trade on the exchange.
+| `/count` | Displays number of trades used and available
+| `/profit` | Display a summary of your profit/loss from close trades and some stats about your performance
+| `/forcesell <trade_id>` | Instantly sells the given trade  (Ignoring `minimum_roi`).
+| `/forcesell all` | Instantly sells all open trades (Ignoring `minimum_roi`).
+| `/forcebuy <pair> [rate]` | Instantly buys the given pair. Rate is optional. (`forcebuy_enable` must be set to True)
+| `/performance` | Show performance of each finished trade grouped by pair
+| `/balance` | Show account balance per currency
+| `/daily <n>` | Shows profit or loss per day, over the last n days (n defaults to 7)
+| `/whitelist` | Show the current whitelist
+| `/blacklist [pair]` | Show the current blacklist, or adds a pair to the blacklist.
+| `/edge` | Show validated pairs by Edge if it is enabled.
+| `/help` | Show help message
+| `/version` | Show version
 
 ## Telegram commands in action
 
@@ -84,16 +134,16 @@ Below, example of Telegram message you will receive for each command.
 
 ### /stopbuy
 
-> **status:** `Setting max_open_trades to 0. Run /reload_conf to reset.`
+> **status:** `Setting max_open_trades to 0. Run /reload_config to reset.`
 
 Prevents the bot from opening new trades by temporarily setting "max_open_trades" to 0. Open trades will be handled via their regular rules (ROI / Sell-signal, stoploss, ...).
 
 After this, give the bot time to close off open trades (can be checked via `/status table`).
 Once all positions are sold, run `/stop` to completely stop the bot.
 
-`/reload_conf` resets "max_open_trades" to the value set in the configuration and resets this command. 
+`/reload_config` resets "max_open_trades" to the value set in the configuration and resets this command.
 
-!!! warning
+!!! Warning
    The stop-buy signal is ONLY active while the bot is running, and is not persisted anyway, so restarting the bot will cause this to reset.
 
 ### /status
@@ -112,6 +162,7 @@ For each open trade, the bot will send you the following message.
 ### /status table
 
 Return the status of all open trades in a table format.
+
 ```
    ID  Pair      Since    Profit
 ----  --------  -------  --------
@@ -122,6 +173,7 @@ Return the status of all open trades in a table format.
 ### /count
 
 Return the number of trades used and available.
+
 ```
 current    max
 ---------  -----
@@ -207,15 +259,15 @@ Shows the current whitelist
 
 Shows the current blacklist.
 If Pair is set, then this pair will be added to the pairlist.
-Also supports multiple pairs, seperated by a space.
-Use `/reload_conf` to reset the blacklist.
+Also supports multiple pairs, separated by a space.
+Use `/reload_config` to reset the blacklist.
 
 > Using blacklist `StaticPairList` with 2 pairs  
 >`DODGE/BTC`, `HOT/BTC`.
 
 ### /edge
 
-Shows pairs validated by Edge along with their corresponding winrate, expectancy and stoploss values.
+Shows pairs validated by Edge along with their corresponding win-rate, expectancy and stoploss values.
 
 > **Edge only validated following pairs:**
 ```
diff --git a/docs/utils.md b/docs/utils.md
new file mode 100644
index 000000000..409bcc134
--- /dev/null
+++ b/docs/utils.md
@@ -0,0 +1,604 @@
+# Utility Subcommands
+
+Besides the Live-Trade and Dry-Run run modes, the `backtesting`, `edge` and `hyperopt` optimization subcommands, and the `download-data` subcommand which prepares historical data, the bot contains a number of utility subcommands. They are described in this section.
+
+## Create userdir
+
+Creates the directory structure to hold your files for freqtrade.
+Will also create strategy and hyperopt examples for you to get started.
+Can be used multiple times - using `--reset` will reset the sample strategy and hyperopt files to their default state. 
+
+```
+usage: freqtrade create-userdir [-h] [--userdir PATH] [--reset]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+  --reset               Reset sample files to their original state.
+```
+
+!!! Warning
+    Using `--reset` may result in loss of data, since this will overwrite all sample files without asking again.
+
+```
+├── backtest_results
+├── data
+├── hyperopt_results
+├── hyperopts
+│   ├── sample_hyperopt_advanced.py
+│   ├── sample_hyperopt_loss.py
+│   └── sample_hyperopt.py
+├── notebooks
+│   └── strategy_analysis_example.ipynb
+├── plot
+└── strategies
+    └── sample_strategy.py
+```
+
+## Create new config
+
+Creates a new configuration file, asking some questions which are important selections for a configuration.
+
+```
+usage: freqtrade new-config [-h] [-c PATH]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default: `config.json`). Multiple --config options may be used. Can be set to `-`
+                        to read config from stdin.
+```
+
+!!! Warning
+    Only vital questions are asked. Freqtrade offers a lot more configuration possibilities, which are listed in the [Configuration documentation](configuration.md#configuration-parameters)
+
+### Create config examples
+
+```
+$ freqtrade new-config --config config_binance.json
+
+? Do you want to enable Dry-run (simulated trades)?  Yes
+? Please insert your stake currency: BTC
+? Please insert your stake amount: 0.05
+? Please insert max_open_trades (Integer or 'unlimited'): 3
+? Please insert your desired timeframe (e.g. 5m): 5m
+? Please insert your display Currency (for reporting): USD
+? Select exchange  binance
+? Do you want to enable Telegram?  No
+```
+
+## Create new strategy
+
+Creates a new strategy from a template similar to SampleStrategy.
+The file will be named inline with your class name, and will not overwrite existing files.
+
+Results will be located in `user_data/strategies/<strategyclassname>.py`.
+
+``` output
+usage: freqtrade new-strategy [-h] [--userdir PATH] [-s NAME]
+                              [--template {full,minimal,advanced}]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+  -s NAME, --strategy NAME
+                        Specify strategy class name which will be used by the
+                        bot.
+  --template {full,minimal,advanced}
+                        Use a template which is either `minimal`, `full`
+                        (containing multiple sample indicators) or `advanced`.
+                        Default: `full`.
+
+```
+
+### Sample usage of new-strategy
+
+```bash
+freqtrade new-strategy --strategy AwesomeStrategy
+```
+
+With custom user directory
+
+```bash
+freqtrade new-strategy --userdir ~/.freqtrade/ --strategy AwesomeStrategy
+```
+
+Using the advanced template (populates all optional functions and methods)
+
+```bash
+freqtrade new-strategy --strategy AwesomeStrategy --template advanced
+```
+
+## Create new hyperopt
+
+Creates a new hyperopt from a template similar to SampleHyperopt.
+The file will be named inline with your class name, and will not overwrite existing files.
+
+Results will be located in `user_data/hyperopts/<classname>.py`.
+
+``` output
+usage: freqtrade new-hyperopt [-h] [--userdir PATH] [--hyperopt NAME]
+                              [--template {full,minimal,advanced}]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+  --hyperopt NAME       Specify hyperopt class name which will be used by the
+                        bot.
+  --template {full,minimal,advanced}
+                        Use a template which is either `minimal`, `full`
+                        (containing multiple sample indicators) or `advanced`.
+                        Default: `full`.
+```
+
+### Sample usage of new-hyperopt
+
+```bash
+freqtrade new-hyperopt --hyperopt AwesomeHyperopt
+```
+
+With custom user directory
+
+```bash
+freqtrade new-hyperopt --userdir ~/.freqtrade/ --hyperopt AwesomeHyperopt
+```
+
+## List Strategies and List Hyperopts
+
+Use the `list-strategies` subcommand to see all strategies in one particular directory and the `list-hyperopts` subcommand to list custom Hyperopts.
+
+These subcommands are useful for finding problems in your environment with loading strategies or hyperopt classes: modules with strategies or hyperopt classes that contain errors and failed to load are printed in red (LOAD FAILED), while strategies or hyperopt classes with duplicate names are printed in yellow (DUPLICATE NAME).
+
+```
+usage: freqtrade list-strategies [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                                 [-d PATH] [--userdir PATH]
+                                 [--strategy-path PATH] [-1] [--no-color]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --strategy-path PATH  Specify additional strategy lookup path.
+  -1, --one-column      Print output in one column.
+  --no-color            Disable colorization of hyperopt results. May be
+                        useful if you are redirecting output to a file.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default: `config.json`).
+                        Multiple --config options may be used. Can be set to
+                        `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+```
+```
+usage: freqtrade list-hyperopts [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                                [-d PATH] [--userdir PATH]
+                                [--hyperopt-path PATH] [-1] [--no-color]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --hyperopt-path PATH  Specify additional lookup path for Hyperopt and
+                        Hyperopt Loss functions.
+  -1, --one-column      Print output in one column.
+  --no-color            Disable colorization of hyperopt results. May be
+                        useful if you are redirecting output to a file.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default: `config.json`).
+                        Multiple --config options may be used. Can be set to
+                        `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+```
+
+!!! Warning
+    Using these commands will try to load all python files from a directory. This can be a security risk if untrusted files reside in this directory, since all module-level code is executed.
+
+Example: Search default strategies and hyperopts directories (within the default userdir).
+
+``` bash
+freqtrade list-strategies
+freqtrade list-hyperopts
+```
+
+Example: Search strategies and hyperopts directory within the userdir.
+
+``` bash
+freqtrade list-strategies --userdir ~/.freqtrade/
+freqtrade list-hyperopts --userdir ~/.freqtrade/
+```
+
+Example: Search dedicated strategy path.
+
+``` bash
+freqtrade list-strategies --strategy-path ~/.freqtrade/strategies/
+```
+
+Example: Search dedicated hyperopt path.
+
+``` bash
+freqtrade list-hyperopt --hyperopt-path ~/.freqtrade/hyperopts/
+```
+
+## List Exchanges
+
+Use the `list-exchanges` subcommand to see the exchanges available for the bot.
+
+```
+usage: freqtrade list-exchanges [-h] [-1] [-a]
+
+optional arguments:
+  -h, --help        show this help message and exit
+  -1, --one-column  Print output in one column.
+  -a, --all         Print all exchanges known to the ccxt library.
+```
+
+* Example: see exchanges available for the bot:
+```
+$ freqtrade list-exchanges
+Exchanges available for Freqtrade: _1btcxe, acx, allcoin, bequant, bibox, binance, binanceje, binanceus, bitbank, bitfinex, bitfinex2, bitkk, bitlish, bitmart, bittrex, bitz, bleutrade, btcalpha, btcmarkets, btcturk, buda, cex, cobinhood, coinbaseprime, coinbasepro, coinex, cointiger, coss, crex24, digifinex, dsx, dx, ethfinex, fcoin, fcoinjp, gateio, gdax, gemini, hitbtc2, huobipro, huobiru, idex, kkex, kraken, kucoin, kucoin2, kuna, lbank, mandala, mercado, oceanex, okcoincny, okcoinusd, okex, okex3, poloniex, rightbtc, theocean, tidebit, upbit, zb
+```
+
+* Example: see all exchanges supported by the ccxt library (including 'bad' ones, i.e. those that are known to not work with Freqtrade):
+```
+$ freqtrade list-exchanges -a
+All exchanges supported by the ccxt library: _1btcxe, acx, adara, allcoin, anxpro, bcex, bequant, bibox, bigone, binance, binanceje, binanceus, bit2c, bitbank, bitbay, bitfinex, bitfinex2, bitflyer, bitforex, bithumb, bitkk, bitlish, bitmart, bitmex, bitso, bitstamp, bitstamp1, bittrex, bitz, bl3p, bleutrade, braziliex, btcalpha, btcbox, btcchina, btcmarkets, btctradeim, btctradeua, btcturk, buda, bxinth, cex, chilebit, cobinhood, coinbase, coinbaseprime, coinbasepro, coincheck, coinegg, coinex, coinexchange, coinfalcon, coinfloor, coingi, coinmarketcap, coinmate, coinone, coinspot, cointiger, coolcoin, coss, crex24, crypton, deribit, digifinex, dsx, dx, ethfinex, exmo, exx, fcoin, fcoinjp, flowbtc, foxbit, fybse, gateio, gdax, gemini, hitbtc, hitbtc2, huobipro, huobiru, ice3x, idex, independentreserve, indodax, itbit, kkex, kraken, kucoin, kucoin2, kuna, lakebtc, latoken, lbank, liquid, livecoin, luno, lykke, mandala, mercado, mixcoins, negociecoins, nova, oceanex, okcoincny, okcoinusd, okex, okex3, paymium, poloniex, rightbtc, southxchange, stronghold, surbitcoin, theocean, therock, tidebit, tidex, upbit, vaultoro, vbtc, virwox, xbtce, yobit, zaif, zb
+```
+
+## List Timeframes
+
+Use the `list-timeframes` subcommand to see the list of timeframes (ticker intervals) available for the exchange.
+
+```
+usage: freqtrade list-timeframes [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH] [--userdir PATH] [--exchange EXCHANGE] [-1]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --exchange EXCHANGE   Exchange name (default: `bittrex`). Only valid if no config is provided.
+  -1, --one-column      Print output in one column.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are: 'syslog', 'journald'. See the documentation for more details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default: `config.json`). Multiple --config options may be used. Can be set to `-`
+                        to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+```
+
+* Example: see the timeframes for the 'binance' exchange, set in the configuration file:
+
+```
+$ freqtrade list-timeframes -c config_binance.json
+...
+Timeframes available for the exchange `binance`: 1m, 3m, 5m, 15m, 30m, 1h, 2h, 4h, 6h, 8h, 12h, 1d, 3d, 1w, 1M
+```
+
+* Example: enumerate exchanges available for Freqtrade and print timeframes supported by each of them:
+```
+$ for i in `freqtrade list-exchanges -1`; do freqtrade list-timeframes --exchange $i; done
+```
+
+## List pairs/list markets
+
+The `list-pairs` and `list-markets` subcommands allow to see the pairs/markets available on exchange.
+
+Pairs are markets with the '/' character between the base currency part and the quote currency part in the market symbol.
+For example, in the 'ETH/BTC' pair 'ETH' is the base currency, while 'BTC' is the quote currency.
+
+For pairs traded by Freqtrade the pair quote currency is defined by the value of the `stake_currency` configuration setting.
+
+You can print info about any pair/market with these subcommands - and you can filter output by quote-currency using `--quote BTC`, or by base-currency using `--base ETH` options correspondingly.
+
+These subcommands have same usage and same set of available options:
+
+```
+usage: freqtrade list-markets [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                              [-d PATH] [--userdir PATH] [--exchange EXCHANGE]
+                              [--print-list] [--print-json] [-1] [--print-csv]
+                              [--base BASE_CURRENCY [BASE_CURRENCY ...]]
+                              [--quote QUOTE_CURRENCY [QUOTE_CURRENCY ...]]
+                              [-a]
+
+usage: freqtrade list-pairs [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                            [-d PATH] [--userdir PATH] [--exchange EXCHANGE]
+                            [--print-list] [--print-json] [-1] [--print-csv]
+                            [--base BASE_CURRENCY [BASE_CURRENCY ...]]
+                            [--quote QUOTE_CURRENCY [QUOTE_CURRENCY ...]] [-a]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --exchange EXCHANGE   Exchange name (default: `bittrex`). Only valid if no
+                        config is provided.
+  --print-list          Print list of pairs or market symbols. By default data
+                        is printed in the tabular format.
+  --print-json          Print list of pairs or market symbols in JSON format.
+  -1, --one-column      Print output in one column.
+  --print-csv           Print exchange pair or market data in the csv format.
+  --base BASE_CURRENCY [BASE_CURRENCY ...]
+                        Specify base currency(-ies). Space-separated list.
+  --quote QUOTE_CURRENCY [QUOTE_CURRENCY ...]
+                        Specify quote currency(-ies). Space-separated list.
+  -a, --all             Print all pairs or market symbols. By default only
+                        active ones are shown.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default: `config.json`).
+                        Multiple --config options may be used. Can be set to
+                        `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+```
+
+By default, only active pairs/markets are shown. Active pairs/markets are those that can currently be traded
+on the exchange. The see the list of all pairs/markets (not only the active ones), use the `-a`/`-all` option.
+
+Pairs/markets are sorted by its symbol string in the printed output.
+
+### Examples
+
+* Print the list of active pairs with quote currency USD on exchange, specified in the default
+configuration file (i.e. pairs on the "Bittrex" exchange) in JSON format:
+
+```
+$ freqtrade list-pairs --quote USD --print-json
+```
+
+* Print the list of all pairs on the exchange, specified in the `config_binance.json` configuration file
+(i.e. on the "Binance" exchange) with base currencies BTC or ETH and quote currencies USDT or USD, as the
+human-readable list with summary:
+
+```
+$ freqtrade list-pairs -c config_binance.json --all --base BTC ETH --quote USDT USD --print-list
+```
+
+* Print all markets on exchange "Kraken", in the tabular format:
+
+```
+$ freqtrade list-markets --exchange kraken --all
+```
+
+## Test pairlist
+
+Use the `test-pairlist` subcommand to test the configuration of [dynamic pairlists](configuration.md#pairlists).
+
+Requires a configuration with specified `pairlists` attribute.
+Can be used to generate static pairlists to be used during backtesting / hyperopt.
+
+```
+usage: freqtrade test-pairlist [-h] [-c PATH]
+                               [--quote QUOTE_CURRENCY [QUOTE_CURRENCY ...]]
+                               [-1] [--print-json]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default: `config.json`).
+                        Multiple --config options may be used. Can be set to
+                        `-` to read config from stdin.
+  --quote QUOTE_CURRENCY [QUOTE_CURRENCY ...]
+                        Specify quote currency(-ies). Space-separated list.
+  -1, --one-column      Print output in one column.
+  --print-json          Print list of pairs or market symbols in JSON format.
+```
+
+### Examples
+
+Show whitelist when using a [dynamic pairlist](configuration.md#pairlists).
+
+```
+freqtrade test-pairlist --config config.json --quote USDT BTC
+```
+
+## List Hyperopt results
+
+You can list the hyperoptimization epochs the Hyperopt module evaluated previously with the `hyperopt-list` sub-command.
+
+```
+usage: freqtrade hyperopt-list [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                               [-d PATH] [--userdir PATH] [--best]
+                               [--profitable] [--min-trades INT]
+                               [--max-trades INT] [--min-avg-time FLOAT]
+                               [--max-avg-time FLOAT] [--min-avg-profit FLOAT]
+                               [--max-avg-profit FLOAT]
+                               [--min-total-profit FLOAT]
+                               [--max-total-profit FLOAT]
+                               [--min-objective FLOAT] [--max-objective FLOAT]
+                               [--no-color] [--print-json] [--no-details]
+                               [--hyperopt-filename PATH] [--export-csv FILE]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --best                Select only best epochs.
+  --profitable          Select only profitable epochs.
+  --min-trades INT      Select epochs with more than INT trades.
+  --max-trades INT      Select epochs with less than INT trades.
+  --min-avg-time FLOAT  Select epochs above average time.
+  --max-avg-time FLOAT  Select epochs below average time.
+  --min-avg-profit FLOAT
+                        Select epochs above average profit.
+  --max-avg-profit FLOAT
+                        Select epochs below average profit.
+  --min-total-profit FLOAT
+                        Select epochs above total profit.
+  --max-total-profit FLOAT
+                        Select epochs below total profit.
+  --min-objective FLOAT
+                        Select epochs above objective.
+  --max-objective FLOAT
+                        Select epochs below objective.
+  --no-color            Disable colorization of hyperopt results. May be
+                        useful if you are redirecting output to a file.
+  --print-json          Print output in JSON format.
+  --no-details          Do not print best epoch details.
+  --hyperopt-filename FILENAME
+                        Hyperopt result filename.Example: `--hyperopt-
+                        filename=hyperopt_results_2020-09-27_16-20-48.pickle`
+  --export-csv FILE     Export to CSV-File. This will disable table print.
+                        Example: --export-csv hyperopt.csv
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+```
+
+!!! Note
+    `hyperopt-list` will automatically use the latest available hyperopt results file.
+    You can override this using the `--hyperopt-filename` argument, and specify another, available filename (without path!).
+
+### Examples
+
+List all results, print details of the best result at the end:
+```
+freqtrade hyperopt-list
+```
+
+List only epochs with positive profit. Do not print the details of the best epoch, so that the list can be iterated in a script:
+```
+freqtrade hyperopt-list --profitable --no-details
+```
+
+## Show details of Hyperopt results
+
+You can show the details of any hyperoptimization epoch previously evaluated by the Hyperopt module with the `hyperopt-show` subcommand.
+
+```
+usage: freqtrade hyperopt-show [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                               [-d PATH] [--userdir PATH] [--best]
+                               [--profitable] [-n INT] [--print-json]
+                               [--hyperopt-filename PATH] [--no-header]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --best                Select only best epochs.
+  --profitable          Select only profitable epochs.
+  -n INT, --index INT   Specify the index of the epoch to print details for.
+  --print-json          Print output in JSON format.
+  --hyperopt-filename FILENAME
+                        Hyperopt result filename.Example: `--hyperopt-
+                        filename=hyperopt_results_2020-09-27_16-20-48.pickle`
+  --no-header           Do not print epoch details header.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+```
+
+!!! Note
+    `hyperopt-show` will automatically use the latest available hyperopt results file.
+    You can override this using the `--hyperopt-filename` argument, and specify another, available filename (without path!).
+
+### Examples
+
+Print details for the epoch 168 (the number of the epoch is shown by the `hyperopt-list` subcommand or by Hyperopt itself during hyperoptimization run):
+
+```
+freqtrade hyperopt-show -n 168
+```
+
+Prints JSON data with details for the last best epoch (i.e., the best of all epochs):
+
+```
+freqtrade hyperopt-show --best -n -1 --print-json --no-header
+```
+
+## Show trades
+
+Print selected (or all) trades from database to screen.
+
+```
+usage: freqtrade show-trades [-h] [-v] [--logfile FILE] [-V] [-c PATH]
+                             [-d PATH] [--userdir PATH] [--db-url PATH]
+                             [--trade-ids TRADE_IDS [TRADE_IDS ...]]
+                             [--print-json]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --db-url PATH         Override trades database URL, this is useful in custom
+                        deployments (default: `sqlite:///tradesv3.sqlite` for
+                        Live Run mode, `sqlite:///tradesv3.dryrun.sqlite` for
+                        Dry Run).
+  --trade-ids TRADE_IDS [TRADE_IDS ...]
+                        Specify the list of trade ids.
+  --print-json          Print output in JSON format.
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+```
+
+### Examples
+
+Print trades with id 2 and 3 as json
+
+``` bash
+freqtrade show-trades --db-url sqlite:///tradesv3.sqlite --trade-ids 2 3 --print-json
+```
diff --git a/docs/webhook-config.md b/docs/webhook-config.md
index 112f8a77e..db6d4d1ef 100644
--- a/docs/webhook-config.md
+++ b/docs/webhook-config.md
@@ -15,10 +15,20 @@ Sample configuration (tested using IFTTT).
             "value2": "limit {limit:8f}",
             "value3": "{stake_amount:8f} {stake_currency}"
         },
+        "webhookbuycancel": {
+            "value1": "Cancelling Open Buy Order for {pair}",
+            "value2": "limit {limit:8f}",
+            "value3": "{stake_amount:8f} {stake_currency}"
+        },
         "webhooksell": {
             "value1": "Selling {pair}",
             "value2": "limit {limit:8f}",
-            "value3": "profit: {profit_amount:8f} {stake_currency}"
+            "value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})"
+        },
+        "webhooksellcancel": {
+            "value1": "Cancelling Open Sell Order for {pair}",
+            "value2": "limit {limit:8f}",
+            "value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})"
         },
         "webhookstatus": {
             "value1": "Status: {status}",
@@ -37,19 +47,41 @@ Different payloads can be configured for different events. Not all fields are ne
 The fields in `webhook.webhookbuy` are filled when the bot executes a buy. Parameters are filled using string.format.
 Possible parameters are:
 
+* `trade_id`
 * `exchange`
 * `pair`
 * `limit`
+* `amount`
+* `open_date`
 * `stake_amount`
 * `stake_currency`
 * `fiat_currency`
 * `order_type`
+* `current_rate`
+
+### Webhookbuycancel
+
+The fields in `webhook.webhookbuycancel` are filled when the bot cancels a buy order. Parameters are filled using string.format.
+Possible parameters are:
+
+* `trade_id`
+* `exchange`
+* `pair`
+* `limit`
+* `amount`
+* `open_date`
+* `stake_amount`
+* `stake_currency`
+* `fiat_currency`
+* `order_type`
+* `current_rate`
 
 ### Webhooksell
 
 The fields in `webhook.webhooksell` are filled when the bot sells a trade. Parameters are filled using string.format.
 Possible parameters are:
 
+* `trade_id`
 * `exchange`
 * `pair`
 * `gain`
@@ -58,11 +90,35 @@ Possible parameters are:
 * `open_rate`
 * `current_rate`
 * `profit_amount`
-* `profit_percent`
+* `profit_ratio`
 * `stake_currency`
 * `fiat_currency`
 * `sell_reason`
 * `order_type`
+* `open_date`
+* `close_date`
+
+### Webhooksellcancel
+
+The fields in `webhook.webhooksellcancel` are filled when the bot cancels a sell order. Parameters are filled using string.format.
+Possible parameters are:
+
+* `trade_id`
+* `exchange`
+* `pair`
+* `gain`
+* `limit`
+* `amount`
+* `open_rate`
+* `current_rate`
+* `profit_amount`
+* `profit_ratio`
+* `stake_currency`
+* `fiat_currency`
+* `sell_reason`
+* `order_type`
+* `open_date`
+* `close_date`
 
 ### Webhookstatus
 
diff --git a/docs/windows_installation.md b/docs/windows_installation.md
new file mode 100644
index 000000000..5341ce96b
--- /dev/null
+++ b/docs/windows_installation.md
@@ -0,0 +1,57 @@
+We **strongly** recommend that Windows users use [Docker](docker.md) as this will work much easier and smoother (also more secure).
+
+If that is not possible, try using the Windows Linux subsystem (WSL) - for which the Ubuntu instructions should work.
+Otherwise, try the instructions below.
+
+## Install freqtrade manually
+
+!!! Note
+    Make sure to use 64bit Windows and 64bit Python to avoid problems with backtesting or hyperopt due to the memory constraints 32bit applications have under Windows.
+
+!!! Hint
+    Using the [Anaconda Distribution](https://www.anaconda.com/distribution/) under Windows can greatly help with installation problems. Check out the [Anaconda installation section](installation.md#Anaconda) in this document for more information.
+
+### 1. Clone the git repository
+
+```bash
+git clone https://github.com/freqtrade/freqtrade.git
+```
+
+### 2. Install ta-lib
+
+Install ta-lib according to the [ta-lib documentation](https://github.com/mrjbq7/ta-lib#windows).
+
+As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial precompiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which needs to be downloaded and installed using `pip install TA_Lib‑0.4.19‑cp38‑cp38‑win_amd64.whl` (make sure to use the version matching your python version)
+
+Freqtrade provides these dependencies for the latest 2 Python versions (3.7 and 3.8) and for 64bit Windows.
+Other versions must be downloaded from the above link.
+
+``` powershell
+cd \path\freqtrade
+python -m venv .env
+.env\Scripts\activate.ps1
+# optionally install ta-lib from wheel
+# Eventually adjust the below filename to match the downloaded wheel
+pip install build_helpers/TA_Lib-0.4.19-cp38-cp38-win_amd64.whl
+pip install -r requirements.txt
+pip install -e .
+freqtrade
+```
+
+!!! Note "Use Powershell"
+    The above installation script assumes you're using powershell on a 64bit windows.
+    Commands for the legacy CMD windows console may differ.
+
+> Thanks [Owdr](https://github.com/Owdr) for the commands. Source: [Issue #222](https://github.com/freqtrade/freqtrade/issues/222)
+
+### Error during installation on Windows
+
+``` bash
+error: Microsoft Visual C++ 14.0 is required. Get it with "Microsoft Visual C++ Build Tools": http://landinghub.visualstudio.com/visual-cpp-build-tools
+```
+
+Unfortunately, many packages requiring compilation don't provide a pre-built wheel. It is therefore mandatory to have a C/C++ compiler installed and available for your python environment to use.
+
+The easiest way is to download install Microsoft Visual Studio Community [here](https://visualstudio.microsoft.com/downloads/) and make sure to install "Common Tools for Visual C++" to enable building C code on Windows. Unfortunately, this is a heavy download / dependency (~4Gb) so you might want to consider WSL or [docker](docker.md) first.
+
+---
diff --git a/environment.yml b/environment.yml
new file mode 100644
index 000000000..86ea03519
--- /dev/null
+++ b/environment.yml
@@ -0,0 +1,60 @@
+name: freqtrade
+channels:
+  - defaults
+  - conda-forge
+dependencies:
+  # Required for app
+  - python>=3.6
+  - pip
+  - wheel
+  - numpy
+  - pandas
+  - SQLAlchemy
+  - arrow
+  - requests
+  - urllib3
+  - wrapt
+  - jsonschema
+  - tabulate
+  - python-rapidjson
+  - flask
+  - python-dotenv
+  - cachetools
+  - python-telegram-bot
+  # Optional for plotting
+  - plotly
+  # Optional for hyperopt
+  - scipy
+  - scikit-optimize
+  - scikit-learn
+  - filelock
+  - joblib
+  # Optional for development
+  - flake8
+  - pytest
+  - pytest-mock
+  - pytest-asyncio
+  - pytest-cov
+  - coveralls
+  - mypy
+  # Useful for jupyter
+  - jupyter
+  - ipykernel
+  - isort
+  - yapf
+  - pip:
+    # Required for app
+    - cython
+    - pycoingecko
+    - ccxt
+    - TA-Lib
+    - py_find_1st
+    - sdnotify
+    # Optional for develpment
+    - flake8-tidy-imports
+    - flake8-type-annotations
+    - pytest-random-order
+    - -e .
+
+
+
diff --git a/freqtrade.service b/freqtrade.service
index 9de9f13c7..df220ed39 100644
--- a/freqtrade.service
+++ b/freqtrade.service
@@ -6,7 +6,7 @@ After=network.target
 # Set WorkingDirectory and ExecStart to your file paths accordingly
 # NOTE: %h will be resolved to /home/<username>
 WorkingDirectory=%h/freqtrade
-ExecStart=/usr/bin/freqtrade
+ExecStart=/usr/bin/freqtrade trade
 Restart=on-failure
 
 [Install]
diff --git a/freqtrade.service.watchdog b/freqtrade.service.watchdog
index ba491fa53..66ea00d76 100644
--- a/freqtrade.service.watchdog
+++ b/freqtrade.service.watchdog
@@ -6,7 +6,7 @@ After=network.target
 # Set WorkingDirectory and ExecStart to your file paths accordingly
 # NOTE: %h will be resolved to /home/<username>
 WorkingDirectory=%h/freqtrade
-ExecStart=/usr/bin/freqtrade --sd-notify
+ExecStart=/usr/bin/freqtrade trade --sd-notify
 
 Restart=always
 #Restart=on-failure
diff --git a/freqtrade/__init__.py b/freqtrade/__init__.py
index 2fdcccea5..e96e7f530 100644
--- a/freqtrade/__init__.py
+++ b/freqtrade/__init__.py
@@ -1,33 +1,34 @@
-""" FreqTrade bot """
-__version__ = '2019.6-dev'
+""" Freqtrade bot """
+__version__ = 'develop'
 
+if __version__ == 'develop':
 
-class DependencyException(Exception):
-    """
-    Indicates that an assumed dependency is not met.
-    This could happen when there is currently not enough money on the account.
-    """
+    try:
+        import subprocess
 
+        __version__ = 'develop-' + subprocess.check_output(
+            ['git', 'log', '--format="%h"', '-n 1'],
+            stderr=subprocess.DEVNULL).decode("utf-8").rstrip().strip('"')
 
-class OperationalException(Exception):
-    """
-    Requires manual intervention.
-    This happens when an exchange returns an unexpected error during runtime
-    or given configuration is invalid.
-    """
+        # from datetime import datetime
+        # last_release = subprocess.check_output(
+        #     ['git', 'tag']
+        # ).decode('utf-8').split()[-1].split(".")
+        # # Releases are in the format "2020.1" - we increment the latest version for dev.
+        # prefix = f"{last_release[0]}.{int(last_release[1]) + 1}"
+        # dev_version = int(datetime.now().timestamp() // 1000)
+        # __version__ = f"{prefix}.dev{dev_version}"
 
-
-class InvalidOrderException(Exception):
-    """
-    This is returned when the order is not valid. Example:
-    If stoploss on exchange order is hit, then trying to cancel the order
-    should return this exception.
-    """
-
-
-class TemporaryError(Exception):
-    """
-    Temporary network or exchange related error.
-    This could happen when an exchange is congested, unavailable, or the user
-    has networking problems. Usually resolves itself after a time.
-    """
+        #  subprocess.check_output(
+        #     ['git', 'log', '--format="%h"', '-n 1'],
+        #     stderr=subprocess.DEVNULL).decode("utf-8").rstrip().strip('"')
+    except Exception:
+        # git not available, ignore
+        try:
+            # Try Fallback to freqtrade_commit file (created by CI while building docker image)
+            from pathlib import Path
+            versionfile = Path('./freqtrade_commit')
+            if versionfile.is_file():
+                __version__ = f"docker-{versionfile.read_text()[:8]}"
+        except Exception:
+            pass
diff --git a/freqtrade/__main__.py b/freqtrade/__main__.py
index 97ed9ae67..881a2f562 100644
--- a/freqtrade/__main__.py
+++ b/freqtrade/__main__.py
@@ -8,5 +8,6 @@ To launch Freqtrade as a module
 
 from freqtrade import main
 
+
 if __name__ == '__main__':
     main.main()
diff --git a/freqtrade/commands/__init__.py b/freqtrade/commands/__init__.py
new file mode 100644
index 000000000..21c5d6812
--- /dev/null
+++ b/freqtrade/commands/__init__.py
@@ -0,0 +1,22 @@
+# flake8: noqa: F401
+"""
+Commands module.
+Contains all start-commands, subcommands and CLI Interface creation.
+
+Note: Be careful with file-scoped imports in these subfiles.
+    as they are parsed on startup, nothing containing optional modules should be loaded.
+"""
+from freqtrade.commands.arguments import Arguments
+from freqtrade.commands.build_config_commands import start_new_config
+from freqtrade.commands.data_commands import (start_convert_data, start_download_data,
+                                              start_list_data)
+from freqtrade.commands.deploy_commands import (start_create_userdir, start_new_hyperopt,
+                                                start_new_strategy)
+from freqtrade.commands.hyperopt_commands import start_hyperopt_list, start_hyperopt_show
+from freqtrade.commands.list_commands import (start_list_exchanges, start_list_hyperopts,
+                                              start_list_markets, start_list_strategies,
+                                              start_list_timeframes, start_show_trades)
+from freqtrade.commands.optimize_commands import start_backtesting, start_edge, start_hyperopt
+from freqtrade.commands.pairlist_commands import start_test_pairlist
+from freqtrade.commands.plot_commands import start_plot_dataframe, start_plot_profit
+from freqtrade.commands.trade_commands import start_trading
diff --git a/freqtrade/commands/arguments.py b/freqtrade/commands/arguments.py
new file mode 100644
index 000000000..aa58ff585
--- /dev/null
+++ b/freqtrade/commands/arguments.py
@@ -0,0 +1,371 @@
+"""
+This module contains the argument manager class
+"""
+import argparse
+from functools import partial
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+
+from freqtrade.commands.cli_options import AVAILABLE_CLI_OPTIONS
+from freqtrade.constants import DEFAULT_CONFIG
+
+
+ARGS_COMMON = ["verbosity", "logfile", "version", "config", "datadir", "user_data_dir"]
+
+ARGS_STRATEGY = ["strategy", "strategy_path"]
+
+ARGS_TRADE = ["db_url", "sd_notify", "dry_run"]
+
+ARGS_COMMON_OPTIMIZE = ["timeframe", "timerange", "dataformat_ohlcv",
+                        "max_open_trades", "stake_amount", "fee"]
+
+ARGS_BACKTEST = ARGS_COMMON_OPTIMIZE + ["position_stacking", "use_max_market_positions",
+                                        "strategy_list", "export", "exportfilename"]
+
+ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path",
+                                        "position_stacking", "epochs", "spaces",
+                                        "use_max_market_positions", "print_all",
+                                        "print_colorized", "print_json", "hyperopt_jobs",
+                                        "hyperopt_random_state", "hyperopt_min_trades",
+                                        "hyperopt_loss"]
+
+ARGS_EDGE = ARGS_COMMON_OPTIMIZE + ["stoploss_range"]
+
+ARGS_LIST_STRATEGIES = ["strategy_path", "print_one_column", "print_colorized"]
+
+ARGS_LIST_HYPEROPTS = ["hyperopt_path", "print_one_column", "print_colorized"]
+
+ARGS_LIST_EXCHANGES = ["print_one_column", "list_exchanges_all"]
+
+ARGS_LIST_TIMEFRAMES = ["exchange", "print_one_column"]
+
+ARGS_LIST_PAIRS = ["exchange", "print_list", "list_pairs_print_json", "print_one_column",
+                   "print_csv", "base_currencies", "quote_currencies", "list_pairs_all"]
+
+ARGS_TEST_PAIRLIST = ["config", "quote_currencies", "print_one_column", "list_pairs_print_json"]
+
+ARGS_CREATE_USERDIR = ["user_data_dir", "reset"]
+
+ARGS_BUILD_CONFIG = ["config"]
+
+ARGS_BUILD_STRATEGY = ["user_data_dir", "strategy", "template"]
+
+ARGS_BUILD_HYPEROPT = ["user_data_dir", "hyperopt", "template"]
+
+ARGS_CONVERT_DATA = ["pairs", "format_from", "format_to", "erase"]
+ARGS_CONVERT_DATA_OHLCV = ARGS_CONVERT_DATA + ["timeframes"]
+
+ARGS_LIST_DATA = ["exchange", "dataformat_ohlcv", "pairs"]
+
+ARGS_DOWNLOAD_DATA = ["pairs", "pairs_file", "days", "timerange", "download_trades", "exchange",
+                      "timeframes", "erase", "dataformat_ohlcv", "dataformat_trades"]
+
+ARGS_PLOT_DATAFRAME = ["pairs", "indicators1", "indicators2", "plot_limit",
+                       "db_url", "trade_source", "export", "exportfilename",
+                       "timerange", "timeframe", "no_trades"]
+
+ARGS_PLOT_PROFIT = ["pairs", "timerange", "export", "exportfilename", "db_url",
+                    "trade_source", "timeframe"]
+
+ARGS_SHOW_TRADES = ["db_url", "trade_ids", "print_json"]
+
+ARGS_HYPEROPT_LIST = ["hyperopt_list_best", "hyperopt_list_profitable",
+                      "hyperopt_list_min_trades", "hyperopt_list_max_trades",
+                      "hyperopt_list_min_avg_time", "hyperopt_list_max_avg_time",
+                      "hyperopt_list_min_avg_profit", "hyperopt_list_max_avg_profit",
+                      "hyperopt_list_min_total_profit", "hyperopt_list_max_total_profit",
+                      "hyperopt_list_min_objective", "hyperopt_list_max_objective",
+                      "print_colorized", "print_json", "hyperopt_list_no_details",
+                      "hyperoptexportfilename", "export_csv"]
+
+ARGS_HYPEROPT_SHOW = ["hyperopt_list_best", "hyperopt_list_profitable", "hyperopt_show_index",
+                      "print_json", "hyperoptexportfilename", "hyperopt_show_no_header"]
+
+NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes",
+                    "list-markets", "list-pairs", "list-strategies", "list-data",
+                    "list-hyperopts", "hyperopt-list", "hyperopt-show",
+                    "plot-dataframe", "plot-profit", "show-trades"]
+
+NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-hyperopt", "new-strategy"]
+
+
+class Arguments:
+    """
+    Arguments Class. Manage the arguments received by the cli
+    """
+
+    def __init__(self, args: Optional[List[str]]) -> None:
+        self.args = args
+        self._parsed_arg: Optional[argparse.Namespace] = None
+
+    def get_parsed_arg(self) -> Dict[str, Any]:
+        """
+        Return the list of arguments
+        :return: List[str] List of arguments
+        """
+        if self._parsed_arg is None:
+            self._build_subcommands()
+            self._parsed_arg = self._parse_args()
+
+        return vars(self._parsed_arg)
+
+    def _parse_args(self) -> argparse.Namespace:
+        """
+        Parses given arguments and returns an argparse Namespace instance.
+        """
+        parsed_arg = self.parser.parse_args(self.args)
+
+        # Workaround issue in argparse with action='append' and default value
+        # (see https://bugs.python.org/issue16399)
+        # Allow no-config for certain commands (like downloading / plotting)
+        if ('config' in parsed_arg and parsed_arg.config is None):
+            conf_required = ('command' in parsed_arg and parsed_arg.command in NO_CONF_REQURIED)
+
+            if 'user_data_dir' in parsed_arg and parsed_arg.user_data_dir is not None:
+                user_dir = parsed_arg.user_data_dir
+            else:
+                # Default case
+                user_dir = 'user_data'
+                # Try loading from "user_data/config.json"
+            cfgfile = Path(user_dir) / DEFAULT_CONFIG
+            if cfgfile.is_file():
+                parsed_arg.config = [str(cfgfile)]
+            else:
+                # Else use "config.json".
+                cfgfile = Path.cwd() / DEFAULT_CONFIG
+                if cfgfile.is_file() or not conf_required:
+                    parsed_arg.config = [DEFAULT_CONFIG]
+
+        return parsed_arg
+
+    def _build_args(self, optionlist, parser):
+
+        for val in optionlist:
+            opt = AVAILABLE_CLI_OPTIONS[val]
+            parser.add_argument(*opt.cli, dest=val, **opt.kwargs)
+
+    def _build_subcommands(self) -> None:
+        """
+        Builds and attaches all subcommands.
+        :return: None
+        """
+        # Build shared arguments (as group Common Options)
+        _common_parser = argparse.ArgumentParser(add_help=False)
+        group = _common_parser.add_argument_group("Common arguments")
+        self._build_args(optionlist=ARGS_COMMON, parser=group)
+
+        _strategy_parser = argparse.ArgumentParser(add_help=False)
+        strategy_group = _strategy_parser.add_argument_group("Strategy arguments")
+        self._build_args(optionlist=ARGS_STRATEGY, parser=strategy_group)
+
+        # Build main command
+        self.parser = argparse.ArgumentParser(description='Free, open source crypto trading bot')
+        self._build_args(optionlist=['version'], parser=self.parser)
+
+        from freqtrade.commands import (start_backtesting, start_convert_data, start_create_userdir,
+                                        start_download_data, start_edge, start_hyperopt,
+                                        start_hyperopt_list, start_hyperopt_show, start_list_data,
+                                        start_list_exchanges, start_list_hyperopts,
+                                        start_list_markets, start_list_strategies,
+                                        start_list_timeframes, start_new_config, start_new_hyperopt,
+                                        start_new_strategy, start_plot_dataframe, start_plot_profit,
+                                        start_show_trades, start_test_pairlist, start_trading)
+
+        subparsers = self.parser.add_subparsers(dest='command',
+                                                # Use custom message when no subhandler is added
+                                                # shown from `main.py`
+                                                # required=True
+                                                )
+
+        # Add trade subcommand
+        trade_cmd = subparsers.add_parser('trade', help='Trade module.',
+                                          parents=[_common_parser, _strategy_parser])
+        trade_cmd.set_defaults(func=start_trading)
+        self._build_args(optionlist=ARGS_TRADE, parser=trade_cmd)
+
+        # add create-userdir subcommand
+        create_userdir_cmd = subparsers.add_parser('create-userdir',
+                                                   help="Create user-data directory.",
+                                                   )
+        create_userdir_cmd.set_defaults(func=start_create_userdir)
+        self._build_args(optionlist=ARGS_CREATE_USERDIR, parser=create_userdir_cmd)
+
+        # add new-config subcommand
+        build_config_cmd = subparsers.add_parser('new-config',
+                                                 help="Create new config")
+        build_config_cmd.set_defaults(func=start_new_config)
+        self._build_args(optionlist=ARGS_BUILD_CONFIG, parser=build_config_cmd)
+
+        # add new-hyperopt subcommand
+        build_hyperopt_cmd = subparsers.add_parser('new-hyperopt',
+                                                   help="Create new hyperopt")
+        build_hyperopt_cmd.set_defaults(func=start_new_hyperopt)
+        self._build_args(optionlist=ARGS_BUILD_HYPEROPT, parser=build_hyperopt_cmd)
+
+        # add new-strategy subcommand
+        build_strategy_cmd = subparsers.add_parser('new-strategy',
+                                                   help="Create new strategy")
+        build_strategy_cmd.set_defaults(func=start_new_strategy)
+        self._build_args(optionlist=ARGS_BUILD_STRATEGY, parser=build_strategy_cmd)
+
+        # Add download-data subcommand
+        download_data_cmd = subparsers.add_parser(
+            'download-data',
+            help='Download backtesting data.',
+            parents=[_common_parser],
+        )
+        download_data_cmd.set_defaults(func=start_download_data)
+        self._build_args(optionlist=ARGS_DOWNLOAD_DATA, parser=download_data_cmd)
+
+        # Add convert-data subcommand
+        convert_data_cmd = subparsers.add_parser(
+            'convert-data',
+            help='Convert candle (OHLCV) data from one format to another.',
+            parents=[_common_parser],
+        )
+        convert_data_cmd.set_defaults(func=partial(start_convert_data, ohlcv=True))
+        self._build_args(optionlist=ARGS_CONVERT_DATA_OHLCV, parser=convert_data_cmd)
+
+        # Add convert-trade-data subcommand
+        convert_trade_data_cmd = subparsers.add_parser(
+            'convert-trade-data',
+            help='Convert trade data from one format to another.',
+            parents=[_common_parser],
+        )
+        convert_trade_data_cmd.set_defaults(func=partial(start_convert_data, ohlcv=False))
+        self._build_args(optionlist=ARGS_CONVERT_DATA, parser=convert_trade_data_cmd)
+
+        # Add list-data subcommand
+        list_data_cmd = subparsers.add_parser(
+            'list-data',
+            help='List downloaded data.',
+            parents=[_common_parser],
+        )
+        list_data_cmd.set_defaults(func=start_list_data)
+        self._build_args(optionlist=ARGS_LIST_DATA, parser=list_data_cmd)
+
+        # Add backtesting subcommand
+        backtesting_cmd = subparsers.add_parser('backtesting', help='Backtesting module.',
+                                                parents=[_common_parser, _strategy_parser])
+        backtesting_cmd.set_defaults(func=start_backtesting)
+        self._build_args(optionlist=ARGS_BACKTEST, parser=backtesting_cmd)
+
+        # Add edge subcommand
+        edge_cmd = subparsers.add_parser('edge', help='Edge module.',
+                                         parents=[_common_parser, _strategy_parser])
+        edge_cmd.set_defaults(func=start_edge)
+        self._build_args(optionlist=ARGS_EDGE, parser=edge_cmd)
+
+        # Add hyperopt subcommand
+        hyperopt_cmd = subparsers.add_parser('hyperopt', help='Hyperopt module.',
+                                             parents=[_common_parser, _strategy_parser],
+                                             )
+        hyperopt_cmd.set_defaults(func=start_hyperopt)
+        self._build_args(optionlist=ARGS_HYPEROPT, parser=hyperopt_cmd)
+
+        # Add hyperopt-list subcommand
+        hyperopt_list_cmd = subparsers.add_parser(
+            'hyperopt-list',
+            help='List Hyperopt results',
+            parents=[_common_parser],
+        )
+        hyperopt_list_cmd.set_defaults(func=start_hyperopt_list)
+        self._build_args(optionlist=ARGS_HYPEROPT_LIST, parser=hyperopt_list_cmd)
+
+        # Add hyperopt-show subcommand
+        hyperopt_show_cmd = subparsers.add_parser(
+            'hyperopt-show',
+            help='Show details of Hyperopt results',
+            parents=[_common_parser],
+        )
+        hyperopt_show_cmd.set_defaults(func=start_hyperopt_show)
+        self._build_args(optionlist=ARGS_HYPEROPT_SHOW, parser=hyperopt_show_cmd)
+
+        # Add list-exchanges subcommand
+        list_exchanges_cmd = subparsers.add_parser(
+            'list-exchanges',
+            help='Print available exchanges.',
+            parents=[_common_parser],
+        )
+        list_exchanges_cmd.set_defaults(func=start_list_exchanges)
+        self._build_args(optionlist=ARGS_LIST_EXCHANGES, parser=list_exchanges_cmd)
+
+        # Add list-hyperopts subcommand
+        list_hyperopts_cmd = subparsers.add_parser(
+            'list-hyperopts',
+            help='Print available hyperopt classes.',
+            parents=[_common_parser],
+        )
+        list_hyperopts_cmd.set_defaults(func=start_list_hyperopts)
+        self._build_args(optionlist=ARGS_LIST_HYPEROPTS, parser=list_hyperopts_cmd)
+
+        # Add list-markets subcommand
+        list_markets_cmd = subparsers.add_parser(
+            'list-markets',
+            help='Print markets on exchange.',
+            parents=[_common_parser],
+        )
+        list_markets_cmd.set_defaults(func=partial(start_list_markets, pairs_only=False))
+        self._build_args(optionlist=ARGS_LIST_PAIRS, parser=list_markets_cmd)
+
+        # Add list-pairs subcommand
+        list_pairs_cmd = subparsers.add_parser(
+            'list-pairs',
+            help='Print pairs on exchange.',
+            parents=[_common_parser],
+        )
+        list_pairs_cmd.set_defaults(func=partial(start_list_markets, pairs_only=True))
+        self._build_args(optionlist=ARGS_LIST_PAIRS, parser=list_pairs_cmd)
+
+        # Add list-strategies subcommand
+        list_strategies_cmd = subparsers.add_parser(
+            'list-strategies',
+            help='Print available strategies.',
+            parents=[_common_parser],
+        )
+        list_strategies_cmd.set_defaults(func=start_list_strategies)
+        self._build_args(optionlist=ARGS_LIST_STRATEGIES, parser=list_strategies_cmd)
+
+        # Add list-timeframes subcommand
+        list_timeframes_cmd = subparsers.add_parser(
+            'list-timeframes',
+            help='Print available timeframes for the exchange.',
+            parents=[_common_parser],
+        )
+        list_timeframes_cmd.set_defaults(func=start_list_timeframes)
+        self._build_args(optionlist=ARGS_LIST_TIMEFRAMES, parser=list_timeframes_cmd)
+
+        # Add show-trades subcommand
+        show_trades = subparsers.add_parser(
+            'show-trades',
+            help='Show trades.',
+            parents=[_common_parser],
+        )
+        show_trades.set_defaults(func=start_show_trades)
+        self._build_args(optionlist=ARGS_SHOW_TRADES, parser=show_trades)
+
+        # Add test-pairlist subcommand
+        test_pairlist_cmd = subparsers.add_parser(
+            'test-pairlist',
+            help='Test your pairlist configuration.',
+        )
+        test_pairlist_cmd.set_defaults(func=start_test_pairlist)
+        self._build_args(optionlist=ARGS_TEST_PAIRLIST, parser=test_pairlist_cmd)
+
+        # Add Plotting subcommand
+        plot_dataframe_cmd = subparsers.add_parser(
+            'plot-dataframe',
+            help='Plot candles with indicators.',
+            parents=[_common_parser, _strategy_parser],
+        )
+        plot_dataframe_cmd.set_defaults(func=start_plot_dataframe)
+        self._build_args(optionlist=ARGS_PLOT_DATAFRAME, parser=plot_dataframe_cmd)
+
+        # Plot profit
+        plot_profit_cmd = subparsers.add_parser(
+            'plot-profit',
+            help='Generate plot showing profits.',
+            parents=[_common_parser, _strategy_parser],
+        )
+        plot_profit_cmd.set_defaults(func=start_plot_profit)
+        self._build_args(optionlist=ARGS_PLOT_PROFIT, parser=plot_profit_cmd)
diff --git a/freqtrade/commands/build_config_commands.py b/freqtrade/commands/build_config_commands.py
new file mode 100644
index 000000000..7bdbcc057
--- /dev/null
+++ b/freqtrade/commands/build_config_commands.py
@@ -0,0 +1,195 @@
+import logging
+from pathlib import Path
+from typing import Any, Dict, List
+
+from questionary import Separator, prompt
+
+from freqtrade.constants import UNLIMITED_STAKE_AMOUNT
+from freqtrade.exceptions import OperationalException
+from freqtrade.exchange import MAP_EXCHANGE_CHILDCLASS, available_exchanges
+from freqtrade.misc import render_template
+
+
+logger = logging.getLogger(__name__)
+
+
+def validate_is_int(val):
+    try:
+        _ = int(val)
+        return True
+    except Exception:
+        return False
+
+
+def validate_is_float(val):
+    try:
+        _ = float(val)
+        return True
+    except Exception:
+        return False
+
+
+def ask_user_overwrite(config_path: Path) -> bool:
+    questions = [
+        {
+            "type": "confirm",
+            "name": "overwrite",
+            "message": f"File {config_path} already exists. Overwrite?",
+            "default": False,
+        },
+    ]
+    answers = prompt(questions)
+    return answers['overwrite']
+
+
+def ask_user_config() -> Dict[str, Any]:
+    """
+    Ask user a few questions to build the configuration.
+    Interactive questions built using https://github.com/tmbo/questionary
+    :returns: Dict with keys to put into template
+    """
+    questions: List[Dict[str, Any]] = [
+        {
+            "type": "confirm",
+            "name": "dry_run",
+            "message": "Do you want to enable Dry-run (simulated trades)?",
+            "default": True,
+        },
+        {
+            "type": "text",
+            "name": "stake_currency",
+            "message": "Please insert your stake currency:",
+            "default": 'BTC',
+        },
+        {
+            "type": "text",
+            "name": "stake_amount",
+            "message": "Please insert your stake amount:",
+            "default": "0.01",
+            "validate": lambda val: val == UNLIMITED_STAKE_AMOUNT or validate_is_float(val),
+        },
+        {
+            "type": "text",
+            "name": "max_open_trades",
+            "message": f"Please insert max_open_trades (Integer or '{UNLIMITED_STAKE_AMOUNT}'):",
+            "default": "3",
+            "validate": lambda val: val == UNLIMITED_STAKE_AMOUNT or validate_is_int(val)
+        },
+        {
+            "type": "text",
+            "name": "timeframe",
+            "message": "Please insert your desired timeframe (e.g. 5m):",
+            "default": "5m",
+        },
+        {
+            "type": "text",
+            "name": "fiat_display_currency",
+            "message": "Please insert your display Currency (for reporting):",
+            "default": 'USD',
+        },
+        {
+            "type": "select",
+            "name": "exchange_name",
+            "message": "Select exchange",
+            "choices": [
+                "binance",
+                "binanceje",
+                "binanceus",
+                "bittrex",
+                "kraken",
+                Separator(),
+                "other",
+            ],
+        },
+        {
+            "type": "autocomplete",
+            "name": "exchange_name",
+            "message": "Type your exchange name (Must be supported by ccxt)",
+            "choices": available_exchanges(),
+            "when": lambda x: x["exchange_name"] == 'other'
+        },
+        {
+            "type": "password",
+            "name": "exchange_key",
+            "message": "Insert Exchange Key",
+            "when": lambda x: not x['dry_run']
+        },
+        {
+            "type": "password",
+            "name": "exchange_secret",
+            "message": "Insert Exchange Secret",
+            "when": lambda x: not x['dry_run']
+        },
+        {
+            "type": "confirm",
+            "name": "telegram",
+            "message": "Do you want to enable Telegram?",
+            "default": False,
+        },
+        {
+            "type": "password",
+            "name": "telegram_token",
+            "message": "Insert Telegram token",
+            "when": lambda x: x['telegram']
+        },
+        {
+            "type": "text",
+            "name": "telegram_chat_id",
+            "message": "Insert Telegram chat id",
+            "when": lambda x: x['telegram']
+        },
+    ]
+    answers = prompt(questions)
+
+    if not answers:
+        # Interrupted questionary sessions return an empty dict.
+        raise OperationalException("User interrupted interactive questions.")
+
+    return answers
+
+
+def deploy_new_config(config_path: Path, selections: Dict[str, Any]) -> None:
+    """
+    Applies selections to the template and writes the result to config_path
+    :param config_path: Path object for new config file. Should not exist yet
+    :param selecions: Dict containing selections taken by the user.
+    """
+    from jinja2.exceptions import TemplateNotFound
+    try:
+        exchange_template = MAP_EXCHANGE_CHILDCLASS.get(
+            selections['exchange_name'], selections['exchange_name'])
+
+        selections['exchange'] = render_template(
+            templatefile=f"subtemplates/exchange_{exchange_template}.j2",
+            arguments=selections
+            )
+    except TemplateNotFound:
+        selections['exchange'] = render_template(
+            templatefile="subtemplates/exchange_generic.j2",
+            arguments=selections
+        )
+
+    config_text = render_template(templatefile='base_config.json.j2',
+                                  arguments=selections)
+
+    logger.info(f"Writing config to `{config_path}`.")
+    config_path.write_text(config_text)
+
+
+def start_new_config(args: Dict[str, Any]) -> None:
+    """
+    Create a new strategy from a template
+    Asking the user questions to fill out the templateaccordingly.
+    """
+
+    config_path = Path(args['config'][0])
+    if config_path.exists():
+        overwrite = ask_user_overwrite(config_path)
+        if overwrite:
+            config_path.unlink()
+        else:
+            raise OperationalException(
+                f"Configuration file `{config_path}` already exists. "
+                "Please delete it or use a different configuration file name.")
+    selections = ask_user_config()
+    deploy_new_config(config_path, selections)
diff --git a/freqtrade/commands/cli_options.py b/freqtrade/commands/cli_options.py
new file mode 100644
index 000000000..619a300ae
--- /dev/null
+++ b/freqtrade/commands/cli_options.py
@@ -0,0 +1,515 @@
+"""
+Definition of cli arguments used in arguments.py
+"""
+from argparse import ArgumentTypeError
+
+from freqtrade import __version__, constants
+from freqtrade.constants import HYPEROPT_LOSS_BUILTIN
+
+
+def check_int_positive(value: str) -> int:
+    try:
+        uint = int(value)
+        if uint <= 0:
+            raise ValueError
+    except ValueError:
+        raise ArgumentTypeError(
+            f"{value} is invalid for this parameter, should be a positive integer value"
+        )
+    return uint
+
+
+def check_int_nonzero(value: str) -> int:
+    try:
+        uint = int(value)
+        if uint == 0:
+            raise ValueError
+    except ValueError:
+        raise ArgumentTypeError(
+            f"{value} is invalid for this parameter, should be a non-zero integer value"
+        )
+    return uint
+
+
+class Arg:
+    # Optional CLI arguments
+    def __init__(self, *args, **kwargs):
+        self.cli = args
+        self.kwargs = kwargs
+
+
+# List of available command line options
+AVAILABLE_CLI_OPTIONS = {
+    # Common options
+    "verbosity": Arg(
+        '-v', '--verbose',
+        help='Verbose mode (-vv for more, -vvv to get all messages).',
+        action='count',
+        default=0,
+    ),
+    "logfile": Arg(
+        '--logfile',
+        help="Log to the file specified. Special values are: 'syslog', 'journald'. "
+             "See the documentation for more details.",
+        metavar='FILE',
+    ),
+    "version": Arg(
+        '-V', '--version',
+        action='version',
+        version=f'%(prog)s {__version__}',
+    ),
+    "config": Arg(
+        '-c', '--config',
+        help=f'Specify configuration file (default: `userdir/{constants.DEFAULT_CONFIG}` '
+        f'or `config.json` whichever exists). '
+        f'Multiple --config options may be used. '
+        f'Can be set to `-` to read config from stdin.',
+        action='append',
+        metavar='PATH',
+    ),
+    "datadir": Arg(
+        '-d', '--datadir',
+        help='Path to directory with historical backtesting data.',
+        metavar='PATH',
+    ),
+    "user_data_dir": Arg(
+        '--userdir', '--user-data-dir',
+        help='Path to userdata directory.',
+        metavar='PATH',
+    ),
+    "reset": Arg(
+        '--reset',
+        help='Reset sample files to their original state.',
+        action='store_true',
+    ),
+    # Main options
+    "strategy": Arg(
+        '-s', '--strategy',
+        help='Specify strategy class name which will be used by the bot.',
+        metavar='NAME',
+    ),
+    "strategy_path": Arg(
+        '--strategy-path',
+        help='Specify additional strategy lookup path.',
+        metavar='PATH',
+    ),
+    "db_url": Arg(
+        '--db-url',
+        help=f'Override trades database URL, this is useful in custom deployments '
+        f'(default: `{constants.DEFAULT_DB_PROD_URL}` for Live Run mode, '
+        f'`{constants.DEFAULT_DB_DRYRUN_URL}` for Dry Run).',
+        metavar='PATH',
+    ),
+    "sd_notify": Arg(
+        '--sd-notify',
+        help='Notify systemd service manager.',
+        action='store_true',
+    ),
+    "dry_run": Arg(
+        '--dry-run',
+        help='Enforce dry-run for trading (removes Exchange secrets and simulates trades).',
+        action='store_true',
+    ),
+    # Optimize common
+    "timeframe": Arg(
+        '-i', '--timeframe', '--ticker-interval',
+        help='Specify ticker interval (`1m`, `5m`, `30m`, `1h`, `1d`).',
+    ),
+    "timerange": Arg(
+        '--timerange',
+        help='Specify what timerange of data to use.',
+    ),
+    "max_open_trades": Arg(
+        '--max-open-trades',
+        help='Override the value of the `max_open_trades` configuration setting.',
+        type=int,
+        metavar='INT',
+    ),
+    "stake_amount": Arg(
+        '--stake-amount',
+        help='Override the value of the `stake_amount` configuration setting.',
+        type=float,
+    ),
+    # Backtesting
+    "position_stacking": Arg(
+        '--eps', '--enable-position-stacking',
+        help='Allow buying the same pair multiple times (position stacking).',
+        action='store_true',
+        default=False,
+    ),
+    "use_max_market_positions": Arg(
+        '--dmmp', '--disable-max-market-positions',
+        help='Disable applying `max_open_trades` during backtest '
+        '(same as setting `max_open_trades` to a very high number).',
+        action='store_false',
+        default=True,
+    ),
+    "strategy_list": Arg(
+        '--strategy-list',
+        help='Provide a space-separated list of strategies to backtest. '
+        'Please note that ticker-interval needs to be set either in config '
+        'or via command line. When using this together with `--export trades`, '
+        'the strategy-name is injected into the filename '
+        '(so `backtest-data.json` becomes `backtest-data-DefaultStrategy.json`',
+        nargs='+',
+    ),
+    "export": Arg(
+        '--export',
+        help='Export backtest results, argument are: trades. '
+        'Example: `--export=trades`',
+    ),
+    "exportfilename": Arg(
+        '--export-filename',
+        help='Save backtest results to the file with this filename. '
+        'Requires `--export` to be set as well. '
+        'Example: `--export-filename=user_data/backtest_results/backtest_today.json`',
+        metavar='PATH',
+    ),
+    "fee": Arg(
+        '--fee',
+        help='Specify fee ratio. Will be applied twice (on trade entry and exit).',
+        type=float,
+        metavar='FLOAT',
+    ),
+    # Edge
+    "stoploss_range": Arg(
+        '--stoplosses',
+        help='Defines a range of stoploss values against which edge will assess the strategy. '
+        'The format is "min,max,step" (without any space). '
+        'Example: `--stoplosses=-0.01,-0.1,-0.001`',
+    ),
+    # Hyperopt
+    "hyperopt": Arg(
+        '--hyperopt',
+        help='Specify hyperopt class name which will be used by the bot.',
+        metavar='NAME',
+    ),
+    "hyperopt_path": Arg(
+        '--hyperopt-path',
+        help='Specify additional lookup path for Hyperopt and Hyperopt Loss functions.',
+        metavar='PATH',
+    ),
+    "epochs": Arg(
+        '-e', '--epochs',
+        help='Specify number of epochs (default: %(default)d).',
+        type=check_int_positive,
+        metavar='INT',
+        default=constants.HYPEROPT_EPOCH,
+    ),
+    "spaces": Arg(
+        '--spaces',
+        help='Specify which parameters to hyperopt. Space-separated list.',
+        choices=['all', 'buy', 'sell', 'roi', 'stoploss', 'trailing', 'default'],
+        nargs='+',
+        default='default',
+    ),
+    "print_all": Arg(
+        '--print-all',
+        help='Print all results, not only the best ones.',
+        action='store_true',
+        default=False,
+    ),
+    "print_colorized": Arg(
+        '--no-color',
+        help='Disable colorization of hyperopt results. May be useful if you are '
+        'redirecting output to a file.',
+        action='store_false',
+        default=True,
+    ),
+    "print_json": Arg(
+        '--print-json',
+        help='Print output in JSON format.',
+        action='store_true',
+        default=False,
+    ),
+    "export_csv": Arg(
+        '--export-csv',
+        help='Export to CSV-File.'
+        ' This will disable table print.'
+        ' Example: --export-csv hyperopt.csv',
+        metavar='FILE',
+    ),
+    "hyperopt_jobs": Arg(
+        '-j', '--job-workers',
+        help='The number of concurrently running jobs for hyperoptimization '
+        '(hyperopt worker processes). '
+        'If -1 (default), all CPUs are used, for -2, all CPUs but one are used, etc. '
+        'If 1 is given, no parallel computing code is used at all.',
+        type=int,
+        metavar='JOBS',
+        default=-1,
+    ),
+    "hyperopt_random_state": Arg(
+        '--random-state',
+        help='Set random state to some positive integer for reproducible hyperopt results.',
+        type=check_int_positive,
+        metavar='INT',
+    ),
+    "hyperopt_min_trades": Arg(
+        '--min-trades',
+        help="Set minimal desired number of trades for evaluations in the hyperopt "
+        "optimization path (default: 1).",
+        type=check_int_positive,
+        metavar='INT',
+        default=1,
+    ),
+    "hyperopt_loss": Arg(
+        '--hyperopt-loss',
+        help='Specify the class name of the hyperopt loss function class (IHyperOptLoss). '
+        'Different functions can generate completely different results, '
+        'since the target for optimization is different. Built-in Hyperopt-loss-functions are: '
+        f'{", ".join(HYPEROPT_LOSS_BUILTIN)}',
+        metavar='NAME',
+    ),
+    "hyperoptexportfilename": Arg(
+        '--hyperopt-filename',
+        help='Hyperopt result filename.'
+        'Example: `--hyperopt-filename=hyperopt_results_2020-09-27_16-20-48.pickle`',
+        metavar='FILENAME',
+    ),
+    # List exchanges
+    "print_one_column": Arg(
+        '-1', '--one-column',
+        help='Print output in one column.',
+        action='store_true',
+    ),
+    "list_exchanges_all": Arg(
+        '-a', '--all',
+        help='Print all exchanges known to the ccxt library.',
+        action='store_true',
+    ),
+    # List pairs / markets
+    "list_pairs_all": Arg(
+        '-a', '--all',
+        help='Print all pairs or market symbols. By default only active '
+             'ones are shown.',
+        action='store_true',
+    ),
+    "print_list": Arg(
+        '--print-list',
+        help='Print list of pairs or market symbols. By default data is '
+             'printed in the tabular format.',
+        action='store_true',
+    ),
+    "list_pairs_print_json": Arg(
+        '--print-json',
+        help='Print list of pairs or market symbols in JSON format.',
+        action='store_true',
+        default=False,
+    ),
+    "print_csv": Arg(
+        '--print-csv',
+        help='Print exchange pair or market data in the csv format.',
+        action='store_true',
+    ),
+    "quote_currencies": Arg(
+        '--quote',
+        help='Specify quote currency(-ies). Space-separated list.',
+        nargs='+',
+        metavar='QUOTE_CURRENCY',
+    ),
+    "base_currencies": Arg(
+        '--base',
+        help='Specify base currency(-ies). Space-separated list.',
+        nargs='+',
+        metavar='BASE_CURRENCY',
+    ),
+    # Script options
+    "pairs": Arg(
+        '-p', '--pairs',
+        help='Show profits for only these pairs. Pairs are space-separated.',
+        nargs='+',
+    ),
+    # Download data
+    "pairs_file": Arg(
+        '--pairs-file',
+        help='File containing a list of pairs to download.',
+        metavar='FILE',
+    ),
+    "days": Arg(
+        '--days',
+        help='Download data for given number of days.',
+        type=check_int_positive,
+        metavar='INT',
+    ),
+    "download_trades": Arg(
+        '--dl-trades',
+        help='Download trades instead of OHLCV data. The bot will resample trades to the '
+             'desired timeframe as specified as --timeframes/-t.',
+        action='store_true',
+    ),
+    "format_from": Arg(
+        '--format-from',
+        help='Source format for data conversion.',
+        choices=constants.AVAILABLE_DATAHANDLERS,
+        required=True,
+    ),
+    "format_to": Arg(
+        '--format-to',
+        help='Destination format for data conversion.',
+        choices=constants.AVAILABLE_DATAHANDLERS,
+        required=True,
+    ),
+    "dataformat_ohlcv": Arg(
+        '--data-format-ohlcv',
+        help='Storage format for downloaded candle (OHLCV) data. (default: `%(default)s`).',
+        choices=constants.AVAILABLE_DATAHANDLERS,
+    ),
+    "dataformat_trades": Arg(
+        '--data-format-trades',
+        help='Storage format for downloaded trades data. (default: `%(default)s`).',
+        choices=constants.AVAILABLE_DATAHANDLERS,
+    ),
+    "exchange": Arg(
+        '--exchange',
+        help=f'Exchange name (default: `{constants.DEFAULT_EXCHANGE}`). '
+        f'Only valid if no config is provided.',
+    ),
+    "timeframes": Arg(
+        '-t', '--timeframes',
+        help='Specify which tickers to download. Space-separated list. '
+        'Default: `1m 5m`.',
+        choices=['1m', '3m', '5m', '15m', '30m', '1h', '2h', '4h',
+                 '6h', '8h', '12h', '1d', '3d', '1w', '2w', '1M', '1y'],
+        default=['1m', '5m'],
+        nargs='+',
+    ),
+    "erase": Arg(
+        '--erase',
+        help='Clean all existing data for the selected exchange/pairs/timeframes.',
+        action='store_true',
+    ),
+    # Templating options
+    "template": Arg(
+        '--template',
+        help='Use a template which is either `minimal`, '
+        '`full` (containing multiple sample indicators) or `advanced`. Default: `%(default)s`.',
+        choices=['full', 'minimal', 'advanced'],
+        default='full',
+    ),
+    # Plot dataframe
+    "indicators1": Arg(
+        '--indicators1',
+        help='Set indicators from your strategy you want in the first row of the graph. '
+        "Space-separated list. Example: `ema3 ema5`. Default: `['sma', 'ema3', 'ema5']`.",
+        nargs='+',
+    ),
+    "indicators2": Arg(
+        '--indicators2',
+        help='Set indicators from your strategy you want in the third row of the graph. '
+        "Space-separated list. Example: `fastd fastk`. Default: `['macd', 'macdsignal']`.",
+        nargs='+',
+    ),
+    "plot_limit": Arg(
+        '--plot-limit',
+        help='Specify tick limit for plotting. Notice: too high values cause huge files. '
+        'Default: %(default)s.',
+        type=check_int_positive,
+        metavar='INT',
+        default=750,
+    ),
+    "no_trades": Arg(
+        '--no-trades',
+        help='Skip using trades from backtesting file and DB.',
+        action='store_true',
+    ),
+    "trade_source": Arg(
+        '--trade-source',
+        help='Specify the source for trades (Can be DB or file (backtest file)) '
+        'Default: %(default)s',
+        choices=["DB", "file"],
+        default="file",
+    ),
+    "trade_ids": Arg(
+        '--trade-ids',
+        help='Specify the list of trade ids.',
+        nargs='+',
+    ),
+    # hyperopt-list, hyperopt-show
+    "hyperopt_list_profitable": Arg(
+        '--profitable',
+        help='Select only profitable epochs.',
+        action='store_true',
+    ),
+    "hyperopt_list_best": Arg(
+        '--best',
+        help='Select only best epochs.',
+        action='store_true',
+    ),
+    "hyperopt_list_min_trades": Arg(
+        '--min-trades',
+        help='Select epochs with more than INT trades.',
+        type=check_int_positive,
+        metavar='INT',
+    ),
+    "hyperopt_list_max_trades": Arg(
+        '--max-trades',
+        help='Select epochs with less than INT trades.',
+        type=check_int_positive,
+        metavar='INT',
+    ),
+    "hyperopt_list_min_avg_time": Arg(
+        '--min-avg-time',
+        help='Select epochs above average time.',
+        type=float,
+        metavar='FLOAT',
+    ),
+    "hyperopt_list_max_avg_time": Arg(
+        '--max-avg-time',
+        help='Select epochs below average time.',
+        type=float,
+        metavar='FLOAT',
+    ),
+    "hyperopt_list_min_avg_profit": Arg(
+        '--min-avg-profit',
+        help='Select epochs above average profit.',
+        type=float,
+        metavar='FLOAT',
+    ),
+    "hyperopt_list_max_avg_profit": Arg(
+        '--max-avg-profit',
+        help='Select epochs below average profit.',
+        type=float,
+        metavar='FLOAT',
+    ),
+    "hyperopt_list_min_total_profit": Arg(
+        '--min-total-profit',
+        help='Select epochs above total profit.',
+        type=float,
+        metavar='FLOAT',
+    ),
+    "hyperopt_list_max_total_profit": Arg(
+        '--max-total-profit',
+        help='Select epochs below total profit.',
+        type=float,
+        metavar='FLOAT',
+    ),
+    "hyperopt_list_min_objective": Arg(
+        '--min-objective',
+        help='Select epochs above objective.',
+        type=float,
+        metavar='FLOAT',
+    ),
+    "hyperopt_list_max_objective": Arg(
+        '--max-objective',
+        help='Select epochs below objective.',
+        type=float,
+        metavar='FLOAT',
+    ),
+    "hyperopt_list_no_details": Arg(
+        '--no-details',
+        help='Do not print best epoch details.',
+        action='store_true',
+    ),
+    "hyperopt_show_index": Arg(
+        '-n', '--index',
+        help='Specify the index of the epoch to print details for.',
+        type=check_int_nonzero,
+        metavar='INT',
+    ),
+    "hyperopt_show_no_header": Arg(
+        '--no-header',
+        help='Do not print epoch details header.',
+        action='store_true',
+    ),
+}
diff --git a/freqtrade/commands/data_commands.py b/freqtrade/commands/data_commands.py
new file mode 100644
index 000000000..25c7d0436
--- /dev/null
+++ b/freqtrade/commands/data_commands.py
@@ -0,0 +1,127 @@
+import logging
+import sys
+from collections import defaultdict
+from datetime import datetime, timedelta
+from typing import Any, Dict, List
+
+from freqtrade.configuration import TimeRange, setup_utils_configuration
+from freqtrade.data.converter import convert_ohlcv_format, convert_trades_format
+from freqtrade.data.history import (convert_trades_to_ohlcv, refresh_backtest_ohlcv_data,
+                                    refresh_backtest_trades_data)
+from freqtrade.exceptions import OperationalException
+from freqtrade.exchange import timeframe_to_minutes
+from freqtrade.resolvers import ExchangeResolver
+from freqtrade.state import RunMode
+
+
+logger = logging.getLogger(__name__)
+
+
+def start_download_data(args: Dict[str, Any]) -> None:
+    """
+    Download data (former download_backtest_data.py script)
+    """
+    config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
+
+    if 'days' in config and 'timerange' in config:
+        raise OperationalException("--days and --timerange are mutually exclusive. "
+                                   "You can only specify one or the other.")
+    timerange = TimeRange()
+    if 'days' in config:
+        time_since = (datetime.now() - timedelta(days=config['days'])).strftime("%Y%m%d")
+        timerange = TimeRange.parse_timerange(f'{time_since}-')
+
+    if 'timerange' in config:
+        timerange = timerange.parse_timerange(config['timerange'])
+
+    # Remove stake-currency to skip checks which are not relevant for datadownload
+    config['stake_currency'] = ''
+
+    if 'pairs' not in config:
+        raise OperationalException(
+            "Downloading data requires a list of pairs. "
+            "Please check the documentation on how to configure this.")
+
+    logger.info(f"About to download pairs: {config['pairs']}, "
+                f"intervals: {config['timeframes']} to {config['datadir']}")
+
+    pairs_not_available: List[str] = []
+
+    # Init exchange
+    exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
+    # Manual validations of relevant settings
+    exchange.validate_pairs(config['pairs'])
+    for timeframe in config['timeframes']:
+        exchange.validate_timeframes(timeframe)
+
+    try:
+
+        if config.get('download_trades'):
+            pairs_not_available = refresh_backtest_trades_data(
+                exchange, pairs=config['pairs'], datadir=config['datadir'],
+                timerange=timerange, erase=bool(config.get('erase')),
+                data_format=config['dataformat_trades'])
+
+            # Convert downloaded trade data to different timeframes
+            convert_trades_to_ohlcv(
+                pairs=config['pairs'], timeframes=config['timeframes'],
+                datadir=config['datadir'], timerange=timerange, erase=bool(config.get('erase')),
+                data_format_ohlcv=config['dataformat_ohlcv'],
+                data_format_trades=config['dataformat_trades'],
+                )
+        else:
+            pairs_not_available = refresh_backtest_ohlcv_data(
+                exchange, pairs=config['pairs'], timeframes=config['timeframes'],
+                datadir=config['datadir'], timerange=timerange, erase=bool(config.get('erase')),
+                data_format=config['dataformat_ohlcv'])
+
+    except KeyboardInterrupt:
+        sys.exit("SIGINT received, aborting ...")
+
+    finally:
+        if pairs_not_available:
+            logger.info(f"Pairs [{','.join(pairs_not_available)}] not available "
+                        f"on exchange {exchange.name}.")
+
+
+def start_convert_data(args: Dict[str, Any], ohlcv: bool = True) -> None:
+    """
+    Convert data from one format to another
+    """
+    config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
+    if ohlcv:
+        convert_ohlcv_format(config,
+                             convert_from=args['format_from'], convert_to=args['format_to'],
+                             erase=args['erase'])
+    else:
+        convert_trades_format(config,
+                              convert_from=args['format_from'], convert_to=args['format_to'],
+                              erase=args['erase'])
+
+
+def start_list_data(args: Dict[str, Any]) -> None:
+    """
+    List available backtest data
+    """
+
+    config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
+
+    from tabulate import tabulate
+
+    from freqtrade.data.history.idatahandler import get_datahandler
+    dhc = get_datahandler(config['datadir'], config['dataformat_ohlcv'])
+
+    paircombs = dhc.ohlcv_get_available_data(config['datadir'])
+
+    if args['pairs']:
+        paircombs = [comb for comb in paircombs if comb[0] in args['pairs']]
+
+    print(f"Found {len(paircombs)} pair / timeframe combinations.")
+    groupedpair = defaultdict(list)
+    for pair, timeframe in sorted(paircombs, key=lambda x: (x[0], timeframe_to_minutes(x[1]))):
+        groupedpair[pair].append(timeframe)
+
+    if groupedpair:
+        print(tabulate([(pair, ', '.join(timeframes)) for pair, timeframes in groupedpair.items()],
+                       headers=("Pair", "Timeframe"),
+                       tablefmt='psql', stralign='right'))
diff --git a/freqtrade/commands/deploy_commands.py b/freqtrade/commands/deploy_commands.py
new file mode 100644
index 000000000..a0105e140
--- /dev/null
+++ b/freqtrade/commands/deploy_commands.py
@@ -0,0 +1,139 @@
+import logging
+import sys
+from pathlib import Path
+from typing import Any, Dict
+
+from freqtrade.configuration import setup_utils_configuration
+from freqtrade.configuration.directory_operations import copy_sample_files, create_userdata_dir
+from freqtrade.constants import USERPATH_HYPEROPTS, USERPATH_STRATEGIES
+from freqtrade.exceptions import OperationalException
+from freqtrade.misc import render_template, render_template_with_fallback
+from freqtrade.state import RunMode
+
+
+logger = logging.getLogger(__name__)
+
+
+def start_create_userdir(args: Dict[str, Any]) -> None:
+    """
+    Create "user_data" directory to contain user data strategies, hyperopt, ...)
+    :param args: Cli args from Arguments()
+    :return: None
+    """
+    if "user_data_dir" in args and args["user_data_dir"]:
+        userdir = create_userdata_dir(args["user_data_dir"], create_dir=True)
+        copy_sample_files(userdir, overwrite=args["reset"])
+    else:
+        logger.warning("`create-userdir` requires --userdir to be set.")
+        sys.exit(1)
+
+
+def deploy_new_strategy(strategy_name: str, strategy_path: Path, subtemplate: str) -> None:
+    """
+    Deploy new strategy from template to strategy_path
+    """
+    fallback = 'full'
+    indicators = render_template_with_fallback(
+        templatefile=f"subtemplates/indicators_{subtemplate}.j2",
+        templatefallbackfile=f"subtemplates/indicators_{fallback}.j2",
+        )
+    buy_trend = render_template_with_fallback(
+        templatefile=f"subtemplates/buy_trend_{subtemplate}.j2",
+        templatefallbackfile=f"subtemplates/buy_trend_{fallback}.j2",
+        )
+    sell_trend = render_template_with_fallback(
+        templatefile=f"subtemplates/sell_trend_{subtemplate}.j2",
+        templatefallbackfile=f"subtemplates/sell_trend_{fallback}.j2",
+        )
+    plot_config = render_template_with_fallback(
+        templatefile=f"subtemplates/plot_config_{subtemplate}.j2",
+        templatefallbackfile=f"subtemplates/plot_config_{fallback}.j2",
+    )
+    additional_methods = render_template_with_fallback(
+        templatefile=f"subtemplates/strategy_methods_{subtemplate}.j2",
+        templatefallbackfile="subtemplates/strategy_methods_empty.j2",
+    )
+
+    strategy_text = render_template(templatefile='base_strategy.py.j2',
+                                    arguments={"strategy": strategy_name,
+                                               "indicators": indicators,
+                                               "buy_trend": buy_trend,
+                                               "sell_trend": sell_trend,
+                                               "plot_config": plot_config,
+                                               "additional_methods": additional_methods,
+                                               })
+
+    logger.info(f"Writing strategy to `{strategy_path}`.")
+    strategy_path.write_text(strategy_text)
+
+
+def start_new_strategy(args: Dict[str, Any]) -> None:
+
+    config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
+
+    if "strategy" in args and args["strategy"]:
+        if args["strategy"] == "DefaultStrategy":
+            raise OperationalException("DefaultStrategy is not allowed as name.")
+
+        new_path = config['user_data_dir'] / USERPATH_STRATEGIES / (args['strategy'] + '.py')
+
+        if new_path.exists():
+            raise OperationalException(f"`{new_path}` already exists. "
+                                       "Please choose another Strategy Name.")
+
+        deploy_new_strategy(args['strategy'], new_path, args['template'])
+
+    else:
+        raise OperationalException("`new-strategy` requires --strategy to be set.")
+
+
+def deploy_new_hyperopt(hyperopt_name: str, hyperopt_path: Path, subtemplate: str) -> None:
+    """
+    Deploys a new hyperopt template to hyperopt_path
+    """
+    fallback = 'full'
+    buy_guards = render_template_with_fallback(
+        templatefile=f"subtemplates/hyperopt_buy_guards_{subtemplate}.j2",
+        templatefallbackfile=f"subtemplates/hyperopt_buy_guards_{fallback}.j2",
+        )
+    sell_guards = render_template_with_fallback(
+        templatefile=f"subtemplates/hyperopt_sell_guards_{subtemplate}.j2",
+        templatefallbackfile=f"subtemplates/hyperopt_sell_guards_{fallback}.j2",
+        )
+    buy_space = render_template_with_fallback(
+        templatefile=f"subtemplates/hyperopt_buy_space_{subtemplate}.j2",
+        templatefallbackfile=f"subtemplates/hyperopt_buy_space_{fallback}.j2",
+        )
+    sell_space = render_template_with_fallback(
+        templatefile=f"subtemplates/hyperopt_sell_space_{subtemplate}.j2",
+        templatefallbackfile=f"subtemplates/hyperopt_sell_space_{fallback}.j2",
+        )
+
+    strategy_text = render_template(templatefile='base_hyperopt.py.j2',
+                                    arguments={"hyperopt": hyperopt_name,
+                                               "buy_guards": buy_guards,
+                                               "sell_guards": sell_guards,
+                                               "buy_space": buy_space,
+                                               "sell_space": sell_space,
+                                               })
+
+    logger.info(f"Writing hyperopt to `{hyperopt_path}`.")
+    hyperopt_path.write_text(strategy_text)
+
+
+def start_new_hyperopt(args: Dict[str, Any]) -> None:
+
+    config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
+
+    if 'hyperopt' in args and args['hyperopt']:
+        if args['hyperopt'] == 'DefaultHyperopt':
+            raise OperationalException("DefaultHyperopt is not allowed as name.")
+
+        new_path = config['user_data_dir'] / USERPATH_HYPEROPTS / (args['hyperopt'] + '.py')
+
+        if new_path.exists():
+            raise OperationalException(f"`{new_path}` already exists. "
+                                       "Please choose another Hyperopt Name.")
+        deploy_new_hyperopt(args['hyperopt'], new_path, args['template'])
+    else:
+        raise OperationalException("`new-hyperopt` requires --hyperopt to be set.")
diff --git a/freqtrade/commands/hyperopt_commands.py b/freqtrade/commands/hyperopt_commands.py
new file mode 100755
index 000000000..fd8f737f0
--- /dev/null
+++ b/freqtrade/commands/hyperopt_commands.py
@@ -0,0 +1,228 @@
+import logging
+from operator import itemgetter
+from typing import Any, Dict, List
+
+from colorama import init as colorama_init
+
+from freqtrade.configuration import setup_utils_configuration
+from freqtrade.data.btanalysis import get_latest_hyperopt_file
+from freqtrade.exceptions import OperationalException
+from freqtrade.state import RunMode
+
+
+logger = logging.getLogger(__name__)
+
+
+def start_hyperopt_list(args: Dict[str, Any]) -> None:
+    """
+    List hyperopt epochs previously evaluated
+    """
+    from freqtrade.optimize.hyperopt import Hyperopt
+
+    config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
+
+    print_colorized = config.get('print_colorized', False)
+    print_json = config.get('print_json', False)
+    export_csv = config.get('export_csv', None)
+    no_details = config.get('hyperopt_list_no_details', False)
+    no_header = False
+
+    filteroptions = {
+        'only_best': config.get('hyperopt_list_best', False),
+        'only_profitable': config.get('hyperopt_list_profitable', False),
+        'filter_min_trades': config.get('hyperopt_list_min_trades', 0),
+        'filter_max_trades': config.get('hyperopt_list_max_trades', 0),
+        'filter_min_avg_time': config.get('hyperopt_list_min_avg_time', None),
+        'filter_max_avg_time': config.get('hyperopt_list_max_avg_time', None),
+        'filter_min_avg_profit': config.get('hyperopt_list_min_avg_profit', None),
+        'filter_max_avg_profit': config.get('hyperopt_list_max_avg_profit', None),
+        'filter_min_total_profit': config.get('hyperopt_list_min_total_profit', None),
+        'filter_max_total_profit': config.get('hyperopt_list_max_total_profit', None),
+        'filter_min_objective': config.get('hyperopt_list_min_objective', None),
+        'filter_max_objective': config.get('hyperopt_list_max_objective', None),
+    }
+
+    results_file = get_latest_hyperopt_file(
+        config['user_data_dir'] / 'hyperopt_results',
+        config.get('hyperoptexportfilename'))
+
+    # Previous evaluations
+    epochs = Hyperopt.load_previous_results(results_file)
+    total_epochs = len(epochs)
+
+    epochs = hyperopt_filter_epochs(epochs, filteroptions)
+
+    if print_colorized:
+        colorama_init(autoreset=True)
+
+    if not export_csv:
+        try:
+            print(Hyperopt.get_result_table(config, epochs, total_epochs,
+                                            not filteroptions['only_best'], print_colorized, 0))
+        except KeyboardInterrupt:
+            print('User interrupted..')
+
+    if epochs and not no_details:
+        sorted_epochs = sorted(epochs, key=itemgetter('loss'))
+        results = sorted_epochs[0]
+        Hyperopt.print_epoch_details(results, total_epochs, print_json, no_header)
+
+    if epochs and export_csv:
+        Hyperopt.export_csv_file(
+            config, epochs, total_epochs, not filteroptions['only_best'], export_csv
+        )
+
+
+def start_hyperopt_show(args: Dict[str, Any]) -> None:
+    """
+    Show details of a hyperopt epoch previously evaluated
+    """
+    from freqtrade.optimize.hyperopt import Hyperopt
+
+    config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
+
+    print_json = config.get('print_json', False)
+    no_header = config.get('hyperopt_show_no_header', False)
+    results_file = get_latest_hyperopt_file(
+        config['user_data_dir'] / 'hyperopt_results',
+        config.get('hyperoptexportfilename'))
+
+    n = config.get('hyperopt_show_index', -1)
+
+    filteroptions = {
+        'only_best': config.get('hyperopt_list_best', False),
+        'only_profitable': config.get('hyperopt_list_profitable', False),
+        'filter_min_trades': config.get('hyperopt_list_min_trades', 0),
+        'filter_max_trades': config.get('hyperopt_list_max_trades', 0),
+        'filter_min_avg_time': config.get('hyperopt_list_min_avg_time', None),
+        'filter_max_avg_time': config.get('hyperopt_list_max_avg_time', None),
+        'filter_min_avg_profit': config.get('hyperopt_list_min_avg_profit', None),
+        'filter_max_avg_profit': config.get('hyperopt_list_max_avg_profit', None),
+        'filter_min_total_profit': config.get('hyperopt_list_min_total_profit', None),
+        'filter_max_total_profit': config.get('hyperopt_list_max_total_profit', None),
+        'filter_min_objective': config.get('hyperopt_list_min_objective', None),
+        'filter_max_objective': config.get('hyperopt_list_max_objective', None)
+    }
+
+    # Previous evaluations
+    epochs = Hyperopt.load_previous_results(results_file)
+    total_epochs = len(epochs)
+
+    epochs = hyperopt_filter_epochs(epochs, filteroptions)
+    filtered_epochs = len(epochs)
+
+    if n > filtered_epochs:
+        raise OperationalException(
+            f"The index of the epoch to show should be less than {filtered_epochs + 1}.")
+    if n < -filtered_epochs:
+        raise OperationalException(
+            f"The index of the epoch to show should be greater than {-filtered_epochs - 1}.")
+
+    # Translate epoch index from human-readable format to pythonic
+    if n > 0:
+        n -= 1
+
+    if epochs:
+        val = epochs[n]
+        Hyperopt.print_epoch_details(val, total_epochs, print_json, no_header,
+                                     header_str="Epoch details")
+
+
+def hyperopt_filter_epochs(epochs: List, filteroptions: dict) -> List:
+    """
+    Filter our items from the list of hyperopt results
+    """
+    if filteroptions['only_best']:
+        epochs = [x for x in epochs if x['is_best']]
+    if filteroptions['only_profitable']:
+        epochs = [x for x in epochs if x['results_metrics']['profit'] > 0]
+
+    epochs = _hyperopt_filter_epochs_trade_count(epochs, filteroptions)
+
+    epochs = _hyperopt_filter_epochs_duration(epochs, filteroptions)
+
+    epochs = _hyperopt_filter_epochs_profit(epochs, filteroptions)
+
+    epochs = _hyperopt_filter_epochs_objective(epochs, filteroptions)
+
+    logger.info(f"{len(epochs)} " +
+                ("best " if filteroptions['only_best'] else "") +
+                ("profitable " if filteroptions['only_profitable'] else "") +
+                "epochs found.")
+    return epochs
+
+
+def _hyperopt_filter_epochs_trade_count(epochs: List, filteroptions: dict) -> List:
+
+    if filteroptions['filter_min_trades'] > 0:
+        epochs = [
+            x for x in epochs
+            if x['results_metrics']['trade_count'] > filteroptions['filter_min_trades']
+        ]
+    if filteroptions['filter_max_trades'] > 0:
+        epochs = [
+            x for x in epochs
+            if x['results_metrics']['trade_count'] < filteroptions['filter_max_trades']
+        ]
+    return epochs
+
+
+def _hyperopt_filter_epochs_duration(epochs: List, filteroptions: dict) -> List:
+
+    if filteroptions['filter_min_avg_time'] is not None:
+        epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
+        epochs = [
+            x for x in epochs
+            if x['results_metrics']['duration'] > filteroptions['filter_min_avg_time']
+        ]
+    if filteroptions['filter_max_avg_time'] is not None:
+        epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
+        epochs = [
+            x for x in epochs
+            if x['results_metrics']['duration'] < filteroptions['filter_max_avg_time']
+        ]
+
+    return epochs
+
+
+def _hyperopt_filter_epochs_profit(epochs: List, filteroptions: dict) -> List:
+
+    if filteroptions['filter_min_avg_profit'] is not None:
+        epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
+        epochs = [
+            x for x in epochs
+            if x['results_metrics']['avg_profit'] > filteroptions['filter_min_avg_profit']
+        ]
+    if filteroptions['filter_max_avg_profit'] is not None:
+        epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
+        epochs = [
+            x for x in epochs
+            if x['results_metrics']['avg_profit'] < filteroptions['filter_max_avg_profit']
+        ]
+    if filteroptions['filter_min_total_profit'] is not None:
+        epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
+        epochs = [
+            x for x in epochs
+            if x['results_metrics']['profit'] > filteroptions['filter_min_total_profit']
+        ]
+    if filteroptions['filter_max_total_profit'] is not None:
+        epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
+        epochs = [
+            x for x in epochs
+            if x['results_metrics']['profit'] < filteroptions['filter_max_total_profit']
+        ]
+    return epochs
+
+
+def _hyperopt_filter_epochs_objective(epochs: List, filteroptions: dict) -> List:
+
+    if filteroptions['filter_min_objective'] is not None:
+        epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
+
+        epochs = [x for x in epochs if x['loss'] < filteroptions['filter_min_objective']]
+    if filteroptions['filter_max_objective'] is not None:
+        epochs = [x for x in epochs if x['results_metrics']['trade_count'] > 0]
+
+        epochs = [x for x in epochs if x['loss'] > filteroptions['filter_max_objective']]
+
+    return epochs
diff --git a/freqtrade/commands/list_commands.py b/freqtrade/commands/list_commands.py
new file mode 100644
index 000000000..9e6076dfb
--- /dev/null
+++ b/freqtrade/commands/list_commands.py
@@ -0,0 +1,227 @@
+import csv
+import logging
+import sys
+from collections import OrderedDict
+from pathlib import Path
+from typing import Any, Dict, List
+
+import rapidjson
+from colorama import Fore, Style
+from colorama import init as colorama_init
+from tabulate import tabulate
+
+from freqtrade.configuration import setup_utils_configuration
+from freqtrade.constants import USERPATH_HYPEROPTS, USERPATH_STRATEGIES
+from freqtrade.exceptions import OperationalException
+from freqtrade.exchange import available_exchanges, ccxt_exchanges, market_is_active
+from freqtrade.misc import plural
+from freqtrade.resolvers import ExchangeResolver, StrategyResolver
+from freqtrade.state import RunMode
+
+
+logger = logging.getLogger(__name__)
+
+
+def start_list_exchanges(args: Dict[str, Any]) -> None:
+    """
+    Print available exchanges
+    :param args: Cli args from Arguments()
+    :return: None
+    """
+    exchanges = ccxt_exchanges() if args['list_exchanges_all'] else available_exchanges()
+    if args['print_one_column']:
+        print('\n'.join(exchanges))
+    else:
+        if args['list_exchanges_all']:
+            print(f"All exchanges supported by the ccxt library: {', '.join(exchanges)}")
+        else:
+            print(f"Exchanges available for Freqtrade: {', '.join(exchanges)}")
+
+
+def _print_objs_tabular(objs: List, print_colorized: bool) -> None:
+    if print_colorized:
+        colorama_init(autoreset=True)
+        red = Fore.RED
+        yellow = Fore.YELLOW
+        reset = Style.RESET_ALL
+    else:
+        red = ''
+        yellow = ''
+        reset = ''
+
+    names = [s['name'] for s in objs]
+    objss_to_print = [{
+        'name': s['name'] if s['name'] else "--",
+        'location': s['location'].name,
+        'status': (red + "LOAD FAILED" + reset if s['class'] is None
+                   else "OK" if names.count(s['name']) == 1
+                   else yellow + "DUPLICATE NAME" + reset)
+    } for s in objs]
+
+    print(tabulate(objss_to_print, headers='keys', tablefmt='psql', stralign='right'))
+
+
+def start_list_strategies(args: Dict[str, Any]) -> None:
+    """
+    Print files with Strategy custom classes available in the directory
+    """
+    config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
+
+    directory = Path(config.get('strategy_path', config['user_data_dir'] / USERPATH_STRATEGIES))
+    strategy_objs = StrategyResolver.search_all_objects(directory, not args['print_one_column'])
+    # Sort alphabetically
+    strategy_objs = sorted(strategy_objs, key=lambda x: x['name'])
+
+    if args['print_one_column']:
+        print('\n'.join([s['name'] for s in strategy_objs]))
+    else:
+        _print_objs_tabular(strategy_objs, config.get('print_colorized', False))
+
+
+def start_list_hyperopts(args: Dict[str, Any]) -> None:
+    """
+    Print files with HyperOpt custom classes available in the directory
+    """
+    from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver
+
+    config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
+
+    directory = Path(config.get('hyperopt_path', config['user_data_dir'] / USERPATH_HYPEROPTS))
+    hyperopt_objs = HyperOptResolver.search_all_objects(directory, not args['print_one_column'])
+    # Sort alphabetically
+    hyperopt_objs = sorted(hyperopt_objs, key=lambda x: x['name'])
+
+    if args['print_one_column']:
+        print('\n'.join([s['name'] for s in hyperopt_objs]))
+    else:
+        _print_objs_tabular(hyperopt_objs, config.get('print_colorized', False))
+
+
+def start_list_timeframes(args: Dict[str, Any]) -> None:
+    """
+    Print ticker intervals (timeframes) available on Exchange
+    """
+    config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
+    # Do not use timeframe set in the config
+    config['timeframe'] = None
+
+    # Init exchange
+    exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
+
+    if args['print_one_column']:
+        print('\n'.join(exchange.timeframes))
+    else:
+        print(f"Timeframes available for the exchange `{exchange.name}`: "
+              f"{', '.join(exchange.timeframes)}")
+
+
+def start_list_markets(args: Dict[str, Any], pairs_only: bool = False) -> None:
+    """
+    Print pairs/markets on the exchange
+    :param args: Cli args from Arguments()
+    :param pairs_only: if True print only pairs, otherwise print all instruments (markets)
+    :return: None
+    """
+    config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
+
+    # Init exchange
+    exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
+
+    # By default only active pairs/markets are to be shown
+    active_only = not args.get('list_pairs_all', False)
+
+    base_currencies = args.get('base_currencies', [])
+    quote_currencies = args.get('quote_currencies', [])
+
+    try:
+        pairs = exchange.get_markets(base_currencies=base_currencies,
+                                     quote_currencies=quote_currencies,
+                                     pairs_only=pairs_only,
+                                     active_only=active_only)
+        # Sort the pairs/markets by symbol
+        pairs = OrderedDict(sorted(pairs.items()))
+    except Exception as e:
+        raise OperationalException(f"Cannot get markets. Reason: {e}") from e
+
+    else:
+        summary_str = ((f"Exchange {exchange.name} has {len(pairs)} ") +
+                       ("active " if active_only else "") +
+                       (plural(len(pairs), "pair" if pairs_only else "market")) +
+                       (f" with {', '.join(base_currencies)} as base "
+                        f"{plural(len(base_currencies), 'currency', 'currencies')}"
+                        if base_currencies else "") +
+                       (" and" if base_currencies and quote_currencies else "") +
+                       (f" with {', '.join(quote_currencies)} as quote "
+                        f"{plural(len(quote_currencies), 'currency', 'currencies')}"
+                        if quote_currencies else ""))
+
+        headers = ["Id", "Symbol", "Base", "Quote", "Active",
+                   *(['Is pair'] if not pairs_only else [])]
+
+        tabular_data = []
+        for _, v in pairs.items():
+            tabular_data.append({'Id': v['id'], 'Symbol': v['symbol'],
+                                 'Base': v['base'], 'Quote': v['quote'],
+                                 'Active': market_is_active(v),
+                                 **({'Is pair': exchange.market_is_tradable(v)}
+                                    if not pairs_only else {})})
+
+        if (args.get('print_one_column', False) or
+                args.get('list_pairs_print_json', False) or
+                args.get('print_csv', False)):
+            # Print summary string in the log in case of machine-readable
+            # regular formats.
+            logger.info(f"{summary_str}.")
+        else:
+            # Print empty string separating leading logs and output in case of
+            # human-readable formats.
+            print()
+
+        if len(pairs):
+            if args.get('print_list', False):
+                # print data as a list, with human-readable summary
+                print(f"{summary_str}: {', '.join(pairs.keys())}.")
+            elif args.get('print_one_column', False):
+                print('\n'.join(pairs.keys()))
+            elif args.get('list_pairs_print_json', False):
+                print(rapidjson.dumps(list(pairs.keys()), default=str))
+            elif args.get('print_csv', False):
+                writer = csv.DictWriter(sys.stdout, fieldnames=headers)
+                writer.writeheader()
+                writer.writerows(tabular_data)
+            else:
+                # print data as a table, with the human-readable summary
+                print(f"{summary_str}:")
+                print(tabulate(tabular_data, headers='keys', tablefmt='psql', stralign='right'))
+        elif not (args.get('print_one_column', False) or
+                  args.get('list_pairs_print_json', False) or
+                  args.get('print_csv', False)):
+            print(f"{summary_str}.")
+
+
+def start_show_trades(args: Dict[str, Any]) -> None:
+    """
+    Show trades
+    """
+    import json
+
+    from freqtrade.persistence import Trade, init_db
+    config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
+
+    if 'db_url' not in config:
+        raise OperationalException("--db-url is required for this command.")
+
+    logger.info(f'Using DB: "{config["db_url"]}"')
+    init_db(config['db_url'], clean_open_orders=False)
+    tfilter = []
+
+    if config.get('trade_ids'):
+        tfilter.append(Trade.id.in_(config['trade_ids']))
+
+    trades = Trade.get_trades(tfilter).all()
+    logger.info(f"Printing {len(trades)} Trades: ")
+    if config.get('print_json', False):
+        print(json.dumps([trade.to_json() for trade in trades], indent=4))
+    else:
+        for trade in trades:
+            print(trade)
diff --git a/freqtrade/commands/optimize_commands.py b/freqtrade/commands/optimize_commands.py
new file mode 100644
index 000000000..7411ca9c6
--- /dev/null
+++ b/freqtrade/commands/optimize_commands.py
@@ -0,0 +1,110 @@
+import logging
+from typing import Any, Dict
+
+from freqtrade import constants
+from freqtrade.configuration import setup_utils_configuration
+from freqtrade.exceptions import DependencyException, OperationalException
+from freqtrade.state import RunMode
+
+
+logger = logging.getLogger(__name__)
+
+
+def setup_optimize_configuration(args: Dict[str, Any], method: RunMode) -> Dict[str, Any]:
+    """
+    Prepare the configuration for the Hyperopt module
+    :param args: Cli args from Arguments()
+    :return: Configuration
+    """
+    config = setup_utils_configuration(args, method)
+
+    no_unlimited_runmodes = {
+        RunMode.BACKTEST: 'backtesting',
+        RunMode.HYPEROPT: 'hyperoptimization',
+    }
+    if (method in no_unlimited_runmodes.keys() and
+            config['stake_amount'] == constants.UNLIMITED_STAKE_AMOUNT):
+        raise DependencyException(
+            f'The value of `stake_amount` cannot be set as "{constants.UNLIMITED_STAKE_AMOUNT}" '
+            f'for {no_unlimited_runmodes[method]}')
+
+    return config
+
+
+def start_backtesting(args: Dict[str, Any]) -> None:
+    """
+    Start Backtesting script
+    :param args: Cli args from Arguments()
+    :return: None
+    """
+    # Import here to avoid loading backtesting module when it's not used
+    from freqtrade.optimize.backtesting import Backtesting
+
+    # Initialize configuration
+    config = setup_optimize_configuration(args, RunMode.BACKTEST)
+
+    logger.info('Starting freqtrade in Backtesting mode')
+
+    # Initialize backtesting object
+    backtesting = Backtesting(config)
+    backtesting.start()
+
+
+def start_hyperopt(args: Dict[str, Any]) -> None:
+    """
+    Start hyperopt script
+    :param args: Cli args from Arguments()
+    :return: None
+    """
+    # Import here to avoid loading hyperopt module when it's not used
+    try:
+        from filelock import FileLock, Timeout
+
+        from freqtrade.optimize.hyperopt import Hyperopt
+    except ImportError as e:
+        raise OperationalException(
+            f"{e}. Please ensure that the hyperopt dependencies are installed.") from e
+    # Initialize configuration
+    config = setup_optimize_configuration(args, RunMode.HYPEROPT)
+
+    logger.info('Starting freqtrade in Hyperopt mode')
+
+    lock = FileLock(Hyperopt.get_lock_filename(config))
+
+    try:
+        with lock.acquire(timeout=1):
+
+            # Remove noisy log messages
+            logging.getLogger('hyperopt.tpe').setLevel(logging.WARNING)
+            logging.getLogger('filelock').setLevel(logging.WARNING)
+
+            # Initialize backtesting object
+            hyperopt = Hyperopt(config)
+            hyperopt.start()
+
+    except Timeout:
+        logger.info("Another running instance of freqtrade Hyperopt detected.")
+        logger.info("Simultaneous execution of multiple Hyperopt commands is not supported. "
+                    "Hyperopt module is resource hungry. Please run your Hyperopt sequentially "
+                    "or on separate machines.")
+        logger.info("Quitting now.")
+        # TODO: return False here in order to help freqtrade to exit
+        # with non-zero exit code...
+        # Same in Edge and Backtesting start() functions.
+
+
+def start_edge(args: Dict[str, Any]) -> None:
+    """
+    Start Edge script
+    :param args: Cli args from Arguments()
+    :return: None
+    """
+    from freqtrade.optimize.edge_cli import EdgeCli
+
+    # Initialize configuration
+    config = setup_optimize_configuration(args, RunMode.EDGE)
+    logger.info('Starting freqtrade in Edge mode')
+
+    # Initialize Edge object
+    edge_cli = EdgeCli(config)
+    edge_cli.start()
diff --git a/freqtrade/commands/pairlist_commands.py b/freqtrade/commands/pairlist_commands.py
new file mode 100644
index 000000000..e4ee80ca5
--- /dev/null
+++ b/freqtrade/commands/pairlist_commands.py
@@ -0,0 +1,42 @@
+import logging
+from typing import Any, Dict
+
+import rapidjson
+
+from freqtrade.configuration import setup_utils_configuration
+from freqtrade.resolvers import ExchangeResolver
+from freqtrade.state import RunMode
+
+
+logger = logging.getLogger(__name__)
+
+
+def start_test_pairlist(args: Dict[str, Any]) -> None:
+    """
+    Test Pairlist configuration
+    """
+    from freqtrade.pairlist.pairlistmanager import PairListManager
+    config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
+
+    exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
+
+    quote_currencies = args.get('quote_currencies')
+    if not quote_currencies:
+        quote_currencies = [config.get('stake_currency')]
+    results = {}
+    for curr in quote_currencies:
+        config['stake_currency'] = curr
+        pairlists = PairListManager(exchange, config)
+        pairlists.refresh_pairlist()
+        results[curr] = pairlists.whitelist
+
+    for curr, pairlist in results.items():
+        if not args.get('print_one_column', False):
+            print(f"Pairs for {curr}: ")
+
+        if args.get('print_one_column', False):
+            print('\n'.join(pairlist))
+        elif args.get('list_pairs_print_json', False):
+            print(rapidjson.dumps(list(pairlist), default=str))
+        else:
+            print(pairlist)
diff --git a/freqtrade/commands/plot_commands.py b/freqtrade/commands/plot_commands.py
new file mode 100644
index 000000000..5e547acb0
--- /dev/null
+++ b/freqtrade/commands/plot_commands.py
@@ -0,0 +1,36 @@
+from typing import Any, Dict
+
+from freqtrade.configuration import setup_utils_configuration
+from freqtrade.exceptions import OperationalException
+from freqtrade.state import RunMode
+
+
+def validate_plot_args(args: Dict[str, Any]) -> None:
+    if not args.get('datadir') and not args.get('config'):
+        raise OperationalException(
+            "You need to specify either `--datadir` or `--config` "
+            "for plot-profit and plot-dataframe.")
+
+
+def start_plot_dataframe(args: Dict[str, Any]) -> None:
+    """
+    Entrypoint for dataframe plotting
+    """
+    # Import here to avoid errors if plot-dependencies are not installed.
+    from freqtrade.plot.plotting import load_and_plot_trades
+    validate_plot_args(args)
+    config = setup_utils_configuration(args, RunMode.PLOT)
+
+    load_and_plot_trades(config)
+
+
+def start_plot_profit(args: Dict[str, Any]) -> None:
+    """
+    Entrypoint for plot_profit
+    """
+    # Import here to avoid errors if plot-dependencies are not installed.
+    from freqtrade.plot.plotting import plot_profit
+    validate_plot_args(args)
+    config = setup_utils_configuration(args, RunMode.PLOT)
+
+    plot_profit(config)
diff --git a/freqtrade/commands/trade_commands.py b/freqtrade/commands/trade_commands.py
new file mode 100644
index 000000000..535844844
--- /dev/null
+++ b/freqtrade/commands/trade_commands.py
@@ -0,0 +1,29 @@
+import logging
+from typing import Any, Dict
+
+
+logger = logging.getLogger(__name__)
+
+
+def start_trading(args: Dict[str, Any]) -> int:
+    """
+    Main entry point for trading mode
+    """
+    # Import here to avoid loading worker module when it's not used
+    from freqtrade.worker import Worker
+
+    # Create and run worker
+    worker = None
+    try:
+        worker = Worker(args)
+        worker.run()
+    except Exception as e:
+        logger.error(str(e))
+        logger.exception("Fatal exception!")
+    except KeyboardInterrupt:
+        logger.info('SIGINT received, aborting ...')
+    finally:
+        if worker:
+            logger.info("worker found ... calling exit")
+            worker.exit()
+    return 0
diff --git a/freqtrade/configuration/__init__.py b/freqtrade/configuration/__init__.py
index 548b508a7..607f9cdef 100644
--- a/freqtrade/configuration/__init__.py
+++ b/freqtrade/configuration/__init__.py
@@ -1,2 +1,7 @@
-from freqtrade.configuration.arguments import Arguments, TimeRange  # noqa: F401
-from freqtrade.configuration.configuration import Configuration  # noqa: F401
+# flake8: noqa: F401
+
+from freqtrade.configuration.check_exchange import check_exchange, remove_credentials
+from freqtrade.configuration.config_setup import setup_utils_configuration
+from freqtrade.configuration.config_validation import validate_config_consistency
+from freqtrade.configuration.configuration import Configuration
+from freqtrade.configuration.timerange import TimeRange
diff --git a/freqtrade/configuration/arguments.py b/freqtrade/configuration/arguments.py
deleted file mode 100644
index 3bbdc4bc2..000000000
--- a/freqtrade/configuration/arguments.py
+++ /dev/null
@@ -1,466 +0,0 @@
-"""
-This module contains the argument manager class
-"""
-import argparse
-import os
-import re
-from typing import List, NamedTuple, Optional
-
-import arrow
-from freqtrade import __version__, constants
-
-
-def check_int_positive(value: str) -> int:
-    try:
-        uint = int(value)
-        if uint <= 0:
-            raise ValueError
-    except ValueError:
-        raise argparse.ArgumentTypeError(
-            f"{value} is invalid for this parameter, should be a positive integer value"
-        )
-    return uint
-
-
-class Arg:
-    # Optional CLI arguments
-    def __init__(self, *args, **kwargs):
-        self.cli = args
-        self.kwargs = kwargs
-
-
-# List of available command line options
-AVAILABLE_CLI_OPTIONS = {
-    # Common options
-    "verbosity": Arg(
-        '-v', '--verbose',
-        help='Verbose mode (-vv for more, -vvv to get all messages).',
-        action='count',
-        default=0,
-    ),
-    "logfile": Arg(
-        '--logfile',
-        help='Log to the file specified.',
-        metavar='FILE',
-    ),
-    "version": Arg(
-        '-V', '--version',
-        action='version',
-        version=f'%(prog)s {__version__}',
-    ),
-    "config": Arg(
-        '-c', '--config',
-        help=f'Specify configuration file (default: `{constants.DEFAULT_CONFIG}`). '
-        f'Multiple --config options may be used. '
-        f'Can be set to `-` to read config from stdin.',
-        action='append',
-        metavar='PATH',
-    ),
-    "datadir": Arg(
-        '-d', '--datadir',
-        help='Path to backtest data.',
-        metavar='PATH',
-    ),
-    # Main options
-    "strategy": Arg(
-        '-s', '--strategy',
-        help='Specify strategy class name (default: `%(default)s`).',
-        metavar='NAME',
-        default='DefaultStrategy',
-    ),
-    "strategy_path": Arg(
-        '--strategy-path',
-        help='Specify additional strategy lookup path.',
-        metavar='PATH',
-    ),
-    "db_url": Arg(
-        '--db-url',
-        help=f'Override trades database URL, this is useful in custom deployments '
-        f'(default: `{constants.DEFAULT_DB_PROD_URL}` for Live Run mode, '
-        f'`{constants.DEFAULT_DB_DRYRUN_URL}` for Dry Run).',
-        metavar='PATH',
-    ),
-    "sd_notify": Arg(
-        '--sd-notify',
-        help='Notify systemd service manager.',
-        action='store_true',
-    ),
-    # Optimize common
-    "ticker_interval": Arg(
-        '-i', '--ticker-interval',
-        help='Specify ticker interval (`1m`, `5m`, `30m`, `1h`, `1d`).',
-    ),
-    "timerange": Arg(
-        '--timerange',
-        help='Specify what timerange of data to use.',
-    ),
-    "max_open_trades": Arg(
-        '--max_open_trades',
-        help='Specify max_open_trades to use.',
-        type=int,
-        metavar='INT',
-    ),
-    "stake_amount": Arg(
-        '--stake_amount',
-        help='Specify stake_amount.',
-        type=float,
-    ),
-    "refresh_pairs": Arg(
-        '-r', '--refresh-pairs-cached',
-        help='Refresh the pairs files in tests/testdata with the latest data from the '
-        'exchange. Use it if you want to run your optimization commands with '
-        'up-to-date data.',
-        action='store_true',
-    ),
-    # Backtesting
-    "position_stacking": Arg(
-        '--eps', '--enable-position-stacking',
-        help='Allow buying the same pair multiple times (position stacking).',
-        action='store_true',
-        default=False,
-    ),
-    "use_max_market_positions": Arg(
-        '--dmmp', '--disable-max-market-positions',
-        help='Disable applying `max_open_trades` during backtest '
-        '(same as setting `max_open_trades` to a very high number).',
-        action='store_false',
-        default=True,
-    ),
-    "live": Arg(
-        '-l', '--live',
-        help='Use live data.',
-        action='store_true',
-    ),
-    "strategy_list": Arg(
-        '--strategy-list',
-        help='Provide a comma-separated list of strategies to backtest. '
-        'Please note that ticker-interval needs to be set either in config '
-        'or via command line. When using this together with `--export trades`, '
-        'the strategy-name is injected into the filename '
-        '(so `backtest-data.json` becomes `backtest-data-DefaultStrategy.json`',
-        nargs='+',
-    ),
-    "export": Arg(
-        '--export',
-        help='Export backtest results, argument are: trades. '
-        'Example: `--export=trades`',
-    ),
-    "exportfilename": Arg(
-        '--export-filename',
-        help='Save backtest results to the file with this filename (default: `%(default)s`). '
-        'Requires `--export` to be set as well. '
-        'Example: `--export-filename=user_data/backtest_data/backtest_today.json`',
-        metavar='PATH',
-        default=os.path.join('user_data', 'backtest_data',
-                             'backtest-result.json'),
-    ),
-    # Edge
-    "stoploss_range": Arg(
-        '--stoplosses',
-        help='Defines a range of stoploss values against which edge will assess the strategy. '
-        'The format is "min,max,step" (without any space). '
-        'Example: `--stoplosses=-0.01,-0.1,-0.001`',
-    ),
-    # Hyperopt
-    "hyperopt": Arg(
-        '--customhyperopt',
-        help='Specify hyperopt class name (default: `%(default)s`).',
-        metavar='NAME',
-        default=constants.DEFAULT_HYPEROPT,
-    ),
-    "epochs": Arg(
-        '-e', '--epochs',
-        help='Specify number of epochs (default: %(default)d).',
-        type=check_int_positive,
-        metavar='INT',
-        default=constants.HYPEROPT_EPOCH,
-    ),
-    "spaces": Arg(
-        '-s', '--spaces',
-        help='Specify which parameters to hyperopt. Space-separated list. '
-        'Default: `%(default)s`.',
-        choices=['all', 'buy', 'sell', 'roi', 'stoploss'],
-        nargs='+',
-        default='all',
-    ),
-    "print_all": Arg(
-        '--print-all',
-        help='Print all results, not only the best ones.',
-        action='store_true',
-        default=False,
-    ),
-    "hyperopt_jobs": Arg(
-        '-j', '--job-workers',
-        help='The number of concurrently running jobs for hyperoptimization '
-        '(hyperopt worker processes). '
-        'If -1 (default), all CPUs are used, for -2, all CPUs but one are used, etc. '
-        'If 1 is given, no parallel computing code is used at all.',
-        type=int,
-        metavar='JOBS',
-        default=-1,
-    ),
-    "hyperopt_random_state": Arg(
-        '--random-state',
-        help='Set random state to some positive integer for reproducible hyperopt results.',
-        type=check_int_positive,
-        metavar='INT',
-    ),
-    "hyperopt_min_trades": Arg(
-        '--min-trades',
-        help="Set minimal desired number of trades for evaluations in the hyperopt "
-        "optimization path (default: 1).",
-        type=check_int_positive,
-        metavar='INT',
-        default=1,
-    ),
-    "hyperopt_continue": Arg(
-        "--continue",
-        help="Continue hyperopt from previous runs. "
-        "By default, temporary files will be removed and hyperopt will start from scratch.",
-        default=False,
-        action='store_true',
-    ),
-    "hyperopt_loss": Arg(
-        '--hyperopt-loss',
-        help='Specify the class name of the hyperopt loss function class (IHyperOptLoss). '
-        'Different functions can generate completely different results, '
-        'since the target for optimization is different. (default: `%(default)s`).',
-        metavar='NAME',
-        default=constants.DEFAULT_HYPEROPT_LOSS,
-    ),
-    # List exchanges
-    "print_one_column": Arg(
-        '-1', '--one-column',
-        help='Print exchanges in one column.',
-        action='store_true',
-    ),
-    # Script options
-    "pairs": Arg(
-        '-p', '--pairs',
-        help='Show profits for only these pairs. Pairs are comma-separated.',
-    ),
-    # Download data
-    "pairs_file": Arg(
-        '--pairs-file',
-        help='File containing a list of pairs to download.',
-        metavar='FILE',
-    ),
-    "days": Arg(
-        '--days',
-        help='Download data for given number of days.',
-        type=check_int_positive,
-        metavar='INT',
-    ),
-    "exchange": Arg(
-        '--exchange',
-        help=f'Exchange name (default: `{constants.DEFAULT_EXCHANGE}`). '
-        f'Only valid if no config is provided.',
-    ),
-    "timeframes": Arg(
-        '-t', '--timeframes',
-        help=f'Specify which tickers to download. Space-separated list. '
-        f'Default: `{constants.DEFAULT_DOWNLOAD_TICKER_INTERVALS}`.',
-        choices=['1m', '3m', '5m', '15m', '30m', '1h', '2h', '4h',
-                 '6h', '8h', '12h', '1d', '3d', '1w'],
-        nargs='+',
-    ),
-    "erase": Arg(
-        '--erase',
-        help='Clean all existing data for the selected exchange/pairs/timeframes.',
-        action='store_true',
-    ),
-    # Plot dataframe
-    "indicators1": Arg(
-        '--indicators1',
-        help='Set indicators from your strategy you want in the first row of the graph. '
-        'Comma-separated list. Example: `ema3,ema5`. Default: `%(default)s`.',
-        default='sma,ema3,ema5',
-    ),
-    "indicators2": Arg(
-        '--indicators2',
-        help='Set indicators from your strategy you want in the third row of the graph. '
-        'Comma-separated list. Example: `fastd,fastk`. Default: `%(default)s`.',
-        default='macd,macdsignal',
-    ),
-    "plot_limit": Arg(
-        '--plot-limit',
-        help='Specify tick limit for plotting. Notice: too high values cause huge files. '
-        'Default: %(default)s.',
-        type=check_int_positive,
-        metavar='INT',
-        default=750,
-    ),
-    "trade_source": Arg(
-        '--trade-source',
-        help='Specify the source for trades (Can be DB or file (backtest file)) '
-        'Default: %(default)s',
-        choices=["DB", "file"],
-        default="file",
-    ),
-}
-
-
-ARGS_COMMON = ["verbosity", "logfile", "version", "config", "datadir"]
-
-ARGS_STRATEGY = ["strategy", "strategy_path"]
-
-ARGS_MAIN = ARGS_COMMON + ARGS_STRATEGY + ["db_url", "sd_notify"]
-
-ARGS_COMMON_OPTIMIZE = ["ticker_interval", "timerange",
-                        "max_open_trades", "stake_amount", "refresh_pairs"]
-
-ARGS_BACKTEST = ARGS_COMMON_OPTIMIZE + ["position_stacking", "use_max_market_positions",
-                                        "live", "strategy_list", "export", "exportfilename"]
-
-ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "position_stacking", "epochs", "spaces",
-                                        "use_max_market_positions", "print_all", "hyperopt_jobs",
-                                        "hyperopt_random_state", "hyperopt_min_trades",
-                                        "hyperopt_continue", "hyperopt_loss"]
-
-ARGS_EDGE = ARGS_COMMON_OPTIMIZE + ["stoploss_range"]
-
-ARGS_LIST_EXCHANGES = ["print_one_column"]
-
-ARGS_DOWNLOADER = ARGS_COMMON + ["pairs", "pairs_file", "days", "exchange", "timeframes", "erase"]
-
-ARGS_PLOT_DATAFRAME = (ARGS_COMMON + ARGS_STRATEGY +
-                       ["pairs", "indicators1", "indicators2", "plot_limit", "db_url",
-                        "trade_source", "export", "exportfilename", "timerange",
-                        "refresh_pairs", "live"])
-
-ARGS_PLOT_PROFIT = (ARGS_COMMON + ARGS_STRATEGY +
-                    ["pairs", "timerange", "export", "exportfilename", "db_url", "trade_source"])
-
-
-class TimeRange(NamedTuple):
-    """
-    NamedTuple defining timerange inputs.
-    [start/stop]type defines if [start/stop]ts shall be used.
-    if *type is None, don't use corresponding startvalue.
-    """
-    starttype: Optional[str] = None
-    stoptype: Optional[str] = None
-    startts: int = 0
-    stopts: int = 0
-
-
-class Arguments(object):
-    """
-    Arguments Class. Manage the arguments received by the cli
-    """
-    def __init__(self, args: Optional[List[str]], description: str,
-                 no_default_config: bool = False) -> None:
-        self.args = args
-        self._parsed_arg: Optional[argparse.Namespace] = None
-        self.parser = argparse.ArgumentParser(description=description)
-        self._no_default_config = no_default_config
-
-    def _load_args(self) -> None:
-        self._build_args(optionlist=ARGS_MAIN)
-        self._build_subcommands()
-
-    def get_parsed_arg(self) -> argparse.Namespace:
-        """
-        Return the list of arguments
-        :return: List[str] List of arguments
-        """
-        if self._parsed_arg is None:
-            self._load_args()
-            self._parsed_arg = self._parse_args()
-
-        return self._parsed_arg
-
-    def _parse_args(self) -> argparse.Namespace:
-        """
-        Parses given arguments and returns an argparse Namespace instance.
-        """
-        parsed_arg = self.parser.parse_args(self.args)
-
-        # Workaround issue in argparse with action='append' and default value
-        # (see https://bugs.python.org/issue16399)
-        if not self._no_default_config and parsed_arg.config is None:
-            parsed_arg.config = [constants.DEFAULT_CONFIG]
-
-        return parsed_arg
-
-    def _build_args(self, optionlist, parser=None):
-        parser = parser or self.parser
-
-        for val in optionlist:
-            opt = AVAILABLE_CLI_OPTIONS[val]
-            parser.add_argument(*opt.cli, dest=val, **opt.kwargs)
-
-    def _build_subcommands(self) -> None:
-        """
-        Builds and attaches all subcommands.
-        :return: None
-        """
-        from freqtrade.optimize import start_backtesting, start_hyperopt, start_edge
-        from freqtrade.utils import start_list_exchanges
-
-        subparsers = self.parser.add_subparsers(dest='subparser')
-
-        # Add backtesting subcommand
-        backtesting_cmd = subparsers.add_parser('backtesting', help='Backtesting module.')
-        backtesting_cmd.set_defaults(func=start_backtesting)
-        self._build_args(optionlist=ARGS_BACKTEST, parser=backtesting_cmd)
-
-        # Add edge subcommand
-        edge_cmd = subparsers.add_parser('edge', help='Edge module.')
-        edge_cmd.set_defaults(func=start_edge)
-        self._build_args(optionlist=ARGS_EDGE, parser=edge_cmd)
-
-        # Add hyperopt subcommand
-        hyperopt_cmd = subparsers.add_parser('hyperopt', help='Hyperopt module.')
-        hyperopt_cmd.set_defaults(func=start_hyperopt)
-        self._build_args(optionlist=ARGS_HYPEROPT, parser=hyperopt_cmd)
-
-        # Add list-exchanges subcommand
-        list_exchanges_cmd = subparsers.add_parser(
-            'list-exchanges',
-            help='Print available exchanges.'
-        )
-        list_exchanges_cmd.set_defaults(func=start_list_exchanges)
-        self._build_args(optionlist=ARGS_LIST_EXCHANGES, parser=list_exchanges_cmd)
-
-    @staticmethod
-    def parse_timerange(text: Optional[str]) -> TimeRange:
-        """
-        Parse the value of the argument --timerange to determine what is the range desired
-        :param text: value from --timerange
-        :return: Start and End range period
-        """
-        if text is None:
-            return TimeRange(None, None, 0, 0)
-        syntax = [(r'^-(\d{8})$', (None, 'date')),
-                  (r'^(\d{8})-$', ('date', None)),
-                  (r'^(\d{8})-(\d{8})$', ('date', 'date')),
-                  (r'^-(\d{10})$', (None, 'date')),
-                  (r'^(\d{10})-$', ('date', None)),
-                  (r'^(\d{10})-(\d{10})$', ('date', 'date')),
-                  (r'^(-\d+)$', (None, 'line')),
-                  (r'^(\d+)-$', ('line', None)),
-                  (r'^(\d+)-(\d+)$', ('index', 'index'))]
-        for rex, stype in syntax:
-            # Apply the regular expression to text
-            match = re.match(rex, text)
-            if match:  # Regex has matched
-                rvals = match.groups()
-                index = 0
-                start: int = 0
-                stop: int = 0
-                if stype[0]:
-                    starts = rvals[index]
-                    if stype[0] == 'date' and len(starts) == 8:
-                        start = arrow.get(starts, 'YYYYMMDD').timestamp
-                    else:
-                        start = int(starts)
-                    index += 1
-                if stype[1]:
-                    stops = rvals[index]
-                    if stype[1] == 'date' and len(stops) == 8:
-                        stop = arrow.get(stops, 'YYYYMMDD').timestamp
-                    else:
-                        stop = int(stops)
-                return TimeRange(stype[0], stype[1], start, stop)
-        raise Exception('Incorrect syntax for timerange "%s"' % text)
diff --git a/freqtrade/configuration/check_exchange.py b/freqtrade/configuration/check_exchange.py
index 8dae06f7a..aa36de3ff 100644
--- a/freqtrade/configuration/check_exchange.py
+++ b/freqtrade/configuration/check_exchange.py
@@ -1,14 +1,28 @@
 import logging
 from typing import Any, Dict
 
-from freqtrade import OperationalException
-from freqtrade.exchange import (is_exchange_bad, is_exchange_available,
-                                is_exchange_officially_supported, available_exchanges)
+from freqtrade.exceptions import OperationalException
+from freqtrade.exchange import (available_exchanges, get_exchange_bad_reason, is_exchange_bad,
+                                is_exchange_known_ccxt, is_exchange_officially_supported)
+from freqtrade.state import RunMode
 
 
 logger = logging.getLogger(__name__)
 
 
+def remove_credentials(config: Dict[str, Any]) -> None:
+    """
+    Removes exchange keys from the configuration and specifies dry-run
+    Used for backtesting / hyperopt / edge and utils.
+    Modifies the input dict!
+    """
+    config['exchange']['key'] = ''
+    config['exchange']['secret'] = ''
+    config['exchange']['password'] = ''
+    config['exchange']['uid'] = ''
+    config['dry_run'] = True
+
+
 def check_exchange(config: Dict[str, Any], check_for_bad: bool = True) -> bool:
     """
     Check if the exchange name in the config file is supported by Freqtrade
@@ -19,28 +33,40 @@ def check_exchange(config: Dict[str, Any], check_for_bad: bool = True) -> bool:
              raises an exception if the exchange if not supported by ccxt
              and thus is not known for the Freqtrade at all.
     """
+
+    if (config['runmode'] in [RunMode.PLOT, RunMode.UTIL_NO_EXCHANGE, RunMode.OTHER]
+       and not config.get('exchange', {}).get('name')):
+        # Skip checking exchange in plot mode, since it requires no exchange
+        return True
     logger.info("Checking exchange...")
 
     exchange = config.get('exchange', {}).get('name').lower()
-    if not is_exchange_available(exchange):
+    if not exchange:
         raise OperationalException(
-                f'Exchange "{exchange}" is not supported by ccxt '
+            f'This command requires a configured exchange. You should either use '
+            f'`--exchange <exchange_name>` or specify a configuration file via `--config`.\n'
+            f'The following exchanges are available for Freqtrade: '
+            f'{", ".join(available_exchanges())}'
+        )
+
+    if not is_exchange_known_ccxt(exchange):
+        raise OperationalException(
+                f'Exchange "{exchange}" is not known to the ccxt library '
                 f'and therefore not available for the bot.\n'
-                f'The following exchanges are supported by ccxt: '
+                f'The following exchanges are available for Freqtrade: '
                 f'{", ".join(available_exchanges())}'
         )
 
     if check_for_bad and is_exchange_bad(exchange):
-        logger.warning(f'Exchange "{exchange}" is known to not work with the bot yet. '
-                       f'Use it only for development and testing purposes.')
-        return False
+        raise OperationalException(f'Exchange "{exchange}" is known to not work with the bot yet. '
+                                   f'Reason: {get_exchange_bad_reason(exchange)}')
 
     if is_exchange_officially_supported(exchange):
         logger.info(f'Exchange "{exchange}" is officially supported '
                     f'by the Freqtrade development team.')
     else:
-        logger.warning(f'Exchange "{exchange}" is supported by ccxt '
-                       f'and therefore available for the bot but not officially supported '
+        logger.warning(f'Exchange "{exchange}" is known to the the ccxt library, '
+                       f'available for the bot, but not officially supported '
                        f'by the Freqtrade development team. '
                        f'It may work flawlessly (please report back) or have serious issues. '
                        f'Use it at your own discretion.')
diff --git a/freqtrade/configuration/config_setup.py b/freqtrade/configuration/config_setup.py
new file mode 100644
index 000000000..3b0f778f4
--- /dev/null
+++ b/freqtrade/configuration/config_setup.py
@@ -0,0 +1,27 @@
+import logging
+from typing import Any, Dict
+
+from freqtrade.state import RunMode
+
+from .check_exchange import remove_credentials
+from .config_validation import validate_config_consistency
+from .configuration import Configuration
+
+
+logger = logging.getLogger(__name__)
+
+
+def setup_utils_configuration(args: Dict[str, Any], method: RunMode) -> Dict[str, Any]:
+    """
+    Prepare the configuration for utils subcommands
+    :param args: Cli args from Arguments()
+    :return: Configuration
+    """
+    configuration = Configuration(args, method)
+    config = configuration.get_config()
+
+    # Ensure we do not use Exchange credentials
+    remove_credentials(config)
+    validate_config_consistency(config)
+
+    return config
diff --git a/freqtrade/configuration/config_validation.py b/freqtrade/configuration/config_validation.py
new file mode 100644
index 000000000..d4612d8e0
--- /dev/null
+++ b/freqtrade/configuration/config_validation.py
@@ -0,0 +1,153 @@
+import logging
+from copy import deepcopy
+from typing import Any, Dict
+
+from jsonschema import Draft4Validator, validators
+from jsonschema.exceptions import ValidationError, best_match
+
+from freqtrade import constants
+from freqtrade.exceptions import OperationalException
+from freqtrade.state import RunMode
+
+
+logger = logging.getLogger(__name__)
+
+
+def _extend_validator(validator_class):
+    """
+    Extended validator for the Freqtrade configuration JSON Schema.
+    Currently it only handles defaults for subschemas.
+    """
+    validate_properties = validator_class.VALIDATORS['properties']
+
+    def set_defaults(validator, properties, instance, schema):
+        for prop, subschema in properties.items():
+            if 'default' in subschema:
+                instance.setdefault(prop, subschema['default'])
+
+        for error in validate_properties(
+            validator, properties, instance, schema,
+        ):
+            yield error
+
+    return validators.extend(
+        validator_class, {'properties': set_defaults}
+    )
+
+
+FreqtradeValidator = _extend_validator(Draft4Validator)
+
+
+def validate_config_schema(conf: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    Validate the configuration follow the Config Schema
+    :param conf: Config in JSON format
+    :return: Returns the config if valid, otherwise throw an exception
+    """
+    conf_schema = deepcopy(constants.CONF_SCHEMA)
+    if conf.get('runmode', RunMode.OTHER) in (RunMode.DRY_RUN, RunMode.LIVE):
+        conf_schema['required'] = constants.SCHEMA_TRADE_REQUIRED
+    else:
+        conf_schema['required'] = constants.SCHEMA_MINIMAL_REQUIRED
+    try:
+        FreqtradeValidator(conf_schema).validate(conf)
+        return conf
+    except ValidationError as e:
+        logger.critical(
+            f"Invalid configuration. See config.json.example. Reason: {e}"
+        )
+        raise ValidationError(
+            best_match(Draft4Validator(conf_schema).iter_errors(conf)).message
+        )
+
+
+def validate_config_consistency(conf: Dict[str, Any]) -> None:
+    """
+    Validate the configuration consistency.
+    Should be ran after loading both configuration and strategy,
+    since strategies can set certain configuration settings too.
+    :param conf: Config in JSON format
+    :return: Returns None if everything is ok, otherwise throw an OperationalException
+    """
+
+    # validating trailing stoploss
+    _validate_trailing_stoploss(conf)
+    _validate_edge(conf)
+    _validate_whitelist(conf)
+    _validate_unlimited_amount(conf)
+
+    # validate configuration before returning
+    logger.info('Validating configuration ...')
+    validate_config_schema(conf)
+
+
+def _validate_unlimited_amount(conf: Dict[str, Any]) -> None:
+    """
+    If edge is disabled, either max_open_trades or stake_amount need to be set.
+    :raise: OperationalException if config validation failed
+    """
+    if (not conf.get('edge', {}).get('enabled')
+       and conf.get('max_open_trades') == float('inf')
+       and conf.get('stake_amount') == constants.UNLIMITED_STAKE_AMOUNT):
+        raise OperationalException("`max_open_trades` and `stake_amount` cannot both be unlimited.")
+
+
+def _validate_trailing_stoploss(conf: Dict[str, Any]) -> None:
+
+    if conf.get('stoploss') == 0.0:
+        raise OperationalException(
+            'The config stoploss needs to be different from 0 to avoid problems with sell orders.'
+            )
+    # Skip if trailing stoploss is not activated
+    if not conf.get('trailing_stop', False):
+        return
+
+    tsl_positive = float(conf.get('trailing_stop_positive', 0))
+    tsl_offset = float(conf.get('trailing_stop_positive_offset', 0))
+    tsl_only_offset = conf.get('trailing_only_offset_is_reached', False)
+
+    if tsl_only_offset:
+        if tsl_positive == 0.0:
+            raise OperationalException(
+                'The config trailing_only_offset_is_reached needs '
+                'trailing_stop_positive_offset to be more than 0 in your config.')
+    if tsl_positive > 0 and 0 < tsl_offset <= tsl_positive:
+        raise OperationalException(
+            'The config trailing_stop_positive_offset needs '
+            'to be greater than trailing_stop_positive in your config.')
+
+    # Fetch again without default
+    if 'trailing_stop_positive' in conf and float(conf['trailing_stop_positive']) == 0.0:
+        raise OperationalException(
+            'The config trailing_stop_positive needs to be different from 0 '
+            'to avoid problems with sell orders.'
+        )
+
+
+def _validate_edge(conf: Dict[str, Any]) -> None:
+    """
+    Edge and Dynamic whitelist should not both be enabled, since edge overrides dynamic whitelists.
+    """
+
+    if not conf.get('edge', {}).get('enabled'):
+        return
+
+    if conf.get('pairlist', {}).get('method') == 'VolumePairList':
+        raise OperationalException(
+            "Edge and VolumePairList are incompatible, "
+            "Edge will override whatever pairs VolumePairlist selects."
+        )
+
+
+def _validate_whitelist(conf: Dict[str, Any]) -> None:
+    """
+    Dynamic whitelist does not require pair_whitelist to be set - however StaticWhitelist does.
+    """
+    if conf.get('runmode', RunMode.OTHER) in [RunMode.OTHER, RunMode.PLOT,
+                                              RunMode.UTIL_NO_EXCHANGE, RunMode.UTIL_EXCHANGE]:
+        return
+
+    for pl in conf.get('pairlists', [{'method': 'StaticPairList'}]):
+        if (pl.get('method') == 'StaticPairList'
+                and not conf.get('exchange', {}).get('pair_whitelist')):
+            raise OperationalException("StaticPairList requires pair_whitelist to be set.")
diff --git a/freqtrade/configuration/configuration.py b/freqtrade/configuration/configuration.py
index 737eb0900..1ca3187fb 100644
--- a/freqtrade/configuration/configuration.py
+++ b/freqtrade/configuration/configuration.py
@@ -1,31 +1,33 @@
 """
 This module contains the configuration class
 """
-import json
 import logging
-import sys
-from argparse import Namespace
-from typing import Any, Callable, Dict, Optional
+import warnings
+from copy import deepcopy
+from pathlib import Path
+from typing import Any, Callable, Dict, List, Optional
 
-from freqtrade import OperationalException, constants
+from freqtrade import constants
 from freqtrade.configuration.check_exchange import check_exchange
-from freqtrade.configuration.create_datadir import create_datadir
-from freqtrade.configuration.json_schema import validate_config_schema
+from freqtrade.configuration.deprecated_settings import process_temporary_deprecated_settings
+from freqtrade.configuration.directory_operations import create_datadir, create_userdata_dir
+from freqtrade.configuration.load_config import load_config_file
+from freqtrade.exceptions import OperationalException
 from freqtrade.loggers import setup_logging
-from freqtrade.misc import deep_merge_dicts
-from freqtrade.state import RunMode
+from freqtrade.misc import deep_merge_dicts, json_load
+from freqtrade.state import NON_UTIL_MODES, TRADING_MODES, RunMode
 
 
 logger = logging.getLogger(__name__)
 
 
-class Configuration(object):
+class Configuration:
     """
     Class to read and init the bot configuration
     Reuse this class for the bot, backtesting, hyperopt and every script that required configuration
     """
 
-    def __init__(self, args: Namespace, runmode: RunMode = None) -> None:
+    def __init__(self, args: Dict[str, Any], runmode: RunMode = None) -> None:
         self.args = args
         self.config: Optional[Dict[str, Any]] = None
         self.runmode = runmode
@@ -40,46 +42,48 @@ class Configuration(object):
 
         return self.config
 
-    def _load_config_files(self) -> Dict[str, Any]:
+    @staticmethod
+    def from_files(files: List[str]) -> Dict[str, Any]:
         """
-        Iterate through the config files passed in the args,
-        loading all of them and merging their contents.
+        Iterate through the config files passed in, loading all of them
+        and merging their contents.
+        Files are loaded in sequence, parameters in later configuration files
+        override the same parameter from an earlier file (last definition wins).
+        Runs through the whole Configuration initialization, so all expected config entries
+        are available to interactive environments.
+        :param files: List of file paths
+        :return: configuration dictionary
         """
+        c = Configuration({'config': files}, RunMode.OTHER)
+        return c.get_config()
+
+    def load_from_files(self, files: List[str]) -> Dict[str, Any]:
+
+        # Keep this method as staticmethod, so it can be used from interactive environments
         config: Dict[str, Any] = {}
 
+        if not files:
+            return deepcopy(constants.MINIMAL_CONFIG)
+
         # We expect here a list of config filenames
-        for path in self.args.config:
-            logger.info('Using config: %s ...', path)
+        for path in files:
+            logger.info(f'Using config: {path} ...')
 
             # Merge config options, overwriting old values
-            config = deep_merge_dicts(self._load_config_file(path), config)
+            config = deep_merge_dicts(load_config_file(path), config)
 
-        return config
-
-    def _load_config_file(self, path: str) -> Dict[str, Any]:
-        """
-        Loads a config file from the given path
-        :param path: path as str
-        :return: configuration as dictionary
-        """
-        try:
-            # Read config from stdin if requested in the options
-            with open(path) if path != '-' else sys.stdin as file:
-                config = json.load(file)
-        except FileNotFoundError:
-            raise OperationalException(
-                f'Config file "{path}" not found!'
-                ' Please create a config file or check whether it exists.')
-
-        return config
-
-    def _normalize_config(self, config: Dict[str, Any]) -> None:
-        """
-        Make config more canonical -- i.e. for example add missing parts that we expect
-        to be normally in it...
-        """
+        # Normalize config
         if 'internals' not in config:
             config['internals'] = {}
+        # TODO: This can be deleted along with removal of deprecated
+        # experimental settings
+        if 'ask_strategy' not in config:
+            config['ask_strategy'] = {}
+
+        if 'pairlists' not in config:
+            config['pairlists'] = []
+
+        return config
 
     def load_config(self) -> Dict[str, Any]:
         """
@@ -87,23 +91,29 @@ class Configuration(object):
         :return: Configuration dictionary
         """
         # Load all configs
-        config: Dict[str, Any] = self._load_config_files()
+        config: Dict[str, Any] = self.load_from_files(self.args.get("config", []))
 
-        # Make resulting config more canonical
-        self._normalize_config(config)
+        # Keep a copy of the original configuration file
+        config['original_config'] = deepcopy(config)
 
-        logger.info('Validating configuration ...')
-        validate_config_schema(config)
+        self._process_logging_options(config)
 
-        self._validate_config_consistency(config)
+        self._process_runmode(config)
 
         self._process_common_options(config)
 
+        self._process_trading_options(config)
+
         self._process_optimize_options(config)
 
         self._process_plot_options(config)
 
-        self._process_runmode(config)
+        # Check if the exchange set by the user is supported
+        check_exchange(config, config.get('experimental', {}).get('block_bad_exchanges', True))
+
+        self._resolve_pairs_list(config)
+
+        process_temporary_deprecated_settings(config)
 
         return config
 
@@ -113,34 +123,16 @@ class Configuration(object):
         the -v/--verbose, --logfile options
         """
         # Log level
-        if 'verbosity' in self.args and self.args.verbosity:
-            config.update({'verbosity': self.args.verbosity})
-        else:
-            config.update({'verbosity': 0})
+        config.update({'verbosity': self.args.get('verbosity', 0)})
 
-        if 'logfile' in self.args and self.args.logfile:
-            config.update({'logfile': self.args.logfile})
+        if 'logfile' in self.args and self.args['logfile']:
+            config.update({'logfile': self.args['logfile']})
 
         setup_logging(config)
 
-    def _process_strategy_options(self, config: Dict[str, Any]) -> None:
-
-        # Set strategy if not specified in config and or if it's non default
-        if self.args.strategy != constants.DEFAULT_STRATEGY or not config.get('strategy'):
-            config.update({'strategy': self.args.strategy})
-
-        if self.args.strategy_path:
-            config.update({'strategy_path': self.args.strategy_path})
-
-    def _process_common_options(self, config: Dict[str, Any]) -> None:
-
-        self._process_logging_options(config)
-        self._process_strategy_options(config)
-
-        if ('db_url' in self.args and self.args.db_url and
-                self.args.db_url != constants.DEFAULT_DB_PROD_URL):
-            config.update({'db_url': self.args.db_url})
-            logger.info('Parameter --db-url detected ...')
+    def _process_trading_options(self, config: Dict[str, Any]) -> None:
+        if config['runmode'] not in TRADING_MODES:
+            return
 
         if config.get('dry_run', False):
             logger.info('Dry run is enabled')
@@ -154,90 +146,125 @@ class Configuration(object):
 
         logger.info(f'Using DB: "{config["db_url"]}"')
 
+    def _process_common_options(self, config: Dict[str, Any]) -> None:
+
+        # Set strategy if not specified in config and or if it's non default
+        if self.args.get('strategy') or not config.get('strategy'):
+            config.update({'strategy': self.args.get('strategy')})
+
+        self._args_to_config(config, argname='strategy_path',
+                             logstring='Using additional Strategy lookup path: {}')
+
+        if ('db_url' in self.args and self.args['db_url'] and
+                self.args['db_url'] != constants.DEFAULT_DB_PROD_URL):
+            config.update({'db_url': self.args['db_url']})
+            logger.info('Parameter --db-url detected ...')
+
         if config.get('forcebuy_enable', False):
             logger.warning('`forcebuy` RPC message enabled.')
 
+        # Support for sd_notify
+        if 'sd_notify' in self.args and self.args['sd_notify']:
+            config['internals'].update({'sd_notify': True})
+
+    def _process_datadir_options(self, config: Dict[str, Any]) -> None:
+        """
+        Extract information for sys.argv and load directory configurations
+        --user-data, --datadir
+        """
+        # Check exchange parameter here - otherwise `datadir` might be wrong.
+        if 'exchange' in self.args and self.args['exchange']:
+            config['exchange']['name'] = self.args['exchange']
+            logger.info(f"Using exchange {config['exchange']['name']}")
+
+        if 'pair_whitelist' not in config['exchange']:
+            config['exchange']['pair_whitelist'] = []
+
+        if 'user_data_dir' in self.args and self.args['user_data_dir']:
+            config.update({'user_data_dir': self.args['user_data_dir']})
+        elif 'user_data_dir' not in config:
+            # Default to cwd/user_data (legacy option ...)
+            config.update({'user_data_dir': str(Path.cwd() / 'user_data')})
+
+        # reset to user_data_dir so this contains the absolute path.
+        config['user_data_dir'] = create_userdata_dir(config['user_data_dir'], create_dir=False)
+        logger.info('Using user-data directory: %s ...', config['user_data_dir'])
+
+        config.update({'datadir': create_datadir(config, self.args.get('datadir', None))})
+        logger.info('Using data directory: %s ...', config.get('datadir'))
+
+        if self.args.get('exportfilename'):
+            self._args_to_config(config, argname='exportfilename',
+                                 logstring='Storing backtest results to {} ...')
+            config['exportfilename'] = Path(config['exportfilename'])
+        else:
+            config['exportfilename'] = (config['user_data_dir']
+                                        / 'backtest_results')
+
+    def _process_optimize_options(self, config: Dict[str, Any]) -> None:
+
+        # This will override the strategy configuration
+        self._args_to_config(config, argname='timeframe',
+                             logstring='Parameter -i/--timeframe detected ... '
+                             'Using timeframe: {} ...')
+
+        self._args_to_config(config, argname='position_stacking',
+                             logstring='Parameter --enable-position-stacking detected ...')
+
         # Setting max_open_trades to infinite if -1
         if config.get('max_open_trades') == -1:
             config['max_open_trades'] = float('inf')
 
-        # Support for sd_notify
-        if 'sd_notify' in self.args and self.args.sd_notify:
-            config['internals'].update({'sd_notify': True})
-
-        # Check if the exchange set by the user is supported
-        check_exchange(config)
-
-    def _process_datadir_options(self, config: Dict[str, Any]) -> None:
-        """
-        Extract information for sys.argv and load datadir configuration:
-        the --datadir option
-        """
-        if 'datadir' in self.args and self.args.datadir:
-            config.update({'datadir': create_datadir(config, self.args.datadir)})
-        else:
-            config.update({'datadir': create_datadir(config, None)})
-        logger.info('Using data directory: %s ...', config.get('datadir'))
-
-    def _process_optimize_options(self, config: Dict[str, Any]) -> None:
-
-        # This will override the strategy configuration
-        self._args_to_config(config, argname='ticker_interval',
-                             logstring='Parameter -i/--ticker-interval detected ... '
-                             'Using ticker_interval: {} ...')
-
-        self._args_to_config(config, argname='live',
-                             logstring='Parameter -l/--live detected ...')
-
-        self._args_to_config(config, argname='position_stacking',
-                             logstring='Parameter --enable-position-stacking detected ...')
-
-        if 'use_max_market_positions' in self.args and not self.args.use_max_market_positions:
+        if 'use_max_market_positions' in self.args and not self.args["use_max_market_positions"]:
             config.update({'use_max_market_positions': False})
             logger.info('Parameter --disable-max-market-positions detected ...')
             logger.info('max_open_trades set to unlimited ...')
-        elif 'max_open_trades' in self.args and self.args.max_open_trades:
-            config.update({'max_open_trades': self.args.max_open_trades})
-            logger.info('Parameter --max_open_trades detected, '
+        elif 'max_open_trades' in self.args and self.args['max_open_trades']:
+            config.update({'max_open_trades': self.args['max_open_trades']})
+            logger.info('Parameter --max-open-trades detected, '
                         'overriding max_open_trades to: %s ...', config.get('max_open_trades'))
-        else:
+        elif config['runmode'] in NON_UTIL_MODES:
             logger.info('Using max_open_trades: %s ...', config.get('max_open_trades'))
 
         self._args_to_config(config, argname='stake_amount',
-                             logstring='Parameter --stake_amount detected, '
+                             logstring='Parameter --stake-amount detected, '
                              'overriding stake_amount to: {} ...')
 
+        self._args_to_config(config, argname='fee',
+                             logstring='Parameter --fee detected, '
+                             'setting fee to: {} ...')
+
         self._args_to_config(config, argname='timerange',
                              logstring='Parameter --timerange detected: {} ...')
 
         self._process_datadir_options(config)
 
-        self._args_to_config(config, argname='refresh_pairs',
-                             logstring='Parameter -r/--refresh-pairs-cached detected ...')
-
         self._args_to_config(config, argname='strategy_list',
-                             logstring='Using strategy list of {} Strategies', logfun=len)
+                             logstring='Using strategy list of {} strategies', logfun=len)
 
-        self._args_to_config(config, argname='ticker_interval',
-                             logstring='Overriding ticker interval with Command line argument')
+        self._args_to_config(config, argname='timeframe',
+                             logstring='Overriding timeframe with Command line argument')
 
         self._args_to_config(config, argname='export',
                              logstring='Parameter --export detected: {} ...')
 
-        self._args_to_config(config, argname='exportfilename',
-                             logstring='Storing backtest results to {} ...')
-
         # Edge section:
-        if 'stoploss_range' in self.args and self.args.stoploss_range:
-            txt_range = eval(self.args.stoploss_range)
+        if 'stoploss_range' in self.args and self.args["stoploss_range"]:
+            txt_range = eval(self.args["stoploss_range"])
             config['edge'].update({'stoploss_range_min': txt_range[0]})
             config['edge'].update({'stoploss_range_max': txt_range[1]})
             config['edge'].update({'stoploss_range_step': txt_range[2]})
-            logger.info('Parameter --stoplosses detected: %s ...', self.args.stoploss_range)
+            logger.info('Parameter --stoplosses detected: %s ...', self.args["stoploss_range"])
 
         # Hyperopt section
         self._args_to_config(config, argname='hyperopt',
-                             logstring='Using Hyperopt file {}')
+                             logstring='Using Hyperopt class name: {}')
+
+        self._args_to_config(config, argname='hyperopt_path',
+                             logstring='Using additional Hyperopt lookup path: {}')
+
+        self._args_to_config(config, argname='hyperoptexportfilename',
+                             logstring='Using hyperopt file: {}')
 
         self._args_to_config(config, argname='epochs',
                              logstring='Parameter --epochs detected ... '
@@ -250,6 +277,18 @@ class Configuration(object):
         self._args_to_config(config, argname='print_all',
                              logstring='Parameter --print-all detected ...')
 
+        if 'print_colorized' in self.args and not self.args["print_colorized"]:
+            logger.info('Parameter --no-color detected ...')
+            config.update({'print_colorized': False})
+        else:
+            config.update({'print_colorized': True})
+
+        self._args_to_config(config, argname='print_json',
+                             logstring='Parameter --print-json detected ...')
+
+        self._args_to_config(config, argname='export_csv',
+                             logstring='Parameter --export-csv detected: {}')
+
         self._args_to_config(config, argname='hyperopt_jobs',
                              logstring='Parameter -j/--job-workers detected: {}')
 
@@ -259,11 +298,53 @@ class Configuration(object):
         self._args_to_config(config, argname='hyperopt_min_trades',
                              logstring='Parameter --min-trades detected: {}')
 
-        self._args_to_config(config, argname='hyperopt_continue',
-                             logstring='Hyperopt continue: {}')
-
         self._args_to_config(config, argname='hyperopt_loss',
-                             logstring='Using loss function: {}')
+                             logstring='Using Hyperopt loss class name: {}')
+
+        self._args_to_config(config, argname='hyperopt_show_index',
+                             logstring='Parameter -n/--index detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_list_best',
+                             logstring='Parameter --best detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_list_profitable',
+                             logstring='Parameter --profitable detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_list_min_trades',
+                             logstring='Parameter --min-trades detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_list_max_trades',
+                             logstring='Parameter --max-trades detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_list_min_avg_time',
+                             logstring='Parameter --min-avg-time detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_list_max_avg_time',
+                             logstring='Parameter --max-avg-time detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_list_min_avg_profit',
+                             logstring='Parameter --min-avg-profit detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_list_max_avg_profit',
+                             logstring='Parameter --max-avg-profit detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_list_min_total_profit',
+                             logstring='Parameter --min-total-profit detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_list_max_total_profit',
+                             logstring='Parameter --max-total-profit detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_list_min_objective',
+                             logstring='Parameter --min-objective detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_list_max_objective',
+                             logstring='Parameter --max-objective detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_list_no_details',
+                             logstring='Parameter --no-details detected: {}')
+
+        self._args_to_config(config, argname='hyperopt_show_no_header',
+                             logstring='Parameter --no-header detected: {}')
 
     def _process_plot_options(self, config: Dict[str, Any]) -> None:
 
@@ -276,51 +357,52 @@ class Configuration(object):
         self._args_to_config(config, argname='indicators2',
                              logstring='Using indicators2: {}')
 
+        self._args_to_config(config, argname='trade_ids',
+                             logstring='Filtering on trade_ids: {}')
+
         self._args_to_config(config, argname='plot_limit',
                              logstring='Limiting plot to: {}')
+
         self._args_to_config(config, argname='trade_source',
                              logstring='Using trades from: {}')
 
+        self._args_to_config(config, argname='erase',
+                             logstring='Erase detected. Deleting existing data.')
+
+        self._args_to_config(config, argname='no_trades',
+                             logstring='Parameter --no-trades detected.')
+
+        self._args_to_config(config, argname='timeframes',
+                             logstring='timeframes --timeframes: {}')
+
+        self._args_to_config(config, argname='days',
+                             logstring='Detected --days: {}')
+
+        self._args_to_config(config, argname='download_trades',
+                             logstring='Detected --dl-trades: {}')
+
+        self._args_to_config(config, argname='dataformat_ohlcv',
+                             logstring='Using "{}" to store OHLCV data.')
+
+        self._args_to_config(config, argname='dataformat_trades',
+                             logstring='Using "{}" to store trades data.')
+
     def _process_runmode(self, config: Dict[str, Any]) -> None:
 
+        self._args_to_config(config, argname='dry_run',
+                             logstring='Parameter --dry-run detected, '
+                             'overriding dry_run to: {} ...')
+
         if not self.runmode:
             # Handle real mode, infer dry/live from config
             self.runmode = RunMode.DRY_RUN if config.get('dry_run', True) else RunMode.LIVE
-            logger.info("Runmode set to {self.runmode}.")
+            logger.info(f"Runmode set to {self.runmode.value}.")
 
         config.update({'runmode': self.runmode})
 
-    def _validate_config_consistency(self, conf: Dict[str, Any]) -> None:
-        """
-        Validate the configuration consistency
-        :param conf: Config in JSON format
-        :return: Returns None if everything is ok, otherwise throw an OperationalException
-        """
-        # validating trailing stoploss
-        self._validate_trailing_stoploss(conf)
-
-    def _validate_trailing_stoploss(self, conf: Dict[str, Any]) -> None:
-
-        # Skip if trailing stoploss is not activated
-        if not conf.get('trailing_stop', False):
-            return
-
-        tsl_positive = float(conf.get('trailing_stop_positive', 0))
-        tsl_offset = float(conf.get('trailing_stop_positive_offset', 0))
-        tsl_only_offset = conf.get('trailing_only_offset_is_reached', False)
-
-        if tsl_only_offset:
-            if tsl_positive == 0.0:
-                raise OperationalException(
-                    f'The config trailing_only_offset_is_reached needs '
-                    'trailing_stop_positive_offset to be more than 0 in your config.')
-        if tsl_positive > 0 and 0 < tsl_offset <= tsl_positive:
-            raise OperationalException(
-                f'The config trailing_stop_positive_offset needs '
-                'to be greater than trailing_stop_positive_offset in your config.')
-
     def _args_to_config(self, config: Dict[str, Any], argname: str,
-                        logstring: str, logfun: Optional[Callable] = None) -> None:
+                        logstring: str, logfun: Optional[Callable] = None,
+                        deprecated_msg: Optional[str] = None) -> None:
         """
         :param config: Configuration dictionary
         :param argname: Argumentname in self.args - will be copied to config dict.
@@ -330,10 +412,49 @@ class Configuration(object):
                         sample: logfun=len (prints the length of the found
                         configuration instead of the content)
         """
-        if argname in self.args and getattr(self.args, argname):
+        if (argname in self.args and self.args[argname] is not None
+           and self.args[argname] is not False):
 
-            config.update({argname: getattr(self.args, argname)})
+            config.update({argname: self.args[argname]})
             if logfun:
                 logger.info(logstring.format(logfun(config[argname])))
             else:
                 logger.info(logstring.format(config[argname]))
+            if deprecated_msg:
+                warnings.warn(f"DEPRECATED: {deprecated_msg}", DeprecationWarning)
+
+    def _resolve_pairs_list(self, config: Dict[str, Any]) -> None:
+        """
+        Helper for download script.
+        Takes first found:
+        * -p (pairs argument)
+        * --pairs-file
+        * whitelist from config
+        """
+
+        if "pairs" in config:
+            return
+
+        if "pairs_file" in self.args and self.args["pairs_file"]:
+            pairs_file = Path(self.args["pairs_file"])
+            logger.info(f'Reading pairs file "{pairs_file}".')
+            # Download pairs from the pairs file if no config is specified
+            # or if pairs file is specified explicitely
+            if not pairs_file.exists():
+                raise OperationalException(f'No pairs file found with path "{pairs_file}".')
+            with pairs_file.open('r') as f:
+                config['pairs'] = json_load(f)
+                config['pairs'].sort()
+            return
+
+        if 'config' in self.args and self.args['config']:
+            logger.info("Using pairlist from configuration.")
+            config['pairs'] = config.get('exchange', {}).get('pair_whitelist')
+        else:
+            # Fall back to /dl_path/pairs.json
+            pairs_file = config['datadir'] / 'pairs.json'
+            if pairs_file.exists():
+                with pairs_file.open('r') as f:
+                    config['pairs'] = json_load(f)
+                if 'pairs' in config:
+                    config['pairs'].sort()
diff --git a/freqtrade/configuration/create_datadir.py b/freqtrade/configuration/create_datadir.py
deleted file mode 100644
index acc3a29ca..000000000
--- a/freqtrade/configuration/create_datadir.py
+++ /dev/null
@@ -1,20 +0,0 @@
-import logging
-from typing import Any, Dict, Optional
-from pathlib import Path
-
-
-logger = logging.getLogger(__name__)
-
-
-def create_datadir(config: Dict[str, Any], datadir: Optional[str] = None) -> str:
-
-    folder = Path(datadir) if datadir else Path('user_data/data')
-    if not datadir:
-        # set datadir
-        exchange_name = config.get('exchange', {}).get('name').lower()
-        folder = folder.joinpath(exchange_name)
-
-    if not folder.is_dir():
-        folder.mkdir(parents=True)
-        logger.info(f'Created data directory: {datadir}')
-    return str(folder)
diff --git a/freqtrade/configuration/deprecated_settings.py b/freqtrade/configuration/deprecated_settings.py
new file mode 100644
index 000000000..03ed41ab8
--- /dev/null
+++ b/freqtrade/configuration/deprecated_settings.py
@@ -0,0 +1,80 @@
+"""
+Functions to handle deprecated settings
+"""
+
+import logging
+from typing import Any, Dict
+
+from freqtrade.exceptions import OperationalException
+
+
+logger = logging.getLogger(__name__)
+
+
+def check_conflicting_settings(config: Dict[str, Any],
+                               section1: str, name1: str,
+                               section2: str, name2: str) -> None:
+    section1_config = config.get(section1, {})
+    section2_config = config.get(section2, {})
+    if name1 in section1_config and name2 in section2_config:
+        raise OperationalException(
+            f"Conflicting settings `{section1}.{name1}` and `{section2}.{name2}` "
+            "(DEPRECATED) detected in the configuration file. "
+            "This deprecated setting will be removed in the next versions of Freqtrade. "
+            f"Please delete it from your configuration and use the `{section1}.{name1}` "
+            "setting instead."
+        )
+
+
+def process_deprecated_setting(config: Dict[str, Any],
+                               section1: str, name1: str,
+                               section2: str, name2: str) -> None:
+    section2_config = config.get(section2, {})
+
+    if name2 in section2_config:
+        logger.warning(
+            "DEPRECATED: "
+            f"The `{section2}.{name2}` setting is deprecated and "
+            "will be removed in the next versions of Freqtrade. "
+            f"Please use the `{section1}.{name1}` setting in your configuration instead."
+        )
+        section1_config = config.get(section1, {})
+        section1_config[name1] = section2_config[name2]
+
+
+def process_temporary_deprecated_settings(config: Dict[str, Any]) -> None:
+
+    check_conflicting_settings(config, 'ask_strategy', 'use_sell_signal',
+                               'experimental', 'use_sell_signal')
+    check_conflicting_settings(config, 'ask_strategy', 'sell_profit_only',
+                               'experimental', 'sell_profit_only')
+    check_conflicting_settings(config, 'ask_strategy', 'ignore_roi_if_buy_signal',
+                               'experimental', 'ignore_roi_if_buy_signal')
+
+    process_deprecated_setting(config, 'ask_strategy', 'use_sell_signal',
+                               'experimental', 'use_sell_signal')
+    process_deprecated_setting(config, 'ask_strategy', 'sell_profit_only',
+                               'experimental', 'sell_profit_only')
+    process_deprecated_setting(config, 'ask_strategy', 'ignore_roi_if_buy_signal',
+                               'experimental', 'ignore_roi_if_buy_signal')
+
+    if (config.get('edge', {}).get('enabled', False)
+       and 'capital_available_percentage' in config.get('edge', {})):
+        raise OperationalException(
+            "DEPRECATED: "
+            "Using 'edge.capital_available_percentage' has been deprecated in favor of "
+            "'tradable_balance_ratio'. Please migrate your configuration to "
+            "'tradable_balance_ratio' and remove 'capital_available_percentage' "
+            "from the edge configuration."
+        )
+    if 'ticker_interval' in config:
+        logger.warning(
+            "DEPRECATED: "
+            "Please use 'timeframe' instead of 'ticker_interval."
+        )
+        if 'timeframe' in config:
+            raise OperationalException(
+                "Both 'timeframe' and 'ticker_interval' detected."
+                "Please remove 'ticker_interval' from your configuration to continue operating."
+                )
+        config['timeframe'] = config['ticker_interval']
diff --git a/freqtrade/configuration/directory_operations.py b/freqtrade/configuration/directory_operations.py
new file mode 100644
index 000000000..51310f013
--- /dev/null
+++ b/freqtrade/configuration/directory_operations.py
@@ -0,0 +1,77 @@
+import logging
+import shutil
+from pathlib import Path
+from typing import Any, Dict, Optional
+
+from freqtrade.constants import USER_DATA_FILES
+from freqtrade.exceptions import OperationalException
+
+
+logger = logging.getLogger(__name__)
+
+
+def create_datadir(config: Dict[str, Any], datadir: Optional[str] = None) -> Path:
+
+    folder = Path(datadir) if datadir else Path(f"{config['user_data_dir']}/data")
+    if not datadir:
+        # set datadir
+        exchange_name = config.get('exchange', {}).get('name').lower()
+        folder = folder.joinpath(exchange_name)
+
+    if not folder.is_dir():
+        folder.mkdir(parents=True)
+        logger.info(f'Created data directory: {datadir}')
+    return folder
+
+
+def create_userdata_dir(directory: str, create_dir: bool = False) -> Path:
+    """
+    Create userdata directory structure.
+    if create_dir is True, then the parent-directory will be created if it does not exist.
+    Sub-directories will always be created if the parent directory exists.
+    Raises OperationalException if given a non-existing directory.
+    :param directory: Directory to check
+    :param create_dir: Create directory if it does not exist.
+    :return: Path object containing the directory
+    """
+    sub_dirs = ["backtest_results", "data", "hyperopts", "hyperopt_results", "logs",
+                "notebooks", "plot", "strategies", ]
+    folder = Path(directory)
+    if not folder.is_dir():
+        if create_dir:
+            folder.mkdir(parents=True)
+            logger.info(f'Created user-data directory: {folder}')
+        else:
+            raise OperationalException(
+                f"Directory `{folder}` does not exist. "
+                "Please use `freqtrade create-userdir` to create a user directory")
+
+    # Create required subdirectories
+    for f in sub_dirs:
+        subfolder = folder / f
+        if not subfolder.is_dir():
+            subfolder.mkdir(parents=False)
+    return folder
+
+
+def copy_sample_files(directory: Path, overwrite: bool = False) -> None:
+    """
+    Copy files from templates to User data directory.
+    :param directory: Directory to copy data to
+    :param overwrite: Overwrite existing sample files
+    """
+    if not directory.is_dir():
+        raise OperationalException(f"Directory `{directory}` does not exist.")
+    sourcedir = Path(__file__).parents[1] / "templates"
+    for source, target in USER_DATA_FILES.items():
+        targetdir = directory / target
+        if not targetdir.is_dir():
+            raise OperationalException(f"Directory `{targetdir}` does not exist.")
+        targetfile = targetdir / source
+        if targetfile.exists():
+            if not overwrite:
+                logger.warning(f"File `{targetfile}` exists already, not deploying sample file.")
+                continue
+            else:
+                logger.warning(f"File `{targetfile}` exists already, overwriting.")
+        shutil.copy(str(sourcedir / source), str(targetfile))
diff --git a/freqtrade/configuration/json_schema.py b/freqtrade/configuration/json_schema.py
deleted file mode 100644
index 4c6f4a4a0..000000000
--- a/freqtrade/configuration/json_schema.py
+++ /dev/null
@@ -1,53 +0,0 @@
-import logging
-from typing import Any, Dict
-
-from jsonschema import Draft4Validator, validators
-from jsonschema.exceptions import ValidationError, best_match
-
-from freqtrade import constants
-
-
-logger = logging.getLogger(__name__)
-
-
-def _extend_validator(validator_class):
-    """
-    Extended validator for the Freqtrade configuration JSON Schema.
-    Currently it only handles defaults for subschemas.
-    """
-    validate_properties = validator_class.VALIDATORS['properties']
-
-    def set_defaults(validator, properties, instance, schema):
-        for prop, subschema in properties.items():
-            if 'default' in subschema:
-                instance.setdefault(prop, subschema['default'])
-
-        for error in validate_properties(
-            validator, properties, instance, schema,
-        ):
-            yield error
-
-    return validators.extend(
-        validator_class, {'properties': set_defaults}
-    )
-
-
-FreqtradeValidator = _extend_validator(Draft4Validator)
-
-
-def validate_config_schema(conf: Dict[str, Any]) -> Dict[str, Any]:
-    """
-    Validate the configuration follow the Config Schema
-    :param conf: Config in JSON format
-    :return: Returns the config if valid, otherwise throw an exception
-    """
-    try:
-        FreqtradeValidator(constants.CONF_SCHEMA).validate(conf)
-        return conf
-    except ValidationError as e:
-        logger.critical(
-            f"Invalid configuration. See config.json.example. Reason: {e}"
-        )
-        raise ValidationError(
-            best_match(Draft4Validator(constants.CONF_SCHEMA).iter_errors(conf)).message
-        )
diff --git a/freqtrade/configuration/load_config.py b/freqtrade/configuration/load_config.py
new file mode 100644
index 000000000..726126034
--- /dev/null
+++ b/freqtrade/configuration/load_config.py
@@ -0,0 +1,63 @@
+"""
+This module contain functions to load the configuration file
+"""
+import logging
+import re
+import sys
+from pathlib import Path
+from typing import Any, Dict
+
+import rapidjson
+
+from freqtrade.exceptions import OperationalException
+
+
+logger = logging.getLogger(__name__)
+
+
+CONFIG_PARSE_MODE = rapidjson.PM_COMMENTS | rapidjson.PM_TRAILING_COMMAS
+
+
+def log_config_error_range(path: str, errmsg: str) -> str:
+    """
+    Parses configuration file and prints range around error
+    """
+    if path != '-':
+        offsetlist = re.findall(r'(?<=Parse\serror\sat\soffset\s)\d+', errmsg)
+        if offsetlist:
+            offset = int(offsetlist[0])
+            text = Path(path).read_text()
+            # Fetch an offset of 80 characters around the error line
+            subtext = text[offset-min(80, offset):offset+80]
+            segments = subtext.split('\n')
+            if len(segments) > 3:
+                # Remove first and last lines, to avoid odd truncations
+                return '\n'.join(segments[1:-1])
+            else:
+                return subtext
+    return ''
+
+
+def load_config_file(path: str) -> Dict[str, Any]:
+    """
+    Loads a config file from the given path
+    :param path: path as str
+    :return: configuration as dictionary
+    """
+    try:
+        # Read config from stdin if requested in the options
+        with open(path) if path != '-' else sys.stdin as file:
+            config = rapidjson.load(file, parse_mode=CONFIG_PARSE_MODE)
+    except FileNotFoundError:
+        raise OperationalException(
+            f'Config file "{path}" not found!'
+            ' Please create a config file or check whether it exists.')
+    except rapidjson.JSONDecodeError as e:
+        err_range = log_config_error_range(path, str(e))
+        raise OperationalException(
+            f'{e}\n'
+            f'Please verify the following segment of your configuration:\n{err_range}'
+            if err_range else 'Please verify your configuration file for syntax errors.'
+        )
+
+    return config
diff --git a/freqtrade/configuration/timerange.py b/freqtrade/configuration/timerange.py
new file mode 100644
index 000000000..32bbd02a0
--- /dev/null
+++ b/freqtrade/configuration/timerange.py
@@ -0,0 +1,107 @@
+"""
+This module contains the argument manager class
+"""
+import logging
+import re
+from typing import Optional
+
+import arrow
+
+
+logger = logging.getLogger(__name__)
+
+
+class TimeRange:
+    """
+    object defining timerange inputs.
+    [start/stop]type defines if [start/stop]ts shall be used.
+    if *type is None, don't use corresponding startvalue.
+    """
+
+    def __init__(self, starttype: Optional[str] = None, stoptype: Optional[str] = None,
+                 startts: int = 0, stopts: int = 0):
+
+        self.starttype: Optional[str] = starttype
+        self.stoptype: Optional[str] = stoptype
+        self.startts: int = startts
+        self.stopts: int = stopts
+
+    def __eq__(self, other):
+        """Override the default Equals behavior"""
+        return (self.starttype == other.starttype and self.stoptype == other.stoptype
+                and self.startts == other.startts and self.stopts == other.stopts)
+
+    def subtract_start(self, seconds: int) -> None:
+        """
+        Subtracts <seconds> from startts if startts is set.
+        :param seconds: Seconds to subtract from starttime
+        :return: None (Modifies the object in place)
+        """
+        if self.startts:
+            self.startts = self.startts - seconds
+
+    def adjust_start_if_necessary(self, timeframe_secs: int, startup_candles: int,
+                                  min_date: arrow.Arrow) -> None:
+        """
+        Adjust startts by <startup_candles> candles.
+        Applies only if no startup-candles have been available.
+        :param timeframe_secs: Timeframe in seconds e.g. `timeframe_to_seconds('5m')`
+        :param startup_candles: Number of candles to move start-date forward
+        :param min_date: Minimum data date loaded. Key kriterium to decide if start-time
+                         has to be moved
+        :return: None (Modifies the object in place)
+        """
+        if (not self.starttype or (startup_candles
+                                   and min_date.int_timestamp >= self.startts)):
+            # If no startts was defined, or backtest-data starts at the defined backtest-date
+            logger.warning("Moving start-date by %s candles to account for startup time.",
+                           startup_candles)
+            self.startts = (min_date.int_timestamp + timeframe_secs * startup_candles)
+            self.starttype = 'date'
+
+    @staticmethod
+    def parse_timerange(text: Optional[str]) -> 'TimeRange':
+        """
+        Parse the value of the argument --timerange to determine what is the range desired
+        :param text: value from --timerange
+        :return: Start and End range period
+        """
+        if text is None:
+            return TimeRange(None, None, 0, 0)
+        syntax = [(r'^-(\d{8})$', (None, 'date')),
+                  (r'^(\d{8})-$', ('date', None)),
+                  (r'^(\d{8})-(\d{8})$', ('date', 'date')),
+                  (r'^-(\d{10})$', (None, 'date')),
+                  (r'^(\d{10})-$', ('date', None)),
+                  (r'^(\d{10})-(\d{10})$', ('date', 'date')),
+                  (r'^-(\d{13})$', (None, 'date')),
+                  (r'^(\d{13})-$', ('date', None)),
+                  (r'^(\d{13})-(\d{13})$', ('date', 'date')),
+                  ]
+        for rex, stype in syntax:
+            # Apply the regular expression to text
+            match = re.match(rex, text)
+            if match:  # Regex has matched
+                rvals = match.groups()
+                index = 0
+                start: int = 0
+                stop: int = 0
+                if stype[0]:
+                    starts = rvals[index]
+                    if stype[0] == 'date' and len(starts) == 8:
+                        start = arrow.get(starts, 'YYYYMMDD').int_timestamp
+                    elif len(starts) == 13:
+                        start = int(starts) // 1000
+                    else:
+                        start = int(starts)
+                    index += 1
+                if stype[1]:
+                    stops = rvals[index]
+                    if stype[1] == 'date' and len(stops) == 8:
+                        stop = arrow.get(stops, 'YYYYMMDD').int_timestamp
+                    elif len(stops) == 13:
+                        stop = int(stops) // 1000
+                    else:
+                        stop = int(stops)
+                return TimeRange(stype[0], stype[1], start, stop)
+        raise Exception('Incorrect syntax for timerange "%s"' % text)
diff --git a/freqtrade/constants.py b/freqtrade/constants.py
index 9b73adcfe..3271dda39 100644
--- a/freqtrade/constants.py
+++ b/freqtrade/constants.py
@@ -3,57 +3,103 @@
 """
 bot constants
 """
+from typing import List, Tuple
+
+
 DEFAULT_CONFIG = 'config.json'
 DEFAULT_EXCHANGE = 'bittrex'
-DYNAMIC_WHITELIST = 20  # pairs
 PROCESS_THROTTLE_SECS = 5  # sec
-DEFAULT_TICKER_INTERVAL = 5  # min
 HYPEROPT_EPOCH = 100  # epochs
 RETRY_TIMEOUT = 30  # sec
-DEFAULT_STRATEGY = 'DefaultStrategy'
-DEFAULT_HYPEROPT = 'DefaultHyperOpts'
-DEFAULT_HYPEROPT_LOSS = 'DefaultHyperOptLoss'
 DEFAULT_DB_PROD_URL = 'sqlite:///tradesv3.sqlite'
-DEFAULT_DB_DRYRUN_URL = 'sqlite://'
+DEFAULT_DB_DRYRUN_URL = 'sqlite:///tradesv3.dryrun.sqlite'
 UNLIMITED_STAKE_AMOUNT = 'unlimited'
 DEFAULT_AMOUNT_RESERVE_PERCENT = 0.05
 REQUIRED_ORDERTIF = ['buy', 'sell']
 REQUIRED_ORDERTYPES = ['buy', 'sell', 'stoploss', 'stoploss_on_exchange']
+ORDERBOOK_SIDES = ['ask', 'bid']
 ORDERTYPE_POSSIBILITIES = ['limit', 'market']
 ORDERTIF_POSSIBILITIES = ['gtc', 'fok', 'ioc']
-AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList']
-DRY_RUN_WALLET = 999.9
-DEFAULT_DOWNLOAD_TICKER_INTERVALS = '1m 5m'
+HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss',
+                         'SharpeHyperOptLoss', 'SharpeHyperOptLossDaily',
+                         'SortinoHyperOptLoss', 'SortinoHyperOptLossDaily']
+AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
+                       'AgeFilter', 'PrecisionFilter', 'PriceFilter',
+                       'ShuffleFilter', 'SpreadFilter']
+AVAILABLE_DATAHANDLERS = ['json', 'jsongz', 'hdf5']
+DRY_RUN_WALLET = 1000
+DATETIME_PRINT_FORMAT = '%Y-%m-%d %H:%M:%S'
+MATH_CLOSE_PREC = 1e-14  # Precision used for float comparisons
+DEFAULT_DATAFRAME_COLUMNS = ['date', 'open', 'high', 'low', 'close', 'volume']
+# Don't modify sequence of DEFAULT_TRADES_COLUMNS
+# it has wide consequences for stored trades files
+DEFAULT_TRADES_COLUMNS = ['timestamp', 'id', 'type', 'side', 'price', 'amount', 'cost']
 
-TICKER_INTERVALS = [
-    '1m', '3m', '5m', '15m', '30m',
-    '1h', '2h', '4h', '6h', '8h', '12h',
-    '1d', '3d', '1w',
-]
+LAST_BT_RESULT_FN = '.last_result.json'
+
+USERPATH_HYPEROPTS = 'hyperopts'
+USERPATH_STRATEGIES = 'strategies'
+USERPATH_NOTEBOOKS = 'notebooks'
+
+TELEGRAM_SETTING_OPTIONS = ['on', 'off', 'silent']
+
+# Soure files with destination directories within user-directory
+USER_DATA_FILES = {
+    'sample_strategy.py': USERPATH_STRATEGIES,
+    'sample_hyperopt_advanced.py': USERPATH_HYPEROPTS,
+    'sample_hyperopt_loss.py': USERPATH_HYPEROPTS,
+    'sample_hyperopt.py': USERPATH_HYPEROPTS,
+    'strategy_analysis_example.ipynb': USERPATH_NOTEBOOKS,
+}
 
 SUPPORTED_FIAT = [
     "AUD", "BRL", "CAD", "CHF", "CLP", "CNY", "CZK", "DKK",
     "EUR", "GBP", "HKD", "HUF", "IDR", "ILS", "INR", "JPY",
     "KRW", "MXN", "MYR", "NOK", "NZD", "PHP", "PKR", "PLN",
     "RUB", "SEK", "SGD", "THB", "TRY", "TWD", "ZAR", "USD",
-    "BTC", "XBT", "ETH", "XRP", "LTC", "BCH", "USDT"
+    "BTC", "ETH", "XRP", "LTC", "BCH"
 ]
 
+MINIMAL_CONFIG = {
+    'stake_currency': '',
+    'dry_run': True,
+    'exchange': {
+        'name': '',
+        'key': '',
+        'secret': '',
+        'pair_whitelist': [],
+        'ccxt_async_config': {
+            'enableRateLimit': True,
+        }
+    }
+}
+
 # Required json-schema for user specified config
 CONF_SCHEMA = {
     'type': 'object',
     'properties': {
-        'max_open_trades': {'type': 'integer', 'minimum': -1},
-        'ticker_interval': {'type': 'string', 'enum': TICKER_INTERVALS},
-        'stake_currency': {'type': 'string', 'enum': ['BTC', 'XBT', 'ETH', 'USDT', 'EUR', 'USD']},
+        'max_open_trades': {'type': ['integer', 'number'], 'minimum': -1},
+        'timeframe': {'type': 'string'},
+        'stake_currency': {'type': 'string'},
         'stake_amount': {
-            "type": ["number", "string"],
-            "minimum": 0.0005,
-            "pattern": UNLIMITED_STAKE_AMOUNT
+            'type': ['number', 'string'],
+            'minimum': 0.0001,
+            'pattern': UNLIMITED_STAKE_AMOUNT
+        },
+        'tradable_balance_ratio': {
+            'type': 'number',
+            'minimum': 0.1,
+            'maximum': 1,
+            'default': 0.99
+        },
+        'amend_last_stake_amount': {'type': 'boolean', 'default': False},
+        'last_stake_amount_min_ratio': {
+            'type': 'number', 'minimum': 0.0, 'maximum': 1.0, 'default': 0.5
         },
         'fiat_display_currency': {'type': 'string', 'enum': SUPPORTED_FIAT},
         'dry_run': {'type': 'boolean'},
-        'dry_run_wallet': {'type': 'number'},
+        'dry_run_wallet': {'type': 'number', 'default': DRY_RUN_WALLET},
+        'cancel_open_orders_on_exit': {'type': 'boolean', 'default': False},
         'process_only_new_candles': {'type': 'boolean'},
         'minimal_roi': {
             'type': 'object',
@@ -71,8 +117,8 @@ CONF_SCHEMA = {
         'unfilledtimeout': {
             'type': 'object',
             'properties': {
-                'buy': {'type': 'number', 'minimum': 3},
-                'sell': {'type': 'number', 'minimum': 10}
+                'buy': {'type': 'number', 'minimum': 1},
+                'sell': {'type': 'number', 'minimum': 1}
             }
         },
         'bid_strategy': {
@@ -83,15 +129,16 @@ CONF_SCHEMA = {
                     'minimum': 0,
                     'maximum': 1,
                     'exclusiveMaximum': False,
-                    'use_order_book': {'type': 'boolean'},
-                    'order_book_top': {'type': 'number', 'maximum': 20, 'minimum': 1},
-                    'check_depth_of_market': {
-                        'type': 'object',
-                        'properties': {
-                            'enabled': {'type': 'boolean'},
-                            'bids_to_ask_delta': {'type': 'number', 'minimum': 0},
-                        }
-                    },
+                },
+                'price_side': {'type': 'string', 'enum': ORDERBOOK_SIDES, 'default': 'bid'},
+                'use_order_book': {'type': 'boolean'},
+                'order_book_top': {'type': 'integer', 'maximum': 20, 'minimum': 1},
+                'check_depth_of_market': {
+                    'type': 'object',
+                    'properties': {
+                        'enabled': {'type': 'boolean'},
+                        'bids_to_ask_delta': {'type': 'number', 'minimum': 0},
+                    }
                 },
             },
             'required': ['ask_last_balance']
@@ -99,9 +146,13 @@ CONF_SCHEMA = {
         'ask_strategy': {
             'type': 'object',
             'properties': {
+                'price_side': {'type': 'string', 'enum': ORDERBOOK_SIDES, 'default': 'ask'},
                 'use_order_book': {'type': 'boolean'},
-                'order_book_min': {'type': 'number', 'minimum': 1},
-                'order_book_max': {'type': 'number', 'minimum': 1, 'maximum': 50}
+                'order_book_min': {'type': 'integer', 'minimum': 1},
+                'order_book_max': {'type': 'integer', 'minimum': 1, 'maximum': 50},
+                'use_sell_signal': {'type': 'boolean'},
+                'sell_profit_only': {'type': 'boolean'},
+                'ignore_roi_if_buy_signal': {'type': 'boolean'}
             }
         },
         'order_types': {
@@ -109,9 +160,12 @@ CONF_SCHEMA = {
             'properties': {
                 'buy': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
                 'sell': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
+                'emergencysell': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
                 'stoploss': {'type': 'string', 'enum': ORDERTYPE_POSSIBILITIES},
                 'stoploss_on_exchange': {'type': 'boolean'},
-                'stoploss_on_exchange_interval': {'type': 'number'}
+                'stoploss_on_exchange_interval': {'type': 'number'},
+                'stoploss_on_exchange_limit_ratio': {'type': 'number', 'minimum': 0.0,
+                                                     'maximum': 1.0}
             },
             'required': ['buy', 'sell', 'stoploss', 'stoploss_on_exchange']
         },
@@ -130,16 +184,20 @@ CONF_SCHEMA = {
             'properties': {
                 'use_sell_signal': {'type': 'boolean'},
                 'sell_profit_only': {'type': 'boolean'},
-                'ignore_roi_if_buy_signal_true': {'type': 'boolean'}
+                'ignore_roi_if_buy_signal': {'type': 'boolean'},
+                'block_bad_exchanges': {'type': 'boolean'}
             }
         },
-        'pairlist': {
-            'type': 'object',
-            'properties': {
-                'method': {'type': 'string', 'enum': AVAILABLE_PAIRLISTS},
-                'config': {'type': 'object'}
-            },
-            'required': ['method']
+        'pairlists': {
+            'type': 'array',
+            'items': {
+                'type': 'object',
+                'properties': {
+                    'method': {'type': 'string', 'enum': AVAILABLE_PAIRLISTS},
+                    'config': {'type': 'object'}
+                },
+                'required': ['method'],
+            }
         },
         'telegram': {
             'type': 'object',
@@ -147,6 +205,18 @@ CONF_SCHEMA = {
                 'enabled': {'type': 'boolean'},
                 'token': {'type': 'string'},
                 'chat_id': {'type': 'string'},
+                'notification_settings': {
+                    'type': 'object',
+                    'properties': {
+                        'status': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
+                        'warning': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
+                        'startup': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
+                        'buy': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
+                        'sell': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
+                        'buy_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
+                        'sell_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS}
+                    }
+                }
             },
             'required': ['enabled', 'token', 'chat_id']
         },
@@ -155,7 +225,9 @@ CONF_SCHEMA = {
             'properties': {
                 'enabled': {'type': 'boolean'},
                 'webhookbuy': {'type': 'object'},
+                'webhookbuycancel': {'type': 'object'},
                 'webhooksell': {'type': 'object'},
+                'webhooksellcancel': {'type': 'object'},
                 'webhookstatus': {'type': 'object'},
             },
         },
@@ -166,24 +238,39 @@ CONF_SCHEMA = {
                 'listen_ip_address': {'format': 'ipv4'},
                 'listen_port': {
                     'type': 'integer',
-                    "minimum": 1024,
-                    "maximum": 65535
+                    'minimum': 1024,
+                    'maximum': 65535
                 },
                 'username': {'type': 'string'},
                 'password': {'type': 'string'},
+                'jwt_secret_key': {'type': 'string'},
+                'CORS_origins': {'type': 'array', 'items': {'type': 'string'}},
+                'verbosity': {'type': 'string', 'enum': ['error', 'info']},
             },
             'required': ['enabled', 'listen_ip_address', 'listen_port', 'username', 'password']
         },
         'db_url': {'type': 'string'},
         'initial_state': {'type': 'string', 'enum': ['running', 'stopped']},
         'forcebuy_enable': {'type': 'boolean'},
+        'disable_dataframe_checks': {'type': 'boolean'},
         'internals': {
             'type': 'object',
+            'default': {},
             'properties': {
-                'process_throttle_secs': {'type': 'number'},
+                'process_throttle_secs': {'type': 'integer'},
                 'interval': {'type': 'integer'},
                 'sd_notify': {'type': 'boolean'},
             }
+        },
+        'dataformat_ohlcv': {
+            'type': 'string',
+                    'enum': AVAILABLE_DATAHANDLERS,
+                    'default': 'json'
+        },
+        'dataformat_trades': {
+            'type': 'string',
+                    'enum': AVAILABLE_DATAHANDLERS,
+                    'default': 'jsongz'
         }
     },
     'definitions': {
@@ -200,7 +287,6 @@ CONF_SCHEMA = {
                     'type': 'array',
                     'items': {
                         'type': 'string',
-                        'pattern': '^[0-9A-Z]+/[0-9A-Z]+$'
                     },
                     'uniqueItems': True
                 },
@@ -208,7 +294,6 @@ CONF_SCHEMA = {
                     'type': 'array',
                     'items': {
                         'type': 'string',
-                        'pattern': '^[0-9A-Z]+/[0-9A-Z]+$'
                     },
                     'uniqueItems': True
                 },
@@ -217,37 +302,69 @@ CONF_SCHEMA = {
                 'ccxt_config': {'type': 'object'},
                 'ccxt_async_config': {'type': 'object'}
             },
-            'required': ['name', 'pair_whitelist']
+            'required': ['name']
         },
         'edge': {
             'type': 'object',
             'properties': {
-                "enabled": {'type': 'boolean'},
-                "process_throttle_secs": {'type': 'integer', 'minimum': 600},
-                "calculate_since_number_of_days": {'type': 'integer'},
-                "allowed_risk": {'type': 'number'},
-                "capital_available_percentage": {'type': 'number'},
-                "stoploss_range_min": {'type': 'number'},
-                "stoploss_range_max": {'type': 'number'},
-                "stoploss_range_step": {'type': 'number'},
-                "minimum_winrate": {'type': 'number'},
-                "minimum_expectancy": {'type': 'number'},
-                "min_trade_number": {'type': 'number'},
-                "max_trade_duration_minute": {'type': 'integer'},
-                "remove_pumps": {'type': 'boolean'}
+                'enabled': {'type': 'boolean'},
+                'process_throttle_secs': {'type': 'integer', 'minimum': 600},
+                'calculate_since_number_of_days': {'type': 'integer'},
+                'allowed_risk': {'type': 'number'},
+                'stoploss_range_min': {'type': 'number'},
+                'stoploss_range_max': {'type': 'number'},
+                'stoploss_range_step': {'type': 'number'},
+                'minimum_winrate': {'type': 'number'},
+                'minimum_expectancy': {'type': 'number'},
+                'min_trade_number': {'type': 'number'},
+                'max_trade_duration_minute': {'type': 'integer'},
+                'remove_pumps': {'type': 'boolean'}
             },
-            'required': ['process_throttle_secs', 'allowed_risk', 'capital_available_percentage']
+            'required': ['process_throttle_secs', 'allowed_risk']
         }
     },
-    'anyOf': [
-        {'required': ['exchange']}
-    ],
-    'required': [
-        'max_open_trades',
-        'stake_currency',
-        'stake_amount',
-        'dry_run',
-        'bid_strategy',
-        'telegram'
-    ]
 }
+
+SCHEMA_TRADE_REQUIRED = [
+    'exchange',
+    'timeframe',
+    'max_open_trades',
+    'stake_currency',
+    'stake_amount',
+    'tradable_balance_ratio',
+    'last_stake_amount_min_ratio',
+    'dry_run',
+    'dry_run_wallet',
+    'ask_strategy',
+    'bid_strategy',
+    'unfilledtimeout',
+    'stoploss',
+    'minimal_roi',
+    'internals',
+    'dataformat_ohlcv',
+    'dataformat_trades',
+]
+
+SCHEMA_MINIMAL_REQUIRED = [
+    'exchange',
+    'dry_run',
+    'dataformat_ohlcv',
+    'dataformat_trades',
+]
+
+CANCEL_REASON = {
+    "TIMEOUT": "cancelled due to timeout",
+    "PARTIALLY_FILLED_KEEP_OPEN": "partially filled - keeping order open",
+    "PARTIALLY_FILLED": "partially filled",
+    "FULLY_CANCELLED": "fully cancelled",
+    "ALL_CANCELLED": "cancelled (all unfilled and partially filled open orders cancelled)",
+    "CANCELLED_ON_EXCHANGE": "cancelled on exchange",
+    "FORCE_SELL": "forcesold",
+}
+
+# List of pairs with their timeframes
+PairWithTimeframe = Tuple[str, str]
+ListPairsWithTimeframes = List[PairWithTimeframe]
+
+# Type for trades list
+TradeList = List[List]
diff --git a/freqtrade/data/__init__.py b/freqtrade/data/__init__.py
index 0a31d095c..0e7eea0d0 100644
--- a/freqtrade/data/__init__.py
+++ b/freqtrade/data/__init__.py
@@ -2,7 +2,7 @@
 Module to handle data operations for freqtrade
 """
 
-# limit what's imported when using `from freqtrad.data import *``
+# limit what's imported when using `from freqtrade.data import *`
 __all__ = [
     'converter'
 ]
diff --git a/freqtrade/data/btanalysis.py b/freqtrade/data/btanalysis.py
index dcd544d00..513fba9e7 100644
--- a/freqtrade/data/btanalysis.py
+++ b/freqtrade/data/btanalysis.py
@@ -2,154 +2,381 @@
 Helpers when analyzing backtest data
 """
 import logging
+from datetime import timezone
 from pathlib import Path
-from typing import Dict
+from typing import Any, Dict, Optional, Tuple, Union
 
 import numpy as np
 import pandas as pd
-import pytz
 
-from freqtrade import persistence
+from freqtrade.constants import LAST_BT_RESULT_FN
 from freqtrade.misc import json_load
-from freqtrade.persistence import Trade
+from freqtrade.persistence import Trade, init_db
+
 
 logger = logging.getLogger(__name__)
 
 # must align with columns in backtest.py
-BT_DATA_COLUMNS = ["pair", "profitperc", "open_time", "close_time", "index", "duration",
+BT_DATA_COLUMNS = ["pair", "profit_percent", "open_date", "close_date", "index", "trade_duration",
                    "open_rate", "close_rate", "open_at_end", "sell_reason"]
 
 
-def load_backtest_data(filename) -> pd.DataFrame:
+def get_latest_optimize_filename(directory: Union[Path, str], variant: str) -> str:
     """
-    Load backtest data file.
-    :param filename: pathlib.Path object, or string pointing to the file.
-    :return: a dataframe with the analysis results
+    Get latest backtest export based on '.last_result.json'.
+    :param directory: Directory to search for last result
+    :param variant: 'backtest' or 'hyperopt' - the method to return
+    :return: string containing the filename of the latest backtest result
+    :raises: ValueError in the following cases:
+        * Directory does not exist
+        * `directory/.last_result.json` does not exist
+        * `directory/.last_result.json` has the wrong content
     """
-    if isinstance(filename, str):
-        filename = Path(filename)
+    if isinstance(directory, str):
+        directory = Path(directory)
+    if not directory.is_dir():
+        raise ValueError(f"Directory '{directory}' does not exist.")
+    filename = directory / LAST_BT_RESULT_FN
 
     if not filename.is_file():
-        raise ValueError("File {filename} does not exist.")
+        raise ValueError(
+            f"Directory '{directory}' does not seem to contain backtest statistics yet.")
 
     with filename.open() as file:
         data = json_load(file)
 
-    df = pd.DataFrame(data, columns=BT_DATA_COLUMNS)
+    if f'latest_{variant}' not in data:
+        raise ValueError(f"Invalid '{LAST_BT_RESULT_FN}' format.")
 
-    df['open_time'] = pd.to_datetime(df['open_time'],
-                                     unit='s',
-                                     utc=True,
-                                     infer_datetime_format=True
-                                     )
-    df['close_time'] = pd.to_datetime(df['close_time'],
-                                      unit='s',
-                                      utc=True,
-                                      infer_datetime_format=True
-                                      )
-    df['profitabs'] = df['close_rate'] - df['open_rate']
-    df = df.sort_values("open_time").reset_index(drop=True)
+    return data[f'latest_{variant}']
+
+
+def get_latest_backtest_filename(directory: Union[Path, str]) -> str:
+    """
+    Get latest backtest export based on '.last_result.json'.
+    :param directory: Directory to search for last result
+    :return: string containing the filename of the latest backtest result
+    :raises: ValueError in the following cases:
+        * Directory does not exist
+        * `directory/.last_result.json` does not exist
+        * `directory/.last_result.json` has the wrong content
+    """
+    return get_latest_optimize_filename(directory, 'backtest')
+
+
+def get_latest_hyperopt_filename(directory: Union[Path, str]) -> str:
+    """
+    Get latest hyperopt export based on '.last_result.json'.
+    :param directory: Directory to search for last result
+    :return: string containing the filename of the latest hyperopt result
+    :raises: ValueError in the following cases:
+        * Directory does not exist
+        * `directory/.last_result.json` does not exist
+        * `directory/.last_result.json` has the wrong content
+    """
+    try:
+        return get_latest_optimize_filename(directory, 'hyperopt')
+    except ValueError:
+        # Return default (legacy) pickle filename
+        return 'hyperopt_results.pickle'
+
+
+def get_latest_hyperopt_file(directory: Union[Path, str], predef_filename: str = None) -> Path:
+    """
+    Get latest hyperopt export based on '.last_result.json'.
+    :param directory: Directory to search for last result
+    :return: string containing the filename of the latest hyperopt result
+    :raises: ValueError in the following cases:
+        * Directory does not exist
+        * `directory/.last_result.json` does not exist
+        * `directory/.last_result.json` has the wrong content
+    """
+    if isinstance(directory, str):
+        directory = Path(directory)
+    if predef_filename:
+        return directory / predef_filename
+    return directory / get_latest_hyperopt_filename(directory)
+
+
+def load_backtest_stats(filename: Union[Path, str]) -> Dict[str, Any]:
+    """
+    Load backtest statistics file.
+    :param filename: pathlib.Path object, or string pointing to the file.
+    :return: a dictionary containing the resulting file.
+    """
+    if isinstance(filename, str):
+        filename = Path(filename)
+    if filename.is_dir():
+        filename = filename / get_latest_backtest_filename(filename)
+    if not filename.is_file():
+        raise ValueError(f"File {filename} does not exist.")
+    logger.info(f"Loading backtest result from {filename}")
+    with filename.open() as file:
+        data = json_load(file)
+
+    return data
+
+
+def load_backtest_data(filename: Union[Path, str], strategy: Optional[str] = None) -> pd.DataFrame:
+    """
+    Load backtest data file.
+    :param filename: pathlib.Path object, or string pointing to a file or directory
+    :param strategy: Strategy to load - mainly relevant for multi-strategy backtests
+                     Can also serve as protection to load the correct result.
+    :return: a dataframe with the analysis results
+    :raise: ValueError if loading goes wrong.
+    """
+    data = load_backtest_stats(filename)
+    if not isinstance(data, list):
+        # new, nested format
+        if 'strategy' not in data:
+            raise ValueError("Unknown dataformat.")
+
+        if not strategy:
+            if len(data['strategy']) == 1:
+                strategy = list(data['strategy'].keys())[0]
+            else:
+                raise ValueError("Detected backtest result with more than one strategy. "
+                                 "Please specify a strategy.")
+
+        if strategy not in data['strategy']:
+            raise ValueError(f"Strategy {strategy} not available in the backtest result.")
+
+        data = data['strategy'][strategy]['trades']
+        df = pd.DataFrame(data)
+        df['open_date'] = pd.to_datetime(df['open_date'],
+                                         utc=True,
+                                         infer_datetime_format=True
+                                         )
+        df['close_date'] = pd.to_datetime(df['close_date'],
+                                          utc=True,
+                                          infer_datetime_format=True
+                                          )
+    else:
+        # old format - only with lists.
+        df = pd.DataFrame(data, columns=BT_DATA_COLUMNS)
+
+        df['open_date'] = pd.to_datetime(df['open_date'],
+                                         unit='s',
+                                         utc=True,
+                                         infer_datetime_format=True
+                                         )
+        df['close_date'] = pd.to_datetime(df['close_date'],
+                                          unit='s',
+                                          utc=True,
+                                          infer_datetime_format=True
+                                          )
+        df['profit_abs'] = df['close_rate'] - df['open_rate']
+    df = df.sort_values("open_date").reset_index(drop=True)
     return df
 
 
-def evaluate_result_multi(results: pd.DataFrame, freq: str, max_open_trades: int) -> pd.DataFrame:
+def analyze_trade_parallelism(results: pd.DataFrame, timeframe: str) -> pd.DataFrame:
     """
     Find overlapping trades by expanding each trade once per period it was open
-    and then counting overlaps
+    and then counting overlaps.
     :param results: Results Dataframe - can be loaded
-    :param freq: Frequency used for the backtest
-    :param max_open_trades: parameter max_open_trades used during backtest run
-    :return: dataframe with open-counts per time-period in freq
+    :param timeframe: Timeframe used for backtest
+    :return: dataframe with open-counts per time-period in timeframe
     """
-    dates = [pd.Series(pd.date_range(row[1].open_time, row[1].close_time, freq=freq))
-             for row in results[['open_time', 'close_time']].iterrows()]
+    from freqtrade.exchange import timeframe_to_minutes
+    timeframe_min = timeframe_to_minutes(timeframe)
+    dates = [pd.Series(pd.date_range(row[1]['open_date'], row[1]['close_date'],
+                                     freq=f"{timeframe_min}min"))
+             for row in results[['open_date', 'close_date']].iterrows()]
     deltas = [len(x) for x in dates]
     dates = pd.Series(pd.concat(dates).values, name='date')
     df2 = pd.DataFrame(np.repeat(results.values, deltas, axis=0), columns=results.columns)
 
-    df2 = df2.astype(dtype={"open_time": "datetime64", "close_time": "datetime64"})
     df2 = pd.concat([dates, df2], axis=1)
     df2 = df2.set_index('date')
-    df_final = df2.resample(freq)[['pair']].count()
-    return df_final[df_final['pair'] > max_open_trades]
+    df_final = df2.resample(f"{timeframe_min}min")[['pair']].count()
+    df_final = df_final.rename({'pair': 'open_trades'}, axis=1)
+    return df_final
 
 
-def load_trades_from_db(db_url: str) -> pd.DataFrame:
+def evaluate_result_multi(results: pd.DataFrame, timeframe: str,
+                          max_open_trades: int) -> pd.DataFrame:
+    """
+    Find overlapping trades by expanding each trade once per period it was open
+    and then counting overlaps
+    :param results: Results Dataframe - can be loaded
+    :param timeframe: Frequency used for the backtest
+    :param max_open_trades: parameter max_open_trades used during backtest run
+    :return: dataframe with open-counts per time-period in freq
+    """
+    df_final = analyze_trade_parallelism(results, timeframe)
+    return df_final[df_final['open_trades'] > max_open_trades]
+
+
+def load_trades_from_db(db_url: str, strategy: Optional[str] = None) -> pd.DataFrame:
     """
     Load trades from a DB (using dburl)
     :param db_url: Sqlite url (default format sqlite:///tradesv3.dry-run.sqlite)
+    :param strategy: Strategy to load - mainly relevant for multi-strategy backtests
+                     Can also serve as protection to load the correct result.
     :return: Dataframe containing Trades
     """
-    trades: pd.DataFrame = pd.DataFrame([], columns=BT_DATA_COLUMNS)
-    persistence.init(db_url, clean_open_orders=False)
-    columns = ["pair", "profit", "open_time", "close_time",
-               "open_rate", "close_rate", "duration", "sell_reason",
-               "max_rate", "min_rate"]
+    init_db(db_url, clean_open_orders=False)
 
-    trades = pd.DataFrame([(t.pair, t.calc_profit(),
-                            t.open_date.replace(tzinfo=pytz.UTC),
-                            t.close_date.replace(tzinfo=pytz.UTC) if t.close_date else None,
-                            t.open_rate, t.close_rate,
-                            t.close_date.timestamp() - t.open_date.timestamp()
-                            if t.close_date else None,
+    columns = ["pair", "open_date", "close_date", "profit", "profit_percent",
+               "open_rate", "close_rate", "amount", "trade_duration", "sell_reason",
+               "fee_open", "fee_close", "open_rate_requested", "close_rate_requested",
+               "stake_amount", "max_rate", "min_rate", "id", "exchange",
+               "stop_loss", "initial_stop_loss", "strategy", "timeframe"]
+
+    filters = []
+    if strategy:
+        filters.append(Trade.strategy == strategy)
+
+    trades = pd.DataFrame([(t.pair,
+                            t.open_date.replace(tzinfo=timezone.utc),
+                            t.close_date.replace(tzinfo=timezone.utc) if t.close_date else None,
+                            t.calc_profit(), t.calc_profit_ratio(),
+                            t.open_rate, t.close_rate, t.amount,
+                            (round((t.close_date.timestamp() - t.open_date.timestamp()) / 60, 2)
+                             if t.close_date else None),
                             t.sell_reason,
+                            t.fee_open, t.fee_close,
+                            t.open_rate_requested,
+                            t.close_rate_requested,
+                            t.stake_amount,
                             t.max_rate,
                             t.min_rate,
+                            t.id, t.exchange,
+                            t.stop_loss, t.initial_stop_loss,
+                            t.strategy, t.timeframe
                             )
-                           for t in Trade.query.all()],
+                           for t in Trade.get_trades(filters).all()],
                           columns=columns)
 
     return trades
 
 
-def load_trades(config) -> pd.DataFrame:
+def load_trades(source: str, db_url: str, exportfilename: Path,
+                no_trades: bool = False, strategy: Optional[str] = None) -> pd.DataFrame:
     """
-    Based on configuration option "trade_source":
+    Based on configuration option 'trade_source':
     * loads data from DB (using `db_url`)
     * loads data from backtestfile (using `exportfilename`)
+    :param source: "DB" or "file" - specify source to load from
+    :param db_url: sqlalchemy formatted url to a database
+    :param exportfilename: Json file generated by backtesting
+    :param no_trades: Skip using trades, only return backtesting data columns
+    :return: DataFrame containing trades
     """
-    if config["trade_source"] == "DB":
-        return load_trades_from_db(config["db_url"])
-    elif config["trade_source"] == "file":
-        return load_backtest_data(Path(config["exportfilename"]))
+    if no_trades:
+        df = pd.DataFrame(columns=BT_DATA_COLUMNS)
+        return df
+
+    if source == "DB":
+        return load_trades_from_db(db_url)
+    elif source == "file":
+        return load_backtest_data(exportfilename, strategy)
 
 
-def extract_trades_of_period(dataframe: pd.DataFrame, trades: pd.DataFrame) -> pd.DataFrame:
+def extract_trades_of_period(dataframe: pd.DataFrame, trades: pd.DataFrame,
+                             date_index=False) -> pd.DataFrame:
     """
     Compare trades and backtested pair DataFrames to get trades performed on backtested period
     :return: the DataFrame of a trades of period
     """
-    trades = trades.loc[(trades['open_time'] >= dataframe.iloc[0]['date']) &
-                        (trades['close_time'] <= dataframe.iloc[-1]['date'])]
+    if date_index:
+        trades_start = dataframe.index[0]
+        trades_stop = dataframe.index[-1]
+    else:
+        trades_start = dataframe.iloc[0]['date']
+        trades_stop = dataframe.iloc[-1]['date']
+    trades = trades.loc[(trades['open_date'] >= trades_start) &
+                        (trades['close_date'] <= trades_stop)]
     return trades
 
 
-def combine_tickers_with_mean(tickers: Dict[str, pd.DataFrame], column: str = "close"):
+def calculate_market_change(data: Dict[str, pd.DataFrame], column: str = "close") -> float:
+    """
+    Calculate market change based on "column".
+    Calculation is done by taking the first non-null and the last non-null element of each column
+    and calculating the pctchange as "(last - first) / first".
+    Then the results per pair are combined as mean.
+
+    :param data: Dict of Dataframes, dict key should be pair.
+    :param column: Column in the original dataframes to use
+    :return:
+    """
+    tmp_means = []
+    for pair, df in data.items():
+        start = df[column].dropna().iloc[0]
+        end = df[column].dropna().iloc[-1]
+        tmp_means.append((end - start) / start)
+
+    return np.mean(tmp_means)
+
+
+def combine_dataframes_with_mean(data: Dict[str, pd.DataFrame],
+                                 column: str = "close") -> pd.DataFrame:
     """
     Combine multiple dataframes "column"
-    :param tickers: Dict of Dataframes, dict key should be pair.
+    :param data: Dict of Dataframes, dict key should be pair.
     :param column: Column in the original dataframes to use
     :return: DataFrame with the column renamed to the dict key, and a column
         named mean, containing the mean of all pairs.
     """
-    df_comb = pd.concat([tickers[pair].set_index('date').rename(
-        {column: pair}, axis=1)[pair] for pair in tickers], axis=1)
+    df_comb = pd.concat([data[pair].set_index('date').rename(
+        {column: pair}, axis=1)[pair] for pair in data], axis=1)
 
     df_comb['mean'] = df_comb.mean(axis=1)
 
     return df_comb
 
 
-def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str) -> pd.DataFrame:
+def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
+                      timeframe: str) -> pd.DataFrame:
     """
     Adds a column `col_name` with the cumulative profit for the given trades array.
     :param df: DataFrame with date index
-    :param trades: DataFrame containing trades (requires columns close_time and profitperc)
+    :param trades: DataFrame containing trades (requires columns close_date and profit_percent)
+    :param col_name: Column name that will be assigned the results
+    :param timeframe: Timeframe used during the operations
     :return: Returns df with one additional column, col_name, containing the cumulative profit.
+    :raise: ValueError if trade-dataframe was found empty.
     """
-    df[col_name] = trades.set_index('close_time')['profitperc'].cumsum()
+    if len(trades) == 0:
+        raise ValueError("Trade dataframe empty.")
+    from freqtrade.exchange import timeframe_to_minutes
+    timeframe_minutes = timeframe_to_minutes(timeframe)
+    # Resample to timeframe to make sure trades match candles
+    _trades_sum = trades.resample(f'{timeframe_minutes}min', on='close_date'
+                                  )[['profit_percent']].sum()
+    df.loc[:, col_name] = _trades_sum.cumsum()
     # Set first value to 0
     df.loc[df.iloc[0].name, col_name] = 0
     # FFill to get continuous
     df[col_name] = df[col_name].ffill()
     return df
+
+
+def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date',
+                           value_col: str = 'profit_percent'
+                           ) -> Tuple[float, pd.Timestamp, pd.Timestamp]:
+    """
+    Calculate max drawdown and the corresponding close dates
+    :param trades: DataFrame containing trades (requires columns close_date and profit_percent)
+    :param date_col: Column in DataFrame to use for dates (defaults to 'close_date')
+    :param value_col: Column in DataFrame to use for values (defaults to 'profit_percent')
+    :return: Tuple (float, highdate, lowdate) with absolute max drawdown, high and low time
+    :raise: ValueError if trade-dataframe was found empty.
+    """
+    if len(trades) == 0:
+        raise ValueError("Trade dataframe empty.")
+    profit_results = trades.sort_values(date_col).reset_index(drop=True)
+    max_drawdown_df = pd.DataFrame()
+    max_drawdown_df['cumulative'] = profit_results[value_col].cumsum()
+    max_drawdown_df['high_value'] = max_drawdown_df['cumulative'].cummax()
+    max_drawdown_df['drawdown'] = max_drawdown_df['cumulative'] - max_drawdown_df['high_value']
+
+    idxmin = max_drawdown_df['drawdown'].idxmin()
+    if idxmin == 0:
+        raise ValueError("No losing trade, therefore no drawdown.")
+    high_date = profit_results.loc[max_drawdown_df.iloc[:idxmin]['high_value'].idxmax(), date_col]
+    low_date = profit_results.loc[idxmin, date_col]
+    return abs(min(max_drawdown_df['drawdown'])), high_date, low_date
diff --git a/freqtrade/data/converter.py b/freqtrade/data/converter.py
index b530b3bce..d4053abaa 100644
--- a/freqtrade/data/converter.py
+++ b/freqtrade/data/converter.py
@@ -1,45 +1,68 @@
 """
 Functions to convert data from one format to another
 """
+import itertools
 import logging
+from datetime import datetime, timezone
+from operator import itemgetter
+from typing import Any, Dict, List
 
 import pandas as pd
 from pandas import DataFrame, to_datetime
 
+from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS, TradeList
+
 
 logger = logging.getLogger(__name__)
 
 
-def parse_ticker_dataframe(ticker: list, ticker_interval: str, pair: str, *,
-                           fill_missing: bool = True,
-                           drop_incomplete: bool = True) -> DataFrame:
+def ohlcv_to_dataframe(ohlcv: list, timeframe: str, pair: str, *,
+                       fill_missing: bool = True, drop_incomplete: bool = True) -> DataFrame:
     """
-    Converts a ticker-list (format ccxt.fetch_ohlcv) to a Dataframe
-    :param ticker: ticker list, as returned by exchange.async_get_candle_history
-    :param ticker_interval: ticker_interval (e.g. 5m). Used to fill up eventual missing data
+    Converts a list with candle (OHLCV) data (in format returned by ccxt.fetch_ohlcv)
+    to a Dataframe
+    :param ohlcv: list with candle (OHLCV) data, as returned by exchange.async_get_candle_history
+    :param timeframe: timeframe (e.g. 5m). Used to fill up eventual missing data
     :param pair: Pair this data is for (used to warn if fillup was necessary)
     :param fill_missing: fill up missing candles with 0 candles
                          (see ohlcv_fill_up_missing_data for details)
     :param drop_incomplete: Drop the last candle of the dataframe, assuming it's incomplete
     :return: DataFrame
     """
-    logger.debug("Parsing tickerlist to dataframe")
-    cols = ['date', 'open', 'high', 'low', 'close', 'volume']
-    frame = DataFrame(ticker, columns=cols)
+    logger.debug(f"Converting candle (OHLCV) data to dataframe for pair {pair}.")
+    cols = DEFAULT_DATAFRAME_COLUMNS
+    df = DataFrame(ohlcv, columns=cols)
 
-    frame['date'] = to_datetime(frame['date'],
-                                unit='ms',
-                                utc=True,
-                                infer_datetime_format=True)
+    df['date'] = to_datetime(df['date'], unit='ms', utc=True, infer_datetime_format=True)
 
-    # Some exchanges return int values for volume and even for ohlc.
+    # Some exchanges return int values for Volume and even for OHLC.
     # Convert them since TA-LIB indicators used in the strategy assume floats
     # and fail with exception...
-    frame = frame.astype(dtype={'open': 'float', 'high': 'float', 'low': 'float', 'close': 'float',
-                                'volume': 'float'})
+    df = df.astype(dtype={'open': 'float', 'high': 'float', 'low': 'float', 'close': 'float',
+                          'volume': 'float'})
+    return clean_ohlcv_dataframe(df, timeframe, pair,
+                                 fill_missing=fill_missing,
+                                 drop_incomplete=drop_incomplete)
 
+
+def clean_ohlcv_dataframe(data: DataFrame, timeframe: str, pair: str, *,
+                          fill_missing: bool = True,
+                          drop_incomplete: bool = True) -> DataFrame:
+    """
+    Clense a OHLCV dataframe by
+      * Grouping it by date (removes duplicate tics)
+      * dropping last candles if requested
+      * Filling up missing data (if requested)
+    :param data: DataFrame containing candle (OHLCV) data.
+    :param timeframe: timeframe (e.g. 5m). Used to fill up eventual missing data
+    :param pair: Pair this data is for (used to warn if fillup was necessary)
+    :param fill_missing: fill up missing candles with 0 candles
+                         (see ohlcv_fill_up_missing_data for details)
+    :param drop_incomplete: Drop the last candle of the dataframe, assuming it's incomplete
+    :return: DataFrame
+    """
     # group by index and aggregate results to eliminate duplicate ticks
-    frame = frame.groupby(by='date', as_index=False, sort=True).agg({
+    data = data.groupby(by='date', as_index=False, sort=True).agg({
         'open': 'first',
         'high': 'max',
         'low': 'min',
@@ -48,16 +71,16 @@ def parse_ticker_dataframe(ticker: list, ticker_interval: str, pair: str, *,
     })
     # eliminate partial candle
     if drop_incomplete:
-        frame.drop(frame.tail(1).index, inplace=True)
+        data.drop(data.tail(1).index, inplace=True)
         logger.debug('Dropping last candle')
 
     if fill_missing:
-        return ohlcv_fill_up_missing_data(frame, ticker_interval, pair)
+        return ohlcv_fill_up_missing_data(data, timeframe, pair)
     else:
-        return frame
+        return data
 
 
-def ohlcv_fill_up_missing_data(dataframe: DataFrame, ticker_interval: str, pair: str) -> DataFrame:
+def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str) -> DataFrame:
     """
     Fills up missing data with 0 volume rows,
     using the previous close as price for "open", "high" "low" and "close", volume is set to 0
@@ -65,16 +88,16 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, ticker_interval: str, pair:
     """
     from freqtrade.exchange import timeframe_to_minutes
 
-    ohlc_dict = {
+    ohlcv_dict = {
         'open': 'first',
         'high': 'max',
         'low': 'min',
         'close': 'last',
         'volume': 'sum'
     }
-    ticker_minutes = timeframe_to_minutes(ticker_interval)
+    timeframe_minutes = timeframe_to_minutes(timeframe)
     # Resample to create "NAN" values
-    df = dataframe.resample(f'{ticker_minutes}min', on='date').agg(ohlc_dict)
+    df = dataframe.resample(f'{timeframe_minutes}min', on='date').agg(ohlcv_dict)
 
     # Forwardfill close for missing columns
     df['close'] = df['close'].fillna(method='ffill')
@@ -92,8 +115,26 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, ticker_interval: str, pair:
     return df
 
 
+def trim_dataframe(df: DataFrame, timerange, df_date_col: str = 'date') -> DataFrame:
+    """
+    Trim dataframe based on given timerange
+    :param df: Dataframe to trim
+    :param timerange: timerange (use start and end date if available)
+    :param: df_date_col: Column in the dataframe to use as Date column
+    :return: trimmed dataframe
+    """
+    if timerange.starttype == 'date':
+        start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
+        df = df.loc[df[df_date_col] >= start, :]
+    if timerange.stoptype == 'date':
+        stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
+        df = df.loc[df[df_date_col] <= stop, :]
+    return df
+
+
 def order_book_to_dataframe(bids: list, asks: list) -> DataFrame:
     """
+    TODO: This should get a dedicated test
     Gets order book list, returns dataframe with below format per suggested by creslin
     -------------------------------------------------------------------
      b_sum       b_size       bids       asks       a_size       a_sum
@@ -114,3 +155,110 @@ def order_book_to_dataframe(bids: list, asks: list) -> DataFrame:
                       keys=['b_sum', 'b_size', 'bids', 'asks', 'a_size', 'a_sum'])
     # logger.info('order book %s', frame )
     return frame
+
+
+def trades_remove_duplicates(trades: List[List]) -> List[List]:
+    """
+    Removes duplicates from the trades list.
+    Uses itertools.groupby to avoid converting to pandas.
+    Tests show it as being pretty efficient on lists of 4M Lists.
+    :param trades: List of Lists with constants.DEFAULT_TRADES_COLUMNS as columns
+    :return: same format as above, but with duplicates removed
+    """
+    return [i for i, _ in itertools.groupby(sorted(trades, key=itemgetter(0)))]
+
+
+def trades_dict_to_list(trades: List[Dict]) -> TradeList:
+    """
+    Convert fetch_trades result into a List (to be more memory efficient).
+    :param trades: List of trades, as returned by ccxt.fetch_trades.
+    :return: List of Lists, with constants.DEFAULT_TRADES_COLUMNS as columns
+    """
+    return [[t[col] for col in DEFAULT_TRADES_COLUMNS] for t in trades]
+
+
+def trades_to_ohlcv(trades: TradeList, timeframe: str) -> DataFrame:
+    """
+    Converts trades list to OHLCV list
+    :param trades: List of trades, as returned by ccxt.fetch_trades.
+    :param timeframe: Timeframe to resample data to
+    :return: OHLCV Dataframe.
+    :raises: ValueError if no trades are provided
+    """
+    from freqtrade.exchange import timeframe_to_minutes
+    timeframe_minutes = timeframe_to_minutes(timeframe)
+    if not trades:
+        raise ValueError('Trade-list empty.')
+    df = pd.DataFrame(trades, columns=DEFAULT_TRADES_COLUMNS)
+    df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms',
+                                     utc=True,)
+    df = df.set_index('timestamp')
+
+    df_new = df['price'].resample(f'{timeframe_minutes}min').ohlc()
+    df_new['volume'] = df['amount'].resample(f'{timeframe_minutes}min').sum()
+    df_new['date'] = df_new.index
+    # Drop 0 volume rows
+    df_new = df_new.dropna()
+    return df_new.loc[:, DEFAULT_DATAFRAME_COLUMNS]
+
+
+def convert_trades_format(config: Dict[str, Any], convert_from: str, convert_to: str, erase: bool):
+    """
+    Convert trades from one format to another format.
+    :param config: Config dictionary
+    :param convert_from: Source format
+    :param convert_to: Target format
+    :param erase: Erase souce data (does not apply if source and target format are identical)
+    """
+    from freqtrade.data.history.idatahandler import get_datahandler
+    src = get_datahandler(config['datadir'], convert_from)
+    trg = get_datahandler(config['datadir'], convert_to)
+
+    if 'pairs' not in config:
+        config['pairs'] = src.trades_get_pairs(config['datadir'])
+    logger.info(f"Converting trades for {config['pairs']}")
+
+    for pair in config['pairs']:
+        data = src.trades_load(pair=pair)
+        logger.info(f"Converting {len(data)} trades for {pair}")
+        trg.trades_store(pair, data)
+        if erase and convert_from != convert_to:
+            logger.info(f"Deleting source Trade data for {pair}.")
+            src.trades_purge(pair=pair)
+
+
+def convert_ohlcv_format(config: Dict[str, Any], convert_from: str, convert_to: str, erase: bool):
+    """
+    Convert OHLCV from one format to another
+    :param config: Config dictionary
+    :param convert_from: Source format
+    :param convert_to: Target format
+    :param erase: Erase souce data (does not apply if source and target format are identical)
+    """
+    from freqtrade.data.history.idatahandler import get_datahandler
+    src = get_datahandler(config['datadir'], convert_from)
+    trg = get_datahandler(config['datadir'], convert_to)
+    timeframes = config.get('timeframes', [config.get('timeframe')])
+    logger.info(f"Converting candle (OHLCV) for timeframe {timeframes}")
+
+    if 'pairs' not in config:
+        config['pairs'] = []
+        # Check timeframes or fall back to timeframe.
+        for timeframe in timeframes:
+            config['pairs'].extend(src.ohlcv_get_pairs(config['datadir'],
+                                                       timeframe))
+    logger.info(f"Converting candle (OHLCV) data for {config['pairs']}")
+
+    for timeframe in timeframes:
+        for pair in config['pairs']:
+            data = src.ohlcv_load(pair=pair, timeframe=timeframe,
+                                  timerange=None,
+                                  fill_missing=False,
+                                  drop_incomplete=False,
+                                  startup_candles=0)
+            logger.info(f"Converting {len(data)} candles for {pair}")
+            if len(data) > 0:
+                trg.ohlcv_store(pair=pair, timeframe=timeframe, data=data)
+                if erase and convert_from != convert_to:
+                    logger.info(f"Deleting source data for {pair} / {timeframe}")
+                    src.ohlcv_purge(pair=pair, timeframe=timeframe)
diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py
index b87589df7..a035b7c3b 100644
--- a/freqtrade/data/dataprovider.py
+++ b/freqtrade/data/dataprovider.py
@@ -1,31 +1,53 @@
 """
 Dataprovider
 Responsible to provide data to the bot
-including Klines, tickers, historic data
+including ticker and orderbook data, live and historical candle (OHLCV) data
 Common Interface for bot and strategy to access data.
 """
 import logging
-from pathlib import Path
-from typing import List, Tuple
+from datetime import datetime, timezone
+from typing import Any, Dict, List, Optional, Tuple
 
 from pandas import DataFrame
 
+from freqtrade.constants import ListPairsWithTimeframes, PairWithTimeframe
 from freqtrade.data.history import load_pair_history
+from freqtrade.exceptions import ExchangeError, OperationalException
 from freqtrade.exchange import Exchange
 from freqtrade.state import RunMode
 
+
 logger = logging.getLogger(__name__)
 
 
-class DataProvider():
+class DataProvider:
 
-    def __init__(self, config: dict, exchange: Exchange) -> None:
+    def __init__(self, config: dict, exchange: Exchange, pairlists=None) -> None:
         self._config = config
         self._exchange = exchange
+        self._pairlists = pairlists
+        self.__cached_pairs: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {}
+
+    def _set_cached_df(self, pair: str, timeframe: str, dataframe: DataFrame) -> None:
+        """
+        Store cached Dataframe.
+        Using private method as this should never be used by a user
+        (but the class is exposed via `self.dp` to the strategy)
+        :param pair: pair to get the data for
+        :param timeframe: Timeframe to get data for
+        :param dataframe: analyzed dataframe
+        """
+        self.__cached_pairs[(pair, timeframe)] = (dataframe, datetime.now(timezone.utc))
+
+    def add_pairlisthandler(self, pairlists) -> None:
+        """
+        Allow adding pairlisthandler after initialization
+        """
+        self._pairlists = pairlists
 
     def refresh(self,
-                pairlist: List[Tuple[str, str]],
-                helping_pairs: List[Tuple[str, str]] = None) -> None:
+                pairlist: ListPairsWithTimeframes,
+                helping_pairs: ListPairsWithTimeframes = None) -> None:
         """
         Refresh data, called with each cycle
         """
@@ -35,60 +57,100 @@ class DataProvider():
             self._exchange.refresh_latest_ohlcv(pairlist)
 
     @property
-    def available_pairs(self) -> List[Tuple[str, str]]:
+    def available_pairs(self) -> ListPairsWithTimeframes:
         """
-        Return a list of tuples containing pair, ticker_interval for which data is currently cached.
+        Return a list of tuples containing (pair, timeframe) for which data is currently cached.
         Should be whitelist + open trades.
         """
         return list(self._exchange._klines.keys())
 
-    def ohlcv(self, pair: str, ticker_interval: str = None, copy: bool = True) -> DataFrame:
+    def ohlcv(self, pair: str, timeframe: str = None, copy: bool = True) -> DataFrame:
         """
-        get ohlcv data for the given pair as DataFrame
-        Please check `available_pairs` to verify which pairs are currently cached.
+        Get candle (OHLCV) data for the given pair as DataFrame
+        Please use the `available_pairs` method to verify which pairs are currently cached.
         :param pair: pair to get the data for
-        :param ticker_interval: ticker_interval to get pair for
-        :param copy: copy dataframe before returning.
-                     Use false only for RO operations (where the dataframe is not modified)
+        :param timeframe: Timeframe to get data for
+        :param copy: copy dataframe before returning if True.
+                     Use False only for read-only operations (where the dataframe is not modified)
         """
         if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
-            if ticker_interval:
-                pairtick = (pair, ticker_interval)
-            else:
-                pairtick = (pair, self._config['ticker_interval'])
-
-            return self._exchange.klines(pairtick, copy=copy)
+            return self._exchange.klines((pair, timeframe or self._config['timeframe']),
+                                         copy=copy)
         else:
             return DataFrame()
 
-    def historic_ohlcv(self, pair: str, ticker_interval: str) -> DataFrame:
+    def historic_ohlcv(self, pair: str, timeframe: str = None) -> DataFrame:
         """
-        get stored historic ohlcv data
+        Get stored historical candle (OHLCV) data
         :param pair: pair to get the data for
-        :param ticker_interval: ticker_interval to get pair for
+        :param timeframe: timeframe to get data for
         """
         return load_pair_history(pair=pair,
-                                 ticker_interval=ticker_interval,
-                                 refresh_pairs=False,
-                                 datadir=Path(self._config['datadir']) if self._config.get(
-                                     'datadir') else None
+                                 timeframe=timeframe or self._config['timeframe'],
+                                 datadir=self._config['datadir'],
+                                 data_format=self._config.get('dataformat_ohlcv', 'json')
                                  )
 
+    def get_pair_dataframe(self, pair: str, timeframe: str = None) -> DataFrame:
+        """
+        Return pair candle (OHLCV) data, either live or cached historical -- depending
+        on the runmode.
+        :param pair: pair to get the data for
+        :param timeframe: timeframe to get data for
+        :return: Dataframe for this pair
+        """
+        if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
+            # Get live OHLCV data.
+            data = self.ohlcv(pair=pair, timeframe=timeframe)
+        else:
+            # Get historical OHLCV data (cached on disk).
+            data = self.historic_ohlcv(pair=pair, timeframe=timeframe)
+        if len(data) == 0:
+            logger.warning(f"No data found for ({pair}, {timeframe}).")
+        return data
+
+    def get_analyzed_dataframe(self, pair: str, timeframe: str) -> Tuple[DataFrame, datetime]:
+        """
+        :param pair: pair to get the data for
+        :param timeframe: timeframe to get data for
+        :return: Tuple of (Analyzed Dataframe, lastrefreshed) for the requested pair / timeframe
+            combination.
+            Returns empty dataframe and Epoch 0 (1970-01-01) if no dataframe was cached.
+        """
+        if (pair, timeframe) in self.__cached_pairs:
+            return self.__cached_pairs[(pair, timeframe)]
+        else:
+
+            return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc))
+
+    def market(self, pair: str) -> Optional[Dict[str, Any]]:
+        """
+        Return market data for the pair
+        :param pair: Pair to get the data for
+        :return: Market data dict from ccxt or None if market info is not available for the pair
+        """
+        return self._exchange.markets.get(pair)
+
     def ticker(self, pair: str):
         """
-        Return last ticker data
+        Return last ticker data from exchange
+        :param pair: Pair to get the data for
+        :return: Ticker dict from exchange or empty dict if ticker is not available for the pair
         """
-        # TODO: Implement me
-        pass
+        try:
+            return self._exchange.fetch_ticker(pair)
+        except ExchangeError:
+            return {}
 
-    def orderbook(self, pair: str, maximum: int):
+    def orderbook(self, pair: str, maximum: int) -> Dict[str, List]:
         """
-        return latest orderbook data
+        Fetch latest l2 orderbook data
+        Warning: Does a network request - so use with common sense.
         :param pair: pair to get the data for
         :param maximum: Maximum number of orderbook entries to query
         :return: dict including bids/asks with a total of `maximum` entries.
         """
-        return self._exchange.get_order_book(pair, maximum)
+        return self._exchange.fetch_l2_order_book(pair, maximum)
 
     @property
     def runmode(self) -> RunMode:
@@ -97,3 +159,17 @@ class DataProvider():
         can be "live", "dry-run", "backtest", "edgecli", "hyperopt" or "other".
         """
         return RunMode(self._config.get('runmode', RunMode.OTHER))
+
+    def current_whitelist(self) -> List[str]:
+        """
+        fetch latest available whitelist.
+
+        Useful when you have a large whitelist and need to call each pair as an informative pair.
+        As available pairs does not show whitelist until after informative pairs have been cached.
+        :return: list of pairs in whitelist
+        """
+
+        if self._pairlists:
+            return self._pairlists.whitelist
+        else:
+            raise OperationalException("Dataprovider was not initialized with a pairlist provider.")
diff --git a/freqtrade/data/history.py b/freqtrade/data/history.py
deleted file mode 100644
index f600615df..000000000
--- a/freqtrade/data/history.py
+++ /dev/null
@@ -1,308 +0,0 @@
-"""
-Handle historic data (ohlcv).
-
-Includes:
-* load data for a pair (or a list of pairs) from disk
-* download data from exchange and store to disk
-"""
-
-import logging
-import operator
-from datetime import datetime
-from pathlib import Path
-from typing import Any, Dict, List, Optional, Tuple
-
-import arrow
-from pandas import DataFrame
-
-from freqtrade import OperationalException, misc
-from freqtrade.configuration import TimeRange
-from freqtrade.data.converter import parse_ticker_dataframe
-from freqtrade.exchange import Exchange, timeframe_to_minutes
-
-logger = logging.getLogger(__name__)
-
-
-def trim_tickerlist(tickerlist: List[Dict], timerange: TimeRange) -> List[Dict]:
-    """
-    Trim tickerlist based on given timerange
-    """
-    if not tickerlist:
-        return tickerlist
-
-    start_index = 0
-    stop_index = len(tickerlist)
-
-    if timerange.starttype == 'line':
-        stop_index = timerange.startts
-    if timerange.starttype == 'index':
-        start_index = timerange.startts
-    elif timerange.starttype == 'date':
-        while (start_index < len(tickerlist) and
-               tickerlist[start_index][0] < timerange.startts * 1000):
-            start_index += 1
-
-    if timerange.stoptype == 'line':
-        start_index = len(tickerlist) + timerange.stopts
-    if timerange.stoptype == 'index':
-        stop_index = timerange.stopts
-    elif timerange.stoptype == 'date':
-        while (stop_index > 0 and
-               tickerlist[stop_index-1][0] > timerange.stopts * 1000):
-            stop_index -= 1
-
-    if start_index > stop_index:
-        raise ValueError(f'The timerange [{timerange.startts},{timerange.stopts}] is incorrect')
-
-    return tickerlist[start_index:stop_index]
-
-
-def load_tickerdata_file(
-        datadir: Optional[Path], pair: str,
-        ticker_interval: str,
-        timerange: Optional[TimeRange] = None) -> Optional[list]:
-    """
-    Load a pair from file, either .json.gz or .json
-    :return: tickerlist or None if unsuccesful
-    """
-    filename = pair_data_filename(datadir, pair, ticker_interval)
-    pairdata = misc.file_load_json(filename)
-    if not pairdata:
-        return None
-
-    if timerange:
-        pairdata = trim_tickerlist(pairdata, timerange)
-    return pairdata
-
-
-def load_pair_history(pair: str,
-                      ticker_interval: str,
-                      datadir: Optional[Path],
-                      timerange: TimeRange = TimeRange(None, None, 0, 0),
-                      refresh_pairs: bool = False,
-                      exchange: Optional[Exchange] = None,
-                      fill_up_missing: bool = True,
-                      drop_incomplete: bool = True
-                      ) -> DataFrame:
-    """
-    Loads cached ticker history for the given pair.
-    :param pair: Pair to load data for
-    :param ticker_interval: Ticker-interval (e.g. "5m")
-    :param datadir: Path to the data storage location.
-    :param timerange: Limit data to be loaded to this timerange
-    :param refresh_pairs: Refresh pairs from exchange.
-        (Note: Requires exchange to be passed as well.)
-    :param exchange: Exchange object (needed when using "refresh_pairs")
-    :param fill_up_missing: Fill missing values with "No action"-candles
-    :param drop_incomplete: Drop last candle assuming it may be incomplete.
-    :return: DataFrame with ohlcv data
-    """
-
-    # The user forced the refresh of pairs
-    if refresh_pairs:
-        download_pair_history(datadir=datadir,
-                              exchange=exchange,
-                              pair=pair,
-                              ticker_interval=ticker_interval,
-                              timerange=timerange)
-
-    pairdata = load_tickerdata_file(datadir, pair, ticker_interval, timerange=timerange)
-
-    if pairdata:
-        if timerange.starttype == 'date' and pairdata[0][0] > timerange.startts * 1000:
-            logger.warning('Missing data at start for pair %s, data starts at %s',
-                           pair, arrow.get(pairdata[0][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
-        if timerange.stoptype == 'date' and pairdata[-1][0] < timerange.stopts * 1000:
-            logger.warning('Missing data at end for pair %s, data ends at %s',
-                           pair,
-                           arrow.get(pairdata[-1][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
-        return parse_ticker_dataframe(pairdata, ticker_interval, pair=pair,
-                                      fill_missing=fill_up_missing,
-                                      drop_incomplete=drop_incomplete)
-    else:
-        logger.warning(
-            f'No history data for pair: "{pair}", interval: {ticker_interval}. '
-            'Use --refresh-pairs-cached option or download_backtest_data.py '
-            'script to download the data'
-        )
-        return None
-
-
-def load_data(datadir: Optional[Path],
-              ticker_interval: str,
-              pairs: List[str],
-              refresh_pairs: bool = False,
-              exchange: Optional[Exchange] = None,
-              timerange: TimeRange = TimeRange(None, None, 0, 0),
-              fill_up_missing: bool = True,
-              live: bool = False
-              ) -> Dict[str, DataFrame]:
-    """
-    Loads ticker history data for a list of pairs the given parameters
-    :return: dict(<pair>:<tickerlist>)
-    """
-    result: Dict[str, DataFrame] = {}
-    if live:
-        if exchange:
-            logger.info('Live: Downloading data for all defined pairs ...')
-            exchange.refresh_latest_ohlcv([(pair, ticker_interval) for pair in pairs])
-            result = {key[0]: value for key, value in exchange._klines.items() if value is not None}
-        else:
-            raise OperationalException(
-                "Exchange needs to be initialized when using live data."
-            )
-    else:
-        logger.info('Using local backtesting data ...')
-
-        for pair in pairs:
-            hist = load_pair_history(pair=pair, ticker_interval=ticker_interval,
-                                     datadir=datadir, timerange=timerange,
-                                     refresh_pairs=refresh_pairs,
-                                     exchange=exchange,
-                                     fill_up_missing=fill_up_missing)
-            if hist is not None:
-                result[pair] = hist
-    return result
-
-
-def make_testdata_path(datadir: Optional[Path]) -> Path:
-    """Return the path where testdata files are stored"""
-    return datadir or (Path(__file__).parent.parent / "tests" / "testdata").resolve()
-
-
-def pair_data_filename(datadir: Optional[Path], pair: str, ticker_interval: str) -> Path:
-    path = make_testdata_path(datadir)
-    pair_s = pair.replace("/", "_")
-    filename = path.joinpath(f'{pair_s}-{ticker_interval}.json')
-    return filename
-
-
-def load_cached_data_for_updating(filename: Path, ticker_interval: str,
-                                  timerange: Optional[TimeRange]) -> Tuple[List[Any],
-                                                                           Optional[int]]:
-    """
-    Load cached data and choose what part of the data should be updated
-    """
-
-    since_ms = None
-
-    # user sets timerange, so find the start time
-    if timerange:
-        if timerange.starttype == 'date':
-            since_ms = timerange.startts * 1000
-        elif timerange.stoptype == 'line':
-            num_minutes = timerange.stopts * timeframe_to_minutes(ticker_interval)
-            since_ms = arrow.utcnow().shift(minutes=num_minutes).timestamp * 1000
-
-    # read the cached file
-    if filename.is_file():
-        with open(filename, "rt") as file:
-            data = misc.json_load(file)
-        # remove the last item, could be incomplete candle
-        if data:
-            data.pop()
-    else:
-        data = []
-
-    if data:
-        if since_ms and since_ms < data[0][0]:
-            # Earlier data than existing data requested, redownload all
-            data = []
-        else:
-            # a part of the data was already downloaded, so download unexist data only
-            since_ms = data[-1][0] + 1
-
-    return (data, since_ms)
-
-
-def download_pair_history(datadir: Optional[Path],
-                          exchange: Optional[Exchange],
-                          pair: str,
-                          ticker_interval: str = '5m',
-                          timerange: Optional[TimeRange] = None) -> bool:
-    """
-    Download the latest ticker intervals from the exchange for the pair passed in parameters
-    The data is downloaded starting from the last correct ticker interval data that
-    exists in a cache. If timerange starts earlier than the data in the cache,
-    the full data will be redownloaded
-
-    Based on @Rybolov work: https://github.com/rybolov/freqtrade-data
-
-    :param pair: pair to download
-    :param ticker_interval: ticker interval
-    :param timerange: range of time to download
-    :return: bool with success state
-    """
-    if not exchange:
-        raise OperationalException(
-            "Exchange needs to be initialized when downloading pair history data"
-        )
-
-    try:
-        filename = pair_data_filename(datadir, pair, ticker_interval)
-
-        logger.info(
-            f'Download history data for pair: "{pair}", interval: {ticker_interval} '
-            f'and store in {datadir}.'
-        )
-
-        data, since_ms = load_cached_data_for_updating(filename, ticker_interval, timerange)
-
-        logger.debug("Current Start: %s", misc.format_ms_time(data[1][0]) if data else 'None')
-        logger.debug("Current End: %s", misc.format_ms_time(data[-1][0]) if data else 'None')
-
-        # Default since_ms to 30 days if nothing is given
-        new_data = exchange.get_history(pair=pair, ticker_interval=ticker_interval,
-                                        since_ms=since_ms if since_ms
-                                        else
-                                        int(arrow.utcnow().shift(days=-30).float_timestamp) * 1000)
-        data.extend(new_data)
-
-        logger.debug("New Start: %s", misc.format_ms_time(data[0][0]))
-        logger.debug("New End: %s", misc.format_ms_time(data[-1][0]))
-
-        misc.file_dump_json(filename, data)
-        return True
-
-    except Exception as e:
-        logger.error(
-            f'Failed to download history data for pair: "{pair}", interval: {ticker_interval}. '
-            f'Error: {e}'
-        )
-        return False
-
-
-def get_timeframe(data: Dict[str, DataFrame]) -> Tuple[arrow.Arrow, arrow.Arrow]:
-    """
-    Get the maximum timeframe for the given backtest data
-    :param data: dictionary with preprocessed backtesting data
-    :return: tuple containing min_date, max_date
-    """
-    timeframe = [
-        (arrow.get(frame['date'].min()), arrow.get(frame['date'].max()))
-        for frame in data.values()
-    ]
-    return min(timeframe, key=operator.itemgetter(0))[0], \
-        max(timeframe, key=operator.itemgetter(1))[1]
-
-
-def validate_backtest_data(data: DataFrame, pair: str, min_date: datetime,
-                           max_date: datetime, ticker_interval_mins: int) -> bool:
-    """
-    Validates preprocessed backtesting data for missing values and shows warnings about it that.
-
-    :param data: preprocessed backtesting data (as DataFrame)
-    :param pair: pair used for log output.
-    :param min_date: start-date of the data
-    :param max_date: end-date of the data
-    :param ticker_interval_mins: ticker interval in minutes
-    """
-    # total difference in minutes / interval-minutes
-    expected_frames = int((max_date - min_date).total_seconds() // 60 // ticker_interval_mins)
-    found_missing = False
-    dflen = len(data)
-    if dflen < expected_frames:
-        found_missing = True
-        logger.warning("%s has missing frames: expected %s, got %s, that's %s missing values",
-                       pair, expected_frames, dflen, expected_frames - dflen)
-    return found_missing
diff --git a/freqtrade/data/history/__init__.py b/freqtrade/data/history/__init__.py
new file mode 100644
index 000000000..107f9c401
--- /dev/null
+++ b/freqtrade/data/history/__init__.py
@@ -0,0 +1,12 @@
+"""
+Handle historic data (ohlcv).
+
+Includes:
+* load data for a pair (or a list of pairs) from disk
+* download data from exchange and store to disk
+"""
+# flake8: noqa: F401
+from .history_utils import (convert_trades_to_ohlcv, get_timerange, load_data, load_pair_history,
+                            refresh_backtest_ohlcv_data, refresh_backtest_trades_data, refresh_data,
+                            validate_backtest_data)
+from .idatahandler import get_datahandler
diff --git a/freqtrade/data/history/hdf5datahandler.py b/freqtrade/data/history/hdf5datahandler.py
new file mode 100644
index 000000000..d116637e7
--- /dev/null
+++ b/freqtrade/data/history/hdf5datahandler.py
@@ -0,0 +1,213 @@
+import logging
+import re
+from pathlib import Path
+from typing import List, Optional
+
+import numpy as np
+import pandas as pd
+
+from freqtrade import misc
+from freqtrade.configuration import TimeRange
+from freqtrade.constants import (DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS,
+                                 ListPairsWithTimeframes, TradeList)
+
+from .idatahandler import IDataHandler
+
+
+logger = logging.getLogger(__name__)
+
+
+class HDF5DataHandler(IDataHandler):
+
+    _columns = DEFAULT_DATAFRAME_COLUMNS
+
+    @classmethod
+    def ohlcv_get_available_data(cls, datadir: Path) -> ListPairsWithTimeframes:
+        """
+        Returns a list of all pairs with ohlcv data available in this datadir
+        :param datadir: Directory to search for ohlcv files
+        :return: List of Tuples of (pair, timeframe)
+        """
+        _tmp = [re.search(r'^([a-zA-Z_]+)\-(\d+\S+)(?=.h5)', p.name)
+                for p in datadir.glob("*.h5")]
+        return [(match[1].replace('_', '/'), match[2]) for match in _tmp
+                if match and len(match.groups()) > 1]
+
+    @classmethod
+    def ohlcv_get_pairs(cls, datadir: Path, timeframe: str) -> List[str]:
+        """
+        Returns a list of all pairs with ohlcv data available in this datadir
+        for the specified timeframe
+        :param datadir: Directory to search for ohlcv files
+        :param timeframe: Timeframe to search pairs for
+        :return: List of Pairs
+        """
+
+        _tmp = [re.search(r'^(\S+)(?=\-' + timeframe + '.h5)', p.name)
+                for p in datadir.glob(f"*{timeframe}.h5")]
+        # Check if regex found something and only return these results
+        return [match[0].replace('_', '/') for match in _tmp if match]
+
+    def ohlcv_store(self, pair: str, timeframe: str, data: pd.DataFrame) -> None:
+        """
+        Store data in hdf5 file.
+        :param pair: Pair - used to generate filename
+        :timeframe: Timeframe - used to generate filename
+        :data: Dataframe containing OHLCV data
+        :return: None
+        """
+        key = self._pair_ohlcv_key(pair, timeframe)
+        _data = data.copy()
+
+        filename = self._pair_data_filename(self._datadir, pair, timeframe)
+
+        ds = pd.HDFStore(filename, mode='a', complevel=9, complib='blosc')
+        ds.put(key, _data.loc[:, self._columns], format='table', data_columns=['date'])
+
+        ds.close()
+
+    def _ohlcv_load(self, pair: str, timeframe: str,
+                    timerange: Optional[TimeRange] = None) -> pd.DataFrame:
+        """
+        Internal method used to load data for one pair from disk.
+        Implements the loading and conversion to a Pandas dataframe.
+        Timerange trimming and dataframe validation happens outside of this method.
+        :param pair: Pair to load data
+        :param timeframe: Timeframe (e.g. "5m")
+        :param timerange: Limit data to be loaded to this timerange.
+                        Optionally implemented by subclasses to avoid loading
+                        all data where possible.
+        :return: DataFrame with ohlcv data, or empty DataFrame
+        """
+        key = self._pair_ohlcv_key(pair, timeframe)
+        filename = self._pair_data_filename(self._datadir, pair, timeframe)
+
+        if not filename.exists():
+            return pd.DataFrame(columns=self._columns)
+        where = []
+        if timerange:
+            if timerange.starttype == 'date':
+                where.append(f"date >= Timestamp({timerange.startts * 1e9})")
+            if timerange.stoptype == 'date':
+                where.append(f"date < Timestamp({timerange.stopts * 1e9})")
+
+        pairdata = pd.read_hdf(filename, key=key, mode="r", where=where)
+
+        if list(pairdata.columns) != self._columns:
+            raise ValueError("Wrong dataframe format")
+        pairdata = pairdata.astype(dtype={'open': 'float', 'high': 'float',
+                                          'low': 'float', 'close': 'float', 'volume': 'float'})
+        return pairdata
+
+    def ohlcv_purge(self, pair: str, timeframe: str) -> bool:
+        """
+        Remove data for this pair
+        :param pair: Delete data for this pair.
+        :param timeframe: Timeframe (e.g. "5m")
+        :return: True when deleted, false if file did not exist.
+        """
+        filename = self._pair_data_filename(self._datadir, pair, timeframe)
+        if filename.exists():
+            filename.unlink()
+            return True
+        return False
+
+    def ohlcv_append(self, pair: str, timeframe: str, data: pd.DataFrame) -> None:
+        """
+        Append data to existing data structures
+        :param pair: Pair
+        :param timeframe: Timeframe this ohlcv data is for
+        :param data: Data to append.
+        """
+        raise NotImplementedError()
+
+    @classmethod
+    def trades_get_pairs(cls, datadir: Path) -> List[str]:
+        """
+        Returns a list of all pairs for which trade data is available in this
+        :param datadir: Directory to search for ohlcv files
+        :return: List of Pairs
+        """
+        _tmp = [re.search(r'^(\S+)(?=\-trades.h5)', p.name)
+                for p in datadir.glob("*trades.h5")]
+        # Check if regex found something and only return these results to avoid exceptions.
+        return [match[0].replace('_', '/') for match in _tmp if match]
+
+    def trades_store(self, pair: str, data: TradeList) -> None:
+        """
+        Store trades data (list of Dicts) to file
+        :param pair: Pair - used for filename
+        :param data: List of Lists containing trade data,
+                     column sequence as in DEFAULT_TRADES_COLUMNS
+        """
+        key = self._pair_trades_key(pair)
+
+        ds = pd.HDFStore(self._pair_trades_filename(self._datadir, pair),
+                         mode='a', complevel=9, complib='blosc')
+        ds.put(key, pd.DataFrame(data, columns=DEFAULT_TRADES_COLUMNS),
+               format='table', data_columns=['timestamp'])
+        ds.close()
+
+    def trades_append(self, pair: str, data: TradeList):
+        """
+        Append data to existing files
+        :param pair: Pair - used for filename
+        :param data: List of Lists containing trade data,
+                     column sequence as in DEFAULT_TRADES_COLUMNS
+        """
+        raise NotImplementedError()
+
+    def _trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> TradeList:
+        """
+        Load a pair from h5 file.
+        :param pair: Load trades for this pair
+        :param timerange: Timerange to load trades for - currently not implemented
+        :return: List of trades
+        """
+        key = self._pair_trades_key(pair)
+        filename = self._pair_trades_filename(self._datadir, pair)
+
+        if not filename.exists():
+            return []
+        where = []
+        if timerange:
+            if timerange.starttype == 'date':
+                where.append(f"timestamp >= {timerange.startts * 1e3}")
+            if timerange.stoptype == 'date':
+                where.append(f"timestamp < {timerange.stopts * 1e3}")
+
+        trades: pd.DataFrame = pd.read_hdf(filename, key=key, mode="r", where=where)
+        trades[['id', 'type']] = trades[['id', 'type']].replace({np.nan: None})
+        return trades.values.tolist()
+
+    def trades_purge(self, pair: str) -> bool:
+        """
+        Remove data for this pair
+        :param pair: Delete data for this pair.
+        :return: True when deleted, false if file did not exist.
+        """
+        filename = self._pair_trades_filename(self._datadir, pair)
+        if filename.exists():
+            filename.unlink()
+            return True
+        return False
+
+    @classmethod
+    def _pair_ohlcv_key(cls, pair: str, timeframe: str) -> str:
+        return f"{pair}/ohlcv/tf_{timeframe}"
+
+    @classmethod
+    def _pair_trades_key(cls, pair: str) -> str:
+        return f"{pair}/trades"
+
+    @classmethod
+    def _pair_data_filename(cls, datadir: Path, pair: str, timeframe: str) -> Path:
+        pair_s = misc.pair_to_filename(pair)
+        filename = datadir.joinpath(f'{pair_s}-{timeframe}.h5')
+        return filename
+
+    @classmethod
+    def _pair_trades_filename(cls, datadir: Path, pair: str) -> Path:
+        pair_s = misc.pair_to_filename(pair)
+        filename = datadir.joinpath(f'{pair_s}-trades.h5')
+        return filename
diff --git a/freqtrade/data/history/history_utils.py b/freqtrade/data/history/history_utils.py
new file mode 100644
index 000000000..17b510b92
--- /dev/null
+++ b/freqtrade/data/history/history_utils.py
@@ -0,0 +1,401 @@
+import logging
+import operator
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Dict, List, Optional, Tuple
+
+import arrow
+from pandas import DataFrame
+
+from freqtrade.configuration import TimeRange
+from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS
+from freqtrade.data.converter import (clean_ohlcv_dataframe, ohlcv_to_dataframe,
+                                      trades_remove_duplicates, trades_to_ohlcv)
+from freqtrade.data.history.idatahandler import IDataHandler, get_datahandler
+from freqtrade.exceptions import OperationalException
+from freqtrade.exchange import Exchange
+from freqtrade.misc import format_ms_time
+
+
+logger = logging.getLogger(__name__)
+
+
+def load_pair_history(pair: str,
+                      timeframe: str,
+                      datadir: Path, *,
+                      timerange: Optional[TimeRange] = None,
+                      fill_up_missing: bool = True,
+                      drop_incomplete: bool = True,
+                      startup_candles: int = 0,
+                      data_format: str = None,
+                      data_handler: IDataHandler = None,
+                      ) -> DataFrame:
+    """
+    Load cached ohlcv history for the given pair.
+
+    :param pair: Pair to load data for
+    :param timeframe: Timeframe (e.g. "5m")
+    :param datadir: Path to the data storage location.
+    :param data_format: Format of the data. Ignored if data_handler is set.
+    :param timerange: Limit data to be loaded to this timerange
+    :param fill_up_missing: Fill missing values with "No action"-candles
+    :param drop_incomplete: Drop last candle assuming it may be incomplete.
+    :param startup_candles: Additional candles to load at the start of the period
+    :param data_handler: Initialized data-handler to use.
+                         Will be initialized from data_format if not set
+    :return: DataFrame with ohlcv data, or empty DataFrame
+    """
+    data_handler = get_datahandler(datadir, data_format, data_handler)
+
+    return data_handler.ohlcv_load(pair=pair,
+                                   timeframe=timeframe,
+                                   timerange=timerange,
+                                   fill_missing=fill_up_missing,
+                                   drop_incomplete=drop_incomplete,
+                                   startup_candles=startup_candles,
+                                   )
+
+
+def load_data(datadir: Path,
+              timeframe: str,
+              pairs: List[str], *,
+              timerange: Optional[TimeRange] = None,
+              fill_up_missing: bool = True,
+              startup_candles: int = 0,
+              fail_without_data: bool = False,
+              data_format: str = 'json',
+              ) -> Dict[str, DataFrame]:
+    """
+    Load ohlcv history data for a list of pairs.
+
+    :param datadir: Path to the data storage location.
+    :param timeframe: Timeframe (e.g. "5m")
+    :param pairs: List of pairs to load
+    :param timerange: Limit data to be loaded to this timerange
+    :param fill_up_missing: Fill missing values with "No action"-candles
+    :param startup_candles: Additional candles to load at the start of the period
+    :param fail_without_data: Raise OperationalException if no data is found.
+    :param data_format: Data format which should be used. Defaults to json
+    :return: dict(<pair>:<Dataframe>)
+    """
+    result: Dict[str, DataFrame] = {}
+    if startup_candles > 0 and timerange:
+        logger.info(f'Using indicator startup period: {startup_candles} ...')
+
+    data_handler = get_datahandler(datadir, data_format)
+
+    for pair in pairs:
+        hist = load_pair_history(pair=pair, timeframe=timeframe,
+                                 datadir=datadir, timerange=timerange,
+                                 fill_up_missing=fill_up_missing,
+                                 startup_candles=startup_candles,
+                                 data_handler=data_handler
+                                 )
+        if not hist.empty:
+            result[pair] = hist
+
+    if fail_without_data and not result:
+        raise OperationalException("No data found. Terminating.")
+    return result
+
+
+def refresh_data(datadir: Path,
+                 timeframe: str,
+                 pairs: List[str],
+                 exchange: Exchange,
+                 data_format: str = None,
+                 timerange: Optional[TimeRange] = None,
+                 ) -> None:
+    """
+    Refresh ohlcv history data for a list of pairs.
+
+    :param datadir: Path to the data storage location.
+    :param timeframe: Timeframe (e.g. "5m")
+    :param pairs: List of pairs to load
+    :param exchange: Exchange object
+    :param timerange: Limit data to be loaded to this timerange
+    """
+    data_handler = get_datahandler(datadir, data_format)
+    for pair in pairs:
+        _download_pair_history(pair=pair, timeframe=timeframe,
+                               datadir=datadir, timerange=timerange,
+                               exchange=exchange, data_handler=data_handler)
+
+
+def _load_cached_data_for_updating(pair: str, timeframe: str, timerange: Optional[TimeRange],
+                                   data_handler: IDataHandler) -> Tuple[DataFrame, Optional[int]]:
+    """
+    Load cached data to download more data.
+    If timerange is passed in, checks whether data from an before the stored data will be
+    downloaded.
+    If that's the case then what's available should be completely overwritten.
+    Otherwise downloads always start at the end of the available data to avoid data gaps.
+    Note: Only used by download_pair_history().
+    """
+    start = None
+    if timerange:
+        if timerange.starttype == 'date':
+            start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
+
+    # Intentionally don't pass timerange in - since we need to load the full dataset.
+    data = data_handler.ohlcv_load(pair, timeframe=timeframe,
+                                   timerange=None, fill_missing=False,
+                                   drop_incomplete=True, warn_no_data=False)
+    if not data.empty:
+        if start and start < data.iloc[0]['date']:
+            # Earlier data than existing data requested, redownload all
+            data = DataFrame(columns=DEFAULT_DATAFRAME_COLUMNS)
+        else:
+            start = data.iloc[-1]['date']
+
+    start_ms = int(start.timestamp() * 1000) if start else None
+    return data, start_ms
+
+
+def _download_pair_history(datadir: Path,
+                           exchange: Exchange,
+                           pair: str, *,
+                           timeframe: str = '5m',
+                           timerange: Optional[TimeRange] = None,
+                           data_handler: IDataHandler = None) -> bool:
+    """
+    Download latest candles from the exchange for the pair and timeframe passed in parameters
+    The data is downloaded starting from the last correct data that
+    exists in a cache. If timerange starts earlier than the data in the cache,
+    the full data will be redownloaded
+
+    Based on @Rybolov work: https://github.com/rybolov/freqtrade-data
+
+    :param pair: pair to download
+    :param timeframe: Timeframe (e.g "5m")
+    :param timerange: range of time to download
+    :return: bool with success state
+    """
+    data_handler = get_datahandler(datadir, data_handler=data_handler)
+
+    try:
+        logger.info(
+            f'Download history data for pair: "{pair}", timeframe: {timeframe} '
+            f'and store in {datadir}.'
+        )
+
+        # data, since_ms = _load_cached_data_for_updating_old(datadir, pair, timeframe, timerange)
+        data, since_ms = _load_cached_data_for_updating(pair, timeframe, timerange,
+                                                        data_handler=data_handler)
+
+        logger.debug("Current Start: %s",
+                     f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
+        logger.debug("Current End: %s",
+                     f"{data.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
+
+        # Default since_ms to 30 days if nothing is given
+        new_data = exchange.get_historic_ohlcv(pair=pair,
+                                               timeframe=timeframe,
+                                               since_ms=since_ms if since_ms else
+                                               int(arrow.utcnow().shift(
+                                                   days=-30).float_timestamp) * 1000
+                                               )
+        # TODO: Maybe move parsing to exchange class (?)
+        new_dataframe = ohlcv_to_dataframe(new_data, timeframe, pair,
+                                           fill_missing=False, drop_incomplete=True)
+        if data.empty:
+            data = new_dataframe
+        else:
+            # Run cleaning again to ensure there were no duplicate candles
+            # Especially between existing and new data.
+            data = clean_ohlcv_dataframe(data.append(new_dataframe), timeframe, pair,
+                                         fill_missing=False, drop_incomplete=False)
+
+        logger.debug("New  Start: %s",
+                     f"{data.iloc[0]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
+        logger.debug("New End: %s",
+                     f"{data.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}" if not data.empty else 'None')
+
+        data_handler.ohlcv_store(pair, timeframe, data=data)
+        return True
+
+    except Exception as e:
+        logger.error(
+            f'Failed to download history data for pair: "{pair}", timeframe: {timeframe}. '
+            f'Error: {e}'
+        )
+        return False
+
+
+def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes: List[str],
+                                datadir: Path, timerange: Optional[TimeRange] = None,
+                                erase: bool = False, data_format: str = None) -> List[str]:
+    """
+    Refresh stored ohlcv data for backtesting and hyperopt operations.
+    Used by freqtrade download-data subcommand.
+    :return: List of pairs that are not available.
+    """
+    pairs_not_available = []
+    data_handler = get_datahandler(datadir, data_format)
+    for pair in pairs:
+        if pair not in exchange.markets:
+            pairs_not_available.append(pair)
+            logger.info(f"Skipping pair {pair}...")
+            continue
+        for timeframe in timeframes:
+
+            if erase:
+                if data_handler.ohlcv_purge(pair, timeframe):
+                    logger.info(
+                        f'Deleting existing data for pair {pair}, interval {timeframe}.')
+
+            logger.info(f'Downloading pair {pair}, interval {timeframe}.')
+            _download_pair_history(datadir=datadir, exchange=exchange,
+                                   pair=pair, timeframe=str(timeframe),
+                                   timerange=timerange, data_handler=data_handler)
+    return pairs_not_available
+
+
+def _download_trades_history(exchange: Exchange,
+                             pair: str, *,
+                             timerange: Optional[TimeRange] = None,
+                             data_handler: IDataHandler
+                             ) -> bool:
+    """
+    Download trade history from the exchange.
+    Appends to previously downloaded trades data.
+    """
+    try:
+
+        since = timerange.startts * 1000 if \
+            (timerange and timerange.starttype == 'date') else int(arrow.utcnow().shift(
+                days=-30).float_timestamp) * 1000
+
+        trades = data_handler.trades_load(pair)
+
+        # TradesList columns are defined in constants.DEFAULT_TRADES_COLUMNS
+        # DEFAULT_TRADES_COLUMNS: 0 -> timestamp
+        # DEFAULT_TRADES_COLUMNS: 1 -> id
+
+        if trades and since < trades[0][0]:
+            # since is before the first trade
+            logger.info(f"Start earlier than available data. Redownloading trades for {pair}...")
+            trades = []
+
+        from_id = trades[-1][1] if trades else None
+        if trades and since < trades[-1][0]:
+            # Reset since to the last available point
+            # - 5 seconds (to ensure we're getting all trades)
+            since = trades[-1][0] - (5 * 1000)
+            logger.info(f"Using last trade date -5s - Downloading trades for {pair} "
+                        f"since: {format_ms_time(since)}.")
+
+        logger.debug(f"Current Start: {format_ms_time(trades[0][0]) if trades else 'None'}")
+        logger.debug(f"Current End: {format_ms_time(trades[-1][0]) if trades else 'None'}")
+        logger.info(f"Current Amount of trades: {len(trades)}")
+
+        # Default since_ms to 30 days if nothing is given
+        new_trades = exchange.get_historic_trades(pair=pair,
+                                                  since=since,
+                                                  from_id=from_id,
+                                                  )
+        trades.extend(new_trades[1])
+        # Remove duplicates to make sure we're not storing data we don't need
+        trades = trades_remove_duplicates(trades)
+        data_handler.trades_store(pair, data=trades)
+
+        logger.debug(f"New Start: {format_ms_time(trades[0][0])}")
+        logger.debug(f"New End: {format_ms_time(trades[-1][0])}")
+        logger.info(f"New Amount of trades: {len(trades)}")
+        return True
+
+    except Exception as e:
+        logger.error(
+            f'Failed to download historic trades for pair: "{pair}". '
+            f'Error: {e}'
+        )
+        return False
+
+
+def refresh_backtest_trades_data(exchange: Exchange, pairs: List[str], datadir: Path,
+                                 timerange: TimeRange, erase: bool = False,
+                                 data_format: str = 'jsongz') -> List[str]:
+    """
+    Refresh stored trades data for backtesting and hyperopt operations.
+    Used by freqtrade download-data subcommand.
+    :return: List of pairs that are not available.
+    """
+    pairs_not_available = []
+    data_handler = get_datahandler(datadir, data_format=data_format)
+    for pair in pairs:
+        if pair not in exchange.markets:
+            pairs_not_available.append(pair)
+            logger.info(f"Skipping pair {pair}...")
+            continue
+
+        if erase:
+            if data_handler.trades_purge(pair):
+                logger.info(f'Deleting existing data for pair {pair}.')
+
+        logger.info(f'Downloading trades for pair {pair}.')
+        _download_trades_history(exchange=exchange,
+                                 pair=pair,
+                                 timerange=timerange,
+                                 data_handler=data_handler)
+    return pairs_not_available
+
+
+def convert_trades_to_ohlcv(pairs: List[str], timeframes: List[str],
+                            datadir: Path, timerange: TimeRange, erase: bool = False,
+                            data_format_ohlcv: str = 'json',
+                            data_format_trades: str = 'jsongz') -> None:
+    """
+    Convert stored trades data to ohlcv data
+    """
+    data_handler_trades = get_datahandler(datadir, data_format=data_format_trades)
+    data_handler_ohlcv = get_datahandler(datadir, data_format=data_format_ohlcv)
+
+    for pair in pairs:
+        trades = data_handler_trades.trades_load(pair)
+        for timeframe in timeframes:
+            if erase:
+                if data_handler_ohlcv.ohlcv_purge(pair, timeframe):
+                    logger.info(f'Deleting existing data for pair {pair}, interval {timeframe}.')
+            try:
+                ohlcv = trades_to_ohlcv(trades, timeframe)
+                # Store ohlcv
+                data_handler_ohlcv.ohlcv_store(pair, timeframe, data=ohlcv)
+            except ValueError:
+                logger.exception(f'Could not convert {pair} to OHLCV.')
+
+
+def get_timerange(data: Dict[str, DataFrame]) -> Tuple[arrow.Arrow, arrow.Arrow]:
+    """
+    Get the maximum common timerange for the given backtest data.
+
+    :param data: dictionary with preprocessed backtesting data
+    :return: tuple containing min_date, max_date
+    """
+    timeranges = [
+        (arrow.get(frame['date'].min()), arrow.get(frame['date'].max()))
+        for frame in data.values()
+    ]
+    return (min(timeranges, key=operator.itemgetter(0))[0],
+            max(timeranges, key=operator.itemgetter(1))[1])
+
+
+def validate_backtest_data(data: DataFrame, pair: str, min_date: datetime,
+                           max_date: datetime, timeframe_min: int) -> bool:
+    """
+    Validates preprocessed backtesting data for missing values and shows warnings about it that.
+
+    :param data: preprocessed backtesting data (as DataFrame)
+    :param pair: pair used for log output.
+    :param min_date: start-date of the data
+    :param max_date: end-date of the data
+    :param timeframe_min: Timeframe in minutes
+    """
+    # total difference in minutes / timeframe-minutes
+    expected_frames = int((max_date - min_date).total_seconds() // 60 // timeframe_min)
+    found_missing = False
+    dflen = len(data)
+    if dflen < expected_frames:
+        found_missing = True
+        logger.warning("%s has missing frames: expected %s, got %s, that's %s missing values",
+                       pair, expected_frames, dflen, expected_frames - dflen)
+    return found_missing
diff --git a/freqtrade/data/history/idatahandler.py b/freqtrade/data/history/idatahandler.py
new file mode 100644
index 000000000..070d9039d
--- /dev/null
+++ b/freqtrade/data/history/idatahandler.py
@@ -0,0 +1,255 @@
+"""
+Abstract datahandler interface.
+It's subclasses handle and storing data from disk.
+
+"""
+import logging
+from abc import ABC, abstractclassmethod, abstractmethod
+from copy import deepcopy
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import List, Optional, Type
+
+from pandas import DataFrame
+
+from freqtrade.configuration import TimeRange
+from freqtrade.constants import ListPairsWithTimeframes, TradeList
+from freqtrade.data.converter import clean_ohlcv_dataframe, trades_remove_duplicates, trim_dataframe
+from freqtrade.exchange import timeframe_to_seconds
+
+
+logger = logging.getLogger(__name__)
+
+
+class IDataHandler(ABC):
+
+    def __init__(self, datadir: Path) -> None:
+        self._datadir = datadir
+
+    @abstractclassmethod
+    def ohlcv_get_available_data(cls, datadir: Path) -> ListPairsWithTimeframes:
+        """
+        Returns a list of all pairs with ohlcv data available in this datadir
+        :param datadir: Directory to search for ohlcv files
+        :return: List of Tuples of (pair, timeframe)
+        """
+
+    @abstractclassmethod
+    def ohlcv_get_pairs(cls, datadir: Path, timeframe: str) -> List[str]:
+        """
+        Returns a list of all pairs with ohlcv data available in this datadir
+        for the specified timeframe
+        :param datadir: Directory to search for ohlcv files
+        :param timeframe: Timeframe to search pairs for
+        :return: List of Pairs
+        """
+
+    @abstractmethod
+    def ohlcv_store(self, pair: str, timeframe: str, data: DataFrame) -> None:
+        """
+        Store ohlcv data.
+        :param pair: Pair - used to generate filename
+        :timeframe: Timeframe - used to generate filename
+        :data: Dataframe containing OHLCV data
+        :return: None
+        """
+
+    @abstractmethod
+    def _ohlcv_load(self, pair: str, timeframe: str,
+                    timerange: Optional[TimeRange] = None,
+                    ) -> DataFrame:
+        """
+        Internal method used to load data for one pair from disk.
+        Implements the loading and conversion to a Pandas dataframe.
+        Timerange trimming and dataframe validation happens outside of this method.
+        :param pair: Pair to load data
+        :param timeframe: Timeframe (e.g. "5m")
+        :param timerange: Limit data to be loaded to this timerange.
+                        Optionally implemented by subclasses to avoid loading
+                        all data where possible.
+        :return: DataFrame with ohlcv data, or empty DataFrame
+        """
+
+    @abstractmethod
+    def ohlcv_purge(self, pair: str, timeframe: str) -> bool:
+        """
+        Remove data for this pair
+        :param pair: Delete data for this pair.
+        :param timeframe: Timeframe (e.g. "5m")
+        :return: True when deleted, false if file did not exist.
+        """
+
+    @abstractmethod
+    def ohlcv_append(self, pair: str, timeframe: str, data: DataFrame) -> None:
+        """
+        Append data to existing data structures
+        :param pair: Pair
+        :param timeframe: Timeframe this ohlcv data is for
+        :param data: Data to append.
+        """
+
+    @abstractclassmethod
+    def trades_get_pairs(cls, datadir: Path) -> List[str]:
+        """
+        Returns a list of all pairs for which trade data is available in this
+        :param datadir: Directory to search for ohlcv files
+        :return: List of Pairs
+        """
+
+    @abstractmethod
+    def trades_store(self, pair: str, data: TradeList) -> None:
+        """
+        Store trades data (list of Dicts) to file
+        :param pair: Pair - used for filename
+        :param data: List of Lists containing trade data,
+                     column sequence as in DEFAULT_TRADES_COLUMNS
+        """
+
+    @abstractmethod
+    def trades_append(self, pair: str, data: TradeList):
+        """
+        Append data to existing files
+        :param pair: Pair - used for filename
+        :param data: List of Lists containing trade data,
+                     column sequence as in DEFAULT_TRADES_COLUMNS
+        """
+
+    @abstractmethod
+    def _trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> TradeList:
+        """
+        Load a pair from file, either .json.gz or .json
+        :param pair: Load trades for this pair
+        :param timerange: Timerange to load trades for - currently not implemented
+        :return: List of trades
+        """
+
+    @abstractmethod
+    def trades_purge(self, pair: str) -> bool:
+        """
+        Remove data for this pair
+        :param pair: Delete data for this pair.
+        :return: True when deleted, false if file did not exist.
+        """
+
+    def trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> TradeList:
+        """
+        Load a pair from file, either .json.gz or .json
+        Removes duplicates in the process.
+        :param pair: Load trades for this pair
+        :param timerange: Timerange to load trades for - currently not implemented
+        :return: List of trades
+        """
+        return trades_remove_duplicates(self._trades_load(pair, timerange=timerange))
+
+    def ohlcv_load(self, pair, timeframe: str,
+                   timerange: Optional[TimeRange] = None,
+                   fill_missing: bool = True,
+                   drop_incomplete: bool = True,
+                   startup_candles: int = 0,
+                   warn_no_data: bool = True
+                   ) -> DataFrame:
+        """
+        Load cached candle (OHLCV) data for the given pair.
+
+        :param pair: Pair to load data for
+        :param timeframe: Timeframe (e.g. "5m")
+        :param timerange: Limit data to be loaded to this timerange
+        :param fill_missing: Fill missing values with "No action"-candles
+        :param drop_incomplete: Drop last candle assuming it may be incomplete.
+        :param startup_candles: Additional candles to load at the start of the period
+        :param warn_no_data: Log a warning message when no data is found
+        :return: DataFrame with ohlcv data, or empty DataFrame
+        """
+        # Fix startup period
+        timerange_startup = deepcopy(timerange)
+        if startup_candles > 0 and timerange_startup:
+            timerange_startup.subtract_start(timeframe_to_seconds(timeframe) * startup_candles)
+
+        pairdf = self._ohlcv_load(pair, timeframe,
+                                  timerange=timerange_startup)
+        if self._check_empty_df(pairdf, pair, timeframe, warn_no_data):
+            return pairdf
+        else:
+            enddate = pairdf.iloc[-1]['date']
+
+            if timerange_startup:
+                self._validate_pairdata(pair, pairdf, timerange_startup)
+                pairdf = trim_dataframe(pairdf, timerange_startup)
+                if self._check_empty_df(pairdf, pair, timeframe, warn_no_data):
+                    return pairdf
+
+            # incomplete candles should only be dropped if we didn't trim the end beforehand.
+            pairdf = clean_ohlcv_dataframe(pairdf, timeframe,
+                                           pair=pair,
+                                           fill_missing=fill_missing,
+                                           drop_incomplete=(drop_incomplete and
+                                                            enddate == pairdf.iloc[-1]['date']))
+            self._check_empty_df(pairdf, pair, timeframe, warn_no_data)
+            return pairdf
+
+    def _check_empty_df(self, pairdf: DataFrame, pair: str, timeframe: str, warn_no_data: bool):
+        """
+        Warn on empty dataframe
+        """
+        if pairdf.empty:
+            if warn_no_data:
+                logger.warning(
+                    f'No history data for pair: "{pair}", timeframe: {timeframe}. '
+                    'Use `freqtrade download-data` to download the data'
+                )
+            return True
+        return False
+
+    def _validate_pairdata(self, pair, pairdata: DataFrame, timerange: TimeRange):
+        """
+        Validates pairdata for missing data at start end end and logs warnings.
+        :param pairdata: Dataframe to validate
+        :param timerange: Timerange specified for start and end dates
+        """
+
+        if timerange.starttype == 'date':
+            start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
+            if pairdata.iloc[0]['date'] > start:
+                logger.warning(f"Missing data at start for pair {pair}, "
+                               f"data starts at {pairdata.iloc[0]['date']:%Y-%m-%d %H:%M:%S}")
+        if timerange.stoptype == 'date':
+            stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
+            if pairdata.iloc[-1]['date'] < stop:
+                logger.warning(f"Missing data at end for pair {pair}, "
+                               f"data ends at {pairdata.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}")
+
+
+def get_datahandlerclass(datatype: str) -> Type[IDataHandler]:
+    """
+    Get datahandler class.
+    Could be done using Resolvers, but since this may be called often and resolvers
+    are rather expensive, doing this directly should improve performance.
+    :param datatype: datatype to use.
+    :return: Datahandler class
+    """
+
+    if datatype == 'json':
+        from .jsondatahandler import JsonDataHandler
+        return JsonDataHandler
+    elif datatype == 'jsongz':
+        from .jsondatahandler import JsonGzDataHandler
+        return JsonGzDataHandler
+    elif datatype == 'hdf5':
+        from .hdf5datahandler import HDF5DataHandler
+        return HDF5DataHandler
+    else:
+        raise ValueError(f"No datahandler for datatype {datatype} available.")
+
+
+def get_datahandler(datadir: Path, data_format: str = None,
+                    data_handler: IDataHandler = None) -> IDataHandler:
+    """
+    :param datadir: Folder to save data
+    :data_format: dataformat to use
+    :data_handler: returns this datahandler if it exists or initializes a new one
+    """
+
+    if not data_handler:
+        HandlerClass = get_datahandlerclass(data_format or 'json')
+        data_handler = HandlerClass(datadir)
+    return data_handler
diff --git a/freqtrade/data/history/jsondatahandler.py b/freqtrade/data/history/jsondatahandler.py
new file mode 100644
index 000000000..9122170d5
--- /dev/null
+++ b/freqtrade/data/history/jsondatahandler.py
@@ -0,0 +1,204 @@
+import logging
+import re
+from pathlib import Path
+from typing import List, Optional
+
+import numpy as np
+from pandas import DataFrame, read_json, to_datetime
+
+from freqtrade import misc
+from freqtrade.configuration import TimeRange
+from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, ListPairsWithTimeframes, TradeList
+from freqtrade.data.converter import trades_dict_to_list
+
+from .idatahandler import IDataHandler
+
+
+logger = logging.getLogger(__name__)
+
+
+class JsonDataHandler(IDataHandler):
+
+    _use_zip = False
+    _columns = DEFAULT_DATAFRAME_COLUMNS
+
+    @classmethod
+    def ohlcv_get_available_data(cls, datadir: Path) -> ListPairsWithTimeframes:
+        """
+        Returns a list of all pairs with ohlcv data available in this datadir
+        :param datadir: Directory to search for ohlcv files
+        :return: List of Tuples of (pair, timeframe)
+        """
+        _tmp = [re.search(r'^([a-zA-Z_]+)\-(\d+\S+)(?=.json)', p.name)
+                for p in datadir.glob(f"*.{cls._get_file_extension()}")]
+        return [(match[1].replace('_', '/'), match[2]) for match in _tmp
+                if match and len(match.groups()) > 1]
+
+    @classmethod
+    def ohlcv_get_pairs(cls, datadir: Path, timeframe: str) -> List[str]:
+        """
+        Returns a list of all pairs with ohlcv data available in this datadir
+        for the specified timeframe
+        :param datadir: Directory to search for ohlcv files
+        :param timeframe: Timeframe to search pairs for
+        :return: List of Pairs
+        """
+
+        _tmp = [re.search(r'^(\S+)(?=\-' + timeframe + '.json)', p.name)
+                for p in datadir.glob(f"*{timeframe}.{cls._get_file_extension()}")]
+        # Check if regex found something and only return these results
+        return [match[0].replace('_', '/') for match in _tmp if match]
+
+    def ohlcv_store(self, pair: str, timeframe: str, data: DataFrame) -> None:
+        """
+        Store data in json format "values".
+            format looks as follows:
+            [[<date>,<open>,<high>,<low>,<close>]]
+        :param pair: Pair - used to generate filename
+        :timeframe: Timeframe - used to generate filename
+        :data: Dataframe containing OHLCV data
+        :return: None
+        """
+        filename = self._pair_data_filename(self._datadir, pair, timeframe)
+        _data = data.copy()
+        # Convert date to int
+        _data['date'] = _data['date'].astype(np.int64) // 1000 // 1000
+
+        # Reset index, select only appropriate columns and save as json
+        _data.reset_index(drop=True).loc[:, self._columns].to_json(
+            filename, orient="values",
+            compression='gzip' if self._use_zip else None)
+
+    def _ohlcv_load(self, pair: str, timeframe: str,
+                    timerange: Optional[TimeRange] = None,
+                    ) -> DataFrame:
+        """
+        Internal method used to load data for one pair from disk.
+        Implements the loading and conversion to a Pandas dataframe.
+        Timerange trimming and dataframe validation happens outside of this method.
+        :param pair: Pair to load data
+        :param timeframe: Timeframe (e.g. "5m")
+        :param timerange: Limit data to be loaded to this timerange.
+                        Optionally implemented by subclasses to avoid loading
+                        all data where possible.
+        :return: DataFrame with ohlcv data, or empty DataFrame
+        """
+        filename = self._pair_data_filename(self._datadir, pair, timeframe)
+        if not filename.exists():
+            return DataFrame(columns=self._columns)
+        pairdata = read_json(filename, orient='values')
+        pairdata.columns = self._columns
+        pairdata = pairdata.astype(dtype={'open': 'float', 'high': 'float',
+                                          'low': 'float', 'close': 'float', 'volume': 'float'})
+        pairdata['date'] = to_datetime(pairdata['date'],
+                                       unit='ms',
+                                       utc=True,
+                                       infer_datetime_format=True)
+        return pairdata
+
+    def ohlcv_purge(self, pair: str, timeframe: str) -> bool:
+        """
+        Remove data for this pair
+        :param pair: Delete data for this pair.
+        :param timeframe: Timeframe (e.g. "5m")
+        :return: True when deleted, false if file did not exist.
+        """
+        filename = self._pair_data_filename(self._datadir, pair, timeframe)
+        if filename.exists():
+            filename.unlink()
+            return True
+        return False
+
+    def ohlcv_append(self, pair: str, timeframe: str, data: DataFrame) -> None:
+        """
+        Append data to existing data structures
+        :param pair: Pair
+        :param timeframe: Timeframe this ohlcv data is for
+        :param data: Data to append.
+        """
+        raise NotImplementedError()
+
+    @classmethod
+    def trades_get_pairs(cls, datadir: Path) -> List[str]:
+        """
+        Returns a list of all pairs for which trade data is available in this
+        :param datadir: Directory to search for ohlcv files
+        :return: List of Pairs
+        """
+        _tmp = [re.search(r'^(\S+)(?=\-trades.json)', p.name)
+                for p in datadir.glob(f"*trades.{cls._get_file_extension()}")]
+        # Check if regex found something and only return these results to avoid exceptions.
+        return [match[0].replace('_', '/') for match in _tmp if match]
+
+    def trades_store(self, pair: str, data: TradeList) -> None:
+        """
+        Store trades data (list of Dicts) to file
+        :param pair: Pair - used for filename
+        :param data: List of Lists containing trade data,
+                     column sequence as in DEFAULT_TRADES_COLUMNS
+        """
+        filename = self._pair_trades_filename(self._datadir, pair)
+        misc.file_dump_json(filename, data, is_zip=self._use_zip)
+
+    def trades_append(self, pair: str, data: TradeList):
+        """
+        Append data to existing files
+        :param pair: Pair - used for filename
+        :param data: List of Lists containing trade data,
+                     column sequence as in DEFAULT_TRADES_COLUMNS
+        """
+        raise NotImplementedError()
+
+    def _trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> TradeList:
+        """
+        Load a pair from file, either .json.gz or .json
+        # TODO: respect timerange ...
+        :param pair: Load trades for this pair
+        :param timerange: Timerange to load trades for - currently not implemented
+        :return: List of trades
+        """
+        filename = self._pair_trades_filename(self._datadir, pair)
+        tradesdata = misc.file_load_json(filename)
+
+        if not tradesdata:
+            return []
+
+        if isinstance(tradesdata[0], dict):
+            # Convert trades dict to list
+            logger.info("Old trades format detected - converting")
+            tradesdata = trades_dict_to_list(tradesdata)
+            pass
+        return tradesdata
+
+    def trades_purge(self, pair: str) -> bool:
+        """
+        Remove data for this pair
+        :param pair: Delete data for this pair.
+        :return: True when deleted, false if file did not exist.
+        """
+        filename = self._pair_trades_filename(self._datadir, pair)
+        if filename.exists():
+            filename.unlink()
+            return True
+        return False
+
+    @classmethod
+    def _pair_data_filename(cls, datadir: Path, pair: str, timeframe: str) -> Path:
+        pair_s = misc.pair_to_filename(pair)
+        filename = datadir.joinpath(f'{pair_s}-{timeframe}.{cls._get_file_extension()}')
+        return filename
+
+    @classmethod
+    def _get_file_extension(cls):
+        return "json.gz" if cls._use_zip else "json"
+
+    @classmethod
+    def _pair_trades_filename(cls, datadir: Path, pair: str) -> Path:
+        pair_s = misc.pair_to_filename(pair)
+        filename = datadir.joinpath(f'{pair_s}-trades.{cls._get_file_extension()}')
+        return filename
+
+
+class JsonGzDataHandler(JsonDataHandler):
+
+    _use_zip = True
diff --git a/freqtrade/edge/__init__.py b/freqtrade/edge/__init__.py
index 7085663d6..d275a80e3 100644
--- a/freqtrade/edge/__init__.py
+++ b/freqtrade/edge/__init__.py
@@ -1,453 +1 @@
-# pragma pylint: disable=W0603
-""" Edge positioning package """
-import logging
-from pathlib import Path
-from typing import Any, Dict, NamedTuple
-
-import arrow
-import numpy as np
-import utils_find_1st as utf1st
-from pandas import DataFrame
-
-from freqtrade import constants, OperationalException
-from freqtrade.configuration import Arguments, TimeRange
-from freqtrade.data import history
-from freqtrade.strategy.interface import SellType
-
-
-logger = logging.getLogger(__name__)
-
-
-class PairInfo(NamedTuple):
-    stoploss: float
-    winrate: float
-    risk_reward_ratio: float
-    required_risk_reward: float
-    expectancy: float
-    nb_trades: int
-    avg_trade_duration: float
-
-
-class Edge():
-    """
-    Calculates Win Rate, Risk Reward Ratio, Expectancy
-    against historical data for a give set of markets and a strategy
-    it then adjusts stoploss and position size accordingly
-    and force it into the strategy
-    Author: https://github.com/mishaker
-    """
-
-    config: Dict = {}
-    _cached_pairs: Dict[str, Any] = {}  # Keeps a list of pairs
-
-    def __init__(self, config: Dict[str, Any], exchange, strategy) -> None:
-
-        self.config = config
-        self.exchange = exchange
-        self.strategy = strategy
-
-        self.edge_config = self.config.get('edge', {})
-        self._cached_pairs: Dict[str, Any] = {}  # Keeps a list of pairs
-        self._final_pairs: list = []
-
-        # checking max_open_trades. it should be -1 as with Edge
-        # the number of trades is determined by position size
-        if self.config['max_open_trades'] != float('inf'):
-            logger.critical('max_open_trades should be -1 in config !')
-
-        if self.config['stake_amount'] != constants.UNLIMITED_STAKE_AMOUNT:
-            raise OperationalException('Edge works only with unlimited stake amount')
-
-        self._capital_percentage: float = self.edge_config.get('capital_available_percentage')
-        self._allowed_risk: float = self.edge_config.get('allowed_risk')
-        self._since_number_of_days: int = self.edge_config.get('calculate_since_number_of_days', 14)
-        self._last_updated: int = 0  # Timestamp of pairs last updated time
-        self._refresh_pairs = True
-
-        self._stoploss_range_min = float(self.edge_config.get('stoploss_range_min', -0.01))
-        self._stoploss_range_max = float(self.edge_config.get('stoploss_range_max', -0.05))
-        self._stoploss_range_step = float(self.edge_config.get('stoploss_range_step', -0.001))
-
-        # calculating stoploss range
-        self._stoploss_range = np.arange(
-            self._stoploss_range_min,
-            self._stoploss_range_max,
-            self._stoploss_range_step
-        )
-
-        self._timerange: TimeRange = Arguments.parse_timerange("%s-" % arrow.now().shift(
-            days=-1 * self._since_number_of_days).format('YYYYMMDD'))
-
-        self.fee = self.exchange.get_fee()
-
-    def calculate(self) -> bool:
-        pairs = self.config['exchange']['pair_whitelist']
-        heartbeat = self.edge_config.get('process_throttle_secs')
-
-        if (self._last_updated > 0) and (
-                self._last_updated + heartbeat > arrow.utcnow().timestamp):
-            return False
-
-        data: Dict[str, Any] = {}
-        logger.info('Using stake_currency: %s ...', self.config['stake_currency'])
-        logger.info('Using local backtesting data (using whitelist in given config) ...')
-
-        data = history.load_data(
-            datadir=Path(self.config['datadir']) if self.config.get('datadir') else None,
-            pairs=pairs,
-            ticker_interval=self.strategy.ticker_interval,
-            refresh_pairs=self._refresh_pairs,
-            exchange=self.exchange,
-            timerange=self._timerange
-        )
-
-        if not data:
-            # Reinitializing cached pairs
-            self._cached_pairs = {}
-            logger.critical("No data found. Edge is stopped ...")
-            return False
-
-        preprocessed = self.strategy.tickerdata_to_dataframe(data)
-
-        # Print timeframe
-        min_date, max_date = history.get_timeframe(preprocessed)
-        logger.info(
-            'Measuring data from %s up to %s (%s days) ...',
-            min_date.isoformat(),
-            max_date.isoformat(),
-            (max_date - min_date).days
-        )
-        headers = ['date', 'buy', 'open', 'close', 'sell', 'high', 'low']
-
-        trades: list = []
-        for pair, pair_data in preprocessed.items():
-            # Sorting dataframe by date and reset index
-            pair_data = pair_data.sort_values(by=['date'])
-            pair_data = pair_data.reset_index(drop=True)
-
-            ticker_data = self.strategy.advise_sell(
-                self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
-
-            trades += self._find_trades_for_stoploss_range(ticker_data, pair, self._stoploss_range)
-
-        # If no trade found then exit
-        if len(trades) == 0:
-            logger.info("No trades found.")
-            return False
-
-        # Fill missing, calculable columns, profit, duration , abs etc.
-        trades_df = self._fill_calculable_fields(DataFrame(trades))
-        self._cached_pairs = self._process_expectancy(trades_df)
-        self._last_updated = arrow.utcnow().timestamp
-
-        return True
-
-    def stake_amount(self, pair: str, free_capital: float,
-                     total_capital: float, capital_in_trade: float) -> float:
-        stoploss = self.stoploss(pair)
-        available_capital = (total_capital + capital_in_trade) * self._capital_percentage
-        allowed_capital_at_risk = available_capital * self._allowed_risk
-        max_position_size = abs(allowed_capital_at_risk / stoploss)
-        position_size = min(max_position_size, free_capital)
-        if pair in self._cached_pairs:
-            logger.info(
-                'winrate: %s, expectancy: %s, position size: %s, pair: %s,'
-                ' capital in trade: %s, free capital: %s, total capital: %s,'
-                ' stoploss: %s, available capital: %s.',
-                self._cached_pairs[pair].winrate,
-                self._cached_pairs[pair].expectancy,
-                position_size, pair,
-                capital_in_trade, free_capital, total_capital,
-                stoploss, available_capital
-            )
-        return round(position_size, 15)
-
-    def stoploss(self, pair: str) -> float:
-        if pair in self._cached_pairs:
-            return self._cached_pairs[pair].stoploss
-        else:
-            logger.warning('tried to access stoploss of a non-existing pair, '
-                           'strategy stoploss is returned instead.')
-            return self.strategy.stoploss
-
-    def adjust(self, pairs) -> list:
-        """
-        Filters out and sorts "pairs" according to Edge calculated pairs
-        """
-        final = []
-        for pair, info in self._cached_pairs.items():
-            if info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and \
-                info.winrate > float(self.edge_config.get('minimum_winrate', 0.60)) and \
-                    pair in pairs:
-                final.append(pair)
-
-        if self._final_pairs != final:
-            self._final_pairs = final
-            if self._final_pairs:
-                logger.info(
-                    'Minimum expectancy and minimum winrate are met only for %s,'
-                    ' so other pairs are filtered out.',
-                    self._final_pairs
-                    )
-            else:
-                logger.info(
-                    'Edge removed all pairs as no pair with minimum expectancy '
-                    'and minimum winrate was found !'
-                    )
-
-        return self._final_pairs
-
-    def accepted_pairs(self) -> list:
-        """
-        return a list of accepted pairs along with their winrate, expectancy and stoploss
-        """
-        final = []
-        for pair, info in self._cached_pairs.items():
-            if info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and \
-                 info.winrate > float(self.edge_config.get('minimum_winrate', 0.60)):
-                final.append({
-                    'Pair': pair,
-                    'Winrate': info.winrate,
-                    'Expectancy': info.expectancy,
-                    'Stoploss': info.stoploss,
-                })
-        return final
-
-    def _fill_calculable_fields(self, result: DataFrame) -> DataFrame:
-        """
-        The result frame contains a number of columns that are calculable
-        from other columns. These are left blank till all rows are added,
-        to be populated in single vector calls.
-
-        Columns to be populated are:
-        - Profit
-        - trade duration
-        - profit abs
-        :param result Dataframe
-        :return: result Dataframe
-        """
-
-        # stake and fees
-        # stake = 0.015
-        # 0.05% is 0.0005
-        # fee = 0.001
-
-        # we set stake amount to an arbitrary amount.
-        # as it doesn't change the calculation.
-        # all returned values are relative. they are percentages.
-        stake = 0.015
-        fee = self.fee
-        open_fee = fee / 2
-        close_fee = fee / 2
-
-        result['trade_duration'] = result['close_time'] - result['open_time']
-
-        result['trade_duration'] = result['trade_duration'].map(
-            lambda x: int(x.total_seconds() / 60))
-
-        # Spends, Takes, Profit, Absolute Profit
-
-        # Buy Price
-        result['buy_vol'] = stake / result['open_rate']  # How many target are we buying
-        result['buy_fee'] = stake * open_fee
-        result['buy_spend'] = stake + result['buy_fee']  # How much we're spending
-
-        # Sell price
-        result['sell_sum'] = result['buy_vol'] * result['close_rate']
-        result['sell_fee'] = result['sell_sum'] * close_fee
-        result['sell_take'] = result['sell_sum'] - result['sell_fee']
-
-        # profit_percent
-        result['profit_percent'] = (result['sell_take'] - result['buy_spend']) / result['buy_spend']
-
-        # Absolute profit
-        result['profit_abs'] = result['sell_take'] - result['buy_spend']
-
-        return result
-
-    def _process_expectancy(self, results: DataFrame) -> Dict[str, Any]:
-        """
-        This calculates WinRate, Required Risk Reward, Risk Reward and Expectancy of all pairs
-        The calulation will be done per pair and per strategy.
-        """
-        # Removing pairs having less than min_trades_number
-        min_trades_number = self.edge_config.get('min_trade_number', 10)
-        results = results.groupby(['pair', 'stoploss']).filter(lambda x: len(x) > min_trades_number)
-        ###################################
-
-        # Removing outliers (Only Pumps) from the dataset
-        # The method to detect outliers is to calculate standard deviation
-        # Then every value more than (standard deviation + 2*average) is out (pump)
-        #
-        # Removing Pumps
-        if self.edge_config.get('remove_pumps', False):
-            results = results.groupby(['pair', 'stoploss']).apply(
-                lambda x: x[x['profit_abs'] < 2 * x['profit_abs'].std() + x['profit_abs'].mean()])
-        ##########################################################################
-
-        # Removing trades having a duration more than X minutes (set in config)
-        max_trade_duration = self.edge_config.get('max_trade_duration_minute', 1440)
-        results = results[results.trade_duration < max_trade_duration]
-        #######################################################################
-
-        if results.empty:
-            return {}
-
-        groupby_aggregator = {
-            'profit_abs': [
-                ('nb_trades', 'count'),  # number of all trades
-                ('profit_sum', lambda x: x[x > 0].sum()),  # cumulative profit of all winning trades
-                ('loss_sum', lambda x: abs(x[x < 0].sum())),  # cumulative loss of all losing trades
-                ('nb_win_trades', lambda x: x[x > 0].count())  # number of winning trades
-            ],
-            'trade_duration': [('avg_trade_duration', 'mean')]
-        }
-
-        # Group by (pair and stoploss) by applying above aggregator
-        df = results.groupby(['pair', 'stoploss'])['profit_abs', 'trade_duration'].agg(
-            groupby_aggregator).reset_index(col_level=1)
-
-        # Dropping level 0 as we don't need it
-        df.columns = df.columns.droplevel(0)
-
-        # Calculating number of losing trades, average win and average loss
-        df['nb_loss_trades'] = df['nb_trades'] - df['nb_win_trades']
-        df['average_win'] = df['profit_sum'] / df['nb_win_trades']
-        df['average_loss'] = df['loss_sum'] / df['nb_loss_trades']
-
-        # Win rate = number of profitable trades / number of trades
-        df['winrate'] = df['nb_win_trades'] / df['nb_trades']
-
-        # risk_reward_ratio = average win / average loss
-        df['risk_reward_ratio'] = df['average_win'] / df['average_loss']
-
-        # required_risk_reward = (1 / winrate) - 1
-        df['required_risk_reward'] = (1 / df['winrate']) - 1
-
-        # expectancy = (risk_reward_ratio * winrate) - (lossrate)
-        df['expectancy'] = (df['risk_reward_ratio'] * df['winrate']) - (1 - df['winrate'])
-
-        # sort by expectancy and stoploss
-        df = df.sort_values(by=['expectancy', 'stoploss'], ascending=False).groupby(
-            'pair').first().sort_values(by=['expectancy'], ascending=False).reset_index()
-
-        final = {}
-        for x in df.itertuples():
-            final[x.pair] = PairInfo(
-                x.stoploss,
-                x.winrate,
-                x.risk_reward_ratio,
-                x.required_risk_reward,
-                x.expectancy,
-                x.nb_trades,
-                x.avg_trade_duration
-            )
-
-        # Returning a list of pairs in order of "expectancy"
-        return final
-
-    def _find_trades_for_stoploss_range(self, ticker_data, pair, stoploss_range):
-        buy_column = ticker_data['buy'].values
-        sell_column = ticker_data['sell'].values
-        date_column = ticker_data['date'].values
-        ohlc_columns = ticker_data[['open', 'high', 'low', 'close']].values
-
-        result: list = []
-        for stoploss in stoploss_range:
-            result += self._detect_next_stop_or_sell_point(
-                buy_column, sell_column, date_column, ohlc_columns, round(stoploss, 6), pair
-            )
-
-        return result
-
-    def _detect_next_stop_or_sell_point(self, buy_column, sell_column, date_column,
-                                        ohlc_columns, stoploss, pair):
-        """
-        Iterate through ohlc_columns in order to find the next trade
-        Next trade opens from the first buy signal noticed to
-        The sell or stoploss signal after it.
-        It then cuts OHLC, buy_column, sell_column and date_column.
-        Cut from (the exit trade index) + 1.
-
-        Author: https://github.com/mishaker
-        """
-
-        result: list = []
-        start_point = 0
-
-        while True:
-            open_trade_index = utf1st.find_1st(buy_column, 1, utf1st.cmp_equal)
-
-            # Return empty if we don't find trade entry (i.e. buy==1) or
-            # we find a buy but at the end of array
-            if open_trade_index == -1 or open_trade_index == len(buy_column) - 1:
-                break
-            else:
-                # When a buy signal is seen,
-                # trade opens in reality on the next candle
-                open_trade_index += 1
-
-            stop_price_percentage = stoploss + 1
-            open_price = ohlc_columns[open_trade_index, 0]
-            stop_price = (open_price * stop_price_percentage)
-
-            # Searching for the index where stoploss is hit
-            stop_index = utf1st.find_1st(
-                ohlc_columns[open_trade_index:, 2], stop_price, utf1st.cmp_smaller)
-
-            # If we don't find it then we assume stop_index will be far in future (infinite number)
-            if stop_index == -1:
-                stop_index = float('inf')
-
-            # Searching for the index where sell is hit
-            sell_index = utf1st.find_1st(sell_column[open_trade_index:], 1, utf1st.cmp_equal)
-
-            # If we don't find it then we assume sell_index will be far in future (infinite number)
-            if sell_index == -1:
-                sell_index = float('inf')
-
-            # Check if we don't find any stop or sell point (in that case trade remains open)
-            # It is not interesting for Edge to consider it so we simply ignore the trade
-            # And stop iterating there is no more entry
-            if stop_index == sell_index == float('inf'):
-                break
-
-            if stop_index <= sell_index:
-                exit_index = open_trade_index + stop_index
-                exit_type = SellType.STOP_LOSS
-                exit_price = stop_price
-            elif stop_index > sell_index:
-                # If exit is SELL then we exit at the next candle
-                exit_index = open_trade_index + sell_index + 1
-
-                # Check if we have the next candle
-                if len(ohlc_columns) - 1 < exit_index:
-                    break
-
-                exit_type = SellType.SELL_SIGNAL
-                exit_price = ohlc_columns[exit_index, 0]
-
-            trade = {'pair': pair,
-                     'stoploss': stoploss,
-                     'profit_percent': '',
-                     'profit_abs': '',
-                     'open_time': date_column[open_trade_index],
-                     'close_time': date_column[exit_index],
-                     'open_index': start_point + open_trade_index,
-                     'close_index': start_point + exit_index,
-                     'trade_duration': '',
-                     'open_rate': round(open_price, 15),
-                     'close_rate': round(exit_price, 15),
-                     'exit_type': exit_type
-                     }
-
-            result.append(trade)
-
-            # Giving a view of exit_index till the end of array
-            buy_column = buy_column[exit_index:]
-            sell_column = sell_column[exit_index:]
-            date_column = date_column[exit_index:]
-            ohlc_columns = ohlc_columns[exit_index:]
-            start_point += exit_index
-
-        return result
+from .edge_positioning import Edge, PairInfo  # noqa: F401
diff --git a/freqtrade/edge/edge_positioning.py b/freqtrade/edge/edge_positioning.py
new file mode 100644
index 000000000..037717c68
--- /dev/null
+++ b/freqtrade/edge/edge_positioning.py
@@ -0,0 +1,450 @@
+# pragma pylint: disable=W0603
+""" Edge positioning package """
+import logging
+from typing import Any, Dict, List, NamedTuple
+
+import arrow
+import numpy as np
+import utils_find_1st as utf1st
+from pandas import DataFrame
+
+from freqtrade.configuration import TimeRange
+from freqtrade.constants import DATETIME_PRINT_FORMAT, UNLIMITED_STAKE_AMOUNT
+from freqtrade.data.history import get_timerange, load_data, refresh_data
+from freqtrade.exceptions import OperationalException
+from freqtrade.strategy.interface import SellType
+
+
+logger = logging.getLogger(__name__)
+
+
+class PairInfo(NamedTuple):
+    stoploss: float
+    winrate: float
+    risk_reward_ratio: float
+    required_risk_reward: float
+    expectancy: float
+    nb_trades: int
+    avg_trade_duration: float
+
+
+class Edge:
+    """
+    Calculates Win Rate, Risk Reward Ratio, Expectancy
+    against historical data for a give set of markets and a strategy
+    it then adjusts stoploss and position size accordingly
+    and force it into the strategy
+    Author: https://github.com/mishaker
+    """
+
+    config: Dict = {}
+    _cached_pairs: Dict[str, Any] = {}  # Keeps a list of pairs
+
+    def __init__(self, config: Dict[str, Any], exchange, strategy) -> None:
+
+        self.config = config
+        self.exchange = exchange
+        self.strategy = strategy
+
+        self.edge_config = self.config.get('edge', {})
+        self._cached_pairs: Dict[str, Any] = {}  # Keeps a list of pairs
+        self._final_pairs: list = []
+
+        # checking max_open_trades. it should be -1 as with Edge
+        # the number of trades is determined by position size
+        if self.config['max_open_trades'] != float('inf'):
+            logger.critical('max_open_trades should be -1 in config !')
+
+        if self.config['stake_amount'] != UNLIMITED_STAKE_AMOUNT:
+            raise OperationalException('Edge works only with unlimited stake amount')
+
+        self._capital_ratio: float = self.config['tradable_balance_ratio']
+        self._allowed_risk: float = self.edge_config.get('allowed_risk')
+        self._since_number_of_days: int = self.edge_config.get('calculate_since_number_of_days', 14)
+        self._last_updated: int = 0  # Timestamp of pairs last updated time
+        self._refresh_pairs = True
+
+        self._stoploss_range_min = float(self.edge_config.get('stoploss_range_min', -0.01))
+        self._stoploss_range_max = float(self.edge_config.get('stoploss_range_max', -0.05))
+        self._stoploss_range_step = float(self.edge_config.get('stoploss_range_step', -0.001))
+
+        # calculating stoploss range
+        self._stoploss_range = np.arange(
+            self._stoploss_range_min,
+            self._stoploss_range_max,
+            self._stoploss_range_step
+        )
+
+        self._timerange: TimeRange = TimeRange.parse_timerange("%s-" % arrow.now().shift(
+            days=-1 * self._since_number_of_days).format('YYYYMMDD'))
+        if config.get('fee'):
+            self.fee = config['fee']
+        else:
+            self.fee = self.exchange.get_fee(symbol=self.config['exchange']['pair_whitelist'][0])
+
+    def calculate(self) -> bool:
+        pairs = self.config['exchange']['pair_whitelist']
+        heartbeat = self.edge_config.get('process_throttle_secs')
+
+        if (self._last_updated > 0) and (
+                self._last_updated + heartbeat > arrow.utcnow().int_timestamp):
+            return False
+
+        data: Dict[str, Any] = {}
+        logger.info('Using stake_currency: %s ...', self.config['stake_currency'])
+        logger.info('Using local backtesting data (using whitelist in given config) ...')
+
+        if self._refresh_pairs:
+            refresh_data(
+                datadir=self.config['datadir'],
+                pairs=pairs,
+                exchange=self.exchange,
+                timeframe=self.strategy.timeframe,
+                timerange=self._timerange,
+            )
+
+        data = load_data(
+            datadir=self.config['datadir'],
+            pairs=pairs,
+            timeframe=self.strategy.timeframe,
+            timerange=self._timerange,
+            startup_candles=self.strategy.startup_candle_count,
+            data_format=self.config.get('dataformat_ohlcv', 'json'),
+        )
+
+        if not data:
+            # Reinitializing cached pairs
+            self._cached_pairs = {}
+            logger.critical("No data found. Edge is stopped ...")
+            return False
+
+        preprocessed = self.strategy.ohlcvdata_to_dataframe(data)
+
+        # Print timeframe
+        min_date, max_date = get_timerange(preprocessed)
+        logger.info(f'Measuring data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
+                    f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
+                    f'({(max_date - min_date).days} days)..')
+        headers = ['date', 'buy', 'open', 'close', 'sell', 'high', 'low']
+
+        trades: list = []
+        for pair, pair_data in preprocessed.items():
+            # Sorting dataframe by date and reset index
+            pair_data = pair_data.sort_values(by=['date'])
+            pair_data = pair_data.reset_index(drop=True)
+
+            df_analyzed = self.strategy.advise_sell(
+                self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
+
+            trades += self._find_trades_for_stoploss_range(df_analyzed, pair, self._stoploss_range)
+
+        # If no trade found then exit
+        if len(trades) == 0:
+            logger.info("No trades found.")
+            return False
+
+        # Fill missing, calculable columns, profit, duration , abs etc.
+        trades_df = self._fill_calculable_fields(DataFrame(trades))
+        self._cached_pairs = self._process_expectancy(trades_df)
+        self._last_updated = arrow.utcnow().int_timestamp
+
+        return True
+
+    def stake_amount(self, pair: str, free_capital: float,
+                     total_capital: float, capital_in_trade: float) -> float:
+        stoploss = self.stoploss(pair)
+        available_capital = (total_capital + capital_in_trade) * self._capital_ratio
+        allowed_capital_at_risk = available_capital * self._allowed_risk
+        max_position_size = abs(allowed_capital_at_risk / stoploss)
+        position_size = min(max_position_size, free_capital)
+        if pair in self._cached_pairs:
+            logger.info(
+                'winrate: %s, expectancy: %s, position size: %s, pair: %s,'
+                ' capital in trade: %s, free capital: %s, total capital: %s,'
+                ' stoploss: %s, available capital: %s.',
+                self._cached_pairs[pair].winrate,
+                self._cached_pairs[pair].expectancy,
+                position_size, pair,
+                capital_in_trade, free_capital, total_capital,
+                stoploss, available_capital
+            )
+        return round(position_size, 15)
+
+    def stoploss(self, pair: str) -> float:
+        if pair in self._cached_pairs:
+            return self._cached_pairs[pair].stoploss
+        else:
+            logger.warning('tried to access stoploss of a non-existing pair, '
+                           'strategy stoploss is returned instead.')
+            return self.strategy.stoploss
+
+    def adjust(self, pairs: List[str]) -> list:
+        """
+        Filters out and sorts "pairs" according to Edge calculated pairs
+        """
+        final = []
+        for pair, info in self._cached_pairs.items():
+            if info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and \
+                info.winrate > float(self.edge_config.get('minimum_winrate', 0.60)) and \
+                    pair in pairs:
+                final.append(pair)
+
+        if self._final_pairs != final:
+            self._final_pairs = final
+            if self._final_pairs:
+                logger.info(
+                    'Minimum expectancy and minimum winrate are met only for %s,'
+                    ' so other pairs are filtered out.',
+                    self._final_pairs
+                    )
+            else:
+                logger.info(
+                    'Edge removed all pairs as no pair with minimum expectancy '
+                    'and minimum winrate was found !'
+                    )
+
+        return self._final_pairs
+
+    def accepted_pairs(self) -> list:
+        """
+        return a list of accepted pairs along with their winrate, expectancy and stoploss
+        """
+        final = []
+        for pair, info in self._cached_pairs.items():
+            if info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and \
+                 info.winrate > float(self.edge_config.get('minimum_winrate', 0.60)):
+                final.append({
+                    'Pair': pair,
+                    'Winrate': info.winrate,
+                    'Expectancy': info.expectancy,
+                    'Stoploss': info.stoploss,
+                })
+        return final
+
+    def _fill_calculable_fields(self, result: DataFrame) -> DataFrame:
+        """
+        The result frame contains a number of columns that are calculable
+        from other columns. These are left blank till all rows are added,
+        to be populated in single vector calls.
+
+        Columns to be populated are:
+        - Profit
+        - trade duration
+        - profit abs
+        :param result Dataframe
+        :return: result Dataframe
+        """
+        # We set stake amount to an arbitrary amount, as it doesn't change the calculation.
+        # All returned values are relative, they are defined as ratios.
+        stake = 0.015
+
+        result['trade_duration'] = result['close_date'] - result['open_date']
+
+        result['trade_duration'] = result['trade_duration'].map(
+            lambda x: int(x.total_seconds() / 60))
+
+        # Spends, Takes, Profit, Absolute Profit
+
+        # Buy Price
+        result['buy_vol'] = stake / result['open_rate']  # How many target are we buying
+        result['buy_fee'] = stake * self.fee
+        result['buy_spend'] = stake + result['buy_fee']  # How much we're spending
+
+        # Sell price
+        result['sell_sum'] = result['buy_vol'] * result['close_rate']
+        result['sell_fee'] = result['sell_sum'] * self.fee
+        result['sell_take'] = result['sell_sum'] - result['sell_fee']
+
+        # profit_ratio
+        result['profit_ratio'] = (result['sell_take'] - result['buy_spend']) / result['buy_spend']
+
+        # Absolute profit
+        result['profit_abs'] = result['sell_take'] - result['buy_spend']
+
+        return result
+
+    def _process_expectancy(self, results: DataFrame) -> Dict[str, Any]:
+        """
+        This calculates WinRate, Required Risk Reward, Risk Reward and Expectancy of all pairs
+        The calulation will be done per pair and per strategy.
+        """
+        # Removing pairs having less than min_trades_number
+        min_trades_number = self.edge_config.get('min_trade_number', 10)
+        results = results.groupby(['pair', 'stoploss']).filter(lambda x: len(x) > min_trades_number)
+        ###################################
+
+        # Removing outliers (Only Pumps) from the dataset
+        # The method to detect outliers is to calculate standard deviation
+        # Then every value more than (standard deviation + 2*average) is out (pump)
+        #
+        # Removing Pumps
+        if self.edge_config.get('remove_pumps', False):
+            results = results[results['profit_abs'] < 2 * results['profit_abs'].std()
+                              + results['profit_abs'].mean()]
+        ##########################################################################
+
+        # Removing trades having a duration more than X minutes (set in config)
+        max_trade_duration = self.edge_config.get('max_trade_duration_minute', 1440)
+        results = results[results.trade_duration < max_trade_duration]
+        #######################################################################
+
+        if results.empty:
+            return {}
+
+        groupby_aggregator = {
+            'profit_abs': [
+                ('nb_trades', 'count'),  # number of all trades
+                ('profit_sum', lambda x: x[x > 0].sum()),  # cumulative profit of all winning trades
+                ('loss_sum', lambda x: abs(x[x < 0].sum())),  # cumulative loss of all losing trades
+                ('nb_win_trades', lambda x: x[x > 0].count())  # number of winning trades
+            ],
+            'trade_duration': [('avg_trade_duration', 'mean')]
+        }
+
+        # Group by (pair and stoploss) by applying above aggregator
+        df = results.groupby(['pair', 'stoploss'])[['profit_abs', 'trade_duration']].agg(
+            groupby_aggregator).reset_index(col_level=1)
+
+        # Dropping level 0 as we don't need it
+        df.columns = df.columns.droplevel(0)
+
+        # Calculating number of losing trades, average win and average loss
+        df['nb_loss_trades'] = df['nb_trades'] - df['nb_win_trades']
+        df['average_win'] = np.where(df['nb_win_trades'] == 0, 0.0,
+                                     df['profit_sum'] / df['nb_win_trades'])
+        df['average_loss'] = np.where(df['nb_loss_trades'] == 0, 0.0,
+                                      df['loss_sum'] / df['nb_loss_trades'])
+
+        # Win rate = number of profitable trades / number of trades
+        df['winrate'] = df['nb_win_trades'] / df['nb_trades']
+
+        # risk_reward_ratio = average win / average loss
+        df['risk_reward_ratio'] = df['average_win'] / df['average_loss']
+
+        # required_risk_reward = (1 / winrate) - 1
+        df['required_risk_reward'] = (1 / df['winrate']) - 1
+
+        # expectancy = (risk_reward_ratio * winrate) - (lossrate)
+        df['expectancy'] = (df['risk_reward_ratio'] * df['winrate']) - (1 - df['winrate'])
+
+        # sort by expectancy and stoploss
+        df = df.sort_values(by=['expectancy', 'stoploss'], ascending=False).groupby(
+            'pair').first().sort_values(by=['expectancy'], ascending=False).reset_index()
+
+        final = {}
+        for x in df.itertuples():
+            final[x.pair] = PairInfo(
+                x.stoploss,
+                x.winrate,
+                x.risk_reward_ratio,
+                x.required_risk_reward,
+                x.expectancy,
+                x.nb_trades,
+                x.avg_trade_duration
+            )
+
+        # Returning a list of pairs in order of "expectancy"
+        return final
+
+    def _find_trades_for_stoploss_range(self, df, pair, stoploss_range):
+        buy_column = df['buy'].values
+        sell_column = df['sell'].values
+        date_column = df['date'].values
+        ohlc_columns = df[['open', 'high', 'low', 'close']].values
+
+        result: list = []
+        for stoploss in stoploss_range:
+            result += self._detect_next_stop_or_sell_point(
+                buy_column, sell_column, date_column, ohlc_columns, round(stoploss, 6), pair
+            )
+
+        return result
+
+    def _detect_next_stop_or_sell_point(self, buy_column, sell_column, date_column,
+                                        ohlc_columns, stoploss, pair):
+        """
+        Iterate through ohlc_columns in order to find the next trade
+        Next trade opens from the first buy signal noticed to
+        The sell or stoploss signal after it.
+        It then cuts OHLC, buy_column, sell_column and date_column.
+        Cut from (the exit trade index) + 1.
+
+        Author: https://github.com/mishaker
+        """
+
+        result: list = []
+        start_point = 0
+
+        while True:
+            open_trade_index = utf1st.find_1st(buy_column, 1, utf1st.cmp_equal)
+
+            # Return empty if we don't find trade entry (i.e. buy==1) or
+            # we find a buy but at the end of array
+            if open_trade_index == -1 or open_trade_index == len(buy_column) - 1:
+                break
+            else:
+                # When a buy signal is seen,
+                # trade opens in reality on the next candle
+                open_trade_index += 1
+
+            open_price = ohlc_columns[open_trade_index, 0]
+            stop_price = (open_price * (stoploss + 1))
+
+            # Searching for the index where stoploss is hit
+            stop_index = utf1st.find_1st(
+                ohlc_columns[open_trade_index:, 2], stop_price, utf1st.cmp_smaller)
+
+            # If we don't find it then we assume stop_index will be far in future (infinite number)
+            if stop_index == -1:
+                stop_index = float('inf')
+
+            # Searching for the index where sell is hit
+            sell_index = utf1st.find_1st(sell_column[open_trade_index:], 1, utf1st.cmp_equal)
+
+            # If we don't find it then we assume sell_index will be far in future (infinite number)
+            if sell_index == -1:
+                sell_index = float('inf')
+
+            # Check if we don't find any stop or sell point (in that case trade remains open)
+            # It is not interesting for Edge to consider it so we simply ignore the trade
+            # And stop iterating there is no more entry
+            if stop_index == sell_index == float('inf'):
+                break
+
+            if stop_index <= sell_index:
+                exit_index = open_trade_index + stop_index
+                exit_type = SellType.STOP_LOSS
+                exit_price = stop_price
+            elif stop_index > sell_index:
+                # If exit is SELL then we exit at the next candle
+                exit_index = open_trade_index + sell_index + 1
+
+                # Check if we have the next candle
+                if len(ohlc_columns) - 1 < exit_index:
+                    break
+
+                exit_type = SellType.SELL_SIGNAL
+                exit_price = ohlc_columns[exit_index, 0]
+
+            trade = {'pair': pair,
+                     'stoploss': stoploss,
+                     'profit_ratio': '',
+                     'profit_abs': '',
+                     'open_date': date_column[open_trade_index],
+                     'close_date': date_column[exit_index],
+                     'trade_duration': '',
+                     'open_rate': round(open_price, 15),
+                     'close_rate': round(exit_price, 15),
+                     'exit_type': exit_type
+                     }
+
+            result.append(trade)
+
+            # Giving a view of exit_index till the end of array
+            buy_column = buy_column[exit_index:]
+            sell_column = sell_column[exit_index:]
+            date_column = date_column[exit_index:]
+            ohlc_columns = ohlc_columns[exit_index:]
+            start_point += exit_index
+
+        return result
diff --git a/freqtrade/exceptions.py b/freqtrade/exceptions.py
new file mode 100644
index 000000000..caf970606
--- /dev/null
+++ b/freqtrade/exceptions.py
@@ -0,0 +1,80 @@
+
+
+class FreqtradeException(Exception):
+    """
+    Freqtrade base exception. Handled at the outermost level.
+    All other exception types are subclasses of this exception type.
+    """
+
+
+class OperationalException(FreqtradeException):
+    """
+    Requires manual intervention and will stop the bot.
+    Most of the time, this is caused by an invalid Configuration.
+    """
+
+
+class DependencyException(FreqtradeException):
+    """
+    Indicates that an assumed dependency is not met.
+    This could happen when there is currently not enough money on the account.
+    """
+
+
+class PricingError(DependencyException):
+    """
+    Subclass of DependencyException.
+    Indicates that the price could not be determined.
+    Implicitly a buy / sell operation.
+    """
+
+
+class ExchangeError(DependencyException):
+    """
+    Error raised out of the exchange.
+    Has multiple Errors to determine the appropriate error.
+    """
+
+
+class InvalidOrderException(ExchangeError):
+    """
+    This is returned when the order is not valid. Example:
+    If stoploss on exchange order is hit, then trying to cancel the order
+    should return this exception.
+    """
+
+
+class RetryableOrderError(InvalidOrderException):
+    """
+    This is returned when the order is not found.
+    This Error will be repeated with increasing backof (in line with DDosError).
+    """
+
+
+class InsufficientFundsError(InvalidOrderException):
+    """
+    This error is used when there are not enough funds available on the exchange
+    to create an order.
+    """
+
+
+class TemporaryError(ExchangeError):
+    """
+    Temporary network or exchange related error.
+    This could happen when an exchange is congested, unavailable, or the user
+    has networking problems. Usually resolves itself after a time.
+    """
+
+
+class DDosProtection(TemporaryError):
+    """
+    Temporary error caused by DDOS protection.
+    Bot will wait for a second and then retry.
+    """
+
+
+class StrategyError(FreqtradeException):
+    """
+    Errors with custom user-code deteced.
+    Usually caused by errors in the strategy.
+    """
diff --git a/freqtrade/exchange/__init__.py b/freqtrade/exchange/__init__.py
index 5c58320f6..5b58d7a95 100644
--- a/freqtrade/exchange/__init__.py
+++ b/freqtrade/exchange/__init__.py
@@ -1,10 +1,16 @@
-from freqtrade.exchange.exchange import Exchange  # noqa: F401
-from freqtrade.exchange.exchange import (is_exchange_bad,  # noqa: F401
-                                         is_exchange_available,
-                                         is_exchange_officially_supported,
-                                         available_exchanges)
-from freqtrade.exchange.exchange import (timeframe_to_seconds,  # noqa: F401
-                                         timeframe_to_minutes,
-                                         timeframe_to_msecs)
-from freqtrade.exchange.kraken import Kraken  # noqa: F401
-from freqtrade.exchange.binance import Binance  # noqa: F401
+# flake8: noqa: F401
+# isort: off
+from freqtrade.exchange.common import MAP_EXCHANGE_CHILDCLASS
+from freqtrade.exchange.exchange import Exchange
+# isort: on
+from freqtrade.exchange.bibox import Bibox
+from freqtrade.exchange.binance import Binance
+from freqtrade.exchange.bittrex import Bittrex
+from freqtrade.exchange.exchange import (available_exchanges, ccxt_exchanges,
+                                         get_exchange_bad_reason, is_exchange_bad,
+                                         is_exchange_known_ccxt, is_exchange_officially_supported,
+                                         market_is_active, timeframe_to_minutes, timeframe_to_msecs,
+                                         timeframe_to_next_date, timeframe_to_prev_date,
+                                         timeframe_to_seconds)
+from freqtrade.exchange.ftx import Ftx
+from freqtrade.exchange.kraken import Kraken
diff --git a/freqtrade/exchange/bibox.py b/freqtrade/exchange/bibox.py
new file mode 100644
index 000000000..f0c2dd00b
--- /dev/null
+++ b/freqtrade/exchange/bibox.py
@@ -0,0 +1,23 @@
+""" Bibox exchange subclass """
+import logging
+from typing import Dict
+
+from freqtrade.exchange import Exchange
+
+
+logger = logging.getLogger(__name__)
+
+
+class Bibox(Exchange):
+    """
+    Bibox exchange class. Contains adjustments needed for Freqtrade to work
+    with this exchange.
+
+    Please note that this exchange is not included in the list of exchanges
+    officially supported by the Freqtrade development team. So some features
+    may still not work as expected.
+    """
+
+    # fetchCurrencies API point requires authentication for Bibox,
+    # so switch it off for Freqtrade load_markets()
+    _ccxt_config: Dict = {"has": {"fetchCurrencies": False}}
diff --git a/freqtrade/exchange/binance.py b/freqtrade/exchange/binance.py
index 18e754e3f..099f282a2 100644
--- a/freqtrade/exchange/binance.py
+++ b/freqtrade/exchange/binance.py
@@ -2,7 +2,13 @@
 import logging
 from typing import Dict
 
+import ccxt
+
+from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
+                                  OperationalException, TemporaryError)
 from freqtrade.exchange import Exchange
+from freqtrade.exchange.common import retrier
+
 
 logger = logging.getLogger(__name__)
 
@@ -12,16 +18,72 @@ class Binance(Exchange):
     _ft_has: Dict = {
         "stoploss_on_exchange": True,
         "order_time_in_force": ['gtc', 'fok', 'ioc'],
+        "trades_pagination": "id",
+        "trades_pagination_arg": "fromId",
+        "l2_limit_range": [5, 10, 20, 50, 100, 500, 1000],
     }
 
-    def get_order_book(self, pair: str, limit: int = 100) -> dict:
+    def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
         """
-        get order book level 2 from exchange
-
-        20180619: binance support limits but only on specific range
+        Verify stop_loss against stoploss-order value (limit or price)
+        Returns True if adjustment is necessary.
         """
-        limit_range = [5, 10, 20, 50, 100, 500, 1000]
-        # get next-higher step in the limit_range list
-        limit = min(list(filter(lambda x: limit <= x, limit_range)))
+        return order['type'] == 'stop_loss_limit' and stop_loss > float(order['info']['stopPrice'])
 
-        return super().get_order_book(pair, limit)
+    @retrier(retries=0)
+    def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
+        """
+        creates a stoploss limit order.
+        this stoploss-limit is binance-specific.
+        It may work with a limited number of other exchanges, but this has not been tested yet.
+        """
+        # Limit price threshold: As limit price should always be below stop-price
+        limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
+        rate = stop_price * limit_price_pct
+
+        ordertype = "stop_loss_limit"
+
+        stop_price = self.price_to_precision(pair, stop_price)
+
+        # Ensure rate is less than stop price
+        if stop_price <= rate:
+            raise OperationalException(
+                'In stoploss limit order, stop price should be more than limit price')
+
+        if self._config['dry_run']:
+            dry_order = self.dry_run_order(
+                pair, ordertype, "sell", amount, stop_price)
+            return dry_order
+
+        try:
+            params = self._params.copy()
+            params.update({'stopPrice': stop_price})
+
+            amount = self.amount_to_precision(pair, amount)
+
+            rate = self.price_to_precision(pair, rate)
+
+            order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
+                                           amount=amount, price=rate, params=params)
+            logger.info('stoploss limit order added for %s. '
+                        'stop price: %s. limit: %s', pair, stop_price, rate)
+            return order
+        except ccxt.InsufficientFunds as e:
+            raise InsufficientFundsError(
+                f'Insufficient funds to create {ordertype} sell order on market {pair}. '
+                f'Tried to sell amount {amount} at rate {rate}. '
+                f'Message: {e}') from e
+        except ccxt.InvalidOrder as e:
+            # Errors:
+            # `binance Order would trigger immediately.`
+            raise InvalidOrderException(
+                f'Could not create {ordertype} sell order on market {pair}. '
+                f'Tried to sell amount {amount} at rate {rate}. '
+                f'Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
diff --git a/freqtrade/exchange/bittrex.py b/freqtrade/exchange/bittrex.py
new file mode 100644
index 000000000..4318f9cf0
--- /dev/null
+++ b/freqtrade/exchange/bittrex.py
@@ -0,0 +1,23 @@
+""" Bittrex exchange subclass """
+import logging
+from typing import Dict
+
+from freqtrade.exchange import Exchange
+
+
+logger = logging.getLogger(__name__)
+
+
+class Bittrex(Exchange):
+    """
+    Bittrex exchange class. Contains adjustments needed for Freqtrade to work
+    with this exchange.
+
+    Please note that this exchange is not included in the list of exchanges
+    officially supported by the Freqtrade development team. So some features
+    may still not work as expected.
+    """
+
+    _ft_has: Dict = {
+        "l2_limit_range": [1, 25, 500],
+    }
diff --git a/freqtrade/exchange/common.py b/freqtrade/exchange/common.py
new file mode 100644
index 000000000..ce0fde9e4
--- /dev/null
+++ b/freqtrade/exchange/common.py
@@ -0,0 +1,156 @@
+import asyncio
+import logging
+import time
+from functools import wraps
+
+from freqtrade.exceptions import DDosProtection, RetryableOrderError, TemporaryError
+
+
+logger = logging.getLogger(__name__)
+
+
+# Maximum default retry count.
+# Functions are always called RETRY_COUNT + 1 times (for the original call)
+API_RETRY_COUNT = 4
+API_FETCH_ORDER_RETRY_COUNT = 5
+
+BAD_EXCHANGES = {
+    "bitmex": "Various reasons.",
+    "bitstamp": "Does not provide history. "
+                "Details in https://github.com/freqtrade/freqtrade/issues/1983",
+    "hitbtc": "This API cannot be used with Freqtrade. "
+              "Use `hitbtc2` exchange id to access this exchange.",
+    "phemex": "Does not provide history. ",
+    **dict.fromkeys([
+        'adara',
+        'anxpro',
+        'bigone',
+        'coinbase',
+        'coinexchange',
+        'coinmarketcap',
+        'lykke',
+        'xbtce',
+    ], "Does not provide timeframes. ccxt fetchOHLCV: False"),
+    **dict.fromkeys([
+        'bcex',
+        'bit2c',
+        'bitbay',
+        'bitflyer',
+        'bitforex',
+        'bithumb',
+        'bitso',
+        'bitstamp1',
+        'bl3p',
+        'braziliex',
+        'btcbox',
+        'btcchina',
+        'btctradeim',
+        'btctradeua',
+        'bxinth',
+        'chilebit',
+        'coincheck',
+        'coinegg',
+        'coinfalcon',
+        'coinfloor',
+        'coingi',
+        'coinmate',
+        'coinone',
+        'coinspot',
+        'coolcoin',
+        'crypton',
+        'deribit',
+        'exmo',
+        'exx',
+        'flowbtc',
+        'foxbit',
+        'fybse',
+        # 'hitbtc',
+        'ice3x',
+        'independentreserve',
+        'indodax',
+        'itbit',
+        'lakebtc',
+        'latoken',
+        'liquid',
+        'livecoin',
+        'luno',
+        'mixcoins',
+        'negociecoins',
+        'nova',
+        'paymium',
+        'southxchange',
+        'stronghold',
+        'surbitcoin',
+        'therock',
+        'tidex',
+        'vaultoro',
+        'vbtc',
+        'virwox',
+        'yobit',
+        'zaif',
+    ], "Does not provide timeframes. ccxt fetchOHLCV: emulated"),
+}
+
+MAP_EXCHANGE_CHILDCLASS = {
+    'binanceus': 'binance',
+    'binanceje': 'binance',
+}
+
+
+def calculate_backoff(retrycount, max_retries):
+    """
+    Calculate backoff
+    """
+    return (max_retries - retrycount) ** 2 + 1
+
+
+def retrier_async(f):
+    async def wrapper(*args, **kwargs):
+        count = kwargs.pop('count', API_RETRY_COUNT)
+        try:
+            return await f(*args, **kwargs)
+        except TemporaryError as ex:
+            logger.warning('%s() returned exception: "%s"', f.__name__, ex)
+            if count > 0:
+                logger.warning('retrying %s() still for %s times', f.__name__, count)
+                count -= 1
+                kwargs.update({'count': count})
+                if isinstance(ex, DDosProtection):
+                    backoff_delay = calculate_backoff(count + 1, API_RETRY_COUNT)
+                    logger.info(f"Applying DDosProtection backoff delay: {backoff_delay}")
+                    await asyncio.sleep(backoff_delay)
+                return await wrapper(*args, **kwargs)
+            else:
+                logger.warning('Giving up retrying: %s()', f.__name__)
+                raise ex
+    return wrapper
+
+
+def retrier(_func=None, retries=API_RETRY_COUNT):
+    def decorator(f):
+        @wraps(f)
+        def wrapper(*args, **kwargs):
+            count = kwargs.pop('count', retries)
+            try:
+                return f(*args, **kwargs)
+            except (TemporaryError, RetryableOrderError) as ex:
+                logger.warning('%s() returned exception: "%s"', f.__name__, ex)
+                if count > 0:
+                    logger.warning('retrying %s() still for %s times', f.__name__, count)
+                    count -= 1
+                    kwargs.update({'count': count})
+                    if isinstance(ex, DDosProtection) or isinstance(ex, RetryableOrderError):
+                        # increasing backoff
+                        backoff_delay = calculate_backoff(count + 1, retries)
+                        logger.info(f"Applying DDosProtection backoff delay: {backoff_delay}")
+                        time.sleep(backoff_delay)
+                    return wrapper(*args, **kwargs)
+                else:
+                    logger.warning('Giving up retrying: %s()', f.__name__)
+                    raise ex
+        return wrapper
+    # Support both @retrier and @retrier(retries=2) syntax
+    if _func is None:
+        return decorator
+    else:
+        return decorator(_func)
diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py
index 65f013a03..2bbdb0d59 100644
--- a/freqtrade/exchange/exchange.py
+++ b/freqtrade/exchange/exchange.py
@@ -6,66 +6,41 @@ import asyncio
 import inspect
 import logging
 from copy import deepcopy
-from datetime import datetime
-from math import ceil, floor
-from random import randint
+from datetime import datetime, timezone
+from math import ceil
 from typing import Any, Dict, List, Optional, Tuple
 
 import arrow
 import ccxt
 import ccxt.async_support as ccxt_async
+from ccxt.base.decimal_to_precision import (ROUND_DOWN, ROUND_UP, TICK_SIZE, TRUNCATE,
+                                            decimal_to_precision)
 from pandas import DataFrame
 
-from freqtrade import (DependencyException, InvalidOrderException,
-                       OperationalException, TemporaryError, constants)
-from freqtrade.data.converter import parse_ticker_dataframe
-from freqtrade.misc import deep_merge_dicts
+from freqtrade.constants import ListPairsWithTimeframes
+from freqtrade.data.converter import ohlcv_to_dataframe, trades_dict_to_list
+from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFundsError,
+                                  InvalidOrderException, OperationalException, RetryableOrderError,
+                                  TemporaryError)
+from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, BAD_EXCHANGES, retrier,
+                                       retrier_async)
+from freqtrade.misc import deep_merge_dicts, safe_value_fallback2
+
+
+CcxtModuleType = Any
+
 
 logger = logging.getLogger(__name__)
 
 
-API_RETRY_COUNT = 4
-
-
-def retrier_async(f):
-    async def wrapper(*args, **kwargs):
-        count = kwargs.pop('count', API_RETRY_COUNT)
-        try:
-            return await f(*args, **kwargs)
-        except (TemporaryError, DependencyException) as ex:
-            logger.warning('%s() returned exception: "%s"', f.__name__, ex)
-            if count > 0:
-                count -= 1
-                kwargs.update({'count': count})
-                logger.warning('retrying %s() still for %s times', f.__name__, count)
-                return await wrapper(*args, **kwargs)
-            else:
-                logger.warning('Giving up retrying: %s()', f.__name__)
-                raise ex
-    return wrapper
-
-
-def retrier(f):
-    def wrapper(*args, **kwargs):
-        count = kwargs.pop('count', API_RETRY_COUNT)
-        try:
-            return f(*args, **kwargs)
-        except (TemporaryError, DependencyException) as ex:
-            logger.warning('%s() returned exception: "%s"', f.__name__, ex)
-            if count > 0:
-                count -= 1
-                kwargs.update({'count': count})
-                logger.warning('retrying %s() still for %s times', f.__name__, count)
-                return wrapper(*args, **kwargs)
-            else:
-                logger.warning('Giving up retrying: %s()', f.__name__)
-                raise ex
-    return wrapper
-
-
-class Exchange(object):
+class Exchange:
 
     _config: Dict = {}
+
+    # Parameters to add directly to ccxt sync/async initialization.
+    _ccxt_config: Dict = {}
+
+    # Parameters to add directly to buy/sell calls (like agreeing to trading agreement)
     _params: Dict = {}
 
     # Dict to specify which options each exchange implements
@@ -76,10 +51,13 @@ class Exchange(object):
         "order_time_in_force": ["gtc"],
         "ohlcv_candle_limit": 500,
         "ohlcv_partial_candle": True,
+        "trades_pagination": "time",  # Possible are "time" or "id"
+        "trades_pagination_arg": "since",
+        "l2_limit_range": None,
     }
     _ft_has: Dict = {}
 
-    def __init__(self, config: dict) -> None:
+    def __init__(self, config: Dict[str, Any], validate: bool = True) -> None:
         """
         Initializes this module with the given config,
         it does basic validation whether the specified exchange and pairs are valid.
@@ -90,8 +68,6 @@ class Exchange(object):
 
         self._config.update(config)
 
-        self._cached_ticker: Dict[str, Any] = {}
-
         # Holds last candle refreshed time of each pair
         self._pairs_last_refresh_time: Dict[Tuple[str, str], int] = {}
         # Timestamp of last markets refresh
@@ -105,13 +81,13 @@ class Exchange(object):
 
         if config['dry_run']:
             logger.info('Instance is running with dry_run enabled')
-
+        logger.info(f"Using CCXT {ccxt.__version__}")
         exchange_config = config['exchange']
 
         # Deep merge ft_has with default ft_has options
         self._ft_has = deep_merge_dicts(self._ft_has, deepcopy(self._ft_has_default))
-        if exchange_config.get("_ft_has_params"):
-            self._ft_has = deep_merge_dicts(exchange_config.get("_ft_has_params"),
+        if exchange_config.get('_ft_has_params'):
+            self._ft_has = deep_merge_dicts(exchange_config.get('_ft_has_params'),
                                             self._ft_has)
             logger.info("Overriding exchange._ft_has with config params, result: %s", self._ft_has)
 
@@ -119,28 +95,44 @@ class Exchange(object):
         self._ohlcv_candle_limit = self._ft_has['ohlcv_candle_limit']
         self._ohlcv_partial_candle = self._ft_has['ohlcv_partial_candle']
 
+        self._trades_pagination = self._ft_has['trades_pagination']
+        self._trades_pagination_arg = self._ft_has['trades_pagination_arg']
+
         # Initialize ccxt objects
-        self._api = self._init_ccxt(
-            exchange_config, ccxt_kwargs=exchange_config.get('ccxt_config'))
+        ccxt_config = self._ccxt_config.copy()
+        ccxt_config = deep_merge_dicts(exchange_config.get('ccxt_config', {}), ccxt_config)
+        ccxt_config = deep_merge_dicts(exchange_config.get('ccxt_sync_config', {}), ccxt_config)
+
+        self._api = self._init_ccxt(exchange_config, ccxt_kwargs=ccxt_config)
+
+        ccxt_async_config = self._ccxt_config.copy()
+        ccxt_async_config = deep_merge_dicts(exchange_config.get('ccxt_config', {}),
+                                             ccxt_async_config)
+        ccxt_async_config = deep_merge_dicts(exchange_config.get('ccxt_async_config', {}),
+                                             ccxt_async_config)
         self._api_async = self._init_ccxt(
-            exchange_config, ccxt_async, ccxt_kwargs=exchange_config.get('ccxt_async_config'))
+            exchange_config, ccxt_async, ccxt_kwargs=ccxt_async_config)
 
         logger.info('Using Exchange "%s"', self.name)
 
+        if validate:
+            # Check if timeframe is available
+            self.validate_timeframes(config.get('timeframe'))
+
+            # Initial markets load
+            self._load_markets()
+
+            # Check if all pairs are available
+            self.validate_stakecurrency(config['stake_currency'])
+            if not exchange_config.get('skip_pair_validation'):
+                self.validate_pairs(config['exchange']['pair_whitelist'])
+            self.validate_ordertypes(config.get('order_types', {}))
+            self.validate_order_time_in_force(config.get('order_time_in_force', {}))
+            self.validate_required_startup_candles(config.get('startup_candle_count', 0))
+
         # Converts the interval provided in minutes in config to seconds
         self.markets_refresh_interval: int = exchange_config.get(
             "markets_refresh_interval", 60) * 60
-        # Initial markets load
-        self._load_markets()
-
-        # Check if all pairs are available
-        self.validate_pairs(config['exchange']['pair_whitelist'])
-        self.validate_ordertypes(config.get('order_types', {}))
-        self.validate_order_time_in_force(config.get('order_time_in_force', {}))
-
-        if config.get('ticker_interval'):
-            # Check if timeframe is available
-            self.validate_timeframes(config['ticker_interval'])
 
     def __del__(self):
         """
@@ -150,7 +142,7 @@ class Exchange(object):
         if self._api_async and inspect.iscoroutinefunction(self._api_async.close):
             asyncio.get_event_loop().run_until_complete(self._api_async.close())
 
-    def _init_ccxt(self, exchange_config: dict, ccxt_module=ccxt,
+    def _init_ccxt(self, exchange_config: Dict[str, Any], ccxt_module: CcxtModuleType = ccxt,
                    ccxt_kwargs: dict = None) -> ccxt.Exchange:
         """
         Initialize ccxt with given config and return valid
@@ -159,7 +151,7 @@ class Exchange(object):
         # Find matching class for the given exchange name
         name = exchange_config['name']
 
-        if not is_exchange_available(name, ccxt_module):
+        if not is_exchange_known_ccxt(name, ccxt_module):
             raise OperationalException(f'Exchange {name} is not supported by ccxt')
 
         ex_config = {
@@ -174,10 +166,10 @@ class Exchange(object):
         try:
 
             api = getattr(ccxt_module, name.lower())(ex_config)
-        except (KeyError, AttributeError):
-            raise OperationalException(f'Exchange {name} is not supported')
+        except (KeyError, AttributeError) as e:
+            raise OperationalException(f'Exchange {name} is not supported') from e
         except ccxt.BaseError as e:
-            raise OperationalException(f"Initialization of ccxt failed. Reason: {e}")
+            raise OperationalException(f"Initialization of ccxt failed. Reason: {e}") from e
 
         self.set_sandbox(api, exchange_config, name)
 
@@ -193,37 +185,105 @@ class Exchange(object):
         """exchange ccxt id"""
         return self._api.id
 
+    @property
+    def timeframes(self) -> List[str]:
+        return list((self._api.timeframes or {}).keys())
+
+    @property
+    def ohlcv_candle_limit(self) -> int:
+        """exchange ohlcv candle limit"""
+        return int(self._ohlcv_candle_limit)
+
     @property
     def markets(self) -> Dict:
         """exchange ccxt markets"""
         if not self._api.markets:
-            logger.warning("Markets were not loaded. Loading them now..")
+            logger.info("Markets were not loaded. Loading them now..")
             self._load_markets()
         return self._api.markets
 
-    def klines(self, pair_interval: Tuple[str, str], copy=True) -> DataFrame:
+    @property
+    def precisionMode(self) -> str:
+        """exchange ccxt precisionMode"""
+        return self._api.precisionMode
+
+    def get_markets(self, base_currencies: List[str] = None, quote_currencies: List[str] = None,
+                    pairs_only: bool = False, active_only: bool = False) -> Dict:
+        """
+        Return exchange ccxt markets, filtered out by base currency and quote currency
+        if this was requested in parameters.
+
+        TODO: consider moving it to the Dataprovider
+        """
+        markets = self.markets
+        if not markets:
+            raise OperationalException("Markets were not loaded.")
+
+        if base_currencies:
+            markets = {k: v for k, v in markets.items() if v['base'] in base_currencies}
+        if quote_currencies:
+            markets = {k: v for k, v in markets.items() if v['quote'] in quote_currencies}
+        if pairs_only:
+            markets = {k: v for k, v in markets.items() if self.market_is_tradable(v)}
+        if active_only:
+            markets = {k: v for k, v in markets.items() if market_is_active(v)}
+        return markets
+
+    def get_quote_currencies(self) -> List[str]:
+        """
+        Return a list of supported quote currencies
+        """
+        markets = self.markets
+        return sorted(set([x['quote'] for _, x in markets.items()]))
+
+    def get_pair_quote_currency(self, pair: str) -> str:
+        """
+        Return a pair's quote currency
+        """
+        return self.markets.get(pair, {}).get('quote', '')
+
+    def get_pair_base_currency(self, pair: str) -> str:
+        """
+        Return a pair's quote currency
+        """
+        return self.markets.get(pair, {}).get('base', '')
+
+    def market_is_tradable(self, market: Dict[str, Any]) -> bool:
+        """
+        Check if the market symbol is tradable by Freqtrade.
+        By default, checks if it's splittable by `/` and both sides correspond to base / quote
+        """
+        symbol_parts = market['symbol'].split('/')
+        return (len(symbol_parts) == 2 and
+                len(symbol_parts[0]) > 0 and
+                len(symbol_parts[1]) > 0 and
+                symbol_parts[0] == market.get('base') and
+                symbol_parts[1] == market.get('quote')
+                )
+
+    def klines(self, pair_interval: Tuple[str, str], copy: bool = True) -> DataFrame:
         if pair_interval in self._klines:
             return self._klines[pair_interval].copy() if copy else self._klines[pair_interval]
         else:
             return DataFrame()
 
-    def set_sandbox(self, api, exchange_config: dict, name: str):
+    def set_sandbox(self, api: ccxt.Exchange, exchange_config: dict, name: str) -> None:
         if exchange_config.get('sandbox'):
             if api.urls.get('test'):
                 api.urls['api'] = api.urls['test']
                 logger.info("Enabled Sandbox API on %s", name)
             else:
-                logger.warning(name, "No Sandbox URL in CCXT, exiting. "
-                                     "Please check your config.json")
+                logger.warning(
+                    f"No Sandbox URL in CCXT for {name}, exiting. Please check your config.json")
                 raise OperationalException(f'Exchange {name} does not provide a sandbox api')
 
-    def _load_async_markets(self, reload=False) -> None:
+    def _load_async_markets(self, reload: bool = False) -> None:
         try:
             if self._api_async:
                 asyncio.get_event_loop().run_until_complete(
                     self._api_async.load_markets(reload=reload))
 
-        except ccxt.BaseError as e:
+        except (asyncio.TimeoutError, ccxt.BaseError) as e:
             logger.warning('Could not load async markets. Reason: %s', e)
             return
 
@@ -232,36 +292,50 @@ class Exchange(object):
         try:
             self._api.load_markets()
             self._load_async_markets()
-            self._last_markets_refresh = arrow.utcnow().timestamp
+            self._last_markets_refresh = arrow.utcnow().int_timestamp
         except ccxt.BaseError as e:
             logger.warning('Unable to initialize markets. Reason: %s', e)
 
-    def _reload_markets(self) -> None:
-        """Reload markets both sync and async, if refresh interval has passed"""
+    def reload_markets(self) -> None:
+        """Reload markets both sync and async if refresh interval has passed """
         # Check whether markets have to be reloaded
         if (self._last_markets_refresh > 0) and (
                 self._last_markets_refresh + self.markets_refresh_interval
-                > arrow.utcnow().timestamp):
+                > arrow.utcnow().int_timestamp):
             return None
         logger.debug("Performing scheduled market reload..")
         try:
             self._api.load_markets(reload=True)
-            self._last_markets_refresh = arrow.utcnow().timestamp
+            # Also reload async markets to avoid issues with newly listed pairs
+            self._load_async_markets(reload=True)
+            self._last_markets_refresh = arrow.utcnow().int_timestamp
         except ccxt.BaseError:
             logger.exception("Could not reload markets.")
 
+    def validate_stakecurrency(self, stake_currency: str) -> None:
+        """
+        Checks stake-currency against available currencies on the exchange.
+        :param stake_currency: Stake-currency to validate
+        :raise: OperationalException if stake-currency is not available.
+        """
+        quote_currencies = self.get_quote_currencies()
+        if stake_currency not in quote_currencies:
+            raise OperationalException(
+                f"{stake_currency} is not available as stake on {self.name}. "
+                f"Available currencies are: {', '.join(quote_currencies)}")
+
     def validate_pairs(self, pairs: List[str]) -> None:
         """
         Checks if all given pairs are tradable on the current exchange.
-        Raises OperationalException if one pair is not available.
         :param pairs: list of pairs
+        :raise: OperationalException if one pair is not available
         :return: None
         """
 
         if not self.markets:
             logger.warning('Unable to validate pairs (assuming they are correct).')
-        #     return
-
+            return
+        invalid_pairs = []
         for pair in pairs:
             # Note: ccxt has BaseCurrency/QuoteCurrency format for pairs
             # TODO: add a support for having coins in BTC/USDT format
@@ -270,18 +344,39 @@ class Exchange(object):
                     f'Pair {pair} is not available on {self.name}. '
                     f'Please remove {pair} from your whitelist.')
 
-    def get_valid_pair_combination(self, curr_1, curr_2) -> str:
+                # From ccxt Documentation:
+                # markets.info: An associative array of non-common market properties,
+                # including fees, rates, limits and other general market information.
+                # The internal info array is different for each particular market,
+                # its contents depend on the exchange.
+                # It can also be a string or similar ... so we need to verify that first.
+            elif (isinstance(self.markets[pair].get('info', None), dict)
+                  and self.markets[pair].get('info', {}).get('IsRestricted', False)):
+                # Warn users about restricted pairs in whitelist.
+                # We cannot determine reliably if Users are affected.
+                logger.warning(f"Pair {pair} is restricted for some users on this exchange."
+                               f"Please check if you are impacted by this restriction "
+                               f"on the exchange and eventually remove {pair} from your whitelist.")
+            if (self._config['stake_currency'] and
+                    self.get_pair_quote_currency(pair) != self._config['stake_currency']):
+                invalid_pairs.append(pair)
+        if invalid_pairs:
+            raise OperationalException(
+                f"Stake-currency '{self._config['stake_currency']}' not compatible with "
+                f"pair-whitelist. Please remove the following pairs: {invalid_pairs}")
+
+    def get_valid_pair_combination(self, curr_1: str, curr_2: str) -> str:
         """
         Get valid pair combination of curr_1 and curr_2 by trying both combinations.
         """
         for pair in [f"{curr_1}/{curr_2}", f"{curr_2}/{curr_1}"]:
             if pair in self.markets and self.markets[pair].get('active'):
                 return pair
-        raise DependencyException(f"Could not combine {curr_1} and {curr_2} to get a valid pair.")
+        raise ExchangeError(f"Could not combine {curr_1} and {curr_2} to get a valid pair.")
 
-    def validate_timeframes(self, timeframe: List[str]) -> None:
+    def validate_timeframes(self, timeframe: Optional[str]) -> None:
         """
-        Checks if ticker interval from config is a supported timeframe on the exchange
+        Check if timeframe from config is a supported timeframe on the exchange
         """
         if not hasattr(self._api, "timeframes") or self._api.timeframes is None:
             # If timeframes attribute is missing (or is None), the exchange probably
@@ -292,10 +387,12 @@ class Exchange(object):
                 f"for the exchange \"{self.name}\" and this exchange "
                 f"is therefore not supported. ccxt fetchOHLCV: {self.exchange_has('fetchOHLCV')}")
 
-        timeframes = self._api.timeframes
-        if timeframe not in timeframes:
+        if timeframe and (timeframe not in self.timeframes):
             raise OperationalException(
-                f'Invalid ticker {timeframe}, this Exchange supports {timeframes}')
+                f"Invalid timeframe '{timeframe}'. This exchange supports: {self.timeframes}")
+
+        if timeframe and timeframe_to_minutes(timeframe) < 1:
+            raise OperationalException("Timeframes < 1m are currently not supported by Freqtrade.")
 
     def validate_ordertypes(self, order_types: Dict) -> None:
         """
@@ -309,7 +406,7 @@ class Exchange(object):
         if (order_types.get("stoploss_on_exchange")
                 and not self._ft_has.get("stoploss_on_exchange", False)):
             raise OperationalException(
-                'On exchange stoploss is not supported for %s.' % self.name
+                f'On exchange stoploss is not supported for {self.name}.'
             )
 
     def validate_order_time_in_force(self, order_time_in_force: Dict) -> None:
@@ -321,6 +418,16 @@ class Exchange(object):
             raise OperationalException(
                 f'Time in force policies are not supported for {self.name} yet.')
 
+    def validate_required_startup_candles(self, startup_candles: int) -> None:
+        """
+        Checks if required startup_candles is more than ohlcv_candle_limit.
+        Requires a grace-period of 5 candles - so a startup-period up to 494 is allowed by default.
+        """
+        if startup_candles + 5 > self._ft_has['ohlcv_candle_limit']:
+            raise OperationalException(
+                f"This strategy requires {startup_candles} candles to start. "
+                f"{self.name} only provides {self._ft_has['ohlcv_candle_limit']}.")
+
     def exchange_has(self, endpoint: str) -> bool:
         """
         Checks if exchange implements a specific API endpoint.
@@ -330,88 +437,129 @@ class Exchange(object):
         """
         return endpoint in self._api.has and self._api.has[endpoint]
 
-    def symbol_amount_prec(self, pair, amount: float):
+    def amount_to_precision(self, pair: str, amount: float) -> float:
         '''
         Returns the amount to buy or sell to a precision the Exchange accepts
-        Rounded down
+        Reimplementation of ccxt internal methods - ensuring we can test the result is correct
+        based on our definitions.
         '''
         if self.markets[pair]['precision']['amount']:
-            symbol_prec = self.markets[pair]['precision']['amount']
-            big_amount = amount * pow(10, symbol_prec)
-            amount = floor(big_amount) / pow(10, symbol_prec)
+            amount = float(decimal_to_precision(amount, rounding_mode=TRUNCATE,
+                                                precision=self.markets[pair]['precision']['amount'],
+                                                counting_mode=self.precisionMode,
+                                                ))
+
         return amount
 
-    def symbol_price_prec(self, pair, price: float):
+    def price_to_precision(self, pair: str, price: float) -> float:
         '''
-        Returns the price buying or selling with to the precision the Exchange accepts
+        Returns the price rounded up to the precision the Exchange accepts.
+        Partial Reimplementation of ccxt internal method decimal_to_precision(),
+        which does not support rounding up
+        TODO: If ccxt supports ROUND_UP for decimal_to_precision(), we could remove this and
+        align with amount_to_precision().
         Rounds up
         '''
         if self.markets[pair]['precision']['price']:
-            symbol_prec = self.markets[pair]['precision']['price']
-            big_price = price * pow(10, symbol_prec)
-            price = ceil(big_price) / pow(10, symbol_prec)
+            # price = float(decimal_to_precision(price, rounding_mode=ROUND,
+            #                                    precision=self.markets[pair]['precision']['price'],
+            #                                    counting_mode=self.precisionMode,
+            #                                    ))
+            if self.precisionMode == TICK_SIZE:
+                precision = self.markets[pair]['precision']['price']
+                missing = price % precision
+                if missing != 0:
+                    price = price - missing + precision
+            else:
+                symbol_prec = self.markets[pair]['precision']['price']
+                big_price = price * pow(10, symbol_prec)
+                price = ceil(big_price) / pow(10, symbol_prec)
         return price
 
+    def price_get_one_pip(self, pair: str, price: float) -> float:
+        """
+        Get's the "1 pip" value for this pair.
+        Used in PriceFilter to calculate the 1pip movements.
+        """
+        precision = self.markets[pair]['precision']['price']
+        if self.precisionMode == TICK_SIZE:
+            return precision
+        else:
+            return 1 / pow(10, precision)
+
     def dry_run_order(self, pair: str, ordertype: str, side: str, amount: float,
                       rate: float, params: Dict = {}) -> Dict[str, Any]:
-        order_id = f'dry_run_{side}_{randint(0, 10**6)}'
-        dry_order = {  # TODO: additional entry should be added for stoploss limit
-            "id": order_id,
-            'pair': pair,
+        order_id = f'dry_run_{side}_{datetime.now().timestamp()}'
+        _amount = self.amount_to_precision(pair, amount)
+        dry_order = {
+            'id': order_id,
+            'symbol': pair,
             'price': rate,
-            'amount': amount,
-            "cost": amount * rate,
+            'average': rate,
+            'amount': _amount,
+            'cost': _amount * rate,
             'type': ordertype,
             'side': side,
-            'remaining': amount,
+            'remaining': _amount,
             'datetime': arrow.utcnow().isoformat(),
-            'status': "open",
+            'timestamp': int(arrow.utcnow().int_timestamp * 1000),
+            'status': "closed" if ordertype == "market" else "open",
             'fee': None,
-            "info": {}
+            'info': {}
         }
-        self._store_dry_order(dry_order)
+        self._store_dry_order(dry_order, pair)
+        # Copy order and close it - so the returned order is open unless it's a market order
         return dry_order
 
-    def _store_dry_order(self, dry_order: Dict) -> None:
+    def _store_dry_order(self, dry_order: Dict, pair: str) -> None:
         closed_order = dry_order.copy()
-        if closed_order["type"] in ["market", "limit"]:
+        if closed_order['type'] in ["market", "limit"]:
             closed_order.update({
-                "status": "closed",
-                "filled": closed_order["amount"],
-                "remaining": 0
-                })
+                'status': 'closed',
+                'filled': closed_order['amount'],
+                'remaining': 0,
+                'fee': {
+                    'currency': self.get_pair_quote_currency(pair),
+                    'cost': dry_order['cost'] * self.get_fee(pair),
+                    'rate': self.get_fee(pair)
+                }
+            })
+        if closed_order["type"] in ["stop_loss_limit"]:
+            closed_order["info"].update({"stopPrice": closed_order["price"]})
         self._dry_run_open_orders[closed_order["id"]] = closed_order
 
     def create_order(self, pair: str, ordertype: str, side: str, amount: float,
                      rate: float, params: Dict = {}) -> Dict:
         try:
             # Set the precision for amount and price(rate) as accepted by the exchange
-            amount = self.symbol_amount_prec(pair, amount)
+            amount = self.amount_to_precision(pair, amount)
             needs_price = (ordertype != 'market'
                            or self._api.options.get("createMarketBuyOrderRequiresPrice", False))
-            rate = self.symbol_price_prec(pair, rate) if needs_price else None
+            rate_for_order = self.price_to_precision(pair, rate) if needs_price else None
 
             return self._api.create_order(pair, ordertype, side,
-                                          amount, rate, params)
+                                          amount, rate_for_order, params)
 
         except ccxt.InsufficientFunds as e:
-            raise DependencyException(
-                f'Insufficient funds to create {ordertype} {side} order on market {pair}.'
-                f'Tried to {side} amount {amount} at rate {rate} (total {rate * amount}).'
-                f'Message: {e}')
+            raise InsufficientFundsError(
+                f'Insufficient funds to create {ordertype} {side} order on market {pair}. '
+                f'Tried to {side} amount {amount} at rate {rate}.'
+                f'Message: {e}') from e
         except ccxt.InvalidOrder as e:
-            raise DependencyException(
-                f'Could not create {ordertype} {side} order on market {pair}.'
-                f'Tried to {side} amount {amount} at rate {rate} (total {rate * amount}).'
-                f'Message: {e}')
+            raise ExchangeError(
+                f'Could not create {ordertype} {side} order on market {pair}. '
+                f'Tried to {side} amount {amount} at rate {rate}. '
+                f'Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
         except (ccxt.NetworkError, ccxt.ExchangeError) as e:
             raise TemporaryError(
-                f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}')
+                f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
-            raise OperationalException(e)
+            raise OperationalException(e) from e
 
     def buy(self, pair: str, ordertype: str, amount: float,
-            rate: float, time_in_force) -> Dict:
+            rate: float, time_in_force: str) -> Dict:
 
         if self._config['dry_run']:
             dry_order = self.dry_run_order(pair, ordertype, "buy", amount, rate)
@@ -424,7 +572,7 @@ class Exchange(object):
         return self.create_order(pair, ordertype, 'buy', amount, rate, params)
 
     def sell(self, pair: str, ordertype: str, amount: float,
-             rate: float, time_in_force='gtc') -> Dict:
+             rate: float, time_in_force: str = 'gtc') -> Dict:
 
         if self._config['dry_run']:
             dry_order = self.dry_run_order(pair, ordertype, "sell", amount, rate)
@@ -436,38 +584,30 @@ class Exchange(object):
 
         return self.create_order(pair, ordertype, 'sell', amount, rate, params)
 
-    def stoploss_limit(self, pair: str, amount: float, stop_price: float, rate: float) -> Dict:
+    def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
         """
-        creates a stoploss limit order.
-        NOTICE: it is not supported by all exchanges. only binance is tested for now.
-        TODO: implementation maybe needs to be moved to the binance subclass
+        Verify stop_loss against stoploss-order value (limit or price)
+        Returns True if adjustment is necessary.
         """
-        ordertype = "stop_loss_limit"
+        raise OperationalException(f"stoploss is not implemented for {self.name}.")
 
-        stop_price = self.symbol_price_prec(pair, stop_price)
+    def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
+        """
+        creates a stoploss order.
+        The precise ordertype is determined by the order_types dict or exchange default.
+        Since ccxt does not unify stoploss-limit orders yet, this needs to be implemented in each
+        exchange's subclass.
+        The exception below should never raise, since we disallow
+        starting the bot in validate_ordertypes()
+        Note: Changes to this interface need to be applied to all sub-classes too.
+        """
 
-        # Ensure rate is less than stop price
-        if stop_price <= rate:
-            raise OperationalException(
-                'In stoploss limit order, stop price should be more than limit price')
-
-        if self._config['dry_run']:
-            dry_order = self.dry_run_order(
-                pair, ordertype, "sell", amount, stop_price)
-            return dry_order
-
-        params = self._params.copy()
-        params.update({'stopPrice': stop_price})
-
-        order = self.create_order(pair, ordertype, 'sell', amount, rate, params)
-        logger.info('stoploss limit order added for %s. '
-                    'stop price: %s. limit: %s' % (pair, stop_price, rate))
-        return order
+        raise OperationalException(f"stoploss is not implemented for {self.name}.")
 
     @retrier
     def get_balance(self, currency: str) -> float:
         if self._config['dry_run']:
-            return constants.DRY_RUN_WALLET
+            return self._config['dry_run_wallet']
 
         # ccxt exception is already handled by get_balances
         balances = self.get_balances()
@@ -491,11 +631,13 @@ class Exchange(object):
             balances.pop("used", None)
 
             return balances
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
         except (ccxt.NetworkError, ccxt.ExchangeError) as e:
             raise TemporaryError(
-                f'Could not get balance due to {e.__class__.__name__}. Message: {e}')
+                f'Could not get balance due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
-            raise OperationalException(e)
+            raise OperationalException(e) from e
 
     @retrier
     def get_tickers(self) -> Dict:
@@ -503,236 +645,513 @@ class Exchange(object):
             return self._api.fetch_tickers()
         except ccxt.NotSupported as e:
             raise OperationalException(
-                f'Exchange {self._api.name} does not support fetching tickers in batch.'
-                f'Message: {e}')
+                f'Exchange {self._api.name} does not support fetching tickers in batch. '
+                f'Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
         except (ccxt.NetworkError, ccxt.ExchangeError) as e:
             raise TemporaryError(
-                f'Could not load tickers due to {e.__class__.__name__}. Message: {e}')
+                f'Could not load tickers due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
-            raise OperationalException(e)
+            raise OperationalException(e) from e
 
     @retrier
-    def get_ticker(self, pair: str, refresh: Optional[bool] = True) -> dict:
-        if refresh or pair not in self._cached_ticker.keys():
-            try:
-                if pair not in self._api.markets or not self._api.markets[pair].get('active'):
-                    raise DependencyException(f"Pair {pair} not available")
-                data = self._api.fetch_ticker(pair)
-                try:
-                    self._cached_ticker[pair] = {
-                        'bid': float(data['bid']),
-                        'ask': float(data['ask']),
-                    }
-                except KeyError:
-                    logger.debug("Could not cache ticker data for %s", pair)
-                return data
-            except (ccxt.NetworkError, ccxt.ExchangeError) as e:
-                raise TemporaryError(
-                    f'Could not load ticker due to {e.__class__.__name__}. Message: {e}')
-            except ccxt.BaseError as e:
-                raise OperationalException(e)
-        else:
-            logger.info("returning cached ticker-data for %s", pair)
-            return self._cached_ticker[pair]
+    def fetch_ticker(self, pair: str) -> dict:
+        try:
+            if pair not in self._api.markets or not self._api.markets[pair].get('active'):
+                raise ExchangeError(f"Pair {pair} not available")
+            data = self._api.fetch_ticker(pair)
+            return data
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not load ticker due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
 
-    def get_history(self, pair: str, ticker_interval: str,
-                    since_ms: int) -> List:
+    def get_historic_ohlcv(self, pair: str, timeframe: str,
+                           since_ms: int) -> List:
         """
-        Gets candle history using asyncio and returns the list of candles.
-        Handles all async doing.
+        Get candle history using asyncio and returns the list of candles.
+        Handles all async work for this.
+        Async over one pair, assuming we get `self._ohlcv_candle_limit` candles per call.
+        :param pair: Pair to download
+        :param timeframe: Timeframe to get data for
+        :param since_ms: Timestamp in milliseconds to get history from
+        :returns List with candle (OHLCV) data
         """
         return asyncio.get_event_loop().run_until_complete(
-            self._async_get_history(pair=pair, ticker_interval=ticker_interval,
-                                    since_ms=since_ms))
+            self._async_get_historic_ohlcv(pair=pair, timeframe=timeframe,
+                                           since_ms=since_ms))
 
-    async def _async_get_history(self, pair: str,
-                                 ticker_interval: str,
-                                 since_ms: int) -> List:
+    async def _async_get_historic_ohlcv(self, pair: str,
+                                        timeframe: str,
+                                        since_ms: int) -> List:
+        """
+        Download historic ohlcv
+        """
 
-        one_call = timeframe_to_msecs(ticker_interval) * self._ohlcv_candle_limit
+        one_call = timeframe_to_msecs(timeframe) * self._ohlcv_candle_limit
         logger.debug(
             "one_call: %s msecs (%s)",
             one_call,
             arrow.utcnow().shift(seconds=one_call // 1000).humanize(only_distance=True)
         )
         input_coroutines = [self._async_get_candle_history(
-            pair, ticker_interval, since) for since in
-            range(since_ms, arrow.utcnow().timestamp * 1000, one_call)]
+            pair, timeframe, since) for since in
+            range(since_ms, arrow.utcnow().int_timestamp * 1000, one_call)]
 
-        tickers = await asyncio.gather(*input_coroutines, return_exceptions=True)
+        results = await asyncio.gather(*input_coroutines, return_exceptions=True)
 
-        # Combine tickers
+        # Combine gathered results
         data: List = []
-        for p, ticker_interval, ticker in tickers:
+        for res in results:
+            if isinstance(res, Exception):
+                logger.warning("Async code raised an exception: %s", res.__class__.__name__)
+                continue
+            # Deconstruct tuple if it's not an exception
+            p, _, new_data = res
             if p == pair:
-                data.extend(ticker)
+                data.extend(new_data)
         # Sort data again after extending the result - above calls return in "async order"
         data = sorted(data, key=lambda x: x[0])
-        logger.info("downloaded %s with length %s.", pair, len(data))
+        logger.info("Downloaded data for %s with length %s.", pair, len(data))
         return data
 
-    def refresh_latest_ohlcv(self, pair_list: List[Tuple[str, str]]) -> List[Tuple[str, List]]:
+    def refresh_latest_ohlcv(self, pair_list: ListPairsWithTimeframes) -> List[Tuple[str, List]]:
         """
-        Refresh in-memory ohlcv asyncronously and set `_klines` with the result
+        Refresh in-memory OHLCV asynchronously and set `_klines` with the result
+        Loops asynchronously over pair_list and downloads all pairs async (semi-parallel).
+        Only used in the dataprovider.refresh() method.
+        :param pair_list: List of 2 element tuples containing pair, interval to refresh
+        :return: TODO: return value is only used in the tests, get rid of it
         """
-        logger.debug("Refreshing ohlcv data for %d pairs", len(pair_list))
+        logger.debug("Refreshing candle (OHLCV) data for %d pairs", len(pair_list))
 
         input_coroutines = []
 
         # Gather coroutines to run
-        for pair, ticker_interval in set(pair_list):
-            if (not ((pair, ticker_interval) in self._klines)
-                    or self._now_is_time_to_refresh(pair, ticker_interval)):
-                input_coroutines.append(self._async_get_candle_history(pair, ticker_interval))
+        for pair, timeframe in set(pair_list):
+            if (not ((pair, timeframe) in self._klines)
+                    or self._now_is_time_to_refresh(pair, timeframe)):
+                input_coroutines.append(self._async_get_candle_history(pair, timeframe))
             else:
                 logger.debug(
-                    "Using cached ohlcv data for pair %s, interval %s ...",
-                    pair, ticker_interval
+                    "Using cached candle (OHLCV) data for pair %s, timeframe %s ...",
+                    pair, timeframe
                 )
 
-        tickers = asyncio.get_event_loop().run_until_complete(
+        results = asyncio.get_event_loop().run_until_complete(
             asyncio.gather(*input_coroutines, return_exceptions=True))
 
         # handle caching
-        for res in tickers:
+        for res in results:
             if isinstance(res, Exception):
                 logger.warning("Async code raised an exception: %s", res.__class__.__name__)
                 continue
-            pair = res[0]
-            ticker_interval = res[1]
-            ticks = res[2]
+            # Deconstruct tuple (has 3 elements)
+            pair, timeframe, ticks = res
             # keeping last candle time as last refreshed time of the pair
             if ticks:
-                self._pairs_last_refresh_time[(pair, ticker_interval)] = ticks[-1][0] // 1000
+                self._pairs_last_refresh_time[(pair, timeframe)] = ticks[-1][0] // 1000
             # keeping parsed dataframe in cache
-            self._klines[(pair, ticker_interval)] = parse_ticker_dataframe(
-                ticks, ticker_interval, pair=pair, fill_missing=True,
+            self._klines[(pair, timeframe)] = ohlcv_to_dataframe(
+                ticks, timeframe, pair=pair, fill_missing=True,
                 drop_incomplete=self._ohlcv_partial_candle)
-        return tickers
 
-    def _now_is_time_to_refresh(self, pair: str, ticker_interval: str) -> bool:
-        # Calculating ticker interval in seconds
-        interval_in_sec = timeframe_to_seconds(ticker_interval)
+        return results
 
-        return not ((self._pairs_last_refresh_time.get((pair, ticker_interval), 0)
-                     + interval_in_sec) >= arrow.utcnow().timestamp)
+    def _now_is_time_to_refresh(self, pair: str, timeframe: str) -> bool:
+        # Timeframe in seconds
+        interval_in_sec = timeframe_to_seconds(timeframe)
+
+        return not ((self._pairs_last_refresh_time.get((pair, timeframe), 0)
+                     + interval_in_sec) >= arrow.utcnow().int_timestamp)
 
     @retrier_async
-    async def _async_get_candle_history(self, pair: str, ticker_interval: str,
+    async def _async_get_candle_history(self, pair: str, timeframe: str,
                                         since_ms: Optional[int] = None) -> Tuple[str, str, List]:
         """
-        Asyncronously gets candle histories using fetch_ohlcv
-        returns tuple: (pair, ticker_interval, ohlcv_list)
+        Asynchronously get candle history data using fetch_ohlcv
+        returns tuple: (pair, timeframe, ohlcv_list)
         """
         try:
-            # fetch ohlcv asynchronously
+            # Fetch OHLCV asynchronously
             s = '(' + arrow.get(since_ms // 1000).isoformat() + ') ' if since_ms is not None else ''
             logger.debug(
                 "Fetching pair %s, interval %s, since %s %s...",
-                pair, ticker_interval, since_ms, s
+                pair, timeframe, since_ms, s
             )
 
-            data = await self._api_async.fetch_ohlcv(pair, timeframe=ticker_interval,
+            data = await self._api_async.fetch_ohlcv(pair, timeframe=timeframe,
                                                      since=since_ms)
 
-            # Because some exchange sort Tickers ASC and other DESC.
-            # Ex: Bittrex returns a list of tickers ASC (oldest first, newest last)
-            # when GDAX returns a list of tickers DESC (newest first, oldest last)
+            # Some exchanges sort OHLCV in ASC order and others in DESC.
+            # Ex: Bittrex returns the list of OHLCV in ASC order (oldest first, newest last)
+            # while GDAX returns the list of OHLCV in DESC order (newest first, oldest last)
             # Only sort if necessary to save computing time
             try:
                 if data and data[0][0] > data[-1][0]:
                     data = sorted(data, key=lambda x: x[0])
             except IndexError:
                 logger.exception("Error loading %s. Result was %s.", pair, data)
-                return pair, ticker_interval, []
-            logger.debug("Done fetching pair %s, interval %s ...", pair, ticker_interval)
-            return pair, ticker_interval, data
+                return pair, timeframe, []
+            logger.debug("Done fetching pair %s, interval %s ...", pair, timeframe)
+            return pair, timeframe, data
 
         except ccxt.NotSupported as e:
             raise OperationalException(
-                f'Exchange {self._api.name} does not support fetching historical candlestick data.'
-                f'Message: {e}')
+                f'Exchange {self._api.name} does not support fetching historical '
+                f'candle (OHLCV) data. Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
         except (ccxt.NetworkError, ccxt.ExchangeError) as e:
-            raise TemporaryError(
-                f'Could not load ticker history due to {e.__class__.__name__}. Message: {e}')
+            raise TemporaryError(f'Could not fetch historical candle (OHLCV) data '
+                                 f'for pair {pair} due to {e.__class__.__name__}. '
+                                 f'Message: {e}') from e
         except ccxt.BaseError as e:
-            raise OperationalException(f'Could not fetch ticker data. Msg: {e}')
+            raise OperationalException(f'Could not fetch historical candle (OHLCV) data '
+                                       f'for pair {pair}. Message: {e}') from e
+
+    @retrier_async
+    async def _async_fetch_trades(self, pair: str,
+                                  since: Optional[int] = None,
+                                  params: Optional[dict] = None) -> List[List]:
+        """
+        Asyncronously gets trade history using fetch_trades.
+        Handles exchange errors, does one call to the exchange.
+        :param pair: Pair to fetch trade data for
+        :param since: Since as integer timestamp in milliseconds
+        returns: List of dicts containing trades
+        """
+        try:
+            # fetch trades asynchronously
+            if params:
+                logger.debug("Fetching trades for pair %s, params: %s ", pair, params)
+                trades = await self._api_async.fetch_trades(pair, params=params, limit=1000)
+            else:
+                logger.debug(
+                    "Fetching trades for pair %s, since %s %s...",
+                    pair,  since,
+                    '(' + arrow.get(since // 1000).isoformat() + ') ' if since is not None else ''
+                )
+                trades = await self._api_async.fetch_trades(pair, since=since, limit=1000)
+            return trades_dict_to_list(trades)
+        except ccxt.NotSupported as e:
+            raise OperationalException(
+                f'Exchange {self._api.name} does not support fetching historical trade data.'
+                f'Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(f'Could not load trade history due to {e.__class__.__name__}. '
+                                 f'Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(f'Could not fetch trade data. Msg: {e}') from e
+
+    async def _async_get_trade_history_id(self, pair: str,
+                                          until: int,
+                                          since: Optional[int] = None,
+                                          from_id: Optional[str] = None) -> Tuple[str, List[List]]:
+        """
+        Asyncronously gets trade history using fetch_trades
+        use this when exchange uses id-based iteration (check `self._trades_pagination`)
+        :param pair: Pair to fetch trade data for
+        :param since: Since as integer timestamp in milliseconds
+        :param until: Until as integer timestamp in milliseconds
+        :param from_id: Download data starting with ID (if id is known). Ignores "since" if set.
+        returns tuple: (pair, trades-list)
+        """
+
+        trades: List[List] = []
+
+        if not from_id:
+            # Fetch first elements using timebased method to get an ID to paginate on
+            # Depending on the Exchange, this can introduce a drift at the start of the interval
+            # of up to an hour.
+            # e.g. Binance returns the "last 1000" candles within a 1h time interval
+            # - so we will miss the first trades.
+            t = await self._async_fetch_trades(pair, since=since)
+            # DEFAULT_TRADES_COLUMNS: 0 -> timestamp
+            # DEFAULT_TRADES_COLUMNS: 1 -> id
+            from_id = t[-1][1]
+            trades.extend(t[:-1])
+        while True:
+            t = await self._async_fetch_trades(pair,
+                                               params={self._trades_pagination_arg: from_id})
+            if len(t):
+                # Skip last id since its the key for the next call
+                trades.extend(t[:-1])
+                if from_id == t[-1][1] or t[-1][0] > until:
+                    logger.debug(f"Stopping because from_id did not change. "
+                                 f"Reached {t[-1][0]} > {until}")
+                    # Reached the end of the defined-download period - add last trade as well.
+                    trades.extend(t[-1:])
+                    break
+
+                from_id = t[-1][1]
+            else:
+                break
+
+        return (pair, trades)
+
+    async def _async_get_trade_history_time(self, pair: str, until: int,
+                                            since: Optional[int] = None) -> Tuple[str, List[List]]:
+        """
+        Asyncronously gets trade history using fetch_trades,
+        when the exchange uses time-based iteration (check `self._trades_pagination`)
+        :param pair: Pair to fetch trade data for
+        :param since: Since as integer timestamp in milliseconds
+        :param until: Until as integer timestamp in milliseconds
+        returns tuple: (pair, trades-list)
+        """
+
+        trades: List[List] = []
+        # DEFAULT_TRADES_COLUMNS: 0 -> timestamp
+        # DEFAULT_TRADES_COLUMNS: 1 -> id
+        while True:
+            t = await self._async_fetch_trades(pair, since=since)
+            if len(t):
+                since = t[-1][1]
+                trades.extend(t)
+                # Reached the end of the defined-download period
+                if until and t[-1][0] > until:
+                    logger.debug(
+                        f"Stopping because until was reached. {t[-1][0]} > {until}")
+                    break
+            else:
+                break
+
+        return (pair, trades)
+
+    async def _async_get_trade_history(self, pair: str,
+                                       since: Optional[int] = None,
+                                       until: Optional[int] = None,
+                                       from_id: Optional[str] = None) -> Tuple[str, List[List]]:
+        """
+        Async wrapper handling downloading trades using either time or id based methods.
+        """
+
+        logger.debug(f"_async_get_trade_history(), pair: {pair}, "
+                     f"since: {since}, until: {until}, from_id: {from_id}")
+
+        if until is None:
+            until = ccxt.Exchange.milliseconds()
+            logger.debug(f"Exchange milliseconds: {until}")
+
+        if self._trades_pagination == 'time':
+            return await self._async_get_trade_history_time(
+                pair=pair, since=since, until=until)
+        elif self._trades_pagination == 'id':
+            return await self._async_get_trade_history_id(
+                pair=pair, since=since, until=until, from_id=from_id
+            )
+        else:
+            raise OperationalException(f"Exchange {self.name} does use neither time, "
+                                       f"nor id based pagination")
+
+    def get_historic_trades(self, pair: str,
+                            since: Optional[int] = None,
+                            until: Optional[int] = None,
+                            from_id: Optional[str] = None) -> Tuple[str, List]:
+        """
+        Get trade history data using asyncio.
+        Handles all async work and returns the list of candles.
+        Async over one pair, assuming we get `self._ohlcv_candle_limit` candles per call.
+        :param pair: Pair to download
+        :param since: Timestamp in milliseconds to get history from
+        :param until: Timestamp in milliseconds. Defaults to current timestamp if not defined.
+        :param from_id: Download data starting with ID (if id is known)
+        :returns List of trade data
+        """
+        if not self.exchange_has("fetchTrades"):
+            raise OperationalException("This exchange does not suport downloading Trades.")
+
+        return asyncio.get_event_loop().run_until_complete(
+            self._async_get_trade_history(pair=pair, since=since,
+                                          until=until, from_id=from_id))
+
+    def check_order_canceled_empty(self, order: Dict) -> bool:
+        """
+        Verify if an order has been cancelled without being partially filled
+        :param order: Order dict as returned from fetch_order()
+        :return: True if order has been cancelled without being filled, False otherwise.
+        """
+        return order.get('status') in ('closed', 'canceled') and order.get('filled') == 0.0
 
     @retrier
-    def cancel_order(self, order_id: str, pair: str) -> None:
+    def cancel_order(self, order_id: str, pair: str) -> Dict:
         if self._config['dry_run']:
-            return
+            order = self._dry_run_open_orders.get(order_id)
+            if order:
+                order.update({'status': 'canceled', 'filled': 0.0, 'remaining': order['amount']})
+                return order
+            else:
+                return {}
 
         try:
             return self._api.cancel_order(order_id, pair)
         except ccxt.InvalidOrder as e:
             raise InvalidOrderException(
-                f'Could not cancel order. Message: {e}')
+                f'Could not cancel order. Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
         except (ccxt.NetworkError, ccxt.ExchangeError) as e:
             raise TemporaryError(
-                f'Could not cancel order due to {e.__class__.__name__}. Message: {e}')
+                f'Could not cancel order due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
-            raise OperationalException(e)
+            raise OperationalException(e) from e
 
-    @retrier
-    def get_order(self, order_id: str, pair: str) -> Dict:
+    # Assign method to cancel_stoploss_order to allow easy overriding in other classes
+    cancel_stoploss_order = cancel_order
+
+    def is_cancel_order_result_suitable(self, corder) -> bool:
+        if not isinstance(corder, dict):
+            return False
+
+        required = ('fee', 'status', 'amount')
+        return all(k in corder for k in required)
+
+    def cancel_order_with_result(self, order_id: str, pair: str, amount: float) -> Dict:
+        """
+        Cancel order returning a result.
+        Creates a fake result if cancel order returns a non-usable result
+        and fetch_order does not work (certain exchanges don't return cancelled orders)
+        :param order_id: Orderid to cancel
+        :param pair: Pair corresponding to order_id
+        :param amount: Amount to use for fake response
+        :return: Result from either cancel_order if usable, or fetch_order
+        """
+        try:
+            corder = self.cancel_order(order_id, pair)
+            if self.is_cancel_order_result_suitable(corder):
+                return corder
+        except InvalidOrderException:
+            logger.warning(f"Could not cancel order {order_id} for {pair}.")
+        try:
+            order = self.fetch_order(order_id, pair)
+        except InvalidOrderException:
+            logger.warning(f"Could not fetch cancelled order {order_id}.")
+            order = {'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}}
+
+        return order
+
+    @retrier(retries=API_FETCH_ORDER_RETRY_COUNT)
+    def fetch_order(self, order_id: str, pair: str) -> Dict:
         if self._config['dry_run']:
-            order = self._dry_run_open_orders[order_id]
-            return order
+            try:
+                order = self._dry_run_open_orders[order_id]
+                return order
+            except KeyError as e:
+                # Gracefully handle errors with dry-run orders.
+                raise InvalidOrderException(
+                    f'Tried to get an invalid dry-run-order (id: {order_id}). Message: {e}') from e
         try:
             return self._api.fetch_order(order_id, pair)
+        except ccxt.OrderNotFound as e:
+            raise RetryableOrderError(
+                f'Order not found (pair: {pair} id: {order_id}). Message: {e}') from e
         except ccxt.InvalidOrder as e:
             raise InvalidOrderException(
-                f'Tried to get an invalid order (id: {order_id}). Message: {e}')
+                f'Tried to get an invalid order (pair: {pair} id: {order_id}). Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
         except (ccxt.NetworkError, ccxt.ExchangeError) as e:
             raise TemporaryError(
-                f'Could not get order due to {e.__class__.__name__}. Message: {e}')
+                f'Could not get order due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
-            raise OperationalException(e)
+            raise OperationalException(e) from e
+
+    # Assign method to fetch_stoploss_order to allow easy overriding in other classes
+    fetch_stoploss_order = fetch_order
+
+    def fetch_order_or_stoploss_order(self, order_id: str, pair: str,
+                                      stoploss_order: bool = False) -> Dict:
+        """
+        Simple wrapper calling either fetch_order or fetch_stoploss_order depending on
+        the stoploss_order parameter
+        :param stoploss_order: If true, uses fetch_stoploss_order, otherwise fetch_order.
+        """
+        if stoploss_order:
+            return self.fetch_stoploss_order(order_id, pair)
+        return self.fetch_order(order_id, pair)
+
+    @staticmethod
+    def get_next_limit_in_list(limit: int, limit_range: Optional[List[int]]):
+        """
+        Get next greater value in the list.
+        Used by fetch_l2_order_book if the api only supports a limited range
+        """
+        if not limit_range:
+            return limit
+        return min([x for x in limit_range if limit <= x] + [max(limit_range)])
 
     @retrier
-    def get_order_book(self, pair: str, limit: int = 100) -> dict:
+    def fetch_l2_order_book(self, pair: str, limit: int = 100) -> dict:
         """
-        get order book level 2 from exchange
-
-        Notes:
-        20180619: bittrex doesnt support limits -.-
+        Get L2 order book from exchange.
+        Can be limited to a certain amount (if supported).
+        Returns a dict in the format
+        {'asks': [price, volume], 'bids': [price, volume]}
         """
+        limit1 = self.get_next_limit_in_list(limit, self._ft_has['l2_limit_range'])
         try:
 
-            return self._api.fetch_l2_order_book(pair, limit)
+            return self._api.fetch_l2_order_book(pair, limit1)
         except ccxt.NotSupported as e:
             raise OperationalException(
                 f'Exchange {self._api.name} does not support fetching order book.'
-                f'Message: {e}')
+                f'Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
         except (ccxt.NetworkError, ccxt.ExchangeError) as e:
             raise TemporaryError(
-                f'Could not get order book due to {e.__class__.__name__}. Message: {e}')
+                f'Could not get order book due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
-            raise OperationalException(e)
+            raise OperationalException(e) from e
 
     @retrier
     def get_trades_for_order(self, order_id: str, pair: str, since: datetime) -> List:
+        """
+        Fetch Orders using the "fetch_my_trades" endpoint and filter them by order-id.
+        The "since" argument passed in is coming from the database and is in UTC,
+        as timezone-native datetime object.
+        From the python documentation:
+            > Naive datetime instances are assumed to represent local time
+        Therefore, calling "since.timestamp()" will get the UTC timestamp, after applying the
+        transformation from local timezone to UTC.
+        This works for timezones UTC+ since then the result will contain trades from a few hours
+        instead of from the last 5 seconds, however fails for UTC- timezones,
+        since we're then asking for trades with a "since" argument in the future.
+
+        :param order_id order_id: Order-id as given when creating the order
+        :param pair: Pair the order is for
+        :param since: datetime object of the order creation time. Assumes object is in UTC.
+        """
         if self._config['dry_run']:
             return []
         if not self.exchange_has('fetchMyTrades'):
             return []
         try:
             # Allow 5s offset to catch slight time offsets (discovered in #1185)
-            my_trades = self._api.fetch_my_trades(pair, since.timestamp() - 5)
+            # since needs to be int in milliseconds
+            my_trades = self._api.fetch_my_trades(
+                pair, int((since.replace(tzinfo=timezone.utc).timestamp() - 5) * 1000))
             matched_trades = [trade for trade in my_trades if trade['order'] == order_id]
 
             return matched_trades
-
-        except ccxt.NetworkError as e:
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
             raise TemporaryError(
-                f'Could not get trades due to networking error. Message: {e}')
+                f'Could not get trades due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
-            raise OperationalException(e)
+            raise OperationalException(e) from e
 
     @retrier
-    def get_fee(self, symbol='ETH/BTC', type='', side='', amount=1,
-                price=1, taker_or_maker='maker') -> float:
+    def get_fee(self, symbol: str, type: str = '', side: str = '', amount: float = 1,
+                price: float = 1, taker_or_maker: str = 'maker') -> float:
         try:
             # validate that markets are loaded before trying to get fee
             if self._api.markets is None or len(self._api.markets) == 0:
@@ -740,47 +1159,161 @@ class Exchange(object):
 
             return self._api.calculate_fee(symbol=symbol, type=type, side=side, amount=amount,
                                            price=price, takerOrMaker=taker_or_maker)['rate']
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
         except (ccxt.NetworkError, ccxt.ExchangeError) as e:
             raise TemporaryError(
-                f'Could not get fee info due to {e.__class__.__name__}. Message: {e}')
+                f'Could not get fee info due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
-            raise OperationalException(e)
+            raise OperationalException(e) from e
+
+    @staticmethod
+    def order_has_fee(order: Dict) -> bool:
+        """
+        Verifies if the passed in order dict has the needed keys to extract fees,
+        and that these keys (currency, cost) are not empty.
+        :param order: Order or trade (one trade) dict
+        :return: True if the fee substructure contains currency and cost, false otherwise
+        """
+        if not isinstance(order, dict):
+            return False
+        return ('fee' in order and order['fee'] is not None
+                and (order['fee'].keys() >= {'currency', 'cost'})
+                and order['fee']['currency'] is not None
+                and order['fee']['cost'] is not None
+                )
+
+    def calculate_fee_rate(self, order: Dict) -> Optional[float]:
+        """
+        Calculate fee rate if it's not given by the exchange.
+        :param order: Order or trade (one trade) dict
+        """
+        if order['fee'].get('rate') is not None:
+            return order['fee'].get('rate')
+        fee_curr = order['fee']['currency']
+        # Calculate fee based on order details
+        if fee_curr in self.get_pair_base_currency(order['symbol']):
+            # Base currency - divide by amount
+            return round(
+                order['fee']['cost'] / safe_value_fallback2(order, order, 'filled', 'amount'), 8)
+        elif fee_curr in self.get_pair_quote_currency(order['symbol']):
+            # Quote currency - divide by cost
+            return round(order['fee']['cost'] / order['cost'], 8) if order['cost'] else None
+        else:
+            # If Fee currency is a different currency
+            if not order['cost']:
+                # If cost is None or 0.0 -> falsy, return None
+                return None
+            try:
+                comb = self.get_valid_pair_combination(fee_curr, self._config['stake_currency'])
+                tick = self.fetch_ticker(comb)
+
+                fee_to_quote_rate = safe_value_fallback2(tick, tick, 'last', 'ask')
+                return round((order['fee']['cost'] * fee_to_quote_rate) / order['cost'], 8)
+            except ExchangeError:
+                return None
+
+    def extract_cost_curr_rate(self, order: Dict) -> Tuple[float, str, Optional[float]]:
+        """
+        Extract tuple of cost, currency, rate.
+        Requires order_has_fee to run first!
+        :param order: Order or trade (one trade) dict
+        :return: Tuple with cost, currency, rate of the given fee dict
+        """
+        return (order['fee']['cost'],
+                order['fee']['currency'],
+                self.calculate_fee_rate(order))
 
 
-def is_exchange_bad(exchange: str) -> bool:
-    return exchange in ['bitmex', 'bitstamp']
+def is_exchange_bad(exchange_name: str) -> bool:
+    return exchange_name in BAD_EXCHANGES
 
 
-def is_exchange_available(exchange: str, ccxt_module=None) -> bool:
-    return exchange in available_exchanges(ccxt_module)
+def get_exchange_bad_reason(exchange_name: str) -> str:
+    return BAD_EXCHANGES.get(exchange_name, "")
 
 
-def is_exchange_officially_supported(exchange: str) -> bool:
-    return exchange in ['bittrex', 'binance']
+def is_exchange_known_ccxt(exchange_name: str, ccxt_module: CcxtModuleType = None) -> bool:
+    return exchange_name in ccxt_exchanges(ccxt_module)
 
 
-def available_exchanges(ccxt_module=None) -> List[str]:
+def is_exchange_officially_supported(exchange_name: str) -> bool:
+    return exchange_name in ['bittrex', 'binance', 'kraken']
+
+
+def ccxt_exchanges(ccxt_module: CcxtModuleType = None) -> List[str]:
+    """
+    Return the list of all exchanges known to ccxt
+    """
     return ccxt_module.exchanges if ccxt_module is not None else ccxt.exchanges
 
 
-def timeframe_to_seconds(ticker_interval: str) -> int:
+def available_exchanges(ccxt_module: CcxtModuleType = None) -> List[str]:
+    """
+    Return exchanges available to the bot, i.e. non-bad exchanges in the ccxt list
+    """
+    exchanges = ccxt_exchanges(ccxt_module)
+    return [x for x in exchanges if not is_exchange_bad(x)]
+
+
+def timeframe_to_seconds(timeframe: str) -> int:
     """
     Translates the timeframe interval value written in the human readable
     form ('1m', '5m', '1h', '1d', '1w', etc.) to the number
     of seconds for one timeframe interval.
     """
-    return ccxt.Exchange.parse_timeframe(ticker_interval)
+    return ccxt.Exchange.parse_timeframe(timeframe)
 
 
-def timeframe_to_minutes(ticker_interval: str) -> int:
+def timeframe_to_minutes(timeframe: str) -> int:
     """
-    Same as above, but returns minutes.
+    Same as timeframe_to_seconds, but returns minutes.
     """
-    return ccxt.Exchange.parse_timeframe(ticker_interval) // 60
+    return ccxt.Exchange.parse_timeframe(timeframe) // 60
 
 
-def timeframe_to_msecs(ticker_interval: str) -> int:
+def timeframe_to_msecs(timeframe: str) -> int:
     """
-    Same as above, but returns milliseconds.
+    Same as timeframe_to_seconds, but returns milliseconds.
     """
-    return ccxt.Exchange.parse_timeframe(ticker_interval) * 1000
+    return ccxt.Exchange.parse_timeframe(timeframe) * 1000
+
+
+def timeframe_to_prev_date(timeframe: str, date: datetime = None) -> datetime:
+    """
+    Use Timeframe and determine last possible candle.
+    :param timeframe: timeframe in string format (e.g. "5m")
+    :param date: date to use. Defaults to utcnow()
+    :returns: date of previous candle (with utc timezone)
+    """
+    if not date:
+        date = datetime.now(timezone.utc)
+
+    new_timestamp = ccxt.Exchange.round_timeframe(timeframe, date.timestamp() * 1000,
+                                                  ROUND_DOWN) // 1000
+    return datetime.fromtimestamp(new_timestamp, tz=timezone.utc)
+
+
+def timeframe_to_next_date(timeframe: str, date: datetime = None) -> datetime:
+    """
+    Use Timeframe and determine next candle.
+    :param timeframe: timeframe in string format (e.g. "5m")
+    :param date: date to use. Defaults to utcnow()
+    :returns: date of next candle (with utc timezone)
+    """
+    if not date:
+        date = datetime.now(timezone.utc)
+    new_timestamp = ccxt.Exchange.round_timeframe(timeframe, date.timestamp() * 1000,
+                                                  ROUND_UP) // 1000
+    return datetime.fromtimestamp(new_timestamp, tz=timezone.utc)
+
+
+def market_is_active(market: Dict) -> bool:
+    """
+    Return True if the market is active.
+    """
+    # "It's active, if the active flag isn't explicitly set to false. If it's missing or
+    # true then it's true. If it's undefined, then it's most likely true, but not 100% )"
+    # See https://github.com/ccxt/ccxt/issues/4874,
+    # https://github.com/ccxt/ccxt/issues/4075#issuecomment-434760520
+    return market.get('active', True) is not False
diff --git a/freqtrade/exchange/ftx.py b/freqtrade/exchange/ftx.py
new file mode 100644
index 000000000..f05490cbb
--- /dev/null
+++ b/freqtrade/exchange/ftx.py
@@ -0,0 +1,136 @@
+""" FTX exchange subclass """
+import logging
+from typing import Any, Dict
+
+import ccxt
+
+from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
+                                  OperationalException, TemporaryError)
+from freqtrade.exchange import Exchange
+from freqtrade.exchange.common import API_FETCH_ORDER_RETRY_COUNT, retrier
+
+
+logger = logging.getLogger(__name__)
+
+
+class Ftx(Exchange):
+
+    _ft_has: Dict = {
+        "stoploss_on_exchange": True,
+        "ohlcv_candle_limit": 1500,
+    }
+
+    def market_is_tradable(self, market: Dict[str, Any]) -> bool:
+        """
+        Check if the market symbol is tradable by Freqtrade.
+        Default checks + check if pair is spot pair (no futures trading yet).
+        """
+        parent_check = super().market_is_tradable(market)
+
+        return (parent_check and
+                market.get('spot', False) is True)
+
+    def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
+        """
+        Verify stop_loss against stoploss-order value (limit or price)
+        Returns True if adjustment is necessary.
+        """
+        return order['type'] == 'stop' and stop_loss > float(order['price'])
+
+    @retrier(retries=0)
+    def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
+        """
+        Creates a stoploss order.
+        depending on order_types.stoploss configuration, uses 'market' or limit order.
+
+        Limit orders are defined by having orderPrice set, otherwise a market order is used.
+        """
+        limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
+        limit_rate = stop_price * limit_price_pct
+
+        ordertype = "stop"
+
+        stop_price = self.price_to_precision(pair, stop_price)
+
+        if self._config['dry_run']:
+            dry_order = self.dry_run_order(
+                pair, ordertype, "sell", amount, stop_price)
+            return dry_order
+
+        try:
+            params = self._params.copy()
+            if order_types.get('stoploss', 'market') == 'limit':
+                # set orderPrice to place limit order, otherwise it's a market order
+                params['orderPrice'] = limit_rate
+
+            amount = self.amount_to_precision(pair, amount)
+
+            order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
+                                           amount=amount, price=stop_price, params=params)
+            logger.info('stoploss order added for %s. '
+                        'stop price: %s.', pair, stop_price)
+            return order
+        except ccxt.InsufficientFunds as e:
+            raise InsufficientFundsError(
+                f'Insufficient funds to create {ordertype} sell order on market {pair}. '
+                f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
+                f'Message: {e}') from e
+        except ccxt.InvalidOrder as e:
+            raise InvalidOrderException(
+                f'Could not create {ordertype} sell order on market {pair}. '
+                f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
+                f'Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
+    @retrier(retries=API_FETCH_ORDER_RETRY_COUNT)
+    def fetch_stoploss_order(self, order_id: str, pair: str) -> Dict:
+        if self._config['dry_run']:
+            try:
+                order = self._dry_run_open_orders[order_id]
+                return order
+            except KeyError as e:
+                # Gracefully handle errors with dry-run orders.
+                raise InvalidOrderException(
+                    f'Tried to get an invalid dry-run-order (id: {order_id}). Message: {e}') from e
+        try:
+            orders = self._api.fetch_orders(pair, None, params={'type': 'stop'})
+
+            order = [order for order in orders if order['id'] == order_id]
+            if len(order) == 1:
+                return order[0]
+            else:
+                raise InvalidOrderException(f"Could not get stoploss order for id {order_id}")
+
+        except ccxt.InvalidOrder as e:
+            raise InvalidOrderException(
+                f'Tried to get an invalid order (id: {order_id}). Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not get order due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
+    @retrier
+    def cancel_stoploss_order(self, order_id: str, pair: str) -> Dict:
+        if self._config['dry_run']:
+            return {}
+        try:
+            return self._api.cancel_order(order_id, pair, params={'type': 'stop'})
+        except ccxt.InvalidOrder as e:
+            raise InvalidOrderException(
+                f'Could not cancel order. Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not cancel order due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
diff --git a/freqtrade/exchange/kraken.py b/freqtrade/exchange/kraken.py
index 91b41a159..5b7aa5c5b 100644
--- a/freqtrade/exchange/kraken.py
+++ b/freqtrade/exchange/kraken.py
@@ -1,8 +1,14 @@
 """ Kraken exchange subclass """
 import logging
-from typing import Dict
+from typing import Any, Dict
 
+import ccxt
+
+from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
+                                  OperationalException, TemporaryError)
 from freqtrade.exchange import Exchange
+from freqtrade.exchange.common import retrier
+
 
 logger = logging.getLogger(__name__)
 
@@ -10,3 +16,101 @@ logger = logging.getLogger(__name__)
 class Kraken(Exchange):
 
     _params: Dict = {"trading_agreement": "agree"}
+    _ft_has: Dict = {
+        "stoploss_on_exchange": True,
+        "trades_pagination": "id",
+        "trades_pagination_arg": "since",
+    }
+
+    def market_is_tradable(self, market: Dict[str, Any]) -> bool:
+        """
+        Check if the market symbol is tradable by Freqtrade.
+        Default checks + check if pair is darkpool pair.
+        """
+        parent_check = super().market_is_tradable(market)
+
+        return (parent_check and
+                market.get('darkpool', False) is False)
+
+    @retrier
+    def get_balances(self) -> dict:
+        if self._config['dry_run']:
+            return {}
+
+        try:
+            balances = self._api.fetch_balance()
+            # Remove additional info from ccxt results
+            balances.pop("info", None)
+            balances.pop("free", None)
+            balances.pop("total", None)
+            balances.pop("used", None)
+
+            orders = self._api.fetch_open_orders()
+            order_list = [(x["symbol"].split("/")[0 if x["side"] == "sell" else 1],
+                           x["remaining"],
+                           # Don't remove the below comment, this can be important for debuggung
+                           # x["side"], x["amount"],
+                           ) for x in orders]
+            for bal in balances:
+                balances[bal]['used'] = sum(order[1] for order in order_list if order[0] == bal)
+                balances[bal]['free'] = balances[bal]['total'] - balances[bal]['used']
+
+            return balances
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not get balance due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
+    def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
+        """
+        Verify stop_loss against stoploss-order value (limit or price)
+        Returns True if adjustment is necessary.
+        """
+        return order['type'] == 'stop-loss' and stop_loss > float(order['price'])
+
+    @retrier(retries=0)
+    def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
+        """
+        Creates a stoploss market order.
+        Stoploss market orders is the only stoploss type supported by kraken.
+        """
+
+        ordertype = "stop-loss"
+
+        stop_price = self.price_to_precision(pair, stop_price)
+
+        if self._config['dry_run']:
+            dry_order = self.dry_run_order(
+                pair, ordertype, "sell", amount, stop_price)
+            return dry_order
+
+        try:
+            params = self._params.copy()
+
+            amount = self.amount_to_precision(pair, amount)
+
+            order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
+                                           amount=amount, price=stop_price, params=params)
+            logger.info('stoploss order added for %s. '
+                        'stop price: %s.', pair, stop_price)
+            return order
+        except ccxt.InsufficientFunds as e:
+            raise InsufficientFundsError(
+                f'Insufficient funds to create {ordertype} sell order on market {pair}. '
+                f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
+                f'Message: {e}') from e
+        except ccxt.InvalidOrder as e:
+            raise InvalidOrderException(
+                f'Could not create {ordertype} sell order on market {pair}. '
+                f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
+                f'Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py
index b103d73a7..7416d8236 100644
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@@ -1,34 +1,40 @@
 """
 Freqtrade is the main module of this bot. It contains the class Freqtrade()
 """
-
 import copy
 import logging
 import traceback
-from datetime import datetime
-from typing import Any, Dict, List, Optional, Tuple
+from datetime import datetime, timezone
+from math import isclose
+from threading import Lock
+from typing import Any, Dict, List, Optional
 
 import arrow
-from requests.exceptions import RequestException
+from cachetools import TTLCache
 
-from freqtrade import (DependencyException, OperationalException, InvalidOrderException,
-                       __version__, constants, persistence)
+from freqtrade import __version__, constants
+from freqtrade.configuration import validate_config_consistency
 from freqtrade.data.converter import order_book_to_dataframe
 from freqtrade.data.dataprovider import DataProvider
 from freqtrade.edge import Edge
+from freqtrade.exceptions import (DependencyException, ExchangeError, InsufficientFundsError,
+                                  InvalidOrderException, PricingError)
 from freqtrade.exchange import timeframe_to_minutes
-from freqtrade.persistence import Trade
+from freqtrade.misc import safe_value_fallback, safe_value_fallback2
+from freqtrade.pairlist.pairlistmanager import PairListManager
+from freqtrade.persistence import Order, PairLocks, Trade, cleanup_db, init_db
+from freqtrade.resolvers import ExchangeResolver, StrategyResolver
 from freqtrade.rpc import RPCManager, RPCMessageType
-from freqtrade.resolvers import ExchangeResolver, StrategyResolver, PairListResolver
 from freqtrade.state import State
-from freqtrade.strategy.interface import SellType, IStrategy
+from freqtrade.strategy.interface import IStrategy, SellType
+from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
 from freqtrade.wallets import Wallets
 
 
 logger = logging.getLogger(__name__)
 
 
-class FreqtradeBot(object):
+class FreqtradeBot:
     """
     Freqtrade is the main class of the bot.
     This is from here the bot start its logic.
@@ -49,36 +55,63 @@ class FreqtradeBot(object):
         # Init objects
         self.config = config
 
-        self.strategy: IStrategy = StrategyResolver(self.config).strategy
+        # Cache values for 1800 to avoid frequent polling of the exchange for prices
+        # Caching only applies to RPC methods, so prices for open trades are still
+        # refreshed once every iteration.
+        self._sell_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=1800)
+        self._buy_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=1800)
 
-        self.rpc: RPCManager = RPCManager(self)
+        self.strategy: IStrategy = StrategyResolver.load_strategy(self.config)
 
-        self.exchange = ExchangeResolver(self.config['exchange']['name'], self.config).exchange
+        # Check config consistency here since strategies can set certain options
+        validate_config_consistency(config)
+
+        self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
+
+        init_db(self.config.get('db_url', None), clean_open_orders=self.config['dry_run'])
 
         self.wallets = Wallets(self.config, self.exchange)
-        self.dataprovider = DataProvider(self.config, self.exchange)
+
+        PairLocks.timeframe = self.config['timeframe']
+
+        self.pairlists = PairListManager(self.exchange, self.config)
+
+        self.dataprovider = DataProvider(self.config, self.exchange, self.pairlists)
 
         # Attach Dataprovider to Strategy baseclass
         IStrategy.dp = self.dataprovider
         # Attach Wallets to Strategy baseclass
         IStrategy.wallets = self.wallets
 
-        pairlistname = self.config.get('pairlist', {}).get('method', 'StaticPairList')
-        self.pairlists = PairListResolver(pairlistname, self, self.config).pairlist
-
         # Initializing Edge only if enabled
         self.edge = Edge(self.config, self.exchange, self.strategy) if \
             self.config.get('edge', {}).get('enabled', False) else None
 
-        self.active_pair_whitelist: List[str] = self.config['exchange']['pair_whitelist']
-
-        persistence.init(self.config.get('db_url', None),
-                         clean_open_orders=self.config.get('dry_run', False))
+        self.active_pair_whitelist = self._refresh_active_whitelist()
 
         # Set initial bot state from config
         initial_state = self.config.get('initial_state')
         self.state = State[initial_state.upper()] if initial_state else State.STOPPED
 
+        # RPC runs in separate threads, can start handling external commands just after
+        # initialization, even before Freqtradebot has a chance to start its throttling,
+        # so anything in the Freqtradebot instance should be ready (initialized), including
+        # the initial state of the bot.
+        # Keep this at the end of this initialization method.
+        self.rpc: RPCManager = RPCManager(self)
+        # Protect sell-logic from forcesell and viceversa
+        self._sell_lock = Lock()
+
+    def notify_status(self, msg: str) -> None:
+        """
+        Public method for users of this class (worker, etc.) to send notifications
+        via RPC about changes in the bot status.
+        """
+        self.rpc.send_msg({
+            'type': RPCMessageType.STATUS_NOTIFICATION,
+            'status': msg
+        })
+
     def cleanup(self) -> None:
         """
         Cleanup pending resources on an already stopped bot
@@ -86,8 +119,13 @@ class FreqtradeBot(object):
         """
         logger.info('Cleaning up modules ...')
 
+        if self.config['cancel_open_orders_on_exit']:
+            self.cancel_all_open_orders()
+
+        self.check_for_open_trades()
+
         self.rpc.cleanup()
-        persistence.cleanup()
+        cleanup_db()
 
     def startup(self) -> None:
         """
@@ -99,103 +137,298 @@ class FreqtradeBot(object):
             # Adjust stoploss if it was changed
             Trade.stoploss_reinitialization(self.strategy.stoploss)
 
-    def process(self) -> bool:
+        # Only update open orders on startup
+        # This will update the database after the initial migration
+        self.update_open_orders()
+
+    def process(self) -> None:
         """
         Queries the persistence layer for open trades and handles them,
         otherwise a new trade is created.
         :return: True if one or more trades has been created or closed, False otherwise
         """
-        state_changed = False
 
-        # Check whether markets have to be reloaded
-        self.exchange._reload_markets()
+        # Check whether markets have to be reloaded and reload them when it's needed
+        self.exchange.reload_markets()
 
-        # Refresh whitelist
-        self.pairlists.refresh_pairlist()
-        self.active_pair_whitelist = self.pairlists.whitelist
-
-        # Calculating Edge positioning
-        if self.edge:
-            self.edge.calculate()
-            self.active_pair_whitelist = self.edge.adjust(self.active_pair_whitelist)
+        self.update_closed_trades_without_assigned_fees()
 
         # Query trades from persistence layer
         trades = Trade.get_open_trades()
 
-        # Extend active-pair whitelist with pairs from open trades
-        # It ensures that tickers are downloaded for open trades
-        self._extend_whitelist_with_trades(self.active_pair_whitelist, trades)
+        self.active_pair_whitelist = self._refresh_active_whitelist(trades)
 
         # Refreshing candles
-        self.dataprovider.refresh(self._create_pair_whitelist(self.active_pair_whitelist),
+        self.dataprovider.refresh(self.pairlists.create_pair_list(self.active_pair_whitelist),
                                   self.strategy.informative_pairs())
 
-        # First process current opened trades
-        for trade in trades:
-            state_changed |= self.process_maybe_execute_sell(trade)
+        strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)()
 
-        # Then looking for buy opportunities
-        if len(trades) < self.config['max_open_trades']:
-            state_changed = self.process_maybe_execute_buy()
+        self.strategy.analyze(self.active_pair_whitelist)
 
-        if 'unfilledtimeout' in self.config:
+        with self._sell_lock:
             # Check and handle any timed out open orders
             self.check_handle_timedout()
-            Trade.session.flush()
 
-        return state_changed
+        # Protect from collisions with forcesell.
+        # Without this, freqtrade my try to recreate stoploss_on_exchange orders
+        # while selling is in process, since telegram messages arrive in an different thread.
+        with self._sell_lock:
+            # First process current opened trades (positions)
+            self.exit_positions(trades)
 
-    def _extend_whitelist_with_trades(self, whitelist: List[str], trades: List[Any]):
-        """
-        Extend whitelist with pairs from open trades
-        """
-        whitelist.extend([trade.pair for trade in trades if trade.pair not in whitelist])
+        # Then looking for buy opportunities
+        if self.get_free_open_trades():
+            self.enter_positions()
 
-    def _create_pair_whitelist(self, pairs: List[str]) -> List[Tuple[str, str]]:
-        """
-        Create pair-whitelist tuple with (pair, ticker_interval)
-        """
-        return [(pair, self.config['ticker_interval']) for pair in pairs]
+        Trade.session.flush()
 
-    def get_target_bid(self, pair: str, tick: Dict = None) -> float:
+    def process_stopped(self) -> None:
+        """
+        Close all orders that were left open
+        """
+        if self.config['cancel_open_orders_on_exit']:
+            self.cancel_all_open_orders()
+
+    def check_for_open_trades(self):
+        """
+        Notify the user when the bot is stopped
+        and there are still open trades active.
+        """
+        open_trades = Trade.get_trades([Trade.is_open == 1]).all()
+
+        if len(open_trades) != 0:
+            msg = {
+                'type': RPCMessageType.WARNING_NOTIFICATION,
+                'status':  f"{len(open_trades)} open trades active.\n\n"
+                           f"Handle these trades manually on {self.exchange.name}, "
+                           f"or '/start' the bot again and use '/stopbuy' "
+                           f"to handle open trades gracefully. \n"
+                           f"{'Trades are simulated.' if self.config['dry_run'] else ''}",
+            }
+            self.rpc.send_msg(msg)
+
+    def _refresh_active_whitelist(self, trades: List[Trade] = []) -> List[str]:
+        """
+        Refresh active whitelist from pairlist or edge and extend it with
+        pairs that have open trades.
+        """
+        # Refresh whitelist
+        self.pairlists.refresh_pairlist()
+        _whitelist = self.pairlists.whitelist
+
+        # Calculating Edge positioning
+        if self.edge:
+            self.edge.calculate()
+            _whitelist = self.edge.adjust(_whitelist)
+
+        if trades:
+            # Extend active-pair whitelist with pairs of open trades
+            # It ensures that candle (OHLCV) data are downloaded for open trades as well
+            _whitelist.extend([trade.pair for trade in trades if trade.pair not in _whitelist])
+        return _whitelist
+
+    def get_free_open_trades(self):
+        """
+        Return the number of free open trades slots or 0 if
+        max number of open trades reached
+        """
+        open_trades = len(Trade.get_open_trades())
+        return max(0, self.config['max_open_trades'] - open_trades)
+
+    def update_open_orders(self):
+        """
+        Updates open orders based on order list kept in the database.
+        Mainly updates the state of orders - but may also close trades
+        """
+        orders = Order.get_open_orders()
+        logger.info(f"Updating {len(orders)} open orders.")
+        for order in orders:
+            try:
+                fo = self.exchange.fetch_order_or_stoploss_order(order.order_id, order.ft_pair,
+                                                                 order.ft_order_side == 'stoploss')
+
+                self.update_trade_state(order.trade, order.order_id, fo)
+
+            except ExchangeError as e:
+                logger.warning(f"Error updating Order {order.order_id} due to {e}")
+
+    def update_closed_trades_without_assigned_fees(self):
+        """
+        Update closed trades without close fees assigned.
+        Only acts when Orders are in the database, otherwise the last orderid is unknown.
+        """
+        trades: List[Trade] = Trade.get_sold_trades_without_assigned_fees()
+        for trade in trades:
+
+            if not trade.is_open and not trade.fee_updated('sell'):
+                # Get sell fee
+                order = trade.select_order('sell', False)
+                if order:
+                    logger.info(f"Updating sell-fee on trade {trade} for order {order.order_id}.")
+                    self.update_trade_state(trade, order.order_id,
+                                            stoploss_order=order.ft_order_side == 'stoploss')
+
+        trades: List[Trade] = Trade.get_open_trades_without_assigned_fees()
+        for trade in trades:
+            if trade.is_open and not trade.fee_updated('buy'):
+                order = trade.select_order('buy', False)
+                if order:
+                    logger.info(f"Updating buy-fee on trade {trade} for order {order.order_id}.")
+                    self.update_trade_state(trade, order.order_id)
+
+    def handle_insufficient_funds(self, trade: Trade):
+        """
+        Determine if we ever opened a sell order for this trade.
+        If not, try update buy fees - otherwise "refind" the open order we obviously lost.
+        """
+        sell_order = trade.select_order('sell', None)
+        if sell_order:
+            self.refind_lost_order(trade)
+        else:
+            self.reupdate_buy_order_fees(trade)
+
+    def reupdate_buy_order_fees(self, trade: Trade):
+        """
+        Get buy order from database, and try to reupdate.
+        Handles trades where the initial fee-update did not work.
+        """
+        logger.info(f"Trying to reupdate buy fees for {trade}")
+        order = trade.select_order('buy', False)
+        if order:
+            logger.info(f"Updating buy-fee on trade {trade} for order {order.order_id}.")
+            self.update_trade_state(trade, order.order_id)
+
+    def refind_lost_order(self, trade):
+        """
+        Try refinding a lost trade.
+        Only used when InsufficientFunds appears on sell orders (stoploss or sell).
+        Tries to walk the stored orders and sell them off eventually.
+        """
+        logger.info(f"Trying to refind lost order for {trade}")
+        for order in trade.orders:
+            logger.info(f"Trying to refind {order}")
+            fo = None
+            if not order.ft_is_open:
+                logger.debug(f"Order {order} is no longer open.")
+                continue
+            if order.ft_order_side == 'buy':
+                # Skip buy side - this is handled by reupdate_buy_order_fees
+                continue
+            try:
+                fo = self.exchange.fetch_order_or_stoploss_order(order.order_id, order.ft_pair,
+                                                                 order.ft_order_side == 'stoploss')
+                if order.ft_order_side == 'stoploss':
+                    if fo and fo['status'] == 'open':
+                        # Assume this as the open stoploss order
+                        trade.stoploss_order_id = order.order_id
+                elif order.ft_order_side == 'sell':
+                    if fo and fo['status'] == 'open':
+                        # Assume this as the open order
+                        trade.open_order_id = order.order_id
+                if fo:
+                    logger.info(f"Found {order} for trade {trade}.jj")
+                    self.update_trade_state(trade, order.order_id, fo,
+                                            stoploss_order=order.ft_order_side == 'stoploss')
+
+            except ExchangeError:
+                logger.warning(f"Error updating {order.order_id}.")
+
+#
+# BUY / enter positions / open trades logic and methods
+#
+
+    def enter_positions(self) -> int:
+        """
+        Tries to execute buy orders for new trades (positions)
+        """
+        trades_created = 0
+
+        whitelist = copy.deepcopy(self.active_pair_whitelist)
+        if not whitelist:
+            logger.info("Active pair whitelist is empty.")
+            return trades_created
+        # Remove pairs for currently opened trades from the whitelist
+        for trade in Trade.get_open_trades():
+            if trade.pair in whitelist:
+                whitelist.remove(trade.pair)
+                logger.debug('Ignoring %s in pair whitelist', trade.pair)
+
+        if not whitelist:
+            logger.info("No currency pair in active pair whitelist, "
+                        "but checking to sell open trades.")
+            return trades_created
+        # Create entity and execute trade for each pair from whitelist
+        for pair in whitelist:
+            try:
+                trades_created += self.create_trade(pair)
+            except DependencyException as exception:
+                logger.warning('Unable to create trade for %s: %s', pair, exception)
+
+        if not trades_created:
+            logger.debug("Found no buy signals for whitelisted currencies. "
+                         "Trying again...")
+
+        return trades_created
+
+    def get_buy_rate(self, pair: str, refresh: bool) -> float:
         """
         Calculates bid target between current ask price and last price
+        :param pair: Pair to get rate for
+        :param refresh: allow cached data
         :return: float: Price
         """
-        config_bid_strategy = self.config.get('bid_strategy', {})
-        if 'use_order_book' in config_bid_strategy and\
-                config_bid_strategy.get('use_order_book', False):
-            logger.info('Getting price from order book')
-            order_book_top = config_bid_strategy.get('order_book_top', 1)
-            order_book = self.exchange.get_order_book(pair, order_book_top)
+        if not refresh:
+            rate = self._buy_rate_cache.get(pair)
+            # Check if cache has been invalidated
+            if rate:
+                logger.debug(f"Using cached buy rate for {pair}.")
+                return rate
+
+        bid_strategy = self.config.get('bid_strategy', {})
+        if 'use_order_book' in bid_strategy and bid_strategy.get('use_order_book', False):
+            logger.info(
+                f"Getting price from order book {bid_strategy['price_side'].capitalize()} side."
+            )
+            order_book_top = bid_strategy.get('order_book_top', 1)
+            order_book = self.exchange.fetch_l2_order_book(pair, order_book_top)
             logger.debug('order_book %s', order_book)
             # top 1 = index 0
-            order_book_rate = order_book['bids'][order_book_top - 1][0]
-            logger.info('...top %s order book buy rate %0.8f', order_book_top, order_book_rate)
-            used_rate = order_book_rate
+            try:
+                rate_from_l2 = order_book[f"{bid_strategy['price_side']}s"][order_book_top - 1][0]
+            except (IndexError, KeyError) as e:
+                logger.warning(
+                    "Buy Price from orderbook could not be determined."
+                    f"Orderbook: {order_book}"
+                 )
+                raise PricingError from e
+            logger.info(f'...top {order_book_top} order book buy rate {rate_from_l2:.8f}')
+            used_rate = rate_from_l2
         else:
-            if not tick:
-                logger.info('Using Last Ask / Last Price')
-                ticker = self.exchange.get_ticker(pair)
-            else:
-                ticker = tick
-            if ticker['ask'] < ticker['last']:
-                ticker_rate = ticker['ask']
-            else:
+            logger.info(f"Using Last {bid_strategy['price_side'].capitalize()} / Last Price")
+            ticker = self.exchange.fetch_ticker(pair)
+            ticker_rate = ticker[bid_strategy['price_side']]
+            if ticker['last'] and ticker_rate > ticker['last']:
                 balance = self.config['bid_strategy']['ask_last_balance']
-                ticker_rate = ticker['ask'] + balance * (ticker['last'] - ticker['ask'])
+                ticker_rate = ticker_rate + balance * (ticker['last'] - ticker_rate)
             used_rate = ticker_rate
 
+        self._buy_rate_cache[pair] = used_rate
+
         return used_rate
 
-    def _get_trade_stake_amount(self, pair) -> Optional[float]:
+    def get_trade_stake_amount(self, pair: str) -> float:
         """
-        Check if stake amount can be fulfilled with the available balance
-        for the stake currency
-        :return: float: Stake Amount
+        Calculate stake amount for the trade
+        :return: float: Stake amount
+        :raise: DependencyException if the available stake amount is too low
         """
+        stake_amount: float
+        # Ensure wallets are uptodate.
+        self.wallets.update()
+
         if self.edge:
-            return self.edge.stake_amount(
+            stake_amount = self.edge.stake_amount(
                 pair,
                 self.wallets.get_free(self.config['stake_currency']),
                 self.wallets.get_total(self.config['stake_currency']),
@@ -203,21 +436,60 @@ class FreqtradeBot(object):
             )
         else:
             stake_amount = self.config['stake_amount']
+            if stake_amount == constants.UNLIMITED_STAKE_AMOUNT:
+                stake_amount = self._calculate_unlimited_stake_amount()
 
-        available_amount = self.wallets.get_free(self.config['stake_currency'])
+        return self._check_available_stake_amount(stake_amount)
 
-        if stake_amount == constants.UNLIMITED_STAKE_AMOUNT:
-            open_trades = len(Trade.get_open_trades())
-            if open_trades >= self.config['max_open_trades']:
-                logger.warning('Can\'t open a new trade: max number of trades is reached')
-                return None
-            return available_amount / (self.config['max_open_trades'] - open_trades)
+    def _get_available_stake_amount(self) -> float:
+        """
+        Return the total currently available balance in stake currency,
+        respecting tradable_balance_ratio.
+        Calculated as
+        <open_trade stakes> + free amount ) * tradable_balance_ratio - <open_trade stakes>
+        """
+        val_tied_up = Trade.total_open_trades_stakes()
+
+        # Ensure <tradable_balance_ratio>% is used from the overall balance
+        # Otherwise we'd risk lowering stakes with each open trade.
+        # (tied up + current free) * ratio) - tied up
+        available_amount = ((val_tied_up + self.wallets.get_free(self.config['stake_currency'])) *
+                            self.config['tradable_balance_ratio']) - val_tied_up
+        return available_amount
+
+    def _calculate_unlimited_stake_amount(self) -> float:
+        """
+        Calculate stake amount for "unlimited" stake amount
+        :return: 0 if max number of trades reached, else stake_amount to use.
+        """
+        free_open_trades = self.get_free_open_trades()
+        if not free_open_trades:
+            return 0
+
+        available_amount = self._get_available_stake_amount()
+
+        return available_amount / free_open_trades
+
+    def _check_available_stake_amount(self, stake_amount: float) -> float:
+        """
+        Check if stake amount can be fulfilled with the available balance
+        for the stake currency
+        :return: float: Stake amount
+        """
+        available_amount = self._get_available_stake_amount()
+
+        if self.config['amend_last_stake_amount']:
+            # Remaining amount needs to be at least stake_amount * last_stake_amount_min_ratio
+            # Otherwise the remaining amount is too low to trade.
+            if available_amount > (stake_amount * self.config['last_stake_amount_min_ratio']):
+                stake_amount = min(stake_amount, available_amount)
+            else:
+                stake_amount = 0
 
-        # Check if stake_amount is fulfilled
         if available_amount < stake_amount:
             raise DependencyException(
-                f"Available balance({available_amount} {self.config['stake_currency']}) is "
-                f"lower than stake amount({stake_amount} {self.config['stake_currency']})"
+                f"Available balance ({available_amount} {self.config['stake_currency']}) is "
+                f"lower than stake amount ({stake_amount} {self.config['stake_currency']})"
             )
 
         return stake_amount
@@ -251,108 +523,125 @@ class FreqtradeBot(object):
             amount_reserve_percent += self.strategy.stoploss
         # it should not be more than 50%
         amount_reserve_percent = max(amount_reserve_percent, 0.5)
-        return min(min_stake_amounts) / amount_reserve_percent
 
-    def create_trade(self) -> bool:
-        """
-        Checks the implemented trading indicator(s) for a randomly picked pair,
-        if one pair triggers the buy_signal a new trade record gets created
-        :return: True if a trade object has been created and persisted, False otherwise
-        """
-        interval = self.strategy.ticker_interval
-        whitelist = copy.deepcopy(self.active_pair_whitelist)
+        # The value returned should satisfy both limits: for amount (base currency) and
+        # for cost (quote, stake currency), so max() is used here.
+        # See also #2575 at github.
+        return max(min_stake_amounts) / amount_reserve_percent
 
-        if not whitelist:
-            logger.warning("Whitelist is empty.")
+    def create_trade(self, pair: str) -> bool:
+        """
+        Check the implemented trading strategy for buy signals.
+
+        If the pair triggers the buy signal a new trade record gets created
+        and the buy-order opening the trade gets issued towards the exchange.
+
+        :return: True if a trade has been created.
+        """
+        logger.debug(f"create_trade for pair {pair}")
+
+        analyzed_df, _ = self.dataprovider.get_analyzed_dataframe(pair, self.strategy.timeframe)
+        if self.strategy.is_pair_locked(
+                pair, analyzed_df.iloc[-1]['date'] if len(analyzed_df) > 0 else None):
+            logger.info(f"Pair {pair} is currently locked.")
             return False
 
-        # Remove currently opened and latest pairs from whitelist
-        for trade in Trade.get_open_trades():
-            if trade.pair in whitelist:
-                whitelist.remove(trade.pair)
-                logger.debug('Ignoring %s in pair whitelist', trade.pair)
-
-        if not whitelist:
-            logger.info("No currency pair in whitelist, but checking to sell open trades.")
+        # get_free_open_trades is checked before create_trade is called
+        # but it is still used here to prevent opening too many trades within one iteration
+        if not self.get_free_open_trades():
+            logger.debug(f"Can't open a new trade for {pair}: max number of trades is reached.")
             return False
 
         # running get_signal on historical data fetched
-        for _pair in whitelist:
-            (buy, sell) = self.strategy.get_signal(
-                _pair, interval, self.dataprovider.ohlcv(_pair, self.strategy.ticker_interval))
+        (buy, sell) = self.strategy.get_signal(pair, self.strategy.timeframe, analyzed_df)
 
-            if buy and not sell:
-                stake_amount = self._get_trade_stake_amount(_pair)
-                if not stake_amount:
+        if buy and not sell:
+            stake_amount = self.get_trade_stake_amount(pair)
+            if not stake_amount:
+                logger.debug(f"Stake amount is 0, ignoring possible trade for {pair}.")
+                return False
+
+            logger.info(f"Buy signal found: about create a new trade with stake_amount: "
+                        f"{stake_amount} ...")
+
+            bid_check_dom = self.config.get('bid_strategy', {}).get('check_depth_of_market', {})
+            if ((bid_check_dom.get('enabled', False)) and
+                    (bid_check_dom.get('bids_to_ask_delta', 0) > 0)):
+                if self._check_depth_of_market_buy(pair, bid_check_dom):
+                    logger.info(f'Executing Buy for {pair}.')
+                    return self.execute_buy(pair, stake_amount)
+                else:
                     return False
 
-                logger.info(f"Buy signal found: about create a new trade with stake_amount: "
-                            f"{stake_amount} ...")
-
-                bidstrat_check_depth_of_market = self.config.get('bid_strategy', {}).\
-                    get('check_depth_of_market', {})
-                if (bidstrat_check_depth_of_market.get('enabled', False)) and\
-                        (bidstrat_check_depth_of_market.get('bids_to_ask_delta', 0) > 0):
-                    if self._check_depth_of_market_buy(_pair, bidstrat_check_depth_of_market):
-                        return self.execute_buy(_pair, stake_amount)
-                    else:
-                        return False
-                return self.execute_buy(_pair, stake_amount)
-
-        return False
+            logger.info(f'Executing Buy for {pair}')
+            return self.execute_buy(pair, stake_amount)
+        else:
+            return False
 
     def _check_depth_of_market_buy(self, pair: str, conf: Dict) -> bool:
         """
         Checks depth of market before executing a buy
         """
         conf_bids_to_ask_delta = conf.get('bids_to_ask_delta', 0)
-        logger.info('checking depth of market for %s', pair)
-        order_book = self.exchange.get_order_book(pair, 1000)
+        logger.info(f"Checking depth of market for {pair} ...")
+        order_book = self.exchange.fetch_l2_order_book(pair, 1000)
         order_book_data_frame = order_book_to_dataframe(order_book['bids'], order_book['asks'])
         order_book_bids = order_book_data_frame['b_size'].sum()
         order_book_asks = order_book_data_frame['a_size'].sum()
         bids_ask_delta = order_book_bids / order_book_asks
-        logger.info('bids: %s, asks: %s, delta: %s', order_book_bids,
-                    order_book_asks, bids_ask_delta)
+        logger.info(
+            f"Bids: {order_book_bids}, Asks: {order_book_asks}, Delta: {bids_ask_delta}, "
+            f"Bid Price: {order_book['bids'][0][0]}, Ask Price: {order_book['asks'][0][0]}, "
+            f"Immediate Bid Quantity: {order_book['bids'][0][1]}, "
+            f"Immediate Ask Quantity: {order_book['asks'][0][1]}."
+        )
         if bids_ask_delta >= conf_bids_to_ask_delta:
+            logger.info(f"Bids to asks delta for {pair} DOES satisfy condition.")
             return True
-        return False
+        else:
+            logger.info(f"Bids to asks delta for {pair} does not satisfy condition.")
+            return False
 
     def execute_buy(self, pair: str, stake_amount: float, price: Optional[float] = None) -> bool:
         """
         Executes a limit buy for the given pair
         :param pair: pair for which we want to create a LIMIT_BUY
-        :return: None
+        :return: True if a buy order is created, false if it fails.
         """
-        pair_s = pair.replace('_', '/')
-        stake_currency = self.config['stake_currency']
-        fiat_currency = self.config.get('fiat_display_currency', None)
         time_in_force = self.strategy.order_time_in_force['buy']
 
         if price:
             buy_limit_requested = price
         else:
-            # Calculate amount
-            buy_limit_requested = self.get_target_bid(pair)
+            # Calculate price
+            buy_limit_requested = self.get_buy_rate(pair, True)
 
-        min_stake_amount = self._get_min_pair_stake_amount(pair_s, buy_limit_requested)
+        min_stake_amount = self._get_min_pair_stake_amount(pair, buy_limit_requested)
         if min_stake_amount is not None and min_stake_amount > stake_amount:
             logger.warning(
-                f'Can\'t open a new trade for {pair_s}: stake amount '
-                f'is too small ({stake_amount} < {min_stake_amount})'
+                f"Can't open a new trade for {pair}: stake amount "
+                f"is too small ({stake_amount} < {min_stake_amount})"
             )
             return False
 
         amount = stake_amount / buy_limit_requested
         order_type = self.strategy.order_types['buy']
+        if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
+                pair=pair, order_type=order_type, amount=amount, rate=buy_limit_requested,
+                time_in_force=time_in_force):
+            logger.info(f"User requested abortion of buying {pair}")
+            return False
+        amount = self.exchange.amount_to_precision(pair, amount)
         order = self.exchange.buy(pair=pair, ordertype=order_type,
                                   amount=amount, rate=buy_limit_requested,
                                   time_in_force=time_in_force)
+        order_obj = Order.parse_from_ccxt_object(order, pair, 'buy')
         order_id = order['id']
         order_status = order.get('status', None)
 
         # we assume the order is executed at the price requested
         buy_limit_filled_price = buy_limit_requested
+        amount_requested = amount
 
         if order_status == 'expired' or order_status == 'rejected':
             order_tif = self.strategy.order_time_in_force['buy']
@@ -361,7 +650,7 @@ class FreqtradeBot(object):
             if float(order['filled']) == 0:
                 logger.warning('Buy %s order with time in force %s for %s is %s by %s.'
                                ' zero amount is fulfilled.',
-                               order_tif, order_type, pair_s, order_status, self.exchange.name)
+                               order_tif, order_type, pair, order_status, self.exchange.name)
                 return False
             else:
                 # the order is partially fulfilled
@@ -369,30 +658,18 @@ class FreqtradeBot(object):
                 # if the order is fulfilled fully or partially
                 logger.warning('Buy %s order with time in force %s for %s is %s by %s.'
                                ' %s amount fulfilled out of %s (%s remaining which is canceled).',
-                               order_tif, order_type, pair_s, order_status, self.exchange.name,
+                               order_tif, order_type, pair, order_status, self.exchange.name,
                                order['filled'], order['amount'], order['remaining']
                                )
                 stake_amount = order['cost']
-                amount = order['amount']
-                buy_limit_filled_price = order['price']
-                order_id = None
+                amount = safe_value_fallback(order, 'filled', 'amount')
+                buy_limit_filled_price = safe_value_fallback(order, 'average', 'price')
 
         # in case of FOK the order may be filled immediately and fully
         elif order_status == 'closed':
             stake_amount = order['cost']
-            amount = order['amount']
-            buy_limit_filled_price = order['price']
-
-        self.rpc.send_msg({
-            'type': RPCMessageType.BUY_NOTIFICATION,
-            'exchange': self.exchange.name.capitalize(),
-            'pair': pair_s,
-            'limit': buy_limit_filled_price,
-            'order_type': order_type,
-            'stake_amount': stake_amount,
-            'stake_currency': stake_currency,
-            'fiat_currency': fiat_currency
-        })
+            amount = safe_value_fallback(order, 'filled', 'amount')
+            buy_limit_filled_price = safe_value_fallback(order, 'average', 'price')
 
         # Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
         fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker')
@@ -400,6 +677,7 @@ class FreqtradeBot(object):
             pair=pair,
             stake_amount=stake_amount,
             amount=amount,
+            amount_requested=amount_requested,
             fee_open=fee,
             fee_close=fee,
             open_rate=buy_limit_filled_price,
@@ -408,12 +686,13 @@ class FreqtradeBot(object):
             exchange=self.exchange.id,
             open_order_id=order_id,
             strategy=self.strategy.get_strategy_name(),
-            ticker_interval=timeframe_to_minutes(self.config['ticker_interval'])
+            timeframe=timeframe_to_minutes(self.config['timeframe'])
         )
+        trade.orders.append(order_obj)
 
         # Update fees if order is closed
         if order_status == 'closed':
-            self.update_trade_state(trade, order)
+            self.update_trade_state(trade, order_id, order)
 
         Trade.session.add(trade)
         Trade.session.flush()
@@ -421,144 +700,128 @@ class FreqtradeBot(object):
         # Updating wallets
         self.wallets.update()
 
+        self._notify_buy(trade, order_type)
+
         return True
 
-    def process_maybe_execute_buy(self) -> bool:
+    def _notify_buy(self, trade: Trade, order_type: str) -> None:
         """
-        Tries to execute a buy trade in a safe way
-        :return: True if executed
+        Sends rpc notification when a buy occured.
         """
-        try:
-            # Create entity and execute trade
-            if self.create_trade():
-                return True
+        msg = {
+            'trade_id': trade.id,
+            'type': RPCMessageType.BUY_NOTIFICATION,
+            'exchange': self.exchange.name.capitalize(),
+            'pair': trade.pair,
+            'limit': trade.open_rate,
+            'order_type': order_type,
+            'stake_amount': trade.stake_amount,
+            'stake_currency': self.config['stake_currency'],
+            'fiat_currency': self.config.get('fiat_display_currency', None),
+            'amount': trade.amount,
+            'open_date': trade.open_date or datetime.utcnow(),
+            'current_rate': trade.open_rate_requested,
+        }
 
-            logger.info('Found no buy signals for whitelisted currencies. Trying again..')
-            return False
-        except DependencyException as exception:
-            logger.warning('Unable to create trade: %s', exception)
-            return False
+        # Send the message
+        self.rpc.send_msg(msg)
 
-    def process_maybe_execute_sell(self, trade: Trade) -> bool:
+    def _notify_buy_cancel(self, trade: Trade, order_type: str, reason: str) -> None:
         """
-        Tries to execute a sell trade
-        :return: True if executed
+        Sends rpc notification when a buy cancel occured.
         """
-        try:
-            self.update_trade_state(trade)
+        current_rate = self.get_buy_rate(trade.pair, False)
 
-            if self.strategy.order_types.get('stoploss_on_exchange') and trade.is_open:
-                result = self.handle_stoploss_on_exchange(trade)
-                if result:
-                    self.wallets.update()
-                    return result
+        msg = {
+            'trade_id': trade.id,
+            'type': RPCMessageType.BUY_CANCEL_NOTIFICATION,
+            'exchange': self.exchange.name.capitalize(),
+            'pair': trade.pair,
+            'limit': trade.open_rate,
+            'order_type': order_type,
+            'stake_amount': trade.stake_amount,
+            'stake_currency': self.config['stake_currency'],
+            'fiat_currency': self.config.get('fiat_display_currency', None),
+            'amount': trade.amount,
+            'open_date': trade.open_date,
+            'current_rate': current_rate,
+            'reason': reason,
+        }
 
-            if trade.is_open and trade.open_order_id is None:
-                # Check if we can sell our current pair
-                result = self.handle_trade(trade)
+        # Send the message
+        self.rpc.send_msg(msg)
 
-                # Updating wallets if any trade occured
-                if result:
-                    self.wallets.update()
+#
+# SELL / exit positions / close trades logic and methods
+#
 
-                return result
-
-        except DependencyException as exception:
-            logger.warning('Unable to sell trade: %s', exception)
-        return False
-
-    def get_real_amount(self, trade: Trade, order: Dict) -> float:
+    def exit_positions(self, trades: List[Any]) -> int:
         """
-        Get real amount for the trade
-        Necessary for exchanges which charge fees in base currency (e.g. binance)
+        Tries to execute sell orders for open trades (positions)
         """
-        order_amount = order['amount']
-        # Only run for closed orders
-        if trade.fee_open == 0 or order['status'] == 'open':
-            return order_amount
-
-        # use fee from order-dict if possible
-        if ('fee' in order and order['fee'] is not None and
-                (order['fee'].keys() >= {'currency', 'cost'})):
-            if (order['fee']['currency'] is not None and
-                    order['fee']['cost'] is not None and
-                    trade.pair.startswith(order['fee']['currency'])):
-                new_amount = order_amount - order['fee']['cost']
-                logger.info("Applying fee on amount for %s (from %s to %s) from Order",
-                            trade, order['amount'], new_amount)
-                return new_amount
-
-        # Fallback to Trades
-        trades = self.exchange.get_trades_for_order(trade.open_order_id, trade.pair,
-                                                    trade.open_date)
-
-        if len(trades) == 0:
-            logger.info("Applying fee on amount for %s failed: myTrade-Dict empty found", trade)
-            return order_amount
-        amount = 0
-        fee_abs = 0
-        for exectrade in trades:
-            amount += exectrade['amount']
-            if ("fee" in exectrade and exectrade['fee'] is not None and
-                    (exectrade['fee'].keys() >= {'currency', 'cost'})):
-                # only applies if fee is in quote currency!
-                if (exectrade['fee']['currency'] is not None and
-                        exectrade['fee']['cost'] is not None and
-                        trade.pair.startswith(exectrade['fee']['currency'])):
-                    fee_abs += exectrade['fee']['cost']
-
-        if amount != order_amount:
-            logger.warning(f"Amount {amount} does not match amount {trade.amount}")
-            raise OperationalException("Half bought? Amounts don't match")
-        real_amount = amount - fee_abs
-        if fee_abs != 0:
-            logger.info(f"Applying fee on amount for {trade} "
-                        f"(from {order_amount} to {real_amount}) from Trades")
-        return real_amount
-
-    def update_trade_state(self, trade, action_order: dict = None):
-        """
-        Checks trades with open orders and updates the amount if necessary
-        """
-        # Get order details for actual price per unit
-        if trade.open_order_id:
-            # Update trade with order values
-            logger.info('Found open order for %s', trade)
-            order = action_order or self.exchange.get_order(trade.open_order_id, trade.pair)
-            # Try update amount (binance-fix)
+        trades_closed = 0
+        for trade in trades:
             try:
-                new_amount = self.get_real_amount(trade, order)
-                if order['amount'] != new_amount:
-                    order['amount'] = new_amount
-                    # Fee was applied, so set to 0
-                    trade.fee_open = 0
 
-            except OperationalException as exception:
-                logger.warning("Could not update trade amount: %s", exception)
+                if (self.strategy.order_types.get('stoploss_on_exchange') and
+                        self.handle_stoploss_on_exchange(trade)):
+                    trades_closed += 1
+                    continue
+                # Check if we can sell our current pair
+                if trade.open_order_id is None and trade.is_open and self.handle_trade(trade):
+                    trades_closed += 1
 
-            trade.update(order)
+            except DependencyException as exception:
+                logger.warning('Unable to sell trade %s: %s', trade.pair, exception)
 
-            # Updating wallets when order is closed
-            if not trade.is_open:
-                self.wallets.update()
+        # Updating wallets if any trade occured
+        if trades_closed:
+            self.wallets.update()
+
+        return trades_closed
+
+    def _order_book_gen(self, pair: str, side: str, order_book_max: int = 1,
+                        order_book_min: int = 1):
+        """
+        Helper generator to query orderbook in loop (used for early sell-order placing)
+        """
+        order_book = self.exchange.fetch_l2_order_book(pair, order_book_max)
+        for i in range(order_book_min, order_book_max + 1):
+            yield order_book[side][i - 1][0]
 
     def get_sell_rate(self, pair: str, refresh: bool) -> float:
         """
-        Get sell rate - either using get-ticker bid or first bid based on orderbook
+        Get sell rate - either using ticker bid or first bid based on orderbook
         The orderbook portion is only used for rpc messaging, which would otherwise fail
-        for BitMex (has no bid/ask in get_ticker)
+        for BitMex (has no bid/ask in fetch_ticker)
         or remain static in any other case since it's not updating.
+        :param pair: Pair to get rate for
+        :param refresh: allow cached data
         :return: Bid rate
         """
-        config_ask_strategy = self.config.get('ask_strategy', {})
-        if config_ask_strategy.get('use_order_book', False):
-            logger.debug('Using order book to get sell rate')
-
-            order_book = self.exchange.get_order_book(pair, 1)
-            rate = order_book['bids'][0][0]
+        if not refresh:
+            rate = self._sell_rate_cache.get(pair)
+            # Check if cache has been invalidated
+            if rate:
+                logger.debug(f"Using cached sell rate for {pair}.")
+                return rate
 
+        ask_strategy = self.config.get('ask_strategy', {})
+        if ask_strategy.get('use_order_book', False):
+            # This code is only used for notifications, selling uses the generator directly
+            logger.info(
+                f"Getting price from order book {ask_strategy['price_side'].capitalize()} side."
+            )
+            try:
+                rate = next(self._order_book_gen(pair, f"{ask_strategy['price_side']}s"))
+            except (IndexError, KeyError) as e:
+                logger.warning("Sell Price at location from orderbook could not be determined.")
+                raise PricingError from e
         else:
-            rate = self.exchange.get_ticker(pair, refresh)['bid']
+            rate = self.exchange.fetch_ticker(pair)[ask_strategy['price_side']]
+        if rate is None:
+            raise PricingError(f"Sell-Rate for {pair} was empty.")
+        self._sell_rate_cache[pair] = rate
         return rate
 
     def handle_trade(self, trade: Trade) -> bool:
@@ -567,30 +830,43 @@ class FreqtradeBot(object):
         :return: True if trade has been sold, False otherwise
         """
         if not trade.is_open:
-            raise ValueError(f'Attempt to handle closed trade: {trade}')
+            raise DependencyException(f'Attempt to handle closed trade: {trade}')
 
         logger.debug('Handling %s ...', trade)
 
         (buy, sell) = (False, False)
-        experimental = self.config.get('experimental', {})
-        if experimental.get('use_sell_signal') or experimental.get('ignore_roi_if_buy_signal'):
-            (buy, sell) = self.strategy.get_signal(
-                trade.pair, self.strategy.ticker_interval,
-                self.dataprovider.ohlcv(trade.pair, self.strategy.ticker_interval))
 
         config_ask_strategy = self.config.get('ask_strategy', {})
+
+        if (config_ask_strategy.get('use_sell_signal', True) or
+                config_ask_strategy.get('ignore_roi_if_buy_signal', False)):
+            analyzed_df, _ = self.dataprovider.get_analyzed_dataframe(trade.pair,
+                                                                      self.strategy.timeframe)
+
+            (buy, sell) = self.strategy.get_signal(trade.pair, self.strategy.timeframe, analyzed_df)
+
         if config_ask_strategy.get('use_order_book', False):
-            logger.info('Using order book for selling...')
-            # logger.debug('Order book %s',orderBook)
             order_book_min = config_ask_strategy.get('order_book_min', 1)
             order_book_max = config_ask_strategy.get('order_book_max', 1)
+            logger.debug(f'Using order book between {order_book_min} and {order_book_max} '
+                         f'for selling {trade.pair}...')
 
-            order_book = self.exchange.get_order_book(trade.pair, order_book_max)
-
+            order_book = self._order_book_gen(trade.pair, f"{config_ask_strategy['price_side']}s",
+                                              order_book_min=order_book_min,
+                                              order_book_max=order_book_max)
             for i in range(order_book_min, order_book_max + 1):
-                order_book_rate = order_book['asks'][i - 1][0]
-                logger.info('  order book asks top %s: %0.8f', i, order_book_rate)
-                sell_rate = order_book_rate
+                try:
+                    sell_rate = next(order_book)
+                except (IndexError, KeyError) as e:
+                    logger.warning(
+                        f"Sell Price at location {i} from orderbook could not be determined."
+                    )
+                    raise PricingError from e
+                logger.debug(f"  order book {config_ask_strategy['price_side']} top {i}: "
+                             f"{sell_rate:0.8f}")
+                # Assign sell-rate to cache - otherwise sell-rate is never updated in the cache,
+                # resulting in outdated RPC messages
+                self._sell_rate_cache[trade.pair] = sell_rate
 
                 if self._check_and_execute_sell(trade, sell_rate, buy, sell):
                     return True
@@ -604,6 +880,38 @@ class FreqtradeBot(object):
         logger.debug('Found no sell signal for %s.', trade)
         return False
 
+    def create_stoploss_order(self, trade: Trade, stop_price: float) -> bool:
+        """
+        Abstracts creating stoploss orders from the logic.
+        Handles errors and updates the trade database object.
+        Force-sells the pair (using EmergencySell reason) in case of Problems creating the order.
+        :return: True if the order succeeded, and False in case of problems.
+        """
+        try:
+            stoploss_order = self.exchange.stoploss(pair=trade.pair, amount=trade.amount,
+                                                    stop_price=stop_price,
+                                                    order_types=self.strategy.order_types)
+
+            order_obj = Order.parse_from_ccxt_object(stoploss_order, trade.pair, 'stoploss')
+            trade.orders.append(order_obj)
+            trade.stoploss_order_id = str(stoploss_order['id'])
+            return True
+        except InsufficientFundsError as e:
+            logger.warning(f"Unable to place stoploss order {e}.")
+            # Try to figure out what went wrong
+            self.handle_insufficient_funds(trade)
+
+        except InvalidOrderException as e:
+            trade.stoploss_order_id = None
+            logger.error(f'Unable to place a stoploss order on exchange. {e}')
+            logger.warning('Selling the trade forcefully')
+            self.execute_sell(trade, trade.stop_loss, sell_reason=SellType.EMERGENCY_SELL)
+
+        except ExchangeError:
+            trade.stoploss_order_id = None
+            logger.exception('Unable to place a stoploss order on exchange.')
+        return False
+
     def handle_stoploss_on_exchange(self, trade: Trade) -> bool:
         """
         Check if trade is fulfilled in which case the stoploss
@@ -617,60 +925,48 @@ class FreqtradeBot(object):
 
         try:
             # First we check if there is already a stoploss on exchange
-            stoploss_order = self.exchange.get_order(trade.stoploss_order_id, trade.pair) \
-                if trade.stoploss_order_id else None
+            stoploss_order = self.exchange.fetch_stoploss_order(
+                trade.stoploss_order_id, trade.pair) if trade.stoploss_order_id else None
         except InvalidOrderException as exception:
             logger.warning('Unable to fetch stoploss order: %s', exception)
 
-        # If trade open order id does not exist: buy order is fulfilled
-        buy_order_fulfilled = not trade.open_order_id
-
-        # Limit price threshold: As limit price should always be below price
-        limit_price_pct = 0.99
-
-        # If buy order is fulfilled but there is no stoploss, we add a stoploss on exchange
-        if (buy_order_fulfilled and not stoploss_order):
-            if self.edge:
-                stoploss = self.edge.stoploss(pair=trade.pair)
-            else:
-                stoploss = self.strategy.stoploss
-
-            stop_price = trade.open_rate * (1 + stoploss)
-
-            # limit price should be less than stop price.
-            limit_price = stop_price * limit_price_pct
-
-            try:
-                stoploss_order_id = self.exchange.stoploss_limit(
-                    pair=trade.pair, amount=trade.amount, stop_price=stop_price, rate=limit_price
-                )['id']
-                trade.stoploss_order_id = str(stoploss_order_id)
-                trade.stoploss_last_update = datetime.now()
-                return False
-
-            except DependencyException as exception:
-                logger.warning('Unable to place a stoploss order on exchange: %s', exception)
-
-        # If stoploss order is canceled for some reason we add it
-        if stoploss_order and stoploss_order['status'] == 'canceled':
-            try:
-                stoploss_order_id = self.exchange.stoploss_limit(
-                    pair=trade.pair, amount=trade.amount,
-                    stop_price=trade.stop_loss, rate=trade.stop_loss * limit_price_pct
-                )['id']
-                trade.stoploss_order_id = str(stoploss_order_id)
-                return False
-            except DependencyException as exception:
-                logger.warning('Stoploss order was cancelled, '
-                               'but unable to recreate one: %s', exception)
+        if stoploss_order:
+            trade.update_order(stoploss_order)
 
         # We check if stoploss order is fulfilled
-        if stoploss_order and stoploss_order['status'] == 'closed':
+        if stoploss_order and stoploss_order['status'] in ('closed', 'triggered'):
             trade.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
-            trade.update(stoploss_order)
-            self._notify_sell(trade)
+            self.update_trade_state(trade, trade.stoploss_order_id, stoploss_order,
+                                    stoploss_order=True)
+            # Lock pair for one candle to prevent immediate rebuys
+            self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc),
+                                    reason='Auto lock')
+            self._notify_sell(trade, "stoploss")
             return True
 
+        if trade.open_order_id or not trade.is_open:
+            # Trade has an open Buy or Sell order, Stoploss-handling can't happen in this case
+            # as the Amount on the exchange is tied up in another trade.
+            # The trade can be closed already (sell-order fill confirmation came in this iteration)
+            return False
+
+        # If buy order is fulfilled but there is no stoploss, we add a stoploss on exchange
+        if not stoploss_order:
+            stoploss = self.edge.stoploss(pair=trade.pair) if self.edge else self.strategy.stoploss
+            stop_price = trade.open_rate * (1 + stoploss)
+
+            if self.create_stoploss_order(trade=trade, stop_price=stop_price):
+                trade.stoploss_last_update = datetime.utcnow()
+                return False
+
+        # If stoploss order is canceled for some reason we add it
+        if stoploss_order and stoploss_order['status'] in ('canceled', 'cancelled'):
+            if self.create_stoploss_order(trade=trade, stop_price=trade.stop_loss):
+                return False
+            else:
+                trade.stoploss_order_id = None
+                logger.warning('Stoploss order was cancelled, but unable to recreate one.')
+
         # Finally we check if stoploss on exchange should be moved up because of trailing.
         if stoploss_order and self.config.get('trailing_stop', False):
             # if trailing stoploss is enabled we check if stoploss value has changed
@@ -680,7 +976,7 @@ class FreqtradeBot(object):
 
         return False
 
-    def handle_trailing_stoploss_on_exchange(self, trade: Trade, order):
+    def handle_trailing_stoploss_on_exchange(self, trade: Trade, order: dict) -> None:
         """
         Check to see if stoploss on exchange should be updated
         in case of trailing stoploss on exchange
@@ -688,30 +984,24 @@ class FreqtradeBot(object):
         :param order: Current on exchange stoploss order
         :return: None
         """
-
-        if trade.stop_loss > float(order['info']['stopPrice']):
+        if self.exchange.stoploss_adjust(trade.stop_loss, order):
             # we check if the update is neccesary
             update_beat = self.strategy.order_types.get('stoploss_on_exchange_interval', 60)
-            if (datetime.utcnow() - trade.stoploss_last_update).total_seconds() > update_beat:
+            if (datetime.utcnow() - trade.stoploss_last_update).total_seconds() >= update_beat:
                 # cancelling the current stoploss on exchange first
-                logger.info('Trailing stoploss: cancelling current stoploss on exchange (id:{%s})'
-                            'in order to add another one ...', order['id'])
+                logger.info(f"Cancelling current stoploss on exchange for pair {trade.pair} "
+                            f"(orderid:{order['id']}) in order to add another one ...")
                 try:
-                    self.exchange.cancel_order(order['id'], trade.pair)
+                    co = self.exchange.cancel_stoploss_order(order['id'], trade.pair)
+                    trade.update_order(co)
                 except InvalidOrderException:
                     logger.exception(f"Could not cancel stoploss order {order['id']} "
                                      f"for pair {trade.pair}")
 
-                try:
-                    # creating the new one
-                    stoploss_order_id = self.exchange.stoploss_limit(
-                        pair=trade.pair, amount=trade.amount,
-                        stop_price=trade.stop_loss, rate=trade.stop_loss * 0.99
-                    )['id']
-                    trade.stoploss_order_id = str(stoploss_order_id)
-                except DependencyException:
-                    logger.exception(f"Could create trailing stoploss order "
-                                     f"for pair {trade.pair}.")
+                # Create new stoploss order
+                if not self.create_stoploss_order(trade=trade, stop_price=trade.stop_loss):
+                    logger.warning(f"Could not create trailing stoploss order "
+                                   f"for pair {trade.pair}.")
 
     def _check_and_execute_sell(self, trade: Trade, sell_rate: float,
                                 buy: bool, sell: bool) -> bool:
@@ -719,133 +1009,205 @@ class FreqtradeBot(object):
         Check and execute sell
         """
         should_sell = self.strategy.should_sell(
-                trade, sell_rate, datetime.utcnow(), buy, sell,
-                force_stoploss=self.edge.stoploss(trade.pair) if self.edge else 0
+            trade, sell_rate, datetime.utcnow(), buy, sell,
+            force_stoploss=self.edge.stoploss(trade.pair) if self.edge else 0
         )
 
         if should_sell.sell_flag:
+            logger.info(f'Executing Sell for {trade.pair}. Reason: {should_sell.sell_type}')
             self.execute_sell(trade, sell_rate, should_sell.sell_type)
-            logger.info('executed sell, reason: %s', should_sell.sell_type)
             return True
         return False
 
+    def _check_timed_out(self, side: str, order: dict) -> bool:
+        """
+        Check if timeout is active, and if the order is still open and timed out
+        """
+        timeout = self.config.get('unfilledtimeout', {}).get(side)
+        ordertime = arrow.get(order['datetime']).datetime
+        if timeout is not None:
+            timeout_threshold = arrow.utcnow().shift(minutes=-timeout).datetime
+
+            return (order['status'] == 'open' and order['side'] == side
+                    and ordertime < timeout_threshold)
+        return False
+
     def check_handle_timedout(self) -> None:
         """
         Check if any orders are timed out and cancel if neccessary
         :param timeoutvalue: Number of minutes until order is considered timed out
         :return: None
         """
-        buy_timeout = self.config['unfilledtimeout']['buy']
-        sell_timeout = self.config['unfilledtimeout']['sell']
-        buy_timeoutthreashold = arrow.utcnow().shift(minutes=-buy_timeout).datetime
-        sell_timeoutthreashold = arrow.utcnow().shift(minutes=-sell_timeout).datetime
 
-        for trade in Trade.query.filter(Trade.open_order_id.isnot(None)).all():
+        for trade in Trade.get_open_order_trades():
             try:
-                # FIXME: Somehow the query above returns results
-                # where the open_order_id is in fact None.
-                # This is probably because the record got
-                # updated via /forcesell in a different thread.
                 if not trade.open_order_id:
                     continue
-                order = self.exchange.get_order(trade.open_order_id, trade.pair)
-            except (RequestException, DependencyException):
-                logger.info(
-                    'Cannot query order for %s due to %s',
-                    trade,
-                    traceback.format_exc())
-                continue
-            ordertime = arrow.get(order['datetime']).datetime
-
-            # Check if trade is still actually open
-            if float(order['remaining']) == 0.0:
-                self.wallets.update()
+                order = self.exchange.fetch_order(trade.open_order_id, trade.pair)
+            except (ExchangeError):
+                logger.info('Cannot query order for %s due to %s', trade, traceback.format_exc())
                 continue
 
-            # Handle cancelled on exchange
-            if order['status'] == 'canceled':
-                if order['side'] == 'buy':
-                    self.handle_buy_order_full_cancel(trade, "canceled on Exchange")
-                elif order['side'] == 'sell':
-                    self.handle_timedout_limit_sell(trade, order)
-                    self.wallets.update()
-            # Check if order is still actually open
-            elif order['status'] == 'open':
-                if order['side'] == 'buy' and ordertime < buy_timeoutthreashold:
-                    self.handle_timedout_limit_buy(trade, order)
-                    self.wallets.update()
-                elif order['side'] == 'sell' and ordertime < sell_timeoutthreashold:
-                    self.handle_timedout_limit_sell(trade, order)
-                    self.wallets.update()
+            fully_cancelled = self.update_trade_state(trade, trade.open_order_id, order)
+
+            if (order['side'] == 'buy' and (order['status'] == 'open' or fully_cancelled) and (
+                    fully_cancelled
+                    or self._check_timed_out('buy', order)
+                    or strategy_safe_wrapper(self.strategy.check_buy_timeout,
+                                             default_retval=False)(pair=trade.pair,
+                                                                   trade=trade,
+                                                                   order=order))):
+                self.handle_cancel_buy(trade, order, constants.CANCEL_REASON['TIMEOUT'])
+
+            elif (order['side'] == 'sell' and (order['status'] == 'open' or fully_cancelled) and (
+                  fully_cancelled
+                  or self._check_timed_out('sell', order)
+                  or strategy_safe_wrapper(self.strategy.check_sell_timeout,
+                                           default_retval=False)(pair=trade.pair,
+                                                                 trade=trade,
+                                                                 order=order))):
+                self.handle_cancel_sell(trade, order, constants.CANCEL_REASON['TIMEOUT'])
+
+    def cancel_all_open_orders(self) -> None:
+        """
+        Cancel all orders that are currently open
+        :return: None
+        """
+
+        for trade in Trade.get_open_order_trades():
+            try:
+                order = self.exchange.fetch_order(trade.open_order_id, trade.pair)
+            except (ExchangeError):
+                logger.info('Cannot query order for %s due to %s', trade, traceback.format_exc())
+                continue
+
+            if order['side'] == 'buy':
+                self.handle_cancel_buy(trade, order, constants.CANCEL_REASON['ALL_CANCELLED'])
+
+            elif order['side'] == 'sell':
+                self.handle_cancel_sell(trade, order, constants.CANCEL_REASON['ALL_CANCELLED'])
+
+    def handle_cancel_buy(self, trade: Trade, order: Dict, reason: str) -> bool:
+        """
+        Buy cancel - cancel order
+        :return: True if order was fully cancelled
+        """
+        was_trade_fully_canceled = False
+
+        # Cancelled orders may have the status of 'canceled' or 'closed'
+        if order['status'] not in ('canceled', 'closed'):
+            corder = self.exchange.cancel_order_with_result(trade.open_order_id, trade.pair,
+                                                            trade.amount)
+            # Avoid race condition where the order could not be cancelled coz its already filled.
+            # Simply bailing here is the only safe way - as this order will then be
+            # handled in the next iteration.
+            if corder.get('status') not in ('canceled', 'closed'):
+                logger.warning(f"Order {trade.open_order_id} for {trade.pair} not cancelled.")
+                return False
+        else:
+            # Order was cancelled already, so we can reuse the existing dict
+            corder = order
+            reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE']
 
-    def handle_buy_order_full_cancel(self, trade: Trade, reason: str) -> None:
-        """Close trade in database and send message"""
-        Trade.session.delete(trade)
-        Trade.session.flush()
         logger.info('Buy order %s for %s.', reason, trade)
-        self.rpc.send_msg({
-            'type': RPCMessageType.STATUS_NOTIFICATION,
-            'status': f'Unfilled buy order for {trade.pair} {reason}'
-        })
 
-    def handle_timedout_limit_buy(self, trade: Trade, order: Dict) -> bool:
-        """Buy timeout - cancel order
-        :return: True if order was fully cancelled
-        """
-        self.exchange.cancel_order(trade.open_order_id, trade.pair)
-        if order['remaining'] == order['amount']:
+        # Using filled to determine the filled amount
+        filled_amount = safe_value_fallback2(corder, order, 'filled', 'filled')
+        if isclose(filled_amount, 0.0, abs_tol=constants.MATH_CLOSE_PREC):
+            logger.info('Buy order fully cancelled. Removing %s from database.', trade)
             # if trade is not partially completed, just delete the trade
-            self.handle_buy_order_full_cancel(trade, "cancelled due to timeout")
-            return True
+            trade.delete()
+            was_trade_fully_canceled = True
+            reason += f", {constants.CANCEL_REASON['FULLY_CANCELLED']}"
+        else:
+            # if trade is partially complete, edit the stake details for the trade
+            # and close the order
+            # cancel_order may not contain the full order dict, so we need to fallback
+            # to the order dict aquired before cancelling.
+            # we need to fall back to the values from order if corder does not contain these keys.
+            trade.amount = filled_amount
+            trade.stake_amount = trade.amount * trade.open_rate
+            self.update_trade_state(trade, trade.open_order_id, corder)
 
-        # if trade is partially complete, edit the stake details for the trade
-        # and close the order
-        trade.amount = order['amount'] - order['remaining']
-        trade.stake_amount = trade.amount * trade.open_rate
-        trade.open_order_id = None
-        logger.info('Partial buy order timeout for %s.', trade)
-        self.rpc.send_msg({
-            'type': RPCMessageType.STATUS_NOTIFICATION,
-            'status': f'Remaining buy order for {trade.pair} cancelled due to timeout'
-        })
-        return False
+            trade.open_order_id = None
+            logger.info('Partial buy order timeout for %s.', trade)
+            reason += f", {constants.CANCEL_REASON['PARTIALLY_FILLED']}"
 
-    def handle_timedout_limit_sell(self, trade: Trade, order: Dict) -> bool:
+        self.wallets.update()
+        self._notify_buy_cancel(trade, order_type=self.strategy.order_types['buy'],
+                                reason=reason)
+        return was_trade_fully_canceled
+
+    def handle_cancel_sell(self, trade: Trade, order: Dict, reason: str) -> str:
         """
-        Sell timeout - cancel order and update trade
-        :return: True if order was fully cancelled
+        Sell cancel - cancel order and update trade
+        :return: Reason for cancel
         """
-        if order['remaining'] == order['amount']:
-            # if trade is not partially completed, just cancel the trade
-            if order["status"] != "canceled":
-                reason = "due to timeout"
-                self.exchange.cancel_order(trade.open_order_id, trade.pair)
-                logger.info('Sell order timeout for %s.', trade)
+        # if trade is not partially completed, just cancel the order
+        if order['remaining'] == order['amount'] or order.get('filled') == 0.0:
+            if not self.exchange.check_order_canceled_empty(order):
+                try:
+                    # if trade is not partially completed, just delete the order
+                    self.exchange.cancel_order(trade.open_order_id, trade.pair)
+                except InvalidOrderException:
+                    logger.exception(f"Could not cancel sell order {trade.open_order_id}")
+                    return 'error cancelling order'
+                logger.info('Sell order %s for %s.', reason, trade)
             else:
-                reason = "on exchange"
-                logger.info('Sell order canceled on exchange for %s.', trade)
+                reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE']
+                logger.info('Sell order %s for %s.', reason, trade)
+
             trade.close_rate = None
+            trade.close_rate_requested = None
             trade.close_profit = None
+            trade.close_profit_abs = None
             trade.close_date = None
             trade.is_open = True
             trade.open_order_id = None
-            self.rpc.send_msg({
-                'type': RPCMessageType.STATUS_NOTIFICATION,
-                'status': f'Unfilled sell order for {trade.pair} cancelled {reason}'
-            })
+        else:
+            # TODO: figure out how to handle partially complete sell orders
+            reason = constants.CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
 
-            return True
+        self.wallets.update()
+        self._notify_sell_cancel(
+            trade,
+            order_type=self.strategy.order_types['sell'],
+            reason=reason
+        )
+        return reason
 
-        # TODO: figure out how to handle partially complete sell orders
-        return False
+    def _safe_sell_amount(self, pair: str, amount: float) -> float:
+        """
+        Get sellable amount.
+        Should be trade.amount - but will fall back to the available amount if necessary.
+        This should cover cases where get_real_amount() was not able to update the amount
+        for whatever reason.
+        :param pair: Pair we're trying to sell
+        :param amount: amount we expect to be available
+        :return: amount to sell
+        :raise: DependencyException: if available balance is not within 2% of the available amount.
+        """
+        # Update wallets to ensure amounts tied up in a stoploss is now free!
+        self.wallets.update()
+        trade_base_currency = self.exchange.get_pair_base_currency(pair)
+        wallet_amount = self.wallets.get_free(trade_base_currency)
+        logger.debug(f"{pair} - Wallet: {wallet_amount} - Trade-amount: {amount}")
+        if wallet_amount >= amount:
+            return amount
+        elif wallet_amount > amount * 0.98:
+            logger.info(f"{pair} - Falling back to wallet-amount {wallet_amount} -> {amount}.")
+            return wallet_amount
+        else:
+            raise DependencyException(
+                f"Not enough amount to sell. Trade-amount: {amount}, Wallet: {wallet_amount}")
 
-    def execute_sell(self, trade: Trade, limit: float, sell_reason: SellType) -> None:
+    def execute_sell(self, trade: Trade, limit: float, sell_reason: SellType) -> bool:
         """
         Executes a limit sell for the given trade and limit
         :param trade: Trade instance
         :param limit: limit rate for the sell order
         :param sellreason: Reason the sell was triggered
-        :return: None
+        :return: True if it succeeds (supported) False (not supported)
         """
         sell_type = 'sell'
         if sell_reason in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
@@ -853,64 +1215,284 @@ class FreqtradeBot(object):
 
         # if stoploss is on exchange and we are on dry_run mode,
         # we consider the sell price stop price
-        if self.config.get('dry_run', False) and sell_type == 'stoploss' \
+        if self.config['dry_run'] and sell_type == 'stoploss' \
            and self.strategy.order_types['stoploss_on_exchange']:
             limit = trade.stop_loss
 
         # First cancelling stoploss on exchange ...
         if self.strategy.order_types.get('stoploss_on_exchange') and trade.stoploss_order_id:
             try:
-                self.exchange.cancel_order(trade.stoploss_order_id, trade.pair)
+                self.exchange.cancel_stoploss_order(trade.stoploss_order_id, trade.pair)
             except InvalidOrderException:
                 logger.exception(f"Could not cancel stoploss order {trade.stoploss_order_id}")
 
-        # Execute sell and update trade record
-        order_id = self.exchange.sell(pair=str(trade.pair),
-                                      ordertype=self.strategy.order_types[sell_type],
-                                      amount=trade.amount, rate=limit,
-                                      time_in_force=self.strategy.order_time_in_force['sell']
-                                      )['id']
+        order_type = self.strategy.order_types[sell_type]
+        if sell_reason == SellType.EMERGENCY_SELL:
+            # Emergency sells (default to market!)
+            order_type = self.strategy.order_types.get("emergencysell", "market")
 
-        trade.open_order_id = order_id
+        amount = self._safe_sell_amount(trade.pair, trade.amount)
+        time_in_force = self.strategy.order_time_in_force['sell']
+
+        if not strategy_safe_wrapper(self.strategy.confirm_trade_exit, default_retval=True)(
+                pair=trade.pair, trade=trade, order_type=order_type, amount=amount, rate=limit,
+                time_in_force=time_in_force,
+                sell_reason=sell_reason.value):
+            logger.info(f"User requested abortion of selling {trade.pair}")
+            return False
+
+        try:
+            # Execute sell and update trade record
+            order = self.exchange.sell(pair=trade.pair,
+                                       ordertype=order_type,
+                                       amount=amount, rate=limit,
+                                       time_in_force=time_in_force
+                                       )
+        except InsufficientFundsError as e:
+            logger.warning(f"Unable to place order {e}.")
+            # Try to figure out what went wrong
+            self.handle_insufficient_funds(trade)
+            return False
+
+        order_obj = Order.parse_from_ccxt_object(order, trade.pair, 'sell')
+        trade.orders.append(order_obj)
+
+        trade.open_order_id = order['id']
         trade.close_rate_requested = limit
         trade.sell_reason = sell_reason.value
+        # In case of market sell orders the order can be closed immediately
+        if order.get('status', 'unknown') == 'closed':
+            self.update_trade_state(trade, trade.open_order_id, order)
         Trade.session.flush()
-        self._notify_sell(trade)
 
-    def _notify_sell(self, trade: Trade):
+        # Lock pair for one candle to prevent immediate rebuys
+        self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc),
+                                reason='Auto lock')
+
+        self._notify_sell(trade, order_type)
+
+        return True
+
+    def _notify_sell(self, trade: Trade, order_type: str) -> None:
         """
         Sends rpc notification when a sell occured.
         """
         profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
         profit_trade = trade.calc_profit(rate=profit_rate)
-        # Use cached ticker here - it was updated seconds ago.
+        # Use cached rates here - it was updated seconds ago.
         current_rate = self.get_sell_rate(trade.pair, False)
-        profit_percent = trade.calc_profit_percent(profit_rate)
-        gain = "profit" if profit_percent > 0 else "loss"
+        profit_ratio = trade.calc_profit_ratio(profit_rate)
+        gain = "profit" if profit_ratio > 0 else "loss"
 
         msg = {
             'type': RPCMessageType.SELL_NOTIFICATION,
+            'trade_id': trade.id,
             'exchange': trade.exchange.capitalize(),
             'pair': trade.pair,
             'gain': gain,
-            'limit': trade.close_rate_requested,
-            'order_type': self.strategy.order_types['sell'],
+            'limit': profit_rate,
+            'order_type': order_type,
             'amount': trade.amount,
             'open_rate': trade.open_rate,
             'current_rate': current_rate,
             'profit_amount': profit_trade,
-            'profit_percent': profit_percent,
-            'sell_reason': trade.sell_reason
+            'profit_ratio': profit_ratio,
+            'sell_reason': trade.sell_reason,
+            'open_date': trade.open_date,
+            'close_date': trade.close_date or datetime.utcnow(),
+            'stake_currency': self.config['stake_currency'],
+            'fiat_currency': self.config.get('fiat_display_currency', None),
         }
 
-        # For regular case, when the configuration exists
-        if 'stake_currency' in self.config and 'fiat_display_currency' in self.config:
-            stake_currency = self.config['stake_currency']
-            fiat_currency = self.config['fiat_display_currency']
+        if 'fiat_display_currency' in self.config:
             msg.update({
-                'stake_currency': stake_currency,
-                'fiat_currency': fiat_currency,
+                'fiat_currency': self.config['fiat_display_currency'],
             })
 
         # Send the message
         self.rpc.send_msg(msg)
+
+    def _notify_sell_cancel(self, trade: Trade, order_type: str, reason: str) -> None:
+        """
+        Sends rpc notification when a sell cancel occured.
+        """
+        if trade.sell_order_status == reason:
+            return
+        else:
+            trade.sell_order_status = reason
+
+        profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
+        profit_trade = trade.calc_profit(rate=profit_rate)
+        current_rate = self.get_sell_rate(trade.pair, False)
+        profit_ratio = trade.calc_profit_ratio(profit_rate)
+        gain = "profit" if profit_ratio > 0 else "loss"
+
+        msg = {
+            'type': RPCMessageType.SELL_CANCEL_NOTIFICATION,
+            'trade_id': trade.id,
+            'exchange': trade.exchange.capitalize(),
+            'pair': trade.pair,
+            'gain': gain,
+            'limit': profit_rate,
+            'order_type': order_type,
+            'amount': trade.amount,
+            'open_rate': trade.open_rate,
+            'current_rate': current_rate,
+            'profit_amount': profit_trade,
+            'profit_ratio': profit_ratio,
+            'sell_reason': trade.sell_reason,
+            'open_date': trade.open_date,
+            'close_date': trade.close_date,
+            'stake_currency': self.config['stake_currency'],
+            'fiat_currency': self.config.get('fiat_display_currency', None),
+            'reason': reason,
+        }
+
+        if 'fiat_display_currency' in self.config:
+            msg.update({
+                'fiat_currency': self.config['fiat_display_currency'],
+            })
+
+        # Send the message
+        self.rpc.send_msg(msg)
+
+#
+# Common update trade state methods
+#
+
+    def update_trade_state(self, trade: Trade, order_id: str, action_order: Dict[str, Any] = None,
+                           stoploss_order: bool = False) -> bool:
+        """
+        Checks trades with open orders and updates the amount if necessary
+        Handles closing both buy and sell orders.
+        :param trade: Trade object of the trade we're analyzing
+        :param order_id: Order-id of the order we're analyzing
+        :param action_order: Already aquired order object
+        :return: True if order has been cancelled without being filled partially, False otherwise
+        """
+        if not order_id:
+            logger.warning(f'Orderid for trade {trade} is empty.')
+            return False
+
+        # Update trade with order values
+        logger.info('Found open order for %s', trade)
+        try:
+            order = action_order or self.exchange.fetch_order_or_stoploss_order(order_id,
+                                                                                trade.pair,
+                                                                                stoploss_order)
+        except InvalidOrderException as exception:
+            logger.warning('Unable to fetch order %s: %s', order_id, exception)
+            return False
+
+        trade.update_order(order)
+
+        # Try update amount (binance-fix)
+        try:
+            new_amount = self.get_real_amount(trade, order)
+            if not isclose(safe_value_fallback(order, 'filled', 'amount'), new_amount,
+                           abs_tol=constants.MATH_CLOSE_PREC):
+                order['amount'] = new_amount
+                order.pop('filled', None)
+                trade.recalc_open_trade_price()
+        except DependencyException as exception:
+            logger.warning("Could not update trade amount: %s", exception)
+
+        if self.exchange.check_order_canceled_empty(order):
+            # Trade has been cancelled on exchange
+            # Handling of this will happen in check_handle_timeout.
+            return True
+        trade.update(order)
+
+        # Updating wallets when order is closed
+        if not trade.is_open:
+            self.wallets.update()
+        return False
+
+    def apply_fee_conditional(self, trade: Trade, trade_base_currency: str,
+                              amount: float, fee_abs: float) -> float:
+        """
+        Applies the fee to amount (either from Order or from Trades).
+        Can eat into dust if more than the required asset is available.
+        """
+        self.wallets.update()
+        if fee_abs != 0 and self.wallets.get_free(trade_base_currency) >= amount:
+            # Eat into dust if we own more than base currency
+            logger.info(f"Fee amount for {trade} was in base currency - "
+                        f"Eating Fee {fee_abs} into dust.")
+        elif fee_abs != 0:
+            real_amount = self.exchange.amount_to_precision(trade.pair, amount - fee_abs)
+            logger.info(f"Applying fee on amount for {trade} "
+                        f"(from {amount} to {real_amount}).")
+            return real_amount
+        return amount
+
+    def get_real_amount(self, trade: Trade, order: Dict) -> float:
+        """
+        Detect and update trade fee.
+        Calls trade.update_fee() uppon correct detection.
+        Returns modified amount if the fee was taken from the destination currency.
+        Necessary for exchanges which charge fees in base currency (e.g. binance)
+        :return: identical (or new) amount for the trade
+        """
+        # Init variables
+        order_amount = safe_value_fallback(order, 'filled', 'amount')
+        # Only run for closed orders
+        if trade.fee_updated(order.get('side', '')) or order['status'] == 'open':
+            return order_amount
+
+        trade_base_currency = self.exchange.get_pair_base_currency(trade.pair)
+        # use fee from order-dict if possible
+        if self.exchange.order_has_fee(order):
+            fee_cost, fee_currency, fee_rate = self.exchange.extract_cost_curr_rate(order)
+            logger.info(f"Fee for Trade {trade} [{order.get('side')}]: "
+                        f"{fee_cost:.8g} {fee_currency} - rate: {fee_rate}")
+
+            trade.update_fee(fee_cost, fee_currency, fee_rate, order.get('side', ''))
+            if trade_base_currency == fee_currency:
+                # Apply fee to amount
+                return self.apply_fee_conditional(trade, trade_base_currency,
+                                                  amount=order_amount, fee_abs=fee_cost)
+            return order_amount
+        return self.fee_detection_from_trades(trade, order, order_amount)
+
+    def fee_detection_from_trades(self, trade: Trade, order: Dict, order_amount: float) -> float:
+        """
+        fee-detection fallback to Trades. Parses result of fetch_my_trades to get correct fee.
+        """
+        trades = self.exchange.get_trades_for_order(order['id'], trade.pair,
+                                                    trade.open_date)
+
+        if len(trades) == 0:
+            logger.info("Applying fee on amount for %s failed: myTrade-Dict empty found", trade)
+            return order_amount
+        fee_currency = None
+        amount = 0
+        fee_abs = 0.0
+        fee_cost = 0.0
+        trade_base_currency = self.exchange.get_pair_base_currency(trade.pair)
+        fee_rate_array: List[float] = []
+        for exectrade in trades:
+            amount += exectrade['amount']
+            if self.exchange.order_has_fee(exectrade):
+                fee_cost_, fee_currency, fee_rate_ = self.exchange.extract_cost_curr_rate(exectrade)
+                fee_cost += fee_cost_
+                if fee_rate_ is not None:
+                    fee_rate_array.append(fee_rate_)
+                # only applies if fee is in quote currency!
+                if trade_base_currency == fee_currency:
+                    fee_abs += fee_cost_
+        # Ensure at least one trade was found:
+        if fee_currency:
+            # fee_rate should use mean
+            fee_rate = sum(fee_rate_array) / float(len(fee_rate_array)) if fee_rate_array else None
+            trade.update_fee(fee_cost, fee_currency, fee_rate, order.get('side', ''))
+
+        if not isclose(amount, order_amount, abs_tol=constants.MATH_CLOSE_PREC):
+            logger.warning(f"Amount {amount} does not match amount {trade.amount}")
+            raise DependencyException("Half bought? Amounts don't match")
+
+        if fee_abs != 0:
+            return self.apply_fee_conditional(trade, trade_base_currency,
+                                              amount=amount, fee_abs=fee_abs)
+        else:
+            return amount
diff --git a/freqtrade/indicator_helpers.py b/freqtrade/indicator_helpers.py
deleted file mode 100644
index f8ea0d939..000000000
--- a/freqtrade/indicator_helpers.py
+++ /dev/null
@@ -1,40 +0,0 @@
-from math import cos, exp, pi, sqrt
-
-import numpy as np
-import talib as ta
-from pandas import Series
-
-
-def went_up(series: Series) -> bool:
-    return series > series.shift(1)
-
-
-def went_down(series: Series) -> bool:
-    return series < series.shift(1)
-
-
-def ehlers_super_smoother(series: Series, smoothing: float = 6) -> Series:
-    magic = pi * sqrt(2) / smoothing
-    a1 = exp(-magic)
-    coeff2 = 2 * a1 * cos(magic)
-    coeff3 = -a1 * a1
-    coeff1 = (1 - coeff2 - coeff3) / 2
-
-    filtered = series.copy()
-
-    for i in range(2, len(series)):
-        filtered.iloc[i] = coeff1 * (series.iloc[i] + series.iloc[i-1]) + \
-            coeff2 * filtered.iloc[i-1] + coeff3 * filtered.iloc[i-2]
-
-    return filtered
-
-
-def fishers_inverse(series: Series, smoothing: float = 0) -> np.ndarray:
-    """ Does a smoothed fishers inverse transformation.
-        Can be used with any oscillator that goes from 0 to 100 like RSI or MFI """
-    v1 = 0.1 * (series - 50)
-    if smoothing > 0:
-        v2 = ta.WMA(v1.values, timeperiod=smoothing)
-    else:
-        v2 = v1
-    return (np.exp(2 * v2)-1) / (np.exp(2 * v2) + 1)
diff --git a/freqtrade/loggers.py b/freqtrade/loggers.py
index 90b8905e5..169cd2610 100644
--- a/freqtrade/loggers.py
+++ b/freqtrade/loggers.py
@@ -1,30 +1,56 @@
 import logging
 import sys
+from logging import Formatter
+from logging.handlers import BufferingHandler, RotatingFileHandler, SysLogHandler
+from typing import Any, Dict
 
-from logging.handlers import RotatingFileHandler
-from typing import Any, Dict, List
+from freqtrade.exceptions import OperationalException
 
 
 logger = logging.getLogger(__name__)
+LOGFORMAT = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+
+# Initialize bufferhandler - will be used for /log endpoints
+bufferHandler = BufferingHandler(1000)
+bufferHandler.setFormatter(Formatter(LOGFORMAT))
 
 
-def _set_loggers(verbosity: int = 0) -> None:
+def _set_loggers(verbosity: int = 0, api_verbosity: str = 'info') -> None:
     """
     Set the logging level for third party libraries
     :return: None
     """
 
     logging.getLogger('requests').setLevel(
-            logging.INFO if verbosity <= 1 else logging.DEBUG
+        logging.INFO if verbosity <= 1 else logging.DEBUG
     )
     logging.getLogger("urllib3").setLevel(
-            logging.INFO if verbosity <= 1 else logging.DEBUG
+        logging.INFO if verbosity <= 1 else logging.DEBUG
     )
     logging.getLogger('ccxt.base.exchange').setLevel(
-            logging.INFO if verbosity <= 2 else logging.DEBUG
+        logging.INFO if verbosity <= 2 else logging.DEBUG
     )
     logging.getLogger('telegram').setLevel(logging.INFO)
 
+    logging.getLogger('werkzeug').setLevel(
+        logging.ERROR if api_verbosity == 'error' else logging.INFO
+    )
+
+
+def setup_logging_pre() -> None:
+    """
+    Early setup for logging.
+    Uses INFO loglevel and only the Streamhandler.
+    Early messages (before proper logging setup) will therefore only be sent to additional
+    logging handlers after the real initialization, because we don't know which
+    ones the user desires beforehand.
+    """
+    logging.basicConfig(
+        level=logging.INFO,
+        format=LOGFORMAT,
+        handlers=[logging.StreamHandler(sys.stderr), bufferHandler]
+    )
+
 
 def setup_logging(config: Dict[str, Any]) -> None:
     """
@@ -32,19 +58,45 @@ def setup_logging(config: Dict[str, Any]) -> None:
     """
     # Log level
     verbosity = config['verbosity']
+    logging.root.addHandler(bufferHandler)
 
-    # Log to stdout, not stderr
-    log_handlers: List[logging.Handler] = [logging.StreamHandler(sys.stdout)]
+    logfile = config.get('logfile')
 
-    if config.get('logfile'):
-        log_handlers.append(RotatingFileHandler(config['logfile'],
-                                                maxBytes=1024 * 1024,  # 1Mb
-                                                backupCount=10))
+    if logfile:
+        s = logfile.split(':')
+        if s[0] == 'syslog':
+            # Address can be either a string (socket filename) for Unix domain socket or
+            # a tuple (hostname, port) for UDP socket.
+            # Address can be omitted (i.e. simple 'syslog' used as the value of
+            # config['logfilename']), which defaults to '/dev/log', applicable for most
+            # of the systems.
+            address = (s[1], int(s[2])) if len(s) > 2 else s[1] if len(s) > 1 else '/dev/log'
+            handler = SysLogHandler(address=address)
+            # No datetime field for logging into syslog, to allow syslog
+            # to perform reduction of repeating messages if this is set in the
+            # syslog config. The messages should be equal for this.
+            handler.setFormatter(Formatter('%(name)s - %(levelname)s - %(message)s'))
+            logging.root.addHandler(handler)
+        elif s[0] == 'journald':
+            try:
+                from systemd.journal import JournaldLogHandler
+            except ImportError:
+                raise OperationalException("You need the systemd python package be installed in "
+                                           "order to use logging to journald.")
+            handler_jd = JournaldLogHandler()
+            # No datetime field for logging into journald, to allow syslog
+            # to perform reduction of repeating messages if this is set in the
+            # syslog config. The messages should be equal for this.
+            handler_jd.setFormatter(Formatter('%(name)s - %(levelname)s - %(message)s'))
+            logging.root.addHandler(handler_jd)
+        else:
+            handler_rf = RotatingFileHandler(logfile,
+                                             maxBytes=1024 * 1024 * 10,  # 10Mb
+                                             backupCount=10)
+            handler_rf.setFormatter(Formatter(LOGFORMAT))
+            logging.root.addHandler(handler_rf)
+
+    logging.root.setLevel(logging.INFO if verbosity < 1 else logging.DEBUG)
+    _set_loggers(verbosity, config.get('api_server', {}).get('verbosity', 'info'))
 
-    logging.basicConfig(
-        level=logging.INFO if verbosity < 1 else logging.DEBUG,
-        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
-        handlers=log_handlers
-    )
-    _set_loggers(verbosity)
     logger.info('Verbosity set to %s', verbosity)
diff --git a/freqtrade/main.py b/freqtrade/main.py
index a96fd43c5..5f8d5d19d 100755
--- a/freqtrade/main.py
+++ b/freqtrade/main.py
@@ -3,20 +3,18 @@
 Main Freqtrade bot script.
 Read the documentation to know what cli arguments you need.
 """
-
+import logging
 import sys
+from typing import Any, List
+
+
 # check min. python version
 if sys.version_info < (3, 6):
     sys.exit("Freqtrade requires Python version >= 3.6")
 
-# flake8: noqa E402
-import logging
-from argparse import Namespace
-from typing import Any, List
-
-from freqtrade import OperationalException
-from freqtrade.configuration import Arguments
-from freqtrade.worker import Worker
+from freqtrade.commands import Arguments
+from freqtrade.exceptions import FreqtradeException, OperationalException
+from freqtrade.loggers import setup_logging_pre
 
 
 logger = logging.getLogger('freqtrade')
@@ -29,38 +27,36 @@ def main(sysargv: List[str] = None) -> None:
     """
 
     return_code: Any = 1
-    worker = None
     try:
-        arguments = Arguments(
-            sysargv,
-            'Free, open source crypto trading bot'
-        )
-        args: Namespace = arguments.get_parsed_arg()
+        setup_logging_pre()
+        arguments = Arguments(sysargv)
+        args = arguments.get_parsed_arg()
 
-        # A subcommand has been issued.
-        # Means if Backtesting or Hyperopt have been called we exit the bot
-        if hasattr(args, 'func'):
-            args.func(args)
-            # TODO: fetch return_code as returned by the command function here
-            return_code = 0
+        # Call subcommand.
+        if 'func' in args:
+            return_code = args['func'](args)
         else:
-            # Load and run worker
-            worker = Worker(args)
-            worker.run()
+            # No subcommand was issued.
+            raise OperationalException(
+                "Usage of Freqtrade requires a subcommand to be specified.\n"
+                "To have the bot executing trades in live/dry-run modes, "
+                "depending on the value of the `dry_run` setting in the config, run Freqtrade "
+                "as `freqtrade trade [options...]`.\n"
+                "To see the full list of options available, please use "
+                "`freqtrade --help` or `freqtrade <command> --help`."
+                )
 
     except SystemExit as e:
         return_code = e
     except KeyboardInterrupt:
         logger.info('SIGINT received, aborting ...')
         return_code = 0
-    except OperationalException as e:
+    except FreqtradeException as e:
         logger.error(str(e))
         return_code = 2
     except Exception:
         logger.exception('Fatal exception!')
     finally:
-        if worker:
-            worker.exit()
         sys.exit(return_code)
 
 
diff --git a/freqtrade/misc.py b/freqtrade/misc.py
index 05946e008..359d0d0e4 100644
--- a/freqtrade/misc.py
+++ b/freqtrade/misc.py
@@ -5,6 +5,9 @@ import gzip
 import logging
 import re
 from datetime import datetime
+from pathlib import Path
+from typing import Any
+from typing.io import IO
 
 import numpy as np
 import rapidjson
@@ -39,28 +42,32 @@ def datesarray_to_datetimearray(dates: np.ndarray) -> np.ndarray:
     return dates.dt.to_pydatetime()
 
 
-def file_dump_json(filename, data, is_zip=False) -> None:
+def file_dump_json(filename: Path, data: Any, is_zip: bool = False, log: bool = True) -> None:
     """
     Dump JSON data into a file
     :param filename: file to create
     :param data: JSON Data to save
     :return:
     """
-    logger.info(f'dumping json to "{filename}"')
 
     if is_zip:
-        if not filename.endswith('.gz'):
-            filename = filename + '.gz'
-        with gzip.open(filename, 'w') as fp:
-            rapidjson.dump(data, fp, default=str, number_mode=rapidjson.NM_NATIVE)
+        if filename.suffix != '.gz':
+            filename = filename.with_suffix('.gz')
+        if log:
+            logger.info(f'dumping json to "{filename}"')
+
+        with gzip.open(filename, 'w') as fpz:
+            rapidjson.dump(data, fpz, default=str, number_mode=rapidjson.NM_NATIVE)
     else:
+        if log:
+            logger.info(f'dumping json to "{filename}"')
         with open(filename, 'w') as fp:
             rapidjson.dump(data, fp, default=str, number_mode=rapidjson.NM_NATIVE)
 
     logger.debug(f'done json to "{filename}"')
 
 
-def json_load(datafile):
+def json_load(datafile: IO) -> Any:
     """
     load data with rapidjson
     Use this to have a consistent experience,
@@ -71,22 +78,30 @@ def json_load(datafile):
 
 def file_load_json(file):
 
-    gzipfile = file.with_suffix(file.suffix + '.gz')
-
+    if file.suffix != ".gz":
+        gzipfile = file.with_suffix(file.suffix + '.gz')
+    else:
+        gzipfile = file
     # Try gzip file first, otherwise regular json file.
     if gzipfile.is_file():
-        logger.debug('Loading ticker data from file %s', gzipfile)
-        with gzip.open(gzipfile) as tickerdata:
-            pairdata = json_load(tickerdata)
+        logger.debug(f"Loading historical data from file {gzipfile}")
+        with gzip.open(gzipfile) as datafile:
+            pairdata = json_load(datafile)
     elif file.is_file():
-        logger.debug('Loading ticker data from file %s', file)
-        with open(file) as tickerdata:
-            pairdata = json_load(tickerdata)
+        logger.debug(f"Loading historical data from file {file}")
+        with open(file) as datafile:
+            pairdata = json_load(datafile)
     else:
         return None
     return pairdata
 
 
+def pair_to_filename(pair: str) -> str:
+    for ch in ['/', '-', ' ', '.', '@', '$', '+', ':']:
+        pair = pair.replace(ch, '_')
+    return pair
+
+
 def format_ms_time(date: int) -> str:
     """
     convert MS date to readable format.
@@ -113,3 +128,67 @@ def deep_merge_dicts(source, destination):
             destination[key] = value
 
     return destination
+
+
+def round_dict(d, n):
+    """
+    Rounds float values in the dict to n digits after the decimal point.
+    """
+    return {k: (round(v, n) if isinstance(v, float) else v) for k, v in d.items()}
+
+
+def safe_value_fallback(obj: dict, key1: str, key2: str, default_value=None):
+    """
+    Search a value in obj, return this if it's not None.
+    Then search key2 in obj - return that if it's not none - then use default_value.
+    Else falls back to None.
+    """
+    if key1 in obj and obj[key1] is not None:
+        return obj[key1]
+    else:
+        if key2 in obj and obj[key2] is not None:
+            return obj[key2]
+    return default_value
+
+
+def safe_value_fallback2(dict1: dict, dict2: dict, key1: str, key2: str, default_value=None):
+    """
+    Search a value in dict1, return this if it's not None.
+    Fall back to dict2 - return key2 from dict2 if it's not None.
+    Else falls back to None.
+
+    """
+    if key1 in dict1 and dict1[key1] is not None:
+        return dict1[key1]
+    else:
+        if key2 in dict2 and dict2[key2] is not None:
+            return dict2[key2]
+    return default_value
+
+
+def plural(num: float, singular: str, plural: str = None) -> str:
+    return singular if (num == 1 or num == -1) else plural or singular + 's'
+
+
+def render_template(templatefile: str, arguments: dict = {}) -> str:
+
+    from jinja2 import Environment, PackageLoader, select_autoescape
+
+    env = Environment(
+        loader=PackageLoader('freqtrade', 'templates'),
+        autoescape=select_autoescape(['html', 'xml'])
+    )
+    template = env.get_template(templatefile)
+    return template.render(**arguments)
+
+
+def render_template_with_fallback(templatefile: str, templatefallbackfile: str,
+                                  arguments: dict = {}) -> str:
+    """
+    Use templatefile if possible, otherwise fall back to templatefallbackfile
+    """
+    from jinja2.exceptions import TemplateNotFound
+    try:
+        return render_template(templatefile, arguments)
+    except TemplateNotFound:
+        return render_template(templatefallbackfile, arguments)
diff --git a/freqtrade/optimize/__init__.py b/freqtrade/optimize/__init__.py
index 8b548eefe..e69de29bb 100644
--- a/freqtrade/optimize/__init__.py
+++ b/freqtrade/optimize/__init__.py
@@ -1,111 +0,0 @@
-import logging
-from argparse import Namespace
-from typing import Any, Dict
-
-from filelock import FileLock, Timeout
-
-from freqtrade import DependencyException, constants
-from freqtrade.state import RunMode
-from freqtrade.utils import setup_utils_configuration
-
-
-logger = logging.getLogger(__name__)
-
-
-def setup_configuration(args: Namespace, method: RunMode) -> Dict[str, Any]:
-    """
-    Prepare the configuration for the Hyperopt module
-    :param args: Cli args from Arguments()
-    :return: Configuration
-    """
-    config = setup_utils_configuration(args, method)
-
-    if method == RunMode.BACKTEST:
-        if config['stake_amount'] == constants.UNLIMITED_STAKE_AMOUNT:
-            raise DependencyException('stake amount could not be "%s" for backtesting' %
-                                      constants.UNLIMITED_STAKE_AMOUNT)
-
-    if method == RunMode.HYPEROPT:
-        # Special cases for Hyperopt
-        if config.get('strategy') and config.get('strategy') != 'DefaultStrategy':
-            logger.error("Please don't use --strategy for hyperopt.")
-            logger.error(
-                "Read the documentation at "
-                "https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md "
-                "to understand how to configure hyperopt.")
-            raise DependencyException("--strategy configured but not supported for hyperopt")
-
-    return config
-
-
-def start_backtesting(args: Namespace) -> None:
-    """
-    Start Backtesting script
-    :param args: Cli args from Arguments()
-    :return: None
-    """
-    # Import here to avoid loading backtesting module when it's not used
-    from freqtrade.optimize.backtesting import Backtesting
-
-    # Initialize configuration
-    config = setup_configuration(args, RunMode.BACKTEST)
-
-    logger.info('Starting freqtrade in Backtesting mode')
-
-    # Initialize backtesting object
-    backtesting = Backtesting(config)
-    backtesting.start()
-
-
-def start_hyperopt(args: Namespace) -> None:
-    """
-    Start hyperopt script
-    :param args: Cli args from Arguments()
-    :return: None
-    """
-    # Import here to avoid loading hyperopt module when it's not used
-    from freqtrade.optimize.hyperopt import Hyperopt, HYPEROPT_LOCKFILE
-
-    # Initialize configuration
-    config = setup_configuration(args, RunMode.HYPEROPT)
-
-    logger.info('Starting freqtrade in Hyperopt mode')
-
-    lock = FileLock(HYPEROPT_LOCKFILE)
-
-    try:
-        with lock.acquire(timeout=1):
-
-            # Remove noisy log messages
-            logging.getLogger('hyperopt.tpe').setLevel(logging.WARNING)
-            logging.getLogger('filelock').setLevel(logging.WARNING)
-
-            # Initialize backtesting object
-            hyperopt = Hyperopt(config)
-            hyperopt.start()
-
-    except Timeout:
-        logger.info("Another running instance of freqtrade Hyperopt detected.")
-        logger.info("Simultaneous execution of multiple Hyperopt commands is not supported. "
-                    "Hyperopt module is resource hungry. Please run your Hyperopts sequentially "
-                    "or on separate machines.")
-        logger.info("Quitting now.")
-        # TODO: return False here in order to help freqtrade to exit
-        # with non-zero exit code...
-        # Same in Edge and Backtesting start() functions.
-
-
-def start_edge(args: Namespace) -> None:
-    """
-    Start Edge script
-    :param args: Cli args from Arguments()
-    :return: None
-    """
-    from freqtrade.optimize.edge_cli import EdgeCli
-    # Initialize configuration
-    config = setup_configuration(args, RunMode.EDGE)
-    logger.info('Starting freqtrade in Edge mode')
-
-    # Initialize Edge object
-    edge_cli = EdgeCli(config)
-    edge_cli.start()
diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index 429633f31..883f7338c 100644
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -4,26 +4,39 @@
 This module contains the backtesting logic
 """
 import logging
+from collections import defaultdict
 from copy import deepcopy
 from datetime import datetime, timedelta
-from pathlib import Path
-from typing import Any, Dict, List, NamedTuple, Optional
+from typing import Any, Dict, List, NamedTuple, Optional, Tuple
 
 from pandas import DataFrame
-from tabulate import tabulate
 
-from freqtrade.configuration import Arguments
+from freqtrade.configuration import TimeRange, remove_credentials, validate_config_consistency
+from freqtrade.constants import DATETIME_PRINT_FORMAT
 from freqtrade.data import history
+from freqtrade.data.converter import trim_dataframe
 from freqtrade.data.dataprovider import DataProvider
-from freqtrade.exchange import timeframe_to_minutes
-from freqtrade.misc import file_dump_json
+from freqtrade.exceptions import OperationalException
+from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
+from freqtrade.optimize.optimize_reports import (generate_backtest_stats, show_backtest_results,
+                                                 store_backtest_stats)
+from freqtrade.pairlist.pairlistmanager import PairListManager
 from freqtrade.persistence import Trade
 from freqtrade.resolvers import ExchangeResolver, StrategyResolver
-from freqtrade.state import RunMode
-from freqtrade.strategy.interface import IStrategy, SellType
+from freqtrade.strategy.interface import IStrategy, SellCheckTuple, SellType
+
 
 logger = logging.getLogger(__name__)
 
+# Indexes for backtest tuples
+DATE_IDX = 0
+BUY_IDX = 1
+OPEN_IDX = 2
+CLOSE_IDX = 3
+SELL_IDX = 4
+LOW_IDX = 5
+HIGH_IDX = 6
+
 
 class BacktestResult(NamedTuple):
     """
@@ -32,18 +45,19 @@ class BacktestResult(NamedTuple):
     pair: str
     profit_percent: float
     profit_abs: float
-    open_time: datetime
-    close_time: datetime
-    open_index: int
-    close_index: int
+    open_date: datetime
+    open_rate: float
+    open_fee: float
+    close_date: datetime
+    close_rate: float
+    close_fee: float
+    amount: float
     trade_duration: float
     open_at_end: bool
-    open_rate: float
-    close_rate: float
     sell_reason: SellType
 
 
-class Backtesting(object):
+class Backtesting:
     """
     Backtesting class, this class contains all the logic to run a backtest
 
@@ -56,30 +70,53 @@ class Backtesting(object):
         self.config = config
 
         # Reset keys for backtesting
-        self.config['exchange']['key'] = ''
-        self.config['exchange']['secret'] = ''
-        self.config['exchange']['password'] = ''
-        self.config['exchange']['uid'] = ''
-        self.config['dry_run'] = True
+        remove_credentials(self.config)
         self.strategylist: List[IStrategy] = []
+        self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
 
-        self.exchange = ExchangeResolver(self.config['exchange']['name'], self.config).exchange
-        self.fee = self.exchange.get_fee()
-
-        if self.config.get('runmode') != RunMode.HYPEROPT:
-            self.dataprovider = DataProvider(self.config, self.exchange)
-            IStrategy.dp = self.dataprovider
+        dataprovider = DataProvider(self.config, self.exchange)
+        IStrategy.dp = dataprovider
 
         if self.config.get('strategy_list', None):
             for strat in list(self.config['strategy_list']):
                 stratconf = deepcopy(self.config)
                 stratconf['strategy'] = strat
-                self.strategylist.append(StrategyResolver(stratconf).strategy)
+                self.strategylist.append(StrategyResolver.load_strategy(stratconf))
+                validate_config_consistency(stratconf)
 
         else:
             # No strategy list specified, only one strategy
-            self.strategylist.append(StrategyResolver(self.config).strategy)
+            self.strategylist.append(StrategyResolver.load_strategy(self.config))
+            validate_config_consistency(self.config)
 
+        if "timeframe" not in self.config:
+            raise OperationalException("Timeframe (ticker interval) needs to be set in either "
+                                       "configuration or as cli argument `--timeframe 5m`")
+        self.timeframe = str(self.config.get('timeframe'))
+        self.timeframe_min = timeframe_to_minutes(self.timeframe)
+
+        self.pairlists = PairListManager(self.exchange, self.config)
+        if 'VolumePairList' in self.pairlists.name_list:
+            raise OperationalException("VolumePairList not allowed for backtesting.")
+
+        if len(self.strategylist) > 1 and 'PrecisionFilter' in self.pairlists.name_list:
+            raise OperationalException(
+                "PrecisionFilter not allowed for backtesting multiple strategies."
+            )
+
+        dataprovider.add_pairlisthandler(self.pairlists)
+        self.pairlists.refresh_pairlist()
+
+        if len(self.pairlists.whitelist) == 0:
+            raise OperationalException("No pair in whitelist.")
+
+        if config.get('fee', None) is not None:
+            self.fee = config['fee']
+        else:
+            self.fee = self.exchange.get_fee(symbol=self.pairlists.whitelist[0])
+
+        # Get maximum required startup period
+        self.required_startup = max([strat.startup_candle_count for strat in self.strategylist])
         # Load one (first) strategy
         self._set_strategy(self.strategylist[0])
 
@@ -87,386 +124,319 @@ class Backtesting(object):
         """
         Load strategy into backtesting
         """
-        self.strategy = strategy
-
-        self.ticker_interval = self.config.get('ticker_interval')
-        self.ticker_interval_mins = timeframe_to_minutes(self.ticker_interval)
-        self.advise_buy = strategy.advise_buy
-        self.advise_sell = strategy.advise_sell
+        self.strategy: IStrategy = strategy
         # Set stoploss_on_exchange to false for backtesting,
         # since a "perfect" stoploss-sell is assumed anyway
         # And the regular "stoploss" function would not apply to that case
         self.strategy.order_types['stoploss_on_exchange'] = False
 
-    def _generate_text_table(self, data: Dict[str, Dict], results: DataFrame,
-                             skip_nan: bool = False) -> str:
+    def load_bt_data(self) -> Tuple[Dict[str, DataFrame], TimeRange]:
+        timerange = TimeRange.parse_timerange(None if self.config.get(
+            'timerange') is None else str(self.config.get('timerange')))
+
+        data = history.load_data(
+            datadir=self.config['datadir'],
+            pairs=self.pairlists.whitelist,
+            timeframe=self.timeframe,
+            timerange=timerange,
+            startup_candles=self.required_startup,
+            fail_without_data=True,
+            data_format=self.config.get('dataformat_ohlcv', 'json'),
+        )
+
+        min_date, max_date = history.get_timerange(data)
+
+        logger.info(f'Loading data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
+                    f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
+                    f'({(max_date - min_date).days} days)..')
+
+        # Adjust startts forward if not enough data is available
+        timerange.adjust_start_if_necessary(timeframe_to_seconds(self.timeframe),
+                                            self.required_startup, min_date)
+
+        return data, timerange
+
+    def _get_ohlcv_as_lists(self, processed: Dict[str, DataFrame]) -> Dict[str, Tuple]:
         """
-        Generates and returns a text table for the given backtest data and the results dataframe
-        :return: pretty printed table with tabulate as str
-        """
-        stake_currency = str(self.config.get('stake_currency'))
-        max_open_trades = self.config.get('max_open_trades')
-
-        floatfmt = ('s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', '.1f', '.1f')
-        tabular_data = []
-        headers = ['pair', 'buy count', 'avg profit %', 'cum profit %',
-                   'tot profit ' + stake_currency, 'tot profit %', 'avg duration',
-                   'profit', 'loss']
-        for pair in data:
-            result = results[results.pair == pair]
-            if skip_nan and result.profit_abs.isnull().all():
-                continue
-
-            tabular_data.append([
-                pair,
-                len(result.index),
-                result.profit_percent.mean() * 100.0,
-                result.profit_percent.sum() * 100.0,
-                result.profit_abs.sum(),
-                result.profit_percent.sum() * 100.0 / max_open_trades,
-                str(timedelta(
-                    minutes=round(result.trade_duration.mean()))) if not result.empty else '0:00',
-                len(result[result.profit_abs > 0]),
-                len(result[result.profit_abs < 0])
-            ])
-
-        # Append Total
-        tabular_data.append([
-            'TOTAL',
-            len(results.index),
-            results.profit_percent.mean() * 100.0,
-            results.profit_percent.sum() * 100.0,
-            results.profit_abs.sum(),
-            results.profit_percent.sum() * 100.0 / max_open_trades,
-            str(timedelta(
-                minutes=round(results.trade_duration.mean()))) if not results.empty else '0:00',
-            len(results[results.profit_abs > 0]),
-            len(results[results.profit_abs < 0])
-        ])
-        # Ignore type as floatfmt does allow tuples but mypy does not know that
-        return tabulate(tabular_data, headers=headers,  # type: ignore
-                        floatfmt=floatfmt, tablefmt="pipe")
-
-    def _generate_text_table_sell_reason(self, data: Dict[str, Dict], results: DataFrame) -> str:
-        """
-        Generate small table outlining Backtest results
-        """
-        tabular_data = []
-        headers = ['Sell Reason', 'Count']
-        for reason, count in results['sell_reason'].value_counts().iteritems():
-            tabular_data.append([reason.value,  count])
-        return tabulate(tabular_data, headers=headers, tablefmt="pipe")
-
-    def _generate_text_table_strategy(self, all_results: dict) -> str:
-        """
-        Generate summary table per strategy
-        """
-        stake_currency = str(self.config.get('stake_currency'))
-        max_open_trades = self.config.get('max_open_trades')
-
-        floatfmt = ('s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', '.1f', '.1f')
-        tabular_data = []
-        headers = ['Strategy', 'buy count', 'avg profit %', 'cum profit %',
-                   'tot profit ' + stake_currency, 'tot profit %', 'avg duration',
-                   'profit', 'loss']
-        for strategy, results in all_results.items():
-            tabular_data.append([
-                strategy,
-                len(results.index),
-                results.profit_percent.mean() * 100.0,
-                results.profit_percent.sum() * 100.0,
-                results.profit_abs.sum(),
-                results.profit_percent.sum() * 100.0 / max_open_trades,
-                str(timedelta(
-                    minutes=round(results.trade_duration.mean()))) if not results.empty else '0:00',
-                len(results[results.profit_abs > 0]),
-                len(results[results.profit_abs < 0])
-            ])
-        # Ignore type as floatfmt does allow tuples but mypy does not know that
-        return tabulate(tabular_data, headers=headers,  # type: ignore
-                        floatfmt=floatfmt, tablefmt="pipe")
-
-    def _store_backtest_result(self, recordfilename: str, results: DataFrame,
-                               strategyname: Optional[str] = None) -> None:
-
-        records = [(t.pair, t.profit_percent, t.open_time.timestamp(),
-                    t.close_time.timestamp(), t.open_index - 1, t.trade_duration,
-                    t.open_rate, t.close_rate, t.open_at_end, t.sell_reason.value)
-                   for index, t in results.iterrows()]
-
-        if records:
-            if strategyname:
-                # Inject strategyname to filename
-                recname = Path(recordfilename)
-                recordfilename = str(Path.joinpath(
-                    recname.parent, f'{recname.stem}-{strategyname}').with_suffix(recname.suffix))
-            logger.info('Dumping backtest results to %s', recordfilename)
-            file_dump_json(recordfilename, records)
-
-    def _get_ticker_list(self, processed) -> Dict[str, DataFrame]:
-        """
-        Helper function to convert a processed tickerlist into a list for performance reasons.
+        Helper function to convert a processed dataframes into lists for performance reasons.
 
         Used by backtest() - so keep this optimized for performance.
         """
+        # Every change to this headers list must evaluate further usages of the resulting tuple
+        # and eventually change the constants for indexes at the top
         headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high']
-        ticker: Dict = {}
-        # Create ticker dict
+        data: Dict = {}
+        # Create dict with data
         for pair, pair_data in processed.items():
-            pair_data['buy'], pair_data['sell'] = 0, 0  # cleanup from previous run
+            pair_data.loc[:, 'buy'] = 0  # cleanup from previous run
+            pair_data.loc[:, 'sell'] = 0  # cleanup from previous run
 
-            ticker_data = self.advise_sell(
-                self.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
+            df_analyzed = self.strategy.advise_sell(
+                self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
 
-            # to avoid using data from future, we buy/sell with signal from previous candle
-            ticker_data.loc[:, 'buy'] = ticker_data['buy'].shift(1)
-            ticker_data.loc[:, 'sell'] = ticker_data['sell'].shift(1)
+            # To avoid using data from future, we use buy/sell signals shifted
+            # from the previous candle
+            df_analyzed.loc[:, 'buy'] = df_analyzed.loc[:, 'buy'].shift(1)
+            df_analyzed.loc[:, 'sell'] = df_analyzed.loc[:, 'sell'].shift(1)
 
-            ticker_data.drop(ticker_data.head(1).index, inplace=True)
+            df_analyzed.drop(df_analyzed.head(1).index, inplace=True)
 
             # Convert from Pandas to list for performance reasons
             # (Looping Pandas is slow.)
-            ticker[pair] = [x for x in ticker_data.itertuples()]
-        return ticker
+            data[pair] = [x for x in df_analyzed.itertuples(index=False, name=None)]
+        return data
 
-    def _get_sell_trade_entry(
-            self, pair: str, buy_row: DataFrame,
-            partial_ticker: List, trade_count_lock: Dict,
-            stake_amount: float, max_open_trades: int) -> Optional[BacktestResult]:
+    def _get_close_rate(self, sell_row: Tuple, trade: Trade, sell: SellCheckTuple,
+                        trade_dur: int) -> float:
+        """
+        Get close rate for backtesting result
+        """
+        # Special handling if high or low hit STOP_LOSS or ROI
+        if sell.sell_type in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
+            # Set close_rate to stoploss
+            return trade.stop_loss
+        elif sell.sell_type == (SellType.ROI):
+            roi_entry, roi = self.strategy.min_roi_reached_entry(trade_dur)
+            if roi is not None and roi_entry is not None:
+                if roi == -1 and roi_entry % self.timeframe_min == 0:
+                    # When forceselling with ROI=-1, the roi time will always be equal to trade_dur.
+                    # If that entry is a multiple of the timeframe (so on candle open)
+                    # - we'll use open instead of close
+                    return sell_row[OPEN_IDX]
 
-        trade = Trade(
-            open_rate=buy_row.open,
-            open_date=buy_row.date,
-            stake_amount=stake_amount,
-            amount=stake_amount / buy_row.open,
-            fee_open=self.fee,
-            fee_close=self.fee
-        )
+                # - (Expected abs profit + open_rate + open_fee) / (fee_close -1)
+                close_rate = - (trade.open_rate * roi + trade.open_rate *
+                                (1 + trade.fee_open)) / (trade.fee_close - 1)
 
-        # calculate win/lose forwards from buy point
-        for sell_row in partial_ticker:
-            if max_open_trades > 0:
-                # Increase trade_count_lock for every iteration
-                trade_count_lock[sell_row.date] = trade_count_lock.get(sell_row.date, 0) + 1
+                if (trade_dur > 0 and trade_dur == roi_entry
+                        and roi_entry % self.timeframe_min == 0
+                        and sell_row[OPEN_IDX] > close_rate):
+                    # new ROI entry came into effect.
+                    # use Open rate if open_rate > calculated sell rate
+                    return sell_row[OPEN_IDX]
 
-            sell = self.strategy.should_sell(trade, sell_row.open, sell_row.date, sell_row.buy,
-                                             sell_row.sell, low=sell_row.low, high=sell_row.high)
-            if sell.sell_flag:
-                trade_dur = int((sell_row.date - buy_row.date).total_seconds() // 60)
-                # Special handling if high or low hit STOP_LOSS or ROI
-                if sell.sell_type in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
-                    # Set close_rate to stoploss
-                    closerate = trade.stop_loss
-                elif sell.sell_type == (SellType.ROI):
-                    roi = self.strategy.min_roi_reached_entry(trade_dur)
-                    if roi is not None:
-                        # - (Expected abs profit + open_rate + open_fee) / (fee_close -1)
-                        closerate = - (trade.open_rate * roi + trade.open_rate *
-                                       (1 + trade.fee_open)) / (trade.fee_close - 1)
-                    else:
-                        # This should not be reached...
-                        closerate = sell_row.open
-                else:
-                    closerate = sell_row.open
+                # Use the maximum between close_rate and low as we
+                # cannot sell outside of a candle.
+                # Applies when a new ROI setting comes in place and the whole candle is above that.
+                return max(close_rate, sell_row[LOW_IDX])
 
-                return BacktestResult(pair=pair,
-                                      profit_percent=trade.calc_profit_percent(rate=closerate),
-                                      profit_abs=trade.calc_profit(rate=closerate),
-                                      open_time=buy_row.date,
-                                      close_time=sell_row.date,
-                                      trade_duration=trade_dur,
-                                      open_index=buy_row.Index,
-                                      close_index=sell_row.Index,
-                                      open_at_end=False,
-                                      open_rate=buy_row.open,
-                                      close_rate=closerate,
-                                      sell_reason=sell.sell_type
-                                      )
-        if partial_ticker:
-            # no sell condition found - trade stil open at end of backtest period
-            sell_row = partial_ticker[-1]
-            btr = BacktestResult(pair=pair,
-                                 profit_percent=trade.calc_profit_percent(rate=sell_row.open),
-                                 profit_abs=trade.calc_profit(rate=sell_row.open),
-                                 open_time=buy_row.date,
-                                 close_time=sell_row.date,
-                                 trade_duration=int((
-                                     sell_row.date - buy_row.date).total_seconds() // 60),
-                                 open_index=buy_row.Index,
-                                 close_index=sell_row.Index,
-                                 open_at_end=True,
-                                 open_rate=buy_row.open,
-                                 close_rate=sell_row.open,
-                                 sell_reason=SellType.FORCE_SELL
-                                 )
-            logger.debug('Force_selling still open trade %s with %s perc - %s', btr.pair,
-                         btr.profit_percent, btr.profit_abs)
-            return btr
+            else:
+                # This should not be reached...
+                return sell_row[OPEN_IDX]
+        else:
+            return sell_row[OPEN_IDX]
+
+    def _get_sell_trade_entry(self, trade: Trade, sell_row: Tuple) -> Optional[BacktestResult]:
+
+        sell = self.strategy.should_sell(trade, sell_row[OPEN_IDX], sell_row[DATE_IDX],
+                                         sell_row[BUY_IDX], sell_row[SELL_IDX],
+                                         low=sell_row[LOW_IDX], high=sell_row[HIGH_IDX])
+        if sell.sell_flag:
+            trade_dur = int((sell_row[DATE_IDX] - trade.open_date).total_seconds() // 60)
+            closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)
+
+            return BacktestResult(pair=trade.pair,
+                                  profit_percent=trade.calc_profit_ratio(rate=closerate),
+                                  profit_abs=trade.calc_profit(rate=closerate),
+                                  open_date=trade.open_date,
+                                  open_rate=trade.open_rate,
+                                  open_fee=self.fee,
+                                  close_date=sell_row[DATE_IDX],
+                                  close_rate=closerate,
+                                  close_fee=self.fee,
+                                  amount=trade.amount,
+                                  trade_duration=trade_dur,
+                                  open_at_end=False,
+                                  sell_reason=sell.sell_type
+                                  )
         return None
 
-    def backtest(self, args: Dict) -> DataFrame:
+    def handle_left_open(self, open_trades: Dict[str, List[Trade]],
+                         data: Dict[str, List[Tuple]]) -> List[BacktestResult]:
         """
-        Implements backtesting functionality
+        Handling of left open trades at the end of backtesting
+        """
+        trades = []
+        for pair in open_trades.keys():
+            if len(open_trades[pair]) > 0:
+                for trade in open_trades[pair]:
+                    sell_row = data[pair][-1]
+                    trade_entry = BacktestResult(pair=trade.pair,
+                                                 profit_percent=trade.calc_profit_ratio(
+                                                     rate=sell_row[OPEN_IDX]),
+                                                 profit_abs=trade.calc_profit(sell_row[OPEN_IDX]),
+                                                 open_date=trade.open_date,
+                                                 open_rate=trade.open_rate,
+                                                 open_fee=self.fee,
+                                                 close_date=sell_row[DATE_IDX],
+                                                 close_rate=sell_row[OPEN_IDX],
+                                                 close_fee=self.fee,
+                                                 amount=trade.amount,
+                                                 trade_duration=int((
+                                                     sell_row[DATE_IDX] - trade.open_date
+                                                 ).total_seconds() // 60),
+                                                 open_at_end=True,
+                                                 sell_reason=SellType.FORCE_SELL
+                                                 )
+                    trades.append(trade_entry)
+        return trades
+
+    def backtest(self, processed: Dict, stake_amount: float,
+                 start_date: datetime, end_date: datetime,
+                 max_open_trades: int = 0, position_stacking: bool = False) -> DataFrame:
+        """
+        Implement backtesting functionality
 
         NOTE: This method is used by Hyperopt at each iteration. Please keep it optimized.
         Of course try to not have ugly code. By some accessor are sometime slower than functions.
-        Avoid, logging on this method
+        Avoid extensive logging in this method and functions it calls.
 
-        :param args: a dict containing:
-            stake_amount: btc amount to use for each trade
-            processed: a processed dictionary with format {pair, data}
-            max_open_trades: maximum number of concurrent trades (default: 0, disabled)
-            position_stacking: do we allow position stacking? (default: False)
-        :return: DataFrame
+        :param processed: a processed dictionary with format {pair, data}
+        :param stake_amount: amount to use for each trade
+        :param start_date: backtesting timerange start datetime
+        :param end_date: backtesting timerange end datetime
+        :param max_open_trades: maximum number of concurrent trades, <= 0 means unlimited
+        :param position_stacking: do we allow position stacking?
+        :return: DataFrame with trades (results of backtesting)
         """
-        # Arguments are long and noisy, so this is commented out.
-        # Uncomment if you need to debug the backtest() method.
-#        logger.debug(f"Start backtest, args: {args}")
-        processed = args['processed']
-        stake_amount = args['stake_amount']
-        max_open_trades = args.get('max_open_trades', 0)
-        position_stacking = args.get('position_stacking', False)
-        start_date = args['start_date']
-        end_date = args['end_date']
+        logger.debug(f"Run backtest, stake_amount: {stake_amount}, "
+                     f"start_date: {start_date}, end_date: {end_date}, "
+                     f"max_open_trades: {max_open_trades}, position_stacking: {position_stacking}"
+                     )
         trades = []
-        trade_count_lock: Dict = {}
 
-        # Dict of ticker-lists for performance (looping lists is a lot faster than dataframes)
-        ticker: Dict = self._get_ticker_list(processed)
+        # Use dict of lists with data for performance
+        # (looping lists is a lot faster than pandas DataFrames)
+        data: Dict = self._get_ohlcv_as_lists(processed)
 
-        lock_pair_until: Dict = {}
         # Indexes per pair, so some pairs are allowed to have a missing start.
         indexes: Dict = {}
-        tmp = start_date + timedelta(minutes=self.ticker_interval_mins)
+        tmp = start_date + timedelta(minutes=self.timeframe_min)
+
+        open_trades: Dict[str, List] = defaultdict(list)
+        open_trade_count = 0
 
         # Loop timerange and get candle for each pair at that point in time
-        while tmp < end_date:
+        while tmp <= end_date:
+            open_trade_count_start = open_trade_count
 
-            for i, pair in enumerate(ticker):
+            for i, pair in enumerate(data):
                 if pair not in indexes:
                     indexes[pair] = 0
 
                 try:
-                    row = ticker[pair][indexes[pair]]
+                    row = data[pair][indexes[pair]]
                 except IndexError:
                     # missing Data for one pair at the end.
                     # Warnings for this are shown during data loading
                     continue
 
                 # Waits until the time-counter reaches the start of the data for this pair.
-                if row.date > tmp.datetime:
+                if row[DATE_IDX] > tmp:
                     continue
-
                 indexes[pair] += 1
 
-                if row.buy == 0 or row.sell == 1:
-                    continue  # skip rows where no buy signal or that would immediately sell off
+                # without positionstacking, we can only have one open trade per pair.
+                # max_open_trades must be respected
+                # don't open on the last row
+                if ((position_stacking or len(open_trades[pair]) == 0)
+                        and (max_open_trades <= 0 or open_trade_count_start < max_open_trades)
+                        and tmp != end_date
+                        and row[BUY_IDX] == 1 and row[SELL_IDX] != 1):
+                    # Enter trade
+                    trade = Trade(
+                        pair=pair,
+                        open_rate=row[OPEN_IDX],
+                        open_date=row[DATE_IDX],
+                        stake_amount=stake_amount,
+                        amount=round(stake_amount / row[OPEN_IDX], 8),
+                        fee_open=self.fee,
+                        fee_close=self.fee,
+                        is_open=True,
+                    )
+                    # TODO: hacky workaround to avoid opening > max_open_trades
+                    # This emulates previous behaviour - not sure if this is correct
+                    # Prevents buying if the trade-slot was freed in this candle
+                    open_trade_count_start += 1
+                    open_trade_count += 1
+                    # logger.debug(f"{pair} - Backtesting emulates creation of new trade: {trade}.")
+                    open_trades[pair].append(trade)
 
-                if (not position_stacking and pair in lock_pair_until
-                        and row.date <= lock_pair_until[pair]):
-                    # without positionstacking, we can only have one open trade per pair.
-                    continue
-
-                if max_open_trades > 0:
-                    # Check if max_open_trades has already been reached for the given date
-                    if not trade_count_lock.get(row.date, 0) < max_open_trades:
-                        continue
-                    trade_count_lock[row.date] = trade_count_lock.get(row.date, 0) + 1
-
-                trade_entry = self._get_sell_trade_entry(pair, row, ticker[pair][indexes[pair]:],
-                                                         trade_count_lock, stake_amount,
-                                                         max_open_trades)
-
-                if trade_entry:
-                    lock_pair_until[pair] = trade_entry.close_time
-                    trades.append(trade_entry)
-                else:
-                    # Set lock_pair_until to end of testing period if trade could not be closed
-                    lock_pair_until[pair] = end_date.datetime
+                for trade in open_trades[pair]:
+                    # since indexes has been incremented before, we need to go one step back to
+                    # also check the buying candle for sell conditions.
+                    trade_entry = self._get_sell_trade_entry(trade, row)
+                    # Sell occured
+                    if trade_entry:
+                        # logger.debug(f"{pair} - Backtesting sell {trade}")
+                        open_trade_count -= 1
+                        open_trades[pair].remove(trade)
+                        trades.append(trade_entry)
 
             # Move time one configured time_interval ahead.
-            tmp += timedelta(minutes=self.ticker_interval_mins)
+            tmp += timedelta(minutes=self.timeframe_min)
+
+        trades += self.handle_left_open(open_trades, data=data)
+
         return DataFrame.from_records(trades, columns=BacktestResult._fields)
 
     def start(self) -> None:
         """
-        Run a backtesting end-to-end
+        Run backtesting end-to-end
         :return: None
         """
         data: Dict[str, Any] = {}
-        pairs = self.config['exchange']['pair_whitelist']
+
         logger.info('Using stake_currency: %s ...', self.config['stake_currency'])
         logger.info('Using stake_amount: %s ...', self.config['stake_amount'])
 
-        timerange = Arguments.parse_timerange(None if self.config.get(
-            'timerange') is None else str(self.config.get('timerange')))
-        data = history.load_data(
-            datadir=Path(self.config['datadir']) if self.config.get('datadir') else None,
-            pairs=pairs,
-            ticker_interval=self.ticker_interval,
-            refresh_pairs=self.config.get('refresh_pairs', False),
-            exchange=self.exchange,
-            timerange=timerange,
-            live=self.config.get('live', False)
-        )
+        position_stacking = self.config.get('position_stacking', False)
+
+        data, timerange = self.load_bt_data()
 
-        if not data:
-            logger.critical("No data found. Terminating.")
-            return
-        # Use max_open_trades in backtesting, except --disable-max-market-positions is set
-        if self.config.get('use_max_market_positions', True):
-            max_open_trades = self.config['max_open_trades']
-        else:
-            logger.info('Ignoring max_open_trades (--disable-max-market-positions was used) ...')
-            max_open_trades = 0
         all_results = {}
-
-        min_date, max_date = history.get_timeframe(data)
-
-        logger.info(
-            'Backtesting with data from %s up to %s (%s days)..',
-            min_date.isoformat(),
-            max_date.isoformat(),
-            (max_date - min_date).days
-        )
-
         for strat in self.strategylist:
             logger.info("Running backtesting for Strategy %s", strat.get_strategy_name())
             self._set_strategy(strat)
 
+            # Use max_open_trades in backtesting, except --disable-max-market-positions is set
+            if self.config.get('use_max_market_positions', True):
+                # Must come from strategy config, as the strategy may modify this setting.
+                max_open_trades = self.strategy.config['max_open_trades']
+            else:
+                logger.info(
+                    'Ignoring max_open_trades (--disable-max-market-positions was used) ...')
+                max_open_trades = 0
+
             # need to reprocess data every time to populate signals
-            preprocessed = self.strategy.tickerdata_to_dataframe(data)
+            preprocessed = self.strategy.ohlcvdata_to_dataframe(data)
 
+            # Trim startup period from analyzed dataframe
+            for pair, df in preprocessed.items():
+                preprocessed[pair] = trim_dataframe(df, timerange)
+            min_date, max_date = history.get_timerange(preprocessed)
+
+            logger.info(f'Backtesting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
+                        f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
+                        f'({(max_date - min_date).days} days)..')
             # Execute backtest and print results
-            all_results[self.strategy.get_strategy_name()] = self.backtest(
-                {
-                    'stake_amount': self.config.get('stake_amount'),
-                    'processed': preprocessed,
-                    'max_open_trades': max_open_trades,
-                    'position_stacking': self.config.get('position_stacking', False),
-                    'start_date': min_date,
-                    'end_date': max_date,
-                }
+            results = self.backtest(
+                processed=preprocessed,
+                stake_amount=self.config['stake_amount'],
+                start_date=min_date.datetime,
+                end_date=max_date.datetime,
+                max_open_trades=max_open_trades,
+                position_stacking=position_stacking,
             )
+            all_results[self.strategy.get_strategy_name()] = {
+                'results': results,
+                'config': self.strategy.config,
+            }
 
-        for strategy, results in all_results.items():
+        stats = generate_backtest_stats(data, all_results, min_date=min_date, max_date=max_date)
 
-            if self.config.get('export', False):
-                self._store_backtest_result(self.config['exportfilename'], results,
-                                            strategy if len(self.strategylist) > 1 else None)
+        if self.config.get('export', False):
+            store_backtest_stats(self.config['exportfilename'], stats)
 
-            print(f"Result for strategy {strategy}")
-            print(' BACKTESTING REPORT '.center(133, '='))
-            print(self._generate_text_table(data, results))
-
-            print(' SELL REASON STATS '.center(133, '='))
-            print(self._generate_text_table_sell_reason(data, results))
-
-            print(' LEFT OPEN TRADES REPORT '.center(133, '='))
-            print(self._generate_text_table(data, results.loc[results.open_at_end], True))
-            print()
-        if len(all_results) > 1:
-            # Print Strategy summary table
-            print(' Strategy Summary '.center(133, '='))
-            print(self._generate_text_table_strategy(all_results))
-            print('\nFor more details, please look at the detail tables above')
+        # Show backtest results
+        show_backtest_results(self.config, stats)
diff --git a/freqtrade/optimize/default_hyperopt_loss.py b/freqtrade/optimize/default_hyperopt_loss.py
index 2879c4091..9dbdc4403 100644
--- a/freqtrade/optimize/default_hyperopt_loss.py
+++ b/freqtrade/optimize/default_hyperopt_loss.py
@@ -1,33 +1,32 @@
 """
-DefaultHyperOptLoss
+ShortTradeDurHyperOptLoss
 This module defines the default HyperoptLoss class which is being used for
 Hyperoptimization.
 """
-
 from math import exp
 
 from pandas import DataFrame
 
 from freqtrade.optimize.hyperopt import IHyperOptLoss
 
-# Define some constants:
 
-# set TARGET_TRADES to suit your number concurrent trades so its realistic
+# Set TARGET_TRADES to suit your number concurrent trades so its realistic
 # to the number of days
 TARGET_TRADES = 600
+
 # This is assumed to be expected avg profit * expected trade count.
 # For example, for 0.35% avg per trade (or 0.0035 as ratio) and 1100 trades,
-# self.expected_max_profit = 3.85
+# expected max profit = 3.85
 # Check that the reported Σ% values do not exceed this!
 # Note, this is ratio. 3.85 stated above means 385Σ%.
 EXPECTED_MAX_PROFIT = 3.0
 
-# max average trade duration in minutes
-# if eval ends with higher value, we consider it a failed eval
+# Max average trade duration in minutes.
+# If eval ends with higher value, we consider it a failed eval.
 MAX_ACCEPTED_TRADE_DURATION = 300
 
 
-class DefaultHyperOptLoss(IHyperOptLoss):
+class ShortTradeDurHyperOptLoss(IHyperOptLoss):
     """
     Defines the default loss function for hyperopt
     """
@@ -43,11 +42,15 @@ class DefaultHyperOptLoss(IHyperOptLoss):
         * 0.25: Avoiding trade loss
         * 1.0 to total profit, compared to the expected value (`EXPECTED_MAX_PROFIT`) defined above
         """
-        total_profit = results.profit_percent.sum()
-        trade_duration = results.trade_duration.mean()
+        total_profit = results['profit_percent'].sum()
+        trade_duration = results['trade_duration'].mean()
 
         trade_loss = 1 - 0.25 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.8)
         profit_loss = max(0, 1 - total_profit / EXPECTED_MAX_PROFIT)
         duration_loss = 0.4 * min(trade_duration / MAX_ACCEPTED_TRADE_DURATION, 1)
         result = trade_loss + profit_loss + duration_loss
         return result
+
+
+# Create an alias for This to allow the legacy Method to work as well.
+DefaultHyperOptLoss = ShortTradeDurHyperOptLoss
diff --git a/freqtrade/optimize/edge_cli.py b/freqtrade/optimize/edge_cli.py
index 8d1fa381b..a5f505bee 100644
--- a/freqtrade/optimize/edge_cli.py
+++ b/freqtrade/optimize/edge_cli.py
@@ -4,19 +4,19 @@
 This module contains the edge backtesting interface
 """
 import logging
-from typing import Dict, Any
-from tabulate import tabulate
-from freqtrade import constants
-from freqtrade.edge import Edge
+from typing import Any, Dict
+
+from freqtrade import constants
+from freqtrade.configuration import TimeRange, remove_credentials, validate_config_consistency
+from freqtrade.edge import Edge
+from freqtrade.optimize.optimize_reports import generate_edge_table
+from freqtrade.resolvers import ExchangeResolver, StrategyResolver
 
-from freqtrade.configuration import Arguments
-from freqtrade.exchange import Exchange
-from freqtrade.resolvers import StrategyResolver
 
 logger = logging.getLogger(__name__)
 
 
-class EdgeCli(object):
+class EdgeCli:
     """
     EdgeCli class, this class contains all the logic to run edge backtesting
 
@@ -29,50 +29,22 @@ class EdgeCli(object):
         self.config = config
 
         # Reset keys for edge
-        self.config['exchange']['key'] = ''
-        self.config['exchange']['secret'] = ''
-        self.config['exchange']['password'] = ''
-        self.config['exchange']['uid'] = ''
+        remove_credentials(self.config)
         self.config['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
-        self.config['dry_run'] = True
-        self.exchange = Exchange(self.config)
-        self.strategy = StrategyResolver(self.config).strategy
+        self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
+        self.strategy = StrategyResolver.load_strategy(self.config)
+
+        validate_config_consistency(self.config)
 
         self.edge = Edge(config, self.exchange, self.strategy)
-        self.edge._refresh_pairs = self.config.get('refresh_pairs', False)
+        # Set refresh_pairs to false for edge-cli (it must be true for edge)
+        self.edge._refresh_pairs = False
 
-        self.timerange = Arguments.parse_timerange(None if self.config.get(
+        self.edge._timerange = TimeRange.parse_timerange(None if self.config.get(
             'timerange') is None else str(self.config.get('timerange')))
 
-        self.edge._timerange = self.timerange
-
-    def _generate_edge_table(self, results: dict) -> str:
-
-        floatfmt = ('s', '.10g', '.2f', '.2f', '.2f', '.2f', 'd', '.d')
-        tabular_data = []
-        headers = ['pair', 'stoploss', 'win rate', 'risk reward ratio',
-                   'required risk reward', 'expectancy', 'total number of trades',
-                   'average duration (min)']
-
-        for result in results.items():
-            if result[1].nb_trades > 0:
-                tabular_data.append([
-                    result[0],
-                    result[1].stoploss,
-                    result[1].winrate,
-                    result[1].risk_reward_ratio,
-                    result[1].required_risk_reward,
-                    result[1].expectancy,
-                    result[1].nb_trades,
-                    round(result[1].avg_trade_duration)
-                ])
-
-        # Ignore type as floatfmt does allow tuples but mypy does not know that
-        return tabulate(tabular_data, headers=headers,  # type: ignore
-                        floatfmt=floatfmt, tablefmt="pipe")
-
     def start(self) -> None:
         result = self.edge.calculate()
         if result:
             print('')  # blank line for readability
-            print(self._generate_edge_table(self.edge._cached_pairs))
+            print(generate_edge_table(self.edge._cached_pairs))
diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py
index 759ceffbe..7870ba1cf 100644
--- a/freqtrade/optimize/hyperopt.py
+++ b/freqtrade/optimize/hyperopt.py
@@ -4,39 +4,61 @@
 This module contains the hyperopt logic
 """
 
+import io
+import locale
 import logging
-import os
-import sys
-
+import random
+import warnings
+from collections import OrderedDict
+from datetime import datetime
+from math import ceil
 from operator import itemgetter
 from pathlib import Path
-from pprint import pprint
-from typing import Any, Dict, List
+from pprint import pformat
+from typing import Any, Dict, List, Optional
 
-from joblib import Parallel, delayed, dump, load, wrap_non_picklable_objects, cpu_count
-from pandas import DataFrame
-from skopt import Optimizer
-from skopt.space import Dimension
+import progressbar
+import rapidjson
+import tabulate
+from colorama import Fore, Style
+from colorama import init as colorama_init
+from joblib import Parallel, cpu_count, delayed, dump, load, wrap_non_picklable_objects
+from pandas import DataFrame, isna, json_normalize
 
-from freqtrade.configuration import Arguments
-from freqtrade.data.history import load_data, get_timeframe
+from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN
+from freqtrade.data.converter import trim_dataframe
+from freqtrade.data.history import get_timerange
+from freqtrade.exceptions import OperationalException
+from freqtrade.misc import file_dump_json, plural, round_dict
 from freqtrade.optimize.backtesting import Backtesting
-# Import IHyperOptLoss to allow users import from this file
-from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss  # noqa: F4
-from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver, HyperOptLossResolver
+# Import IHyperOpt and IHyperOptLoss to allow unpickling classes from these modules
+from freqtrade.optimize.hyperopt_interface import IHyperOpt  # noqa: F401
+from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss  # noqa: F401
+from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver, HyperOptResolver
+from freqtrade.strategy import IStrategy
 
 
+# Suppress scikit-learn FutureWarnings from skopt
+with warnings.catch_warnings():
+    warnings.filterwarnings("ignore", category=FutureWarning)
+    from skopt import Optimizer
+    from skopt.space import Dimension
+
+progressbar.streams.wrap_stderr()
+progressbar.streams.wrap_stdout()
 logger = logging.getLogger(__name__)
 
 
 INITIAL_POINTS = 30
+
+# Keep no more than SKOPT_MODEL_QUEUE_SIZE models
+# in the skopt model queue, to optimize memory consumption
+SKOPT_MODEL_QUEUE_SIZE = 10
+
 MAX_LOSS = 100000  # just a big enough number to be bad result in loss optimization
-TICKERDATA_PICKLE = os.path.join('user_data', 'hyperopt_tickerdata.pkl')
-TRIALSDATA_PICKLE = os.path.join('user_data', 'hyperopt_results.pickle')
-HYPEROPT_LOCKFILE = os.path.join('user_data', 'hyperopt.lock')
 
 
-class Hyperopt(Backtesting):
+class Hyperopt:
     """
     Hyperopt class, this class contains all the logic to run a hyperopt simulation
 
@@ -44,306 +66,693 @@ class Hyperopt(Backtesting):
     hyperopt = Hyperopt(config)
     hyperopt.start()
     """
+
     def __init__(self, config: Dict[str, Any]) -> None:
-        super().__init__(config)
-        self.custom_hyperopt = HyperOptResolver(self.config).hyperopt
+        self.config = config
 
-        self.custom_hyperoptloss = HyperOptLossResolver(self.config).hyperoptloss
+        self.backtesting = Backtesting(self.config)
+
+        self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config)
+
+        self.custom_hyperoptloss = HyperOptLossResolver.load_hyperoptloss(self.config)
         self.calculate_loss = self.custom_hyperoptloss.hyperopt_loss_function
+        time_now = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
+        self.results_file = (self.config['user_data_dir'] /
+                             'hyperopt_results' / f'hyperopt_results_{time_now}.pickle')
+        self.data_pickle_file = (self.config['user_data_dir'] /
+                                 'hyperopt_results' / 'hyperopt_tickerdata.pkl')
+        self.total_epochs = config.get('epochs', 0)
 
-        self.total_tries = config.get('epochs', 0)
         self.current_best_loss = 100
 
-        if not self.config.get('hyperopt_continue'):
-            self.clean_hyperopt()
-        else:
-            logger.info("Continuing on previous hyperopt results.")
+        self.clean_hyperopt()
+
+        self.num_epochs_saved = 0
 
         # Previous evaluations
-        self.trials_file = TRIALSDATA_PICKLE
-        self.trials: List = []
+        self.epochs: List = []
 
         # Populate functions here (hasattr is slow so should not be run during "regular" operations)
+        if hasattr(self.custom_hyperopt, 'populate_indicators'):
+            self.backtesting.strategy.advise_indicators = (  # type: ignore
+                self.custom_hyperopt.populate_indicators)  # type: ignore
         if hasattr(self.custom_hyperopt, 'populate_buy_trend'):
-            self.advise_buy = self.custom_hyperopt.populate_buy_trend  # type: ignore
-
+            self.backtesting.strategy.advise_buy = (  # type: ignore
+                self.custom_hyperopt.populate_buy_trend)  # type: ignore
         if hasattr(self.custom_hyperopt, 'populate_sell_trend'):
-            self.advise_sell = self.custom_hyperopt.populate_sell_trend  # type: ignore
+            self.backtesting.strategy.advise_sell = (  # type: ignore
+                self.custom_hyperopt.populate_sell_trend)  # type: ignore
 
-            # Use max_open_trades for hyperopt as well, except --disable-max-market-positions is set
+        # Use max_open_trades for hyperopt as well, except --disable-max-market-positions is set
         if self.config.get('use_max_market_positions', True):
             self.max_open_trades = self.config['max_open_trades']
         else:
             logger.debug('Ignoring max_open_trades (--disable-max-market-positions was used) ...')
             self.max_open_trades = 0
-        self.position_stacking = self.config.get('position_stacking', False),
+        self.position_stacking = self.config.get('position_stacking', False)
 
-    def clean_hyperopt(self):
+        if self.has_space('sell'):
+            # Make sure use_sell_signal is enabled
+            if 'ask_strategy' not in self.config:
+                self.config['ask_strategy'] = {}
+            self.config['ask_strategy']['use_sell_signal'] = True
+
+        self.print_all = self.config.get('print_all', False)
+        self.hyperopt_table_header = 0
+        self.print_colorized = self.config.get('print_colorized', False)
+        self.print_json = self.config.get('print_json', False)
+
+    @staticmethod
+    def get_lock_filename(config: Dict[str, Any]) -> str:
+
+        return str(config['user_data_dir'] / 'hyperopt.lock')
+
+    def clean_hyperopt(self) -> None:
         """
         Remove hyperopt pickle files to restart hyperopt.
         """
-        for f in [TICKERDATA_PICKLE, TRIALSDATA_PICKLE]:
+        for f in [self.data_pickle_file, self.results_file]:
             p = Path(f)
             if p.is_file():
                 logger.info(f"Removing `{p}`.")
                 p.unlink()
 
-    def get_args(self, params):
-        dimensions = self.hyperopt_space()
+    def _get_params_dict(self, raw_params: List[Any]) -> Dict:
+
+        dimensions: List[Dimension] = self.dimensions
+
         # Ensure the number of dimensions match
-        # the number of parameters in the list x.
-        if len(params) != len(dimensions):
-            raise ValueError('Mismatch in number of search-space dimensions. '
-                             f'len(dimensions)=={len(dimensions)} and len(x)=={len(params)}')
+        # the number of parameters in the list.
+        if len(raw_params) != len(dimensions):
+            raise ValueError('Mismatch in number of search-space dimensions.')
 
-        # Create a dict where the keys are the names of the dimensions
-        # and the values are taken from the list of parameters x.
-        arg_dict = {dim.name: value for dim, value in zip(dimensions, params)}
-        return arg_dict
+        # Return a dict where the keys are the names of the dimensions
+        # and the values are taken from the list of parameters.
+        return {d.name: v for d, v in zip(dimensions, raw_params)}
 
-    def save_trials(self) -> None:
+    def _save_results(self) -> None:
         """
-        Save hyperopt trials to file
+        Save hyperopt results to file
         """
-        if self.trials:
-            logger.info('Saving %d evaluations to \'%s\'', len(self.trials), self.trials_file)
-            dump(self.trials, self.trials_file)
+        num_epochs = len(self.epochs)
+        if num_epochs > self.num_epochs_saved:
+            logger.debug(f"Saving {num_epochs} {plural(num_epochs, 'epoch')}.")
+            dump(self.epochs, self.results_file)
+            self.num_epochs_saved = num_epochs
+            logger.debug(f"{self.num_epochs_saved} {plural(self.num_epochs_saved, 'epoch')} "
+                         f"saved to '{self.results_file}'.")
+            # Store hyperopt filename
+            latest_filename = Path.joinpath(self.results_file.parent, LAST_BT_RESULT_FN)
+            file_dump_json(latest_filename, {'latest_hyperopt': str(self.results_file.name)},
+                           log=False)
 
-    def read_trials(self) -> List:
+    @staticmethod
+    def _read_results(results_file: Path) -> List:
         """
-        Read hyperopt trials file
+        Read hyperopt results from file
         """
-        logger.info('Reading Trials from \'%s\'', self.trials_file)
-        trials = load(self.trials_file)
-        os.remove(self.trials_file)
-        return trials
+        logger.info("Reading epochs from '%s'", results_file)
+        data = load(results_file)
+        return data
 
-    def log_trials_result(self) -> None:
+    def _get_params_details(self, params: Dict) -> Dict:
         """
-        Display Best hyperopt result
+        Return the params for each space
         """
-        results = sorted(self.trials, key=itemgetter('loss'))
-        best_result = results[0]
-        logger.info(
-            'Best result:\n%s\nwith values:\n',
-            best_result['result']
-        )
-        pprint(best_result['params'], indent=4)
-        if 'roi_t1' in best_result['params']:
-            logger.info('ROI table:')
-            pprint(self.custom_hyperopt.generate_roi_table(best_result['params']), indent=4)
+        result: Dict = {}
 
-    def log_results(self, results) -> None:
+        if self.has_space('buy'):
+            result['buy'] = {p.name: params.get(p.name)
+                             for p in self.hyperopt_space('buy')}
+        if self.has_space('sell'):
+            result['sell'] = {p.name: params.get(p.name)
+                              for p in self.hyperopt_space('sell')}
+        if self.has_space('roi'):
+            result['roi'] = self.custom_hyperopt.generate_roi_table(params)
+        if self.has_space('stoploss'):
+            result['stoploss'] = {p.name: params.get(p.name)
+                                  for p in self.hyperopt_space('stoploss')}
+        if self.has_space('trailing'):
+            result['trailing'] = self.custom_hyperopt.generate_trailing_params(params)
+
+        return result
+
+    @staticmethod
+    def print_epoch_details(results, total_epochs: int, print_json: bool,
+                            no_header: bool = False, header_str: str = None) -> None:
+        """
+        Display details of the hyperopt result
+        """
+        params = results.get('params_details', {})
+
+        # Default header string
+        if header_str is None:
+            header_str = "Best result"
+
+        if not no_header:
+            explanation_str = Hyperopt._format_explanation_string(results, total_epochs)
+            print(f"\n{header_str}:\n\n{explanation_str}\n")
+
+        if print_json:
+            result_dict: Dict = {}
+            for s in ['buy', 'sell', 'roi', 'stoploss', 'trailing']:
+                Hyperopt._params_update_for_json(result_dict, params, s)
+            print(rapidjson.dumps(result_dict, default=str, number_mode=rapidjson.NM_NATIVE))
+
+        else:
+            Hyperopt._params_pretty_print(params, 'buy', "Buy hyperspace params:")
+            Hyperopt._params_pretty_print(params, 'sell', "Sell hyperspace params:")
+            Hyperopt._params_pretty_print(params, 'roi', "ROI table:")
+            Hyperopt._params_pretty_print(params, 'stoploss', "Stoploss:")
+            Hyperopt._params_pretty_print(params, 'trailing', "Trailing stop:")
+
+    @staticmethod
+    def _params_update_for_json(result_dict, params, space: str) -> None:
+        if space in params:
+            space_params = Hyperopt._space_params(params, space)
+            if space in ['buy', 'sell']:
+                result_dict.setdefault('params', {}).update(space_params)
+            elif space == 'roi':
+                # TODO: get rid of OrderedDict when support for python 3.6 will be
+                # dropped (dicts keep the order as the language feature)
+
+                # Convert keys in min_roi dict to strings because
+                # rapidjson cannot dump dicts with integer keys...
+                # OrderedDict is used to keep the numeric order of the items
+                # in the dict.
+                result_dict['minimal_roi'] = OrderedDict(
+                    (str(k), v) for k, v in space_params.items()
+                )
+            else:  # 'stoploss', 'trailing'
+                result_dict.update(space_params)
+
+    @staticmethod
+    def _params_pretty_print(params, space: str, header: str) -> None:
+        if space in params:
+            space_params = Hyperopt._space_params(params, space, 5)
+            params_result = f"\n# {header}\n"
+            if space == 'stoploss':
+                params_result += f"stoploss = {space_params.get('stoploss')}"
+            elif space == 'roi':
+                # TODO: get rid of OrderedDict when support for python 3.6 will be
+                # dropped (dicts keep the order as the language feature)
+                minimal_roi_result = rapidjson.dumps(
+                    OrderedDict(
+                        (str(k), v) for k, v in space_params.items()
+                    ),
+                    default=str, indent=4, number_mode=rapidjson.NM_NATIVE)
+                params_result += f"minimal_roi = {minimal_roi_result}"
+            elif space == 'trailing':
+
+                for k, v in space_params.items():
+                    params_result += f'{k} = {v}\n'
+
+            else:
+                params_result += f"{space}_params = {pformat(space_params, indent=4)}"
+                params_result = params_result.replace("}", "\n}").replace("{", "{\n ")
+
+            params_result = params_result.replace("\n", "\n    ")
+            print(params_result)
+
+    @staticmethod
+    def _space_params(params, space: str, r: int = None) -> Dict:
+        d = params[space]
+        # Round floats to `r` digits after the decimal point if requested
+        return round_dict(d, r) if r else d
+
+    @staticmethod
+    def is_best_loss(results, current_best_loss: float) -> bool:
+        return results['loss'] < current_best_loss
+
+    def print_results(self, results) -> None:
         """
         Log results if it is better than any previous evaluation
         """
-        print_all = self.config.get('print_all', False)
-        if print_all or results['loss'] < self.current_best_loss:
-            # Output human-friendly index here (starting from 1)
-            current = results['current_tries'] + 1
-            total = results['total_tries']
-            res = results['result']
-            loss = results['loss']
-            self.current_best_loss = results['loss']
-            log_msg = f'{current:5d}/{total}: {res} Objective: {loss:.5f}'
-            log_msg = f'*{log_msg}' if results['initial_point'] else f' {log_msg}'
-            if print_all:
-                print(log_msg)
-            else:
-                print('\n' + log_msg)
+        is_best = results['is_best']
+
+        if self.print_all or is_best:
+            print(
+                self.get_result_table(
+                    self.config, results, self.total_epochs,
+                    self.print_all, self.print_colorized,
+                    self.hyperopt_table_header
+                )
+            )
+            self.hyperopt_table_header = 2
+
+    @staticmethod
+    def _format_explanation_string(results, total_epochs) -> str:
+        return (("*" if results['is_initial_point'] else " ") +
+                f"{results['current_epoch']:5d}/{total_epochs}: " +
+                f"{results['results_explanation']} " +
+                f"Objective: {results['loss']:.5f}")
+
+    @staticmethod
+    def get_result_table(config: dict, results: list, total_epochs: int, highlight_best: bool,
+                         print_colorized: bool, remove_header: int) -> str:
+        """
+        Log result table
+        """
+        if not results:
+            return ''
+
+        tabulate.PRESERVE_WHITESPACE = True
+
+        trials = json_normalize(results, max_level=1)
+        trials['Best'] = ''
+        if 'results_metrics.winsdrawslosses' not in trials.columns:
+            # Ensure compatibility with older versions of hyperopt results
+            trials['results_metrics.winsdrawslosses'] = 'N/A'
+
+        trials = trials[['Best', 'current_epoch', 'results_metrics.trade_count',
+                         'results_metrics.winsdrawslosses',
+                         'results_metrics.avg_profit', 'results_metrics.total_profit',
+                         'results_metrics.profit', 'results_metrics.duration',
+                         'loss', 'is_initial_point', 'is_best']]
+        trials.columns = ['Best', 'Epoch', 'Trades', ' Win Draw Loss', 'Avg profit',
+                          'Total profit', 'Profit', 'Avg duration', 'Objective',
+                          'is_initial_point', 'is_best']
+        trials['is_profit'] = False
+        trials.loc[trials['is_initial_point'], 'Best'] = '*     '
+        trials.loc[trials['is_best'], 'Best'] = 'Best'
+        trials.loc[trials['is_initial_point'] & trials['is_best'], 'Best'] = '* Best'
+        trials.loc[trials['Total profit'] > 0, 'is_profit'] = True
+        trials['Trades'] = trials['Trades'].astype(str)
+
+        trials['Epoch'] = trials['Epoch'].apply(
+            lambda x: '{}/{}'.format(str(x).rjust(len(str(total_epochs)), ' '), total_epochs)
+        )
+        trials['Avg profit'] = trials['Avg profit'].apply(
+            lambda x: '{:,.2f}%'.format(x).rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ')
+        )
+        trials['Avg duration'] = trials['Avg duration'].apply(
+            lambda x: '{:,.1f} m'.format(x).rjust(7, ' ') if not isna(x) else "--".rjust(7, ' ')
+        )
+        trials['Objective'] = trials['Objective'].apply(
+            lambda x: '{:,.5f}'.format(x).rjust(8, ' ') if x != 100000 else "N/A".rjust(8, ' ')
+        )
+
+        trials['Profit'] = trials.apply(
+            lambda x: '{:,.8f} {} {}'.format(
+                x['Total profit'], config['stake_currency'],
+                '({:,.2f}%)'.format(x['Profit']).rjust(10, ' ')
+            ).rjust(25+len(config['stake_currency']))
+            if x['Total profit'] != 0.0 else '--'.rjust(25+len(config['stake_currency'])),
+            axis=1
+        )
+        trials = trials.drop(columns=['Total profit'])
+
+        if print_colorized:
+            for i in range(len(trials)):
+                if trials.loc[i]['is_profit']:
+                    for j in range(len(trials.loc[i])-3):
+                        trials.iat[i, j] = "{}{}{}".format(Fore.GREEN,
+                                                           str(trials.loc[i][j]), Fore.RESET)
+                if trials.loc[i]['is_best'] and highlight_best:
+                    for j in range(len(trials.loc[i])-3):
+                        trials.iat[i, j] = "{}{}{}".format(Style.BRIGHT,
+                                                           str(trials.loc[i][j]), Style.RESET_ALL)
+
+        trials = trials.drop(columns=['is_initial_point', 'is_best', 'is_profit'])
+        if remove_header > 0:
+            table = tabulate.tabulate(
+                trials.to_dict(orient='list'), tablefmt='orgtbl',
+                headers='keys', stralign="right"
+            )
+
+            table = table.split("\n", remove_header)[remove_header]
+        elif remove_header < 0:
+            table = tabulate.tabulate(
+                trials.to_dict(orient='list'), tablefmt='psql',
+                headers='keys', stralign="right"
+            )
+            table = "\n".join(table.split("\n")[0:remove_header])
         else:
-            print('.', end='')
-            sys.stdout.flush()
+            table = tabulate.tabulate(
+                trials.to_dict(orient='list'), tablefmt='psql',
+                headers='keys', stralign="right"
+            )
+        return table
+
+    @staticmethod
+    def export_csv_file(config: dict, results: list, total_epochs: int, highlight_best: bool,
+                        csv_file: str) -> None:
+        """
+        Log result to csv-file
+        """
+        if not results:
+            return
+
+        # Verification for overwrite
+        if Path(csv_file).is_file():
+            logger.error(f"CSV file already exists: {csv_file}")
+            return
+
+        try:
+            io.open(csv_file, 'w+').close()
+        except IOError:
+            logger.error(f"Failed to create CSV file: {csv_file}")
+            return
+
+        trials = json_normalize(results, max_level=1)
+        trials['Best'] = ''
+        trials['Stake currency'] = config['stake_currency']
+
+        base_metrics = ['Best', 'current_epoch', 'results_metrics.trade_count',
+                        'results_metrics.avg_profit', 'results_metrics.total_profit',
+                        'Stake currency', 'results_metrics.profit', 'results_metrics.duration',
+                        'loss', 'is_initial_point', 'is_best']
+        param_metrics = [("params_dict."+param) for param in results[0]['params_dict'].keys()]
+        trials = trials[base_metrics + param_metrics]
+
+        base_columns = ['Best', 'Epoch', 'Trades', 'Avg profit', 'Total profit', 'Stake currency',
+                        'Profit', 'Avg duration', 'Objective', 'is_initial_point', 'is_best']
+        param_columns = list(results[0]['params_dict'].keys())
+        trials.columns = base_columns + param_columns
+
+        trials['is_profit'] = False
+        trials.loc[trials['is_initial_point'], 'Best'] = '*'
+        trials.loc[trials['is_best'], 'Best'] = 'Best'
+        trials.loc[trials['is_initial_point'] & trials['is_best'], 'Best'] = '* Best'
+        trials.loc[trials['Total profit'] > 0, 'is_profit'] = True
+        trials['Epoch'] = trials['Epoch'].astype(str)
+        trials['Trades'] = trials['Trades'].astype(str)
+
+        trials['Total profit'] = trials['Total profit'].apply(
+            lambda x: '{:,.8f}'.format(x) if x != 0.0 else ""
+        )
+        trials['Profit'] = trials['Profit'].apply(
+            lambda x: '{:,.2f}'.format(x) if not isna(x) else ""
+        )
+        trials['Avg profit'] = trials['Avg profit'].apply(
+            lambda x: '{:,.2f}%'.format(x) if not isna(x) else ""
+        )
+        trials['Avg duration'] = trials['Avg duration'].apply(
+            lambda x: '{:,.1f} m'.format(x) if not isna(x) else ""
+        )
+        trials['Objective'] = trials['Objective'].apply(
+            lambda x: '{:,.5f}'.format(x) if x != 100000 else ""
+        )
+
+        trials = trials.drop(columns=['is_initial_point', 'is_best', 'is_profit'])
+        trials.to_csv(csv_file, index=False, header=True, mode='w', encoding='UTF-8')
+        logger.info(f"CSV file created: {csv_file}")
 
     def has_space(self, space: str) -> bool:
         """
-        Tell if a space value is contained in the configuration
+        Tell if the space value is contained in the configuration
         """
-        if space in self.config['spaces'] or 'all' in self.config['spaces']:
-            return True
-        return False
+        # The 'trailing' space is not included in the 'default' set of spaces
+        if space == 'trailing':
+            return any(s in self.config['spaces'] for s in [space, 'all'])
+        else:
+            return any(s in self.config['spaces'] for s in [space, 'all', 'default'])
 
-    def hyperopt_space(self) -> List[Dimension]:
+    def hyperopt_space(self, space: Optional[str] = None) -> List[Dimension]:
         """
-        Return the space to use during Hyperopt
+        Return the dimensions in the hyperoptimization space.
+        :param space: Defines hyperspace to return dimensions for.
+        If None, then the self.has_space() will be used to return dimensions
+        for all hyperspaces used.
         """
         spaces: List[Dimension] = []
-        if self.has_space('buy'):
+
+        if space == 'buy' or (space is None and self.has_space('buy')):
+            logger.debug("Hyperopt has 'buy' space")
             spaces += self.custom_hyperopt.indicator_space()
-        if self.has_space('sell'):
+
+        if space == 'sell' or (space is None and self.has_space('sell')):
+            logger.debug("Hyperopt has 'sell' space")
             spaces += self.custom_hyperopt.sell_indicator_space()
-            # Make sure experimental is enabled
-            if 'experimental' not in self.config:
-                self.config['experimental'] = {}
-            self.config['experimental']['use_sell_signal'] = True
-        if self.has_space('roi'):
+
+        if space == 'roi' or (space is None and self.has_space('roi')):
+            logger.debug("Hyperopt has 'roi' space")
             spaces += self.custom_hyperopt.roi_space()
-        if self.has_space('stoploss'):
+
+        if space == 'stoploss' or (space is None and self.has_space('stoploss')):
+            logger.debug("Hyperopt has 'stoploss' space")
             spaces += self.custom_hyperopt.stoploss_space()
+
+        if space == 'trailing' or (space is None and self.has_space('trailing')):
+            logger.debug("Hyperopt has 'trailing' space")
+            spaces += self.custom_hyperopt.trailing_space()
+
         return spaces
 
-    def generate_optimizer(self, _params: Dict) -> Dict:
+    def generate_optimizer(self, raw_params: List[Any], iteration=None) -> Dict:
         """
         Used Optimize function. Called once per epoch to optimize whatever is configured.
         Keep this function as optimized as possible!
         """
-        params = self.get_args(_params)
+        params_dict = self._get_params_dict(raw_params)
+        params_details = self._get_params_details(params_dict)
+
         if self.has_space('roi'):
-            self.strategy.minimal_roi = self.custom_hyperopt.generate_roi_table(params)
+            self.backtesting.strategy.minimal_roi = (  # type: ignore
+                self.custom_hyperopt.generate_roi_table(params_dict))
 
         if self.has_space('buy'):
-            self.advise_buy = self.custom_hyperopt.buy_strategy_generator(params)
+            self.backtesting.strategy.advise_buy = (  # type: ignore
+                self.custom_hyperopt.buy_strategy_generator(params_dict))
 
         if self.has_space('sell'):
-            self.advise_sell = self.custom_hyperopt.sell_strategy_generator(params)
+            self.backtesting.strategy.advise_sell = (  # type: ignore
+                self.custom_hyperopt.sell_strategy_generator(params_dict))
 
         if self.has_space('stoploss'):
-            self.strategy.stoploss = params['stoploss']
+            self.backtesting.strategy.stoploss = params_dict['stoploss']
 
-        processed = load(TICKERDATA_PICKLE)
+        if self.has_space('trailing'):
+            d = self.custom_hyperopt.generate_trailing_params(params_dict)
+            self.backtesting.strategy.trailing_stop = d['trailing_stop']
+            self.backtesting.strategy.trailing_stop_positive = d['trailing_stop_positive']
+            self.backtesting.strategy.trailing_stop_positive_offset = \
+                d['trailing_stop_positive_offset']
+            self.backtesting.strategy.trailing_only_offset_is_reached = \
+                d['trailing_only_offset_is_reached']
 
-        min_date, max_date = get_timeframe(processed)
+        processed = load(self.data_pickle_file)
 
-        results = self.backtest(
-            {
-                'stake_amount': self.config['stake_amount'],
-                'processed': processed,
-                'max_open_trades': self.max_open_trades,
-                'position_stacking': self.position_stacking,
-                'start_date': min_date,
-                'end_date': max_date,
-            }
+        min_date, max_date = get_timerange(processed)
+
+        backtesting_results = self.backtesting.backtest(
+            processed=processed,
+            stake_amount=self.config['stake_amount'],
+            start_date=min_date.datetime,
+            end_date=max_date.datetime,
+            max_open_trades=self.max_open_trades,
+            position_stacking=self.position_stacking,
         )
-        result_explanation = self.format_results(results)
+        return self._get_results_dict(backtesting_results, min_date, max_date,
+                                      params_dict, params_details)
 
-        trade_count = len(results.index)
+    def _get_results_dict(self, backtesting_results, min_date, max_date,
+                          params_dict, params_details):
+        results_metrics = self._calculate_results_metrics(backtesting_results)
+        results_explanation = self._format_results_explanation_string(results_metrics)
+
+        trade_count = results_metrics['trade_count']
+        total_profit = results_metrics['total_profit']
 
         # If this evaluation contains too short amount of trades to be
         # interesting -- consider it as 'bad' (assigned max. loss value)
         # in order to cast this hyperspace point away from optimization
         # path. We do not want to optimize 'hodl' strategies.
-        if trade_count < self.config['hyperopt_min_trades']:
-            return {
-                'loss': MAX_LOSS,
-                'params': params,
-                'result': result_explanation,
-            }
-
-        loss = self.calculate_loss(results=results, trade_count=trade_count,
-                                   min_date=min_date.datetime, max_date=max_date.datetime)
-
+        loss: float = MAX_LOSS
+        if trade_count >= self.config['hyperopt_min_trades']:
+            loss = self.calculate_loss(results=backtesting_results, trade_count=trade_count,
+                                       min_date=min_date.datetime, max_date=max_date.datetime)
         return {
             'loss': loss,
-            'params': params,
-            'result': result_explanation,
+            'params_dict': params_dict,
+            'params_details': params_details,
+            'results_metrics': results_metrics,
+            'results_explanation': results_explanation,
+            'total_profit': total_profit,
         }
 
-    def format_results(self, results: DataFrame) -> str:
+    def _calculate_results_metrics(self, backtesting_results: DataFrame) -> Dict:
+        wins = len(backtesting_results[backtesting_results.profit_percent > 0])
+        draws = len(backtesting_results[backtesting_results.profit_percent == 0])
+        losses = len(backtesting_results[backtesting_results.profit_percent < 0])
+        return {
+            'trade_count': len(backtesting_results.index),
+            'wins': wins,
+            'draws': draws,
+            'losses': losses,
+            'winsdrawslosses': f"{wins:>4} {draws:>4} {losses:>4}",
+            'avg_profit': backtesting_results.profit_percent.mean() * 100.0,
+            'median_profit': backtesting_results.profit_percent.median() * 100.0,
+            'total_profit': backtesting_results.profit_abs.sum(),
+            'profit': backtesting_results.profit_percent.sum() * 100.0,
+            'duration': backtesting_results.trade_duration.mean(),
+        }
+
+    def _format_results_explanation_string(self, results_metrics: Dict) -> str:
         """
-        Return the format result in a string
+        Return the formatted results explanation in a string
         """
-        trades = len(results.index)
-        avg_profit = results.profit_percent.mean() * 100.0
-        total_profit = results.profit_abs.sum()
         stake_cur = self.config['stake_currency']
-        profit = results.profit_percent.sum() * 100.0
-        duration = results.trade_duration.mean()
+        return (f"{results_metrics['trade_count']:6d} trades. "
+                f"{results_metrics['wins']}/{results_metrics['draws']}"
+                f"/{results_metrics['losses']} Wins/Draws/Losses. "
+                f"Avg profit {results_metrics['avg_profit']: 6.2f}%. "
+                f"Median profit {results_metrics['median_profit']: 6.2f}%. "
+                f"Total profit {results_metrics['total_profit']: 11.8f} {stake_cur} "
+                f"({results_metrics['profit']: 7.2f}\N{GREEK CAPITAL LETTER SIGMA}%). "
+                f"Avg duration {results_metrics['duration']:5.1f} min."
+                ).encode(locale.getpreferredencoding(), 'replace').decode('utf-8')
 
-        return (f'{trades:6d} trades. Avg profit {avg_profit: 5.2f}%. '
-                f'Total profit {total_profit: 11.8f} {stake_cur} '
-                f'({profit: 7.2f}Σ%). Avg duration {duration:5.1f} mins.')
-
-    def get_optimizer(self, cpu_count) -> Optimizer:
+    def get_optimizer(self, dimensions: List[Dimension], cpu_count) -> Optimizer:
         return Optimizer(
-            self.hyperopt_space(),
+            dimensions,
             base_estimator="ET",
             acq_optimizer="auto",
             n_initial_points=INITIAL_POINTS,
             acq_optimizer_kwargs={'n_jobs': cpu_count},
-            random_state=self.config.get('hyperopt_random_state', None)
+            random_state=self.random_state,
+            model_queue_size=SKOPT_MODEL_QUEUE_SIZE,
         )
 
-    def run_optimizer_parallel(self, parallel, asked) -> List:
+    def run_optimizer_parallel(self, parallel, asked, i) -> List:
         return parallel(delayed(
-                        wrap_non_picklable_objects(self.generate_optimizer))(v) for v in asked)
+                        wrap_non_picklable_objects(self.generate_optimizer))(v, i) for v in asked)
 
-    def load_previous_results(self):
-        """ read trials file if we have one """
-        if os.path.exists(self.trials_file) and os.path.getsize(self.trials_file) > 0:
-            self.trials = self.read_trials()
-            logger.info(
-                'Loaded %d previous evaluations from disk.',
-                len(self.trials)
-            )
+    @staticmethod
+    def load_previous_results(results_file: Path) -> List:
+        """
+        Load data for epochs from the file if we have one
+        """
+        epochs: List = []
+        if results_file.is_file() and results_file.stat().st_size > 0:
+            epochs = Hyperopt._read_results(results_file)
+            # Detection of some old format, without 'is_best' field saved
+            if epochs[0].get('is_best') is None:
+                raise OperationalException(
+                    "The file with Hyperopt results is incompatible with this version "
+                    "of Freqtrade and cannot be loaded.")
+            logger.info(f"Loaded {len(epochs)} previous evaluations from disk.")
+        return epochs
+
+    def _set_random_state(self, random_state: Optional[int]) -> int:
+        return random_state or random.randint(1, 2**16 - 1)
 
     def start(self) -> None:
-        timerange = Arguments.parse_timerange(None if self.config.get(
-            'timerange') is None else str(self.config.get('timerange')))
-        data = load_data(
-            datadir=Path(self.config['datadir']) if self.config.get('datadir') else None,
-            pairs=self.config['exchange']['pair_whitelist'],
-            ticker_interval=self.ticker_interval,
-            refresh_pairs=self.config.get('refresh_pairs', False),
-            exchange=self.exchange,
-            timerange=timerange
-        )
+        self.random_state = self._set_random_state(self.config.get('hyperopt_random_state', None))
+        logger.info(f"Using optimizer random state: {self.random_state}")
+        self.hyperopt_table_header = -1
+        data, timerange = self.backtesting.load_bt_data()
 
-        if not data:
-            logger.critical("No data found. Terminating.")
-            return
+        preprocessed = self.backtesting.strategy.ohlcvdata_to_dataframe(data)
 
-        min_date, max_date = get_timeframe(data)
+        # Trim startup period from analyzed dataframe
+        for pair, df in preprocessed.items():
+            preprocessed[pair] = trim_dataframe(df, timerange)
+        min_date, max_date = get_timerange(data)
 
-        logger.info(
-            'Hyperopting with data from %s up to %s (%s days)..',
-            min_date.isoformat(),
-            max_date.isoformat(),
-            (max_date - min_date).days
-        )
+        logger.info(f'Hyperopting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
+                    f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
+                    f'({(max_date - min_date).days} days)..')
 
-        self.strategy.advise_indicators = \
-            self.custom_hyperopt.populate_indicators  # type: ignore
-
-        preprocessed = self.strategy.tickerdata_to_dataframe(data)
-
-        dump(preprocessed, TICKERDATA_PICKLE)
+        dump(preprocessed, self.data_pickle_file)
 
         # We don't need exchange instance anymore while running hyperopt
-        self.exchange = None  # type: ignore
-
-        self.load_previous_results()
+        self.backtesting.exchange = None  # type: ignore
+        self.backtesting.pairlists = None  # type: ignore
+        self.backtesting.strategy.dp = None  # type: ignore
+        IStrategy.dp = None  # type: ignore
 
         cpus = cpu_count()
-        logger.info(f'Found {cpus} CPU cores. Let\'s make them scream!')
+        logger.info(f"Found {cpus} CPU cores. Let's make them scream!")
         config_jobs = self.config.get('hyperopt_jobs', -1)
         logger.info(f'Number of parallel jobs set as: {config_jobs}')
 
-        opt = self.get_optimizer(config_jobs)
+        self.dimensions: List[Dimension] = self.hyperopt_space()
+        self.opt = self.get_optimizer(self.dimensions, config_jobs)
+
+        if self.print_colorized:
+            colorama_init(autoreset=True)
+
         try:
             with Parallel(n_jobs=config_jobs) as parallel:
                 jobs = parallel._effective_n_jobs()
                 logger.info(f'Effective number of parallel workers used: {jobs}')
-                EVALS = max(self.total_tries // jobs, 1)
-                for i in range(EVALS):
-                    asked = opt.ask(n_points=jobs)
-                    f_val = self.run_optimizer_parallel(parallel, asked)
-                    opt.tell(asked, [i['loss'] for i in f_val])
 
-                    self.trials += f_val
-                    for j in range(jobs):
-                        current = i * jobs + j
-                        self.log_results({
-                            'loss': f_val[j]['loss'],
-                            'current_tries': current,
-                            'initial_point': current < INITIAL_POINTS,
-                            'total_tries': self.total_tries,
-                            'result': f_val[j]['result'],
-                        })
-                        logger.debug(f"Optimizer params: {f_val[j]['params']}")
-                    for j in range(jobs):
-                        logger.debug(f"Optimizer state: Xi: {opt.Xi[-j-1]}, yi: {opt.yi[-j-1]}")
+                # Define progressbar
+                if self.print_colorized:
+                    widgets = [
+                        ' [Epoch ', progressbar.Counter(), ' of ', str(self.total_epochs),
+                        ' (', progressbar.Percentage(), ')] ',
+                        progressbar.Bar(marker=progressbar.AnimatedMarker(
+                            fill='\N{FULL BLOCK}',
+                            fill_wrap=Fore.GREEN + '{}' + Fore.RESET,
+                            marker_wrap=Style.BRIGHT + '{}' + Style.RESET_ALL,
+                        )),
+                        ' [', progressbar.ETA(), ', ', progressbar.Timer(), ']',
+                    ]
+                else:
+                    widgets = [
+                        ' [Epoch ', progressbar.Counter(), ' of ', str(self.total_epochs),
+                        ' (', progressbar.Percentage(), ')] ',
+                        progressbar.Bar(marker=progressbar.AnimatedMarker(
+                            fill='\N{FULL BLOCK}',
+                        )),
+                        ' [', progressbar.ETA(), ', ', progressbar.Timer(), ']',
+                    ]
+                with progressbar.ProgressBar(
+                         max_value=self.total_epochs, redirect_stdout=False, redirect_stderr=False,
+                         widgets=widgets
+                     ) as pbar:
+                    EVALS = ceil(self.total_epochs / jobs)
+                    for i in range(EVALS):
+                        # Correct the number of epochs to be processed for the last
+                        # iteration (should not exceed self.total_epochs in total)
+                        n_rest = (i + 1) * jobs - self.total_epochs
+                        current_jobs = jobs - n_rest if n_rest > 0 else jobs
+
+                        asked = self.opt.ask(n_points=current_jobs)
+                        f_val = self.run_optimizer_parallel(parallel, asked, i)
+                        self.opt.tell(asked, [v['loss'] for v in f_val])
+
+                        # Calculate progressbar outputs
+                        for j, val in enumerate(f_val):
+                            # Use human-friendly indexes here (starting from 1)
+                            current = i * jobs + j + 1
+                            val['current_epoch'] = current
+                            val['is_initial_point'] = current <= INITIAL_POINTS
+
+                            logger.debug(f"Optimizer epoch evaluated: {val}")
+
+                            is_best = self.is_best_loss(val, self.current_best_loss)
+                            # This value is assigned here and not in the optimization method
+                            # to keep proper order in the list of results. That's because
+                            # evaluations can take different time. Here they are aligned in the
+                            # order they will be shown to the user.
+                            val['is_best'] = is_best
+                            self.print_results(val)
+
+                            if is_best:
+                                self.current_best_loss = val['loss']
+                            self.epochs.append(val)
+
+                            # Save results after each best epoch and every 100 epochs
+                            if is_best or current % 100 == 0:
+                                self._save_results()
+
+                            pbar.update(current)
+
         except KeyboardInterrupt:
             print('User interrupted..')
 
-        self.save_trials()
-        self.log_trials_result()
+        self._save_results()
+        logger.info(f"{self.num_epochs_saved} {plural(self.num_epochs_saved, 'epoch')} "
+                    f"saved to '{self.results_file}'.")
+
+        if self.epochs:
+            sorted_epochs = sorted(self.epochs, key=itemgetter('loss'))
+            best_epoch = sorted_epochs[0]
+            self.print_epoch_details(best_epoch, self.total_epochs, self.print_json)
+        else:
+            # This is printed when Ctrl+C is pressed quickly, before first epochs have
+            # a chance to be evaluated.
+            print("No epochs evaluated yet, no best result.")
diff --git a/freqtrade/optimize/hyperopt_interface.py b/freqtrade/optimize/hyperopt_interface.py
index 08823ece0..b8c44ed59 100644
--- a/freqtrade/optimize/hyperopt_interface.py
+++ b/freqtrade/optimize/hyperopt_interface.py
@@ -1,81 +1,230 @@
 """
 IHyperOpt interface
-This module defines the interface to apply for hyperopts
+This module defines the interface to apply for hyperopt
 """
+import logging
+import math
+from abc import ABC
+from typing import Any, Callable, Dict, List
 
-from abc import ABC, abstractmethod
-from typing import Dict, Any, Callable, List
+from skopt.space import Categorical, Dimension, Integer, Real
 
-from pandas import DataFrame
-from skopt.space import Dimension
+from freqtrade.exceptions import OperationalException
+from freqtrade.exchange import timeframe_to_minutes
+from freqtrade.misc import round_dict
+
+
+logger = logging.getLogger(__name__)
+
+
+def _format_exception_message(method: str, space: str) -> str:
+    return (f"The '{space}' space is included into the hyperoptimization "
+            f"but {method}() method is not found in your "
+            f"custom Hyperopt class. You should either implement this "
+            f"method or remove the '{space}' space from hyperoptimization.")
 
 
 class IHyperOpt(ABC):
     """
-    Interface for freqtrade hyperopts
-    Defines the mandatory structure must follow any custom strategies
+    Interface for freqtrade hyperopt
+    Defines the mandatory structure must follow any custom hyperopt
 
-    Attributes you can use:
-        minimal_roi -> Dict: Minimal ROI designed for the strategy
-        stoploss -> float: optimal stoploss designed for the strategy
+    Class attributes you can use:
         ticker_interval -> int: value of the ticker interval to use for the strategy
     """
-    ticker_interval: str
+    ticker_interval: str  # DEPRECATED
+    timeframe: str
+
+    def __init__(self, config: dict) -> None:
+        self.config = config
+
+        # Assign ticker_interval to be used in hyperopt
+        IHyperOpt.ticker_interval = str(config['timeframe'])  # DEPRECATED
+        IHyperOpt.timeframe = str(config['timeframe'])
 
     @staticmethod
-    @abstractmethod
-    def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
-        """
-        Populate indicators that will be used in the Buy and Sell strategy
-        :param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
-        :return: a Dataframe with all mandatory indicators for the strategies
-        """
-
-    @staticmethod
-    @abstractmethod
     def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
         """
-        Create a buy strategy generator
+        Create a buy strategy generator.
         """
+        raise OperationalException(_format_exception_message('buy_strategy_generator', 'buy'))
 
     @staticmethod
-    @abstractmethod
     def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
         """
-        Create a sell strategy generator
+        Create a sell strategy generator.
         """
+        raise OperationalException(_format_exception_message('sell_strategy_generator', 'sell'))
 
     @staticmethod
-    @abstractmethod
     def indicator_space() -> List[Dimension]:
         """
-        Create an indicator space
+        Create an indicator space.
         """
+        raise OperationalException(_format_exception_message('indicator_space', 'buy'))
 
     @staticmethod
-    @abstractmethod
     def sell_indicator_space() -> List[Dimension]:
         """
-        Create a sell indicator space
+        Create a sell indicator space.
         """
+        raise OperationalException(_format_exception_message('sell_indicator_space', 'sell'))
 
     @staticmethod
-    @abstractmethod
     def generate_roi_table(params: Dict) -> Dict[int, float]:
         """
-        Create an roi table
+        Create a ROI table.
+
+        Generates the ROI table that will be used by Hyperopt.
+        You may override it in your custom Hyperopt class.
         """
+        roi_table = {}
+        roi_table[0] = params['roi_p1'] + params['roi_p2'] + params['roi_p3']
+        roi_table[params['roi_t3']] = params['roi_p1'] + params['roi_p2']
+        roi_table[params['roi_t3'] + params['roi_t2']] = params['roi_p1']
+        roi_table[params['roi_t3'] + params['roi_t2'] + params['roi_t1']] = 0
+
+        return roi_table
 
     @staticmethod
-    @abstractmethod
-    def stoploss_space() -> List[Dimension]:
-        """
-        Create a stoploss space
-        """
-
-    @staticmethod
-    @abstractmethod
     def roi_space() -> List[Dimension]:
         """
-        Create a roi space
+        Create a ROI space.
+
+        Defines values to search for each ROI steps.
+
+        This method implements adaptive roi hyperspace with varied
+        ranges for parameters which automatically adapts to the
+        ticker interval used.
+
+        It's used by Freqtrade by default, if no custom roi_space method is defined.
         """
+
+        # Default scaling coefficients for the roi hyperspace. Can be changed
+        # to adjust resulting ranges of the ROI tables.
+        # Increase if you need wider ranges in the roi hyperspace, decrease if shorter
+        # ranges are needed.
+        roi_t_alpha = 1.0
+        roi_p_alpha = 1.0
+
+        timeframe_min = timeframe_to_minutes(IHyperOpt.ticker_interval)
+
+        # We define here limits for the ROI space parameters automagically adapted to the
+        # timeframe used by the bot:
+        #
+        # * 'roi_t' (limits for the time intervals in the ROI tables) components
+        #   are scaled linearly.
+        # * 'roi_p' (limits for the ROI value steps) components are scaled logarithmically.
+        #
+        # The scaling is designed so that it maps exactly to the legacy Freqtrade roi_space()
+        # method for the 5m ticker interval.
+        roi_t_scale = timeframe_min / 5
+        roi_p_scale = math.log1p(timeframe_min) / math.log1p(5)
+        roi_limits = {
+            'roi_t1_min': int(10 * roi_t_scale * roi_t_alpha),
+            'roi_t1_max': int(120 * roi_t_scale * roi_t_alpha),
+            'roi_t2_min': int(10 * roi_t_scale * roi_t_alpha),
+            'roi_t2_max': int(60 * roi_t_scale * roi_t_alpha),
+            'roi_t3_min': int(10 * roi_t_scale * roi_t_alpha),
+            'roi_t3_max': int(40 * roi_t_scale * roi_t_alpha),
+            'roi_p1_min': 0.01 * roi_p_scale * roi_p_alpha,
+            'roi_p1_max': 0.04 * roi_p_scale * roi_p_alpha,
+            'roi_p2_min': 0.01 * roi_p_scale * roi_p_alpha,
+            'roi_p2_max': 0.07 * roi_p_scale * roi_p_alpha,
+            'roi_p3_min': 0.01 * roi_p_scale * roi_p_alpha,
+            'roi_p3_max': 0.20 * roi_p_scale * roi_p_alpha,
+        }
+        logger.debug(f"Using roi space limits: {roi_limits}")
+        p = {
+            'roi_t1': roi_limits['roi_t1_min'],
+            'roi_t2': roi_limits['roi_t2_min'],
+            'roi_t3': roi_limits['roi_t3_min'],
+            'roi_p1': roi_limits['roi_p1_min'],
+            'roi_p2': roi_limits['roi_p2_min'],
+            'roi_p3': roi_limits['roi_p3_min'],
+        }
+        logger.info(f"Min roi table: {round_dict(IHyperOpt.generate_roi_table(p), 5)}")
+        p = {
+            'roi_t1': roi_limits['roi_t1_max'],
+            'roi_t2': roi_limits['roi_t2_max'],
+            'roi_t3': roi_limits['roi_t3_max'],
+            'roi_p1': roi_limits['roi_p1_max'],
+            'roi_p2': roi_limits['roi_p2_max'],
+            'roi_p3': roi_limits['roi_p3_max'],
+        }
+        logger.info(f"Max roi table: {round_dict(IHyperOpt.generate_roi_table(p), 5)}")
+
+        return [
+            Integer(roi_limits['roi_t1_min'], roi_limits['roi_t1_max'], name='roi_t1'),
+            Integer(roi_limits['roi_t2_min'], roi_limits['roi_t2_max'], name='roi_t2'),
+            Integer(roi_limits['roi_t3_min'], roi_limits['roi_t3_max'], name='roi_t3'),
+            Real(roi_limits['roi_p1_min'], roi_limits['roi_p1_max'], name='roi_p1'),
+            Real(roi_limits['roi_p2_min'], roi_limits['roi_p2_max'], name='roi_p2'),
+            Real(roi_limits['roi_p3_min'], roi_limits['roi_p3_max'], name='roi_p3'),
+        ]
+
+    @staticmethod
+    def stoploss_space() -> List[Dimension]:
+        """
+        Create a stoploss space.
+
+        Defines range of stoploss values to search.
+        You may override it in your custom Hyperopt class.
+        """
+        return [
+            Real(-0.35, -0.02, name='stoploss'),
+        ]
+
+    @staticmethod
+    def generate_trailing_params(params: Dict) -> Dict:
+        """
+        Create dict with trailing stop parameters.
+        """
+        return {
+            'trailing_stop': params['trailing_stop'],
+            'trailing_stop_positive': params['trailing_stop_positive'],
+            'trailing_stop_positive_offset': (params['trailing_stop_positive'] +
+                                              params['trailing_stop_positive_offset_p1']),
+            'trailing_only_offset_is_reached': params['trailing_only_offset_is_reached'],
+        }
+
+    @staticmethod
+    def trailing_space() -> List[Dimension]:
+        """
+        Create a trailing stoploss space.
+
+        You may override it in your custom Hyperopt class.
+        """
+        return [
+            # It was decided to always set trailing_stop is to True if the 'trailing' hyperspace
+            # is used. Otherwise hyperopt will vary other parameters that won't have effect if
+            # trailing_stop is set False.
+            # This parameter is included into the hyperspace dimensions rather than assigning
+            # it explicitly in the code in order to have it printed in the results along with
+            # other 'trailing' hyperspace parameters.
+            Categorical([True], name='trailing_stop'),
+
+            Real(0.01, 0.35, name='trailing_stop_positive'),
+
+            # 'trailing_stop_positive_offset' should be greater than 'trailing_stop_positive',
+            # so this intermediate parameter is used as the value of the difference between
+            # them. The value of the 'trailing_stop_positive_offset' is constructed in the
+            # generate_trailing_params() method.
+            # This is similar to the hyperspace dimensions used for constructing the ROI tables.
+            Real(0.001, 0.1, name='trailing_stop_positive_offset_p1'),
+
+            Categorical([True, False], name='trailing_only_offset_is_reached'),
+        ]
+
+    # This is needed for proper unpickling the class attribute ticker_interval
+    # which is set to the actual value by the resolver.
+    # Why do I still need such shamanic mantras in modern python?
+    def __getstate__(self):
+        state = self.__dict__.copy()
+        state['timeframe'] = self.timeframe
+        return state
+
+    def __setstate__(self, state):
+        self.__dict__.update(state)
+        IHyperOpt.ticker_interval = state['timeframe']
+        IHyperOpt.timeframe = state['timeframe']
diff --git a/freqtrade/optimize/hyperopt_loss_interface.py b/freqtrade/optimize/hyperopt_loss_interface.py
index b11b6e661..48407a8a8 100644
--- a/freqtrade/optimize/hyperopt_loss_interface.py
+++ b/freqtrade/optimize/hyperopt_loss_interface.py
@@ -1,6 +1,6 @@
 """
 IHyperOptLoss interface
-This module defines the interface for the loss-function for hyperopts
+This module defines the interface for the loss-function for hyperopt
 """
 
 from abc import ABC, abstractmethod
@@ -11,10 +11,10 @@ from pandas import DataFrame
 
 class IHyperOptLoss(ABC):
     """
-    Interface for freqtrade hyperopts Loss functions.
+    Interface for freqtrade hyperopt Loss functions.
     Defines the custom loss function (`hyperopt_loss_function()` which is evaluated every epoch.)
     """
-    ticker_interval: str
+    timeframe: str
 
     @staticmethod
     @abstractmethod
diff --git a/freqtrade/optimize/hyperopt_loss_onlyprofit.py b/freqtrade/optimize/hyperopt_loss_onlyprofit.py
new file mode 100644
index 000000000..43176dbad
--- /dev/null
+++ b/freqtrade/optimize/hyperopt_loss_onlyprofit.py
@@ -0,0 +1,38 @@
+"""
+OnlyProfitHyperOptLoss
+
+This module defines the alternative HyperOptLoss class which can be used for
+Hyperoptimization.
+"""
+from pandas import DataFrame
+
+from freqtrade.optimize.hyperopt import IHyperOptLoss
+
+
+# This is assumed to be expected avg profit * expected trade count.
+# For example, for 0.35% avg per trade (or 0.0035 as ratio) and 1100 trades,
+# expected max profit = 3.85
+#
+# Note, this is ratio. 3.85 stated above means 385Σ%, 3.0 means 300Σ%.
+#
+# In this implementation it's only used in calculation of the resulting value
+# of the objective function as a normalization coefficient and does not
+# represent any limit for profits as in the Freqtrade legacy default loss function.
+EXPECTED_MAX_PROFIT = 3.0
+
+
+class OnlyProfitHyperOptLoss(IHyperOptLoss):
+    """
+    Defines the loss function for hyperopt.
+
+    This implementation takes only profit into account.
+    """
+
+    @staticmethod
+    def hyperopt_loss_function(results: DataFrame, trade_count: int,
+                               *args, **kwargs) -> float:
+        """
+        Objective function, returns smaller number for better results.
+        """
+        total_profit = results['profit_percent'].sum()
+        return 1 - total_profit / EXPECTED_MAX_PROFIT
diff --git a/freqtrade/optimize/hyperopt_loss_sharpe.py b/freqtrade/optimize/hyperopt_loss_sharpe.py
index be1a3d4b4..232fb33b6 100644
--- a/freqtrade/optimize/hyperopt_loss_sharpe.py
+++ b/freqtrade/optimize/hyperopt_loss_sharpe.py
@@ -1,20 +1,22 @@
 """
-IHyperOptLoss interface
-This module defines the interface for the loss-function for hyperopts
-"""
+SharpeHyperOptLoss
 
+This module defines the alternative HyperOptLoss class which can be used for
+Hyperoptimization.
+"""
 from datetime import datetime
 
-from pandas import DataFrame
 import numpy as np
+from pandas import DataFrame
 
 from freqtrade.optimize.hyperopt import IHyperOptLoss
 
 
 class SharpeHyperOptLoss(IHyperOptLoss):
     """
-    Defines the a loss function for hyperopt.
-    This implementation uses the sharpe ratio calculation.
+    Defines the loss function for hyperopt.
+
+    This implementation uses the Sharpe Ratio calculation.
     """
 
     @staticmethod
@@ -22,21 +24,23 @@ class SharpeHyperOptLoss(IHyperOptLoss):
                                min_date: datetime, max_date: datetime,
                                *args, **kwargs) -> float:
         """
-        Objective function, returns smaller number for more optimal results
-        Using sharpe ratio calculation
+        Objective function, returns smaller number for more optimal results.
+
+        Uses Sharpe Ratio calculation.
         """
-        total_profit = results.profit_percent
+        total_profit = results["profit_percent"]
         days_period = (max_date - min_date).days
 
         # adding slippage of 0.1% per trade
         total_profit = total_profit - 0.0005
-        expected_yearly_return = total_profit.sum() / days_period
+        expected_returns_mean = total_profit.sum() / days_period
+        up_stdev = np.std(total_profit)
 
-        if (np.std(total_profit) != 0.):
-            sharp_ratio = expected_yearly_return / np.std(total_profit) * np.sqrt(365)
+        if up_stdev != 0:
+            sharp_ratio = expected_returns_mean / up_stdev * np.sqrt(365)
         else:
             # Define high (negative) sharpe ratio to be clear that this is NOT optimal.
-            sharp_ratio = 20.
+            sharp_ratio = -20.
 
-        # print(expected_yearly_return, np.std(total_profit), sharp_ratio)
+        # print(expected_returns_mean, up_stdev, sharp_ratio)
         return -sharp_ratio
diff --git a/freqtrade/optimize/hyperopt_loss_sharpe_daily.py b/freqtrade/optimize/hyperopt_loss_sharpe_daily.py
new file mode 100644
index 000000000..bcba73a7f
--- /dev/null
+++ b/freqtrade/optimize/hyperopt_loss_sharpe_daily.py
@@ -0,0 +1,62 @@
+"""
+SharpeHyperOptLossDaily
+
+This module defines the alternative HyperOptLoss class which can be used for
+Hyperoptimization.
+"""
+import math
+from datetime import datetime
+
+from pandas import DataFrame, date_range
+
+from freqtrade.optimize.hyperopt import IHyperOptLoss
+
+
+class SharpeHyperOptLossDaily(IHyperOptLoss):
+    """
+    Defines the loss function for hyperopt.
+
+    This implementation uses the Sharpe Ratio calculation.
+    """
+
+    @staticmethod
+    def hyperopt_loss_function(results: DataFrame, trade_count: int,
+                               min_date: datetime, max_date: datetime,
+                               *args, **kwargs) -> float:
+        """
+        Objective function, returns smaller number for more optimal results.
+
+        Uses Sharpe Ratio calculation.
+        """
+        resample_freq = '1D'
+        slippage_per_trade_ratio = 0.0005
+        days_in_year = 365
+        annual_risk_free_rate = 0.0
+        risk_free_rate = annual_risk_free_rate / days_in_year
+
+        # apply slippage per trade to profit_percent
+        results.loc[:, 'profit_percent_after_slippage'] = \
+            results['profit_percent'] - slippage_per_trade_ratio
+
+        # create the index within the min_date and end max_date
+        t_index = date_range(start=min_date, end=max_date, freq=resample_freq,
+                             normalize=True)
+
+        sum_daily = (
+            results.resample(resample_freq, on='close_date').agg(
+                {"profit_percent_after_slippage": sum}).reindex(t_index).fillna(0)
+        )
+
+        total_profit = sum_daily["profit_percent_after_slippage"] - risk_free_rate
+        expected_returns_mean = total_profit.mean()
+        up_stdev = total_profit.std()
+
+        if up_stdev != 0:
+            sharp_ratio = expected_returns_mean / up_stdev * math.sqrt(days_in_year)
+        else:
+            # Define high (negative) sharpe ratio to be clear that this is NOT optimal.
+            sharp_ratio = -20.
+
+        # print(t_index, sum_daily, total_profit)
+        # print(risk_free_rate, expected_returns_mean, up_stdev, sharp_ratio)
+        return -sharp_ratio
diff --git a/freqtrade/optimize/hyperopt_loss_sortino.py b/freqtrade/optimize/hyperopt_loss_sortino.py
new file mode 100644
index 000000000..c0ff0773a
--- /dev/null
+++ b/freqtrade/optimize/hyperopt_loss_sortino.py
@@ -0,0 +1,49 @@
+"""
+SortinoHyperOptLoss
+
+This module defines the alternative HyperOptLoss class which can be used for
+Hyperoptimization.
+"""
+from datetime import datetime
+
+import numpy as np
+from pandas import DataFrame
+
+from freqtrade.optimize.hyperopt import IHyperOptLoss
+
+
+class SortinoHyperOptLoss(IHyperOptLoss):
+    """
+    Defines the loss function for hyperopt.
+
+    This implementation uses the Sortino Ratio calculation.
+    """
+
+    @staticmethod
+    def hyperopt_loss_function(results: DataFrame, trade_count: int,
+                               min_date: datetime, max_date: datetime,
+                               *args, **kwargs) -> float:
+        """
+        Objective function, returns smaller number for more optimal results.
+
+        Uses Sortino Ratio calculation.
+        """
+        total_profit = results["profit_percent"]
+        days_period = (max_date - min_date).days
+
+        # adding slippage of 0.1% per trade
+        total_profit = total_profit - 0.0005
+        expected_returns_mean = total_profit.sum() / days_period
+
+        results['downside_returns'] = 0
+        results.loc[total_profit < 0, 'downside_returns'] = results['profit_percent']
+        down_stdev = np.std(results['downside_returns'])
+
+        if down_stdev != 0:
+            sortino_ratio = expected_returns_mean / down_stdev * np.sqrt(365)
+        else:
+            # Define high (negative) sortino ratio to be clear that this is NOT optimal.
+            sortino_ratio = -20.
+
+        # print(expected_returns_mean, down_stdev, sortino_ratio)
+        return -sortino_ratio
diff --git a/freqtrade/optimize/hyperopt_loss_sortino_daily.py b/freqtrade/optimize/hyperopt_loss_sortino_daily.py
new file mode 100644
index 000000000..3b099a253
--- /dev/null
+++ b/freqtrade/optimize/hyperopt_loss_sortino_daily.py
@@ -0,0 +1,70 @@
+"""
+SortinoHyperOptLossDaily
+
+This module defines the alternative HyperOptLoss class which can be used for
+Hyperoptimization.
+"""
+import math
+from datetime import datetime
+
+from pandas import DataFrame, date_range
+
+from freqtrade.optimize.hyperopt import IHyperOptLoss
+
+
+class SortinoHyperOptLossDaily(IHyperOptLoss):
+    """
+    Defines the loss function for hyperopt.
+
+    This implementation uses the Sortino Ratio calculation.
+    """
+
+    @staticmethod
+    def hyperopt_loss_function(results: DataFrame, trade_count: int,
+                               min_date: datetime, max_date: datetime,
+                               *args, **kwargs) -> float:
+        """
+        Objective function, returns smaller number for more optimal results.
+
+        Uses Sortino Ratio calculation.
+
+        Sortino Ratio calculated as described in
+        http://www.redrockcapital.com/Sortino__A__Sharper__Ratio_Red_Rock_Capital.pdf
+        """
+        resample_freq = '1D'
+        slippage_per_trade_ratio = 0.0005
+        days_in_year = 365
+        minimum_acceptable_return = 0.0
+
+        # apply slippage per trade to profit_percent
+        results.loc[:, 'profit_percent_after_slippage'] = \
+            results['profit_percent'] - slippage_per_trade_ratio
+
+        # create the index within the min_date and end max_date
+        t_index = date_range(start=min_date, end=max_date, freq=resample_freq,
+                             normalize=True)
+
+        sum_daily = (
+            results.resample(resample_freq, on='close_date').agg(
+                {"profit_percent_after_slippage": sum}).reindex(t_index).fillna(0)
+        )
+
+        total_profit = sum_daily["profit_percent_after_slippage"] - minimum_acceptable_return
+        expected_returns_mean = total_profit.mean()
+
+        sum_daily['downside_returns'] = 0
+        sum_daily.loc[total_profit < 0, 'downside_returns'] = total_profit
+        total_downside = sum_daily['downside_returns']
+        # Here total_downside contains min(0, P - MAR) values,
+        # where P = sum_daily["profit_percent_after_slippage"]
+        down_stdev = math.sqrt((total_downside**2).sum() / len(total_downside))
+
+        if down_stdev != 0:
+            sortino_ratio = expected_returns_mean / down_stdev * math.sqrt(days_in_year)
+        else:
+            # Define high (negative) sortino ratio to be clear that this is NOT optimal.
+            sortino_ratio = -20.
+
+        # print(t_index, sum_daily, total_profit)
+        # print(minimum_acceptable_return, expected_returns_mean, down_stdev, sortino_ratio)
+        return -sortino_ratio
diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py
new file mode 100644
index 000000000..c977a991b
--- /dev/null
+++ b/freqtrade/optimize/optimize_reports.py
@@ -0,0 +1,461 @@
+import logging
+from datetime import datetime, timedelta, timezone
+from pathlib import Path
+from typing import Any, Dict, List, Union
+
+from arrow import Arrow
+from numpy import int64
+from pandas import DataFrame
+from tabulate import tabulate
+
+from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN
+from freqtrade.data.btanalysis import calculate_market_change, calculate_max_drawdown
+from freqtrade.misc import file_dump_json
+
+
+logger = logging.getLogger(__name__)
+
+
+def store_backtest_stats(recordfilename: Path, stats: Dict[str, DataFrame]) -> None:
+    """
+    Stores backtest results
+    :param recordfilename: Path object, which can either be a filename or a directory.
+        Filenames will be appended with a timestamp right before the suffix
+        while for diectories, <directory>/backtest-result-<datetime>.json will be used as filename
+    :param stats: Dataframe containing the backtesting statistics
+    """
+    if recordfilename.is_dir():
+        filename = (recordfilename /
+                    f'backtest-result-{datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}.json')
+    else:
+        filename = Path.joinpath(
+            recordfilename.parent,
+            f'{recordfilename.stem}-{datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}'
+            ).with_suffix(recordfilename.suffix)
+    file_dump_json(filename, stats)
+
+    latest_filename = Path.joinpath(filename.parent, LAST_BT_RESULT_FN)
+    file_dump_json(latest_filename, {'latest_backtest': str(filename.name)})
+
+
+def _get_line_floatfmt() -> List[str]:
+    """
+    Generate floatformat (goes in line with _generate_result_line())
+    """
+    return ['s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', 'd', 'd', 'd']
+
+
+def _get_line_header(first_column: str, stake_currency: str) -> List[str]:
+    """
+    Generate header lines (goes in line with _generate_result_line())
+    """
+    return [first_column, 'Buys', 'Avg Profit %', 'Cum Profit %',
+            f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration',
+            'Wins', 'Draws', 'Losses']
+
+
+def _generate_result_line(result: DataFrame, max_open_trades: int, first_column: str) -> Dict:
+    """
+    Generate one result dict, with "first_column" as key.
+    """
+    return {
+        'key': first_column,
+        'trades': len(result),
+        'profit_mean': result['profit_percent'].mean() if len(result) > 0 else 0.0,
+        'profit_mean_pct': result['profit_percent'].mean() * 100.0 if len(result) > 0 else 0.0,
+        'profit_sum': result['profit_percent'].sum(),
+        'profit_sum_pct': result['profit_percent'].sum() * 100.0,
+        'profit_total_abs': result['profit_abs'].sum(),
+        'profit_total': result['profit_percent'].sum() / max_open_trades,
+        'profit_total_pct': result['profit_percent'].sum() * 100.0 / max_open_trades,
+        'duration_avg': str(timedelta(
+                            minutes=round(result['trade_duration'].mean()))
+                            ) if not result.empty else '0:00',
+        # 'duration_max': str(timedelta(
+        #                     minutes=round(result['trade_duration'].max()))
+        #                     ) if not result.empty else '0:00',
+        # 'duration_min': str(timedelta(
+        #                     minutes=round(result['trade_duration'].min()))
+        #                     ) if not result.empty else '0:00',
+        'wins': len(result[result['profit_abs'] > 0]),
+        'draws': len(result[result['profit_abs'] == 0]),
+        'losses': len(result[result['profit_abs'] < 0]),
+    }
+
+
+def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, max_open_trades: int,
+                          results: DataFrame, skip_nan: bool = False) -> List[Dict]:
+    """
+    Generates and returns a list  for the given backtest data and the results dataframe
+    :param data: Dict of <pair: dataframe> containing data that was used during backtesting.
+    :param stake_currency: stake-currency - used to correctly name headers
+    :param max_open_trades: Maximum allowed open trades
+    :param results: Dataframe containing the backtest results
+    :param skip_nan: Print "left open" open trades
+    :return: List of Dicts containing the metrics per pair
+    """
+
+    tabular_data = []
+
+    for pair in data:
+        result = results[results['pair'] == pair]
+        if skip_nan and result['profit_abs'].isnull().all():
+            continue
+
+        tabular_data.append(_generate_result_line(result, max_open_trades, pair))
+
+    # Append Total
+    tabular_data.append(_generate_result_line(results, max_open_trades, 'TOTAL'))
+    return tabular_data
+
+
+def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List[Dict]:
+    """
+    Generate small table outlining Backtest results
+    :param max_open_trades: Max_open_trades parameter
+    :param results: Dataframe containing the backtest result for one strategy
+    :return: List of Dicts containing the metrics per Sell reason
+    """
+    tabular_data = []
+
+    for reason, count in results['sell_reason'].value_counts().iteritems():
+        result = results.loc[results['sell_reason'] == reason]
+
+        profit_mean = result['profit_percent'].mean()
+        profit_sum = result["profit_percent"].sum()
+        profit_percent_tot = result['profit_percent'].sum() / max_open_trades
+
+        tabular_data.append(
+            {
+                'sell_reason': reason.value,
+                'trades': count,
+                'wins': len(result[result['profit_abs'] > 0]),
+                'draws': len(result[result['profit_abs'] == 0]),
+                'losses': len(result[result['profit_abs'] < 0]),
+                'profit_mean': profit_mean,
+                'profit_mean_pct': round(profit_mean * 100, 2),
+                'profit_sum': profit_sum,
+                'profit_sum_pct': round(profit_sum * 100, 2),
+                'profit_total_abs': result['profit_abs'].sum(),
+                'profit_total': profit_percent_tot,
+                'profit_total_pct': round(profit_percent_tot * 100, 2),
+            }
+        )
+    return tabular_data
+
+
+def generate_strategy_metrics(all_results: Dict) -> List[Dict]:
+    """
+    Generate summary per strategy
+    :param all_results: Dict of <Strategyname: BacktestResult> containing results for all strategies
+    :return: List of Dicts containing the metrics per Strategy
+    """
+
+    tabular_data = []
+    for strategy, results in all_results.items():
+        tabular_data.append(_generate_result_line(
+            results['results'], results['config']['max_open_trades'], strategy)
+            )
+    return tabular_data
+
+
+def generate_edge_table(results: dict) -> str:
+
+    floatfmt = ('s', '.10g', '.2f', '.2f', '.2f', '.2f', 'd', 'd', 'd')
+    tabular_data = []
+    headers = ['Pair', 'Stoploss', 'Win Rate', 'Risk Reward Ratio',
+               'Required Risk Reward', 'Expectancy', 'Total Number of Trades',
+               'Average Duration (min)']
+
+    for result in results.items():
+        if result[1].nb_trades > 0:
+            tabular_data.append([
+                result[0],
+                result[1].stoploss,
+                result[1].winrate,
+                result[1].risk_reward_ratio,
+                result[1].required_risk_reward,
+                result[1].expectancy,
+                result[1].nb_trades,
+                round(result[1].avg_trade_duration)
+            ])
+
+    # Ignore type as floatfmt does allow tuples but mypy does not know that
+    return tabulate(tabular_data, headers=headers,
+                    floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")  # type: ignore
+
+
+def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
+    if len(results) == 0:
+        return {
+            'backtest_best_day': 0,
+            'backtest_worst_day': 0,
+            'winning_days': 0,
+            'draw_days': 0,
+            'losing_days': 0,
+            'winner_holding_avg': timedelta(),
+            'loser_holding_avg': timedelta(),
+        }
+    daily_profit = results.resample('1d', on='close_date')['profit_percent'].sum()
+    worst = min(daily_profit)
+    best = max(daily_profit)
+    winning_days = sum(daily_profit > 0)
+    draw_days = sum(daily_profit == 0)
+    losing_days = sum(daily_profit < 0)
+
+    winning_trades = results.loc[results['profit_percent'] > 0]
+    losing_trades = results.loc[results['profit_percent'] < 0]
+
+    return {
+        'backtest_best_day': best,
+        'backtest_worst_day': worst,
+        'winning_days': winning_days,
+        'draw_days': draw_days,
+        'losing_days': losing_days,
+        'winner_holding_avg': (timedelta(minutes=round(winning_trades['trade_duration'].mean()))
+                               if not winning_trades.empty else timedelta()),
+        'loser_holding_avg': (timedelta(minutes=round(losing_trades['trade_duration'].mean()))
+                              if not losing_trades.empty else timedelta()),
+    }
+
+
+def generate_backtest_stats(btdata: Dict[str, DataFrame],
+                            all_results: Dict[str, Dict[str, Union[DataFrame, Dict]]],
+                            min_date: Arrow, max_date: Arrow
+                            ) -> Dict[str, Any]:
+    """
+    :param btdata: Backtest data
+    :param all_results: backtest result - dictionary in the form:
+                     { Strategy: {'results: results, 'config: config}}.
+    :param min_date: Backtest start date
+    :param max_date: Backtest end date
+    :return:
+    Dictionary containing results per strategy and a stratgy summary.
+    """
+    result: Dict[str, Any] = {'strategy': {}}
+    market_change = calculate_market_change(btdata, 'close')
+
+    for strategy, content in all_results.items():
+        results: Dict[str, DataFrame] = content['results']
+        if not isinstance(results, DataFrame):
+            continue
+        config = content['config']
+        max_open_trades = config['max_open_trades']
+        stake_currency = config['stake_currency']
+
+        pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
+                                             max_open_trades=max_open_trades,
+                                             results=results, skip_nan=False)
+        sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades,
+                                                       results=results)
+        left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
+                                                  max_open_trades=max_open_trades,
+                                                  results=results.loc[results['open_at_end']],
+                                                  skip_nan=True)
+        daily_stats = generate_daily_stats(results)
+
+        results['open_timestamp'] = results['open_date'].astype(int64) // 1e6
+        results['close_timestamp'] = results['close_date'].astype(int64) // 1e6
+
+        backtest_days = (max_date - min_date).days
+        strat_stats = {
+            'trades': results.to_dict(orient='records'),
+            'results_per_pair': pair_results,
+            'sell_reason_summary': sell_reason_stats,
+            'left_open_trades': left_open_results,
+            'total_trades': len(results),
+            'profit_mean': results['profit_percent'].mean() if len(results) > 0 else 0,
+            'profit_total': results['profit_percent'].sum(),
+            'profit_total_abs': results['profit_abs'].sum(),
+            'backtest_start': min_date.datetime,
+            'backtest_start_ts': min_date.int_timestamp * 1000,
+            'backtest_end': max_date.datetime,
+            'backtest_end_ts': max_date.int_timestamp * 1000,
+            'backtest_days': backtest_days,
+
+            'trades_per_day': round(len(results) / backtest_days, 2) if backtest_days > 0 else 0,
+            'market_change': market_change,
+            'pairlist': list(btdata.keys()),
+            'stake_amount': config['stake_amount'],
+            'stake_currency': config['stake_currency'],
+            'max_open_trades': (config['max_open_trades']
+                                if config['max_open_trades'] != float('inf') else -1),
+            'timeframe': config['timeframe'],
+            # Parameters relevant for backtesting
+            'stoploss': config['stoploss'],
+            'trailing_stop': config.get('trailing_stop', False),
+            'trailing_stop_positive': config.get('trailing_stop_positive'),
+            'trailing_stop_positive_offset': config.get('trailing_stop_positive_offset', 0.0),
+            'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached', False),
+            'minimal_roi': config['minimal_roi'],
+            'use_sell_signal': config['ask_strategy']['use_sell_signal'],
+            'sell_profit_only': config['ask_strategy']['sell_profit_only'],
+            'ignore_roi_if_buy_signal': config['ask_strategy']['ignore_roi_if_buy_signal'],
+            **daily_stats,
+        }
+        result['strategy'][strategy] = strat_stats
+
+        try:
+            max_drawdown, drawdown_start, drawdown_end = calculate_max_drawdown(
+                results, value_col='profit_percent')
+            strat_stats.update({
+                'max_drawdown': max_drawdown,
+                'drawdown_start': drawdown_start,
+                'drawdown_start_ts': drawdown_start.timestamp() * 1000,
+                'drawdown_end': drawdown_end,
+                'drawdown_end_ts': drawdown_end.timestamp() * 1000,
+            })
+        except ValueError:
+            strat_stats.update({
+                'max_drawdown': 0.0,
+                'drawdown_start': datetime(1970, 1, 1, tzinfo=timezone.utc),
+                'drawdown_start_ts': 0,
+                'drawdown_end': datetime(1970, 1, 1, tzinfo=timezone.utc),
+                'drawdown_end_ts': 0,
+            })
+
+    strategy_results = generate_strategy_metrics(all_results=all_results)
+
+    result['strategy_comparison'] = strategy_results
+
+    return result
+
+
+###
+# Start output section
+###
+
+def text_table_bt_results(pair_results: List[Dict[str, Any]], stake_currency: str) -> str:
+    """
+    Generates and returns a text table for the given backtest data and the results dataframe
+    :param pair_results: List of Dictionaries - one entry per pair + final TOTAL row
+    :param stake_currency: stake-currency - used to correctly name headers
+    :return: pretty printed table with tabulate as string
+    """
+
+    headers = _get_line_header('Pair', stake_currency)
+    floatfmt = _get_line_floatfmt()
+    output = [[
+        t['key'], t['trades'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'],
+        t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses']
+    ] for t in pair_results]
+    # Ignore type as floatfmt does allow tuples but mypy does not know that
+    return tabulate(output, headers=headers,
+                    floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")
+
+
+def text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]], stake_currency: str) -> str:
+    """
+    Generate small table outlining Backtest results
+    :param sell_reason_stats: Sell reason metrics
+    :param stake_currency: Stakecurrency used
+    :return: pretty printed table with tabulate as string
+    """
+    headers = [
+        'Sell Reason',
+        'Sells',
+        'Wins',
+        'Draws',
+        'Losses',
+        'Avg Profit %',
+        'Cum Profit %',
+        f'Tot Profit {stake_currency}',
+        'Tot Profit %',
+    ]
+
+    output = [[
+        t['sell_reason'], t['trades'], t['wins'], t['draws'], t['losses'],
+        t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'], t['profit_total_pct'],
+    ] for t in sell_reason_stats]
+    return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right")
+
+
+def text_table_strategy(strategy_results, stake_currency: str) -> str:
+    """
+    Generate summary table per strategy
+    :param stake_currency: stake-currency - used to correctly name headers
+    :param max_open_trades: Maximum allowed open trades used for backtest
+    :param all_results: Dict of <Strategyname: BacktestResult> containing results for all strategies
+    :return: pretty printed table with tabulate as string
+    """
+    floatfmt = _get_line_floatfmt()
+    headers = _get_line_header('Strategy', stake_currency)
+
+    output = [[
+        t['key'], t['trades'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'],
+        t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses']
+    ] for t in strategy_results]
+    # Ignore type as floatfmt does allow tuples but mypy does not know that
+    return tabulate(output, headers=headers,
+                    floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")
+
+
+def text_table_add_metrics(strat_results: Dict) -> str:
+    if len(strat_results['trades']) > 0:
+        min_trade = min(strat_results['trades'], key=lambda x: x['open_date'])
+        metrics = [
+            ('Backtesting from', strat_results['backtest_start'].strftime(DATETIME_PRINT_FORMAT)),
+            ('Backtesting to', strat_results['backtest_end'].strftime(DATETIME_PRINT_FORMAT)),
+            ('Total trades', strat_results['total_trades']),
+            ('First trade', min_trade['open_date'].strftime(DATETIME_PRINT_FORMAT)),
+            ('First trade Pair', min_trade['pair']),
+            ('Total Profit %', f"{round(strat_results['profit_total'] * 100, 2)}%"),
+            ('Trades per day', strat_results['trades_per_day']),
+            ('Best day', f"{round(strat_results['backtest_best_day'] * 100, 2)}%"),
+            ('Worst day', f"{round(strat_results['backtest_worst_day'] * 100, 2)}%"),
+            ('Days win/draw/lose', f"{strat_results['winning_days']} / "
+                f"{strat_results['draw_days']} / {strat_results['losing_days']}"),
+            ('Avg. Duration Winners', f"{strat_results['winner_holding_avg']}"),
+            ('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"),
+            ('', ''),  # Empty line to improve readability
+            ('Max Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"),
+            ('Drawdown Start', strat_results['drawdown_start'].strftime(DATETIME_PRINT_FORMAT)),
+            ('Drawdown End', strat_results['drawdown_end'].strftime(DATETIME_PRINT_FORMAT)),
+            ('Market change', f"{round(strat_results['market_change'] * 100, 2)}%"),
+        ]
+
+        return tabulate(metrics, headers=["Metric", "Value"], tablefmt="orgtbl")
+    else:
+        return ''
+
+
+def show_backtest_results(config: Dict, backtest_stats: Dict):
+    stake_currency = config['stake_currency']
+
+    for strategy, results in backtest_stats['strategy'].items():
+
+        # Print results
+        print(f"Result for strategy {strategy}")
+        table = text_table_bt_results(results['results_per_pair'], stake_currency=stake_currency)
+        if isinstance(table, str):
+            print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '='))
+        print(table)
+
+        table = text_table_sell_reason(sell_reason_stats=results['sell_reason_summary'],
+                                       stake_currency=stake_currency)
+        if isinstance(table, str) and len(table) > 0:
+            print(' SELL REASON STATS '.center(len(table.splitlines()[0]), '='))
+        print(table)
+
+        table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency)
+        if isinstance(table, str) and len(table) > 0:
+            print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
+        print(table)
+
+        table = text_table_add_metrics(results)
+        if isinstance(table, str) and len(table) > 0:
+            print(' SUMMARY METRICS '.center(len(table.splitlines()[0]), '='))
+        print(table)
+
+        if isinstance(table, str) and len(table) > 0:
+            print('=' * len(table.splitlines()[0]))
+        print()
+
+    if len(backtest_stats['strategy']) > 1:
+        # Print Strategy summary table
+
+        table = text_table_strategy(backtest_stats['strategy_comparison'], stake_currency)
+        print(' STRATEGY SUMMARY '.center(len(table.splitlines()[0]), '='))
+        print(table)
+        print('=' * len(table.splitlines()[0]))
+        print('\nFor more details, please look at the detail tables above')
diff --git a/freqtrade/pairlist/AgeFilter.py b/freqtrade/pairlist/AgeFilter.py
new file mode 100644
index 000000000..19cf1c090
--- /dev/null
+++ b/freqtrade/pairlist/AgeFilter.py
@@ -0,0 +1,84 @@
+"""
+Minimum age (days listed) pair list filter
+"""
+import logging
+from typing import Any, Dict
+
+import arrow
+
+from freqtrade.exceptions import OperationalException
+from freqtrade.misc import plural
+from freqtrade.pairlist.IPairList import IPairList
+
+
+logger = logging.getLogger(__name__)
+
+
+class AgeFilter(IPairList):
+
+    # Checked symbols cache (dictionary of ticker symbol => timestamp)
+    _symbolsChecked: Dict[str, int] = {}
+
+    def __init__(self, exchange, pairlistmanager,
+                 config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+                 pairlist_pos: int) -> None:
+        super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
+
+        self._min_days_listed = pairlistconfig.get('min_days_listed', 10)
+
+        if self._min_days_listed < 1:
+            raise OperationalException("AgeFilter requires min_days_listed to be >= 1")
+        if self._min_days_listed > exchange.ohlcv_candle_limit:
+            raise OperationalException("AgeFilter requires min_days_listed to not exceed "
+                                       "exchange max request size "
+                                       f"({exchange.ohlcv_candle_limit})")
+
+    @property
+    def needstickers(self) -> bool:
+        """
+        Boolean property defining if tickers are necessary.
+        If no Pairlist requires tickers, an empty List is passed
+        as tickers argument to filter_pairlist
+        """
+        return True
+
+    def short_desc(self) -> str:
+        """
+        Short whitelist method description - used for startup-messages
+        """
+        return (f"{self.name} - Filtering pairs with age less than "
+                f"{self._min_days_listed} {plural(self._min_days_listed, 'day')}.")
+
+    def _validate_pair(self, ticker: dict) -> bool:
+        """
+        Validate age for the ticker
+        :param ticker: ticker dict as returned from ccxt.load_markets()
+        :return: True if the pair can stay, False if it should be removed
+        """
+
+        # Check symbol in cache
+        if ticker['symbol'] in self._symbolsChecked:
+            return True
+
+        since_ms = int(arrow.utcnow()
+                       .floor('day')
+                       .shift(days=-self._min_days_listed)
+                       .float_timestamp) * 1000
+
+        daily_candles = self._exchange.get_historic_ohlcv(pair=ticker['symbol'],
+                                                          timeframe='1d',
+                                                          since_ms=since_ms)
+
+        if daily_candles is not None:
+            if len(daily_candles) > self._min_days_listed:
+                # We have fetched at least the minimum required number of daily candles
+                # Add to cache, store the time we last checked this symbol
+                self._symbolsChecked[ticker['symbol']] = int(arrow.utcnow().float_timestamp) * 1000
+                return True
+            else:
+                self.log_on_refresh(logger.info, f"Removed {ticker['symbol']} from whitelist, "
+                                                 f"because age {len(daily_candles)} is less than "
+                                                 f"{self._min_days_listed} "
+                                                 f"{plural(self._min_days_listed, 'day')}")
+                return False
+        return False
diff --git a/freqtrade/pairlist/IPairList.py b/freqtrade/pairlist/IPairList.py
index a112c63b4..6b5bd11e7 100644
--- a/freqtrade/pairlist/IPairList.py
+++ b/freqtrade/pairlist/IPairList.py
@@ -1,23 +1,42 @@
 """
-Static List provider
-
-Provides lists as configured in config.json
-
- """
+PairList Handler base class
+"""
 import logging
-from abc import ABC, abstractmethod
-from typing import List
+from abc import ABC, abstractmethod, abstractproperty
+from copy import deepcopy
+from typing import Any, Dict, List
+
+from cachetools import TTLCache, cached
+
+from freqtrade.exceptions import OperationalException
+from freqtrade.exchange import market_is_active
+
 
 logger = logging.getLogger(__name__)
 
 
 class IPairList(ABC):
 
-    def __init__(self, freqtrade, config: dict) -> None:
-        self._freqtrade = freqtrade
+    def __init__(self, exchange, pairlistmanager,
+                 config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+                 pairlist_pos: int) -> None:
+        """
+        :param exchange: Exchange instance
+        :param pairlistmanager: Instantiated Pairlist manager
+        :param config: Global bot configuration
+        :param pairlistconfig: Configuration for this Pairlist Handler - can be empty.
+        :param pairlist_pos: Position of the Pairlist Handler in the chain
+        """
+        self._enabled = True
+
+        self._exchange = exchange
+        self._pairlistmanager = pairlistmanager
         self._config = config
-        self._whitelist = self._config['exchange']['pair_whitelist']
-        self._blacklist = self._config['exchange'].get('pair_blacklist', [])
+        self._pairlistconfig = pairlistconfig
+        self._pairlist_pos = pairlist_pos
+        self.refresh_period = self._pairlistconfig.get('refresh_period', 1800)
+        self._last_refresh = 0
+        self._log_cache: TTLCache = TTLCache(maxsize=1024, ttl=self.refresh_period)
 
     @property
     def name(self) -> str:
@@ -27,21 +46,31 @@ class IPairList(ABC):
         """
         return self.__class__.__name__
 
-    @property
-    def whitelist(self) -> List[str]:
+    def log_on_refresh(self, logmethod, message: str) -> None:
         """
-        Has the current whitelist
-        -> no need to overwrite in subclasses
+        Logs message - not more often than "refresh_period" to avoid log spamming
+        Logs the log-message as debug as well to simplify debugging.
+        :param logmethod: Function that'll be called. Most likely `logger.info`.
+        :param message: String containing the message to be sent to the function.
+        :return: None.
         """
-        return self._whitelist
 
-    @property
-    def blacklist(self) -> List[str]:
+        @cached(cache=self._log_cache)
+        def _log_on_refresh(message: str):
+            logmethod(message)
+
+        # Log as debug first
+        logger.debug(message)
+        # Call hidden function.
+        _log_on_refresh(message)
+
+    @abstractproperty
+    def needstickers(self) -> bool:
         """
-        Has the current blacklist
-        -> no need to overwrite in subclasses
+        Boolean property defining if tickers are necessary.
+        If no Pairlist requires tickers, an empty List is passed
+        as tickers argument to filter_pairlist
         """
-        return self._blacklist
 
     @abstractmethod
     def short_desc(self) -> str:
@@ -50,37 +79,106 @@ class IPairList(ABC):
         -> Please overwrite in subclasses
         """
 
-    @abstractmethod
-    def refresh_pairlist(self) -> None:
-        """
-        Refreshes pairlists and assigns them to self._whitelist and self._blacklist respectively
-        -> Please overwrite in subclasses
+    def _validate_pair(self, ticker) -> bool:
         """
+        Check one pair against Pairlist Handler's specific conditions.
 
-    def _validate_whitelist(self, whitelist: List[str]) -> List[str]:
+        Either implement it in the Pairlist Handler or override the generic
+        filter_pairlist() method.
+
+        :param ticker: ticker dict as returned from ccxt.load_markets()
+        :return: True if the pair can stay, false if it should be removed
+        """
+        raise NotImplementedError()
+
+    def gen_pairlist(self, cached_pairlist: List[str], tickers: Dict) -> List[str]:
+        """
+        Generate the pairlist.
+
+        This method is called once by the pairlistmanager in the refresh_pairlist()
+        method to supply the starting pairlist for the chain of the Pairlist Handlers.
+        Pairlist Filters (those Pairlist Handlers that cannot be used at the first
+        position in the chain) shall not override this base implementation --
+        it will raise the exception if a Pairlist Handler is used at the first
+        position in the chain.
+
+        :param cached_pairlist: Previously generated pairlist (cached)
+        :param tickers: Tickers (from exchange.get_tickers()).
+        :return: List of pairs
+        """
+        raise OperationalException("This Pairlist Handler should not be used "
+                                   "at the first position in the list of Pairlist Handlers.")
+
+    def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
+        """
+        Filters and sorts pairlist and returns the whitelist again.
+
+        Called on each bot iteration - please use internal caching if necessary
+        This generic implementation calls self._validate_pair() for each pair
+        in the pairlist.
+
+        Some Pairlist Handlers override this generic implementation and employ
+        own filtration.
+
+        :param pairlist: pairlist to filter or sort
+        :param tickers: Tickers (from exchange.get_tickers()). May be cached.
+        :return: new whitelist
+        """
+        if self._enabled:
+            # Copy list since we're modifying this list
+            for p in deepcopy(pairlist):
+                # Filter out assets
+                if not self._validate_pair(tickers[p]):
+                    pairlist.remove(p)
+
+        return pairlist
+
+    def verify_blacklist(self, pairlist: List[str], logmethod) -> List[str]:
+        """
+        Proxy method to verify_blacklist for easy access for child classes.
+        :param pairlist: Pairlist to validate
+        :param logmethod: Function that'll be called, `logger.info` or `logger.warning`.
+        :return: pairlist - blacklisted pairs
+        """
+        return self._pairlistmanager.verify_blacklist(pairlist, logmethod)
+
+    def _whitelist_for_active_markets(self, pairlist: List[str]) -> List[str]:
         """
         Check available markets and remove pair from whitelist if necessary
         :param whitelist: the sorted list of pairs the user might want to trade
         :return: the list of pairs the user wants to trade without those unavailable or
         black_listed
         """
-        markets = self._freqtrade.exchange.markets
+        markets = self._exchange.markets
+        if not markets:
+            raise OperationalException(
+                    'Markets not loaded. Make sure that exchange is initialized correctly.')
 
-        sanitized_whitelist = set()
-        for pair in whitelist:
-            # pair is not in the generated dynamic market, or in the blacklist ... ignore it
-            if (pair in self.blacklist or pair not in markets
-                    or not pair.endswith(self._config['stake_currency'])):
+        sanitized_whitelist: List[str] = []
+        for pair in pairlist:
+            # pair is not in the generated dynamic market or has the wrong stake currency
+            if pair not in markets:
                 logger.warning(f"Pair {pair} is not compatible with exchange "
-                               f"{self._freqtrade.exchange.name} or contained in "
-                               f"your blacklist. Removing it from whitelist..")
+                               f"{self._exchange.name}. Removing it from whitelist..")
                 continue
+
+            if not self._exchange.market_is_tradable(markets[pair]):
+                logger.warning(f"Pair {pair} is not tradable with Freqtrade."
+                               "Removing it from whitelist..")
+                continue
+
+            if self._exchange.get_pair_quote_currency(pair) != self._config['stake_currency']:
+                logger.warning(f"Pair {pair} is not compatible with your stake currency "
+                               f"{self._config['stake_currency']}. Removing it from whitelist..")
+                continue
+
             # Check if market is active
             market = markets[pair]
-            if not market['active']:
+            if not market_is_active(market):
                 logger.info(f"Ignoring {pair} from whitelist. Market is not active.")
                 continue
-            sanitized_whitelist.add(pair)
+            if pair not in sanitized_whitelist:
+                sanitized_whitelist.append(pair)
 
         # We need to remove pairs that are unknown
-        return list(sanitized_whitelist)
+        return sanitized_whitelist
diff --git a/freqtrade/pairlist/PrecisionFilter.py b/freqtrade/pairlist/PrecisionFilter.py
new file mode 100644
index 000000000..cf853397b
--- /dev/null
+++ b/freqtrade/pairlist/PrecisionFilter.py
@@ -0,0 +1,67 @@
+"""
+Precision pair list filter
+"""
+import logging
+from typing import Any, Dict
+
+from freqtrade.exceptions import OperationalException
+from freqtrade.pairlist.IPairList import IPairList
+
+
+logger = logging.getLogger(__name__)
+
+
+class PrecisionFilter(IPairList):
+
+    def __init__(self, exchange, pairlistmanager,
+                 config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+                 pairlist_pos: int) -> None:
+        super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
+
+        if 'stoploss' not in self._config:
+            raise OperationalException(
+                'PrecisionFilter can only work with stoploss defined. Please add the '
+                'stoploss key to your configuration (overwrites eventual strategy settings).')
+        self._stoploss = self._config['stoploss']
+        self._enabled = self._stoploss != 0
+
+        # Precalculate sanitized stoploss value to avoid recalculation for every pair
+        self._stoploss = 1 - abs(self._stoploss)
+
+    @property
+    def needstickers(self) -> bool:
+        """
+        Boolean property defining if tickers are necessary.
+        If no Pairlist requires tickers, an empty List is passed
+        as tickers argument to filter_pairlist
+        """
+        return True
+
+    def short_desc(self) -> str:
+        """
+        Short whitelist method description - used for startup-messages
+        """
+        return f"{self.name} - Filtering untradable pairs."
+
+    def _validate_pair(self, ticker: dict) -> bool:
+        """
+        Check if pair has enough room to add a stoploss to avoid "unsellable" buys of very
+        low value pairs.
+        :param ticker: ticker dict as returned from ccxt.load_markets()
+        :return: True if the pair can stay, False if it should be removed
+        """
+        stop_price = ticker['ask'] * self._stoploss
+
+        # Adjust stop-prices to precision
+        sp = self._exchange.price_to_precision(ticker["symbol"], stop_price)
+
+        stop_gap_price = self._exchange.price_to_precision(ticker["symbol"], stop_price * 0.99)
+        logger.debug(f"{ticker['symbol']} - {sp} : {stop_gap_price}")
+
+        if sp <= stop_gap_price:
+            self.log_on_refresh(logger.info,
+                                f"Removed {ticker['symbol']} from whitelist, "
+                                f"because stop price {sp} would be <= stop limit {stop_gap_price}")
+            return False
+
+        return True
diff --git a/freqtrade/pairlist/PriceFilter.py b/freqtrade/pairlist/PriceFilter.py
new file mode 100644
index 000000000..8cd57ee1d
--- /dev/null
+++ b/freqtrade/pairlist/PriceFilter.py
@@ -0,0 +1,95 @@
+"""
+Price pair list filter
+"""
+import logging
+from typing import Any, Dict
+
+from freqtrade.exceptions import OperationalException
+from freqtrade.pairlist.IPairList import IPairList
+
+
+logger = logging.getLogger(__name__)
+
+
+class PriceFilter(IPairList):
+
+    def __init__(self, exchange, pairlistmanager,
+                 config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+                 pairlist_pos: int) -> None:
+        super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
+
+        self._low_price_ratio = pairlistconfig.get('low_price_ratio', 0)
+        if self._low_price_ratio < 0:
+            raise OperationalException("PriceFilter requires low_price_ratio to be >= 0")
+        self._min_price = pairlistconfig.get('min_price', 0)
+        if self._min_price < 0:
+            raise OperationalException("PriceFilter requires min_price to be >= 0")
+        self._max_price = pairlistconfig.get('max_price', 0)
+        if self._max_price < 0:
+            raise OperationalException("PriceFilter requires max_price to be >= 0")
+        self._enabled = ((self._low_price_ratio > 0) or
+                         (self._min_price > 0) or
+                         (self._max_price > 0))
+
+    @property
+    def needstickers(self) -> bool:
+        """
+        Boolean property defining if tickers are necessary.
+        If no Pairlist requires tickers, an empty List is passed
+        as tickers argument to filter_pairlist
+        """
+        return True
+
+    def short_desc(self) -> str:
+        """
+        Short whitelist method description - used for startup-messages
+        """
+        active_price_filters = []
+        if self._low_price_ratio != 0:
+            active_price_filters.append(f"below {self._low_price_ratio * 100}%")
+        if self._min_price != 0:
+            active_price_filters.append(f"below {self._min_price:.8f}")
+        if self._max_price != 0:
+            active_price_filters.append(f"above {self._max_price:.8f}")
+
+        if len(active_price_filters):
+            return f"{self.name} - Filtering pairs priced {' or '.join(active_price_filters)}."
+
+        return f"{self.name} - No price filters configured."
+
+    def _validate_pair(self, ticker) -> bool:
+        """
+        Check if if one price-step (pip) is > than a certain barrier.
+        :param ticker: ticker dict as returned from ccxt.load_markets()
+        :return: True if the pair can stay, false if it should be removed
+        """
+        if ticker['last'] is None or ticker['last'] == 0:
+            self.log_on_refresh(logger.info,
+                                f"Removed {ticker['symbol']} from whitelist, because "
+                                "ticker['last'] is empty (Usually no trade in the last 24h).")
+            return False
+
+        # Perform low_price_ratio check.
+        if self._low_price_ratio != 0:
+            compare = self._exchange.price_get_one_pip(ticker['symbol'], ticker['last'])
+            changeperc = compare / ticker['last']
+            if changeperc > self._low_price_ratio:
+                self.log_on_refresh(logger.info, f"Removed {ticker['symbol']} from whitelist, "
+                                                 f"because 1 unit is {changeperc * 100:.3f}%")
+                return False
+
+        # Perform min_price check.
+        if self._min_price != 0:
+            if ticker['last'] < self._min_price:
+                self.log_on_refresh(logger.info, f"Removed {ticker['symbol']} from whitelist, "
+                                                 f"because last price < {self._min_price:.8f}")
+                return False
+
+        # Perform max_price check.
+        if self._max_price != 0:
+            if ticker['last'] > self._max_price:
+                self.log_on_refresh(logger.info, f"Removed {ticker['symbol']} from whitelist, "
+                                                 f"because last price > {self._max_price:.8f}")
+                return False
+
+        return True
diff --git a/freqtrade/pairlist/ShuffleFilter.py b/freqtrade/pairlist/ShuffleFilter.py
new file mode 100644
index 000000000..eb4f6dcc3
--- /dev/null
+++ b/freqtrade/pairlist/ShuffleFilter.py
@@ -0,0 +1,51 @@
+"""
+Shuffle pair list filter
+"""
+import logging
+import random
+from typing import Any, Dict, List
+
+from freqtrade.pairlist.IPairList import IPairList
+
+
+logger = logging.getLogger(__name__)
+
+
+class ShuffleFilter(IPairList):
+
+    def __init__(self, exchange, pairlistmanager,
+                 config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+                 pairlist_pos: int) -> None:
+        super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
+
+        self._seed = pairlistconfig.get('seed')
+        self._random = random.Random(self._seed)
+
+    @property
+    def needstickers(self) -> bool:
+        """
+        Boolean property defining if tickers are necessary.
+        If no Pairlist requires tickers, an empty List is passed
+        as tickers argument to filter_pairlist
+        """
+        return False
+
+    def short_desc(self) -> str:
+        """
+        Short whitelist method description - used for startup-messages
+        """
+        return (f"{self.name} - Shuffling pairs" +
+                (f", seed = {self._seed}." if self._seed is not None else "."))
+
+    def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
+        """
+        Filters and sorts pairlist and returns the whitelist again.
+        Called on each bot iteration - please use internal caching if necessary
+        :param pairlist: pairlist to filter or sort
+        :param tickers: Tickers (from exchange.get_tickers()). May be cached.
+        :return: new whitelist
+        """
+        # Shuffle is done inplace
+        self._random.shuffle(pairlist)
+
+        return pairlist
diff --git a/freqtrade/pairlist/SpreadFilter.py b/freqtrade/pairlist/SpreadFilter.py
new file mode 100644
index 000000000..2527a3131
--- /dev/null
+++ b/freqtrade/pairlist/SpreadFilter.py
@@ -0,0 +1,54 @@
+"""
+Spread pair list filter
+"""
+import logging
+from typing import Any, Dict
+
+from freqtrade.pairlist.IPairList import IPairList
+
+
+logger = logging.getLogger(__name__)
+
+
+class SpreadFilter(IPairList):
+
+    def __init__(self, exchange, pairlistmanager,
+                 config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+                 pairlist_pos: int) -> None:
+        super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
+
+        self._max_spread_ratio = pairlistconfig.get('max_spread_ratio', 0.005)
+        self._enabled = self._max_spread_ratio != 0
+
+    @property
+    def needstickers(self) -> bool:
+        """
+        Boolean property defining if tickers are necessary.
+        If no Pairlist requires tickers, an empty List is passed
+        as tickers argument to filter_pairlist
+        """
+        return True
+
+    def short_desc(self) -> str:
+        """
+        Short whitelist method description - used for startup-messages
+        """
+        return (f"{self.name} - Filtering pairs with ask/bid diff above "
+                f"{self._max_spread_ratio * 100}%.")
+
+    def _validate_pair(self, ticker: dict) -> bool:
+        """
+        Validate spread for the ticker
+        :param ticker: ticker dict as returned from ccxt.load_markets()
+        :return: True if the pair can stay, False if it should be removed
+        """
+        if 'bid' in ticker and 'ask' in ticker:
+            spread = 1 - ticker['bid'] / ticker['ask']
+            if spread > self._max_spread_ratio:
+                self.log_on_refresh(logger.info, f"Removed {ticker['symbol']} from whitelist, "
+                                                 f"because spread {spread * 100:.3f}% >"
+                                                 f"{self._max_spread_ratio * 100}%")
+                return False
+            else:
+                return True
+        return False
diff --git a/freqtrade/pairlist/StaticPairList.py b/freqtrade/pairlist/StaticPairList.py
index 5896e814a..3b6440763 100644
--- a/freqtrade/pairlist/StaticPairList.py
+++ b/freqtrade/pairlist/StaticPairList.py
@@ -1,30 +1,65 @@
 """
-Static List provider
+Static Pair List provider
 
-Provides lists as configured in config.json
-
- """
+Provides pair white list as it configured in config
+"""
 import logging
+from typing import Any, Dict, List
 
+from freqtrade.exceptions import OperationalException
 from freqtrade.pairlist.IPairList import IPairList
 
+
 logger = logging.getLogger(__name__)
 
 
 class StaticPairList(IPairList):
 
-    def __init__(self, freqtrade, config: dict) -> None:
-        super().__init__(freqtrade, config)
+    def __init__(self, exchange, pairlistmanager,
+                 config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+                 pairlist_pos: int) -> None:
+        super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
+
+        if self._pairlist_pos != 0:
+            raise OperationalException(f"{self.name} can only be used in the first position "
+                                       "in the list of Pairlist Handlers.")
+
+        self._allow_inactive = self._pairlistconfig.get('allow_inactive', False)
+
+    @property
+    def needstickers(self) -> bool:
+        """
+        Boolean property defining if tickers are necessary.
+        If no Pairlist requires tickers, an empty List is passed
+        as tickers argument to filter_pairlist
+        """
+        return False
 
     def short_desc(self) -> str:
         """
         Short whitelist method description - used for startup-messages
         -> Please overwrite in subclasses
         """
-        return f"{self.name}: {self.whitelist}"
+        return f"{self.name}"
 
-    def refresh_pairlist(self) -> None:
+    def gen_pairlist(self, cached_pairlist: List[str], tickers: Dict) -> List[str]:
         """
-        Refreshes pairlists and assigns them to self._whitelist and self._blacklist respectively
+        Generate the pairlist
+        :param cached_pairlist: Previously generated pairlist (cached)
+        :param tickers: Tickers (from exchange.get_tickers()).
+        :return: List of pairs
         """
-        self._whitelist = self._validate_whitelist(self._config['exchange']['pair_whitelist'])
+        if self._allow_inactive:
+            return self._config['exchange']['pair_whitelist']
+        else:
+            return self._whitelist_for_active_markets(self._config['exchange']['pair_whitelist'])
+
+    def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
+        """
+        Filters and sorts pairlist and returns the whitelist again.
+        Called on each bot iteration - please use internal caching if necessary
+        :param pairlist: pairlist to filter or sort
+        :param tickers: Tickers (from exchange.get_tickers()). May be cached.
+        :return: new whitelist
+        """
+        return pairlist
diff --git a/freqtrade/pairlist/VolumePairList.py b/freqtrade/pairlist/VolumePairList.py
index 9a2e2eac4..44e5c52d7 100644
--- a/freqtrade/pairlist/VolumePairList.py
+++ b/freqtrade/pairlist/VolumePairList.py
@@ -1,95 +1,116 @@
 """
 Volume PairList provider
 
-Provides lists as configured in config.json
-
- """
+Provides dynamic pair list based on trade volumes
+"""
 import logging
-from typing import List
-from cachetools import TTLCache, cached
+from datetime import datetime
+from typing import Any, Dict, List
 
+from freqtrade.exceptions import OperationalException
 from freqtrade.pairlist.IPairList import IPairList
-from freqtrade import OperationalException
+
+
 logger = logging.getLogger(__name__)
 
-SORT_VALUES = ['askVolume', 'bidVolume', 'quoteVolume']
+
+SORT_VALUES = ['quoteVolume']
 
 
 class VolumePairList(IPairList):
 
-    def __init__(self, freqtrade, config: dict) -> None:
-        super().__init__(freqtrade, config)
-        self._whitelistconf = self._config.get('pairlist', {}).get('config')
-        if 'number_assets' not in self._whitelistconf:
-            raise OperationalException(
-                f'`number_assets` not specified. Please check your configuration '
-                'for "pairlist.config.number_assets"')
-        self._number_pairs = self._whitelistconf['number_assets']
-        self._sort_key = self._whitelistconf.get('sort_key', 'quoteVolume')
-        self._precision_filter = self._whitelistconf.get('precision_filter', False)
+    def __init__(self, exchange, pairlistmanager,
+                 config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+                 pairlist_pos: int) -> None:
+        super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
 
-        if not self._freqtrade.exchange.exchange_has('fetchTickers'):
+        if 'number_assets' not in self._pairlistconfig:
             raise OperationalException(
-                'Exchange does not support dynamic whitelist.'
-                'Please edit your config and restart the bot'
+                '`number_assets` not specified. Please check your configuration '
+                'for "pairlist.config.number_assets"')
+
+        self._stake_currency = config['stake_currency']
+        self._number_pairs = self._pairlistconfig['number_assets']
+        self._sort_key = self._pairlistconfig.get('sort_key', 'quoteVolume')
+        self._min_value = self._pairlistconfig.get('min_value', 0)
+        self.refresh_period = self._pairlistconfig.get('refresh_period', 1800)
+
+        if not self._exchange.exchange_has('fetchTickers'):
+            raise OperationalException(
+                'Exchange does not support dynamic whitelist. '
+                'Please edit your config and restart the bot.'
             )
+
         if not self._validate_keys(self._sort_key):
             raise OperationalException(
                 f'key {self._sort_key} not in {SORT_VALUES}')
 
+    @property
+    def needstickers(self) -> bool:
+        """
+        Boolean property defining if tickers are necessary.
+        If no Pairlist requires tickers, an empty List is passed
+        as tickers argument to filter_pairlist
+        """
+        return True
+
     def _validate_keys(self, key):
         return key in SORT_VALUES
 
     def short_desc(self) -> str:
         """
         Short whitelist method description - used for startup-messages
-        -> Please overwrite in subclasses
         """
-        return f"{self.name} - top {self._whitelistconf['number_assets']} volume pairs."
+        return f"{self.name} - top {self._pairlistconfig['number_assets']} volume pairs."
 
-    def refresh_pairlist(self) -> None:
+    def gen_pairlist(self, cached_pairlist: List[str], tickers: Dict) -> List[str]:
         """
-        Refreshes pairlists and assigns them to self._whitelist and self._blacklist respectively
-        -> Please overwrite in subclasses
-        """
-        # Generate dynamic whitelist
-        self._whitelist = self._gen_pair_whitelist(
-            self._config['stake_currency'], self._sort_key)[:self._number_pairs]
-        logger.info(f"Searching pairs: {self._whitelist}")
-
-    @cached(TTLCache(maxsize=1, ttl=1800))
-    def _gen_pair_whitelist(self, base_currency: str, key: str) -> List[str]:
-        """
-        Updates the whitelist with with a dynamically generated list
-        :param base_currency: base currency as str
-        :param key: sort key (defaults to 'quoteVolume')
+        Generate the pairlist
+        :param cached_pairlist: Previously generated pairlist (cached)
+        :param tickers: Tickers (from exchange.get_tickers()).
         :return: List of pairs
         """
+        # Generate dynamic whitelist
+        # Must always run if this pairlist is not the first in the list.
+        if self._last_refresh + self.refresh_period < datetime.now().timestamp():
+            self._last_refresh = int(datetime.now().timestamp())
+
+            # Use fresh pairlist
+            # Check if pair quote currency equals to the stake currency.
+            filtered_tickers = [
+                    v for k, v in tickers.items()
+                    if (self._exchange.get_pair_quote_currency(k) == self._stake_currency
+                        and v[self._sort_key] is not None)]
+            pairlist = [s['symbol'] for s in filtered_tickers]
+        else:
+            # Use the cached pairlist if it's not time yet to refresh
+            pairlist = cached_pairlist
+
+        return pairlist
+
+    def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
+        """
+        Filters and sorts pairlist and returns the whitelist again.
+        Called on each bot iteration - please use internal caching if necessary
+        :param pairlist: pairlist to filter or sort
+        :param tickers: Tickers (from exchange.get_tickers()). May be cached.
+        :return: new whitelist
+        """
+        # Use the incoming pairlist.
+        filtered_tickers = [v for k, v in tickers.items() if k in pairlist]
+
+        if self._min_value > 0:
+            filtered_tickers = [
+                    v for v in filtered_tickers if v[self._sort_key] > self._min_value]
+
+        sorted_tickers = sorted(filtered_tickers, reverse=True, key=lambda t: t[self._sort_key])
 
-        tickers = self._freqtrade.exchange.get_tickers()
-        # check length so that we make sure that '/' is actually in the string
-        tickers = [v for k, v in tickers.items()
-                   if (len(k.split('/')) == 2 and k.split('/')[1] == base_currency
-                       and v[key] is not None)]
-        sorted_tickers = sorted(tickers, reverse=True, key=lambda t: t[key])
         # Validate whitelist to only have active market pairs
-        valid_pairs = self._validate_whitelist([s['symbol'] for s in sorted_tickers])
-        valid_tickers = [t for t in sorted_tickers if t["symbol"] in valid_pairs]
+        pairs = self._whitelist_for_active_markets([s['symbol'] for s in sorted_tickers])
+        pairs = self.verify_blacklist(pairs, logger.info)
+        # Limit pairlist to the requested number of pairs
+        pairs = pairs[:self._number_pairs]
 
-        if self._freqtrade.strategy.stoploss is not None and self._precision_filter:
+        self.log_on_refresh(logger.info, f"Searching {self._number_pairs} pairs: {pairs}")
 
-            stop_prices = [self._freqtrade.get_target_bid(t["symbol"], t)
-                           * (1 - abs(self._freqtrade.strategy.stoploss)) for t in valid_tickers]
-            rates = [sp * 0.99 for sp in stop_prices]
-            logger.debug("\n".join([f"{sp} : {r}" for sp, r in zip(stop_prices[:10], rates[:10])]))
-            for i, t in enumerate(valid_tickers):
-                sp = self._freqtrade.exchange.symbol_price_prec(t["symbol"], stop_prices[i])
-                r = self._freqtrade.exchange.symbol_price_prec(t["symbol"], rates[i])
-                logger.debug(f"{t['symbol']} - {sp} : {r}")
-                if sp <= r:
-                    logger.info(f"Removed {t['symbol']} from whitelist, "
-                                f"because stop price {sp} would be <= stop limit {r}")
-                    valid_tickers.remove(t)
-
-        pairs = [s['symbol'] for s in valid_tickers]
         return pairs
diff --git a/freqtrade/pairlist/pairlistmanager.py b/freqtrade/pairlist/pairlistmanager.py
new file mode 100644
index 000000000..89bab99be
--- /dev/null
+++ b/freqtrade/pairlist/pairlistmanager.py
@@ -0,0 +1,136 @@
+"""
+PairList manager class
+"""
+import logging
+from copy import deepcopy
+from typing import Dict, List
+
+from cachetools import TTLCache, cached
+
+from freqtrade.constants import ListPairsWithTimeframes
+from freqtrade.exceptions import OperationalException
+from freqtrade.pairlist.IPairList import IPairList
+from freqtrade.resolvers import PairListResolver
+
+
+logger = logging.getLogger(__name__)
+
+
+class PairListManager():
+
+    def __init__(self, exchange, config: dict) -> None:
+        self._exchange = exchange
+        self._config = config
+        self._whitelist = self._config['exchange'].get('pair_whitelist')
+        self._blacklist = self._config['exchange'].get('pair_blacklist', [])
+        self._pairlist_handlers: List[IPairList] = []
+        self._tickers_needed = False
+        for pairlist_handler_config in self._config.get('pairlists', None):
+            if 'method' not in pairlist_handler_config:
+                logger.warning(f"No method found in {pairlist_handler_config}, ignoring.")
+                continue
+            pairlist_handler = PairListResolver.load_pairlist(
+                    pairlist_handler_config['method'],
+                    exchange=exchange,
+                    pairlistmanager=self,
+                    config=config,
+                    pairlistconfig=pairlist_handler_config,
+                    pairlist_pos=len(self._pairlist_handlers)
+                    )
+            self._tickers_needed |= pairlist_handler.needstickers
+            self._pairlist_handlers.append(pairlist_handler)
+
+        if not self._pairlist_handlers:
+            raise OperationalException("No Pairlist Handlers defined")
+
+    @property
+    def whitelist(self) -> List[str]:
+        """
+        Has the current whitelist
+        """
+        return self._whitelist
+
+    @property
+    def blacklist(self) -> List[str]:
+        """
+        Has the current blacklist
+        -> no need to overwrite in subclasses
+        """
+        return self._blacklist
+
+    @property
+    def name_list(self) -> List[str]:
+        """
+        Get list of loaded Pairlist Handler names
+        """
+        return [p.name for p in self._pairlist_handlers]
+
+    def short_desc(self) -> List[Dict]:
+        """
+        List of short_desc for each Pairlist Handler
+        """
+        return [{p.name: p.short_desc()} for p in self._pairlist_handlers]
+
+    @cached(TTLCache(maxsize=1, ttl=1800))
+    def _get_cached_tickers(self):
+        return self._exchange.get_tickers()
+
+    def refresh_pairlist(self) -> None:
+        """
+        Run pairlist through all configured Pairlist Handlers.
+        """
+        # Tickers should be cached to avoid calling the exchange on each call.
+        tickers: Dict = {}
+        if self._tickers_needed:
+            tickers = self._get_cached_tickers()
+
+        # Adjust whitelist if filters are using tickers
+        pairlist = self._prepare_whitelist(self._whitelist.copy(), tickers)
+
+        # Generate the pairlist with first Pairlist Handler in the chain
+        pairlist = self._pairlist_handlers[0].gen_pairlist(self._whitelist, tickers)
+
+        # Process all Pairlist Handlers in the chain
+        for pairlist_handler in self._pairlist_handlers:
+            pairlist = pairlist_handler.filter_pairlist(pairlist, tickers)
+
+        # Validation against blacklist happens after the chain of Pairlist Handlers
+        # to ensure blacklist is respected.
+        pairlist = self.verify_blacklist(pairlist, logger.warning)
+
+        self._whitelist = pairlist
+
+    def _prepare_whitelist(self, pairlist: List[str], tickers) -> List[str]:
+        """
+        Prepare sanitized pairlist for Pairlist Handlers that use tickers data - remove
+        pairs that do not have ticker available
+        """
+        if self._tickers_needed:
+            # Copy list since we're modifying this list
+            for p in deepcopy(pairlist):
+                if p not in tickers:
+                    pairlist.remove(p)
+
+        return pairlist
+
+    def verify_blacklist(self, pairlist: List[str], logmethod) -> List[str]:
+        """
+        Verify and remove items from pairlist - returning a filtered pairlist.
+        Logs a warning or info depending on `aswarning`.
+        Pairlist Handlers explicitly using this method shall use
+        `logmethod=logger.info` to avoid spamming with warning messages
+        :param pairlist: Pairlist to validate
+        :param logmethod: Function that'll be called, `logger.info` or `logger.warning`.
+        :return: pairlist - blacklisted pairs
+        """
+        for pair in deepcopy(pairlist):
+            if pair in self._blacklist:
+                logmethod(f"Pair {pair} in your blacklist. Removing it from whitelist...")
+                pairlist.remove(pair)
+        return pairlist
+
+    def create_pair_list(self, pairs: List[str], timeframe: str = None) -> ListPairsWithTimeframes:
+        """
+        Create list of pair tuples with (pair, timeframe)
+        """
+        return [(pair, timeframe or self._config['timeframe']) for pair in pairs]
diff --git a/freqtrade/persistence.py b/freqtrade/persistence.py
deleted file mode 100644
index c844bbc4c..000000000
--- a/freqtrade/persistence.py
+++ /dev/null
@@ -1,443 +0,0 @@
-"""
-This module contains the class to persist trades into SQLite
-"""
-
-import logging
-from datetime import datetime
-from decimal import Decimal
-from typing import Any, Dict, List, Optional
-
-import arrow
-from sqlalchemy import (Boolean, Column, DateTime, Float, Integer, String,
-                        create_engine, inspect)
-from sqlalchemy.exc import NoSuchModuleError
-from sqlalchemy.ext.declarative import declarative_base
-from sqlalchemy.orm.scoping import scoped_session
-from sqlalchemy.orm.session import sessionmaker
-from sqlalchemy import func
-from sqlalchemy.pool import StaticPool
-
-from freqtrade import OperationalException
-
-logger = logging.getLogger(__name__)
-
-_DECL_BASE: Any = declarative_base()
-_SQL_DOCS_URL = 'http://docs.sqlalchemy.org/en/latest/core/engines.html#database-urls'
-
-
-def init(db_url: str, clean_open_orders: bool = False) -> None:
-    """
-    Initializes this module with the given config,
-    registers all known command handlers
-    and starts polling for message updates
-    :param db_url: Database to use
-    :param clean_open_orders: Remove open orders from the database.
-        Useful for dry-run or if all orders have been reset on the exchange.
-    :return: None
-    """
-    kwargs = {}
-
-    # Take care of thread ownership if in-memory db
-    if db_url == 'sqlite://':
-        kwargs.update({
-            'connect_args': {'check_same_thread': False},
-            'poolclass': StaticPool,
-            'echo': False,
-        })
-
-    try:
-        engine = create_engine(db_url, **kwargs)
-    except NoSuchModuleError:
-        raise OperationalException(f'Given value for db_url: \'{db_url}\' '
-                                   f'is no valid database URL! (See {_SQL_DOCS_URL})')
-
-    session = scoped_session(sessionmaker(bind=engine, autoflush=True, autocommit=True))
-    Trade.session = session()
-    Trade.query = session.query_property()
-    _DECL_BASE.metadata.create_all(engine)
-    check_migrate(engine)
-
-    # Clean dry_run DB if the db is not in-memory
-    if clean_open_orders and db_url != 'sqlite://':
-        clean_dry_run_db()
-
-
-def has_column(columns, searchname: str) -> bool:
-    return len(list(filter(lambda x: x["name"] == searchname, columns))) == 1
-
-
-def get_column_def(columns, column: str, default: str) -> str:
-    return default if not has_column(columns, column) else column
-
-
-def check_migrate(engine) -> None:
-    """
-    Checks if migration is necessary and migrates if necessary
-    """
-    inspector = inspect(engine)
-
-    cols = inspector.get_columns('trades')
-    tabs = inspector.get_table_names()
-    table_back_name = 'trades_bak'
-    for i, table_back_name in enumerate(tabs):
-        table_back_name = f'trades_bak{i}'
-        logger.debug(f'trying {table_back_name}')
-
-    # Check for latest column
-    if not has_column(cols, 'stop_loss_pct'):
-        logger.info(f'Running database migration - backup available as {table_back_name}')
-
-        fee_open = get_column_def(cols, 'fee_open', 'fee')
-        fee_close = get_column_def(cols, 'fee_close', 'fee')
-        open_rate_requested = get_column_def(cols, 'open_rate_requested', 'null')
-        close_rate_requested = get_column_def(cols, 'close_rate_requested', 'null')
-        stop_loss = get_column_def(cols, 'stop_loss', '0.0')
-        stop_loss_pct = get_column_def(cols, 'stop_loss_pct', 'null')
-        initial_stop_loss = get_column_def(cols, 'initial_stop_loss', '0.0')
-        initial_stop_loss_pct = get_column_def(cols, 'initial_stop_loss_pct', 'null')
-        stoploss_order_id = get_column_def(cols, 'stoploss_order_id', 'null')
-        stoploss_last_update = get_column_def(cols, 'stoploss_last_update', 'null')
-        max_rate = get_column_def(cols, 'max_rate', '0.0')
-        min_rate = get_column_def(cols, 'min_rate', 'null')
-        sell_reason = get_column_def(cols, 'sell_reason', 'null')
-        strategy = get_column_def(cols, 'strategy', 'null')
-        ticker_interval = get_column_def(cols, 'ticker_interval', 'null')
-
-        # Schema migration necessary
-        engine.execute(f"alter table trades rename to {table_back_name}")
-        # drop indexes on backup table
-        for index in inspector.get_indexes(table_back_name):
-            engine.execute(f"drop index {index['name']}")
-        # let SQLAlchemy create the schema as required
-        _DECL_BASE.metadata.create_all(engine)
-
-        # Copy data back - following the correct schema
-        engine.execute(f"""insert into trades
-                (id, exchange, pair, is_open, fee_open, fee_close, open_rate,
-                open_rate_requested, close_rate, close_rate_requested, close_profit,
-                stake_amount, amount, open_date, close_date, open_order_id,
-                stop_loss, stop_loss_pct, initial_stop_loss, initial_stop_loss_pct,
-                stoploss_order_id, stoploss_last_update,
-                max_rate, min_rate, sell_reason, strategy,
-                ticker_interval
-                )
-            select id, lower(exchange),
-                case
-                    when instr(pair, '_') != 0 then
-                    substr(pair,    instr(pair, '_') + 1) || '/' ||
-                    substr(pair, 1, instr(pair, '_') - 1)
-                    else pair
-                    end
-                pair,
-                is_open, {fee_open} fee_open, {fee_close} fee_close,
-                open_rate, {open_rate_requested} open_rate_requested, close_rate,
-                {close_rate_requested} close_rate_requested, close_profit,
-                stake_amount, amount, open_date, close_date, open_order_id,
-                {stop_loss} stop_loss, {stop_loss_pct} stop_loss_pct,
-                {initial_stop_loss} initial_stop_loss,
-                {initial_stop_loss_pct} initial_stop_loss_pct,
-                {stoploss_order_id} stoploss_order_id, {stoploss_last_update} stoploss_last_update,
-                {max_rate} max_rate, {min_rate} min_rate, {sell_reason} sell_reason,
-                {strategy} strategy, {ticker_interval} ticker_interval
-                from {table_back_name}
-             """)
-
-        # Reread columns - the above recreated the table!
-        inspector = inspect(engine)
-        cols = inspector.get_columns('trades')
-
-
-def cleanup() -> None:
-    """
-    Flushes all pending operations to disk.
-    :return: None
-    """
-    Trade.session.flush()
-
-
-def clean_dry_run_db() -> None:
-    """
-    Remove open_order_id from a Dry_run DB
-    :return: None
-    """
-    for trade in Trade.query.filter(Trade.open_order_id.isnot(None)).all():
-        # Check we are updating only a dry_run order not a prod one
-        if 'dry_run' in trade.open_order_id:
-            trade.open_order_id = None
-
-
-class Trade(_DECL_BASE):
-    """
-    Class used to define a trade structure
-    """
-    __tablename__ = 'trades'
-
-    id = Column(Integer, primary_key=True)
-    exchange = Column(String, nullable=False)
-    pair = Column(String, nullable=False, index=True)
-    is_open = Column(Boolean, nullable=False, default=True, index=True)
-    fee_open = Column(Float, nullable=False, default=0.0)
-    fee_close = Column(Float, nullable=False, default=0.0)
-    open_rate = Column(Float)
-    open_rate_requested = Column(Float)
-    close_rate = Column(Float)
-    close_rate_requested = Column(Float)
-    close_profit = Column(Float)
-    stake_amount = Column(Float, nullable=False)
-    amount = Column(Float)
-    open_date = Column(DateTime, nullable=False, default=datetime.utcnow)
-    close_date = Column(DateTime)
-    open_order_id = Column(String)
-    # absolute value of the stop loss
-    stop_loss = Column(Float, nullable=True, default=0.0)
-    # percentage value of the stop loss
-    stop_loss_pct = Column(Float, nullable=True)
-    # absolute value of the initial stop loss
-    initial_stop_loss = Column(Float, nullable=True, default=0.0)
-    # percentage value of the initial stop loss
-    initial_stop_loss_pct = Column(Float, nullable=True)
-    # stoploss order id which is on exchange
-    stoploss_order_id = Column(String, nullable=True, index=True)
-    # last update time of the stoploss order on exchange
-    stoploss_last_update = Column(DateTime, nullable=True)
-    # absolute value of the highest reached price
-    max_rate = Column(Float, nullable=True, default=0.0)
-    # Lowest price reached
-    min_rate = Column(Float, nullable=True)
-    sell_reason = Column(String, nullable=True)
-    strategy = Column(String, nullable=True)
-    ticker_interval = Column(Integer, nullable=True)
-
-    def __repr__(self):
-        open_since = arrow.get(self.open_date).humanize() if self.is_open else 'closed'
-
-        return (f'Trade(id={self.id}, pair={self.pair}, amount={self.amount:.8f}, '
-                f'open_rate={self.open_rate:.8f}, open_since={open_since})')
-
-    def to_json(self) -> Dict[str, Any]:
-        return {
-            'trade_id': self.id,
-            'pair': self.pair,
-            'open_date_hum': arrow.get(self.open_date).humanize(),
-            'open_date': self.open_date.strftime("%Y-%m-%d %H:%M:%S"),
-            'close_date_hum': (arrow.get(self.close_date).humanize()
-                               if self.close_date else None),
-            'close_date': (self.close_date.strftime("%Y-%m-%d %H:%M:%S")
-                           if self.close_date else None),
-            'open_rate': self.open_rate,
-            'close_rate': self.close_rate,
-            'amount': round(self.amount, 8),
-            'stake_amount': round(self.stake_amount, 8),
-            'stop_loss': self.stop_loss,
-            'stop_loss_pct': (self.stop_loss_pct * 100) if self.stop_loss_pct else None,
-            'initial_stop_loss': self.initial_stop_loss,
-            'initial_stop_loss_pct': (self.initial_stop_loss_pct * 100
-                                      if self.initial_stop_loss_pct else None),
-        }
-
-    def adjust_min_max_rates(self, current_price: float):
-        """
-        Adjust the max_rate and min_rate.
-        """
-        self.max_rate = max(current_price, self.max_rate or self.open_rate)
-        self.min_rate = min(current_price, self.min_rate or self.open_rate)
-
-    def adjust_stop_loss(self, current_price: float, stoploss: float, initial: bool = False):
-        """
-        This adjusts the stop loss to it's most recently observed setting
-        :param current_price: Current rate the asset is traded
-        :param stoploss: Stoploss as factor (sample -0.05 -> -5% below current price).
-        :param initial: Called to initiate stop_loss.
-            Skips everything if self.stop_loss is already set.
-        """
-
-        if initial and not (self.stop_loss is None or self.stop_loss == 0):
-            # Don't modify if called with initial and nothing to do
-            return
-
-        new_loss = float(current_price * (1 - abs(stoploss)))
-
-        # no stop loss assigned yet
-        if not self.stop_loss:
-            logger.debug("assigning new stop loss")
-            self.stop_loss = new_loss
-            self.stop_loss_pct = -1 * abs(stoploss)
-            self.initial_stop_loss = new_loss
-            self.initial_stop_loss_pct = -1 * abs(stoploss)
-            self.stoploss_last_update = datetime.utcnow()
-
-        # evaluate if the stop loss needs to be updated
-        else:
-            if new_loss > self.stop_loss:  # stop losses only walk up, never down!
-                self.stop_loss = new_loss
-                self.stop_loss_pct = -1 * abs(stoploss)
-                self.stoploss_last_update = datetime.utcnow()
-                logger.debug("adjusted stop loss")
-            else:
-                logger.debug("keeping current stop loss")
-
-        logger.debug(
-            f"{self.pair} - current price {current_price:.8f}, "
-            f"bought at {self.open_rate:.8f} and calculated "
-            f"stop loss is at: {self.initial_stop_loss:.8f} initial "
-            f"stop at {self.stop_loss:.8f}. "
-            f"trailing stop loss saved us: "
-            f"{float(self.stop_loss) - float(self.initial_stop_loss):.8f} "
-            f"and max observed rate was {self.max_rate:.8f}")
-
-    def update(self, order: Dict) -> None:
-        """
-        Updates this entity with amount and actual open/close rates.
-        :param order: order retrieved by exchange.get_order()
-        :return: None
-        """
-        order_type = order['type']
-        # Ignore open and cancelled orders
-        if order['status'] == 'open' or order['price'] is None:
-            return
-
-        logger.info('Updating trade (id=%s) ...', self.id)
-
-        if order_type in ('market', 'limit') and order['side'] == 'buy':
-            # Update open rate and actual amount
-            self.open_rate = Decimal(order['price'])
-            self.amount = Decimal(order['amount'])
-            logger.info('%s_BUY has been fulfilled for %s.', order_type.upper(), self)
-            self.open_order_id = None
-        elif order_type in ('market', 'limit') and order['side'] == 'sell':
-            self.close(order['price'])
-            logger.info('%s_SELL has been fulfilled for %s.', order_type.upper(), self)
-        elif order_type == 'stop_loss_limit':
-            self.stoploss_order_id = None
-            self.close_rate_requested = self.stop_loss
-            logger.info('STOP_LOSS_LIMIT is hit for %s.', self)
-            self.close(order['average'])
-        else:
-            raise ValueError(f'Unknown order type: {order_type}')
-        cleanup()
-
-    def close(self, rate: float) -> None:
-        """
-        Sets close_rate to the given rate, calculates total profit
-        and marks trade as closed
-        """
-        self.close_rate = Decimal(rate)
-        self.close_profit = self.calc_profit_percent()
-        self.close_date = datetime.utcnow()
-        self.is_open = False
-        self.open_order_id = None
-        logger.info(
-            'Marking %s as closed as the trade is fulfilled and found no open orders for it.',
-            self
-        )
-
-    def calc_open_trade_price(
-            self,
-            fee: Optional[float] = None) -> float:
-        """
-        Calculate the open_rate including fee.
-        :param fee: fee to use on the open rate (optional).
-        If rate is not set self.fee will be used
-        :return: Price in of the open trade incl. Fees
-        """
-
-        buy_trade = (Decimal(self.amount) * Decimal(self.open_rate))
-        fees = buy_trade * Decimal(fee or self.fee_open)
-        return float(buy_trade + fees)
-
-    def calc_close_trade_price(
-            self,
-            rate: Optional[float] = None,
-            fee: Optional[float] = None) -> float:
-        """
-        Calculate the close_rate including fee
-        :param fee: fee to use on the close rate (optional).
-        If rate is not set self.fee will be used
-        :param rate: rate to compare with (optional).
-        If rate is not set self.close_rate will be used
-        :return: Price in BTC of the open trade
-        """
-
-        if rate is None and not self.close_rate:
-            return 0.0
-
-        sell_trade = (Decimal(self.amount) * Decimal(rate or self.close_rate))
-        fees = sell_trade * Decimal(fee or self.fee_close)
-        return float(sell_trade - fees)
-
-    def calc_profit(
-            self,
-            rate: Optional[float] = None,
-            fee: Optional[float] = None) -> float:
-        """
-        Calculate the absolute profit in stake currency between Close and Open trade
-        :param fee: fee to use on the close rate (optional).
-        If rate is not set self.fee will be used
-        :param rate: close rate to compare with (optional).
-        If rate is not set self.close_rate will be used
-        :return:  profit in stake currency as float
-        """
-        open_trade_price = self.calc_open_trade_price()
-        close_trade_price = self.calc_close_trade_price(
-            rate=(rate or self.close_rate),
-            fee=(fee or self.fee_close)
-        )
-        profit = close_trade_price - open_trade_price
-        return float(f"{profit:.8f}")
-
-    def calc_profit_percent(
-            self,
-            rate: Optional[float] = None,
-            fee: Optional[float] = None) -> float:
-        """
-        Calculates the profit in percentage (including fee).
-        :param rate: rate to compare with (optional).
-        If rate is not set self.close_rate will be used
-        :param fee: fee to use on the close rate (optional).
-        :return: profit in percentage as float
-        """
-
-        open_trade_price = self.calc_open_trade_price()
-        close_trade_price = self.calc_close_trade_price(
-            rate=(rate or self.close_rate),
-            fee=(fee or self.fee_close)
-        )
-        profit_percent = (close_trade_price / open_trade_price) - 1
-        return float(f"{profit_percent:.8f}")
-
-    @staticmethod
-    def total_open_trades_stakes() -> float:
-        """
-        Calculates total invested amount in open trades
-        in stake currency
-        """
-        total_open_stake_amount = Trade.session.query(func.sum(Trade.stake_amount))\
-            .filter(Trade.is_open.is_(True))\
-            .scalar()
-        return total_open_stake_amount or 0
-
-    @staticmethod
-    def get_open_trades() -> List[Any]:
-        """
-        Query trades from persistence layer
-        """
-        return Trade.query.filter(Trade.is_open.is_(True)).all()
-
-    @staticmethod
-    def stoploss_reinitialization(desired_stoploss):
-        """
-        Adjust initial Stoploss to desired stoploss for all open trades.
-        """
-        for trade in Trade.get_open_trades():
-            logger.info("Found open trade: %s", trade)
-
-            # skip case if trailing-stop changed the stoploss already.
-            if (trade.stop_loss == trade.initial_stop_loss
-               and trade.initial_stop_loss_pct != desired_stoploss):
-                # Stoploss value got changed
-
-                logger.info(f"Stoploss for {trade} needs adjustment.")
-                # Force reset of stoploss
-                trade.stop_loss = None
-                trade.adjust_stop_loss(trade.open_rate, desired_stoploss)
-                logger.info(f"new stoploss: {trade.stop_loss}, ")
diff --git a/freqtrade/persistence/__init__.py b/freqtrade/persistence/__init__.py
new file mode 100644
index 000000000..35f2bc406
--- /dev/null
+++ b/freqtrade/persistence/__init__.py
@@ -0,0 +1,4 @@
+# flake8: noqa: F401
+
+from freqtrade.persistence.models import Order, Trade, clean_dry_run_db, cleanup_db, init_db
+from freqtrade.persistence.pairlock_middleware import PairLocks
diff --git a/freqtrade/persistence/migrations.py b/freqtrade/persistence/migrations.py
new file mode 100644
index 000000000..84f3ed7e6
--- /dev/null
+++ b/freqtrade/persistence/migrations.py
@@ -0,0 +1,150 @@
+import logging
+from typing import List
+
+from sqlalchemy import inspect
+
+
+logger = logging.getLogger(__name__)
+
+
+def get_table_names_for_table(inspector, tabletype):
+    return [t for t in inspector.get_table_names() if t.startswith(tabletype)]
+
+
+def has_column(columns: List, searchname: str) -> bool:
+    return len(list(filter(lambda x: x["name"] == searchname, columns))) == 1
+
+
+def get_column_def(columns: List, column: str, default: str) -> str:
+    return default if not has_column(columns, column) else column
+
+
+def get_backup_name(tabs, backup_prefix: str):
+    table_back_name = backup_prefix
+    for i, table_back_name in enumerate(tabs):
+        table_back_name = f'{backup_prefix}{i}'
+        logger.debug(f'trying {table_back_name}')
+
+    return table_back_name
+
+
+def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, cols: List):
+    fee_open = get_column_def(cols, 'fee_open', 'fee')
+    fee_open_cost = get_column_def(cols, 'fee_open_cost', 'null')
+    fee_open_currency = get_column_def(cols, 'fee_open_currency', 'null')
+    fee_close = get_column_def(cols, 'fee_close', 'fee')
+    fee_close_cost = get_column_def(cols, 'fee_close_cost', 'null')
+    fee_close_currency = get_column_def(cols, 'fee_close_currency', 'null')
+    open_rate_requested = get_column_def(cols, 'open_rate_requested', 'null')
+    close_rate_requested = get_column_def(cols, 'close_rate_requested', 'null')
+    stop_loss = get_column_def(cols, 'stop_loss', '0.0')
+    stop_loss_pct = get_column_def(cols, 'stop_loss_pct', 'null')
+    initial_stop_loss = get_column_def(cols, 'initial_stop_loss', '0.0')
+    initial_stop_loss_pct = get_column_def(cols, 'initial_stop_loss_pct', 'null')
+    stoploss_order_id = get_column_def(cols, 'stoploss_order_id', 'null')
+    stoploss_last_update = get_column_def(cols, 'stoploss_last_update', 'null')
+    max_rate = get_column_def(cols, 'max_rate', '0.0')
+    min_rate = get_column_def(cols, 'min_rate', 'null')
+    sell_reason = get_column_def(cols, 'sell_reason', 'null')
+    strategy = get_column_def(cols, 'strategy', 'null')
+    # If ticker-interval existed use that, else null.
+    if has_column(cols, 'ticker_interval'):
+        timeframe = get_column_def(cols, 'timeframe', 'ticker_interval')
+    else:
+        timeframe = get_column_def(cols, 'timeframe', 'null')
+
+    open_trade_price = get_column_def(cols, 'open_trade_price',
+                                      f'amount * open_rate * (1 + {fee_open})')
+    close_profit_abs = get_column_def(
+        cols, 'close_profit_abs',
+        f"(amount * close_rate * (1 - {fee_close})) - {open_trade_price}")
+    sell_order_status = get_column_def(cols, 'sell_order_status', 'null')
+    amount_requested = get_column_def(cols, 'amount_requested', 'amount')
+
+    # Schema migration necessary
+    engine.execute(f"alter table trades rename to {table_back_name}")
+    # drop indexes on backup table
+    for index in inspector.get_indexes(table_back_name):
+        engine.execute(f"drop index {index['name']}")
+    # let SQLAlchemy create the schema as required
+    decl_base.metadata.create_all(engine)
+
+    # Copy data back - following the correct schema
+    engine.execute(f"""insert into trades
+            (id, exchange, pair, is_open,
+            fee_open, fee_open_cost, fee_open_currency,
+            fee_close, fee_close_cost, fee_open_currency, open_rate,
+            open_rate_requested, close_rate, close_rate_requested, close_profit,
+            stake_amount, amount, amount_requested, open_date, close_date, open_order_id,
+            stop_loss, stop_loss_pct, initial_stop_loss, initial_stop_loss_pct,
+            stoploss_order_id, stoploss_last_update,
+            max_rate, min_rate, sell_reason, sell_order_status, strategy,
+            timeframe, open_trade_price, close_profit_abs
+            )
+        select id, lower(exchange),
+            case
+                when instr(pair, '_') != 0 then
+                substr(pair,    instr(pair, '_') + 1) || '/' ||
+                substr(pair, 1, instr(pair, '_') - 1)
+                else pair
+                end
+            pair,
+            is_open, {fee_open} fee_open, {fee_open_cost} fee_open_cost,
+            {fee_open_currency} fee_open_currency, {fee_close} fee_close,
+            {fee_close_cost} fee_close_cost, {fee_close_currency} fee_close_currency,
+            open_rate, {open_rate_requested} open_rate_requested, close_rate,
+            {close_rate_requested} close_rate_requested, close_profit,
+            stake_amount, amount, {amount_requested}, open_date, close_date, open_order_id,
+            {stop_loss} stop_loss, {stop_loss_pct} stop_loss_pct,
+            {initial_stop_loss} initial_stop_loss,
+            {initial_stop_loss_pct} initial_stop_loss_pct,
+            {stoploss_order_id} stoploss_order_id, {stoploss_last_update} stoploss_last_update,
+            {max_rate} max_rate, {min_rate} min_rate, {sell_reason} sell_reason,
+            {sell_order_status} sell_order_status,
+            {strategy} strategy, {timeframe} timeframe,
+            {open_trade_price} open_trade_price, {close_profit_abs} close_profit_abs
+            from {table_back_name}
+            """)
+
+
+def migrate_open_orders_to_trades(engine):
+    engine.execute("""
+        insert into orders (ft_trade_id, ft_pair, order_id, ft_order_side, ft_is_open)
+        select id ft_trade_id, pair ft_pair, open_order_id,
+            case when close_rate_requested is null then 'buy'
+            else 'sell' end ft_order_side, 1 ft_is_open
+        from trades
+        where open_order_id is not null
+        union all
+        select id ft_trade_id, pair ft_pair, stoploss_order_id order_id,
+            'stoploss' ft_order_side, 1 ft_is_open
+        from trades
+        where stoploss_order_id is not null
+        """)
+
+
+def check_migrate(engine, decl_base, previous_tables) -> None:
+    """
+    Checks if migration is necessary and migrates if necessary
+    """
+    inspector = inspect(engine)
+
+    cols = inspector.get_columns('trades')
+    tabs = get_table_names_for_table(inspector, 'trades')
+    table_back_name = get_backup_name(tabs, 'trades_bak')
+
+    # Check for latest column
+    if not has_column(cols, 'amount_requested'):
+        logger.info(f'Running database migration for trades - backup: {table_back_name}')
+        migrate_trades_table(decl_base, inspector, engine, table_back_name, cols)
+        # Reread columns - the above recreated the table!
+        inspector = inspect(engine)
+        cols = inspector.get_columns('trades')
+
+    if 'orders' not in previous_tables:
+        logger.info('Moving open orders to Orders table.')
+        migrate_open_orders_to_trades(engine)
+    else:
+        pass
+        # Empty for now - as there is only one iteration of the orders table so far.
+        # table_back_name = get_backup_name(tabs, 'orders_bak')
diff --git a/freqtrade/persistence/models.py b/freqtrade/persistence/models.py
new file mode 100644
index 000000000..8160ffbbf
--- /dev/null
+++ b/freqtrade/persistence/models.py
@@ -0,0 +1,715 @@
+"""
+This module contains the class to persist trades into SQLite
+"""
+import logging
+from datetime import datetime, timezone
+from decimal import Decimal
+from typing import Any, Dict, List, Optional
+
+import arrow
+from sqlalchemy import (Boolean, Column, DateTime, Float, ForeignKey, Integer, String,
+                        create_engine, desc, func, inspect)
+from sqlalchemy.exc import NoSuchModuleError
+from sqlalchemy.ext.declarative import declarative_base
+from sqlalchemy.orm import Query, relationship
+from sqlalchemy.orm.scoping import scoped_session
+from sqlalchemy.orm.session import sessionmaker
+from sqlalchemy.pool import StaticPool
+from sqlalchemy.sql.schema import UniqueConstraint
+
+from freqtrade.constants import DATETIME_PRINT_FORMAT
+from freqtrade.exceptions import DependencyException, OperationalException
+from freqtrade.misc import safe_value_fallback
+from freqtrade.persistence.migrations import check_migrate
+
+
+logger = logging.getLogger(__name__)
+
+
+_DECL_BASE: Any = declarative_base()
+_SQL_DOCS_URL = 'http://docs.sqlalchemy.org/en/latest/core/engines.html#database-urls'
+
+
+def init_db(db_url: str, clean_open_orders: bool = False) -> None:
+    """
+    Initializes this module with the given config,
+    registers all known command handlers
+    and starts polling for message updates
+    :param db_url: Database to use
+    :param clean_open_orders: Remove open orders from the database.
+        Useful for dry-run or if all orders have been reset on the exchange.
+    :return: None
+    """
+    kwargs = {}
+
+    # Take care of thread ownership if in-memory db
+    if db_url == 'sqlite://':
+        kwargs.update({
+            'connect_args': {'check_same_thread': False},
+            'poolclass': StaticPool,
+            'echo': False,
+        })
+
+    try:
+        engine = create_engine(db_url, **kwargs)
+    except NoSuchModuleError:
+        raise OperationalException(f"Given value for db_url: '{db_url}' "
+                                   f"is no valid database URL! (See {_SQL_DOCS_URL})")
+
+    # https://docs.sqlalchemy.org/en/13/orm/contextual.html#thread-local-scope
+    # Scoped sessions proxy requests to the appropriate thread-local session.
+    # We should use the scoped_session object - not a seperately initialized version
+    Trade.session = scoped_session(sessionmaker(bind=engine, autoflush=True, autocommit=True))
+    Trade.query = Trade.session.query_property()
+    # Copy session attributes to order object too
+    Order.session = Trade.session
+    Order.query = Order.session.query_property()
+    PairLock.session = Trade.session
+    PairLock.query = PairLock.session.query_property()
+
+    previous_tables = inspect(engine).get_table_names()
+    _DECL_BASE.metadata.create_all(engine)
+    check_migrate(engine, decl_base=_DECL_BASE, previous_tables=previous_tables)
+
+    # Clean dry_run DB if the db is not in-memory
+    if clean_open_orders and db_url != 'sqlite://':
+        clean_dry_run_db()
+
+
+def cleanup_db() -> None:
+    """
+    Flushes all pending operations to disk.
+    :return: None
+    """
+    Trade.session.flush()
+
+
+def clean_dry_run_db() -> None:
+    """
+    Remove open_order_id from a Dry_run DB
+    :return: None
+    """
+    for trade in Trade.query.filter(Trade.open_order_id.isnot(None)).all():
+        # Check we are updating only a dry_run order not a prod one
+        if 'dry_run' in trade.open_order_id:
+            trade.open_order_id = None
+
+
+class Order(_DECL_BASE):
+    """
+    Order database model
+    Keeps a record of all orders placed on the exchange
+
+    One to many relationship with Trades:
+      - One trade can have many orders
+      - One Order can only be associated with one Trade
+
+    Mirrors CCXT Order structure
+    """
+    __tablename__ = 'orders'
+    # Uniqueness should be ensured over pair, order_id
+    # its likely that order_id is unique per Pair on some exchanges.
+    __table_args__ = (UniqueConstraint('ft_pair', 'order_id', name="_order_pair_order_id"),)
+
+    id = Column(Integer, primary_key=True)
+    ft_trade_id = Column(Integer, ForeignKey('trades.id'), index=True)
+
+    trade = relationship("Trade", back_populates="orders")
+
+    ft_order_side = Column(String, nullable=False)
+    ft_pair = Column(String, nullable=False)
+    ft_is_open = Column(Boolean, nullable=False, default=True, index=True)
+
+    order_id = Column(String, nullable=False, index=True)
+    status = Column(String, nullable=True)
+    symbol = Column(String, nullable=True)
+    order_type = Column(String, nullable=True)
+    side = Column(String, nullable=True)
+    price = Column(Float, nullable=True)
+    amount = Column(Float, nullable=True)
+    filled = Column(Float, nullable=True)
+    remaining = Column(Float, nullable=True)
+    cost = Column(Float, nullable=True)
+    order_date = Column(DateTime, nullable=True, default=datetime.utcnow)
+    order_filled_date = Column(DateTime, nullable=True)
+    order_update_date = Column(DateTime, nullable=True)
+
+    def __repr__(self):
+
+        return (f'Order(id={self.id}, order_id={self.order_id}, trade_id={self.ft_trade_id}, '
+                f'side={self.side}, order_type={self.order_type}, status={self.status})')
+
+    def update_from_ccxt_object(self, order):
+        """
+        Update Order from ccxt response
+        Only updates if fields are available from ccxt -
+        """
+        if self.order_id != str(order['id']):
+            raise DependencyException("Order-id's don't match")
+
+        self.status = order.get('status', self.status)
+        self.symbol = order.get('symbol', self.symbol)
+        self.order_type = order.get('type', self.order_type)
+        self.side = order.get('side', self.side)
+        self.price = order.get('price', self.price)
+        self.amount = order.get('amount', self.amount)
+        self.filled = order.get('filled', self.filled)
+        self.remaining = order.get('remaining', self.remaining)
+        self.cost = order.get('cost', self.cost)
+        if 'timestamp' in order and order['timestamp'] is not None:
+            self.order_date = datetime.fromtimestamp(order['timestamp'] / 1000, tz=timezone.utc)
+
+        self.ft_is_open = True
+        if self.status in ('closed', 'canceled', 'cancelled'):
+            self.ft_is_open = False
+            if order.get('filled', 0) > 0:
+                self.order_filled_date = arrow.utcnow().datetime
+        self.order_update_date = arrow.utcnow().datetime
+
+    @staticmethod
+    def update_orders(orders: List['Order'], order: Dict[str, Any]):
+        """
+        Get all non-closed orders - useful when trying to batch-update orders
+        """
+        filtered_orders = [o for o in orders if o.order_id == order.get('id')]
+        if filtered_orders:
+            oobj = filtered_orders[0]
+            oobj.update_from_ccxt_object(order)
+        else:
+            logger.warning(f"Did not find order for {order}.")
+
+    @staticmethod
+    def parse_from_ccxt_object(order: Dict[str, Any], pair: str, side: str) -> 'Order':
+        """
+        Parse an order from a ccxt object and return a new order Object.
+        """
+        o = Order(order_id=str(order['id']), ft_order_side=side, ft_pair=pair)
+
+        o.update_from_ccxt_object(order)
+        return o
+
+    @staticmethod
+    def get_open_orders() -> List['Order']:
+        """
+        """
+        return Order.query.filter(Order.ft_is_open.is_(True)).all()
+
+
+class Trade(_DECL_BASE):
+    """
+    Trade database model.
+    Also handles updating and querying trades
+    """
+    __tablename__ = 'trades'
+
+    id = Column(Integer, primary_key=True)
+
+    orders = relationship("Order", order_by="Order.id", cascade="all, delete-orphan")
+
+    exchange = Column(String, nullable=False)
+    pair = Column(String, nullable=False, index=True)
+    is_open = Column(Boolean, nullable=False, default=True, index=True)
+    fee_open = Column(Float, nullable=False, default=0.0)
+    fee_open_cost = Column(Float, nullable=True)
+    fee_open_currency = Column(String, nullable=True)
+    fee_close = Column(Float, nullable=False, default=0.0)
+    fee_close_cost = Column(Float, nullable=True)
+    fee_close_currency = Column(String, nullable=True)
+    open_rate = Column(Float)
+    open_rate_requested = Column(Float)
+    # open_trade_price - calculated via _calc_open_trade_price
+    open_trade_price = Column(Float)
+    close_rate = Column(Float)
+    close_rate_requested = Column(Float)
+    close_profit = Column(Float)
+    close_profit_abs = Column(Float)
+    stake_amount = Column(Float, nullable=False)
+    amount = Column(Float)
+    amount_requested = Column(Float)
+    open_date = Column(DateTime, nullable=False, default=datetime.utcnow)
+    close_date = Column(DateTime)
+    open_order_id = Column(String)
+    # absolute value of the stop loss
+    stop_loss = Column(Float, nullable=True, default=0.0)
+    # percentage value of the stop loss
+    stop_loss_pct = Column(Float, nullable=True)
+    # absolute value of the initial stop loss
+    initial_stop_loss = Column(Float, nullable=True, default=0.0)
+    # percentage value of the initial stop loss
+    initial_stop_loss_pct = Column(Float, nullable=True)
+    # stoploss order id which is on exchange
+    stoploss_order_id = Column(String, nullable=True, index=True)
+    # last update time of the stoploss order on exchange
+    stoploss_last_update = Column(DateTime, nullable=True)
+    # absolute value of the highest reached price
+    max_rate = Column(Float, nullable=True, default=0.0)
+    # Lowest price reached
+    min_rate = Column(Float, nullable=True)
+    sell_reason = Column(String, nullable=True)
+    sell_order_status = Column(String, nullable=True)
+    strategy = Column(String, nullable=True)
+    timeframe = Column(Integer, nullable=True)
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.recalc_open_trade_price()
+
+    def __repr__(self):
+        open_since = self.open_date.strftime(DATETIME_PRINT_FORMAT) if self.is_open else 'closed'
+
+        return (f'Trade(id={self.id}, pair={self.pair}, amount={self.amount:.8f}, '
+                f'open_rate={self.open_rate:.8f}, open_since={open_since})')
+
+    def to_json(self) -> Dict[str, Any]:
+        return {
+            'trade_id': self.id,
+            'pair': self.pair,
+            'is_open': self.is_open,
+            'exchange': self.exchange,
+            'amount': round(self.amount, 8),
+            'amount_requested': round(self.amount_requested, 8) if self.amount_requested else None,
+            'stake_amount': round(self.stake_amount, 8),
+            'strategy': self.strategy,
+            'timeframe': self.timeframe,
+
+            'fee_open': self.fee_open,
+            'fee_open_cost': self.fee_open_cost,
+            'fee_open_currency': self.fee_open_currency,
+            'fee_close': self.fee_close,
+            'fee_close_cost': self.fee_close_cost,
+            'fee_close_currency': self.fee_close_currency,
+
+            'open_date_hum': arrow.get(self.open_date).humanize(),
+            'open_date': self.open_date.strftime(DATETIME_PRINT_FORMAT),
+            'open_timestamp': int(self.open_date.replace(tzinfo=timezone.utc).timestamp() * 1000),
+            'open_rate': self.open_rate,
+            'open_rate_requested': self.open_rate_requested,
+            'open_trade_price': round(self.open_trade_price, 8),
+
+            'close_date_hum': (arrow.get(self.close_date).humanize()
+                               if self.close_date else None),
+            'close_date': (self.close_date.strftime(DATETIME_PRINT_FORMAT)
+                           if self.close_date else None),
+            'close_timestamp': int(self.close_date.replace(
+                tzinfo=timezone.utc).timestamp() * 1000) if self.close_date else None,
+            'close_rate': self.close_rate,
+            'close_rate_requested': self.close_rate_requested,
+            'close_profit': self.close_profit,  # Deprecated
+            'close_profit_pct': round(self.close_profit * 100, 2) if self.close_profit else None,
+            'close_profit_abs': self.close_profit_abs,  # Deprecated
+
+            'profit_ratio': self.close_profit,
+            'profit_pct': round(self.close_profit * 100, 2) if self.close_profit else None,
+            'profit_abs': self.close_profit_abs,
+
+            'sell_reason': self.sell_reason,
+            'sell_order_status': self.sell_order_status,
+            'stop_loss_abs': self.stop_loss,
+            'stop_loss_ratio': self.stop_loss_pct if self.stop_loss_pct else None,
+            'stop_loss_pct': (self.stop_loss_pct * 100) if self.stop_loss_pct else None,
+            'stoploss_order_id': self.stoploss_order_id,
+            'stoploss_last_update': (self.stoploss_last_update.strftime(DATETIME_PRINT_FORMAT)
+                                     if self.stoploss_last_update else None),
+            'stoploss_last_update_timestamp': int(self.stoploss_last_update.replace(
+                tzinfo=timezone.utc).timestamp() * 1000) if self.stoploss_last_update else None,
+            'initial_stop_loss_abs': self.initial_stop_loss,
+            'initial_stop_loss_ratio': (self.initial_stop_loss_pct
+                                        if self.initial_stop_loss_pct else None),
+            'initial_stop_loss_pct': (self.initial_stop_loss_pct * 100
+                                      if self.initial_stop_loss_pct else None),
+            'min_rate': self.min_rate,
+            'max_rate': self.max_rate,
+
+            'open_order_id': self.open_order_id,
+        }
+
+    def adjust_min_max_rates(self, current_price: float) -> None:
+        """
+        Adjust the max_rate and min_rate.
+        """
+        self.max_rate = max(current_price, self.max_rate or self.open_rate)
+        self.min_rate = min(current_price, self.min_rate or self.open_rate)
+
+    def adjust_stop_loss(self, current_price: float, stoploss: float,
+                         initial: bool = False) -> None:
+        """
+        This adjusts the stop loss to it's most recently observed setting
+        :param current_price: Current rate the asset is traded
+        :param stoploss: Stoploss as factor (sample -0.05 -> -5% below current price).
+        :param initial: Called to initiate stop_loss.
+            Skips everything if self.stop_loss is already set.
+        """
+        if initial and not (self.stop_loss is None or self.stop_loss == 0):
+            # Don't modify if called with initial and nothing to do
+            return
+
+        new_loss = float(current_price * (1 - abs(stoploss)))
+
+        # no stop loss assigned yet
+        if not self.stop_loss:
+            logger.debug(f"{self.pair} - Assigning new stoploss...")
+            self.stop_loss = new_loss
+            self.stop_loss_pct = -1 * abs(stoploss)
+            self.initial_stop_loss = new_loss
+            self.initial_stop_loss_pct = -1 * abs(stoploss)
+            self.stoploss_last_update = datetime.utcnow()
+
+        # evaluate if the stop loss needs to be updated
+        else:
+            if new_loss > self.stop_loss:  # stop losses only walk up, never down!
+                logger.debug(f"{self.pair} - Adjusting stoploss...")
+                self.stop_loss = new_loss
+                self.stop_loss_pct = -1 * abs(stoploss)
+                self.stoploss_last_update = datetime.utcnow()
+            else:
+                logger.debug(f"{self.pair} - Keeping current stoploss...")
+
+        logger.debug(
+            f"{self.pair} - Stoploss adjusted. current_price={current_price:.8f}, "
+            f"open_rate={self.open_rate:.8f}, max_rate={self.max_rate:.8f}, "
+            f"initial_stop_loss={self.initial_stop_loss:.8f}, "
+            f"stop_loss={self.stop_loss:.8f}. "
+            f"Trailing stoploss saved us: "
+            f"{float(self.stop_loss) - float(self.initial_stop_loss):.8f}.")
+
+    def update(self, order: Dict) -> None:
+        """
+        Updates this entity with amount and actual open/close rates.
+        :param order: order retrieved by exchange.fetch_order()
+        :return: None
+        """
+        order_type = order['type']
+        # Ignore open and cancelled orders
+        if order['status'] == 'open' or safe_value_fallback(order, 'average', 'price') is None:
+            return
+
+        logger.info('Updating trade (id=%s) ...', self.id)
+
+        if order_type in ('market', 'limit') and order['side'] == 'buy':
+            # Update open rate and actual amount
+            self.open_rate = Decimal(safe_value_fallback(order, 'average', 'price'))
+            self.amount = Decimal(safe_value_fallback(order, 'filled', 'amount'))
+            self.recalc_open_trade_price()
+            if self.is_open:
+                logger.info(f'{order_type.upper()}_BUY has been fulfilled for {self}.')
+            self.open_order_id = None
+        elif order_type in ('market', 'limit') and order['side'] == 'sell':
+            if self.is_open:
+                logger.info(f'{order_type.upper()}_SELL has been fulfilled for {self}.')
+            self.close(safe_value_fallback(order, 'average', 'price'))
+        elif order_type in ('stop_loss_limit', 'stop-loss', 'stop'):
+            self.stoploss_order_id = None
+            self.close_rate_requested = self.stop_loss
+            if self.is_open:
+                logger.info(f'{order_type.upper()} is hit for {self}.')
+            self.close(order['average'])
+        else:
+            raise ValueError(f'Unknown order type: {order_type}')
+        cleanup_db()
+
+    def close(self, rate: float) -> None:
+        """
+        Sets close_rate to the given rate, calculates total profit
+        and marks trade as closed
+        """
+        self.close_rate = Decimal(rate)
+        self.close_profit = self.calc_profit_ratio()
+        self.close_profit_abs = self.calc_profit()
+        self.close_date = self.close_date or datetime.utcnow()
+        self.is_open = False
+        self.sell_order_status = 'closed'
+        self.open_order_id = None
+        logger.info(
+            'Marking %s as closed as the trade is fulfilled and found no open orders for it.',
+            self
+        )
+
+    def update_fee(self, fee_cost: float, fee_currency: Optional[str], fee_rate: Optional[float],
+                   side: str) -> None:
+        """
+        Update Fee parameters. Only acts once per side
+        """
+        if side == 'buy' and self.fee_open_currency is None:
+            self.fee_open_cost = fee_cost
+            self.fee_open_currency = fee_currency
+            if fee_rate is not None:
+                self.fee_open = fee_rate
+                # Assume close-fee will fall into the same fee category and take an educated guess
+                self.fee_close = fee_rate
+        elif side == 'sell' and self.fee_close_currency is None:
+            self.fee_close_cost = fee_cost
+            self.fee_close_currency = fee_currency
+            if fee_rate is not None:
+                self.fee_close = fee_rate
+
+    def fee_updated(self, side: str) -> bool:
+        """
+        Verify if this side (buy / sell) has already been updated
+        """
+        if side == 'buy':
+            return self.fee_open_currency is not None
+        elif side == 'sell':
+            return self.fee_close_currency is not None
+        else:
+            return False
+
+    def update_order(self, order: Dict) -> None:
+        Order.update_orders(self.orders, order)
+
+    def delete(self) -> None:
+
+        for order in self.orders:
+            Order.session.delete(order)
+
+        Trade.session.delete(self)
+        Trade.session.flush()
+
+    def _calc_open_trade_price(self) -> float:
+        """
+        Calculate the open_rate including open_fee.
+        :return: Price in of the open trade incl. Fees
+        """
+        buy_trade = Decimal(self.amount) * Decimal(self.open_rate)
+        fees = buy_trade * Decimal(self.fee_open)
+        return float(buy_trade + fees)
+
+    def recalc_open_trade_price(self) -> None:
+        """
+        Recalculate open_trade_price.
+        Must be called whenever open_rate or fee_open is changed.
+        """
+        self.open_trade_price = self._calc_open_trade_price()
+
+    def calc_close_trade_price(self, rate: Optional[float] = None,
+                               fee: Optional[float] = None) -> float:
+        """
+        Calculate the close_rate including fee
+        :param fee: fee to use on the close rate (optional).
+            If rate is not set self.fee will be used
+        :param rate: rate to compare with (optional).
+            If rate is not set self.close_rate will be used
+        :return: Price in BTC of the open trade
+        """
+        if rate is None and not self.close_rate:
+            return 0.0
+
+        sell_trade = Decimal(self.amount) * Decimal(rate or self.close_rate)
+        fees = sell_trade * Decimal(fee or self.fee_close)
+        return float(sell_trade - fees)
+
+    def calc_profit(self, rate: Optional[float] = None,
+                    fee: Optional[float] = None) -> float:
+        """
+        Calculate the absolute profit in stake currency between Close and Open trade
+        :param fee: fee to use on the close rate (optional).
+            If rate is not set self.fee will be used
+        :param rate: close rate to compare with (optional).
+            If rate is not set self.close_rate will be used
+        :return:  profit in stake currency as float
+        """
+        close_trade_price = self.calc_close_trade_price(
+            rate=(rate or self.close_rate),
+            fee=(fee or self.fee_close)
+        )
+        profit = close_trade_price - self.open_trade_price
+        return float(f"{profit:.8f}")
+
+    def calc_profit_ratio(self, rate: Optional[float] = None,
+                          fee: Optional[float] = None) -> float:
+        """
+        Calculates the profit as ratio (including fee).
+        :param rate: rate to compare with (optional).
+            If rate is not set self.close_rate will be used
+        :param fee: fee to use on the close rate (optional).
+        :return: profit ratio as float
+        """
+        close_trade_price = self.calc_close_trade_price(
+            rate=(rate or self.close_rate),
+            fee=(fee or self.fee_close)
+        )
+        profit_ratio = (close_trade_price / self.open_trade_price) - 1
+        return float(f"{profit_ratio:.8f}")
+
+    def select_order(self, order_side: str, is_open: Optional[bool]) -> Optional[Order]:
+        """
+        Finds latest order for this orderside and status
+        :param order_side: Side of the order (either 'buy' or 'sell')
+        :param is_open: Only search for open orders?
+        :return: latest Order object if it exists, else None
+        """
+        orders = [o for o in self.orders if o.side == order_side]
+        if is_open is not None:
+            orders = [o for o in orders if o.ft_is_open == is_open]
+        if len(orders) > 0:
+            return orders[-1]
+        else:
+            return None
+
+    @staticmethod
+    def get_trades(trade_filter=None) -> Query:
+        """
+        Helper function to query Trades using filters.
+        :param trade_filter: Optional filter to apply to trades
+                             Can be either a Filter object, or a List of filters
+                             e.g. `(trade_filter=[Trade.id == trade_id, Trade.is_open.is_(True),])`
+                             e.g. `(trade_filter=Trade.id == trade_id)`
+        :return: unsorted query object
+        """
+        if trade_filter is not None:
+            if not isinstance(trade_filter, list):
+                trade_filter = [trade_filter]
+            return Trade.query.filter(*trade_filter)
+        else:
+            return Trade.query
+
+    @staticmethod
+    def get_open_trades() -> List[Any]:
+        """
+        Query trades from persistence layer
+        """
+        return Trade.get_trades(Trade.is_open.is_(True)).all()
+
+    @staticmethod
+    def get_open_order_trades():
+        """
+        Returns all open trades
+        """
+        return Trade.get_trades(Trade.open_order_id.isnot(None)).all()
+
+    @staticmethod
+    def get_open_trades_without_assigned_fees():
+        """
+        Returns all open trades which don't have open fees set correctly
+        """
+        return Trade.get_trades([Trade.fee_open_currency.is_(None),
+                                 Trade.orders.any(),
+                                 Trade.is_open.is_(True),
+                                 ]).all()
+
+    @staticmethod
+    def get_sold_trades_without_assigned_fees():
+        """
+        Returns all closed trades which don't have fees set correctly
+        """
+        return Trade.get_trades([Trade.fee_close_currency.is_(None),
+                                 Trade.orders.any(),
+                                 Trade.is_open.is_(False),
+                                 ]).all()
+
+    @staticmethod
+    def total_open_trades_stakes() -> float:
+        """
+        Calculates total invested amount in open trades
+        in stake currency
+        """
+        total_open_stake_amount = Trade.session.query(func.sum(Trade.stake_amount))\
+            .filter(Trade.is_open.is_(True))\
+            .scalar()
+        return total_open_stake_amount or 0
+
+    @staticmethod
+    def get_overall_performance() -> List[Dict[str, Any]]:
+        """
+        Returns List of dicts containing all Trades, including profit and trade count
+        """
+        pair_rates = Trade.session.query(
+            Trade.pair,
+            func.sum(Trade.close_profit).label('profit_sum'),
+            func.count(Trade.pair).label('count')
+        ).filter(Trade.is_open.is_(False))\
+            .group_by(Trade.pair) \
+            .order_by(desc('profit_sum')) \
+            .all()
+        return [
+            {
+                'pair': pair,
+                'profit': rate,
+                'count': count
+            }
+            for pair, rate, count in pair_rates
+        ]
+
+    @staticmethod
+    def get_best_pair():
+        """
+        Get best pair with closed trade.
+        :returns: Tuple containing (pair, profit_sum)
+        """
+        best_pair = Trade.session.query(
+            Trade.pair, func.sum(Trade.close_profit).label('profit_sum')
+        ).filter(Trade.is_open.is_(False)) \
+            .group_by(Trade.pair) \
+            .order_by(desc('profit_sum')).first()
+        return best_pair
+
+    @staticmethod
+    def stoploss_reinitialization(desired_stoploss):
+        """
+        Adjust initial Stoploss to desired stoploss for all open trades.
+        """
+        for trade in Trade.get_open_trades():
+            logger.info("Found open trade: %s", trade)
+
+            # skip case if trailing-stop changed the stoploss already.
+            if (trade.stop_loss == trade.initial_stop_loss
+               and trade.initial_stop_loss_pct != desired_stoploss):
+                # Stoploss value got changed
+
+                logger.info(f"Stoploss for {trade} needs adjustment...")
+                # Force reset of stoploss
+                trade.stop_loss = None
+                trade.adjust_stop_loss(trade.open_rate, desired_stoploss)
+                logger.info(f"New stoploss: {trade.stop_loss}.")
+
+
+class PairLock(_DECL_BASE):
+    """
+    Pair Locks database model.
+    """
+    __tablename__ = 'pairlocks'
+
+    id = Column(Integer, primary_key=True)
+
+    pair = Column(String, nullable=False, index=True)
+    reason = Column(String, nullable=True)
+    # Time the pair was locked (start time)
+    lock_time = Column(DateTime, nullable=False)
+    # Time until the pair is locked (end time)
+    lock_end_time = Column(DateTime, nullable=False, index=True)
+
+    active = Column(Boolean, nullable=False, default=True, index=True)
+
+    def __repr__(self):
+        lock_time = self.lock_time.strftime(DATETIME_PRINT_FORMAT)
+        lock_end_time = self.lock_end_time.strftime(DATETIME_PRINT_FORMAT)
+        return (f'PairLock(id={self.id}, pair={self.pair}, lock_time={lock_time}, '
+                f'lock_end_time={lock_end_time})')
+
+    @staticmethod
+    def query_pair_locks(pair: Optional[str], now: datetime) -> Query:
+        """
+        Get all locks for this pair
+        :param pair: Pair to check for. Returns all current locks if pair is empty
+        :param now: Datetime object (generated via datetime.now(timezone.utc)).
+        """
+
+        filters = [PairLock.lock_end_time > now,
+                   # Only active locks
+                   PairLock.active.is_(True), ]
+        if pair:
+            filters.append(PairLock.pair == pair)
+        return PairLock.query.filter(
+            *filters
+        )
+
+    def to_json(self) -> Dict[str, Any]:
+        return {
+            'pair': self.pair,
+            'lock_time': self.lock_time.strftime(DATETIME_PRINT_FORMAT),
+            'lock_timestamp': int(self.lock_time.replace(tzinfo=timezone.utc).timestamp() * 1000),
+            'lock_end_time': self.lock_end_time.strftime(DATETIME_PRINT_FORMAT),
+            'lock_end_timestamp': int(self.lock_end_time.replace(tzinfo=timezone.utc
+                                                                 ).timestamp() * 1000),
+            'reason': self.reason,
+            'active': self.active,
+        }
diff --git a/freqtrade/persistence/pairlock_middleware.py b/freqtrade/persistence/pairlock_middleware.py
new file mode 100644
index 000000000..44fc228f6
--- /dev/null
+++ b/freqtrade/persistence/pairlock_middleware.py
@@ -0,0 +1,99 @@
+import logging
+from datetime import datetime, timezone
+from typing import List, Optional
+
+from freqtrade.exchange import timeframe_to_next_date
+from freqtrade.persistence.models import PairLock
+
+
+logger = logging.getLogger(__name__)
+
+
+class PairLocks():
+    """
+    Pairlocks middleware class
+    Abstracts the database layer away so it becomes optional - which will be necessary to support
+    backtesting and hyperopt in the future.
+    """
+
+    use_db = True
+    locks: List[PairLock] = []
+
+    timeframe: str = ''
+
+    @staticmethod
+    def lock_pair(pair: str, until: datetime, reason: str = None) -> None:
+        lock = PairLock(
+            pair=pair,
+            lock_time=datetime.now(timezone.utc),
+            lock_end_time=timeframe_to_next_date(PairLocks.timeframe, until),
+            reason=reason,
+            active=True
+        )
+        if PairLocks.use_db:
+            PairLock.session.add(lock)
+            PairLock.session.flush()
+        else:
+            PairLocks.locks.append(lock)
+
+    @staticmethod
+    def get_pair_locks(pair: Optional[str], now: Optional[datetime] = None) -> List[PairLock]:
+        """
+        Get all currently active locks for this pair
+        :param pair: Pair to check for. Returns all current locks if pair is empty
+        :param now: Datetime object (generated via datetime.now(timezone.utc)).
+                    defaults to datetime.now(timezone.utc)
+        """
+        if not now:
+            now = datetime.now(timezone.utc)
+
+        if PairLocks.use_db:
+            return PairLock.query_pair_locks(pair, now).all()
+        else:
+            locks = [lock for lock in PairLocks.locks if (
+                lock.lock_end_time >= now
+                and lock.active is True
+                and (pair is None or lock.pair == pair)
+            )]
+            return locks
+
+    @staticmethod
+    def unlock_pair(pair: str, now: Optional[datetime] = None) -> None:
+        """
+        Release all locks for this pair.
+        :param pair: Pair to unlock
+        :param now: Datetime object (generated via datetime.now(timezone.utc)).
+            defaults to datetime.now(timezone.utc)
+        """
+        if not now:
+            now = datetime.now(timezone.utc)
+
+        logger.info(f"Releasing all locks for {pair}.")
+        locks = PairLocks.get_pair_locks(pair, now)
+        for lock in locks:
+            lock.active = False
+        if PairLocks.use_db:
+            PairLock.session.flush()
+
+    @staticmethod
+    def is_global_lock(now: Optional[datetime] = None) -> bool:
+        """
+        :param now: Datetime object (generated via datetime.now(timezone.utc)).
+            defaults to datetime.now(timezone.utc)
+        """
+        if not now:
+            now = datetime.now(timezone.utc)
+
+        return len(PairLocks.get_pair_locks('*', now)) > 0
+
+    @staticmethod
+    def is_pair_locked(pair: str, now: Optional[datetime] = None) -> bool:
+        """
+        :param pair: Pair to check for
+        :param now: Datetime object (generated via datetime.now(timezone.utc)).
+            defaults to datetime.now(timezone.utc)
+        """
+        if not now:
+            now = datetime.now(timezone.utc)
+
+        return len(PairLocks.get_pair_locks(pair, now)) > 0 or PairLocks.is_global_lock(now)
diff --git a/freqtrade/plot/plotting.py b/freqtrade/plot/plotting.py
index dde6f78f0..f7d300593 100644
--- a/freqtrade/plot/plotting.py
+++ b/freqtrade/plot/plotting.py
@@ -1,85 +1,111 @@
 import logging
 from pathlib import Path
-from typing import Dict, List, Optional
+from typing import Any, Dict, List
 
 import pandas as pd
 
-from freqtrade.configuration import Arguments
-from freqtrade.data import history
-from freqtrade.data.btanalysis import (combine_tickers_with_mean,
-                                       create_cum_profit, load_trades)
-from freqtrade.exchange import Exchange
+from freqtrade.configuration import TimeRange
+from freqtrade.data.btanalysis import (calculate_max_drawdown, combine_dataframes_with_mean,
+                                       create_cum_profit, extract_trades_of_period, load_trades)
+from freqtrade.data.converter import trim_dataframe
+from freqtrade.data.dataprovider import DataProvider
+from freqtrade.data.history import get_timerange, load_data
+from freqtrade.exceptions import OperationalException
+from freqtrade.exchange import timeframe_to_prev_date, timeframe_to_seconds
+from freqtrade.misc import pair_to_filename
 from freqtrade.resolvers import ExchangeResolver, StrategyResolver
+from freqtrade.strategy import IStrategy
+
 
 logger = logging.getLogger(__name__)
 
 
 try:
-    from plotly import tools
+    import plotly.graph_objects as go
     from plotly.offline import plot
-    import plotly.graph_objs as go
+    from plotly.subplots import make_subplots
 except ImportError:
-    logger.exception("Module plotly not found \n Please install using `pip install plotly`")
+    logger.exception("Module plotly not found \n Please install using `pip3 install plotly`")
     exit(1)
 
 
-def init_plotscript(config):
+def init_plotscript(config, startup_candles: int = 0):
     """
     Initialize objects needed for plotting
-    :return: Dict with tickers, trades, pairs and strategy
+    :return: Dict with candle (OHLCV) data, trades and pairs
     """
-    exchange: Optional[Exchange] = None
 
-    # Exchange is only needed when downloading data!
-    if config.get("live", False) or config.get("refresh_pairs", False):
-        exchange = ExchangeResolver(config.get('exchange', {}).get('name'),
-                                    config).exchange
-
-    strategy = StrategyResolver(config).strategy
     if "pairs" in config:
-        pairs = config["pairs"].split(',')
+        pairs = config['pairs']
     else:
-        pairs = config["exchange"]["pair_whitelist"]
+        pairs = config['exchange']['pair_whitelist']
 
     # Set timerange to use
-    timerange = Arguments.parse_timerange(config.get("timerange"))
+    timerange = TimeRange.parse_timerange(config.get('timerange'))
 
-    tickers = history.load_data(
-        datadir=Path(str(config.get("datadir"))),
+    data = load_data(
+        datadir=config.get('datadir'),
         pairs=pairs,
-        ticker_interval=config['ticker_interval'],
-        refresh_pairs=config.get('refresh_pairs', False),
+        timeframe=config.get('timeframe', '5m'),
         timerange=timerange,
-        exchange=exchange,
-        live=config.get("live", False),
+        startup_candles=startup_candles,
+        data_format=config.get('dataformat_ohlcv', 'json'),
     )
 
-    trades = load_trades(config)
-    return {"tickers": tickers,
+    if startup_candles:
+        min_date, max_date = get_timerange(data)
+        logger.info(f"Loading data from {min_date} to {max_date}")
+        timerange.adjust_start_if_necessary(timeframe_to_seconds(config.get('timeframe', '5m')),
+                                            startup_candles, min_date)
+
+    no_trades = False
+    filename = config.get('exportfilename')
+    if config.get('no_trades', False):
+        no_trades = True
+    elif config['trade_source'] == 'file':
+        if not filename.is_dir() and not filename.is_file():
+            logger.warning("Backtest file is missing skipping trades.")
+            no_trades = True
+
+    trades = load_trades(
+        config['trade_source'],
+        db_url=config.get('db_url'),
+        exportfilename=filename,
+        no_trades=no_trades,
+        strategy=config.get('strategy'),
+    )
+    trades = trim_dataframe(trades, timerange, 'open_date')
+
+    return {"ohlcv": data,
             "trades": trades,
             "pairs": pairs,
-            "strategy": strategy,
+            "timerange": timerange,
             }
 
 
-def add_indicators(fig, row, indicators: List[str], data: pd.DataFrame) -> tools.make_subplots:
+def add_indicators(fig, row, indicators: Dict[str, Dict], data: pd.DataFrame) -> make_subplots:
     """
-    Generator all the indicator selected by the user for a specific row
+    Generate all the indicators selected by the user for a specific row, based on the configuration
     :param fig: Plot figure to append to
     :param row: row number for this plot
-    :param indicators: List of indicators present in the dataframe
+    :param indicators: Dict of Indicators with configuration options.
+                       Dict key must correspond to dataframe column.
     :param data: candlestick DataFrame
     """
-    for indicator in indicators:
+    for indicator, conf in indicators.items():
+        logger.debug(f"indicator {indicator} with config {conf}")
         if indicator in data:
-            # TODO: Figure out why scattergl causes problems
-            scattergl = go.Scatter(
-                x=data['date'],
-                y=data[indicator].values,
-                mode='lines',
-                name=indicator
+            kwargs = {'x': data['date'],
+                      'y': data[indicator].values,
+                      'mode': 'lines',
+                      'name': indicator
+                      }
+            if 'color' in conf:
+                kwargs.update({'line': {'color': conf['color']}})
+            scatter = go.Scatter(
+                **kwargs
             )
-            fig.append_trace(scattergl, row, 1)
+            fig.add_trace(scatter, row, 1)
         else:
             logger.info(
                 'Indicator "%s" ignored. Reason: This indicator is not found '
@@ -90,7 +116,7 @@ def add_indicators(fig, row, indicators: List[str], data: pd.DataFrame) -> tools
     return fig
 
 
-def add_profit(fig, row, data: pd.DataFrame, column: str, name: str) -> tools.make_subplots:
+def add_profit(fig, row, data: pd.DataFrame, column: str, name: str) -> make_subplots:
     """
     Add profit-plot
     :param fig: Plot figure to append to
@@ -100,27 +126,79 @@ def add_profit(fig, row, data: pd.DataFrame, column: str, name: str) -> tools.ma
     :param name: Name to use
     :return: fig with added profit plot
     """
-    profit = go.Scattergl(
+    profit = go.Scatter(
         x=data.index,
         y=data[column],
         name=name,
     )
-    fig.append_trace(profit, row, 1)
+    fig.add_trace(profit, row, 1)
 
     return fig
 
 
-def plot_trades(fig, trades: pd.DataFrame) -> tools.make_subplots:
+def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
+                     timeframe: str) -> make_subplots:
+    """
+    Add scatter points indicating max drawdown
+    """
+    try:
+        max_drawdown, highdate, lowdate = calculate_max_drawdown(trades)
+
+        drawdown = go.Scatter(
+            x=[highdate, lowdate],
+            y=[
+                df_comb.loc[timeframe_to_prev_date(timeframe, highdate), 'cum_profit'],
+                df_comb.loc[timeframe_to_prev_date(timeframe, lowdate), 'cum_profit'],
+            ],
+            mode='markers',
+            name=f"Max drawdown {max_drawdown * 100:.2f}%",
+            text=f"Max drawdown {max_drawdown * 100:.2f}%",
+            marker=dict(
+                symbol='square-open',
+                size=9,
+                line=dict(width=2),
+                color='green'
+
+            )
+        )
+        fig.add_trace(drawdown, row, 1)
+    except ValueError:
+        logger.warning("No trades found - not plotting max drawdown.")
+    return fig
+
+
+def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
     """
     Add trades to "fig"
     """
     # Trades can be empty
     if trades is not None and len(trades) > 0:
+        # Create description for sell summarizing the trade
+        trades['desc'] = trades.apply(lambda row: f"{round(row['profit_percent'] * 100, 1)}%, "
+                                                  f"{row['sell_reason']}, "
+                                                  f"{row['trade_duration']} min",
+                                                  axis=1)
         trade_buys = go.Scatter(
-            x=trades["open_time"],
+            x=trades["open_date"],
             y=trades["open_rate"],
             mode='markers',
-            name='trade_buy',
+            name='Trade buy',
+            text=trades["desc"],
+            marker=dict(
+                symbol='circle-open',
+                size=11,
+                line=dict(width=2),
+                color='cyan'
+
+            )
+        )
+
+        trade_sells = go.Scatter(
+            x=trades.loc[trades['profit_percent'] > 0, "close_date"],
+            y=trades.loc[trades['profit_percent'] > 0, "close_rate"],
+            text=trades.loc[trades['profit_percent'] > 0, "desc"],
+            mode='markers',
+            name='Sell - Profit',
             marker=dict(
                 symbol='square-open',
                 size=11,
@@ -128,16 +206,12 @@ def plot_trades(fig, trades: pd.DataFrame) -> tools.make_subplots:
                 color='green'
             )
         )
-        # Create description for sell summarizing the trade
-        desc = trades.apply(lambda row: f"{round(row['profitperc'], 3)}%, {row['sell_reason']}, "
-                                        f"{row['duration']}min",
-                            axis=1)
-        trade_sells = go.Scatter(
-            x=trades["close_time"],
-            y=trades["close_rate"],
-            text=desc,
+        trade_sells_loss = go.Scatter(
+            x=trades.loc[trades['profit_percent'] <= 0, "close_date"],
+            y=trades.loc[trades['profit_percent'] <= 0, "close_rate"],
+            text=trades.loc[trades['profit_percent'] <= 0, "desc"],
             mode='markers',
-            name='trade_sell',
+            name='Sell - Loss',
             marker=dict(
                 symbol='square-open',
                 size=11,
@@ -145,16 +219,55 @@ def plot_trades(fig, trades: pd.DataFrame) -> tools.make_subplots:
                 color='red'
             )
         )
-        fig.append_trace(trade_buys, 1, 1)
-        fig.append_trace(trade_sells, 1, 1)
+        fig.add_trace(trade_buys, 1, 1)
+        fig.add_trace(trade_sells, 1, 1)
+        fig.add_trace(trade_sells_loss, 1, 1)
     else:
         logger.warning("No trades found.")
     return fig
 
 
-def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFrame = None,
+def create_plotconfig(indicators1: List[str], indicators2: List[str],
+                      plot_config: Dict[str, Dict]) -> Dict[str, Dict]:
+    """
+    Combines indicators 1 and indicators 2 into plot_config if necessary
+    :param indicators1: List containing Main plot indicators
+    :param indicators2: List containing Sub plot indicators
+    :param plot_config: Dict of Dicts containing advanced plot configuration
+    :return: plot_config - eventually with indicators 1 and 2
+    """
+
+    if plot_config:
+        if indicators1:
+            plot_config['main_plot'] = {ind: {} for ind in indicators1}
+        if indicators2:
+            plot_config['subplots'] = {'Other': {ind: {} for ind in indicators2}}
+
+    if not plot_config:
+        # If no indicators and no plot-config given, use defaults.
+        if not indicators1:
+            indicators1 = ['sma', 'ema3', 'ema5']
+        if not indicators2:
+            indicators2 = ['macd', 'macdsignal']
+
+        # Create subplot configuration if plot_config is not available.
+        plot_config = {
+            'main_plot': {ind: {} for ind in indicators1},
+            'subplots': {'Other': {ind: {} for ind in indicators2}},
+        }
+    if 'main_plot' not in plot_config:
+        plot_config['main_plot'] = {}
+
+    if 'subplots' not in plot_config:
+        plot_config['subplots'] = {}
+    return plot_config
+
+
+def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFrame = None, *,
                                indicators1: List[str] = [],
-                               indicators2: List[str] = [],) -> go.Figure:
+                               indicators2: List[str] = [],
+                               plot_config: Dict[str, Dict] = {},
+                               ) -> go.Figure:
     """
     Generate the graph from the data generated by Backtesting or from DB
     Volume will always be ploted in row2, so Row 1 and 3 are to our disposal for custom indicators
@@ -163,21 +276,26 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
     :param trades: All trades created
     :param indicators1: List containing Main plot indicators
     :param indicators2: List containing Sub plot indicators
-    :return: None
+    :param plot_config: Dict of Dicts containing advanced plot configuration
+    :return: Plotly figure
     """
+    plot_config = create_plotconfig(indicators1, indicators2, plot_config)
 
+    rows = 2 + len(plot_config['subplots'])
+    row_widths = [1 for _ in plot_config['subplots']]
     # Define the graph
-    fig = tools.make_subplots(
-        rows=3,
+    fig = make_subplots(
+        rows=rows,
         cols=1,
         shared_xaxes=True,
-        row_width=[1, 1, 4],
+        row_width=row_widths + [1, 4],
         vertical_spacing=0.0001,
     )
     fig['layout'].update(title=pair)
     fig['layout']['yaxis1'].update(title='Price')
     fig['layout']['yaxis2'].update(title='Volume')
-    fig['layout']['yaxis3'].update(title='Other')
+    for i, name in enumerate(plot_config['subplots']):
+        fig['layout'][f'yaxis{3 + i}'].update(title=name)
     fig['layout']['xaxis']['rangeslider'].update(visible=False)
 
     # Common information
@@ -189,7 +307,7 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
         close=data.close,
         name='Price'
     )
-    fig.append_trace(candles, 1, 1)
+    fig.add_trace(candles, 1, 1)
 
     if 'buy' in data.columns:
         df_buy = data[data['buy'] == 1]
@@ -206,7 +324,7 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
                     color='green',
                 )
             )
-            fig.append_trace(buys, 1, 1)
+            fig.add_trace(buys, 1, 1)
         else:
             logger.warning("No buy-signals found.")
 
@@ -225,30 +343,35 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
                     color='red',
                 )
             )
-            fig.append_trace(sells, 1, 1)
+            fig.add_trace(sells, 1, 1)
         else:
             logger.warning("No sell-signals found.")
 
+    # TODO: Figure out why scattergl causes problems plotly/plotly.js#2284
     if 'bb_lowerband' in data and 'bb_upperband' in data:
-        bb_lower = go.Scattergl(
+        bb_lower = go.Scatter(
             x=data.date,
             y=data.bb_lowerband,
-            name='BB lower',
+            showlegend=False,
             line={'color': 'rgba(255,255,255,0)'},
         )
-        bb_upper = go.Scattergl(
+        bb_upper = go.Scatter(
             x=data.date,
             y=data.bb_upperband,
-            name='BB upper',
+            name='Bollinger Band',
             fill="tonexty",
             fillcolor="rgba(0,176,246,0.2)",
             line={'color': 'rgba(255,255,255,0)'},
         )
-        fig.append_trace(bb_lower, 1, 1)
-        fig.append_trace(bb_upper, 1, 1)
+        fig.add_trace(bb_lower, 1, 1)
+        fig.add_trace(bb_upper, 1, 1)
+        if ('bb_upperband' in plot_config['main_plot']
+           and 'bb_lowerband' in plot_config['main_plot']):
+            del plot_config['main_plot']['bb_upperband']
+            del plot_config['main_plot']['bb_lowerband']
 
     # Add indicators to main plot
-    fig = add_indicators(fig=fig, row=1, indicators=indicators1, data=data)
+    fig = add_indicators(fig=fig, row=1, indicators=plot_config['main_plot'], data=data)
 
     fig = plot_trades(fig, trades)
 
@@ -256,68 +379,159 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
     volume = go.Bar(
         x=data['date'],
         y=data['volume'],
-        name='Volume'
+        name='Volume',
+        marker_color='DarkSlateGrey',
+        marker_line_color='DarkSlateGrey'
     )
-    fig.append_trace(volume, 2, 1)
+    fig.add_trace(volume, 2, 1)
 
-    # Add indicators to seperate row
-    fig = add_indicators(fig=fig, row=3, indicators=indicators2, data=data)
+    # Add indicators to separate row
+    for i, name in enumerate(plot_config['subplots']):
+        fig = add_indicators(fig=fig, row=3 + i,
+                             indicators=plot_config['subplots'][name],
+                             data=data)
 
     return fig
 
 
-def generate_profit_graph(pairs: str, tickers: Dict[str, pd.DataFrame],
-                          trades: pd.DataFrame) -> go.Figure:
+def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
+                          trades: pd.DataFrame, timeframe: str) -> go.Figure:
     # Combine close-values for all pairs, rename columns to "pair"
-    df_comb = combine_tickers_with_mean(tickers, "close")
+    df_comb = combine_dataframes_with_mean(data, "close")
+
+    # Trim trades to available OHLCV data
+    trades = extract_trades_of_period(df_comb, trades, date_index=True)
 
     # Add combined cumulative profit
-    df_comb = create_cum_profit(df_comb, trades, 'cum_profit')
+    df_comb = create_cum_profit(df_comb, trades, 'cum_profit', timeframe)
 
     # Plot the pairs average close prices, and total profit growth
-    avgclose = go.Scattergl(
+    avgclose = go.Scatter(
         x=df_comb.index,
         y=df_comb['mean'],
         name='Avg close price',
     )
 
-    fig = tools.make_subplots(rows=3, cols=1, shared_xaxes=True, row_width=[1, 1, 1])
-    fig['layout'].update(title="Profit plot")
+    fig = make_subplots(rows=3, cols=1, shared_xaxes=True,
+                        row_width=[1, 1, 1],
+                        vertical_spacing=0.05,
+                        subplot_titles=["AVG Close Price", "Combined Profit", "Profit per pair"])
+    fig['layout'].update(title="Freqtrade Profit plot")
+    fig['layout']['yaxis1'].update(title='Price')
+    fig['layout']['yaxis2'].update(title='Profit')
+    fig['layout']['yaxis3'].update(title='Profit')
+    fig['layout']['xaxis']['rangeslider'].update(visible=False)
 
-    fig.append_trace(avgclose, 1, 1)
+    fig.add_trace(avgclose, 1, 1)
     fig = add_profit(fig, 2, df_comb, 'cum_profit', 'Profit')
+    fig = add_max_drawdown(fig, 2, trades, df_comb, timeframe)
 
     for pair in pairs:
         profit_col = f'cum_profit_{pair}'
-        df_comb = create_cum_profit(df_comb, trades[trades['pair'] == pair], profit_col)
-
-        fig = add_profit(fig, 3, df_comb, profit_col, f"Profit {pair}")
+        try:
+            df_comb = create_cum_profit(df_comb, trades[trades['pair'] == pair], profit_col,
+                                        timeframe)
+            fig = add_profit(fig, 3, df_comb, profit_col, f"Profit {pair}")
+        except ValueError:
+            pass
 
     return fig
 
 
-def generate_plot_filename(pair, ticker_interval) -> str:
+def generate_plot_filename(pair: str, timeframe: str) -> str:
     """
-    Generate filenames per pair/ticker_interval to be used for storing plots
+    Generate filenames per pair/timeframe to be used for storing plots
     """
-    pair_name = pair.replace("/", "_")
-    file_name = 'freqtrade-plot-' + pair_name + '-' + ticker_interval + '.html'
+    pair_s = pair_to_filename(pair)
+    file_name = 'freqtrade-plot-' + pair_s + '-' + timeframe + '.html'
 
     logger.info('Generate plot file for %s', pair)
 
     return file_name
 
 
-def store_plot_file(fig, filename: str, auto_open: bool = False) -> None:
+def store_plot_file(fig, filename: str, directory: Path, auto_open: bool = False) -> None:
     """
     Generate a plot html file from pre populated fig plotly object
     :param fig: Plotly Figure to plot
-    :param pair: Pair to plot (used as filename and Plot title)
-    :param ticker_interval: Used as part of the filename
+    :param filename: Name to store the file as
+    :param directory: Directory to store the file in
+    :param auto_open: Automatically open files saved
     :return: None
     """
+    directory.mkdir(parents=True, exist_ok=True)
 
-    Path("user_data/plots").mkdir(parents=True, exist_ok=True)
-
-    plot(fig, filename=str(Path('user_data/plots').joinpath(filename)),
+    _filename = directory.joinpath(filename)
+    plot(fig, filename=str(_filename),
          auto_open=auto_open)
+    logger.info(f"Stored plot as {_filename}")
+
+
+def load_and_plot_trades(config: Dict[str, Any]):
+    """
+    From configuration provided
+    - Initializes plot-script
+    - Get candle (OHLCV) data
+    - Generate Dafaframes populated with indicators and signals based on configured strategy
+    - Load trades excecuted during the selected period
+    - Generate Plotly plot objects
+    - Generate plot files
+    :return: None
+    """
+    strategy = StrategyResolver.load_strategy(config)
+
+    exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config)
+    IStrategy.dp = DataProvider(config, exchange)
+    plot_elements = init_plotscript(config, strategy.startup_candle_count)
+    timerange = plot_elements['timerange']
+    trades = plot_elements['trades']
+    pair_counter = 0
+    for pair, data in plot_elements["ohlcv"].items():
+        pair_counter += 1
+        logger.info("analyse pair %s", pair)
+
+        df_analyzed = strategy.analyze_ticker(data, {'pair': pair})
+        df_analyzed = trim_dataframe(df_analyzed, timerange)
+        trades_pair = trades.loc[trades['pair'] == pair]
+        trades_pair = extract_trades_of_period(df_analyzed, trades_pair)
+
+        fig = generate_candlestick_graph(
+            pair=pair,
+            data=df_analyzed,
+            trades=trades_pair,
+            indicators1=config.get('indicators1', []),
+            indicators2=config.get('indicators2', []),
+            plot_config=strategy.plot_config if hasattr(strategy, 'plot_config') else {}
+        )
+
+        store_plot_file(fig, filename=generate_plot_filename(pair, config['timeframe']),
+                        directory=config['user_data_dir'] / 'plot')
+
+    logger.info('End of plotting process. %s plots generated', pair_counter)
+
+
+def plot_profit(config: Dict[str, Any]) -> None:
+    """
+    Plots the total profit for all pairs.
+    Note, the profit calculation isn't realistic.
+    But should be somewhat proportional, and therefor useful
+    in helping out to find a good algorithm.
+    """
+    plot_elements = init_plotscript(config)
+    trades = plot_elements['trades']
+    # Filter trades to relevant pairs
+    # Remove open pairs - we don't know the profit yet so can't calculate profit for these.
+    # Also, If only one open pair is left, then the profit-generation would fail.
+    trades = trades[(trades['pair'].isin(plot_elements['pairs']))
+                    & (~trades['close_date'].isnull())
+                    ]
+    if len(trades) == 0:
+        raise OperationalException("No trades found, cannot generate Profit-plot without "
+                                   "trades from either Backtest result or database.")
+
+    # Create an average close price of all the pairs that were involved.
+    # this could be useful to gauge the overall market trend
+    fig = generate_profit_graph(plot_elements['pairs'], plot_elements['ohlcv'],
+                                trades, config.get('timeframe', '5m'))
+    store_plot_file(fig, filename='freqtrade-profit-plot.html',
+                    directory=config['user_data_dir'] / 'plot', auto_open=True)
diff --git a/freqtrade/resolvers/__init__.py b/freqtrade/resolvers/__init__.py
index 8f79349fe..b42ec4931 100644
--- a/freqtrade/resolvers/__init__.py
+++ b/freqtrade/resolvers/__init__.py
@@ -1,6 +1,12 @@
-from freqtrade.resolvers.iresolver import IResolver  # noqa: F401
-from freqtrade.resolvers.exchange_resolver import ExchangeResolver  # noqa: F401
+# flake8: noqa: F401
+# isort: off
+from freqtrade.resolvers.iresolver import IResolver
+from freqtrade.resolvers.exchange_resolver import ExchangeResolver
+# isort: on
 # Don't import HyperoptResolver to avoid loading the whole Optimize tree
-# from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver  # noqa: F401
-from freqtrade.resolvers.pairlist_resolver import PairListResolver  # noqa: F401
-from freqtrade.resolvers.strategy_resolver import StrategyResolver  # noqa: F401
+# from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver
+from freqtrade.resolvers.pairlist_resolver import PairListResolver
+from freqtrade.resolvers.strategy_resolver import StrategyResolver
+
+
+
diff --git a/freqtrade/resolvers/exchange_resolver.py b/freqtrade/resolvers/exchange_resolver.py
index 6fb12a65f..ed6715d15 100644
--- a/freqtrade/resolvers/exchange_resolver.py
+++ b/freqtrade/resolvers/exchange_resolver.py
@@ -3,10 +3,11 @@ This module loads custom exchanges
 """
 import logging
 
-from freqtrade.exchange import Exchange
 import freqtrade.exchange as exchanges
+from freqtrade.exchange import MAP_EXCHANGE_CHILDCLASS, Exchange
 from freqtrade.resolvers import IResolver
 
+
 logger = logging.getLogger(__name__)
 
 
@@ -14,25 +15,31 @@ class ExchangeResolver(IResolver):
     """
     This class contains all the logic to load a custom exchange class
     """
+    object_type = Exchange
 
-    __slots__ = ['exchange']
-
-    def __init__(self, exchange_name: str, config: dict) -> None:
+    @staticmethod
+    def load_exchange(exchange_name: str, config: dict, validate: bool = True) -> Exchange:
         """
         Load the custom class from config parameter
         :param config: configuration dictionary
         """
+        # Map exchange name to avoid duplicate classes for identical exchanges
+        exchange_name = MAP_EXCHANGE_CHILDCLASS.get(exchange_name, exchange_name)
         exchange_name = exchange_name.title()
+        exchange = None
         try:
-            self.exchange = self._load_exchange(exchange_name, kwargs={'config': config})
+            exchange = ExchangeResolver._load_exchange(exchange_name,
+                                                       kwargs={'config': config,
+                                                               'validate': validate})
         except ImportError:
             logger.info(
                 f"No {exchange_name} specific subclass found. Using the generic class instead.")
-        if not hasattr(self, "exchange"):
-            self.exchange = Exchange(config)
+        if not exchange:
+            exchange = Exchange(config, validate=validate)
+        return exchange
 
-    def _load_exchange(
-            self, exchange_name: str, kwargs: dict) -> Exchange:
+    @staticmethod
+    def _load_exchange(exchange_name: str, kwargs: dict) -> Exchange:
         """
         Loads the specified exchange.
         Only checks for exchanges exported in freqtrade.exchanges
@@ -43,7 +50,7 @@ class ExchangeResolver(IResolver):
         try:
             ex_class = getattr(exchanges, exchange_name)
 
-            exchange = ex_class(kwargs['config'])
+            exchange = ex_class(**kwargs)
             if exchange:
                 logger.info(f"Using resolved exchange '{exchange_name}'...")
                 return exchange
diff --git a/freqtrade/resolvers/hyperopt_resolver.py b/freqtrade/resolvers/hyperopt_resolver.py
index 74412e738..8327a4d13 100644
--- a/freqtrade/resolvers/hyperopt_resolver.py
+++ b/freqtrade/resolvers/hyperopt_resolver.py
@@ -1,18 +1,19 @@
 # pragma pylint: disable=attribute-defined-outside-init
 
 """
-This module load custom hyperopts
+This module load custom hyperopt
 """
 import logging
 from pathlib import Path
-from typing import Optional, Dict
+from typing import Dict
 
-from freqtrade import OperationalException
-from freqtrade.constants import DEFAULT_HYPEROPT, DEFAULT_HYPEROPT_LOSS
+from freqtrade.constants import HYPEROPT_LOSS_BUILTIN, USERPATH_HYPEROPTS
+from freqtrade.exceptions import OperationalException
 from freqtrade.optimize.hyperopt_interface import IHyperOpt
 from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss
 from freqtrade.resolvers import IResolver
 
+
 logger = logging.getLogger(__name__)
 
 
@@ -20,109 +21,68 @@ class HyperOptResolver(IResolver):
     """
     This class contains all the logic to load custom hyperopt class
     """
+    object_type = IHyperOpt
+    object_type_str = "Hyperopt"
+    user_subdir = USERPATH_HYPEROPTS
+    initial_search_path = None
 
-    __slots__ = ['hyperopt']
-
-    def __init__(self, config: Dict) -> None:
+    @staticmethod
+    def load_hyperopt(config: Dict) -> IHyperOpt:
         """
-        Load the custom class from config parameter
+        Load the custom hyperopt class from config parameter
         :param config: configuration dictionary
         """
+        if not config.get('hyperopt'):
+            raise OperationalException("No Hyperopt set. Please use `--hyperopt` to specify "
+                                       "the Hyperopt class to use.")
 
-        # Verify the hyperopt is in the configuration, otherwise fallback to the default hyperopt
-        hyperopt_name = config.get('hyperopt') or DEFAULT_HYPEROPT
-        self.hyperopt = self._load_hyperopt(hyperopt_name, extra_dir=config.get('hyperopt_path'))
+        hyperopt_name = config['hyperopt']
 
-        # Assign ticker_interval to be used in hyperopt
-        self.hyperopt.__class__.ticker_interval = str(config['ticker_interval'])
+        hyperopt = HyperOptResolver.load_object(hyperopt_name, config,
+                                                kwargs={'config': config},
+                                                extra_dir=config.get('hyperopt_path'))
 
-        if not hasattr(self.hyperopt, 'populate_buy_trend'):
-            logger.warning("Custom Hyperopt does not provide populate_buy_trend. "
-                           "Using populate_buy_trend from DefaultStrategy.")
-        if not hasattr(self.hyperopt, 'populate_sell_trend'):
-            logger.warning("Custom Hyperopt does not provide populate_sell_trend. "
-                           "Using populate_sell_trend from DefaultStrategy.")
-
-    def _load_hyperopt(
-            self, hyperopt_name: str, extra_dir: Optional[str] = None) -> IHyperOpt:
-        """
-        Search and loads the specified hyperopt.
-        :param hyperopt_name: name of the module to import
-        :param extra_dir: additional directory to search for the given hyperopt
-        :return: HyperOpt instance or None
-        """
-        current_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
-
-        abs_paths = [
-            Path.cwd().joinpath('user_data/hyperopts'),
-            current_path,
-        ]
-
-        if extra_dir:
-            # Add extra hyperopt directory on top of search paths
-            abs_paths.insert(0, Path(extra_dir))
-
-        hyperopt = self._load_object(paths=abs_paths, object_type=IHyperOpt,
-                                     object_name=hyperopt_name)
-        if hyperopt:
-            return hyperopt
-        raise OperationalException(
-            f"Impossible to load Hyperopt '{hyperopt_name}'. This class does not exist "
-            "or contains Python code errors."
-        )
+        if not hasattr(hyperopt, 'populate_indicators'):
+            logger.info("Hyperopt class does not provide populate_indicators() method. "
+                        "Using populate_indicators from the strategy.")
+        if not hasattr(hyperopt, 'populate_buy_trend'):
+            logger.info("Hyperopt class does not provide populate_buy_trend() method. "
+                        "Using populate_buy_trend from the strategy.")
+        if not hasattr(hyperopt, 'populate_sell_trend'):
+            logger.info("Hyperopt class does not provide populate_sell_trend() method. "
+                        "Using populate_sell_trend from the strategy.")
+        return hyperopt
 
 
 class HyperOptLossResolver(IResolver):
     """
     This class contains all the logic to load custom hyperopt loss class
     """
+    object_type = IHyperOptLoss
+    object_type_str = "HyperoptLoss"
+    user_subdir = USERPATH_HYPEROPTS
+    initial_search_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
 
-    __slots__ = ['hyperoptloss']
-
-    def __init__(self, config: Optional[Dict] = None) -> None:
+    @staticmethod
+    def load_hyperoptloss(config: Dict) -> IHyperOptLoss:
         """
         Load the custom class from config parameter
-        :param config: configuration dictionary or None
+        :param config: configuration dictionary
         """
-        config = config or {}
 
-        # Verify the hyperopt is in the configuration, otherwise fallback to the default hyperopt
-        hyperopt_name = config.get('hyperopt_loss') or DEFAULT_HYPEROPT_LOSS
-        self.hyperoptloss = self._load_hyperoptloss(
-            hyperopt_name, extra_dir=config.get('hyperopt_path'))
-
-        # Assign ticker_interval to be used in hyperopt
-        self.hyperoptloss.__class__.ticker_interval = str(config['ticker_interval'])
-
-        if not hasattr(self.hyperoptloss, 'hyperopt_loss_function'):
+        hyperoptloss_name = config.get('hyperopt_loss')
+        if not hyperoptloss_name:
             raise OperationalException(
-                f"Found hyperopt {hyperopt_name} does not implement `hyperopt_loss_function`.")
+                "No Hyperopt loss set. Please use `--hyperopt-loss` to "
+                "specify the Hyperopt-Loss class to use.\n"
+                f"Built-in Hyperopt-loss-functions are: {', '.join(HYPEROPT_LOSS_BUILTIN)}"
+            )
+        hyperoptloss = HyperOptLossResolver.load_object(hyperoptloss_name,
+                                                        config, kwargs={},
+                                                        extra_dir=config.get('hyperopt_path'))
 
-    def _load_hyperoptloss(
-            self, hyper_loss_name: str, extra_dir: Optional[str] = None) -> IHyperOptLoss:
-        """
-        Search and loads the specified hyperopt loss class.
-        :param hyper_loss_name: name of the module to import
-        :param extra_dir: additional directory to search for the given hyperopt
-        :return: HyperOptLoss instance or None
-        """
-        current_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
+        # Assign timeframe to be used in hyperopt
+        hyperoptloss.__class__.ticker_interval = str(config['timeframe'])
+        hyperoptloss.__class__.timeframe = str(config['timeframe'])
 
-        abs_paths = [
-            Path.cwd().joinpath('user_data/hyperopts'),
-            current_path,
-        ]
-
-        if extra_dir:
-            # Add extra hyperopt directory on top of search paths
-            abs_paths.insert(0, Path(extra_dir))
-
-        hyperoptloss = self._load_object(paths=abs_paths, object_type=IHyperOptLoss,
-                                         object_name=hyper_loss_name)
-        if hyperoptloss:
-            return hyperoptloss
-
-        raise OperationalException(
-            f"Impossible to load HyperoptLoss '{hyper_loss_name}'. This class does not exist "
-            "or contains Python code errors."
-        )
+        return hyperoptloss
diff --git a/freqtrade/resolvers/iresolver.py b/freqtrade/resolvers/iresolver.py
index 9d0c97917..37cfd70e6 100644
--- a/freqtrade/resolvers/iresolver.py
+++ b/freqtrade/resolvers/iresolver.py
@@ -7,66 +7,103 @@ import importlib.util
 import inspect
 import logging
 from pathlib import Path
-from typing import Any, List, Optional, Tuple, Type, Union
+from typing import Any, Dict, Iterator, List, Optional, Tuple, Type, Union
+
+from freqtrade.exceptions import OperationalException
+
 
 logger = logging.getLogger(__name__)
 
 
-class IResolver(object):
+class IResolver:
     """
     This class contains all the logic to load custom classes
     """
+    # Childclasses need to override this
+    object_type: Type[Any]
+    object_type_str: str
+    user_subdir: Optional[str] = None
+    initial_search_path: Optional[Path]
 
-    @staticmethod
-    def _get_valid_object(object_type, module_path: Path,
-                          object_name: str) -> Optional[Type[Any]]:
+    @classmethod
+    def build_search_paths(cls, config: Dict[str, Any], user_subdir: Optional[str] = None,
+                           extra_dir: Optional[str] = None) -> List[Path]:
+
+        abs_paths: List[Path] = []
+        if cls.initial_search_path:
+            abs_paths.append(cls.initial_search_path)
+
+        if user_subdir:
+            abs_paths.insert(0, config['user_data_dir'].joinpath(user_subdir))
+
+        if extra_dir:
+            # Add extra directory to the top of the search paths
+            abs_paths.insert(0, Path(extra_dir).resolve())
+
+        return abs_paths
+
+    @classmethod
+    def _get_valid_object(cls, module_path: Path, object_name: Optional[str],
+                          enum_failed: bool = False) -> Iterator[Any]:
         """
-        Returns the first object with matching object_type and object_name in the path given.
-        :param object_type: object_type (class)
+        Generator returning objects with matching object_type and object_name in the path given.
         :param module_path: absolute path to the module
         :param object_name: Class name of the object
-        :return: class or None
+        :param enum_failed: If True, will return None for modules which fail.
+            Otherwise, failing modules are skipped.
+        :return: generator containing tuple of matching objects
+             Tuple format: [Object, source]
         """
 
         # Generate spec based on absolute path
-        spec = importlib.util.spec_from_file_location('unknown', str(module_path))
+        # Pass object_name as first argument to have logging print a reasonable name.
+        spec = importlib.util.spec_from_file_location(object_name or "", str(module_path))
         module = importlib.util.module_from_spec(spec)
         try:
             spec.loader.exec_module(module)  # type: ignore # importlib does not use typehints
-        except (ModuleNotFoundError, SyntaxError) as err:
+        except (ModuleNotFoundError, SyntaxError, ImportError) as err:
             # Catch errors in case a specific module is not installed
             logger.warning(f"Could not import {module_path} due to '{err}'")
+            if enum_failed:
+                return iter([None])
 
         valid_objects_gen = (
-            obj for name, obj in inspect.getmembers(module, inspect.isclass)
-            if object_name == name and object_type in obj.__bases__
+            (obj, inspect.getsource(module)) for
+            name, obj in inspect.getmembers(
+                module, inspect.isclass) if ((object_name is None or object_name == name)
+                                             and issubclass(obj, cls.object_type)
+                                             and obj is not cls.object_type)
         )
-        return next(valid_objects_gen, None)
+        return valid_objects_gen
 
-    @staticmethod
-    def _search_object(directory: Path, object_type, object_name: str,
-                       kwargs: dict = {}) -> Union[Tuple[Any, Path], Tuple[None, None]]:
+    @classmethod
+    def _search_object(cls, directory: Path, *, object_name: str, add_source: bool = False
+                       ) -> Union[Tuple[Any, Path], Tuple[None, None]]:
         """
         Search for the objectname in the given directory
         :param directory: relative or absolute directory path
-        :return: object instance
+        :param object_name: ClassName of the object to load
+        :return: object class
         """
-        logger.debug("Searching for %s %s in '%s'", object_type.__name__, object_name, directory)
+        logger.debug(f"Searching for {cls.object_type.__name__} {object_name} in '{directory}'")
         for entry in directory.iterdir():
             # Only consider python files
             if not str(entry).endswith('.py'):
                 logger.debug('Ignoring %s', entry)
                 continue
-            module_path = Path.resolve(directory.joinpath(entry))
-            obj = IResolver._get_valid_object(
-                object_type, module_path, object_name
-            )
+            module_path = entry.resolve()
+
+            obj = next(cls._get_valid_object(module_path, object_name), None)
+
             if obj:
-                return (obj(**kwargs), module_path)
+                obj[0].__file__ = str(entry)
+                if add_source:
+                    obj[0].__source__ = obj[1]
+                return (obj[0], module_path)
         return (None, None)
 
-    @staticmethod
-    def _load_object(paths: List[Path], object_type, object_name: str,
+    @classmethod
+    def _load_object(cls, paths: List[Path], *, object_name: str, add_source: bool = False,
                      kwargs: dict = {}) -> Optional[Any]:
         """
         Try to load object from path list.
@@ -74,16 +111,68 @@ class IResolver(object):
 
         for _path in paths:
             try:
-                (module, module_path) = IResolver._search_object(directory=_path,
-                                                                 object_type=object_type,
-                                                                 object_name=object_name,
-                                                                 kwargs=kwargs)
+                (module, module_path) = cls._search_object(directory=_path,
+                                                           object_name=object_name,
+                                                           add_source=add_source)
                 if module:
                     logger.info(
-                        f"Using resolved {object_type.__name__.lower()[1:]} {object_name} "
+                        f"Using resolved {cls.object_type.__name__.lower()[1:]} {object_name} "
                         f"from '{module_path}'...")
-                    return module
+                    return module(**kwargs)
             except FileNotFoundError:
-                logger.warning('Path "%s" does not exist.', _path.relative_to(Path.cwd()))
+                logger.warning('Path "%s" does not exist.', _path.resolve())
 
         return None
+
+    @classmethod
+    def load_object(cls, object_name: str, config: dict, *, kwargs: dict,
+                    extra_dir: Optional[str] = None) -> Any:
+        """
+        Search and loads the specified object as configured in hte child class.
+        :param objectname: name of the module to import
+        :param config: configuration dictionary
+        :param extra_dir: additional directory to search for the given pairlist
+        :raises: OperationalException if the class is invalid or does not exist.
+        :return: Object instance or None
+        """
+
+        abs_paths = cls.build_search_paths(config,
+                                           user_subdir=cls.user_subdir,
+                                           extra_dir=extra_dir)
+
+        found_object = cls._load_object(paths=abs_paths, object_name=object_name,
+                                        kwargs=kwargs)
+        if found_object:
+            return found_object
+        raise OperationalException(
+            f"Impossible to load {cls.object_type_str} '{object_name}'. This class does not exist "
+            "or contains Python code errors."
+        )
+
+    @classmethod
+    def search_all_objects(cls, directory: Path,
+                           enum_failed: bool) -> List[Dict[str, Any]]:
+        """
+        Searches a directory for valid objects
+        :param directory: Path to search
+        :param enum_failed: If True, will return None for modules which fail.
+            Otherwise, failing modules are skipped.
+        :return: List of dicts containing 'name', 'class' and 'location' entires
+        """
+        logger.debug(f"Searching for {cls.object_type.__name__} '{directory}'")
+        objects = []
+        for entry in directory.iterdir():
+            # Only consider python files
+            if not str(entry).endswith('.py'):
+                logger.debug('Ignoring %s', entry)
+                continue
+            module_path = entry.resolve()
+            logger.debug(f"Path {module_path}")
+            for obj in cls._get_valid_object(module_path, object_name=None,
+                                             enum_failed=enum_failed):
+                objects.append(
+                    {'name': obj[0].__name__ if obj is not None else '',
+                     'class': obj[0] if obj is not None else None,
+                     'location': entry,
+                     })
+        return objects
diff --git a/freqtrade/resolvers/pairlist_resolver.py b/freqtrade/resolvers/pairlist_resolver.py
index 3d95c0295..4df5da37c 100644
--- a/freqtrade/resolvers/pairlist_resolver.py
+++ b/freqtrade/resolvers/pairlist_resolver.py
@@ -1,53 +1,44 @@
 # pragma pylint: disable=attribute-defined-outside-init
 
 """
-This module load custom hyperopts
+This module load custom pairlists
 """
 import logging
 from pathlib import Path
 
-from freqtrade import OperationalException
 from freqtrade.pairlist.IPairList import IPairList
 from freqtrade.resolvers import IResolver
 
+
 logger = logging.getLogger(__name__)
 
 
 class PairListResolver(IResolver):
     """
-    This class contains all the logic to load custom hyperopt class
+    This class contains all the logic to load custom PairList class
     """
+    object_type = IPairList
+    object_type_str = "Pairlist"
+    user_subdir = None
+    initial_search_path = Path(__file__).parent.parent.joinpath('pairlist').resolve()
 
-    __slots__ = ['pairlist']
-
-    def __init__(self, pairlist_name: str, freqtrade, config: dict) -> None:
+    @staticmethod
+    def load_pairlist(pairlist_name: str, exchange, pairlistmanager,
+                      config: dict, pairlistconfig: dict, pairlist_pos: int) -> IPairList:
         """
-        Load the custom class from config parameter
-        :param config: configuration dictionary or None
+        Load the pairlist with pairlist_name
+        :param pairlist_name: Classname of the pairlist
+        :param exchange: Initialized exchange class
+        :param pairlistmanager: Initialized pairlist manager
+        :param config: configuration dictionary
+        :param pairlistconfig: Configuration dedicated to this pairlist
+        :param pairlist_pos: Position of the pairlist in the list of pairlists
+        :return: initialized Pairlist class
         """
-        self.pairlist = self._load_pairlist(pairlist_name, kwargs={'freqtrade': freqtrade,
-                                                                   'config': config})
-
-    def _load_pairlist(
-            self, pairlist_name: str, kwargs: dict) -> IPairList:
-        """
-        Search and loads the specified pairlist.
-        :param pairlist_name: name of the module to import
-        :param extra_dir: additional directory to search for the given pairlist
-        :return: PairList instance or None
-        """
-        current_path = Path(__file__).parent.parent.joinpath('pairlist').resolve()
-
-        abs_paths = [
-            Path.cwd().joinpath('user_data/pairlist'),
-            current_path,
-        ]
-
-        pairlist = self._load_object(paths=abs_paths, object_type=IPairList,
-                                     object_name=pairlist_name, kwargs=kwargs)
-        if pairlist:
-            return pairlist
-        raise OperationalException(
-            f"Impossible to load Pairlist '{pairlist_name}'. This class does not exist "
-            "or contains Python code errors."
-        )
+        return PairListResolver.load_object(pairlist_name, config,
+                                            kwargs={'exchange': exchange,
+                                                    'pairlistmanager': pairlistmanager,
+                                                    'config': config,
+                                                    'pairlistconfig': pairlistconfig,
+                                                    'pairlist_pos': pairlist_pos},
+                                            )
diff --git a/freqtrade/resolvers/strategy_resolver.py b/freqtrade/resolvers/strategy_resolver.py
index aa73327ff..63a3f784e 100644
--- a/freqtrade/resolvers/strategy_resolver.py
+++ b/freqtrade/resolvers/strategy_resolver.py
@@ -9,81 +9,107 @@ from base64 import urlsafe_b64decode
 from collections import OrderedDict
 from inspect import getfullargspec
 from pathlib import Path
-from typing import Dict, Optional
+from typing import Any, Dict, Optional
 
-from freqtrade import constants, OperationalException
+from freqtrade.constants import REQUIRED_ORDERTIF, REQUIRED_ORDERTYPES, USERPATH_STRATEGIES
+from freqtrade.exceptions import OperationalException
 from freqtrade.resolvers import IResolver
-from freqtrade.strategy import import_strategy
 from freqtrade.strategy.interface import IStrategy
 
+
 logger = logging.getLogger(__name__)
 
 
 class StrategyResolver(IResolver):
     """
-    This class contains all the logic to load custom strategy class
+    This class contains the logic to load custom strategy class
     """
+    object_type = IStrategy
+    object_type_str = "Strategy"
+    user_subdir = USERPATH_STRATEGIES
+    initial_search_path = None
 
-    __slots__ = ['strategy']
-
-    def __init__(self, config: Optional[Dict] = None) -> None:
+    @staticmethod
+    def load_strategy(config: Dict[str, Any] = None) -> IStrategy:
         """
         Load the custom class from config parameter
         :param config: configuration dictionary or None
         """
         config = config or {}
 
-        # Verify the strategy is in the configuration, otherwise fallback to the default strategy
-        strategy_name = config.get('strategy') or constants.DEFAULT_STRATEGY
-        self.strategy: IStrategy = self._load_strategy(strategy_name,
-                                                       config=config,
-                                                       extra_dir=config.get('strategy_path'))
+        if not config.get('strategy'):
+            raise OperationalException("No strategy set. Please use `--strategy` to specify "
+                                       "the strategy class to use.")
 
-        # make sure experimental dict is available
-        if 'experimental' not in config:
-            config['experimental'] = {}
+        strategy_name = config['strategy']
+        strategy: IStrategy = StrategyResolver._load_strategy(
+            strategy_name, config=config,
+            extra_dir=config.get('strategy_path'))
+
+        # make sure ask_strategy dict is available
+        if 'ask_strategy' not in config:
+            config['ask_strategy'] = {}
+
+        if hasattr(strategy, 'ticker_interval') and not hasattr(strategy, 'timeframe'):
+            # Assign ticker_interval to timeframe to keep compatibility
+            if 'timeframe' not in config:
+                logger.warning(
+                    "DEPRECATED: Please migrate to using 'timeframe' instead of 'ticker_interval'."
+                    )
+                strategy.timeframe = strategy.ticker_interval
 
         # Set attributes
         # Check if we need to override configuration
-        # (Attribute name,                              default, experimental)
-        attributes = [("minimal_roi",                     {"0": 10.0}, False),
-                      ("ticker_interval",                 None,        False),
-                      ("stoploss",                        None,        False),
-                      ("trailing_stop",                   None,        False),
-                      ("trailing_stop_positive",          None,        False),
-                      ("trailing_stop_positive_offset",   0.0,         False),
-                      ("trailing_only_offset_is_reached", None,        False),
-                      ("process_only_new_candles",        None,        False),
-                      ("order_types",                     None,        False),
-                      ("order_time_in_force",             None,        False),
-                      ("stake_currency",                  None,        False),
-                      ("stake_amount",                    None,        False),
-                      ("use_sell_signal",                 False,       True),
-                      ("sell_profit_only",                False,       True),
-                      ("ignore_roi_if_buy_signal",        False,       True),
+        #             (Attribute name,                    default,     subkey)
+        attributes = [("minimal_roi",                     {"0": 10.0}, None),
+                      ("timeframe",                       None,        None),
+                      ("stoploss",                        None,        None),
+                      ("trailing_stop",                   None,        None),
+                      ("trailing_stop_positive",          None,        None),
+                      ("trailing_stop_positive_offset",   0.0,         None),
+                      ("trailing_only_offset_is_reached", None,        None),
+                      ("process_only_new_candles",        None,        None),
+                      ("order_types",                     None,        None),
+                      ("order_time_in_force",             None,        None),
+                      ("stake_currency",                  None,        None),
+                      ("stake_amount",                    None,        None),
+                      ("startup_candle_count",            None,        None),
+                      ("unfilledtimeout",                 None,        None),
+                      ("use_sell_signal",                 True,        'ask_strategy'),
+                      ("sell_profit_only",                False,       'ask_strategy'),
+                      ("ignore_roi_if_buy_signal",        False,       'ask_strategy'),
+                      ("disable_dataframe_checks",        False,       None),
                       ]
-        for attribute, default, experimental in attributes:
-            if experimental:
-                self._override_attribute_helper(config['experimental'], attribute, default)
+        for attribute, default, subkey in attributes:
+            if subkey:
+                StrategyResolver._override_attribute_helper(strategy, config.get(subkey, {}),
+                                                            attribute, default)
             else:
-                self._override_attribute_helper(config, attribute, default)
+                StrategyResolver._override_attribute_helper(strategy, config,
+                                                            attribute, default)
+
+        # Assign deprecated variable - to not break users code relying on this.
+        strategy.ticker_interval = strategy.timeframe
 
         # Loop this list again to have output combined
-        for attribute, _, exp in attributes:
-            if exp and attribute in config['experimental']:
-                logger.info("Strategy using %s: %s", attribute, config['experimental'][attribute])
+        for attribute, _, subkey in attributes:
+            if subkey and attribute in config[subkey]:
+                logger.info("Strategy using %s: %s", attribute, config[subkey][attribute])
             elif attribute in config:
                 logger.info("Strategy using %s: %s", attribute, config[attribute])
 
         # Sort and apply type conversions
-        self.strategy.minimal_roi = OrderedDict(sorted(
-            {int(key): value for (key, value) in self.strategy.minimal_roi.items()}.items(),
+        strategy.minimal_roi = OrderedDict(sorted(
+            {int(key): value for (key, value) in strategy.minimal_roi.items()}.items(),
             key=lambda t: t[0]))
-        self.strategy.stoploss = float(self.strategy.stoploss)
+        strategy.stoploss = float(strategy.stoploss)
 
-        self._strategy_sanity_validations()
+        StrategyResolver._strategy_sanity_validations(strategy)
+        return strategy
 
-    def _override_attribute_helper(self, config, attribute: str, default):
+    @staticmethod
+    def _override_attribute_helper(strategy, config: Dict[str, Any],
+                                   attribute: str, default: Any):
         """
         Override attributes in the strategy.
         Prevalence:
@@ -92,27 +118,32 @@ class StrategyResolver(IResolver):
         - default (if not None)
         """
         if attribute in config:
-            setattr(self.strategy, attribute, config[attribute])
+            setattr(strategy, attribute, config[attribute])
             logger.info("Override strategy '%s' with value in config file: %s.",
                         attribute, config[attribute])
-        elif hasattr(self.strategy, attribute):
-            config[attribute] = getattr(self.strategy, attribute)
+        elif hasattr(strategy, attribute):
+            val = getattr(strategy, attribute)
+            # None's cannot exist in the config, so do not copy them
+            if val is not None:
+                config[attribute] = val
         # Explicitly check for None here as other "falsy" values are possible
         elif default is not None:
-            setattr(self.strategy, attribute, default)
+            setattr(strategy, attribute, default)
             config[attribute] = default
 
-    def _strategy_sanity_validations(self):
-        if not all(k in self.strategy.order_types for k in constants.REQUIRED_ORDERTYPES):
-            raise ImportError(f"Impossible to load Strategy '{self.strategy.__class__.__name__}'. "
+    @staticmethod
+    def _strategy_sanity_validations(strategy):
+        if not all(k in strategy.order_types for k in REQUIRED_ORDERTYPES):
+            raise ImportError(f"Impossible to load Strategy '{strategy.__class__.__name__}'. "
                               f"Order-types mapping is incomplete.")
 
-        if not all(k in self.strategy.order_time_in_force for k in constants.REQUIRED_ORDERTIF):
-            raise ImportError(f"Impossible to load Strategy '{self.strategy.__class__.__name__}'. "
+        if not all(k in strategy.order_time_in_force for k in REQUIRED_ORDERTIF):
+            raise ImportError(f"Impossible to load Strategy '{strategy.__class__.__name__}'. "
                               f"Order-time-in-force mapping is incomplete.")
 
-    def _load_strategy(
-            self, strategy_name: str, config: dict, extra_dir: Optional[str] = None) -> IStrategy:
+    @staticmethod
+    def _load_strategy(strategy_name: str,
+                       config: dict, extra_dir: Optional[str] = None) -> IStrategy:
         """
         Search and loads the specified strategy.
         :param strategy_name: name of the module to import
@@ -120,16 +151,10 @@ class StrategyResolver(IResolver):
         :param extra_dir: additional directory to search for the given strategy
         :return: Strategy instance or None
         """
-        current_path = Path(__file__).parent.parent.joinpath('strategy').resolve()
 
-        abs_paths = [
-            Path.cwd().joinpath('user_data/strategies'),
-            current_path,
-        ]
-
-        if extra_dir:
-            # Add extra strategy directory on top of search paths
-            abs_paths.insert(0, Path(extra_dir).resolve())
+        abs_paths = StrategyResolver.build_search_paths(config,
+                                                        user_subdir=USERPATH_STRATEGIES,
+                                                        extra_dir=extra_dir)
 
         if ":" in strategy_name:
             logger.info("loading base64 encoded strategy")
@@ -147,19 +172,21 @@ class StrategyResolver(IResolver):
                 # register temp path with the bot
                 abs_paths.insert(0, temp.resolve())
 
-        strategy = self._load_object(paths=abs_paths, object_type=IStrategy,
-                                     object_name=strategy_name, kwargs={'config': config})
+        strategy = StrategyResolver._load_object(paths=abs_paths,
+                                                 object_name=strategy_name,
+                                                 add_source=True,
+                                                 kwargs={'config': config},
+                                                 )
         if strategy:
             strategy._populate_fun_len = len(getfullargspec(strategy.populate_indicators).args)
             strategy._buy_fun_len = len(getfullargspec(strategy.populate_buy_trend).args)
             strategy._sell_fun_len = len(getfullargspec(strategy.populate_sell_trend).args)
+            if any([x == 2 for x in [strategy._populate_fun_len,
+                                     strategy._buy_fun_len,
+                                     strategy._sell_fun_len]]):
+                strategy.INTERFACE_VERSION = 1
 
-            try:
-                return import_strategy(strategy, config=config)
-            except TypeError as e:
-                logger.warning(
-                    f"Impossible to load strategy '{strategy_name}'. "
-                    f"Error: {e}")
+            return strategy
 
         raise OperationalException(
             f"Impossible to load Strategy '{strategy_name}'. This class does not exist "
diff --git a/freqtrade/rpc/__init__.py b/freqtrade/rpc/__init__.py
index 31c854f82..88978519b 100644
--- a/freqtrade/rpc/__init__.py
+++ b/freqtrade/rpc/__init__.py
@@ -1,2 +1,3 @@
-from .rpc import RPC, RPCMessageType, RPCException  # noqa
-from .rpc_manager import RPCManager  # noqa
+# flake8: noqa: F401
+from .rpc import RPC, RPCException, RPCMessageType
+from .rpc_manager import RPCManager
diff --git a/freqtrade/rpc/api_server.py b/freqtrade/rpc/api_server.py
index 711202b27..384d7c6c2 100644
--- a/freqtrade/rpc/api_server.py
+++ b/freqtrade/rpc/api_server.py
@@ -1,31 +1,43 @@
 import logging
 import threading
+from copy import deepcopy
 from datetime import date, datetime
 from ipaddress import IPv4Address
-from typing import Dict
+from pathlib import Path
+from typing import Any, Callable, Dict
 
 from arrow import Arrow
 from flask import Flask, jsonify, request
 from flask.json import JSONEncoder
+from flask_cors import CORS
+from flask_jwt_extended import (JWTManager, create_access_token, create_refresh_token,
+                                get_jwt_identity, jwt_refresh_token_required,
+                                verify_jwt_in_request_optional)
+from werkzeug.security import safe_str_cmp
 from werkzeug.serving import make_server
 
 from freqtrade.__init__ import __version__
+from freqtrade.constants import DATETIME_PRINT_FORMAT, USERPATH_STRATEGIES
+from freqtrade.exceptions import OperationalException
+from freqtrade.persistence import Trade
+from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
 from freqtrade.rpc.rpc import RPC, RPCException
 
+
 logger = logging.getLogger(__name__)
 
 BASE_URI = "/api/v1"
 
 
-class ArrowJSONEncoder(JSONEncoder):
+class FTJSONEncoder(JSONEncoder):
     def default(self, obj):
         try:
             if isinstance(obj, Arrow):
                 return obj.for_json()
+            elif isinstance(obj, datetime):
+                return obj.strftime(DATETIME_PRINT_FORMAT)
             elif isinstance(obj, date):
                 return obj.strftime("%Y-%m-%d")
-            elif isinstance(obj, datetime):
-                return obj.strftime("%Y-%m-%d %H:%M:%S")
             iterable = iter(obj)
         except TypeError:
             pass
@@ -34,40 +46,49 @@ class ArrowJSONEncoder(JSONEncoder):
         return JSONEncoder.default(self, obj)
 
 
+# Type should really be Callable[[ApiServer, Any], Any], but that will create a circular dependency
+def require_login(func: Callable[[Any, Any], Any]):
+
+    def func_wrapper(obj, *args, **kwargs):
+        verify_jwt_in_request_optional()
+        auth = request.authorization
+        if get_jwt_identity() or auth and obj.check_auth(auth.username, auth.password):
+            return func(obj, *args, **kwargs)
+        else:
+            return jsonify({"error": "Unauthorized"}), 401
+
+    return func_wrapper
+
+
+# Type should really be Callable[[ApiServer], Any], but that will create a circular dependency
+def rpc_catch_errors(func: Callable[..., Any]):
+
+    def func_wrapper(obj, *args, **kwargs):
+
+        try:
+            return func(obj, *args, **kwargs)
+        except RPCException as e:
+            logger.exception("API Error calling %s: %s", func.__name__, e)
+            return obj.rest_error(f"Error querying {func.__name__}: {e}")
+
+    return func_wrapper
+
+
+def shutdown_session(exception=None):
+    # Remove scoped session
+    Trade.session.remove()
+
+
 class ApiServer(RPC):
     """
     This class runs api server and provides rpc.rpc functionality to it
 
-    This class starts a none blocking thread the api server runs within
+    This class starts a non-blocking thread the api server runs within
     """
 
-    def rpc_catch_errors(func):
-
-        def func_wrapper(self, *args, **kwargs):
-
-            try:
-                return func(self, *args, **kwargs)
-            except RPCException as e:
-                logger.exception("API Error calling %s: %s", func.__name__, e)
-                return self.rest_error(f"Error querying {func.__name__}: {e}")
-
-        return func_wrapper
-
     def check_auth(self, username, password):
-        return (username == self._config['api_server'].get('username') and
-                password == self._config['api_server'].get('password'))
-
-    def require_login(func):
-
-        def func_wrapper(self, *args, **kwargs):
-
-            auth = request.authorization
-            if auth and self.check_auth(auth.username, auth.password):
-                return func(self, *args, **kwargs)
-            else:
-                return jsonify({"error": "Unauthorized"}), 401
-
-        return func_wrapper
+        return (safe_str_cmp(username, self._config['api_server'].get('username')) and
+                safe_str_cmp(password, self._config['api_server'].get('password')))
 
     def __init__(self, freqtrade) -> None:
         """
@@ -79,11 +100,27 @@ class ApiServer(RPC):
 
         self._config = freqtrade.config
         self.app = Flask(__name__)
-        self.app.json_encoder = ArrowJSONEncoder
+        self._cors = CORS(self.app,
+                          resources={r"/api/*": {
+                              "supports_credentials": True,
+                              "origins": self._config['api_server'].get('CORS_origins', [])}}
+                          )
+
+        # Setup the Flask-JWT-Extended extension
+        self.app.config['JWT_SECRET_KEY'] = self._config['api_server'].get(
+            'jwt_secret_key', 'super-secret')
+
+        self.jwt = JWTManager(self.app)
+        self.app.json_encoder = FTJSONEncoder
+
+        self.app.teardown_appcontext(shutdown_session)
 
         # Register application handling
         self.register_rest_rpc_urls()
 
+        if self._config.get('fiat_display_currency', None):
+            self._fiat_converter = CryptoToFiatConverter()
+
         thread = threading.Thread(target=self.run, daemon=True)
         thread.start()
 
@@ -126,16 +163,12 @@ class ApiServer(RPC):
         """
         pass
 
-    def rest_dump(self, return_value):
-        """ Helper function to jsonify object for a webserver """
-        return jsonify(return_value)
-
-    def rest_error(self, error_msg):
-        return jsonify({"error": error_msg}), 502
+    def rest_error(self, error_msg, error_code=502):
+        return jsonify({"error": error_msg}), error_code
 
     def register_rest_rpc_urls(self):
         """
-        Registers flask app URLs that are calls to functonality in rpc.rpc.
+        Registers flask app URLs that are calls to functionality in rpc.rpc.
 
         First two arguments passed are /URL and 'Label'
         Label can be used as a shortcut when refactoring
@@ -144,19 +177,25 @@ class ApiServer(RPC):
         self.app.register_error_handler(404, self.page_not_found)
 
         # Actions to control the bot
+        self.app.add_url_rule(f'{BASE_URI}/token/login', 'login',
+                              view_func=self._token_login, methods=['POST'])
+        self.app.add_url_rule(f'{BASE_URI}/token/refresh', 'token_refresh',
+                              view_func=self._token_refresh, methods=['POST'])
         self.app.add_url_rule(f'{BASE_URI}/start', 'start',
                               view_func=self._start, methods=['POST'])
         self.app.add_url_rule(f'{BASE_URI}/stop', 'stop', view_func=self._stop, methods=['POST'])
         self.app.add_url_rule(f'{BASE_URI}/stopbuy', 'stopbuy',
                               view_func=self._stopbuy, methods=['POST'])
-        self.app.add_url_rule(f'{BASE_URI}/reload_conf', 'reload_conf',
-                              view_func=self._reload_conf, methods=['POST'])
+        self.app.add_url_rule(f'{BASE_URI}/reload_config', 'reload_config',
+                              view_func=self._reload_config, methods=['POST'])
         # Info commands
         self.app.add_url_rule(f'{BASE_URI}/balance', 'balance',
                               view_func=self._balance, methods=['GET'])
         self.app.add_url_rule(f'{BASE_URI}/count', 'count', view_func=self._count, methods=['GET'])
+        self.app.add_url_rule(f'{BASE_URI}/locks', 'locks', view_func=self._locks, methods=['GET'])
         self.app.add_url_rule(f'{BASE_URI}/daily', 'daily', view_func=self._daily, methods=['GET'])
         self.app.add_url_rule(f'{BASE_URI}/edge', 'edge', view_func=self._edge, methods=['GET'])
+        self.app.add_url_rule(f'{BASE_URI}/logs', 'log', view_func=self._get_logs, methods=['GET'])
         self.app.add_url_rule(f'{BASE_URI}/profit', 'profit',
                               view_func=self._profit, methods=['GET'])
         self.app.add_url_rule(f'{BASE_URI}/performance', 'performance',
@@ -165,6 +204,27 @@ class ApiServer(RPC):
                               view_func=self._status, methods=['GET'])
         self.app.add_url_rule(f'{BASE_URI}/version', 'version',
                               view_func=self._version, methods=['GET'])
+        self.app.add_url_rule(f'{BASE_URI}/show_config', 'show_config',
+                              view_func=self._show_config, methods=['GET'])
+        self.app.add_url_rule(f'{BASE_URI}/ping', 'ping',
+                              view_func=self._ping, methods=['GET'])
+        self.app.add_url_rule(f'{BASE_URI}/trades', 'trades',
+                              view_func=self._trades, methods=['GET'])
+        self.app.add_url_rule(f'{BASE_URI}/trades/<int:tradeid>', 'trades_delete',
+                              view_func=self._trades_delete, methods=['DELETE'])
+
+        self.app.add_url_rule(f'{BASE_URI}/pair_candles', 'pair_candles',
+                              view_func=self._analysed_candles, methods=['GET'])
+        self.app.add_url_rule(f'{BASE_URI}/pair_history', 'pair_history',
+                              view_func=self._analysed_history, methods=['GET'])
+        self.app.add_url_rule(f'{BASE_URI}/plot_config', 'plot_config',
+                              view_func=self._plot_config, methods=['GET'])
+        self.app.add_url_rule(f'{BASE_URI}/strategies', 'strategies',
+                              view_func=self._list_strategies, methods=['GET'])
+        self.app.add_url_rule(f'{BASE_URI}/strategy/<string:strategy>', 'strategy',
+                              view_func=self._get_strategy, methods=['GET'])
+        self.app.add_url_rule(f'{BASE_URI}/available_pairs', 'pairs',
+                              view_func=self._list_available_pairs, methods=['GET'])
 
         # Combined actions and infos
         self.app.add_url_rule(f'{BASE_URI}/blacklist', 'blacklist', view_func=self._blacklist,
@@ -176,20 +236,48 @@ class ApiServer(RPC):
         self.app.add_url_rule(f'{BASE_URI}/forcesell', 'forcesell', view_func=self._forcesell,
                               methods=['POST'])
 
-        # TODO: Implement the following
-        # help (?)
-
     @require_login
     def page_not_found(self, error):
         """
         Return "404 not found", 404.
         """
-        return self.rest_dump({
+        return jsonify({
             'status': 'error',
             'reason': f"There's no API call for {request.base_url}.",
             'code': 404
         }), 404
 
+    @require_login
+    @rpc_catch_errors
+    def _token_login(self):
+        """
+        Handler for /token/login
+        Returns a JWT token
+        """
+        auth = request.authorization
+        if auth and self.check_auth(auth.username, auth.password):
+            keystuff = {'u': auth.username}
+            ret = {
+                'access_token': create_access_token(identity=keystuff),
+                'refresh_token': create_refresh_token(identity=keystuff),
+            }
+            return jsonify(ret)
+
+        return jsonify({"error": "Unauthorized"}), 401
+
+    @jwt_refresh_token_required
+    @rpc_catch_errors
+    def _token_refresh(self):
+        """
+        Handler for /token/refresh
+        Returns a JWT token based on a JWT refresh token
+        """
+        current_user = get_jwt_identity()
+        new_token = create_access_token(identity=current_user, fresh=False)
+
+        ret = {'access_token': new_token}
+        return jsonify(ret)
+
     @require_login
     @rpc_catch_errors
     def _start(self):
@@ -198,7 +286,7 @@ class ApiServer(RPC):
         Starts TradeThread in bot if stopped.
         """
         msg = self._rpc_start()
-        return self.rest_dump(msg)
+        return jsonify(msg)
 
     @require_login
     @rpc_catch_errors
@@ -208,7 +296,7 @@ class ApiServer(RPC):
         Stops TradeThread in bot if running
         """
         msg = self._rpc_stop()
-        return self.rest_dump(msg)
+        return jsonify(msg)
 
     @require_login
     @rpc_catch_errors
@@ -218,7 +306,14 @@ class ApiServer(RPC):
         Sets max_open_trades to 0 and gracefully sells all open trades
         """
         msg = self._rpc_stopbuy()
-        return self.rest_dump(msg)
+        return jsonify(msg)
+
+    @rpc_catch_errors
+    def _ping(self):
+        """
+        simple ping version
+        """
+        return jsonify({"status": "pong"})
 
     @require_login
     @rpc_catch_errors
@@ -226,17 +321,25 @@ class ApiServer(RPC):
         """
         Prints the bot's version
         """
-        return self.rest_dump({"version": __version__})
+        return jsonify({"version": __version__})
 
     @require_login
     @rpc_catch_errors
-    def _reload_conf(self):
+    def _show_config(self):
         """
-        Handler for /reload_conf.
+        Prints the bot's version
+        """
+        return jsonify(RPC._rpc_show_config(self._config, self._freqtrade.state))
+
+    @require_login
+    @rpc_catch_errors
+    def _reload_config(self):
+        """
+        Handler for /reload_config.
         Triggers a config file reload
         """
-        msg = self._rpc_reload_conf()
-        return self.rest_dump(msg)
+        msg = self._rpc_reload_config()
+        return jsonify(msg)
 
     @require_login
     @rpc_catch_errors
@@ -246,7 +349,16 @@ class ApiServer(RPC):
         Returns the number of trades running
         """
         msg = self._rpc_count()
-        return self.rest_dump(msg)
+        return jsonify(msg)
+
+    @require_login
+    @rpc_catch_errors
+    def _locks(self):
+        """
+        Handler for /locks.
+        Returns the currently active locks.
+        """
+        return jsonify(self._rpc_locks())
 
     @require_login
     @rpc_catch_errors
@@ -261,10 +373,22 @@ class ApiServer(RPC):
 
         stats = self._rpc_daily_profit(timescale,
                                        self._config['stake_currency'],
-                                       self._config['fiat_display_currency']
+                                       self._config.get('fiat_display_currency', '')
                                        )
 
-        return self.rest_dump(stats)
+        return jsonify(stats)
+
+    @require_login
+    @rpc_catch_errors
+    def _get_logs(self):
+        """
+        Returns latest logs
+         get:
+          param:
+            limit: Only get a certain number of records
+        """
+        limit = int(request.args.get('limit', 0)) or None
+        return jsonify(self._rpc_get_logs(limit))
 
     @require_login
     @rpc_catch_errors
@@ -275,7 +399,7 @@ class ApiServer(RPC):
         """
         stats = self._rpc_edge()
 
-        return self.rest_dump(stats)
+        return jsonify(stats)
 
     @require_login
     @rpc_catch_errors
@@ -286,13 +410,12 @@ class ApiServer(RPC):
         Returns a cumulative profit statistics
         :return: stats
         """
-        logger.info("LocalRPC - Profit Command Called")
 
         stats = self._rpc_trade_statistics(self._config['stake_currency'],
-                                           self._config['fiat_display_currency']
+                                           self._config.get('fiat_display_currency')
                                            )
 
-        return self.rest_dump(stats)
+        return jsonify(stats)
 
     @require_login
     @rpc_catch_errors
@@ -303,11 +426,9 @@ class ApiServer(RPC):
         Returns a cumulative performance statistics
         :return: stats
         """
-        logger.info("LocalRPC - performance Command Called")
-
         stats = self._rpc_performance()
 
-        return self.rest_dump(stats)
+        return jsonify(stats)
 
     @require_login
     @rpc_catch_errors
@@ -317,8 +438,11 @@ class ApiServer(RPC):
 
         Returns the current status of the trades in json format
         """
-        results = self._rpc_trade_status()
-        return self.rest_dump(results)
+        try:
+            results = self._rpc_trade_status()
+            return jsonify(results)
+        except RPCException:
+            return jsonify([])
 
     @require_login
     @rpc_catch_errors
@@ -328,8 +452,34 @@ class ApiServer(RPC):
 
         Returns the current status of the trades in json format
         """
-        results = self._rpc_balance(self._config.get('fiat_display_currency', ''))
-        return self.rest_dump(results)
+        results = self._rpc_balance(self._config['stake_currency'],
+                                    self._config.get('fiat_display_currency', ''))
+        return jsonify(results)
+
+    @require_login
+    @rpc_catch_errors
+    def _trades(self):
+        """
+        Handler for /trades.
+
+        Returns the X last trades in json format
+        """
+        limit = int(request.args.get('limit', 0))
+        results = self._rpc_trade_history(limit)
+        return jsonify(results)
+
+    @require_login
+    @rpc_catch_errors
+    def _trades_delete(self, tradeid):
+        """
+        Handler for DELETE /trades/<tradeid> endpoint.
+        Removes the trade from the database (tries to cancel open orders first!)
+        get:
+          param:
+            tradeid: Numeric trade-id assigned to the trade.
+        """
+        result = self._rpc_delete(tradeid)
+        return jsonify(result)
 
     @require_login
     @rpc_catch_errors
@@ -338,7 +488,7 @@ class ApiServer(RPC):
         Handler for /whitelist.
         """
         results = self._rpc_whitelist()
-        return self.rest_dump(results)
+        return jsonify(results)
 
     @require_login
     @rpc_catch_errors
@@ -348,7 +498,7 @@ class ApiServer(RPC):
         """
         add = request.json.get("blacklist", None) if request.method == 'POST' else None
         results = self._rpc_blacklist(add)
-        return self.rest_dump(results)
+        return jsonify(results)
 
     @require_login
     @rpc_catch_errors
@@ -358,11 +508,13 @@ class ApiServer(RPC):
         """
         asset = request.json.get("pair")
         price = request.json.get("price", None)
+        price = float(price) if price is not None else price
+
         trade = self._rpc_forcebuy(asset, price)
         if trade:
-            return self.rest_dump(trade.to_json())
+            return jsonify(trade.to_json())
         else:
-            return self.rest_dump({"status": f"Error buying pair {asset}."})
+            return jsonify({"status": f"Error buying pair {asset}."})
 
     @require_login
     @rpc_catch_errors
@@ -372,4 +524,132 @@ class ApiServer(RPC):
         """
         tradeid = request.json.get("tradeid")
         results = self._rpc_forcesell(tradeid)
-        return self.rest_dump(results)
+        return jsonify(results)
+
+    @require_login
+    @rpc_catch_errors
+    def _analysed_candles(self):
+        """
+        Handler for /pair_candles.
+        Returns the dataframe the bot is using during live/dry operations.
+        Takes the following get arguments:
+        get:
+          parameters:
+            - pair: Pair
+            - timeframe: Timeframe to get data for (should be aligned to strategy.timeframe)
+            - limit: Limit return length to the latest X candles
+        """
+        pair = request.args.get("pair")
+        timeframe = request.args.get("timeframe")
+        limit = request.args.get("limit", type=int)
+        if not pair or not timeframe:
+            return self.rest_error("Mandatory parameter missing.", 400)
+
+        results = self._rpc_analysed_dataframe(pair, timeframe, limit)
+        return jsonify(results)
+
+    @require_login
+    @rpc_catch_errors
+    def _analysed_history(self):
+        """
+        Handler for /pair_history.
+        Returns the dataframe of a given timerange
+        Takes the following get arguments:
+        get:
+          parameters:
+            - pair: Pair
+            - timeframe: Timeframe to get data for (should be aligned to strategy.timeframe)
+            - strategy: Strategy to use - Must exist in configured strategy-path!
+            - timerange: timerange in the format YYYYMMDD-YYYYMMDD (YYYYMMDD- or (-YYYYMMDD))
+                         are als possible. If omitted uses all available data.
+        """
+        pair = request.args.get("pair")
+        timeframe = request.args.get("timeframe")
+        timerange = request.args.get("timerange")
+        strategy = request.args.get("strategy")
+
+        if not pair or not timeframe or not timerange or not strategy:
+            return self.rest_error("Mandatory parameter missing.", 400)
+
+        config = deepcopy(self._config)
+        config.update({
+            'strategy': strategy,
+        })
+        results = RPC._rpc_analysed_history_full(config, pair, timeframe, timerange)
+        return jsonify(results)
+
+    @require_login
+    @rpc_catch_errors
+    def _plot_config(self):
+        """
+        Handler for /plot_config.
+        """
+        return jsonify(self._rpc_plot_config())
+
+    @require_login
+    @rpc_catch_errors
+    def _list_strategies(self):
+        directory = Path(self._config.get(
+            'strategy_path', self._config['user_data_dir'] / USERPATH_STRATEGIES))
+        from freqtrade.resolvers.strategy_resolver import StrategyResolver
+        strategy_objs = StrategyResolver.search_all_objects(directory, False)
+        strategy_objs = sorted(strategy_objs, key=lambda x: x['name'])
+
+        return jsonify({'strategies': [x['name'] for x in strategy_objs]})
+
+    @require_login
+    @rpc_catch_errors
+    def _get_strategy(self, strategy: str):
+        """
+        Get a single strategy
+        get:
+          parameters:
+            - strategy: Only get this strategy
+        """
+        config = deepcopy(self._config)
+        from freqtrade.resolvers.strategy_resolver import StrategyResolver
+        try:
+            strategy_obj = StrategyResolver._load_strategy(strategy, config,
+                                                           extra_dir=config.get('strategy_path'))
+        except OperationalException:
+            return self.rest_error("Strategy not found.", 404)
+
+        return jsonify({
+            'strategy': strategy_obj.get_strategy_name(),
+            'code': strategy_obj.__source__,
+         })
+
+    @require_login
+    @rpc_catch_errors
+    def _list_available_pairs(self):
+        """
+        Handler for /available_pairs.
+        Returns an object, with pairs, available pair length and pair_interval combinations
+        Takes the following get arguments:
+        get:
+          parameters:
+            - stake_currency: Filter on this stake currency
+            - timeframe: Timeframe to get data for Filter elements to this timeframe
+        """
+        timeframe = request.args.get("timeframe")
+        stake_currency = request.args.get("stake_currency")
+
+        from freqtrade.data.history import get_datahandler
+        dh = get_datahandler(self._config['datadir'], self._config.get('dataformat_ohlcv', None))
+
+        pair_interval = dh.ohlcv_get_available_data(self._config['datadir'])
+
+        if timeframe:
+            pair_interval = [pair for pair in pair_interval if pair[1] == timeframe]
+        if stake_currency:
+            pair_interval = [pair for pair in pair_interval if pair[0].endswith(stake_currency)]
+        pair_interval = sorted(pair_interval, key=lambda x: x[0])
+
+        pairs = list({x[0] for x in pair_interval})
+
+        result = {
+            'length': len(pairs),
+            'pairs': pairs,
+            'pair_interval': pair_interval,
+        }
+        return jsonify(result)
diff --git a/freqtrade/rpc/fiat_convert.py b/freqtrade/rpc/fiat_convert.py
index 6812bf77f..4e26432d4 100644
--- a/freqtrade/rpc/fiat_convert.py
+++ b/freqtrade/rpc/fiat_convert.py
@@ -7,7 +7,7 @@ import logging
 import time
 from typing import Dict, List
 
-from coinmarketcap import Market
+from pycoingecko import CoinGeckoAPI
 
 from freqtrade.constants import SUPPORTED_FIAT
 
@@ -15,7 +15,7 @@ from freqtrade.constants import SUPPORTED_FIAT
 logger = logging.getLogger(__name__)
 
 
-class CryptoFiat(object):
+class CryptoFiat:
     """
     Object to describe what is the price of Crypto-currency in a FIAT
     """
@@ -38,8 +38,8 @@ class CryptoFiat(object):
         # Private attributes
         self._expiration = 0.0
 
-        self.crypto_symbol = crypto_symbol.upper()
-        self.fiat_symbol = fiat_symbol.upper()
+        self.crypto_symbol = crypto_symbol.lower()
+        self.fiat_symbol = fiat_symbol.lower()
         self.set_price(price=price)
 
     def set_price(self, price: float) -> None:
@@ -60,24 +60,27 @@ class CryptoFiat(object):
         return self._expiration - time.time() <= 0
 
 
-class CryptoToFiatConverter(object):
+class CryptoToFiatConverter:
     """
     Main class to initiate Crypto to FIAT.
     This object contains a list of pair Crypto, FIAT
     This object is also a Singleton
     """
     __instance = None
-    _coinmarketcap: Market = None
+    _coingekko: CoinGeckoAPI = None
 
     _cryptomap: Dict = {}
 
     def __new__(cls):
+        """
+        This class is a singleton - cannot be instantiated twice.
+        """
         if CryptoToFiatConverter.__instance is None:
             CryptoToFiatConverter.__instance = object.__new__(cls)
             try:
-                CryptoToFiatConverter._coinmarketcap = Market()
+                CryptoToFiatConverter._coingekko = CoinGeckoAPI()
             except BaseException:
-                CryptoToFiatConverter._coinmarketcap = None
+                CryptoToFiatConverter._coingekko = None
         return CryptoToFiatConverter.__instance
 
     def __init__(self) -> None:
@@ -86,14 +89,12 @@ class CryptoToFiatConverter(object):
 
     def _load_cryptomap(self) -> None:
         try:
-            coinlistings = self._coinmarketcap.listings()
-            self._cryptomap = dict(map(lambda coin: (coin["symbol"], str(coin["id"])),
-                                       coinlistings["data"]))
-        except (BaseException) as exception:
+            coinlistings = self._coingekko.get_coins_list()
+            # Create mapping table from synbol to coingekko_id
+            self._cryptomap = {x['symbol']: x['id'] for x in coinlistings}
+        except (Exception) as exception:
             logger.error(
-                "Could not load FIAT Cryptocurrency map for the following problem: %s",
-                type(exception).__name__
-            )
+                f"Could not load FIAT Cryptocurrency map for the following problem: {exception}")
 
     def convert_amount(self, crypto_amount: float, crypto_symbol: str, fiat_symbol: str) -> float:
         """
@@ -104,7 +105,7 @@ class CryptoToFiatConverter(object):
         :return: float, value in fiat of the crypto-currency amount
         """
         if crypto_symbol == fiat_symbol:
-            return crypto_amount
+            return float(crypto_amount)
         price = self.get_price(crypto_symbol=crypto_symbol, fiat_symbol=fiat_symbol)
         return float(crypto_amount) * float(price)
 
@@ -115,8 +116,8 @@ class CryptoToFiatConverter(object):
         :param fiat_symbol: FIAT currency you want to convert to (e.g USD)
         :return: Price in FIAT
         """
-        crypto_symbol = crypto_symbol.upper()
-        fiat_symbol = fiat_symbol.upper()
+        crypto_symbol = crypto_symbol.lower()
+        fiat_symbol = fiat_symbol.lower()
 
         # Check if the fiat convertion you want is supported
         if not self._is_supported_fiat(fiat=fiat_symbol):
@@ -170,15 +171,13 @@ class CryptoToFiatConverter(object):
         :return: bool, True supported, False not supported
         """
 
-        fiat = fiat.upper()
-
-        return fiat in SUPPORTED_FIAT
+        return fiat.upper() in SUPPORTED_FIAT
 
     def _find_price(self, crypto_symbol: str, fiat_symbol: str) -> float:
         """
-        Call CoinMarketCap API to retrieve the price in the FIAT
-        :param crypto_symbol: Crypto-currency you want to convert (e.g BTC)
-        :param fiat_symbol: FIAT currency you want to convert to (e.g USD)
+        Call CoinGekko API to retrieve the price in the FIAT
+        :param crypto_symbol: Crypto-currency you want to convert (e.g btc)
+        :param fiat_symbol: FIAT currency you want to convert to (e.g usd)
         :return: float, price of the crypto-currency in Fiat
         """
         # Check if the fiat convertion you want is supported
@@ -195,12 +194,13 @@ class CryptoToFiatConverter(object):
             return 0.0
 
         try:
+            _gekko_id = self._cryptomap[crypto_symbol]
             return float(
-                self._coinmarketcap.ticker(
-                    currency=self._cryptomap[crypto_symbol],
-                    convert=fiat_symbol
-                )['data']['quotes'][fiat_symbol.upper()]['price']
+                self._coingekko.get_price(
+                    ids=_gekko_id,
+                    vs_currencies=fiat_symbol
+                )[_gekko_id][fiat_symbol]
             )
-        except BaseException as exception:
+        except Exception as exception:
             logger.error("Error in _find_price: %s", exception)
             return 0.0
diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index f77e0eddb..e608a2274 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -3,36 +3,46 @@ This module contains class to define a RPC communications
 """
 import logging
 from abc import abstractmethod
-from datetime import timedelta, datetime, date
-from decimal import Decimal
+from datetime import date, datetime, timedelta
 from enum import Enum
-from typing import Dict, Any, List, Optional
+from math import isnan
+from typing import Any, Dict, List, Optional, Tuple, Union
 
 import arrow
-import sqlalchemy as sql
-from numpy import mean, nan_to_num, NAN
+from numpy import NAN, int64, mean
 from pandas import DataFrame
 
-from freqtrade import TemporaryError, DependencyException
+from freqtrade.configuration.timerange import TimeRange
+from freqtrade.constants import CANCEL_REASON, DATETIME_PRINT_FORMAT
+from freqtrade.data.history import load_data
+from freqtrade.exceptions import ExchangeError, PricingError
+from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs
+from freqtrade.loggers import bufferHandler
 from freqtrade.misc import shorten_date
-from freqtrade.persistence import Trade
+from freqtrade.persistence import PairLocks, Trade
 from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
 from freqtrade.state import State
 from freqtrade.strategy.interface import SellType
 
+
 logger = logging.getLogger(__name__)
 
 
 class RPCMessageType(Enum):
     STATUS_NOTIFICATION = 'status'
     WARNING_NOTIFICATION = 'warning'
-    CUSTOM_NOTIFICATION = 'custom'
+    STARTUP_NOTIFICATION = 'startup'
     BUY_NOTIFICATION = 'buy'
+    BUY_CANCEL_NOTIFICATION = 'buy_cancel'
     SELL_NOTIFICATION = 'sell'
+    SELL_CANCEL_NOTIFICATION = 'sell_cancel'
 
     def __repr__(self):
         return self.value
 
+    def __str__(self):
+        return self.value
+
 
 class RPCException(Exception):
     """
@@ -41,6 +51,7 @@ class RPCException(Exception):
 
     raise RPCException('*Status:* `no active trade`')
     """
+
     def __init__(self, message: str) -> None:
         super().__init__(self)
         self.message = message
@@ -54,7 +65,7 @@ class RPCException(Exception):
         }
 
 
-class RPC(object):
+class RPC:
     """
     RPC class can be used to have extra feature, like bot data, and access to DB data
     """
@@ -82,6 +93,39 @@ class RPC(object):
     def send_msg(self, msg: Dict[str, str]) -> None:
         """ Sends a message to all registered rpc modules """
 
+    @staticmethod
+    def _rpc_show_config(config, botstate: State) -> Dict[str, Any]:
+        """
+        Return a dict of config options.
+        Explicitly does NOT return the full config to avoid leakage of sensitive
+        information via rpc.
+        """
+        val = {
+            'dry_run': config['dry_run'],
+            'stake_currency': config['stake_currency'],
+            'stake_amount': config['stake_amount'],
+            'max_open_trades': config['max_open_trades'],
+            'minimal_roi': config['minimal_roi'].copy() if 'minimal_roi' in config else {},
+            'stoploss': config.get('stoploss'),
+            'trailing_stop': config.get('trailing_stop'),
+            'trailing_stop_positive': config.get('trailing_stop_positive'),
+            'trailing_stop_positive_offset': config.get('trailing_stop_positive_offset'),
+            'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached'),
+            'timeframe': config.get('timeframe'),
+            'timeframe_ms': timeframe_to_msecs(config['timeframe']
+                                               ) if 'timeframe' in config else '',
+            'timeframe_min': timeframe_to_minutes(config['timeframe']
+                                                  ) if 'timeframe' in config else '',
+            'exchange': config['exchange']['name'],
+            'strategy': config['strategy'],
+            'forcebuy_enabled': config.get('forcebuy_enable', False),
+            'ask_strategy': config.get('ask_strategy', {}),
+            'bid_strategy': config.get('bid_strategy', {}),
+            'state': str(botstate),
+            'runmode': config['runmode'].value
+        }
+        return val
+
     def _rpc_trade_status(self) -> List[Dict[str, Any]]:
         """
         Below follows the RPC backend it is prefixed with rpc_ to raise awareness that it is
@@ -96,21 +140,38 @@ class RPC(object):
             for trade in trades:
                 order = None
                 if trade.open_order_id:
-                    order = self._freqtrade.exchange.get_order(trade.open_order_id, trade.pair)
+                    order = self._freqtrade.exchange.fetch_order(trade.open_order_id, trade.pair)
                 # calculate profit and send message to user
                 try:
                     current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
-                except DependencyException:
+                except (ExchangeError, PricingError):
                     current_rate = NAN
-                current_profit = trade.calc_profit_percent(current_rate)
-                fmt_close_profit = (f'{round(trade.close_profit * 100, 2):.2f}%'
-                                    if trade.close_profit else None)
+                current_profit = trade.calc_profit_ratio(current_rate)
+                current_profit_abs = trade.calc_profit(current_rate)
+                # Calculate guaranteed profit (in case of trailing stop)
+                stoploss_entry_dist = trade.calc_profit(trade.stop_loss)
+                stoploss_entry_dist_ratio = trade.calc_profit_ratio(trade.stop_loss)
+                # calculate distance to stoploss
+                stoploss_current_dist = trade.stop_loss - current_rate
+                stoploss_current_dist_ratio = stoploss_current_dist / current_rate
+
                 trade_dict = trade.to_json()
                 trade_dict.update(dict(
                     base_currency=self._freqtrade.config['stake_currency'],
-                    close_profit=fmt_close_profit,
+                    close_profit=trade.close_profit if trade.close_profit is not None else None,
                     current_rate=current_rate,
-                    current_profit=round(current_profit * 100, 2),
+                    current_profit=current_profit,  # Deprectated
+                    current_profit_pct=round(current_profit * 100, 2),  # Deprectated
+                    current_profit_abs=current_profit_abs,  # Deprectated
+                    profit_ratio=current_profit,
+                    profit_pct=round(current_profit * 100, 2),
+                    profit_abs=current_profit_abs,
+
+                    stoploss_current_dist=stoploss_current_dist,
+                    stoploss_current_dist_ratio=round(stoploss_current_dist_ratio, 8),
+                    stoploss_current_dist_pct=round(stoploss_current_dist_ratio * 100, 2),
+                    stoploss_entry_dist=stoploss_entry_dist,
+                    stoploss_entry_dist_ratio=round(stoploss_entry_dist_ratio, 8),
                     open_order='({} {} rem={:.8f})'.format(
                         order['type'], order['side'], order['remaining']
                     ) if order else None,
@@ -118,34 +179,48 @@ class RPC(object):
                 results.append(trade_dict)
             return results
 
-    def _rpc_status_table(self) -> DataFrame:
+    def _rpc_status_table(self, stake_currency: str,
+                          fiat_display_currency: str) -> Tuple[List, List]:
         trades = Trade.get_open_trades()
         if not trades:
-            raise RPCException('no active order')
+            raise RPCException('no active trade')
         else:
             trades_list = []
             for trade in trades:
                 # calculate profit and send message to user
                 try:
                     current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
-                except DependencyException:
+                except (PricingError, ExchangeError):
                     current_rate = NAN
-                trade_perc = (100 * trade.calc_profit_percent(current_rate))
+                trade_percent = (100 * trade.calc_profit_ratio(current_rate))
+                trade_profit = trade.calc_profit(current_rate)
+                profit_str = f'{trade_percent:.2f}%'
+                if self._fiat_converter:
+                    fiat_profit = self._fiat_converter.convert_amount(
+                        trade_profit,
+                        stake_currency,
+                        fiat_display_currency
+                    )
+                    if fiat_profit and not isnan(fiat_profit):
+                        profit_str += f" ({fiat_profit:.2f})"
                 trades_list.append([
                     trade.id,
-                    trade.pair,
+                    trade.pair + ('*' if (trade.open_order_id is not None
+                                          and trade.close_rate_requested is None) else '')
+                               + ('**' if (trade.close_rate_requested is not None) else ''),
                     shorten_date(arrow.get(trade.open_date).humanize(only_distance=True)),
-                    f'{trade_perc:.2f}%'
+                    profit_str
                 ])
+            profitcol = "Profit"
+            if self._fiat_converter:
+                profitcol += " (" + fiat_display_currency + ")"
 
-            columns = ['ID', 'Pair', 'Since', 'Profit']
-            df_statuses = DataFrame.from_records(trades_list, columns=columns)
-            df_statuses = df_statuses.set_index(columns[0])
-            return df_statuses
+            columns = ['ID', 'Pair', 'Since', profitcol]
+            return trades_list, columns
 
     def _rpc_daily_profit(
             self, timescale: int,
-            stake_currency: str, fiat_display_currency: str) -> List[List[Any]]:
+            stake_currency: str, fiat_display_currency: str) -> Dict[str, Any]:
         today = datetime.utcnow().date()
         profit_days: Dict[date, Dict] = {}
 
@@ -154,51 +229,64 @@ class RPC(object):
 
         for day in range(0, timescale):
             profitday = today - timedelta(days=day)
-            trades = Trade.query \
-                .filter(Trade.is_open.is_(False)) \
-                .filter(Trade.close_date >= profitday)\
-                .filter(Trade.close_date < (profitday + timedelta(days=1)))\
-                .order_by(Trade.close_date)\
-                .all()
-            curdayprofit = sum(trade.calc_profit() for trade in trades)
+            trades = Trade.get_trades(trade_filter=[
+                Trade.is_open.is_(False),
+                Trade.close_date >= profitday,
+                Trade.close_date < (profitday + timedelta(days=1))
+            ]).order_by(Trade.close_date).all()
+            curdayprofit = sum(
+                trade.close_profit_abs for trade in trades if trade.close_profit_abs is not None)
             profit_days[profitday] = {
-                'amount': f'{curdayprofit:.8f}',
+                'amount': curdayprofit,
                 'trades': len(trades)
             }
 
-        return [
-            [
-                key,
-                '{value:.8f} {symbol}'.format(
-                    value=float(value['amount']),
-                    symbol=stake_currency
-                ),
-                '{value:.3f} {symbol}'.format(
-                    value=self._fiat_converter.convert_amount(
+        data = [
+            {
+                'date': key,
+                'abs_profit': value["amount"],
+                'fiat_value': self._fiat_converter.convert_amount(
                         value['amount'],
                         stake_currency,
                         fiat_display_currency
                     ) if self._fiat_converter else 0,
-                    symbol=fiat_display_currency
-                ),
-                '{value} trade{s}'.format(
-                    value=value['trades'],
-                    s='' if value['trades'] < 2 else 's'
-                ),
-            ]
+                'trade_count': value["trades"],
+            }
             for key, value in profit_days.items()
         ]
+        return {
+            'stake_currency': stake_currency,
+            'fiat_display_currency': fiat_display_currency,
+            'data': data
+        }
+
+    def _rpc_trade_history(self, limit: int) -> Dict:
+        """ Returns the X last trades """
+        if limit > 0:
+            trades = Trade.get_trades([Trade.is_open.is_(False)]).order_by(
+                Trade.id.desc()).limit(limit)
+        else:
+            trades = Trade.get_trades([Trade.is_open.is_(False)]).order_by(Trade.id.desc()).all()
+
+        output = [trade.to_json() for trade in trades]
+
+        return {
+            "trades": output,
+            "trades_count": len(output)
+        }
 
     def _rpc_trade_statistics(
             self, stake_currency: str, fiat_display_currency: str) -> Dict[str, Any]:
         """ Returns cumulative profit statistics """
-        trades = Trade.query.order_by(Trade.id).all()
+        trades = Trade.get_trades().order_by(Trade.id).all()
 
         profit_all_coin = []
-        profit_all_percent = []
+        profit_all_ratio = []
         profit_closed_coin = []
-        profit_closed_percent = []
+        profit_closed_ratio = []
         durations = []
+        winning_trades = 0
+        losing_trades = 0
 
         for trade in trades:
             current_rate: float = 0.0
@@ -209,36 +297,33 @@ class RPC(object):
                 durations.append((trade.close_date - trade.open_date).total_seconds())
 
             if not trade.is_open:
-                profit_percent = trade.calc_profit_percent()
-                profit_closed_coin.append(trade.calc_profit())
-                profit_closed_percent.append(profit_percent)
+                profit_ratio = trade.close_profit
+                profit_closed_coin.append(trade.close_profit_abs)
+                profit_closed_ratio.append(profit_ratio)
+                if trade.close_profit >= 0:
+                    winning_trades += 1
+                else:
+                    losing_trades += 1
             else:
                 # Get current rate
                 try:
                     current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
-                except DependencyException:
+                except (PricingError, ExchangeError):
                     current_rate = NAN
-                profit_percent = trade.calc_profit_percent(rate=current_rate)
+                profit_ratio = trade.calc_profit_ratio(rate=current_rate)
 
             profit_all_coin.append(
-                trade.calc_profit(rate=Decimal(trade.close_rate or current_rate))
+                trade.calc_profit(rate=trade.close_rate or current_rate)
             )
-            profit_all_percent.append(profit_percent)
+            profit_all_ratio.append(profit_ratio)
 
-        best_pair = Trade.session.query(
-            Trade.pair, sql.func.sum(Trade.close_profit).label('profit_sum')
-        ).filter(Trade.is_open.is_(False)) \
-            .group_by(Trade.pair) \
-            .order_by(sql.text('profit_sum DESC')).first()
-
-        if not best_pair:
-            raise RPCException('no closed trade')
-
-        bp_pair, bp_rate = best_pair
+        best_pair = Trade.get_best_pair()
 
         # Prepare data to display
         profit_closed_coin_sum = round(sum(profit_closed_coin), 8)
-        profit_closed_percent = round(nan_to_num(mean(profit_closed_percent)) * 100, 2)
+        profit_closed_ratio_mean = mean(profit_closed_ratio) if profit_closed_ratio else 0.0
+        profit_closed_ratio_sum = sum(profit_closed_ratio) if profit_closed_ratio else 0.0
+
         profit_closed_fiat = self._fiat_converter.convert_amount(
             profit_closed_coin_sum,
             stake_currency,
@@ -246,72 +331,100 @@ class RPC(object):
         ) if self._fiat_converter else 0
 
         profit_all_coin_sum = round(sum(profit_all_coin), 8)
-        profit_all_percent = round(nan_to_num(mean(profit_all_percent)) * 100, 2)
+        profit_all_ratio_mean = mean(profit_all_ratio) if profit_all_ratio else 0.0
+        profit_all_ratio_sum = sum(profit_all_ratio) if profit_all_ratio else 0.0
         profit_all_fiat = self._fiat_converter.convert_amount(
             profit_all_coin_sum,
             stake_currency,
             fiat_display_currency
         ) if self._fiat_converter else 0
 
+        first_date = trades[0].open_date if trades else None
+        last_date = trades[-1].open_date if trades else None
         num = float(len(durations) or 1)
         return {
             'profit_closed_coin': profit_closed_coin_sum,
-            'profit_closed_percent': profit_closed_percent,
+            'profit_closed_percent': round(profit_closed_ratio_mean * 100, 2),  # DEPRECATED
+            'profit_closed_percent_mean': round(profit_closed_ratio_mean * 100, 2),
+            'profit_closed_ratio_mean': profit_closed_ratio_mean,
+            'profit_closed_percent_sum': round(profit_closed_ratio_sum * 100, 2),
+            'profit_closed_ratio_sum': profit_closed_ratio_sum,
             'profit_closed_fiat': profit_closed_fiat,
             'profit_all_coin': profit_all_coin_sum,
-            'profit_all_percent': profit_all_percent,
+            'profit_all_percent': round(profit_all_ratio_mean * 100, 2),  # DEPRECATED
+            'profit_all_percent_mean': round(profit_all_ratio_mean * 100, 2),
+            'profit_all_ratio_mean': profit_all_ratio_mean,
+            'profit_all_percent_sum': round(profit_all_ratio_sum * 100, 2),
+            'profit_all_ratio_sum': profit_all_ratio_sum,
             'profit_all_fiat': profit_all_fiat,
             'trade_count': len(trades),
-            'first_trade_date': arrow.get(trades[0].open_date).humanize(),
-            'latest_trade_date': arrow.get(trades[-1].open_date).humanize(),
+            'closed_trade_count': len([t for t in trades if not t.is_open]),
+            'first_trade_date': arrow.get(first_date).humanize() if first_date else '',
+            'first_trade_timestamp': int(first_date.timestamp() * 1000) if first_date else 0,
+            'latest_trade_date': arrow.get(last_date).humanize() if last_date else '',
+            'latest_trade_timestamp': int(last_date.timestamp() * 1000) if last_date else 0,
             'avg_duration': str(timedelta(seconds=sum(durations) / num)).split('.')[0],
-            'best_pair': bp_pair,
-            'best_rate': round(bp_rate * 100, 2),
+            'best_pair': best_pair[0] if best_pair else '',
+            'best_rate': round(best_pair[1] * 100, 2) if best_pair else 0,
+            'winning_trades': winning_trades,
+            'losing_trades': losing_trades,
         }
 
-    def _rpc_balance(self, fiat_display_currency: str) -> Dict:
+    def _rpc_balance(self, stake_currency: str, fiat_display_currency: str) -> Dict:
         """ Returns current account balance per crypto """
         output = []
         total = 0.0
-        for coin, balance in self._freqtrade.exchange.get_balances().items():
-            if not balance['total']:
+        try:
+            tickers = self._freqtrade.exchange.get_tickers()
+        except (ExchangeError):
+            raise RPCException('Error getting current tickers.')
+
+        self._freqtrade.wallets.update(require_update=False)
+
+        for coin, balance in self._freqtrade.wallets.get_all_balances().items():
+            if not balance.total:
                 continue
 
-            if coin == 'BTC':
+            est_stake: float = 0
+            if coin == stake_currency:
                 rate = 1.0
+                est_stake = balance.total
             else:
                 try:
-                    pair = self._freqtrade.exchange.get_valid_pair_combination(coin, "BTC")
-                    if pair.startswith("BTC"):
-                        rate = 1.0 / self._freqtrade.get_sell_rate(pair, False)
-                    else:
-                        rate = self._freqtrade.get_sell_rate(pair, False)
-                except (TemporaryError, DependencyException):
+                    pair = self._freqtrade.exchange.get_valid_pair_combination(coin, stake_currency)
+                    rate = tickers.get(pair, {}).get('bid', None)
+                    if rate:
+                        if pair.startswith(stake_currency):
+                            rate = 1.0 / rate
+                        est_stake = rate * balance.total
+                except (ExchangeError):
                     logger.warning(f" Could not get rate for pair {coin}.")
                     continue
-            est_btc: float = rate * balance['total']
-            total = total + est_btc
+            total = total + (est_stake or 0)
             output.append({
                 'currency': coin,
-                'available': balance['free'],
-                'balance': balance['total'],
-                'pending': balance['used'],
-                'est_btc': est_btc,
+                'free': balance.free if balance.free is not None else 0,
+                'balance': balance.total if balance.total is not None else 0,
+                'used': balance.used if balance.used is not None else 0,
+                'est_stake': est_stake or 0,
+                'stake': stake_currency,
             })
         if total == 0.0:
-            if self._freqtrade.config.get('dry_run', False):
+            if self._freqtrade.config['dry_run']:
                 raise RPCException('Running in Dry Run, balances are not available.')
             else:
                 raise RPCException('All balances are zero.')
 
         symbol = fiat_display_currency
-        value = self._fiat_converter.convert_amount(total, 'BTC',
+        value = self._fiat_converter.convert_amount(total, stake_currency,
                                                     symbol) if self._fiat_converter else 0
         return {
             'currencies': output,
             'total': total,
             'symbol': symbol,
             'value': value,
+            'stake': stake_currency,
+            'note': 'Simulated balances' if self._freqtrade.config['dry_run'] else ''
         }
 
     def _rpc_start(self) -> Dict[str, str]:
@@ -330,10 +443,10 @@ class RPC(object):
 
         return {'status': 'already stopped'}
 
-    def _rpc_reload_conf(self) -> Dict[str, str]:
-        """ Handler for reload_conf. """
-        self._freqtrade.state = State.RELOAD_CONF
-        return {'status': 'reloading config ...'}
+    def _rpc_reload_config(self) -> Dict[str, str]:
+        """ Handler for reload_config. """
+        self._freqtrade.state = State.RELOAD_CONFIG
+        return {'status': 'Reloading config ...'}
 
     def _rpc_stopbuy(self) -> Dict[str, str]:
         """
@@ -343,64 +456,57 @@ class RPC(object):
             # Set 'max_open_trades' to 0
             self._freqtrade.config['max_open_trades'] = 0
 
-        return {'status': 'No more buy will occur from now. Run /reload_conf to reset.'}
+        return {'status': 'No more buy will occur from now. Run /reload_config to reset.'}
 
-    def _rpc_forcesell(self, trade_id) -> Dict[str, str]:
+    def _rpc_forcesell(self, trade_id: str) -> Dict[str, str]:
         """
         Handler for forcesell <id>.
         Sells the given trade at current price
         """
         def _exec_forcesell(trade: Trade) -> None:
             # Check if there is there is an open order
+            fully_canceled = False
             if trade.open_order_id:
-                order = self._freqtrade.exchange.get_order(trade.open_order_id, trade.pair)
+                order = self._freqtrade.exchange.fetch_order(trade.open_order_id, trade.pair)
 
-                # Cancel open LIMIT_BUY orders and close trade
-                if order and order['status'] == 'open' \
-                        and order['type'] == 'limit' \
-                        and order['side'] == 'buy':
-                    self._freqtrade.exchange.cancel_order(trade.open_order_id, trade.pair)
-                    trade.close(order.get('price') or trade.open_rate)
-                    # Do the best effort, if we don't know 'filled' amount, don't try selling
-                    if order['filled'] is None:
-                        return
-                    trade.amount = order['filled']
+                if order['side'] == 'buy':
+                    fully_canceled = self._freqtrade.handle_cancel_buy(
+                        trade, order, CANCEL_REASON['FORCE_SELL'])
 
-                # Ignore trades with an attached LIMIT_SELL order
-                if order and order['status'] == 'open' \
-                        and order['type'] == 'limit' \
-                        and order['side'] == 'sell':
-                    return
+                if order['side'] == 'sell':
+                    # Cancel order - so it is placed anew with a fresh price.
+                    self._freqtrade.handle_cancel_sell(trade, order, CANCEL_REASON['FORCE_SELL'])
 
-            # Get current rate and execute sell
-            current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
-            self._freqtrade.execute_sell(trade, current_rate, SellType.FORCE_SELL)
+            if not fully_canceled:
+                # Get current rate and execute sell
+                current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
+                self._freqtrade.execute_sell(trade, current_rate, SellType.FORCE_SELL)
         # ---- EOF def _exec_forcesell ----
 
         if self._freqtrade.state != State.RUNNING:
             raise RPCException('trader is not running')
 
-        if trade_id == 'all':
-            # Execute sell for all open orders
-            for trade in Trade.get_open_trades():
-                _exec_forcesell(trade)
+        with self._freqtrade._sell_lock:
+            if trade_id == 'all':
+                # Execute sell for all open orders
+                for trade in Trade.get_open_trades():
+                    _exec_forcesell(trade)
+                Trade.session.flush()
+                self._freqtrade.wallets.update()
+                return {'result': 'Created sell orders for all open trades.'}
+
+            # Query for trade
+            trade = Trade.get_trades(
+                trade_filter=[Trade.id == trade_id, Trade.is_open.is_(True), ]
+            ).first()
+            if not trade:
+                logger.warning('forcesell: Invalid argument received')
+                raise RPCException('invalid argument')
+
+            _exec_forcesell(trade)
             Trade.session.flush()
-            return {'result': 'Created sell orders for all open trades.'}
-
-        # Query for trade
-        trade = Trade.query.filter(
-            sql.and_(
-                Trade.id == trade_id,
-                Trade.is_open.is_(True)
-            )
-        ).first()
-        if not trade:
-            logger.warning('forcesell: Invalid argument received')
-            raise RPCException('invalid argument')
-
-        _exec_forcesell(trade)
-        Trade.session.flush()
-        return {'result': f'Created sell order for trade {trade_id}.'}
+            self._freqtrade.wallets.update()
+            return {'result': f'Created sell order for trade {trade_id}.'}
 
     def _rpc_forcebuy(self, pair: str, price: Optional[float]) -> Optional[Trade]:
         """
@@ -414,45 +520,76 @@ class RPC(object):
         if self._freqtrade.state != State.RUNNING:
             raise RPCException('trader is not running')
 
-        # Check pair is in stake currency
+        # Check if pair quote currency equals to the stake currency.
         stake_currency = self._freqtrade.config.get('stake_currency')
-        if not pair.endswith(stake_currency):
+        if not self._freqtrade.exchange.get_pair_quote_currency(pair) == stake_currency:
             raise RPCException(
-                f'Wrong pair selected. Please pairs with stake {stake_currency} pairs only')
+                f'Wrong pair selected. Only pairs with stake-currency {stake_currency} allowed.')
         # check if valid pair
 
         # check if pair already has an open pair
-        trade = Trade.query.filter(Trade.is_open.is_(True)).filter(Trade.pair.is_(pair)).first()
+        trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first()
         if trade:
             raise RPCException(f'position for {pair} already open - id: {trade.id}')
 
         # gen stake amount
-        stakeamount = self._freqtrade._get_trade_stake_amount(pair)
+        stakeamount = self._freqtrade.get_trade_stake_amount(pair)
 
         # execute buy
         if self._freqtrade.execute_buy(pair, stakeamount, price):
-            trade = Trade.query.filter(Trade.is_open.is_(True)).filter(Trade.pair.is_(pair)).first()
+            trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first()
             return trade
         else:
             return None
 
-    def _rpc_performance(self) -> List[Dict]:
+    def _rpc_delete(self, trade_id: str) -> Dict[str, Union[str, int]]:
+        """
+        Handler for delete <id>.
+        Delete the given trade and close eventually existing open orders.
+        """
+        with self._freqtrade._sell_lock:
+            c_count = 0
+            trade = Trade.get_trades(trade_filter=[Trade.id == trade_id]).first()
+            if not trade:
+                logger.warning('delete trade: Invalid argument received')
+                raise RPCException('invalid argument')
+
+            # Try cancelling regular order if that exists
+            if trade.open_order_id:
+                try:
+                    self._freqtrade.exchange.cancel_order(trade.open_order_id, trade.pair)
+                    c_count += 1
+                except (ExchangeError):
+                    pass
+
+            # cancel stoploss on exchange ...
+            if (self._freqtrade.strategy.order_types.get('stoploss_on_exchange')
+                    and trade.stoploss_order_id):
+                try:
+                    self._freqtrade.exchange.cancel_stoploss_order(trade.stoploss_order_id,
+                                                                   trade.pair)
+                    c_count += 1
+                except (ExchangeError):
+                    pass
+
+            trade.delete()
+            self._freqtrade.wallets.update()
+            return {
+                'result': 'success',
+                'trade_id': trade_id,
+                'result_msg': f'Deleted trade {trade_id}. Closed {c_count} open orders.',
+                'cancel_order_count': c_count,
+            }
+
+    def _rpc_performance(self) -> List[Dict[str, Any]]:
         """
         Handler for performance.
         Shows a performance statistic from finished trades
         """
-
-        pair_rates = Trade.session.query(Trade.pair,
-                                         sql.func.sum(Trade.close_profit).label('profit_sum'),
-                                         sql.func.count(Trade.pair).label('count')) \
-            .filter(Trade.is_open.is_(False)) \
-            .group_by(Trade.pair) \
-            .order_by(sql.text('profit_sum DESC')) \
-            .all()
-        return [
-            {'pair': pair, 'profit': round(rate * 100, 2), 'count': count}
-            for pair, rate, count in pair_rates
-        ]
+        pair_rates = Trade.get_overall_performance()
+        # Round and convert to %
+        [x.update({'profit': round(x['profit'] * 100, 2)}) for x in pair_rates]
+        return pair_rates
 
     def _rpc_count(self) -> Dict[str, float]:
         """ Returns the number of trades running """
@@ -466,9 +603,18 @@ class RPC(object):
             'total_stake': sum((trade.open_rate * trade.amount) for trade in trades)
         }
 
+    def _rpc_locks(self) -> Dict[str, Any]:
+        """ Returns the  current locks"""
+
+        locks = PairLocks.get_pair_locks(None)
+        return {
+            'lock_count': len(locks),
+            'locks': [lock.to_json() for lock in locks]
+        }
+
     def _rpc_whitelist(self) -> Dict:
         """ Returns the currently active whitelist"""
-        res = {'method': self._freqtrade.pairlists.name,
+        res = {'method': self._freqtrade.pairlists.name_list,
                'length': len(self._freqtrade.active_pair_whitelist),
                'whitelist': self._freqtrade.active_pair_whitelist
                }
@@ -476,21 +622,128 @@ class RPC(object):
 
     def _rpc_blacklist(self, add: List[str] = None) -> Dict:
         """ Returns the currently active blacklist"""
+        errors = {}
         if add:
             stake_currency = self._freqtrade.config.get('stake_currency')
             for pair in add:
-                if (pair.endswith(stake_currency)
-                        and pair not in self._freqtrade.pairlists.blacklist):
-                    self._freqtrade.pairlists.blacklist.append(pair)
+                if self._freqtrade.exchange.get_pair_quote_currency(pair) == stake_currency:
+                    if pair not in self._freqtrade.pairlists.blacklist:
+                        self._freqtrade.pairlists.blacklist.append(pair)
+                    else:
+                        errors[pair] = {
+                            'error_msg': f'Pair {pair} already in pairlist.'}
 
-        res = {'method': self._freqtrade.pairlists.name,
+                else:
+                    errors[pair] = {
+                        'error_msg': f"Pair {pair} does not match stake currency."
+                    }
+
+        res = {'method': self._freqtrade.pairlists.name_list,
                'length': len(self._freqtrade.pairlists.blacklist),
                'blacklist': self._freqtrade.pairlists.blacklist,
+               'errors': errors,
                }
         return res
 
+    def _rpc_get_logs(self, limit: Optional[int]) -> Dict[str, Any]:
+        """Returns the last X logs"""
+        if limit:
+            buffer = bufferHandler.buffer[-limit:]
+        else:
+            buffer = bufferHandler.buffer
+        records = [[datetime.fromtimestamp(r.created).strftime(DATETIME_PRINT_FORMAT),
+                   r.created * 1000, r.name, r.levelname,
+                   r.message + ('\n' + r.exc_text if r.exc_text else '')]
+                   for r in buffer]
+
+        # Log format:
+        # [logtime-formatted, logepoch, logger-name, loglevel, message \n + exception]
+        # e.g. ["2020-08-27 11:35:01", 1598520901097.9397,
+        #       "freqtrade.worker", "INFO", "Starting worker develop"]
+
+        return {'log_count': len(records), 'logs': records}
+
     def _rpc_edge(self) -> List[Dict[str, Any]]:
         """ Returns information related to Edge """
         if not self._freqtrade.edge:
-            raise RPCException(f'Edge is not enabled.')
+            raise RPCException('Edge is not enabled.')
         return self._freqtrade.edge.accepted_pairs()
+
+    @staticmethod
+    def _convert_dataframe_to_dict(strategy: str, pair: str, timeframe: str, dataframe: DataFrame,
+                                   last_analyzed: datetime) -> Dict[str, Any]:
+        has_content = len(dataframe) != 0
+        buy_signals = 0
+        sell_signals = 0
+        if has_content:
+
+            dataframe.loc[:, '__date_ts'] = dataframe.loc[:, 'date'].astype(int64) // 1000 // 1000
+            # Move open to seperate column when signal for easy plotting
+            if 'buy' in dataframe.columns:
+                buy_mask = (dataframe['buy'] == 1)
+                buy_signals = int(buy_mask.sum())
+                dataframe.loc[buy_mask, '_buy_signal_open'] = dataframe.loc[buy_mask, 'open']
+            if 'sell' in dataframe.columns:
+                sell_mask = (dataframe['sell'] == 1)
+                sell_signals = int(sell_mask.sum())
+                dataframe.loc[sell_mask, '_sell_signal_open'] = dataframe.loc[sell_mask, 'open']
+            dataframe = dataframe.replace({NAN: None})
+
+        res = {
+            'pair': pair,
+            'timeframe': timeframe,
+            'timeframe_ms': timeframe_to_msecs(timeframe),
+            'strategy': strategy,
+            'columns': list(dataframe.columns),
+            'data': dataframe.values.tolist(),
+            'length': len(dataframe),
+            'buy_signals': buy_signals,
+            'sell_signals': sell_signals,
+            'last_analyzed': last_analyzed,
+            'last_analyzed_ts': int(last_analyzed.timestamp()),
+            'data_start': '',
+            'data_start_ts': 0,
+            'data_stop': '',
+            'data_stop_ts': 0,
+        }
+        if has_content:
+            res.update({
+                'data_start': str(dataframe.iloc[0]['date']),
+                'data_start_ts': int(dataframe.iloc[0]['__date_ts']),
+                'data_stop': str(dataframe.iloc[-1]['date']),
+                'data_stop_ts': int(dataframe.iloc[-1]['__date_ts']),
+            })
+        return res
+
+    def _rpc_analysed_dataframe(self, pair: str, timeframe: str, limit: int) -> Dict[str, Any]:
+
+        _data, last_analyzed = self._freqtrade.dataprovider.get_analyzed_dataframe(
+            pair, timeframe)
+        _data = _data.copy()
+        if limit:
+            _data = _data.iloc[-limit:]
+        return self._convert_dataframe_to_dict(self._freqtrade.config['strategy'],
+                                               pair, timeframe, _data, last_analyzed)
+
+    @staticmethod
+    def _rpc_analysed_history_full(config, pair: str, timeframe: str,
+                                   timerange: str) -> Dict[str, Any]:
+        timerange_parsed = TimeRange.parse_timerange(timerange)
+
+        _data = load_data(
+            datadir=config.get("datadir"),
+            pairs=[pair],
+            timeframe=timeframe,
+            timerange=timerange_parsed,
+            data_format=config.get('dataformat_ohlcv', 'json'),
+        )
+        from freqtrade.resolvers.strategy_resolver import StrategyResolver
+        strategy = StrategyResolver.load_strategy(config)
+        df_analyzed = strategy.analyze_ticker(_data[pair], {'pair': pair})
+
+        return RPC._convert_dataframe_to_dict(strategy.get_strategy_name(), pair, timeframe,
+                                              df_analyzed, arrow.Arrow.utcnow().datetime)
+
+    def _rpc_plot_config(self) -> Dict[str, Any]:
+
+        return self._freqtrade.strategy.plot_config
diff --git a/freqtrade/rpc/rpc_manager.py b/freqtrade/rpc/rpc_manager.py
index fad532aa0..b97a5357b 100644
--- a/freqtrade/rpc/rpc_manager.py
+++ b/freqtrade/rpc/rpc_manager.py
@@ -6,10 +6,11 @@ from typing import Any, Dict, List
 
 from freqtrade.rpc import RPC, RPCMessageType
 
+
 logger = logging.getLogger(__name__)
 
 
-class RPCManager(object):
+class RPCManager:
     """
     Class to manage RPC objects (Telegram, Slack, ...)
     """
@@ -18,7 +19,7 @@ class RPCManager(object):
         self.registered_modules: List[RPC] = []
 
         # Enable telegram
-        if freqtrade.config['telegram'].get('enabled', False):
+        if freqtrade.config.get('telegram', {}).get('enabled', False):
             logger.info('Enabling rpc.telegram ...')
             from freqtrade.rpc.telegram import Telegram
             self.registered_modules.append(Telegram(freqtrade))
@@ -56,10 +57,13 @@ class RPCManager(object):
         logger.info('Sending rpc message: %s', msg)
         for mod in self.registered_modules:
             logger.debug('Forwarding message to rpc.%s', mod.name)
-            mod.send_msg(msg)
+            try:
+                mod.send_msg(msg)
+            except NotImplementedError:
+                logger.error(f"Message type '{msg['type']}' not implemented by handler {mod.name}.")
 
-    def startup_messages(self, config, pairlist) -> None:
-        if config.get('dry_run', False):
+    def startup_messages(self, config: Dict[str, Any], pairlist) -> None:
+        if config['dry_run']:
             self.send_msg({
                 'type': RPCMessageType.WARNING_NOTIFICATION,
                 'status': 'Dry run is enabled. All trades are simulated.'
@@ -69,20 +73,20 @@ class RPCManager(object):
         minimal_roi = config['minimal_roi']
         stoploss = config['stoploss']
         trailing_stop = config['trailing_stop']
-        ticker_interval = config['ticker_interval']
+        timeframe = config['timeframe']
         exchange_name = config['exchange']['name']
         strategy_name = config.get('strategy', '')
         self.send_msg({
-            'type': RPCMessageType.CUSTOM_NOTIFICATION,
+            'type': RPCMessageType.STARTUP_NOTIFICATION,
             'status': f'*Exchange:* `{exchange_name}`\n'
                       f'*Stake per trade:* `{stake_amount} {stake_currency}`\n'
                       f'*Minimum ROI:* `{minimal_roi}`\n'
                       f'*{"Trailing " if trailing_stop else ""}Stoploss:* `{stoploss}`\n'
-                      f'*Ticker Interval:* `{ticker_interval}`\n'
+                      f'*Timeframe:* `{timeframe}`\n'
                       f'*Strategy:* `{strategy_name}`'
         })
         self.send_msg({
-            'type': RPCMessageType.STATUS_NOTIFICATION,
+            'type': RPCMessageType.STARTUP_NOTIFICATION,
             'status': f'Searching for {stake_currency} pairs to buy and sell '
                       f'based on {pairlist.short_desc()}'
         })
diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py
index fe4929780..31d5bbfbd 100644
--- a/freqtrade/rpc/telegram.py
+++ b/freqtrade/rpc/telegram.py
@@ -3,23 +3,26 @@
 """
 This module manage Telegram communication
 """
+import json
 import logging
-from typing import Any, Callable, Dict, List
+from typing import Any, Callable, Dict
 
+import arrow
 from tabulate import tabulate
-from telegram import Bot, ParseMode, ReplyKeyboardMarkup, Update
+from telegram import ParseMode, ReplyKeyboardMarkup, Update
 from telegram.error import NetworkError, TelegramError
-from telegram.ext import CommandHandler, Updater
+from telegram.ext import CallbackContext, CommandHandler, Updater
+from telegram.utils.helpers import escape_markdown
 
 from freqtrade.__init__ import __version__
 from freqtrade.rpc import RPC, RPCException, RPCMessageType
 from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
 
+
 logger = logging.getLogger(__name__)
 
 logger.debug('Included module rpc.telegram ...')
 
-
 MAX_TELEGRAM_MESSAGE_LENGTH = 4096
 
 
@@ -29,9 +32,10 @@ def authorized_only(command_handler: Callable[..., None]) -> Callable[..., Any]:
     :param command_handler: Telegram CommandHandler
     :return: decorated function
     """
+
     def wrapper(self, *args, **kwargs):
         """ Decorator logic """
-        update = kwargs.get('update') or args[1]
+        update = kwargs.get('update') or args[0]
 
         # Reject unauthorized messages
         chat_id = int(self._config['telegram']['chat_id'])
@@ -79,7 +83,8 @@ class Telegram(RPC):
         registers all known command handlers
         and starts polling for message updates
         """
-        self._updater = Updater(token=self._config['telegram']['token'], workers=0)
+        self._updater = Updater(token=self._config['telegram']['token'], workers=0,
+                                use_context=True)
 
         # Register command handler and start telegram message polling
         handles = [
@@ -90,13 +95,18 @@ class Telegram(RPC):
             CommandHandler('stop', self._stop),
             CommandHandler('forcesell', self._forcesell),
             CommandHandler('forcebuy', self._forcebuy),
+            CommandHandler('trades', self._trades),
+            CommandHandler('delete', self._delete_trade),
             CommandHandler('performance', self._performance),
             CommandHandler('daily', self._daily),
             CommandHandler('count', self._count),
-            CommandHandler('reload_conf', self._reload_conf),
+            CommandHandler('locks', self._locks),
+            CommandHandler(['reload_config', 'reload_conf'], self._reload_config),
+            CommandHandler(['show_config', 'show_conf'], self._show_config),
             CommandHandler('stopbuy', self._stopbuy),
             CommandHandler('whitelist', self._whitelist),
-            CommandHandler('blacklist', self._blacklist, pass_args=True),
+            CommandHandler('blacklist', self._blacklist),
+            CommandHandler('logs', self._logs),
             CommandHandler('edge', self._edge),
             CommandHandler('help', self._help),
             CommandHandler('version', self._version),
@@ -124,6 +134,13 @@ class Telegram(RPC):
     def send_msg(self, msg: Dict[str, Any]) -> None:
         """ Send a message to telegram channel """
 
+        noti = self._config['telegram'].get('notification_settings', {}
+                                            ).get(str(msg['type']), 'on')
+        if noti == 'off':
+            logger.info(f"Notification '{msg['type']}' not sent.")
+            # Notification disabled
+            return
+
         if msg['type'] == RPCMessageType.BUY_NOTIFICATION:
             if self._fiat_converter:
                 msg['stake_amount_fiat'] = self._fiat_converter.convert_amount(
@@ -131,51 +148,81 @@ class Telegram(RPC):
             else:
                 msg['stake_amount_fiat'] = 0
 
-            message = ("*{exchange}:* Buying {pair}\n"
-                       "at rate `{limit:.8f}\n"
-                       "({stake_amount:.6f} {stake_currency}").format(**msg)
+            message = ("\N{LARGE BLUE CIRCLE} *{exchange}:* Buying {pair}\n"
+                       "*Amount:* `{amount:.8f}`\n"
+                       "*Open Rate:* `{limit:.8f}`\n"
+                       "*Current Rate:* `{current_rate:.8f}`\n"
+                       "*Total:* `({stake_amount:.6f} {stake_currency}").format(**msg)
 
             if msg.get('fiat_currency', None):
-                message += ",{stake_amount_fiat:.3f} {fiat_currency}".format(**msg)
+                message += ", {stake_amount_fiat:.3f} {fiat_currency}".format(**msg)
             message += ")`"
 
+        elif msg['type'] == RPCMessageType.BUY_CANCEL_NOTIFICATION:
+            message = ("\N{WARNING SIGN} *{exchange}:* "
+                       "Cancelling open buy Order for {pair}. Reason: {reason}.".format(**msg))
+
         elif msg['type'] == RPCMessageType.SELL_NOTIFICATION:
             msg['amount'] = round(msg['amount'], 8)
-            msg['profit_percent'] = round(msg['profit_percent'] * 100, 2)
+            msg['profit_percent'] = round(msg['profit_ratio'] * 100, 2)
+            msg['duration'] = msg['close_date'].replace(
+                microsecond=0) - msg['open_date'].replace(microsecond=0)
+            msg['duration_min'] = msg['duration'].total_seconds() / 60
 
-            message = ("*{exchange}:* Selling {pair}\n"
-                       "*Rate:* `{limit:.8f}`\n"
+            msg['emoji'] = self._get_sell_emoji(msg)
+
+            message = ("{emoji} *{exchange}:* Selling {pair}\n"
                        "*Amount:* `{amount:.8f}`\n"
                        "*Open Rate:* `{open_rate:.8f}`\n"
                        "*Current Rate:* `{current_rate:.8f}`\n"
+                       "*Close Rate:* `{limit:.8f}`\n"
                        "*Sell Reason:* `{sell_reason}`\n"
+                       "*Duration:* `{duration} ({duration_min:.1f} min)`\n"
                        "*Profit:* `{profit_percent:.2f}%`").format(**msg)
 
             # Check if all sell properties are available.
             # This might not be the case if the message origin is triggered by /forcesell
             if (all(prop in msg for prop in ['gain', 'fiat_currency', 'stake_currency'])
-               and self._fiat_converter):
+                    and self._fiat_converter):
                 msg['profit_fiat'] = self._fiat_converter.convert_amount(
                     msg['profit_amount'], msg['stake_currency'], msg['fiat_currency'])
-                message += ('` ({gain}: {profit_amount:.8f} {stake_currency}`'
-                            '` / {profit_fiat:.3f} {fiat_currency})`').format(**msg)
+                message += (' `({gain}: {profit_amount:.8f} {stake_currency}'
+                            ' / {profit_fiat:.3f} {fiat_currency})`').format(**msg)
+
+        elif msg['type'] == RPCMessageType.SELL_CANCEL_NOTIFICATION:
+            message = ("\N{WARNING SIGN} *{exchange}:* Cancelling Open Sell Order "
+                       "for {pair}. Reason: {reason}").format(**msg)
 
         elif msg['type'] == RPCMessageType.STATUS_NOTIFICATION:
             message = '*Status:* `{status}`'.format(**msg)
 
         elif msg['type'] == RPCMessageType.WARNING_NOTIFICATION:
-            message = '*Warning:* `{status}`'.format(**msg)
+            message = '\N{WARNING SIGN} *Warning:* `{status}`'.format(**msg)
 
-        elif msg['type'] == RPCMessageType.CUSTOM_NOTIFICATION:
+        elif msg['type'] == RPCMessageType.STARTUP_NOTIFICATION:
             message = '{status}'.format(**msg)
 
         else:
             raise NotImplementedError('Unknown message type: {}'.format(msg['type']))
 
-        self._send_msg(message)
+        self._send_msg(message, disable_notification=(noti == 'silent'))
+
+    def _get_sell_emoji(self, msg):
+        """
+        Get emoji for sell-side
+        """
+
+        if float(msg['profit_percent']) >= 5.0:
+            return "\N{ROCKET}"
+        elif float(msg['profit_percent']) >= 0.0:
+            return "\N{EIGHT SPOKED ASTERISK}"
+        elif msg['sell_reason'] == "stop_loss":
+            return"\N{WARNING SIGN}"
+        else:
+            return "\N{CROSS MARK}"
 
     @authorized_only
-    def _status(self, bot: Bot, update: Update) -> None:
+    def _status(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /status.
         Returns the current TradeThread status
@@ -184,11 +231,8 @@ class Telegram(RPC):
         :return: None
         """
 
-        # Check if additional parameters are passed
-        params = update.message.text.replace('/status', '').split(' ') \
-            if update.message.text else []
-        if 'table' in params:
-            self._status_table(bot, update)
+        if 'table' in context.args:
+            self._status_table(update, context)
             return
 
         try:
@@ -203,31 +247,37 @@ class Telegram(RPC):
                     "*Open Rate:* `{open_rate:.8f}`",
                     "*Close Rate:* `{close_rate}`" if r['close_rate'] else "",
                     "*Current Rate:* `{current_rate:.8f}`",
-                    "*Close Profit:* `{close_profit}`" if r['close_profit'] else "",
-                    "*Current Profit:* `{current_profit:.2f}%`",
-
-                    # Adding initial stoploss only if it is different from stoploss
-                    "*Initial Stoploss:* `{initial_stop_loss:.8f}` " +
-                    ("`({initial_stop_loss_pct:.2f}%)`" if r['initial_stop_loss_pct'] else "")
-                    if r['stop_loss'] != r['initial_stop_loss'] else "",
-
-                    # Adding stoploss and stoploss percentage only if it is not None
-                    "*Stoploss:* `{stop_loss:.8f}` " +
-                    ("`({stop_loss_pct:.2f}%)`" if r['stop_loss_pct'] else ""),
-
-                    "*Open Order:* `{open_order}`" if r['open_order'] else ""
+                    ("*Current Profit:* " if r['is_open'] else "*Close Profit: *")
+                    + "`{profit_pct:.2f}%`",
                 ]
+                if (r['stop_loss_abs'] != r['initial_stop_loss_abs']
+                        and r['initial_stop_loss_pct'] is not None):
+                    # Adding initial stoploss only if it is different from stoploss
+                    lines.append("*Initial Stoploss:* `{initial_stop_loss_abs:.8f}` "
+                                 "`({initial_stop_loss_pct:.2f}%)`")
+
+                # Adding stoploss and stoploss percentage only if it is not None
+                lines.append("*Stoploss:* `{stop_loss_abs:.8f}` " +
+                             ("`({stop_loss_pct:.2f}%)`" if r['stop_loss_pct'] else ""))
+                lines.append("*Stoploss distance:* `{stoploss_current_dist:.8f}` "
+                             "`({stoploss_current_dist_pct:.2f}%)`")
+                if r['open_order']:
+                    if r['sell_order_status']:
+                        lines.append("*Open Order:* `{open_order}` - `{sell_order_status}`")
+                    else:
+                        lines.append("*Open Order:* `{open_order}`")
+
                 # Filter empty lines using list-comprehension
-                messages.append("\n".join([l for l in lines if l]).format(**r))
+                messages.append("\n".join([line for line in lines if line]).format(**r))
 
             for msg in messages:
-                self._send_msg(msg, bot=bot)
+                self._send_msg(msg)
 
         except RPCException as e:
-            self._send_msg(str(e), bot=bot)
+            self._send_msg(str(e))
 
     @authorized_only
-    def _status_table(self, bot: Bot, update: Update) -> None:
+    def _status_table(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /status table.
         Returns the current TradeThread status in table format
@@ -236,14 +286,15 @@ class Telegram(RPC):
         :return: None
         """
         try:
-            df_statuses = self._rpc_status_table()
-            message = tabulate(df_statuses, headers='keys', tablefmt='simple')
+            statlist, head = self._rpc_status_table(self._config['stake_currency'],
+                                                    self._config.get('fiat_display_currency', ''))
+            message = tabulate(statlist, headers=head, tablefmt='simple')
             self._send_msg(f"<pre>{message}</pre>", parse_mode=ParseMode.HTML)
         except RPCException as e:
-            self._send_msg(str(e), bot=bot)
+            self._send_msg(str(e))
 
     @authorized_only
-    def _daily(self, bot: Bot, update: Update) -> None:
+    def _daily(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /daily <n>
         Returns a daily profit (in BTC) over the last n days.
@@ -254,8 +305,8 @@ class Telegram(RPC):
         stake_cur = self._config['stake_currency']
         fiat_disp_cur = self._config.get('fiat_display_currency', '')
         try:
-            timescale = int(update.message.text.replace('/daily', '').strip())
-        except (TypeError, ValueError):
+            timescale = int(context.args[0])
+        except (TypeError, ValueError, IndexError):
             timescale = 7
         try:
             stats = self._rpc_daily_profit(
@@ -263,21 +314,25 @@ class Telegram(RPC):
                 stake_cur,
                 fiat_disp_cur
             )
-            stats_tab = tabulate(stats,
-                                 headers=[
-                                     'Day',
-                                     f'Profit {stake_cur}',
-                                     f'Profit {fiat_disp_cur}',
-                                     f'Trades'
-                                 ],
-                                 tablefmt='simple')
+            stats_tab = tabulate(
+                [[day['date'],
+                  f"{day['abs_profit']:.8f} {stats['stake_currency']}",
+                  f"{day['fiat_value']:.3f} {stats['fiat_display_currency']}",
+                  f"{day['trade_count']} trades"] for day in stats['data']],
+                headers=[
+                    'Day',
+                    f'Profit {stake_cur}',
+                    f'Profit {fiat_disp_cur}',
+                    'Trades',
+                ],
+                tablefmt='simple')
             message = f'<b>Daily Profit over the last {timescale} days</b>:\n<pre>{stats_tab}</pre>'
-            self._send_msg(message, bot=bot, parse_mode=ParseMode.HTML)
+            self._send_msg(message, parse_mode=ParseMode.HTML)
         except RPCException as e:
-            self._send_msg(str(e), bot=bot)
+            self._send_msg(str(e))
 
     @authorized_only
-    def _profit(self, bot: Bot, update: Update) -> None:
+    def _profit(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /profit.
         Returns a cumulative profit statistics.
@@ -288,71 +343,92 @@ class Telegram(RPC):
         stake_cur = self._config['stake_currency']
         fiat_disp_cur = self._config.get('fiat_display_currency', '')
 
-        try:
-            stats = self._rpc_trade_statistics(
-                stake_cur,
-                fiat_disp_cur)
-            profit_closed_coin = stats['profit_closed_coin']
-            profit_closed_percent = stats['profit_closed_percent']
-            profit_closed_fiat = stats['profit_closed_fiat']
-            profit_all_coin = stats['profit_all_coin']
-            profit_all_percent = stats['profit_all_percent']
-            profit_all_fiat = stats['profit_all_fiat']
-            trade_count = stats['trade_count']
-            first_trade_date = stats['first_trade_date']
-            latest_trade_date = stats['latest_trade_date']
-            avg_duration = stats['avg_duration']
-            best_pair = stats['best_pair']
-            best_rate = stats['best_rate']
+        stats = self._rpc_trade_statistics(
+            stake_cur,
+            fiat_disp_cur)
+        profit_closed_coin = stats['profit_closed_coin']
+        profit_closed_percent_mean = stats['profit_closed_percent_mean']
+        profit_closed_percent_sum = stats['profit_closed_percent_sum']
+        profit_closed_fiat = stats['profit_closed_fiat']
+        profit_all_coin = stats['profit_all_coin']
+        profit_all_percent_mean = stats['profit_all_percent_mean']
+        profit_all_percent_sum = stats['profit_all_percent_sum']
+        profit_all_fiat = stats['profit_all_fiat']
+        trade_count = stats['trade_count']
+        first_trade_date = stats['first_trade_date']
+        latest_trade_date = stats['latest_trade_date']
+        avg_duration = stats['avg_duration']
+        best_pair = stats['best_pair']
+        best_rate = stats['best_rate']
+        if stats['trade_count'] == 0:
+            markdown_msg = 'No trades yet.'
+        else:
             # Message to display
-            markdown_msg = "*ROI:* Close trades\n" \
-                           f"∙ `{profit_closed_coin:.8f} {stake_cur} "\
-                           f"({profit_closed_percent:.2f}%)`\n" \
-                           f"∙ `{profit_closed_fiat:.3f} {fiat_disp_cur}`\n" \
-                           f"*ROI:* All trades\n" \
-                           f"∙ `{profit_all_coin:.8f} {stake_cur} ({profit_all_percent:.2f}%)`\n" \
-                           f"∙ `{profit_all_fiat:.3f} {fiat_disp_cur}`\n" \
-                           f"*Total Trade Count:* `{trade_count}`\n" \
-                           f"*First Trade opened:* `{first_trade_date}`\n" \
-                           f"*Latest Trade opened:* `{latest_trade_date}`\n" \
-                           f"*Avg. Duration:* `{avg_duration}`\n" \
-                           f"*Best Performing:* `{best_pair}: {best_rate:.2f}%`"
-            self._send_msg(markdown_msg, bot=bot)
-        except RPCException as e:
-            self._send_msg(str(e), bot=bot)
+            if stats['closed_trade_count'] > 0:
+                markdown_msg = ("*ROI:* Closed trades\n"
+                                f"∙ `{profit_closed_coin:.8f} {stake_cur} "
+                                f"({profit_closed_percent_mean:.2f}%) "
+                                f"({profit_closed_percent_sum} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
+                                f"∙ `{profit_closed_fiat:.3f} {fiat_disp_cur}`\n")
+            else:
+                markdown_msg = "`No closed trade` \n"
+
+            markdown_msg += (f"*ROI:* All trades\n"
+                             f"∙ `{profit_all_coin:.8f} {stake_cur} "
+                             f"({profit_all_percent_mean:.2f}%) "
+                             f"({profit_all_percent_sum} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
+                             f"∙ `{profit_all_fiat:.3f} {fiat_disp_cur}`\n"
+                             f"*Total Trade Count:* `{trade_count}`\n"
+                             f"*First Trade opened:* `{first_trade_date}`\n"
+                             f"*Latest Trade opened:* `{latest_trade_date}\n`"
+                             f"*Win / Loss:* `{stats['winning_trades']} / {stats['losing_trades']}`"
+                             )
+            if stats['closed_trade_count'] > 0:
+                markdown_msg += (f"\n*Avg. Duration:* `{avg_duration}`\n"
+                                 f"*Best Performing:* `{best_pair}: {best_rate:.2f}%`")
+        self._send_msg(markdown_msg)
 
     @authorized_only
-    def _balance(self, bot: Bot, update: Update) -> None:
+    def _balance(self, update: Update, context: CallbackContext) -> None:
         """ Handler for /balance """
         try:
-            result = self._rpc_balance(self._config.get('fiat_display_currency', ''))
+            result = self._rpc_balance(self._config['stake_currency'],
+                                       self._config.get('fiat_display_currency', ''))
+
             output = ''
+            if self._config['dry_run']:
+                output += (
+                    f"*Warning:* Simulated balances in Dry Mode.\n"
+                    "This mode is still experimental!\n"
+                    "Starting capital: "
+                    f"`{self._config['dry_run_wallet']}` {self._config['stake_currency']}.\n"
+                )
             for currency in result['currencies']:
-                if currency['est_btc'] > 0.0001:
-                    curr_output = "*{currency}:*\n" \
-                            "\t`Available: {available: .8f}`\n" \
-                            "\t`Balance: {balance: .8f}`\n" \
-                            "\t`Pending: {pending: .8f}`\n" \
-                            "\t`Est. BTC: {est_btc: .8f}`\n".format(**currency)
+                if currency['est_stake'] > 0.0001:
+                    curr_output = ("*{currency}:*\n"
+                                   "\t`Available: {free: .8f}`\n"
+                                   "\t`Balance: {balance: .8f}`\n"
+                                   "\t`Pending: {used: .8f}`\n"
+                                   "\t`Est. {stake}: {est_stake: .8f}`\n").format(**currency)
                 else:
                     curr_output = "*{currency}:* not showing <1$ amount \n".format(**currency)
 
                 # Handle overflowing messsage length
                 if len(output + curr_output) >= MAX_TELEGRAM_MESSAGE_LENGTH:
-                    self._send_msg(output, bot=bot)
+                    self._send_msg(output)
                     output = curr_output
                 else:
                     output += curr_output
 
-            output += "\n*Estimated Value*:\n" \
-                      "\t`BTC: {total: .8f}`\n" \
-                      "\t`{symbol}: {value: .2f}`\n".format(**result)
-            self._send_msg(output, bot=bot)
+            output += ("\n*Estimated Value*:\n"
+                       "\t`{stake}: {total: .8f}`\n"
+                       "\t`{symbol}: {value: .2f}`\n").format(**result)
+            self._send_msg(output)
         except RPCException as e:
-            self._send_msg(str(e), bot=bot)
+            self._send_msg(str(e))
 
     @authorized_only
-    def _start(self, bot: Bot, update: Update) -> None:
+    def _start(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /start.
         Starts TradeThread
@@ -361,10 +437,10 @@ class Telegram(RPC):
         :return: None
         """
         msg = self._rpc_start()
-        self._send_msg('Status: `{status}`'.format(**msg), bot=bot)
+        self._send_msg('Status: `{status}`'.format(**msg))
 
     @authorized_only
-    def _stop(self, bot: Bot, update: Update) -> None:
+    def _stop(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /stop.
         Stops TradeThread
@@ -373,22 +449,22 @@ class Telegram(RPC):
         :return: None
         """
         msg = self._rpc_stop()
-        self._send_msg('Status: `{status}`'.format(**msg), bot=bot)
+        self._send_msg('Status: `{status}`'.format(**msg))
 
     @authorized_only
-    def _reload_conf(self, bot: Bot, update: Update) -> None:
+    def _reload_config(self, update: Update, context: CallbackContext) -> None:
         """
-        Handler for /reload_conf.
+        Handler for /reload_config.
         Triggers a config file reload
         :param bot: telegram bot
         :param update: message update
         :return: None
         """
-        msg = self._rpc_reload_conf()
-        self._send_msg('Status: `{status}`'.format(**msg), bot=bot)
+        msg = self._rpc_reload_config()
+        self._send_msg('Status: `{status}`'.format(**msg))
 
     @authorized_only
-    def _stopbuy(self, bot: Bot, update: Update) -> None:
+    def _stopbuy(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /stop_buy.
         Sets max_open_trades to 0 and gracefully sells all open trades
@@ -397,10 +473,10 @@ class Telegram(RPC):
         :return: None
         """
         msg = self._rpc_stopbuy()
-        self._send_msg('Status: `{status}`'.format(**msg), bot=bot)
+        self._send_msg('Status: `{status}`'.format(**msg))
 
     @authorized_only
-    def _forcesell(self, bot: Bot, update: Update) -> None:
+    def _forcesell(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /forcesell <id>.
         Sells the given trade at current price
@@ -409,16 +485,16 @@ class Telegram(RPC):
         :return: None
         """
 
-        trade_id = update.message.text.replace('/forcesell', '').strip()
+        trade_id = context.args[0] if len(context.args) > 0 else None
         try:
             msg = self._rpc_forcesell(trade_id)
-            self._send_msg('Forcesell Result: `{result}`'.format(**msg), bot=bot)
+            self._send_msg('Forcesell Result: `{result}`'.format(**msg))
 
         except RPCException as e:
-            self._send_msg(str(e), bot=bot)
+            self._send_msg(str(e))
 
     @authorized_only
-    def _forcebuy(self, bot: Bot, update: Update) -> None:
+    def _forcebuy(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /forcebuy <asset> <price>.
         Buys a pair trade at the given or current price
@@ -427,16 +503,71 @@ class Telegram(RPC):
         :return: None
         """
 
-        message = update.message.text.replace('/forcebuy', '').strip().split()
-        pair = message[0]
-        price = float(message[1]) if len(message) > 1 else None
+        pair = context.args[0]
+        price = float(context.args[1]) if len(context.args) > 1 else None
         try:
             self._rpc_forcebuy(pair, price)
         except RPCException as e:
-            self._send_msg(str(e), bot=bot)
+            self._send_msg(str(e))
 
     @authorized_only
-    def _performance(self, bot: Bot, update: Update) -> None:
+    def _trades(self, update: Update, context: CallbackContext) -> None:
+        """
+        Handler for /trades <n>
+        Returns last n recent trades.
+        :param bot: telegram bot
+        :param update: message update
+        :return: None
+        """
+        stake_cur = self._config['stake_currency']
+        try:
+            nrecent = int(context.args[0])
+        except (TypeError, ValueError, IndexError):
+            nrecent = 10
+        try:
+            trades = self._rpc_trade_history(
+                nrecent
+            )
+            trades_tab = tabulate(
+                [[arrow.get(trade['open_date']).humanize(),
+                  trade['pair'],
+                  f"{(100 * trade['close_profit']):.2f}% ({trade['close_profit_abs']})"]
+                 for trade in trades['trades']],
+                headers=[
+                    'Open Date',
+                    'Pair',
+                    f'Profit ({stake_cur})',
+                ],
+                tablefmt='simple')
+            message = (f"<b>{min(trades['trades_count'], nrecent)} recent trades</b>:\n"
+                       + (f"<pre>{trades_tab}</pre>" if trades['trades_count'] > 0 else ''))
+            self._send_msg(message, parse_mode=ParseMode.HTML)
+        except RPCException as e:
+            self._send_msg(str(e))
+
+    @authorized_only
+    def _delete_trade(self, update: Update, context: CallbackContext) -> None:
+        """
+        Handler for /delete <id>.
+        Delete the given trade
+        :param bot: telegram bot
+        :param update: message update
+        :return: None
+        """
+
+        trade_id = context.args[0] if len(context.args) > 0 else None
+        try:
+            msg = self._rpc_delete(trade_id)
+            self._send_msg((
+                '`{result_msg}`\n'
+                'Please make sure to take care of this asset on the exchange manually.'
+            ).format(**msg))
+
+        except RPCException as e:
+            self._send_msg(str(e))
+
+    @authorized_only
+    def _performance(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /performance.
         Shows a performance statistic from finished trades
@@ -455,10 +586,10 @@ class Telegram(RPC):
             message = '<b>Performance:</b>\n{}'.format(stats)
             self._send_msg(message, parse_mode=ParseMode.HTML)
         except RPCException as e:
-            self._send_msg(str(e), bot=bot)
+            self._send_msg(str(e))
 
     @authorized_only
-    def _count(self, bot: Bot, update: Update) -> None:
+    def _count(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /count.
         Returns the number of trades running
@@ -475,10 +606,30 @@ class Telegram(RPC):
             logger.debug(message)
             self._send_msg(message, parse_mode=ParseMode.HTML)
         except RPCException as e:
-            self._send_msg(str(e), bot=bot)
+            self._send_msg(str(e))
 
     @authorized_only
-    def _whitelist(self, bot: Bot, update: Update) -> None:
+    def _locks(self, update: Update, context: CallbackContext) -> None:
+        """
+        Handler for /locks.
+        Returns the currently active locks
+        """
+        try:
+            locks = self._rpc_locks()
+            message = tabulate([[
+                lock['pair'],
+                lock['lock_end_time'],
+                lock['reason']] for lock in locks['locks']],
+                headers=['Pair', 'Until', 'Reason'],
+                tablefmt='simple')
+            message = "<pre>{}</pre>".format(message)
+            logger.debug(message)
+            self._send_msg(message, parse_mode=ParseMode.HTML)
+        except RPCException as e:
+            self._send_msg(str(e))
+
+    @authorized_only
+    def _whitelist(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /whitelist
         Shows the currently active whitelist
@@ -492,17 +643,22 @@ class Telegram(RPC):
             logger.debug(message)
             self._send_msg(message)
         except RPCException as e:
-            self._send_msg(str(e), bot=bot)
+            self._send_msg(str(e))
 
     @authorized_only
-    def _blacklist(self, bot: Bot, update: Update, args: List[str]) -> None:
+    def _blacklist(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /blacklist
         Shows the currently active blacklist
         """
         try:
 
-            blacklist = self._rpc_blacklist(args)
+            blacklist = self._rpc_blacklist(context.args)
+            errmsgs = []
+            for pair, error in blacklist['errors'].items():
+                errmsgs.append(f"Error adding `{pair}` to blacklist: `{error['error_msg']}`")
+            if errmsgs:
+                self._send_msg('\n'.join(errmsgs))
 
             message = f"Blacklist contains {blacklist['length']} pairs\n"
             message += f"`{', '.join(blacklist['blacklist'])}`"
@@ -510,10 +666,42 @@ class Telegram(RPC):
             logger.debug(message)
             self._send_msg(message)
         except RPCException as e:
-            self._send_msg(str(e), bot=bot)
+            self._send_msg(str(e))
 
     @authorized_only
-    def _edge(self, bot: Bot, update: Update) -> None:
+    def _logs(self, update: Update, context: CallbackContext) -> None:
+        """
+        Handler for /logs
+        Shows the latest logs
+        """
+        try:
+            try:
+                limit = int(context.args[0])
+            except (TypeError, ValueError, IndexError):
+                limit = 10
+            logs = self._rpc_get_logs(limit)['logs']
+            msgs = ''
+            msg_template = "*{}* {}: {} \\- `{}`"
+            for logrec in logs:
+                msg = msg_template.format(escape_markdown(logrec[0], version=2),
+                                          escape_markdown(logrec[2], version=2),
+                                          escape_markdown(logrec[3], version=2),
+                                          escape_markdown(logrec[4], version=2))
+                if len(msgs + msg) + 10 >= MAX_TELEGRAM_MESSAGE_LENGTH:
+                    # Send message immediately if it would become too long
+                    self._send_msg(msgs, parse_mode=ParseMode.MARKDOWN_V2)
+                    msgs = msg + '\n'
+                else:
+                    # Append message to messages to send
+                    msgs += msg + '\n'
+
+            if msgs:
+                self._send_msg(msgs, parse_mode=ParseMode.MARKDOWN_V2)
+        except RPCException as e:
+            self._send_msg(str(e))
+
+    @authorized_only
+    def _edge(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /edge
         Shows information related to Edge
@@ -522,12 +710,12 @@ class Telegram(RPC):
             edge_pairs = self._rpc_edge()
             edge_pairs_tab = tabulate(edge_pairs, headers='keys', tablefmt='simple')
             message = f'<b>Edge only validated following pairs:</b>\n<pre>{edge_pairs_tab}</pre>'
-            self._send_msg(message, bot=bot, parse_mode=ParseMode.HTML)
+            self._send_msg(message, parse_mode=ParseMode.HTML)
         except RPCException as e:
-            self._send_msg(str(e), bot=bot)
+            self._send_msg(str(e))
 
     @authorized_only
-    def _help(self, bot: Bot, update: Update) -> None:
+    def _help(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /help.
         Show commands of the bot
@@ -535,34 +723,40 @@ class Telegram(RPC):
         :param update: message update
         :return: None
         """
-        forcebuy_text = "*/forcebuy <pair> [<rate>]:* `Instantly buys the given pair. " \
-                        "Optionally takes a rate at which to buy.` \n"
-        message = "*/start:* `Starts the trader`\n" \
-                  "*/stop:* `Stops the trader`\n" \
-                  "*/status [table]:* `Lists all open trades`\n" \
-                  "         *table :* `will display trades in a table`\n" \
-                  "*/profit:* `Lists cumulative profit from all finished trades`\n" \
-                  "*/forcesell <trade_id>|all:* `Instantly sells the given trade or all trades, " \
-                  "regardless of profit`\n" \
-                  f"{forcebuy_text if self._config.get('forcebuy_enable', False) else '' }" \
-                  "*/performance:* `Show performance of each finished trade grouped by pair`\n" \
-                  "*/daily <n>:* `Shows profit or loss per day, over the last n days`\n" \
-                  "*/count:* `Show number of trades running compared to allowed number of trades`" \
-                  "\n" \
-                  "*/balance:* `Show account balance per currency`\n" \
-                  "*/stopbuy:* `Stops buying, but handles open trades gracefully` \n" \
-                  "*/reload_conf:* `Reload configuration file` \n" \
-                  "*/whitelist:* `Show current whitelist` \n" \
-                  "*/blacklist [pair]:* `Show current blacklist, or adds one or more pairs " \
-                  "to the blacklist.` \n" \
-                  "*/edge:* `Shows validated pairs by Edge if it is enabeld` \n" \
-                  "*/help:* `This help message`\n" \
-                  "*/version:* `Show version`"
+        forcebuy_text = ("*/forcebuy <pair> [<rate>]:* `Instantly buys the given pair. "
+                         "Optionally takes a rate at which to buy.` \n")
+        message = ("*/start:* `Starts the trader`\n"
+                   "*/stop:* `Stops the trader`\n"
+                   "*/status [table]:* `Lists all open trades`\n"
+                   "         *table :* `will display trades in a table`\n"
+                   "                `pending buy orders are marked with an asterisk (*)`\n"
+                   "                `pending sell orders are marked with a double asterisk (**)`\n"
+                   "*/trades [limit]:* `Lists last closed trades (limited to 10 by default)`\n"
+                   "*/profit:* `Lists cumulative profit from all finished trades`\n"
+                   "*/forcesell <trade_id>|all:* `Instantly sells the given trade or all trades, "
+                   "regardless of profit`\n"
+                   f"{forcebuy_text if self._config.get('forcebuy_enable', False) else ''}"
+                   "*/delete <trade_id>:* `Instantly delete the given trade in the database`\n"
+                   "*/performance:* `Show performance of each finished trade grouped by pair`\n"
+                   "*/daily <n>:* `Shows profit or loss per day, over the last n days`\n"
+                   "*/count:* `Show number of active trades compared to allowed number of trades`\n"
+                   "*/locks:* `Show currently locked pairs`\n"
+                   "*/balance:* `Show account balance per currency`\n"
+                   "*/stopbuy:* `Stops buying, but handles open trades gracefully` \n"
+                   "*/reload_config:* `Reload configuration file` \n"
+                   "*/show_config:* `Show running configuration` \n"
+                   "*/logs [limit]:* `Show latest logs - defaults to 10` \n"
+                   "*/whitelist:* `Show current whitelist` \n"
+                   "*/blacklist [pair]:* `Show current blacklist, or adds one or more pairs "
+                   "to the blacklist.` \n"
+                   "*/edge:* `Shows validated pairs by Edge if it is enabled` \n"
+                   "*/help:* `This help message`\n"
+                   "*/version:* `Show version`")
 
-        self._send_msg(message, bot=bot)
+        self._send_msg(message)
 
     @authorized_only
-    def _version(self, bot: Bot, update: Update) -> None:
+    def _version(self, update: Update, context: CallbackContext) -> None:
         """
         Handler for /version.
         Show version information
@@ -570,10 +764,46 @@ class Telegram(RPC):
         :param update: message update
         :return: None
         """
-        self._send_msg('*Version:* `{}`'.format(__version__), bot=bot)
+        self._send_msg('*Version:* `{}`'.format(__version__))
 
-    def _send_msg(self, msg: str, bot: Bot = None,
-                  parse_mode: ParseMode = ParseMode.MARKDOWN) -> None:
+    @authorized_only
+    def _show_config(self, update: Update, context: CallbackContext) -> None:
+        """
+        Handler for /show_config.
+        Show config information information
+        :param bot: telegram bot
+        :param update: message update
+        :return: None
+        """
+        val = RPC._rpc_show_config(self._freqtrade.config, self._freqtrade.state)
+
+        if val['trailing_stop']:
+            sl_info = (
+                f"*Initial Stoploss:* `{val['stoploss']}`\n"
+                f"*Trailing stop positive:* `{val['trailing_stop_positive']}`\n"
+                f"*Trailing stop offset:* `{val['trailing_stop_positive_offset']}`\n"
+                f"*Only trail above offset:* `{val['trailing_only_offset_is_reached']}`\n"
+            )
+
+        else:
+            sl_info = f"*Stoploss:* `{val['stoploss']}`\n"
+
+        self._send_msg(
+            f"*Mode:* `{'Dry-run' if val['dry_run'] else 'Live'}`\n"
+            f"*Exchange:* `{val['exchange']}`\n"
+            f"*Stake per trade:* `{val['stake_amount']} {val['stake_currency']}`\n"
+            f"*Max open Trades:* `{val['max_open_trades']}`\n"
+            f"*Minimum ROI:* `{val['minimal_roi']}`\n"
+            f"*Ask strategy:* ```\n{json.dumps(val['ask_strategy'])}```\n"
+            f"*Bid strategy:* ```\n{json.dumps(val['bid_strategy'])}```\n"
+            f"{sl_info}"
+            f"*Timeframe:* `{val['timeframe']}`\n"
+            f"*Strategy:* `{val['strategy']}`\n"
+            f"*Current state:* `{val['state']}`"
+        )
+
+    def _send_msg(self, msg: str, parse_mode: ParseMode = ParseMode.MARKDOWN,
+                  disable_notification: bool = False) -> None:
         """
         Send given markdown message
         :param msg: message
@@ -581,7 +811,6 @@ class Telegram(RPC):
         :param parse_mode: telegram parse mode
         :return: None
         """
-        bot = bot or self._updater.bot
 
         keyboard = [['/daily', '/profit', '/balance'],
                     ['/status', '/status table', '/performance'],
@@ -591,11 +820,12 @@ class Telegram(RPC):
 
         try:
             try:
-                bot.send_message(
+                self._updater.bot.send_message(
                     self._config['telegram']['chat_id'],
                     text=msg,
                     parse_mode=parse_mode,
-                    reply_markup=reply_markup
+                    reply_markup=reply_markup,
+                    disable_notification=disable_notification,
                 )
             except NetworkError as network_err:
                 # Sometimes the telegram server resets the current connection,
@@ -604,11 +834,12 @@ class Telegram(RPC):
                     'Telegram NetworkError: %s! Trying one more time.',
                     network_err.message
                 )
-                bot.send_message(
+                self._updater.bot.send_message(
                     self._config['telegram']['chat_id'],
                     text=msg,
                     parse_mode=parse_mode,
-                    reply_markup=reply_markup
+                    reply_markup=reply_markup,
+                    disable_notification=disable_notification,
                 )
         except TelegramError as telegram_err:
             logger.warning(
diff --git a/freqtrade/rpc/webhook.py b/freqtrade/rpc/webhook.py
index bfc82b8d6..21413f165 100644
--- a/freqtrade/rpc/webhook.py
+++ b/freqtrade/rpc/webhook.py
@@ -2,9 +2,9 @@
 This module manages webhook communication
 """
 import logging
-from typing import Any,  Dict
+from typing import Any, Dict
 
-from requests import post, RequestException
+from requests import RequestException, post
 
 from freqtrade.rpc import RPC, RPCMessageType
 
@@ -41,14 +41,20 @@ class Webhook(RPC):
 
             if msg['type'] == RPCMessageType.BUY_NOTIFICATION:
                 valuedict = self._config['webhook'].get('webhookbuy', None)
+            elif msg['type'] == RPCMessageType.BUY_CANCEL_NOTIFICATION:
+                valuedict = self._config['webhook'].get('webhookbuycancel', None)
             elif msg['type'] == RPCMessageType.SELL_NOTIFICATION:
                 valuedict = self._config['webhook'].get('webhooksell', None)
-            elif msg['type'] == RPCMessageType.STATUS_NOTIFICATION:
+            elif msg['type'] == RPCMessageType.SELL_CANCEL_NOTIFICATION:
+                valuedict = self._config['webhook'].get('webhooksellcancel', None)
+            elif msg['type'] in (RPCMessageType.STATUS_NOTIFICATION,
+                                 RPCMessageType.STARTUP_NOTIFICATION,
+                                 RPCMessageType.WARNING_NOTIFICATION):
                 valuedict = self._config['webhook'].get('webhookstatus', None)
             else:
                 raise NotImplementedError('Unknown message type: {}'.format(msg['type']))
             if not valuedict:
-                logger.info("Message type %s not configured for webhooks", msg['type'])
+                logger.info("Message type '%s' not configured for webhooks", msg['type'])
                 return
 
             payload = {key: value.format(**msg) for (key, value) in valuedict.items()}
diff --git a/freqtrade/state.py b/freqtrade/state.py
index ce2683a77..8ddff71d9 100644
--- a/freqtrade/state.py
+++ b/freqtrade/state.py
@@ -12,7 +12,10 @@ class State(Enum):
     """
     RUNNING = 1
     STOPPED = 2
-    RELOAD_CONF = 3
+    RELOAD_CONFIG = 3
+
+    def __str__(self):
+        return f"{self.name.lower()}"
 
 
 class RunMode(Enum):
@@ -25,4 +28,12 @@ class RunMode(Enum):
     BACKTEST = "backtest"
     EDGE = "edge"
     HYPEROPT = "hyperopt"
-    OTHER = "other"  # Used for plotting scripts and test
+    UTIL_EXCHANGE = "util_exchange"
+    UTIL_NO_EXCHANGE = "util_no_exchange"
+    PLOT = "plot"
+    OTHER = "other"
+
+
+TRADING_MODES = [RunMode.LIVE, RunMode.DRY_RUN]
+OPTIMIZE_MODES = [RunMode.BACKTEST, RunMode.EDGE, RunMode.HYPEROPT]
+NON_UTIL_MODES = TRADING_MODES + OPTIMIZE_MODES
diff --git a/freqtrade/strategy/__init__.py b/freqtrade/strategy/__init__.py
index c62bfe5dc..662156ae9 100644
--- a/freqtrade/strategy/__init__.py
+++ b/freqtrade/strategy/__init__.py
@@ -1,45 +1,5 @@
-import logging
-import sys
-from copy import deepcopy
-
+# flake8: noqa: F401
+from freqtrade.exchange import (timeframe_to_minutes, timeframe_to_msecs, timeframe_to_next_date,
+                                timeframe_to_prev_date, timeframe_to_seconds)
 from freqtrade.strategy.interface import IStrategy
-# Import Default-Strategy to have hyperopt correctly resolve
-from freqtrade.strategy.default_strategy import DefaultStrategy  # noqa: F401
-
-
-logger = logging.getLogger(__name__)
-
-
-def import_strategy(strategy: IStrategy, config: dict) -> IStrategy:
-    """
-    Imports given Strategy instance to global scope
-    of freqtrade.strategy and returns an instance of it
-    """
-
-    # Copy all attributes from base class and class
-    comb = {**strategy.__class__.__dict__, **strategy.__dict__}
-
-    # Delete '_abc_impl' from dict as deepcopy fails on 3.7 with
-    # `TypeError: can't pickle _abc_data objects``
-    # This will only apply to python 3.7
-    if sys.version_info.major == 3 and sys.version_info.minor == 7 and '_abc_impl' in comb:
-        del comb['_abc_impl']
-
-    attr = deepcopy(comb)
-
-    # Adjust module name
-    attr['__module__'] = 'freqtrade.strategy'
-
-    name = strategy.__class__.__name__
-    clazz = type(name, (IStrategy,), attr)
-
-    logger.debug(
-        'Imported strategy %s.%s as %s.%s',
-        strategy.__module__, strategy.__class__.__name__,
-        clazz.__module__, strategy.__class__.__name__,
-    )
-
-    # Modify global scope to declare class
-    globals()[name] = clazz
-
-    return clazz(config)
+from freqtrade.strategy.strategy_helper import merge_informative_pair
diff --git a/freqtrade/strategy/default_strategy.py b/freqtrade/strategy/default_strategy.py
deleted file mode 100644
index 5c7d50a65..000000000
--- a/freqtrade/strategy/default_strategy.py
+++ /dev/null
@@ -1,272 +0,0 @@
-# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
-
-import talib.abstract as ta
-from pandas import DataFrame
-
-import freqtrade.vendor.qtpylib.indicators as qtpylib
-from freqtrade.indicator_helpers import fishers_inverse
-from freqtrade.strategy.interface import IStrategy
-
-
-class DefaultStrategy(IStrategy):
-    """
-    Default Strategy provided by freqtrade bot.
-    You can override it with your own strategy
-    """
-
-    # Minimal ROI designed for the strategy
-    minimal_roi = {
-        "40": 0.0,
-        "30": 0.01,
-        "20": 0.02,
-        "0": 0.04
-    }
-
-    # Optimal stoploss designed for the strategy
-    stoploss = -0.10
-
-    # Optimal ticker interval for the strategy
-    ticker_interval = '5m'
-
-    # Optional order type mapping
-    order_types = {
-        'buy': 'limit',
-        'sell': 'limit',
-        'stoploss': 'limit',
-        'stoploss_on_exchange': False
-    }
-
-    # Optional time in force for orders
-    order_time_in_force = {
-        'buy': 'gtc',
-        'sell': 'gtc',
-    }
-
-    def informative_pairs(self):
-        """
-        Define additional, informative pair/interval combinations to be cached from the exchange.
-        These pair/interval combinations are non-tradeable, unless they are part
-        of the whitelist as well.
-        For more information, please consult the documentation
-        :return: List of tuples in the format (pair, interval)
-            Sample: return [("ETH/USDT", "5m"),
-                            ("BTC/USDT", "15m"),
-                            ]
-        """
-        return []
-
-    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-        """
-        Adds several different TA indicators to the given DataFrame
-
-        Performance Note: For the best performance be frugal on the number of indicators
-        you are using. Let uncomment only the indicator you are using in your strategies
-        or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
-        :param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
-        :param metadata: Additional information, like the currently traded pair
-        :return: a Dataframe with all mandatory indicators for the strategies
-        """
-
-        # Momentum Indicator
-        # ------------------------------------
-
-        # ADX
-        dataframe['adx'] = ta.ADX(dataframe)
-
-        # Awesome oscillator
-        dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
-        """
-        # Commodity Channel Index: values Oversold:<-100, Overbought:>100
-        dataframe['cci'] = ta.CCI(dataframe)
-        """
-        # MACD
-        macd = ta.MACD(dataframe)
-        dataframe['macd'] = macd['macd']
-        dataframe['macdsignal'] = macd['macdsignal']
-        dataframe['macdhist'] = macd['macdhist']
-
-        # MFI
-        dataframe['mfi'] = ta.MFI(dataframe)
-
-        # Minus Directional Indicator / Movement
-        dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
-        dataframe['minus_di'] = ta.MINUS_DI(dataframe)
-
-        # Plus Directional Indicator / Movement
-        dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
-        dataframe['plus_di'] = ta.PLUS_DI(dataframe)
-        dataframe['minus_di'] = ta.MINUS_DI(dataframe)
-
-        """
-        # ROC
-        dataframe['roc'] = ta.ROC(dataframe)
-        """
-        # RSI
-        dataframe['rsi'] = ta.RSI(dataframe)
-
-        # Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
-        dataframe['fisher_rsi'] = fishers_inverse(dataframe['rsi'])
-
-        # Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
-        dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
-
-        # Stoch
-        stoch = ta.STOCH(dataframe)
-        dataframe['slowd'] = stoch['slowd']
-        dataframe['slowk'] = stoch['slowk']
-
-        # Stoch fast
-        stoch_fast = ta.STOCHF(dataframe)
-        dataframe['fastd'] = stoch_fast['fastd']
-        dataframe['fastk'] = stoch_fast['fastk']
-        """
-        # Stoch RSI
-        stoch_rsi = ta.STOCHRSI(dataframe)
-        dataframe['fastd_rsi'] = stoch_rsi['fastd']
-        dataframe['fastk_rsi'] = stoch_rsi['fastk']
-        """
-
-        # Overlap Studies
-        # ------------------------------------
-
-        # Previous Bollinger bands
-        # Because ta.BBANDS implementation is broken with small numbers, it actually
-        # returns middle band for all the three bands. Switch to qtpylib.bollinger_bands
-        # and use middle band instead.
-        dataframe['blower'] = ta.BBANDS(dataframe, nbdevup=2, nbdevdn=2)['lowerband']
-
-        # Bollinger bands
-        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
-        dataframe['bb_lowerband'] = bollinger['lower']
-        dataframe['bb_middleband'] = bollinger['mid']
-        dataframe['bb_upperband'] = bollinger['upper']
-
-        # EMA - Exponential Moving Average
-        dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3)
-        dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
-        dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
-        dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
-        dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
-
-        # SAR Parabol
-        dataframe['sar'] = ta.SAR(dataframe)
-
-        # SMA - Simple Moving Average
-        dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
-
-        # TEMA - Triple Exponential Moving Average
-        dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
-
-        # Cycle Indicator
-        # ------------------------------------
-        # Hilbert Transform Indicator - SineWave
-        hilbert = ta.HT_SINE(dataframe)
-        dataframe['htsine'] = hilbert['sine']
-        dataframe['htleadsine'] = hilbert['leadsine']
-
-        # Pattern Recognition - Bullish candlestick patterns
-        # ------------------------------------
-        """
-        # Hammer: values [0, 100]
-        dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
-        # Inverted Hammer: values [0, 100]
-        dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
-        # Dragonfly Doji: values [0, 100]
-        dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
-        # Piercing Line: values [0, 100]
-        dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
-        # Morningstar: values [0, 100]
-        dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
-        # Three White Soldiers: values [0, 100]
-        dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
-        """
-
-        # Pattern Recognition - Bearish candlestick patterns
-        # ------------------------------------
-        """
-        # Hanging Man: values [0, 100]
-        dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
-        # Shooting Star: values [0, 100]
-        dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
-        # Gravestone Doji: values [0, 100]
-        dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
-        # Dark Cloud Cover: values [0, 100]
-        dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
-        # Evening Doji Star: values [0, 100]
-        dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
-        # Evening Star: values [0, 100]
-        dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
-        """
-
-        # Pattern Recognition - Bullish/Bearish candlestick patterns
-        # ------------------------------------
-        """
-        # Three Line Strike: values [0, -100, 100]
-        dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
-        # Spinning Top: values [0, -100, 100]
-        dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
-        # Engulfing: values [0, -100, 100]
-        dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
-        # Harami: values [0, -100, 100]
-        dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
-        # Three Outside Up/Down: values [0, -100, 100]
-        dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
-        # Three Inside Up/Down: values [0, -100, 100]
-        dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
-        """
-
-        # Chart type
-        # ------------------------------------
-        # Heikinashi stategy
-        heikinashi = qtpylib.heikinashi(dataframe)
-        dataframe['ha_open'] = heikinashi['open']
-        dataframe['ha_close'] = heikinashi['close']
-        dataframe['ha_high'] = heikinashi['high']
-        dataframe['ha_low'] = heikinashi['low']
-
-        return dataframe
-
-    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-        """
-        Based on TA indicators, populates the buy signal for the given dataframe
-        :param dataframe: DataFrame
-        :param metadata: Additional information, like the currently traded pair
-        :return: DataFrame with buy column
-        """
-        dataframe.loc[
-            (
-                (dataframe['rsi'] < 35) &
-                (dataframe['fastd'] < 35) &
-                (dataframe['adx'] > 30) &
-                (dataframe['plus_di'] > 0.5)
-            ) |
-            (
-                (dataframe['adx'] > 65) &
-                (dataframe['plus_di'] > 0.5)
-            ),
-            'buy'] = 1
-
-        return dataframe
-
-    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-        """
-        Based on TA indicators, populates the sell signal for the given dataframe
-        :param dataframe: DataFrame
-        :param metadata: Additional information, like the currently traded pair
-        :return: DataFrame with buy column
-        """
-        dataframe.loc[
-            (
-                (
-                    (qtpylib.crossed_above(dataframe['rsi'], 70)) |
-                    (qtpylib.crossed_above(dataframe['fastd'], 70))
-                ) &
-                (dataframe['adx'] > 10) &
-                (dataframe['minus_di'] > 0)
-            ) |
-            (
-                (dataframe['adx'] > 70) &
-                (dataframe['minus_di'] > 0.5)
-            ),
-            'sell'] = 1
-        return dataframe
diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py
index 2a28bcd22..1c6aa535d 100644
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@@ -3,18 +3,22 @@ IStrategy interface
 This module defines the interface to apply for strategies
 """
 import logging
+import warnings
 from abc import ABC, abstractmethod
-from datetime import datetime
+from datetime import datetime, timezone
 from enum import Enum
 from typing import Dict, List, NamedTuple, Optional, Tuple
-import warnings
 
 import arrow
 from pandas import DataFrame
 
+from freqtrade.constants import ListPairsWithTimeframes
 from freqtrade.data.dataprovider import DataProvider
+from freqtrade.exceptions import OperationalException, StrategyError
 from freqtrade.exchange import timeframe_to_minutes
-from freqtrade.persistence import Trade
+from freqtrade.exchange.exchange import timeframe_to_next_date
+from freqtrade.persistence import PairLocks, Trade
+from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
 from freqtrade.wallets import Wallets
 
 
@@ -39,8 +43,13 @@ class SellType(Enum):
     TRAILING_STOP_LOSS = "trailing_stop_loss"
     SELL_SIGNAL = "sell_signal"
     FORCE_SELL = "force_sell"
+    EMERGENCY_SELL = "emergency_sell"
     NONE = ""
 
+    def __str__(self):
+        # explicitly convert to String to help with exporting data.
+        return self.value
+
 
 class SellCheckTuple(NamedTuple):
     """
@@ -58,8 +67,13 @@ class IStrategy(ABC):
     Attributes you can use:
         minimal_roi -> Dict: Minimal ROI designed for the strategy
         stoploss -> float: optimal stoploss designed for the strategy
-        ticker_interval -> str: value of the ticker interval to use for the strategy
+        timeframe -> str: value of the timeframe (ticker interval) to use with the strategy
     """
+    # Strategy interface version
+    # Default to version 2
+    # Version 1 is the initial interface without metadata dict
+    # Version 2 populate_* include metadata dict
+    INTERFACE_VERSION: int = 2
 
     _populate_fun_len: int = 0
     _buy_fun_len: int = 0
@@ -72,12 +86,13 @@ class IStrategy(ABC):
 
     # trailing stoploss
     trailing_stop: bool = False
-    trailing_stop_positive: float
-    trailing_stop_positive_offset: float
+    trailing_stop_positive: Optional[float] = None
+    trailing_stop_positive_offset: float = 0.0
     trailing_only_offset_is_reached = False
 
-    # associated ticker interval
-    ticker_interval: str
+    # associated timeframe
+    ticker_interval: str  # DEPRECATED
+    timeframe: str
 
     # Optional order types
     order_types: Dict = {
@@ -97,11 +112,22 @@ class IStrategy(ABC):
     # run "populate_indicators" only for new candle
     process_only_new_candles: bool = False
 
+    # Disable checking the dataframe (converts the error into a warning message)
+    disable_dataframe_checks: bool = False
+
+    # Count of candles the strategy requires before producing valid signals
+    startup_candle_count: int = 0
+
     # Class level variables (intentional) containing
     # the dataprovider (dp) (access to other candles, historic data, ...)
     # and wallets - access to the current balance.
-    dp: DataProvider
-    wallets: Wallets
+    dp: Optional[DataProvider] = None
+    wallets: Optional[Wallets] = None
+    # container variable for strategy source code
+    __source__: str = ''
+
+    # Definition of plot_config. See plotting documentation for more details.
+    plot_config: Dict = {}
 
     def __init__(self, config: dict) -> None:
         self.config = config
@@ -112,7 +138,7 @@ class IStrategy(ABC):
     def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Populate indicators that will be used in the Buy and Sell strategy
-        :param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
+        :param dataframe: DataFrame with data from the exchange
         :param metadata: Additional information, like the currently traded pair
         :return: a Dataframe with all mandatory indicators for the strategies
         """
@@ -135,7 +161,100 @@ class IStrategy(ABC):
         :return: DataFrame with sell column
         """
 
-    def informative_pairs(self) -> List[Tuple[str, str]]:
+    def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
+        """
+        Check buy timeout function callback.
+        This method can be used to override the buy-timeout.
+        It is called whenever a limit buy order has been created,
+        and is not yet fully filled.
+        Configuration options in `unfilledtimeout` will be verified before this,
+        so ensure to set these timeouts high enough.
+
+        When not implemented by a strategy, this simply returns False.
+        :param pair: Pair the trade is for
+        :param trade: trade object.
+        :param order: Order dictionary as returned from CCXT.
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return bool: When True is returned, then the buy-order is cancelled.
+        """
+        return False
+
+    def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
+        """
+        Check sell timeout function callback.
+        This method can be used to override the sell-timeout.
+        It is called whenever a limit sell order has been created,
+        and is not yet fully filled.
+        Configuration options in `unfilledtimeout` will be verified before this,
+        so ensure to set these timeouts high enough.
+
+        When not implemented by a strategy, this simply returns False.
+        :param pair: Pair the trade is for
+        :param trade: trade object.
+        :param order: Order dictionary as returned from CCXT.
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return bool: When True is returned, then the sell-order is cancelled.
+        """
+        return False
+
+    def bot_loop_start(self, **kwargs) -> None:
+        """
+        Called at the start of the bot iteration (one loop).
+        Might be used to perform pair-independent tasks
+        (e.g. gather some remote resource for comparison)
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        """
+        pass
+
+    def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
+                            time_in_force: str, **kwargs) -> bool:
+        """
+        Called right before placing a buy order.
+        Timing for this function is critical, so avoid doing heavy computations or
+        network requests in this method.
+
+        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+        When not implemented by a strategy, returns True (always confirming).
+
+        :param pair: Pair that's about to be bought.
+        :param order_type: Order type (as configured in order_types). usually limit or market.
+        :param amount: Amount in target (quote) currency that's going to be traded.
+        :param rate: Rate that's going to be used when using limit orders
+        :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return bool: When True is returned, then the buy-order is placed on the exchange.
+            False aborts the process
+        """
+        return True
+
+    def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
+                           rate: float, time_in_force: str, sell_reason: str, **kwargs) -> bool:
+        """
+        Called right before placing a regular sell order.
+        Timing for this function is critical, so avoid doing heavy computations or
+        network requests in this method.
+
+        For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+        When not implemented by a strategy, returns True (always confirming).
+
+        :param pair: Pair that's about to be sold.
+        :param trade: trade object.
+        :param order_type: Order type (as configured in order_types). usually limit or market.
+        :param amount: Amount in quote currency.
+        :param rate: Rate that's going to be used when using limit orders
+        :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
+        :param sell_reason: Sell reason.
+            Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
+                           'sell_signal', 'force_sell', 'emergency_sell']
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        :return bool: When True is returned, then the sell-order is placed on the exchange.
+            False aborts the process
+        """
+        return True
+
+    def informative_pairs(self) -> ListPairsWithTimeframes:
         """
         Define additional, informative pair/interval combinations to be cached from the exchange.
         These pair/interval combinations are non-tradeable, unless they are part
@@ -148,19 +267,79 @@ class IStrategy(ABC):
         """
         return []
 
+###
+# END - Intended to be overridden by strategy
+###
+
     def get_strategy_name(self) -> str:
         """
         Returns strategy class name
         """
         return self.__class__.__name__
 
-    def analyze_ticker(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    def lock_pair(self, pair: str, until: datetime, reason: str = None) -> None:
         """
-        Parses the given ticker history and returns a populated DataFrame
-        add several TA indicators and buy signal to it
-        :return: DataFrame with ticker data and indicator data
+        Locks pair until a given timestamp happens.
+        Locked pairs are not analyzed, and are prevented from opening new trades.
+        Locks can only count up (allowing users to lock pairs for a longer period of time).
+        To remove a lock from a pair, use `unlock_pair()`
+        :param pair: Pair to lock
+        :param until: datetime in UTC until the pair should be blocked from opening new trades.
+                Needs to be timezone aware `datetime.now(timezone.utc)`
+        :param reason: Optional string explaining why the pair was locked.
+        """
+        PairLocks.lock_pair(pair, until, reason)
+
+    def unlock_pair(self, pair: str) -> None:
+        """
+        Unlocks a pair previously locked using lock_pair.
+        Not used by freqtrade itself, but intended to be used if users lock pairs
+        manually from within the strategy, to allow an easy way to unlock pairs.
+        :param pair: Unlock pair to allow trading again
+        """
+        PairLocks.unlock_pair(pair, datetime.now(timezone.utc))
+
+    def is_pair_locked(self, pair: str, candle_date: datetime = None) -> bool:
+        """
+        Checks if a pair is currently locked
+        The 2nd, optional parameter ensures that locks are applied until the new candle arrives,
+        and not stop at 14:00:00 - while the next candle arrives at 14:00:02 leaving a gap
+        of 2 seconds for a buy to happen on an old signal.
+        :param: pair: "Pair to check"
+        :param candle_date: Date of the last candle. Optional, defaults to current date
+        :returns: locking state of the pair in question.
         """
 
+        if not candle_date:
+            # Simple call ...
+            return PairLocks.is_pair_locked(pair, candle_date)
+        else:
+            lock_time = timeframe_to_next_date(self.timeframe, candle_date)
+            return PairLocks.is_pair_locked(pair, lock_time)
+
+    def analyze_ticker(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Parses the given candle (OHLCV) data and returns a populated DataFrame
+        add several TA indicators and buy signal to it
+        :param dataframe: Dataframe containing data from exchange
+        :param metadata: Metadata dictionary with additional data (e.g. 'pair')
+        :return: DataFrame of candle (OHLCV) data with indicator data and signals added
+        """
+        logger.debug("TA Analysis Launched")
+        dataframe = self.advise_indicators(dataframe, metadata)
+        dataframe = self.advise_buy(dataframe, metadata)
+        dataframe = self.advise_sell(dataframe, metadata)
+        return dataframe
+
+    def _analyze_ticker_internal(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Parses the given candle (OHLCV) data and returns a populated DataFrame
+        add several TA indicators and buy signal to it
+        WARNING: Used internally only, may skip analysis if `process_only_new_candles` is set.
+        :param dataframe: Dataframe containing data from exchange
+        :param metadata: Metadata dictionary with additional data (e.g. 'pair')
+        :return: DataFrame of candle (OHLCV) data with indicator data and signals added
+        """
         pair = str(metadata.get('pair'))
 
         # Test if seen this pair and last candle before.
@@ -168,11 +347,10 @@ class IStrategy(ABC):
         if (not self.process_only_new_candles or
                 self._last_candle_seen_per_pair.get(pair, None) != dataframe.iloc[-1]['date']):
             # Defs that only make change on new candle data.
-            logger.debug("TA Analysis Launched")
-            dataframe = self.advise_indicators(dataframe, metadata)
-            dataframe = self.advise_buy(dataframe, metadata)
-            dataframe = self.advise_sell(dataframe, metadata)
+            dataframe = self.analyze_ticker(dataframe, metadata)
             self._last_candle_seen_per_pair[pair] = dataframe.iloc[-1]['date']
+            if self.dp:
+                self.dp._set_cached_df(pair, self.timeframe, dataframe)
         else:
             logger.debug("Skipping TA Analysis for already analyzed candle")
             dataframe['buy'] = 0
@@ -184,79 +362,113 @@ class IStrategy(ABC):
 
         return dataframe
 
-    def get_signal(self, pair: str, interval: str,
-                   dataframe: DataFrame) -> Tuple[bool, bool]:
+    def analyze_pair(self, pair: str) -> None:
         """
-        Calculates current signal based several technical analysis indicators
-        :param pair: pair in format ANT/BTC
-        :param interval: Interval to use (in min)
-        :param dataframe: Dataframe to analyze
-        :return: (Buy, Sell) A bool-tuple indicating buy/sell signal
+        Fetch data for this pair from dataprovider and analyze.
+        Stores the dataframe into the dataprovider.
+        The analyzed dataframe is then accessible via `dp.get_analyzed_dataframe()`.
+        :param pair: Pair to analyze.
         """
+        if not self.dp:
+            raise OperationalException("DataProvider not found.")
+        dataframe = self.dp.ohlcv(pair, self.timeframe)
         if not isinstance(dataframe, DataFrame) or dataframe.empty:
-            logger.warning('Empty ticker history for pair %s', pair)
-            return False, False
+            logger.warning('Empty candle (OHLCV) data for pair %s', pair)
+            return
 
         try:
-            dataframe = self.analyze_ticker(dataframe, {'pair': pair})
-        except ValueError as error:
-            logger.warning(
-                'Unable to analyze ticker for pair %s: %s',
-                pair,
-                str(error)
-            )
-            return False, False
-        except Exception as error:
-            logger.exception(
-                'Unexpected error when analyzing ticker for pair %s: %s',
-                pair,
-                str(error)
-            )
-            return False, False
+            df_len, df_close, df_date = self.preserve_df(dataframe)
+
+            dataframe = strategy_safe_wrapper(
+                self._analyze_ticker_internal, message=""
+            )(dataframe, {'pair': pair})
+
+            self.assert_df(dataframe, df_len, df_close, df_date)
+        except StrategyError as error:
+            logger.warning(f"Unable to analyze candle (OHLCV) data for pair {pair}: {error}")
+            return
 
         if dataframe.empty:
             logger.warning('Empty dataframe for pair %s', pair)
+            return
+
+    def analyze(self, pairs: List[str]) -> None:
+        """
+        Analyze all pairs using analyze_pair().
+        :param pairs: List of pairs to analyze
+        """
+        for pair in pairs:
+            self.analyze_pair(pair)
+
+    @staticmethod
+    def preserve_df(dataframe: DataFrame) -> Tuple[int, float, datetime]:
+        """ keep some data for dataframes """
+        return len(dataframe), dataframe["close"].iloc[-1], dataframe["date"].iloc[-1]
+
+    def assert_df(self, dataframe: DataFrame, df_len: int, df_close: float, df_date: datetime):
+        """
+        Ensure dataframe (length, last candle) was not modified, and has all elements we need.
+        """
+        message = ""
+        if df_len != len(dataframe):
+            message = "length"
+        elif df_close != dataframe["close"].iloc[-1]:
+            message = "last close price"
+        elif df_date != dataframe["date"].iloc[-1]:
+            message = "last date"
+        if message:
+            if self.disable_dataframe_checks:
+                logger.warning(f"Dataframe returned from strategy has mismatching {message}.")
+            else:
+                raise StrategyError(f"Dataframe returned from strategy has mismatching {message}.")
+
+    def get_signal(self, pair: str, timeframe: str, dataframe: DataFrame) -> Tuple[bool, bool]:
+        """
+        Calculates current signal based based on the buy / sell columns of the dataframe.
+        Used by Bot to get the signal to buy or sell
+        :param pair: pair in format ANT/BTC
+        :param timeframe: timeframe to use
+        :param dataframe: Analyzed dataframe to get signal from.
+        :return: (Buy, Sell) A bool-tuple indicating buy/sell signal
+        """
+        if not isinstance(dataframe, DataFrame) or dataframe.empty:
+            logger.warning(f'Empty candle (OHLCV) data for pair {pair}')
             return False, False
 
-        latest = dataframe.iloc[-1]
+        latest_date = dataframe['date'].max()
+        latest = dataframe.loc[dataframe['date'] == latest_date].iloc[-1]
+        # Explicitly convert to arrow object to ensure the below comparison does not fail
+        latest_date = arrow.get(latest_date)
 
         # Check if dataframe is out of date
-        signal_date = arrow.get(latest['date'])
-        interval_minutes = timeframe_to_minutes(interval)
+        timeframe_minutes = timeframe_to_minutes(timeframe)
         offset = self.config.get('exchange', {}).get('outdated_offset', 5)
-        if signal_date < (arrow.utcnow().shift(minutes=-(interval_minutes * 2 + offset))):
+        if latest_date < (arrow.utcnow().shift(minutes=-(timeframe_minutes * 2 + offset))):
             logger.warning(
                 'Outdated history for pair %s. Last tick is %s minutes old',
-                pair,
-                (arrow.utcnow() - signal_date).seconds // 60
+                pair, int((arrow.utcnow() - latest_date).total_seconds() // 60)
             )
             return False, False
 
         (buy, sell) = latest[SignalType.BUY.value] == 1, latest[SignalType.SELL.value] == 1
-        logger.debug(
-            'trigger: %s (pair=%s) buy=%s sell=%s',
-            latest['date'],
-            pair,
-            str(buy),
-            str(sell)
-        )
+        logger.debug('trigger: %s (pair=%s) buy=%s sell=%s',
+                     latest['date'], pair, str(buy), str(sell))
         return buy, sell
 
     def should_sell(self, trade: Trade, rate: float, date: datetime, buy: bool,
                     sell: bool, low: float = None, high: float = None,
                     force_stoploss: float = 0) -> SellCheckTuple:
         """
-        This function evaluate if on the condition required to trigger a sell has been reached
-        if the threshold is reached and updates the trade record.
+        This function evaluates if one of the conditions required to trigger a sell
+        has been reached, which can either be a stop-loss, ROI or sell-signal.
         :param low: Only used during backtesting to simulate stoploss
         :param high: Only used during backtesting, to simulate ROI
         :param force_stoploss: Externally provided stoploss
         :return: True if trade should be sold, False otherwise
         """
-
         # Set current rate to low for backtesting sell
         current_rate = low or rate
-        current_profit = trade.calc_profit_percent(current_rate)
+        current_profit = trade.calc_profit_ratio(current_rate)
 
         trade.adjust_min_max_rates(high or current_rate)
 
@@ -265,30 +477,41 @@ class IStrategy(ABC):
                                               force_stoploss=force_stoploss, high=high)
 
         if stoplossflag.sell_flag:
+            logger.debug(f"{trade.pair} - Stoploss hit. sell_flag=True, "
+                         f"sell_type={stoplossflag.sell_type}")
             return stoplossflag
 
         # Set current rate to high for backtesting sell
         current_rate = high or rate
-        current_profit = trade.calc_profit_percent(current_rate)
-        experimental = self.config.get('experimental', {})
+        current_profit = trade.calc_profit_ratio(current_rate)
+        config_ask_strategy = self.config.get('ask_strategy', {})
 
-        if buy and experimental.get('ignore_roi_if_buy_signal', False):
-            logger.debug('Buy signal still active - not selling.')
+        if buy and config_ask_strategy.get('ignore_roi_if_buy_signal', False):
+            # This one is noisy, commented out
+            # logger.debug(f"{trade.pair} - Buy signal still active. sell_flag=False")
             return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
 
         # Check if minimal roi has been reached and no longer in buy conditions (avoiding a fee)
         if self.min_roi_reached(trade=trade, current_profit=current_profit, current_time=date):
-            logger.debug('Required profit reached. Selling..')
+            logger.debug(f"{trade.pair} - Required profit reached. sell_flag=True, "
+                         f"sell_type=SellType.ROI")
             return SellCheckTuple(sell_flag=True, sell_type=SellType.ROI)
 
-        if experimental.get('sell_profit_only', False):
-            logger.debug('Checking if trade is profitable..')
+        if config_ask_strategy.get('sell_profit_only', False):
+            # This one is noisy, commented out
+            # logger.debug(f"{trade.pair} - Checking if trade is profitable...")
             if trade.calc_profit(rate=rate) <= 0:
+                # This one is noisy, commented out
+                # logger.debug(f"{trade.pair} - Trade is not profitable. sell_flag=False")
                 return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
-        if sell and not buy and experimental.get('use_sell_signal', False):
-            logger.debug('Sell signal received. Selling..')
+
+        if sell and not buy and config_ask_strategy.get('use_sell_signal', True):
+            logger.debug(f"{trade.pair} - Sell signal received. sell_flag=True, "
+                         f"sell_type=SellType.SELL_SIGNAL")
             return SellCheckTuple(sell_flag=True, sell_type=SellType.SELL_SIGNAL)
 
+        # This one is noisy, commented out...
+        # logger.debug(f"{trade.pair} - No sell signal. sell_flag=False")
         return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
 
     def stop_loss_reached(self, current_rate: float, trade: Trade,
@@ -297,57 +520,55 @@ class IStrategy(ABC):
         """
         Based on current profit of the trade and configured (trailing) stoploss,
         decides to sell or not
-        :param current_profit: current profit in percent
+        :param current_profit: current profit as ratio
         """
-
-        trailing_stop = self.config.get('trailing_stop', False)
         stop_loss_value = force_stoploss if force_stoploss else self.stoploss
 
         # Initiate stoploss with open_rate. Does nothing if stoploss is already set.
         trade.adjust_stop_loss(trade.open_rate, stop_loss_value, initial=True)
 
-        if trailing_stop:
+        if self.trailing_stop:
             # trailing stoploss handling
-            sl_offset = self.config.get('trailing_stop_positive_offset') or 0.0
-            tsl_only_offset = self.config.get('trailing_only_offset_is_reached', False)
+            sl_offset = self.trailing_stop_positive_offset
 
             # Make sure current_profit is calculated using high for backtesting.
-            high_profit = current_profit if not high else trade.calc_profit_percent(high)
+            high_profit = current_profit if not high else trade.calc_profit_ratio(high)
 
             # Don't update stoploss if trailing_only_offset_is_reached is true.
-            if not (tsl_only_offset and high_profit < sl_offset):
+            if not (self.trailing_only_offset_is_reached and high_profit < sl_offset):
                 # Specific handling for trailing_stop_positive
-                if 'trailing_stop_positive' in self.config and high_profit > sl_offset:
-                    # Ignore mypy error check in configuration that this is a float
-                    stop_loss_value = self.config.get('trailing_stop_positive')  # type: ignore
-                    logger.debug(f"using positive stop loss: {stop_loss_value} "
+                if self.trailing_stop_positive is not None and high_profit > sl_offset:
+                    stop_loss_value = self.trailing_stop_positive
+                    logger.debug(f"{trade.pair} - Using positive stoploss: {stop_loss_value} "
                                  f"offset: {sl_offset:.4g} profit: {current_profit:.4f}%")
 
                 trade.adjust_stop_loss(high or current_rate, stop_loss_value)
 
         # evaluate if the stoploss was hit if stoploss is not on exchange
+        # in Dry-Run, this handles stoploss logic as well, as the logic will not be different to
+        # regular stoploss handling.
         if ((self.stoploss is not None) and
             (trade.stop_loss >= current_rate) and
-                (not self.order_types.get('stoploss_on_exchange'))):
+                (not self.order_types.get('stoploss_on_exchange') or self.config['dry_run'])):
 
-            selltype = SellType.STOP_LOSS
+            sell_type = SellType.STOP_LOSS
 
             # If initial stoploss is not the same as current one then it is trailing.
             if trade.initial_stop_loss != trade.stop_loss:
-                selltype = SellType.TRAILING_STOP_LOSS
+                sell_type = SellType.TRAILING_STOP_LOSS
                 logger.debug(
-                    f"HIT STOP: current price at {current_rate:.6f}, "
-                    f"stop loss is {trade.stop_loss:.6f}, "
-                    f"initial stop loss was at {trade.initial_stop_loss:.6f}, "
+                    f"{trade.pair} - HIT STOP: current price at {current_rate:.6f}, "
+                    f"stoploss is {trade.stop_loss:.6f}, "
+                    f"initial stoploss was at {trade.initial_stop_loss:.6f}, "
                     f"trade opened at {trade.open_rate:.6f}")
-                logger.debug(f"trailing stop saved {trade.stop_loss - trade.initial_stop_loss:.6f}")
+                logger.debug(f"{trade.pair} - Trailing stop saved "
+                             f"{trade.stop_loss - trade.initial_stop_loss:.6f}")
 
-            logger.debug('Stop loss hit.')
-            return SellCheckTuple(sell_flag=True, sell_type=selltype)
+            return SellCheckTuple(sell_flag=True, sell_type=sell_type)
 
         return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
 
-    def min_roi_reached_entry(self, trade_dur: int) -> Optional[float]:
+    def min_roi_reached_entry(self, trade_dur: int) -> Tuple[Optional[int], Optional[float]]:
         """
         Based on trade duration defines the ROI entry that may have been reached.
         :param trade_dur: trade duration in minutes
@@ -356,36 +577,42 @@ class IStrategy(ABC):
         # Get highest entry in ROI dict where key <= trade-duration
         roi_list = list(filter(lambda x: x <= trade_dur, self.minimal_roi.keys()))
         if not roi_list:
-            return None
+            return None, None
         roi_entry = max(roi_list)
-        return self.minimal_roi[roi_entry]
+        return roi_entry, self.minimal_roi[roi_entry]
 
     def min_roi_reached(self, trade: Trade, current_profit: float, current_time: datetime) -> bool:
         """
-        Based on trade duration, current price and ROI configuration, decides whether bot should
-        sell. Requires current_profit to be in percent!!
+        Based on trade duration, current profit of the trade and ROI configuration,
+        decides whether bot should sell.
+        :param current_profit: current profit as ratio
         :return: True if bot should sell at current rate
         """
         # Check if time matches and current rate is above threshold
         trade_dur = int((current_time.timestamp() - trade.open_date.timestamp()) // 60)
-        roi = self.min_roi_reached_entry(trade_dur)
+        _, roi = self.min_roi_reached_entry(trade_dur)
         if roi is None:
             return False
         else:
             return current_profit > roi
 
-    def tickerdata_to_dataframe(self, tickerdata: Dict[str, List]) -> Dict[str, DataFrame]:
+    def ohlcvdata_to_dataframe(self, data: Dict[str, DataFrame]) -> Dict[str, DataFrame]:
         """
-        Creates a dataframe and populates indicators for given ticker data
+        Populates indicators for given candle (OHLCV) data (for multiple pairs)
+        Does not run advice_buy or advise_sell!
+        Used by optimize operations only, not during dry / live runs.
+        Using .copy() to get a fresh copy of the dataframe for every strategy run.
+        Has positive effects on memory usage for whatever reason - also when
+        using only one strategy.
         """
-        return {pair: self.advise_indicators(pair_data, {'pair': pair})
-                for pair, pair_data in tickerdata.items()}
+        return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair})
+                for pair, pair_data in data.items()}
 
     def advise_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
         Populate indicators that will be used in the Buy and Sell strategy
         This method should not be overridden.
-        :param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
+        :param dataframe: Dataframe with data from the exchange
         :param metadata: Additional information, like the currently traded pair
         :return: a Dataframe with all mandatory indicators for the strategies
         """
diff --git a/freqtrade/strategy/strategy_helper.py b/freqtrade/strategy/strategy_helper.py
new file mode 100644
index 000000000..ea0e234ec
--- /dev/null
+++ b/freqtrade/strategy/strategy_helper.py
@@ -0,0 +1,49 @@
+import pandas as pd
+
+from freqtrade.exchange import timeframe_to_minutes
+
+
+def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
+                           timeframe: str, timeframe_inf: str, ffill: bool = True) -> pd.DataFrame:
+    """
+    Correctly merge informative samples to the original dataframe, avoiding lookahead bias.
+
+    Since dates are candle open dates, merging a 15m candle that starts at 15:00, and a
+    1h candle that starts at 15:00 will result in all candles to know the close at 16:00
+    which they should not know.
+
+    Moves the date of the informative pair by 1 time interval forward.
+    This way, the 14:00 1h candle is merged to 15:00 15m candle, since the 14:00 1h candle is the
+    last candle that's closed at 15:00, 15:15, 15:30 or 15:45.
+
+    Assuming inf_tf = '1d' - then the resulting columns will be:
+    date_1d, open_1d, high_1d, low_1d, close_1d, rsi_1d
+
+    :param dataframe: Original dataframe
+    :param informative: Informative pair, most likely loaded via dp.get_pair_dataframe
+    :param timeframe: Timeframe of the original pair sample.
+    :param timeframe_inf: Timeframe of the informative pair sample.
+    :param ffill: Forwardfill missing values - optional but usually required
+    """
+
+    minutes_inf = timeframe_to_minutes(timeframe_inf)
+    minutes = timeframe_to_minutes(timeframe)
+    if minutes >= minutes_inf:
+        # No need to forwardshift if the timeframes are identical
+        informative['date_merge'] = informative["date"]
+    else:
+        informative['date_merge'] = informative["date"] + pd.to_timedelta(minutes_inf, 'm')
+
+    # Rename columns to be unique
+    informative.columns = [f"{col}_{timeframe_inf}" for col in informative.columns]
+
+    # Combine the 2 dataframes
+    # all indicators on the informative sample MUST be calculated before this point
+    dataframe = pd.merge(dataframe, informative, left_on='date',
+                         right_on=f'date_merge_{timeframe_inf}', how='left')
+    dataframe = dataframe.drop(f'date_merge_{timeframe_inf}', axis=1)
+
+    if ffill:
+        dataframe = dataframe.ffill()
+
+    return dataframe
diff --git a/freqtrade/strategy/strategy_wrapper.py b/freqtrade/strategy/strategy_wrapper.py
new file mode 100644
index 000000000..121189b68
--- /dev/null
+++ b/freqtrade/strategy/strategy_wrapper.py
@@ -0,0 +1,36 @@
+import logging
+
+from freqtrade.exceptions import StrategyError
+
+
+logger = logging.getLogger(__name__)
+
+
+def strategy_safe_wrapper(f, message: str = "", default_retval=None, supress_error=False):
+    """
+    Wrapper around user-provided methods and functions.
+    Caches all exceptions and returns either the default_retval (if it's not None) or raises
+    a StrategyError exception, which then needs to be handled by the calling method.
+    """
+    def wrapper(*args, **kwargs):
+        try:
+            return f(*args, **kwargs)
+        except ValueError as error:
+            logger.warning(
+                f"{message}"
+                f"Strategy caused the following exception: {error}"
+                f"{f}"
+            )
+            if default_retval is None and not supress_error:
+                raise StrategyError(str(error)) from error
+            return default_retval
+        except Exception as error:
+            logger.exception(
+                f"{message}"
+                f"Unexpected error {error} calling {f}"
+            )
+            if default_retval is None and not supress_error:
+                raise StrategyError(str(error)) from error
+            return default_retval
+
+    return wrapper
diff --git a/freqtrade/templates/base_config.json.j2 b/freqtrade/templates/base_config.json.j2
new file mode 100644
index 000000000..b362690f9
--- /dev/null
+++ b/freqtrade/templates/base_config.json.j2
@@ -0,0 +1,71 @@
+{
+    "max_open_trades": {{ max_open_trades }},
+    "stake_currency": "{{ stake_currency }}",
+    "stake_amount": {{ stake_amount }},
+    "tradable_balance_ratio": 0.99,
+    "fiat_display_currency": "{{ fiat_display_currency }}",
+    "timeframe": "{{ timeframe }}",
+    "dry_run": {{ dry_run | lower }},
+    "cancel_open_orders_on_exit": false,
+    "unfilledtimeout": {
+        "buy": 10,
+        "sell": 30
+    },
+    "bid_strategy": {
+        "price_side": "bid",
+        "ask_last_balance": 0.0,
+        "use_order_book": false,
+        "order_book_top": 1,
+        "check_depth_of_market": {
+            "enabled": false,
+            "bids_to_ask_delta": 1
+        }
+    },
+    "ask_strategy": {
+        "price_side": "ask",
+        "use_order_book": false,
+        "order_book_min": 1,
+        "order_book_max": 1,
+        "use_sell_signal": true,
+        "sell_profit_only": false,
+        "ignore_roi_if_buy_signal": false
+    },
+    {{ exchange | indent(4) }},
+    "pairlists": [
+        {"method": "StaticPairList"}
+    ],
+    "edge": {
+        "enabled": false,
+        "process_throttle_secs": 3600,
+        "calculate_since_number_of_days": 7,
+        "allowed_risk": 0.01,
+        "stoploss_range_min": -0.01,
+        "stoploss_range_max": -0.1,
+        "stoploss_range_step": -0.01,
+        "minimum_winrate": 0.60,
+        "minimum_expectancy": 0.20,
+        "min_trade_number": 10,
+        "max_trade_duration_minute": 1440,
+        "remove_pumps": false
+    },
+    "telegram": {
+        "enabled": {{ telegram | lower }},
+        "token": "{{ telegram_token }}",
+        "chat_id": "{{ telegram_chat_id }}"
+    },
+    "api_server": {
+        "enabled": false,
+        "listen_ip_address": "127.0.0.1",
+        "listen_port": 8080,
+        "verbosity": "info",
+        "jwt_secret_key": "somethingrandom",
+        "CORS_origins": [],
+        "username": "",
+        "password": ""
+    },
+    "initial_state": "running",
+    "forcebuy_enable": false,
+    "internals": {
+        "process_throttle_secs": 5
+    }
+}
diff --git a/freqtrade/templates/base_hyperopt.py.j2 b/freqtrade/templates/base_hyperopt.py.j2
new file mode 100644
index 000000000..ec787cbb6
--- /dev/null
+++ b/freqtrade/templates/base_hyperopt.py.j2
@@ -0,0 +1,136 @@
+# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
+
+# --- Do not remove these libs ---
+from functools import reduce
+from typing import Any, Callable, Dict, List
+
+import numpy as np  # noqa
+import pandas as pd  # noqa
+from pandas import DataFrame
+from skopt.space import Categorical, Dimension, Integer, Real  # noqa
+
+from freqtrade.optimize.hyperopt_interface import IHyperOpt
+
+# --------------------------------
+# Add your lib to import here
+import talib.abstract as ta  # noqa
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+
+
+class {{ hyperopt }}(IHyperOpt):
+    """
+    This is a Hyperopt template to get you started.
+
+    More information in the documentation: https://www.freqtrade.io/en/latest/hyperopt/
+
+    You should:
+    - Add any lib you need to build your hyperopt.
+
+    You must keep:
+    - The prototypes for the methods: populate_indicators, indicator_space, buy_strategy_generator.
+
+    The methods roi_space, generate_roi_table and stoploss_space are not required
+    and are provided by default.
+    However, you may override them if you need 'roi' and 'stoploss' spaces that
+    differ from the defaults offered by Freqtrade.
+    Sample implementation of these methods will be copied to `user_data/hyperopts` when
+    creating the user-data directory using `freqtrade create-userdir --userdir user_data`,
+    or is available online under the following URL:
+    https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py.
+    """
+
+    @staticmethod
+    def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
+        """
+        Define the buy strategy parameters to be used by Hyperopt.
+        """
+        def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
+            """
+            Buy strategy Hyperopt will build and use.
+            """
+            conditions = []
+
+            # GUARDS AND TRENDS
+            {{ buy_guards | indent(12) }}
+
+            # TRIGGERS
+            if 'trigger' in params:
+                if params['trigger'] == 'bb_lower':
+                    conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
+                if params['trigger'] == 'macd_cross_signal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['macd'], dataframe['macdsignal']
+                    ))
+                if params['trigger'] == 'sar_reversal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['close'], dataframe['sar']
+                    ))
+
+            # Check that the candle had volume
+            conditions.append(dataframe['volume'] > 0)
+
+            if conditions:
+                dataframe.loc[
+                    reduce(lambda x, y: x & y, conditions),
+                    'buy'] = 1
+
+            return dataframe
+
+        return populate_buy_trend
+
+    @staticmethod
+    def indicator_space() -> List[Dimension]:
+        """
+        Define your Hyperopt space for searching buy strategy parameters.
+        """
+        return [
+            {{ buy_space | indent(12) }}
+        ]
+
+    @staticmethod
+    def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
+        """
+        Define the sell strategy parameters to be used by Hyperopt.
+        """
+        def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
+            """
+            Sell strategy Hyperopt will build and use.
+            """
+            conditions = []
+
+            # GUARDS AND TRENDS
+            {{ sell_guards | indent(12) }}
+
+            # TRIGGERS
+            if 'sell-trigger' in params:
+                if params['sell-trigger'] == 'sell-bb_upper':
+                    conditions.append(dataframe['close'] > dataframe['bb_upperband'])
+                if params['sell-trigger'] == 'sell-macd_cross_signal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['macdsignal'], dataframe['macd']
+                    ))
+                if params['sell-trigger'] == 'sell-sar_reversal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['sar'], dataframe['close']
+                    ))
+
+            # Check that the candle had volume
+            conditions.append(dataframe['volume'] > 0)
+
+            if conditions:
+                dataframe.loc[
+                    reduce(lambda x, y: x & y, conditions),
+                    'sell'] = 1
+
+            return dataframe
+
+        return populate_sell_trend
+
+    @staticmethod
+    def sell_indicator_space() -> List[Dimension]:
+        """
+        Define your Hyperopt space for searching sell strategy parameters.
+        """
+        return [
+            {{ sell_space | indent(12) }}
+        ]
diff --git a/freqtrade/templates/base_strategy.py.j2 b/freqtrade/templates/base_strategy.py.j2
new file mode 100644
index 000000000..4a1b43e36
--- /dev/null
+++ b/freqtrade/templates/base_strategy.py.j2
@@ -0,0 +1,140 @@
+# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
+
+# --- Do not remove these libs ---
+import numpy as np  # noqa
+import pandas as pd  # noqa
+from pandas import DataFrame
+
+from freqtrade.strategy.interface import IStrategy
+
+# --------------------------------
+# Add your lib to import here
+import talib.abstract as ta
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+
+
+class {{ strategy }}(IStrategy):
+    """
+    This is a strategy template to get you started.
+    More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md
+
+    You can:
+        :return: a Dataframe with all mandatory indicators for the strategies
+    - Rename the class name (Do not forget to update class_name)
+    - Add any methods you want to build your strategy
+    - Add any lib you need to build your strategy
+
+    You must keep:
+    - the lib in the section "Do not remove these libs"
+    - the prototype for the methods: minimal_roi, stoploss, populate_indicators, populate_buy_trend,
+    populate_sell_trend, hyperopt_space, buy_strategy_generator
+    """
+    # Strategy interface version - allow new iterations of the strategy interface.
+    # Check the documentation or the Sample strategy to get the latest version.
+    INTERFACE_VERSION = 2
+
+    # Minimal ROI designed for the strategy.
+    # This attribute will be overridden if the config file contains "minimal_roi".
+    minimal_roi = {
+        "60": 0.01,
+        "30": 0.02,
+        "0": 0.04
+    }
+
+    # Optimal stoploss designed for the strategy.
+    # This attribute will be overridden if the config file contains "stoploss".
+    stoploss = -0.10
+
+    # Trailing stoploss
+    trailing_stop = False
+    # trailing_only_offset_is_reached = False
+    # trailing_stop_positive = 0.01
+    # trailing_stop_positive_offset = 0.0  # Disabled / not configured
+
+    # Optimal timeframe for the strategy.
+    timeframe = '5m'
+
+    # Run "populate_indicators()" only for new candle.
+    process_only_new_candles = False
+
+    # These values can be overridden in the "ask_strategy" section in the config.
+    use_sell_signal = True
+    sell_profit_only = False
+    ignore_roi_if_buy_signal = False
+
+    # Number of candles the strategy requires before producing valid signals
+    startup_candle_count: int = 30
+
+    # Optional order type mapping.
+    order_types = {
+        'buy': 'limit',
+        'sell': 'limit',
+        'stoploss': 'market',
+        'stoploss_on_exchange': False
+    }
+
+    # Optional order time in force.
+    order_time_in_force = {
+        'buy': 'gtc',
+        'sell': 'gtc'
+    }
+    {{ plot_config | indent(4) }}
+    def informative_pairs(self):
+        """
+        Define additional, informative pair/interval combinations to be cached from the exchange.
+        These pair/interval combinations are non-tradeable, unless they are part
+        of the whitelist as well.
+        For more information, please consult the documentation
+        :return: List of tuples in the format (pair, interval)
+            Sample: return [("ETH/USDT", "5m"),
+                            ("BTC/USDT", "15m"),
+                            ]
+        """
+        return []
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Adds several different TA indicators to the given DataFrame
+
+        Performance Note: For the best performance be frugal on the number of indicators
+        you are using. Let uncomment only the indicator you are using in your strategies
+        or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
+        :param dataframe: Dataframe with data from the exchange
+        :param metadata: Additional information, like the currently traded pair
+        :return: a Dataframe with all mandatory indicators for the strategies
+        """
+        {{ indicators | indent(8) }}
+
+        return dataframe
+
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Based on TA indicators, populates the buy signal for the given dataframe
+        :param dataframe: DataFrame populated with indicators
+        :param metadata: Additional information, like the currently traded pair
+        :return: DataFrame with buy column
+        """
+        dataframe.loc[
+            (
+                {{ buy_trend | indent(16) }}
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
+            ),
+            'buy'] = 1
+
+        return dataframe
+
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Based on TA indicators, populates the sell signal for the given dataframe
+        :param dataframe: DataFrame populated with indicators
+        :param metadata: Additional information, like the currently traded pair
+        :return: DataFrame with buy column
+        """
+        dataframe.loc[
+            (
+                {{ sell_trend | indent(16) }}
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
+            ),
+            'sell'] = 1
+        return dataframe
+    {{ additional_methods | indent(4) }}
diff --git a/freqtrade/templates/sample_hyperopt.py b/freqtrade/templates/sample_hyperopt.py
new file mode 100644
index 000000000..10743e911
--- /dev/null
+++ b/freqtrade/templates/sample_hyperopt.py
@@ -0,0 +1,208 @@
+# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
+# isort: skip_file
+
+# --- Do not remove these libs ---
+from functools import reduce
+from typing import Any, Callable, Dict, List
+
+import numpy as np  # noqa
+import pandas as pd  # noqa
+from pandas import DataFrame
+from skopt.space import Categorical, Dimension, Integer, Real  # noqa
+
+from freqtrade.optimize.hyperopt_interface import IHyperOpt
+
+# --------------------------------
+# Add your lib to import here
+import talib.abstract as ta  # noqa
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+
+
+class SampleHyperOpt(IHyperOpt):
+    """
+    This is a sample Hyperopt to inspire you.
+
+    More information in the documentation: https://www.freqtrade.io/en/latest/hyperopt/
+
+    You should:
+    - Rename the class name to some unique name.
+    - Add any methods you want to build your hyperopt.
+    - Add any lib you need to build your hyperopt.
+
+    An easier way to get a new hyperopt file is by using
+    `freqtrade new-hyperopt --hyperopt MyCoolHyperopt`.
+
+    You must keep:
+    - The prototypes for the methods: populate_indicators, indicator_space, buy_strategy_generator.
+
+    The methods roi_space, generate_roi_table and stoploss_space are not required
+    and are provided by default.
+    However, you may override them if you need 'roi' and 'stoploss' spaces that
+    differ from the defaults offered by Freqtrade.
+    Sample implementation of these methods will be copied to `user_data/hyperopts` when
+    creating the user-data directory using `freqtrade create-userdir --userdir user_data`,
+    or is available online under the following URL:
+    https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py.
+    """
+
+    @staticmethod
+    def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
+        """
+        Define the buy strategy parameters to be used by Hyperopt.
+        """
+        def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
+            """
+            Buy strategy Hyperopt will build and use.
+            """
+            conditions = []
+
+            # GUARDS AND TRENDS
+            if 'mfi-enabled' in params and params['mfi-enabled']:
+                conditions.append(dataframe['mfi'] < params['mfi-value'])
+            if 'fastd-enabled' in params and params['fastd-enabled']:
+                conditions.append(dataframe['fastd'] < params['fastd-value'])
+            if 'adx-enabled' in params and params['adx-enabled']:
+                conditions.append(dataframe['adx'] > params['adx-value'])
+            if 'rsi-enabled' in params and params['rsi-enabled']:
+                conditions.append(dataframe['rsi'] < params['rsi-value'])
+
+            # TRIGGERS
+            if 'trigger' in params:
+                if params['trigger'] == 'bb_lower':
+                    conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
+                if params['trigger'] == 'macd_cross_signal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['macd'], dataframe['macdsignal']
+                    ))
+                if params['trigger'] == 'sar_reversal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['close'], dataframe['sar']
+                    ))
+
+            # Check that volume is not 0
+            conditions.append(dataframe['volume'] > 0)
+
+            if conditions:
+                dataframe.loc[
+                    reduce(lambda x, y: x & y, conditions),
+                    'buy'] = 1
+
+            return dataframe
+
+        return populate_buy_trend
+
+    @staticmethod
+    def indicator_space() -> List[Dimension]:
+        """
+        Define your Hyperopt space for searching buy strategy parameters.
+        """
+        return [
+            Integer(10, 25, name='mfi-value'),
+            Integer(15, 45, name='fastd-value'),
+            Integer(20, 50, name='adx-value'),
+            Integer(20, 40, name='rsi-value'),
+            Categorical([True, False], name='mfi-enabled'),
+            Categorical([True, False], name='fastd-enabled'),
+            Categorical([True, False], name='adx-enabled'),
+            Categorical([True, False], name='rsi-enabled'),
+            Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
+        ]
+
+    @staticmethod
+    def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
+        """
+        Define the sell strategy parameters to be used by Hyperopt.
+        """
+        def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
+            """
+            Sell strategy Hyperopt will build and use.
+            """
+            conditions = []
+
+            # GUARDS AND TRENDS
+            if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
+                conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
+            if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']:
+                conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
+            if 'sell-adx-enabled' in params and params['sell-adx-enabled']:
+                conditions.append(dataframe['adx'] < params['sell-adx-value'])
+            if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']:
+                conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
+
+            # TRIGGERS
+            if 'sell-trigger' in params:
+                if params['sell-trigger'] == 'sell-bb_upper':
+                    conditions.append(dataframe['close'] > dataframe['bb_upperband'])
+                if params['sell-trigger'] == 'sell-macd_cross_signal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['macdsignal'], dataframe['macd']
+                    ))
+                if params['sell-trigger'] == 'sell-sar_reversal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['sar'], dataframe['close']
+                    ))
+
+            # Check that volume is not 0
+            conditions.append(dataframe['volume'] > 0)
+
+            if conditions:
+                dataframe.loc[
+                    reduce(lambda x, y: x & y, conditions),
+                    'sell'] = 1
+
+            return dataframe
+
+        return populate_sell_trend
+
+    @staticmethod
+    def sell_indicator_space() -> List[Dimension]:
+        """
+        Define your Hyperopt space for searching sell strategy parameters.
+        """
+        return [
+            Integer(75, 100, name='sell-mfi-value'),
+            Integer(50, 100, name='sell-fastd-value'),
+            Integer(50, 100, name='sell-adx-value'),
+            Integer(60, 100, name='sell-rsi-value'),
+            Categorical([True, False], name='sell-mfi-enabled'),
+            Categorical([True, False], name='sell-fastd-enabled'),
+            Categorical([True, False], name='sell-adx-enabled'),
+            Categorical([True, False], name='sell-rsi-enabled'),
+            Categorical(['sell-bb_upper',
+                         'sell-macd_cross_signal',
+                         'sell-sar_reversal'], name='sell-trigger')
+        ]
+
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Based on TA indicators. Should be a copy of same method from strategy.
+        Must align to populate_indicators in this file.
+        Only used when --spaces does not include buy space.
+        """
+        dataframe.loc[
+            (
+                (dataframe['close'] < dataframe['bb_lowerband']) &
+                (dataframe['mfi'] < 16) &
+                (dataframe['adx'] > 25) &
+                (dataframe['rsi'] < 21)
+            ),
+            'buy'] = 1
+
+        return dataframe
+
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Based on TA indicators. Should be a copy of same method from strategy.
+        Must align to populate_indicators in this file.
+        Only used when --spaces does not include sell space.
+        """
+        dataframe.loc[
+            (
+                (qtpylib.crossed_above(
+                    dataframe['macdsignal'], dataframe['macd']
+                )) &
+                (dataframe['fastd'] > 54)
+            ),
+            'sell'] = 1
+
+        return dataframe
diff --git a/user_data/hyperopts/sample_hyperopt.py b/freqtrade/templates/sample_hyperopt_advanced.py
similarity index 67%
rename from user_data/hyperopts/sample_hyperopt.py
rename to freqtrade/templates/sample_hyperopt_advanced.py
index a78906cf3..52e397466 100644
--- a/user_data/hyperopts/sample_hyperopt.py
+++ b/freqtrade/templates/sample_hyperopt_advanced.py
@@ -1,35 +1,49 @@
 # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
-
+# isort: skip_file
+# --- Do not remove these libs ---
 from functools import reduce
-from math import exp
 from typing import Any, Callable, Dict, List
-from datetime import datetime
 
-import numpy as np# noqa F401
-import talib.abstract as ta
+import numpy as np  # noqa
+import pandas as pd  # noqa
 from pandas import DataFrame
-from skopt.space import Categorical, Dimension, Integer, Real
+from skopt.space import Categorical, Dimension, Integer, Real  # noqa
 
-import freqtrade.vendor.qtpylib.indicators as qtpylib
 from freqtrade.optimize.hyperopt_interface import IHyperOpt
 
+# --------------------------------
+# Add your lib to import here
+import talib.abstract as ta  # noqa
+import freqtrade.vendor.qtpylib.indicators as qtpylib
 
-# This class is a sample. Feel free to customize it.
-class SampleHyperOpts(IHyperOpt):
-    """
-    This is a test hyperopt to inspire you.
-    More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md
-     You can:
-    - Rename the class name (Do not forget to update class_name)
-    - Add any methods you want to build your hyperopt
-    - Add any lib you need to build your hyperopt
-     You must keep:
-    - the prototype for the methods: populate_indicators, indicator_space, buy_strategy_generator,
-    roi_space, generate_roi_table, stoploss_space
-    """
 
+class AdvancedSampleHyperOpt(IHyperOpt):
+    """
+    This is a sample hyperopt to inspire you.
+    Feel free to customize it.
+
+    More information in the documentation: https://www.freqtrade.io/en/latest/hyperopt/
+
+    You should:
+    - Rename the class name to some unique name.
+    - Add any methods you want to build your hyperopt.
+    - Add any lib you need to build your hyperopt.
+
+    You must keep:
+    - The prototypes for the methods: populate_indicators, indicator_space, buy_strategy_generator.
+
+    The methods roi_space, generate_roi_table and stoploss_space are not required
+    and are provided by default.
+    However, you may override them if you need the
+    'roi' and the 'stoploss' spaces that differ from the defaults offered by Freqtrade.
+
+    This sample illustrates how to override these methods.
+    """
     @staticmethod
     def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        This method can also be loaded from the strategy, if it doesn't exist in the hyperopt class.
+        """
         dataframe['adx'] = ta.ADX(dataframe)
         macd = ta.MACD(dataframe)
         dataframe['macd'] = macd['macd']
@@ -79,6 +93,9 @@ class SampleHyperOpts(IHyperOpt):
                         dataframe['close'], dataframe['sar']
                     ))
 
+            # Check that volume is not 0
+            conditions.append(dataframe['volume'] > 0)
+
             if conditions:
                 dataframe.loc[
                     reduce(lambda x, y: x & y, conditions),
@@ -139,6 +156,9 @@ class SampleHyperOpts(IHyperOpt):
                         dataframe['sar'], dataframe['close']
                     ))
 
+            # Check that volume is not 0
+            conditions.append(dataframe['volume'] > 0)
+
             if conditions:
                 dataframe.loc[
                     reduce(lambda x, y: x & y, conditions),
@@ -171,6 +191,14 @@ class SampleHyperOpts(IHyperOpt):
     def generate_roi_table(params: Dict) -> Dict[int, float]:
         """
         Generate the ROI table that will be used by Hyperopt
+
+        This implementation generates the default legacy Freqtrade ROI tables.
+
+        Change it if you need different number of steps in the generated
+        ROI tables or other structure of the ROI tables.
+
+        Please keep it aligned with parameters in the 'roi' optimization
+        hyperspace defined by the roi_space method.
         """
         roi_table = {}
         roi_table[0] = params['roi_p1'] + params['roi_p2'] + params['roi_p3']
@@ -180,19 +208,16 @@ class SampleHyperOpts(IHyperOpt):
 
         return roi_table
 
-    @staticmethod
-    def stoploss_space() -> List[Dimension]:
-        """
-        Stoploss Value to search
-        """
-        return [
-            Real(-0.5, -0.02, name='stoploss'),
-        ]
-
     @staticmethod
     def roi_space() -> List[Dimension]:
         """
         Values to search for each ROI steps
+
+        Override it if you need some different ranges for the parameters in the
+        'roi' optimization hyperspace.
+
+        Please keep it aligned with the implementation of the
+        generate_roi_table method.
         """
         return [
             Integer(10, 120, name='roi_t1'),
@@ -203,10 +228,52 @@ class SampleHyperOpts(IHyperOpt):
             Real(0.01, 0.20, name='roi_p3'),
         ]
 
+    @staticmethod
+    def stoploss_space() -> List[Dimension]:
+        """
+        Stoploss Value to search
+
+        Override it if you need some different range for the parameter in the
+        'stoploss' optimization hyperspace.
+        """
+        return [
+            Real(-0.35, -0.02, name='stoploss'),
+        ]
+
+    @staticmethod
+    def trailing_space() -> List[Dimension]:
+        """
+        Create a trailing stoploss space.
+
+        You may override it in your custom Hyperopt class.
+        """
+        return [
+            # It was decided to always set trailing_stop is to True if the 'trailing' hyperspace
+            # is used. Otherwise hyperopt will vary other parameters that won't have effect if
+            # trailing_stop is set False.
+            # This parameter is included into the hyperspace dimensions rather than assigning
+            # it explicitly in the code in order to have it printed in the results along with
+            # other 'trailing' hyperspace parameters.
+            Categorical([True], name='trailing_stop'),
+
+            Real(0.01, 0.35, name='trailing_stop_positive'),
+
+            # 'trailing_stop_positive_offset' should be greater than 'trailing_stop_positive',
+            # so this intermediate parameter is used as the value of the difference between
+            # them. The value of the 'trailing_stop_positive_offset' is constructed in the
+            # generate_trailing_params() method.
+            # This is similar to the hyperspace dimensions used for constructing the ROI tables.
+            Real(0.001, 0.1, name='trailing_stop_positive_offset_p1'),
+
+            Categorical([True, False], name='trailing_only_offset_is_reached'),
+        ]
+
     def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Based on TA indicators. Should be a copy of from strategy
-        must align to populate_indicators in this file
+        Based on TA indicators.
+        Can be a copy of the corresponding method from the strategy,
+        or will be loaded from the strategy.
+        Must align to populate_indicators used (either from this File, or from the strategy)
         Only used when --spaces does not include buy
         """
         dataframe.loc[
@@ -222,8 +289,10 @@ class SampleHyperOpts(IHyperOpt):
 
     def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Based on TA indicators. Should be a copy of from strategy
-        must align to populate_indicators in this file
+        Based on TA indicators.
+        Can be a copy of the corresponding method from the strategy,
+        or will be loaded from the strategy.
+        Must align to populate_indicators used (either from this File, or from the strategy)
         Only used when --spaces does not include sell
         """
         dataframe.loc[
diff --git a/user_data/hyperopts/sample_hyperopt_loss.py b/freqtrade/templates/sample_hyperopt_loss.py
similarity index 97%
rename from user_data/hyperopts/sample_hyperopt_loss.py
rename to freqtrade/templates/sample_hyperopt_loss.py
index 5a2fb72b6..59e6d814a 100644
--- a/user_data/hyperopts/sample_hyperopt_loss.py
+++ b/freqtrade/templates/sample_hyperopt_loss.py
@@ -1,10 +1,11 @@
-from math import exp
 from datetime import datetime
+from math import exp
 
 from pandas import DataFrame
 
 from freqtrade.optimize.hyperopt import IHyperOptLoss
 
+
 # Define some constants:
 
 # set TARGET_TRADES to suit your number concurrent trades so its realistic
@@ -27,7 +28,8 @@ class SampleHyperOptLoss(IHyperOptLoss):
     Defines the default loss function for hyperopt
     This is intended to give you some inspiration for your own loss function.
 
-    The Function needs to return a number (float) - which becomes for better backtest results.
+    The Function needs to return a number (float) - which becomes smaller for better backtest
+    results.
     """
 
     @staticmethod
diff --git a/freqtrade/templates/sample_strategy.py b/freqtrade/templates/sample_strategy.py
new file mode 100644
index 000000000..b3f9fef07
--- /dev/null
+++ b/freqtrade/templates/sample_strategy.py
@@ -0,0 +1,366 @@
+# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
+# isort: skip_file
+# --- Do not remove these libs ---
+import numpy as np  # noqa
+import pandas as pd  # noqa
+from pandas import DataFrame
+
+from freqtrade.strategy.interface import IStrategy
+
+# --------------------------------
+# Add your lib to import here
+import talib.abstract as ta
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+
+
+# This class is a sample. Feel free to customize it.
+class SampleStrategy(IStrategy):
+    """
+    This is a sample strategy to inspire you.
+    More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md
+
+    You can:
+        :return: a Dataframe with all mandatory indicators for the strategies
+    - Rename the class name (Do not forget to update class_name)
+    - Add any methods you want to build your strategy
+    - Add any lib you need to build your strategy
+
+    You must keep:
+    - the lib in the section "Do not remove these libs"
+    - the prototype for the methods: minimal_roi, stoploss, populate_indicators, populate_buy_trend,
+    populate_sell_trend, hyperopt_space, buy_strategy_generator
+    """
+    # Strategy interface version - allow new iterations of the strategy interface.
+    # Check the documentation or the Sample strategy to get the latest version.
+    INTERFACE_VERSION = 2
+
+    # Minimal ROI designed for the strategy.
+    # This attribute will be overridden if the config file contains "minimal_roi".
+    minimal_roi = {
+        "60": 0.01,
+        "30": 0.02,
+        "0": 0.04
+    }
+
+    # Optimal stoploss designed for the strategy.
+    # This attribute will be overridden if the config file contains "stoploss".
+    stoploss = -0.10
+
+    # Trailing stoploss
+    trailing_stop = False
+    # trailing_only_offset_is_reached = False
+    # trailing_stop_positive = 0.01
+    # trailing_stop_positive_offset = 0.0  # Disabled / not configured
+
+    # Optimal ticker interval for the strategy.
+    timeframe = '5m'
+
+    # Run "populate_indicators()" only for new candle.
+    process_only_new_candles = False
+
+    # These values can be overridden in the "ask_strategy" section in the config.
+    use_sell_signal = True
+    sell_profit_only = False
+    ignore_roi_if_buy_signal = False
+
+    # Number of candles the strategy requires before producing valid signals
+    startup_candle_count: int = 30
+
+    # Optional order type mapping.
+    order_types = {
+        'buy': 'limit',
+        'sell': 'limit',
+        'stoploss': 'market',
+        'stoploss_on_exchange': False
+    }
+
+    # Optional order time in force.
+    order_time_in_force = {
+        'buy': 'gtc',
+        'sell': 'gtc'
+    }
+
+    plot_config = {
+        'main_plot': {
+            'tema': {},
+            'sar': {'color': 'white'},
+        },
+        'subplots': {
+            "MACD": {
+                'macd': {'color': 'blue'},
+                'macdsignal': {'color': 'orange'},
+            },
+            "RSI": {
+                'rsi': {'color': 'red'},
+            }
+        }
+    }
+
+    def informative_pairs(self):
+        """
+        Define additional, informative pair/interval combinations to be cached from the exchange.
+        These pair/interval combinations are non-tradeable, unless they are part
+        of the whitelist as well.
+        For more information, please consult the documentation
+        :return: List of tuples in the format (pair, interval)
+            Sample: return [("ETH/USDT", "5m"),
+                            ("BTC/USDT", "15m"),
+                            ]
+        """
+        return []
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Adds several different TA indicators to the given DataFrame
+
+        Performance Note: For the best performance be frugal on the number of indicators
+        you are using. Let uncomment only the indicator you are using in your strategies
+        or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
+        :param dataframe: Dataframe with data from the exchange
+        :param metadata: Additional information, like the currently traded pair
+        :return: a Dataframe with all mandatory indicators for the strategies
+        """
+
+        # Momentum Indicators
+        # ------------------------------------
+
+        # ADX
+        dataframe['adx'] = ta.ADX(dataframe)
+
+        # # Plus Directional Indicator / Movement
+        # dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
+        # dataframe['plus_di'] = ta.PLUS_DI(dataframe)
+
+        # # Minus Directional Indicator / Movement
+        # dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
+        # dataframe['minus_di'] = ta.MINUS_DI(dataframe)
+
+        # # Aroon, Aroon Oscillator
+        # aroon = ta.AROON(dataframe)
+        # dataframe['aroonup'] = aroon['aroonup']
+        # dataframe['aroondown'] = aroon['aroondown']
+        # dataframe['aroonosc'] = ta.AROONOSC(dataframe)
+
+        # # Awesome Oscillator
+        # dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
+
+        # # Keltner Channel
+        # keltner = qtpylib.keltner_channel(dataframe)
+        # dataframe["kc_upperband"] = keltner["upper"]
+        # dataframe["kc_lowerband"] = keltner["lower"]
+        # dataframe["kc_middleband"] = keltner["mid"]
+        # dataframe["kc_percent"] = (
+        #     (dataframe["close"] - dataframe["kc_lowerband"]) /
+        #     (dataframe["kc_upperband"] - dataframe["kc_lowerband"])
+        # )
+        # dataframe["kc_width"] = (
+        #     (dataframe["kc_upperband"] - dataframe["kc_lowerband"]) / dataframe["kc_middleband"]
+        # )
+
+        # # Ultimate Oscillator
+        # dataframe['uo'] = ta.ULTOSC(dataframe)
+
+        # # Commodity Channel Index: values [Oversold:-100, Overbought:100]
+        # dataframe['cci'] = ta.CCI(dataframe)
+
+        # RSI
+        dataframe['rsi'] = ta.RSI(dataframe)
+
+        # # Inverse Fisher transform on RSI: values [-1.0, 1.0] (https://goo.gl/2JGGoy)
+        # rsi = 0.1 * (dataframe['rsi'] - 50)
+        # dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1)
+
+        # # Inverse Fisher transform on RSI normalized: values [0.0, 100.0] (https://goo.gl/2JGGoy)
+        # dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
+
+        # # Stochastic Slow
+        # stoch = ta.STOCH(dataframe)
+        # dataframe['slowd'] = stoch['slowd']
+        # dataframe['slowk'] = stoch['slowk']
+
+        # Stochastic Fast
+        stoch_fast = ta.STOCHF(dataframe)
+        dataframe['fastd'] = stoch_fast['fastd']
+        dataframe['fastk'] = stoch_fast['fastk']
+
+        # # Stochastic RSI
+        # Please read https://github.com/freqtrade/freqtrade/issues/2961 before using this.
+        # STOCHRSI is NOT aligned with tradingview, which may result in non-expected results.
+        # stoch_rsi = ta.STOCHRSI(dataframe)
+        # dataframe['fastd_rsi'] = stoch_rsi['fastd']
+        # dataframe['fastk_rsi'] = stoch_rsi['fastk']
+
+        # MACD
+        macd = ta.MACD(dataframe)
+        dataframe['macd'] = macd['macd']
+        dataframe['macdsignal'] = macd['macdsignal']
+        dataframe['macdhist'] = macd['macdhist']
+
+        # MFI
+        dataframe['mfi'] = ta.MFI(dataframe)
+
+        # # ROC
+        # dataframe['roc'] = ta.ROC(dataframe)
+
+        # Overlap Studies
+        # ------------------------------------
+
+        # Bollinger Bands
+        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
+        dataframe['bb_lowerband'] = bollinger['lower']
+        dataframe['bb_middleband'] = bollinger['mid']
+        dataframe['bb_upperband'] = bollinger['upper']
+        dataframe["bb_percent"] = (
+            (dataframe["close"] - dataframe["bb_lowerband"]) /
+            (dataframe["bb_upperband"] - dataframe["bb_lowerband"])
+        )
+        dataframe["bb_width"] = (
+            (dataframe["bb_upperband"] - dataframe["bb_lowerband"]) / dataframe["bb_middleband"]
+        )
+
+        # Bollinger Bands - Weighted (EMA based instead of SMA)
+        # weighted_bollinger = qtpylib.weighted_bollinger_bands(
+        #     qtpylib.typical_price(dataframe), window=20, stds=2
+        # )
+        # dataframe["wbb_upperband"] = weighted_bollinger["upper"]
+        # dataframe["wbb_lowerband"] = weighted_bollinger["lower"]
+        # dataframe["wbb_middleband"] = weighted_bollinger["mid"]
+        # dataframe["wbb_percent"] = (
+        #     (dataframe["close"] - dataframe["wbb_lowerband"]) /
+        #     (dataframe["wbb_upperband"] - dataframe["wbb_lowerband"])
+        # )
+        # dataframe["wbb_width"] = (
+        #     (dataframe["wbb_upperband"] - dataframe["wbb_lowerband"]) /
+        #     dataframe["wbb_middleband"]
+        # )
+
+        # # EMA - Exponential Moving Average
+        # dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3)
+        # dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
+        # dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
+        # dataframe['ema21'] = ta.EMA(dataframe, timeperiod=21)
+        # dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
+        # dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
+
+        # # SMA - Simple Moving Average
+        # dataframe['sma3'] = ta.SMA(dataframe, timeperiod=3)
+        # dataframe['sma5'] = ta.SMA(dataframe, timeperiod=5)
+        # dataframe['sma10'] = ta.SMA(dataframe, timeperiod=10)
+        # dataframe['sma21'] = ta.SMA(dataframe, timeperiod=21)
+        # dataframe['sma50'] = ta.SMA(dataframe, timeperiod=50)
+        # dataframe['sma100'] = ta.SMA(dataframe, timeperiod=100)
+
+        # Parabolic SAR
+        dataframe['sar'] = ta.SAR(dataframe)
+
+        # TEMA - Triple Exponential Moving Average
+        dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
+
+        # Cycle Indicator
+        # ------------------------------------
+        # Hilbert Transform Indicator - SineWave
+        hilbert = ta.HT_SINE(dataframe)
+        dataframe['htsine'] = hilbert['sine']
+        dataframe['htleadsine'] = hilbert['leadsine']
+
+        # Pattern Recognition - Bullish candlestick patterns
+        # ------------------------------------
+        # # Hammer: values [0, 100]
+        # dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
+        # # Inverted Hammer: values [0, 100]
+        # dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
+        # # Dragonfly Doji: values [0, 100]
+        # dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
+        # # Piercing Line: values [0, 100]
+        # dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
+        # # Morningstar: values [0, 100]
+        # dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
+        # # Three White Soldiers: values [0, 100]
+        # dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
+
+        # Pattern Recognition - Bearish candlestick patterns
+        # ------------------------------------
+        # # Hanging Man: values [0, 100]
+        # dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
+        # # Shooting Star: values [0, 100]
+        # dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
+        # # Gravestone Doji: values [0, 100]
+        # dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
+        # # Dark Cloud Cover: values [0, 100]
+        # dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
+        # # Evening Doji Star: values [0, 100]
+        # dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
+        # # Evening Star: values [0, 100]
+        # dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
+
+        # Pattern Recognition - Bullish/Bearish candlestick patterns
+        # ------------------------------------
+        # # Three Line Strike: values [0, -100, 100]
+        # dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
+        # # Spinning Top: values [0, -100, 100]
+        # dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
+        # # Engulfing: values [0, -100, 100]
+        # dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
+        # # Harami: values [0, -100, 100]
+        # dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
+        # # Three Outside Up/Down: values [0, -100, 100]
+        # dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
+        # # Three Inside Up/Down: values [0, -100, 100]
+        # dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
+
+        # # Chart type
+        # # ------------------------------------
+        # # Heikin Ashi Strategy
+        # heikinashi = qtpylib.heikinashi(dataframe)
+        # dataframe['ha_open'] = heikinashi['open']
+        # dataframe['ha_close'] = heikinashi['close']
+        # dataframe['ha_high'] = heikinashi['high']
+        # dataframe['ha_low'] = heikinashi['low']
+
+        # Retrieve best bid and best ask from the orderbook
+        # ------------------------------------
+        """
+        # first check if dataprovider is available
+        if self.dp:
+            if self.dp.runmode in ('live', 'dry_run'):
+                ob = self.dp.orderbook(metadata['pair'], 1)
+                dataframe['best_bid'] = ob['bids'][0][0]
+                dataframe['best_ask'] = ob['asks'][0][0]
+        """
+
+        return dataframe
+
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Based on TA indicators, populates the buy signal for the given dataframe
+        :param dataframe: DataFrame populated with indicators
+        :param metadata: Additional information, like the currently traded pair
+        :return: DataFrame with buy column
+        """
+        dataframe.loc[
+            (
+                (qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
+                (dataframe['tema'] <= dataframe['bb_middleband']) &  # Guard: tema below BB middle
+                (dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard: tema is raising
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
+            ),
+            'buy'] = 1
+
+        return dataframe
+
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Based on TA indicators, populates the sell signal for the given dataframe
+        :param dataframe: DataFrame populated with indicators
+        :param metadata: Additional information, like the currently traded pair
+        :return: DataFrame with buy column
+        """
+        dataframe.loc[
+            (
+                (qtpylib.crossed_above(dataframe['rsi'], 70)) &  # Signal: RSI crosses above 70
+                (dataframe['tema'] > dataframe['bb_middleband']) &  # Guard: tema above BB middle
+                (dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard: tema is falling
+                (dataframe['volume'] > 0)  # Make sure Volume is not 0
+            ),
+            'sell'] = 1
+        return dataframe
diff --git a/freqtrade/templates/strategy_analysis_example.ipynb b/freqtrade/templates/strategy_analysis_example.ipynb
new file mode 100644
index 000000000..c6e64c74e
--- /dev/null
+++ b/freqtrade/templates/strategy_analysis_example.ipynb
@@ -0,0 +1,360 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Strategy analysis example\n",
+    "\n",
+    "Debugging a strategy can be time-consuming. Freqtrade offers helper functions to visualize raw data.\n",
+    "The following assumes you work with SampleStrategy, data for 5m timeframe from Binance and have downloaded them into the data directory in the default location."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "from freqtrade.configuration import Configuration\n",
+    "\n",
+    "# Customize these according to your needs.\n",
+    "\n",
+    "# Initialize empty configuration object\n",
+    "config = Configuration.from_files([])\n",
+    "# Optionally, use existing configuration file\n",
+    "# config = Configuration.from_files([\"config.json\"])\n",
+    "\n",
+    "# Define some constants\n",
+    "config[\"timeframe\"] = \"5m\"\n",
+    "# Name of the strategy class\n",
+    "config[\"strategy\"] = \"SampleStrategy\"\n",
+    "# Location of the data\n",
+    "data_location = Path(config['user_data_dir'], 'data', 'binance')\n",
+    "# Pair to analyze - Only use one pair here\n",
+    "pair = \"BTC_USDT\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load data using values set above\n",
+    "from freqtrade.data.history import load_pair_history\n",
+    "\n",
+    "candles = load_pair_history(datadir=data_location,\n",
+    "                            timeframe=config[\"timeframe\"],\n",
+    "                            pair=pair)\n",
+    "\n",
+    "# Confirm success\n",
+    "print(\"Loaded \" + str(len(candles)) + f\" rows of data for {pair} from {data_location}\")\n",
+    "candles.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load and run strategy\n",
+    "* Rerun each time the strategy file is changed"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load strategy using values set above\n",
+    "from freqtrade.resolvers import StrategyResolver\n",
+    "strategy = StrategyResolver.load_strategy(config)\n",
+    "\n",
+    "# Generate buy/sell signals using strategy\n",
+    "df = strategy.analyze_ticker(candles, {'pair': pair})\n",
+    "df.tail()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Display the trade details\n",
+    "\n",
+    "* Note that using `data.head()` would also work, however most indicators have some \"startup\" data at the top of the dataframe.\n",
+    "* Some possible problems\n",
+    "    * Columns with NaN values at the end of the dataframe\n",
+    "    * Columns used in `crossed*()` functions with completely different units\n",
+    "* Comparison with full backtest\n",
+    "    * having 200 buy signals as output for one pair from `analyze_ticker()` does not necessarily mean that 200 trades will be made during backtesting.\n",
+    "    * Assuming you use only one condition such as, `df['rsi'] < 30` as buy condition, this will generate multiple \"buy\" signals for each pair in sequence (until rsi returns > 29). The bot will only buy on the first of these signals (and also only if a trade-slot (\"max_open_trades\") is still available), or on one of the middle signals, as soon as a \"slot\" becomes available.  \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Report results\n",
+    "print(f\"Generated {df['buy'].sum()} buy signals\")\n",
+    "data = df.set_index('date', drop=False)\n",
+    "data.tail()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load existing objects into a Jupyter notebook\n",
+    "\n",
+    "The following cells assume that you have already generated data using the cli.  \n",
+    "They will allow you to drill deeper into your results, and perform analysis which otherwise would make the output very difficult to digest due to information overload."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Load backtest results to pandas dataframe\n",
+    "\n",
+    "Analyze a trades dataframe (also used below for plotting)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats\n",
+    "\n",
+    "# if backtest_dir points to a directory, it'll automatically load the last backtest file.\n",
+    "backtest_dir = config[\"user_data_dir\"] / \"backtest_results\"\n",
+    "# backtest_dir can also point to a specific file \n",
+    "# backtest_dir = config[\"user_data_dir\"] / \"backtest_results/backtest-result-2020-07-01_20-04-22.json\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# You can get the full backtest statistics by using the following command.\n",
+    "# This contains all information used to generate the backtest result.\n",
+    "stats = load_backtest_stats(backtest_dir)\n",
+    "\n",
+    "strategy = 'SampleStrategy'\n",
+    "# All statistics are available per strategy, so if `--strategy-list` was used during backtest, this will be reflected here as well.\n",
+    "# Example usages:\n",
+    "print(stats['strategy'][strategy]['results_per_pair'])\n",
+    "# Get pairlist used for this backtest\n",
+    "print(stats['strategy'][strategy]['pairlist'])\n",
+    "# Get market change (average change of all pairs from start to end of the backtest period)\n",
+    "print(stats['strategy'][strategy]['market_change'])\n",
+    "# Maximum drawdown ()\n",
+    "print(stats['strategy'][strategy]['max_drawdown'])\n",
+    "# Maximum drawdown start and end\n",
+    "print(stats['strategy'][strategy]['drawdown_start'])\n",
+    "print(stats['strategy'][strategy]['drawdown_end'])\n",
+    "\n",
+    "\n",
+    "# Get strategy comparison (only relevant if multiple strategies were compared)\n",
+    "print(stats['strategy_comparison'])\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load backtested trades as dataframe\n",
+    "trades = load_backtest_data(backtest_dir)\n",
+    "\n",
+    "# Show value-counts per pair\n",
+    "trades.groupby(\"pair\")[\"sell_reason\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Load live trading results into a pandas dataframe\n",
+    "\n",
+    "In case you did already some trading and want to analyze your performance"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from freqtrade.data.btanalysis import load_trades_from_db\n",
+    "\n",
+    "# Fetch trades from database\n",
+    "trades = load_trades_from_db(\"sqlite:///tradesv3.sqlite\")\n",
+    "\n",
+    "# Display results\n",
+    "trades.groupby(\"pair\")[\"sell_reason\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Analyze the loaded trades for trade parallelism\n",
+    "This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with `--disable-max-market-positions`.\n",
+    "\n",
+    "`analyze_trade_parallelism()` returns a timeseries dataframe with an \"open_trades\" column, specifying the number of open trades for each candle."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from freqtrade.data.btanalysis import analyze_trade_parallelism\n",
+    "\n",
+    "# Analyze the above\n",
+    "parallel_trades = analyze_trade_parallelism(trades, '5m')\n",
+    "\n",
+    "parallel_trades.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plot results\n",
+    "\n",
+    "Freqtrade offers interactive plotting capabilities based on plotly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from freqtrade.plot.plotting import  generate_candlestick_graph\n",
+    "# Limit graph period to keep plotly quick and reactive\n",
+    "\n",
+    "# Filter trades to one pair\n",
+    "trades_red = trades.loc[trades['pair'] == pair]\n",
+    "\n",
+    "data_red = data['2019-06-01':'2019-06-10']\n",
+    "# Generate candlestick graph\n",
+    "graph = generate_candlestick_graph(pair=pair,\n",
+    "                                   data=data_red,\n",
+    "                                   trades=trades_red,\n",
+    "                                   indicators1=['sma20', 'ema50', 'ema55'],\n",
+    "                                   indicators2=['rsi', 'macd', 'macdsignal', 'macdhist']\n",
+    "                                  )\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Show graph inline\n",
+    "# graph.show()\n",
+    "\n",
+    "# Render graph in a seperate window\n",
+    "graph.show(renderer=\"browser\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Feel free to submit an issue or Pull Request enhancing this document if you would like to share ideas on how to best analyze the data."
+   ]
+  }
+ ],
+ "metadata": {
+  "file_extension": ".py",
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  },
+  "mimetype": "text/x-python",
+  "name": "python",
+  "npconvert_exporter": "python",
+  "pygments_lexer": "ipython3",
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
+  },
+  "varInspector": {
+   "cols": {
+    "lenName": 16,
+    "lenType": 16,
+    "lenVar": 40
+   },
+   "kernels_config": {
+    "python": {
+     "delete_cmd_postfix": "",
+     "delete_cmd_prefix": "del ",
+     "library": "var_list.py",
+     "varRefreshCmd": "print(var_dic_list())"
+    },
+    "r": {
+     "delete_cmd_postfix": ") ",
+     "delete_cmd_prefix": "rm(",
+     "library": "var_list.r",
+     "varRefreshCmd": "cat(var_dic_list()) "
+    }
+   },
+   "types_to_exclude": [
+    "module",
+    "function",
+    "builtin_function_or_method",
+    "instance",
+    "_Feature"
+   ],
+   "window_display": false
+  },
+  "version": 3
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/freqtrade/templates/subtemplates/buy_trend_full.j2 b/freqtrade/templates/subtemplates/buy_trend_full.j2
new file mode 100644
index 000000000..1a0d326b3
--- /dev/null
+++ b/freqtrade/templates/subtemplates/buy_trend_full.j2
@@ -0,0 +1,3 @@
+(qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
+(dataframe['tema'] <= dataframe['bb_middleband']) &  # Guard: tema below BB middle
+(dataframe['tema'] > dataframe['tema'].shift(1)) &  # Guard: tema is raising
diff --git a/freqtrade/templates/subtemplates/buy_trend_minimal.j2 b/freqtrade/templates/subtemplates/buy_trend_minimal.j2
new file mode 100644
index 000000000..6a4079cf3
--- /dev/null
+++ b/freqtrade/templates/subtemplates/buy_trend_minimal.j2
@@ -0,0 +1 @@
+(qtpylib.crossed_above(dataframe['rsi'], 30)) &  # Signal: RSI crosses above 30
diff --git a/freqtrade/templates/subtemplates/exchange_binance.j2 b/freqtrade/templates/subtemplates/exchange_binance.j2
new file mode 100644
index 000000000..03aa0560c
--- /dev/null
+++ b/freqtrade/templates/subtemplates/exchange_binance.j2
@@ -0,0 +1,41 @@
+"exchange": {
+    "name": "{{ exchange_name | lower }}",
+    "key": "{{ exchange_key }}",
+    "secret": "{{ exchange_secret }}",
+    "ccxt_config": {"enableRateLimit": true},
+    "ccxt_async_config": {
+        "enableRateLimit": true,
+        "rateLimit": 200
+    },
+    "pair_whitelist": [
+        "ALGO/BTC",
+        "ATOM/BTC",
+        "BAT/BTC",
+        "BCH/BTC",
+        "BRD/BTC",
+        "EOS/BTC",
+        "ETH/BTC",
+        "IOTA/BTC",
+        "LINK/BTC",
+        "LTC/BTC",
+        "NEO/BTC",
+        "NXS/BTC",
+        "XMR/BTC",
+        "XRP/BTC",
+        "XTZ/BTC"
+    ],
+    "pair_blacklist": [
+        "BNB/BTC",
+        "BNB/BUSD",
+        "BNB/ETH",
+        "BNB/EUR",
+        "BNB/NGN",
+        "BNB/PAX",
+        "BNB/RUB",
+        "BNB/TRY",
+        "BNB/TUSD",
+        "BNB/USDC",
+        "BNB/USDS",
+        "BNB/USDT",
+    ]
+}
diff --git a/freqtrade/templates/subtemplates/exchange_bittrex.j2 b/freqtrade/templates/subtemplates/exchange_bittrex.j2
new file mode 100644
index 000000000..7b27318ca
--- /dev/null
+++ b/freqtrade/templates/subtemplates/exchange_bittrex.j2
@@ -0,0 +1,31 @@
+"order_types": {
+    "buy": "limit",
+    "sell": "limit",
+    "emergencysell": "limit",
+    "stoploss": "limit",
+    "stoploss_on_exchange": false
+},
+"exchange": {
+    "name": "{{ exchange_name | lower }}",
+    "key": "{{ exchange_key }}",
+    "secret": "{{ exchange_secret }}",
+    "ccxt_config": {"enableRateLimit": true},
+    "ccxt_async_config": {
+        "enableRateLimit": true,
+        "rateLimit": 500
+    },
+    "pair_whitelist": [
+        "ETH/BTC",
+        "LTC/BTC",
+        "ETC/BTC",
+        "DASH/BTC",
+        "ZEC/BTC",
+        "XLM/BTC",
+        "XRP/BTC",
+        "TRX/BTC",
+        "ADA/BTC",
+        "XMR/BTC"
+    ],
+    "pair_blacklist": [
+    ]
+}
diff --git a/freqtrade/templates/subtemplates/exchange_generic.j2 b/freqtrade/templates/subtemplates/exchange_generic.j2
new file mode 100644
index 000000000..ade9c2f28
--- /dev/null
+++ b/freqtrade/templates/subtemplates/exchange_generic.j2
@@ -0,0 +1,15 @@
+"exchange": {
+    "name": "{{ exchange_name | lower }}",
+    "key": "{{ exchange_key }}",
+    "secret": "{{ exchange_secret }}",
+    "ccxt_config": {"enableRateLimit": true},
+    "ccxt_async_config": {
+        "enableRateLimit": true
+    },
+    "pair_whitelist": [
+
+    ],
+    "pair_blacklist": [
+
+    ]
+}
diff --git a/freqtrade/templates/subtemplates/exchange_kraken.j2 b/freqtrade/templates/subtemplates/exchange_kraken.j2
new file mode 100644
index 000000000..7139a0830
--- /dev/null
+++ b/freqtrade/templates/subtemplates/exchange_kraken.j2
@@ -0,0 +1,36 @@
+"download_trades": true,
+"exchange": {
+    "name": "kraken",
+    "key": "{{ exchange_key }}",
+    "secret": "{{ exchange_secret }}",
+    "ccxt_config": {"enableRateLimit": true},
+    "ccxt_async_config": {
+        "enableRateLimit": true,
+        "rateLimit": 1000
+    },
+    "pair_whitelist": [
+        "ADA/EUR",
+        "ATOM/EUR",
+        "BAT/EUR",
+        "BCH/EUR",
+        "BTC/EUR",
+        "DAI/EUR",
+        "DASH/EUR",
+        "EOS/EUR",
+        "ETC/EUR",
+        "ETH/EUR",
+        "LINK/EUR",
+        "LTC/EUR",
+        "QTUM/EUR",
+        "REP/EUR",
+        "WAVES/EUR",
+        "XLM/EUR",
+        "XMR/EUR",
+        "XRP/EUR",
+        "XTZ/EUR",
+        "ZEC/EUR"
+    ],
+    "pair_blacklist": [
+
+    ]
+}
diff --git a/freqtrade/templates/subtemplates/hyperopt_buy_guards_full.j2 b/freqtrade/templates/subtemplates/hyperopt_buy_guards_full.j2
new file mode 100644
index 000000000..5b967f4ed
--- /dev/null
+++ b/freqtrade/templates/subtemplates/hyperopt_buy_guards_full.j2
@@ -0,0 +1,8 @@
+if params.get('mfi-enabled'):
+    conditions.append(dataframe['mfi'] < params['mfi-value'])
+if params.get('fastd-enabled'):
+    conditions.append(dataframe['fastd'] < params['fastd-value'])
+if params.get('adx-enabled'):
+    conditions.append(dataframe['adx'] > params['adx-value'])
+if params.get('rsi-enabled'):
+    conditions.append(dataframe['rsi'] < params['rsi-value'])
diff --git a/freqtrade/templates/subtemplates/hyperopt_buy_guards_minimal.j2 b/freqtrade/templates/subtemplates/hyperopt_buy_guards_minimal.j2
new file mode 100644
index 000000000..5e1022f59
--- /dev/null
+++ b/freqtrade/templates/subtemplates/hyperopt_buy_guards_minimal.j2
@@ -0,0 +1,2 @@
+if params.get('rsi-enabled'):
+    conditions.append(dataframe['rsi'] < params['rsi-value'])
diff --git a/freqtrade/templates/subtemplates/hyperopt_buy_space_full.j2 b/freqtrade/templates/subtemplates/hyperopt_buy_space_full.j2
new file mode 100644
index 000000000..29bafbd93
--- /dev/null
+++ b/freqtrade/templates/subtemplates/hyperopt_buy_space_full.j2
@@ -0,0 +1,9 @@
+Integer(10, 25, name='mfi-value'),
+Integer(15, 45, name='fastd-value'),
+Integer(20, 50, name='adx-value'),
+Integer(20, 40, name='rsi-value'),
+Categorical([True, False], name='mfi-enabled'),
+Categorical([True, False], name='fastd-enabled'),
+Categorical([True, False], name='adx-enabled'),
+Categorical([True, False], name='rsi-enabled'),
+Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
diff --git a/freqtrade/templates/subtemplates/hyperopt_buy_space_minimal.j2 b/freqtrade/templates/subtemplates/hyperopt_buy_space_minimal.j2
new file mode 100644
index 000000000..5ddf537fb
--- /dev/null
+++ b/freqtrade/templates/subtemplates/hyperopt_buy_space_minimal.j2
@@ -0,0 +1,3 @@
+Integer(20, 40, name='rsi-value'),
+Categorical([True, False], name='rsi-enabled'),
+Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
diff --git a/freqtrade/templates/subtemplates/hyperopt_sell_guards_full.j2 b/freqtrade/templates/subtemplates/hyperopt_sell_guards_full.j2
new file mode 100644
index 000000000..bd7b499f4
--- /dev/null
+++ b/freqtrade/templates/subtemplates/hyperopt_sell_guards_full.j2
@@ -0,0 +1,8 @@
+if params.get('sell-mfi-enabled'):
+    conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
+if params.get('sell-fastd-enabled'):
+    conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
+if params.get('sell-adx-enabled'):
+    conditions.append(dataframe['adx'] < params['sell-adx-value'])
+if params.get('sell-rsi-enabled'):
+    conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
diff --git a/freqtrade/templates/subtemplates/hyperopt_sell_guards_minimal.j2 b/freqtrade/templates/subtemplates/hyperopt_sell_guards_minimal.j2
new file mode 100644
index 000000000..8b4adebf6
--- /dev/null
+++ b/freqtrade/templates/subtemplates/hyperopt_sell_guards_minimal.j2
@@ -0,0 +1,2 @@
+if params.get('sell-rsi-enabled'):
+    conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
diff --git a/freqtrade/templates/subtemplates/hyperopt_sell_space_full.j2 b/freqtrade/templates/subtemplates/hyperopt_sell_space_full.j2
new file mode 100644
index 000000000..46469d532
--- /dev/null
+++ b/freqtrade/templates/subtemplates/hyperopt_sell_space_full.j2
@@ -0,0 +1,11 @@
+Integer(75, 100, name='sell-mfi-value'),
+Integer(50, 100, name='sell-fastd-value'),
+Integer(50, 100, name='sell-adx-value'),
+Integer(60, 100, name='sell-rsi-value'),
+Categorical([True, False], name='sell-mfi-enabled'),
+Categorical([True, False], name='sell-fastd-enabled'),
+Categorical([True, False], name='sell-adx-enabled'),
+Categorical([True, False], name='sell-rsi-enabled'),
+Categorical(['sell-bb_upper',
+             'sell-macd_cross_signal',
+             'sell-sar_reversal'], name='sell-trigger')
diff --git a/freqtrade/templates/subtemplates/hyperopt_sell_space_minimal.j2 b/freqtrade/templates/subtemplates/hyperopt_sell_space_minimal.j2
new file mode 100644
index 000000000..dfb110543
--- /dev/null
+++ b/freqtrade/templates/subtemplates/hyperopt_sell_space_minimal.j2
@@ -0,0 +1,5 @@
+Integer(60, 100, name='sell-rsi-value'),
+Categorical([True, False], name='sell-rsi-enabled'),
+Categorical(['sell-bb_upper',
+             'sell-macd_cross_signal',
+             'sell-sar_reversal'], name='sell-trigger')
diff --git a/freqtrade/templates/subtemplates/indicators_full.j2 b/freqtrade/templates/subtemplates/indicators_full.j2
new file mode 100644
index 000000000..57d2ca665
--- /dev/null
+++ b/freqtrade/templates/subtemplates/indicators_full.j2
@@ -0,0 +1,206 @@
+
+# Momentum Indicators
+# ------------------------------------
+
+# ADX
+dataframe['adx'] = ta.ADX(dataframe)
+
+# # Plus Directional Indicator / Movement
+# dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
+# dataframe['plus_di'] = ta.PLUS_DI(dataframe)
+
+# # Minus Directional Indicator / Movement
+# dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
+# dataframe['minus_di'] = ta.MINUS_DI(dataframe)
+
+# # Aroon, Aroon Oscillator
+# aroon = ta.AROON(dataframe)
+# dataframe['aroonup'] = aroon['aroonup']
+# dataframe['aroondown'] = aroon['aroondown']
+# dataframe['aroonosc'] = ta.AROONOSC(dataframe)
+
+# # Awesome Oscillator
+# dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
+
+# # Keltner Channel
+# keltner = qtpylib.keltner_channel(dataframe)
+# dataframe["kc_upperband"] = keltner["upper"]
+# dataframe["kc_lowerband"] = keltner["lower"]
+# dataframe["kc_middleband"] = keltner["mid"]
+# dataframe["kc_percent"] = (
+#     (dataframe["close"] - dataframe["kc_lowerband"]) /
+#     (dataframe["kc_upperband"] - dataframe["kc_lowerband"])
+# )
+# dataframe["kc_width"] = (
+#     (dataframe["kc_upperband"] - dataframe["kc_lowerband"]) / dataframe["kc_middleband"]
+# )
+
+# # Ultimate Oscillator
+# dataframe['uo'] = ta.ULTOSC(dataframe)
+
+# # Commodity Channel Index: values [Oversold:-100, Overbought:100]
+# dataframe['cci'] = ta.CCI(dataframe)
+
+# RSI
+dataframe['rsi'] = ta.RSI(dataframe)
+
+# # Inverse Fisher transform on RSI: values [-1.0, 1.0] (https://goo.gl/2JGGoy)
+# rsi = 0.1 * (dataframe['rsi'] - 50)
+# dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1)
+
+# # Inverse Fisher transform on RSI normalized: values [0.0, 100.0] (https://goo.gl/2JGGoy)
+# dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
+
+# # Stochastic Slow
+# stoch = ta.STOCH(dataframe)
+# dataframe['slowd'] = stoch['slowd']
+# dataframe['slowk'] = stoch['slowk']
+
+# Stochastic Fast
+stoch_fast = ta.STOCHF(dataframe)
+dataframe['fastd'] = stoch_fast['fastd']
+dataframe['fastk'] = stoch_fast['fastk']
+
+# # Stochastic RSI
+# Please read https://github.com/freqtrade/freqtrade/issues/2961 before using this.
+# STOCHRSI is NOT aligned with tradingview, which may result in non-expected results.
+# stoch_rsi = ta.STOCHRSI(dataframe)
+# dataframe['fastd_rsi'] = stoch_rsi['fastd']
+# dataframe['fastk_rsi'] = stoch_rsi['fastk']
+
+# MACD
+macd = ta.MACD(dataframe)
+dataframe['macd'] = macd['macd']
+dataframe['macdsignal'] = macd['macdsignal']
+dataframe['macdhist'] = macd['macdhist']
+
+# MFI
+dataframe['mfi'] = ta.MFI(dataframe)
+
+# # ROC
+# dataframe['roc'] = ta.ROC(dataframe)
+
+# Overlap Studies
+# ------------------------------------
+
+# Bollinger Bands
+bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
+dataframe['bb_lowerband'] = bollinger['lower']
+dataframe['bb_middleband'] = bollinger['mid']
+dataframe['bb_upperband'] = bollinger['upper']
+dataframe["bb_percent"] = (
+    (dataframe["close"] - dataframe["bb_lowerband"]) /
+    (dataframe["bb_upperband"] - dataframe["bb_lowerband"])
+)
+dataframe["bb_width"] = (
+    (dataframe["bb_upperband"] - dataframe["bb_lowerband"]) / dataframe["bb_middleband"]
+)
+
+# Bollinger Bands - Weighted (EMA based instead of SMA)
+# weighted_bollinger = qtpylib.weighted_bollinger_bands(
+#     qtpylib.typical_price(dataframe), window=20, stds=2
+# )
+# dataframe["wbb_upperband"] = weighted_bollinger["upper"]
+# dataframe["wbb_lowerband"] = weighted_bollinger["lower"]
+# dataframe["wbb_middleband"] = weighted_bollinger["mid"]
+# dataframe["wbb_percent"] = (
+#     (dataframe["close"] - dataframe["wbb_lowerband"]) /
+#     (dataframe["wbb_upperband"] - dataframe["wbb_lowerband"])
+# )
+# dataframe["wbb_width"] = (
+#     (dataframe["wbb_upperband"] - dataframe["wbb_lowerband"]) / dataframe["wbb_middleband"]
+# )
+
+# # EMA - Exponential Moving Average
+# dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3)
+# dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
+# dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
+# dataframe['ema21'] = ta.EMA(dataframe, timeperiod=21)
+# dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
+# dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
+
+# # SMA - Simple Moving Average
+# dataframe['sma3'] = ta.SMA(dataframe, timeperiod=3)
+# dataframe['sma5'] = ta.SMA(dataframe, timeperiod=5)
+# dataframe['sma10'] = ta.SMA(dataframe, timeperiod=10)
+# dataframe['sma21'] = ta.SMA(dataframe, timeperiod=21)
+# dataframe['sma50'] = ta.SMA(dataframe, timeperiod=50)
+# dataframe['sma100'] = ta.SMA(dataframe, timeperiod=100)
+
+# Parabolic SAR
+dataframe['sar'] = ta.SAR(dataframe)
+
+# TEMA - Triple Exponential Moving Average
+dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
+
+# Cycle Indicator
+# ------------------------------------
+# Hilbert Transform Indicator - SineWave
+hilbert = ta.HT_SINE(dataframe)
+dataframe['htsine'] = hilbert['sine']
+dataframe['htleadsine'] = hilbert['leadsine']
+
+# Pattern Recognition - Bullish candlestick patterns
+# ------------------------------------
+# # Hammer: values [0, 100]
+# dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
+# # Inverted Hammer: values [0, 100]
+# dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
+# # Dragonfly Doji: values [0, 100]
+# dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
+# # Piercing Line: values [0, 100]
+# dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
+# # Morningstar: values [0, 100]
+# dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
+# # Three White Soldiers: values [0, 100]
+# dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
+
+# Pattern Recognition - Bearish candlestick patterns
+# ------------------------------------
+# # Hanging Man: values [0, 100]
+# dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
+# # Shooting Star: values [0, 100]
+# dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
+# # Gravestone Doji: values [0, 100]
+# dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
+# # Dark Cloud Cover: values [0, 100]
+# dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
+# # Evening Doji Star: values [0, 100]
+# dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
+# # Evening Star: values [0, 100]
+# dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
+
+# Pattern Recognition - Bullish/Bearish candlestick patterns
+# ------------------------------------
+# # Three Line Strike: values [0, -100, 100]
+# dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
+# # Spinning Top: values [0, -100, 100]
+# dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
+# # Engulfing: values [0, -100, 100]
+# dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
+# # Harami: values [0, -100, 100]
+# dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
+# # Three Outside Up/Down: values [0, -100, 100]
+# dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
+# # Three Inside Up/Down: values [0, -100, 100]
+# dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
+
+# # Chart type
+# # ------------------------------------
+# # Heikin Ashi Strategy
+# heikinashi = qtpylib.heikinashi(dataframe)
+# dataframe['ha_open'] = heikinashi['open']
+# dataframe['ha_close'] = heikinashi['close']
+# dataframe['ha_high'] = heikinashi['high']
+# dataframe['ha_low'] = heikinashi['low']
+
+# Retrieve best bid and best ask from the orderbook
+# ------------------------------------
+"""
+# first check if dataprovider is available
+if self.dp:
+    if self.dp.runmode in ('live', 'dry_run'):
+        ob = self.dp.orderbook(metadata['pair'], 1)
+        dataframe['best_bid'] = ob['bids'][0][0]
+        dataframe['best_ask'] = ob['asks'][0][0]
+"""
diff --git a/freqtrade/templates/subtemplates/indicators_minimal.j2 b/freqtrade/templates/subtemplates/indicators_minimal.j2
new file mode 100644
index 000000000..7d75b4610
--- /dev/null
+++ b/freqtrade/templates/subtemplates/indicators_minimal.j2
@@ -0,0 +1,17 @@
+
+# Momentum Indicators
+# ------------------------------------
+
+# RSI
+dataframe['rsi'] = ta.RSI(dataframe)
+
+# Retrieve best bid and best ask from the orderbook
+# ------------------------------------
+"""
+# first check if dataprovider is available
+if self.dp:
+    if self.dp.runmode in ('live', 'dry_run'):
+        ob = self.dp.orderbook(metadata['pair'], 1)
+        dataframe['best_bid'] = ob['bids'][0][0]
+        dataframe['best_ask'] = ob['asks'][0][0]
+"""
diff --git a/freqtrade/templates/subtemplates/plot_config_full.j2 b/freqtrade/templates/subtemplates/plot_config_full.j2
new file mode 100644
index 000000000..ab02c7892
--- /dev/null
+++ b/freqtrade/templates/subtemplates/plot_config_full.j2
@@ -0,0 +1,18 @@
+
+plot_config = {
+    # Main plot indicators (Moving averages, ...)
+    'main_plot': {
+        'tema': {},
+        'sar': {'color': 'white'},
+    },
+    'subplots': {
+        # Subplots - each dict defines one additional plot
+        "MACD": {
+            'macd': {'color': 'blue'},
+            'macdsignal': {'color': 'orange'},
+        },
+        "RSI": {
+            'rsi': {'color': 'red'},
+        }
+    }
+}
diff --git a/freqtrade/tests/__init__.py b/freqtrade/templates/subtemplates/plot_config_minimal.j2
similarity index 100%
rename from freqtrade/tests/__init__.py
rename to freqtrade/templates/subtemplates/plot_config_minimal.j2
diff --git a/freqtrade/templates/subtemplates/sell_trend_full.j2 b/freqtrade/templates/subtemplates/sell_trend_full.j2
new file mode 100644
index 000000000..36c08c947
--- /dev/null
+++ b/freqtrade/templates/subtemplates/sell_trend_full.j2
@@ -0,0 +1,3 @@
+(qtpylib.crossed_above(dataframe['rsi'], 70)) &  # Signal: RSI crosses above 70
+(dataframe['tema'] > dataframe['bb_middleband']) &  # Guard: tema above BB middle
+(dataframe['tema'] < dataframe['tema'].shift(1)) &  # Guard: tema is falling
diff --git a/freqtrade/templates/subtemplates/sell_trend_minimal.j2 b/freqtrade/templates/subtemplates/sell_trend_minimal.j2
new file mode 100644
index 000000000..42a7b81a2
--- /dev/null
+++ b/freqtrade/templates/subtemplates/sell_trend_minimal.j2
@@ -0,0 +1 @@
+(qtpylib.crossed_above(dataframe['rsi'], 70)) &  # Signal: RSI crosses above 70
diff --git a/freqtrade/templates/subtemplates/strategy_methods_advanced.j2 b/freqtrade/templates/subtemplates/strategy_methods_advanced.j2
new file mode 100644
index 000000000..5ca6e6971
--- /dev/null
+++ b/freqtrade/templates/subtemplates/strategy_methods_advanced.j2
@@ -0,0 +1,101 @@
+
+def bot_loop_start(self, **kwargs) -> None:
+    """
+    Called at the start of the bot iteration (one loop).
+    Might be used to perform pair-independent tasks
+    (e.g. gather some remote ressource for comparison)
+
+    For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+    When not implemented by a strategy, this simply does nothing.
+    :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+    """
+    pass
+
+def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
+                        time_in_force: str, **kwargs) -> bool:
+    """
+    Called right before placing a buy order.
+    Timing for this function is critical, so avoid doing heavy computations or
+    network requests in this method.
+
+    For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+    When not implemented by a strategy, returns True (always confirming).
+
+    :param pair: Pair that's about to be bought.
+    :param order_type: Order type (as configured in order_types). usually limit or market.
+    :param amount: Amount in target (quote) currency that's going to be traded.
+    :param rate: Rate that's going to be used when using limit orders
+    :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
+    :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+    :return bool: When True is returned, then the buy-order is placed on the exchange.
+        False aborts the process
+    """
+    return True
+
+def confirm_trade_exit(self, pair: str, trade: 'Trade', order_type: str, amount: float,
+                       rate: float, time_in_force: str, sell_reason: str, **kwargs) -> bool:
+    """
+    Called right before placing a regular sell order.
+    Timing for this function is critical, so avoid doing heavy computations or
+    network requests in this method.
+
+    For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+    When not implemented by a strategy, returns True (always confirming).
+
+    :param pair: Pair that's about to be sold.
+    :param trade: trade object.
+    :param order_type: Order type (as configured in order_types). usually limit or market.
+    :param amount: Amount in quote currency.
+    :param rate: Rate that's going to be used when using limit orders
+    :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
+    :param sell_reason: Sell reason.
+        Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
+                        'sell_signal', 'force_sell', 'emergency_sell']
+    :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+    :return bool: When True is returned, then the sell-order is placed on the exchange.
+        False aborts the process
+    """
+    return True
+
+def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool:
+    """
+    Check buy timeout function callback.
+    This method can be used to override the buy-timeout.
+    It is called whenever a limit buy order has been created,
+    and is not yet fully filled.
+    Configuration options in `unfilledtimeout` will be verified before this,
+    so ensure to set these timeouts high enough.
+
+    For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+    When not implemented by a strategy, this simply returns False.
+    :param pair: Pair the trade is for
+    :param trade: trade object.
+    :param order: Order dictionary as returned from CCXT.
+    :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+    :return bool: When True is returned, then the buy-order is cancelled.
+    """
+    return False
+
+def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool:
+    """
+    Check sell timeout function callback.
+    This method can be used to override the sell-timeout.
+    It is called whenever a limit sell order has been created,
+    and is not yet fully filled.
+    Configuration options in `unfilledtimeout` will be verified before this,
+    so ensure to set these timeouts high enough.
+
+    For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+    When not implemented by a strategy, this simply returns False.
+    :param pair: Pair the trade is for
+    :param trade: trade object.
+    :param order: Order dictionary as returned from CCXT.
+    :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+    :return bool: When True is returned, then the sell-order is cancelled.
+    """
+    return False
diff --git a/freqtrade/tests/data/__init__.py b/freqtrade/templates/subtemplates/strategy_methods_empty.j2
similarity index 100%
rename from freqtrade/tests/data/__init__.py
rename to freqtrade/templates/subtemplates/strategy_methods_empty.j2
diff --git a/freqtrade/tests/conftest.py b/freqtrade/tests/conftest.py
deleted file mode 100644
index 5862a2e89..000000000
--- a/freqtrade/tests/conftest.py
+++ /dev/null
@@ -1,1043 +0,0 @@
-# pragma pylint: disable=missing-docstring
-import json
-import logging
-import re
-from copy import deepcopy
-from datetime import datetime
-from functools import reduce
-from pathlib import Path
-from unittest.mock import MagicMock, PropertyMock
-
-import arrow
-import pytest
-from telegram import Chat, Message, Update
-
-from freqtrade import constants, persistence
-from freqtrade.configuration import Arguments
-from freqtrade.data.converter import parse_ticker_dataframe
-from freqtrade.edge import Edge, PairInfo
-from freqtrade.exchange import Exchange
-from freqtrade.freqtradebot import FreqtradeBot
-from freqtrade.resolvers import ExchangeResolver
-from freqtrade.worker import Worker
-
-
-logging.getLogger('').setLevel(logging.INFO)
-
-
-def log_has(line, logs):
-    # caplog mocker returns log as a tuple: ('freqtrade.something', logging.WARNING, 'foobar')
-    # and we want to match line against foobar in the tuple
-    return reduce(lambda a, b: a or b,
-                  filter(lambda x: x[2] == line, logs),
-                  False)
-
-
-def log_has_re(line, logs):
-    return reduce(lambda a, b: a or b,
-                  filter(lambda x: re.match(line, x[2]), logs),
-                  False)
-
-
-def get_args(args):
-    return Arguments(args, '').get_parsed_arg()
-
-
-def patched_configuration_load_config_file(mocker, config) -> None:
-    mocker.patch(
-        'freqtrade.configuration.configuration.Configuration._load_config_file',
-        lambda *args, **kwargs: config
-    )
-
-
-def patch_exchange(mocker, api_mock=None, id='bittrex') -> None:
-    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
-    mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
-    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
-    mocker.patch('freqtrade.exchange.Exchange.validate_ordertypes', MagicMock())
-    mocker.patch('freqtrade.exchange.Exchange.id', PropertyMock(return_value=id))
-    mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value=id.title()))
-
-    if api_mock:
-        mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
-    else:
-        mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock())
-
-
-def get_patched_exchange(mocker, config, api_mock=None, id='bittrex') -> Exchange:
-    patch_exchange(mocker, api_mock, id)
-    config["exchange"]["name"] = id
-    try:
-        exchange = ExchangeResolver(id, config).exchange
-    except ImportError:
-        exchange = Exchange(config)
-    return exchange
-
-
-def patch_wallet(mocker, free=999.9) -> None:
-    mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(
-        return_value=free
-    ))
-
-
-def patch_edge(mocker) -> None:
-    # "ETH/BTC",
-    # "LTC/BTC",
-    # "XRP/BTC",
-    # "NEO/BTC"
-
-    mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
-        return_value={
-            'NEO/BTC': PairInfo(-0.20, 0.66, 3.71, 0.50, 1.71, 10, 25),
-            'LTC/BTC': PairInfo(-0.21, 0.66, 3.71, 0.50, 1.71, 11, 20),
-        }
-    ))
-    mocker.patch('freqtrade.edge.Edge.calculate', MagicMock(return_value=True))
-
-
-def get_patched_edge(mocker, config) -> Edge:
-    patch_edge(mocker)
-    edge = Edge(config)
-    return edge
-
-# Functions for recurrent object patching
-
-
-def patch_freqtradebot(mocker, config) -> None:
-    """
-    This function patch _init_modules() to not call dependencies
-    :param mocker: a Mocker object to apply patches
-    :param config: Config to pass to the bot
-    :return: None
-    """
-    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
-    persistence.init(config['db_url'])
-    patch_exchange(mocker, None)
-    mocker.patch('freqtrade.freqtradebot.RPCManager._init', MagicMock())
-    mocker.patch('freqtrade.freqtradebot.RPCManager.send_msg', MagicMock())
-
-
-def get_patched_freqtradebot(mocker, config) -> FreqtradeBot:
-    """
-    This function patches _init_modules() to not call dependencies
-    :param mocker: a Mocker object to apply patches
-    :param config: Config to pass to the bot
-    :return: FreqtradeBot
-    """
-    patch_freqtradebot(mocker, config)
-    return FreqtradeBot(config)
-
-
-def get_patched_worker(mocker, config) -> Worker:
-    """
-    This function patches _init_modules() to not call dependencies
-    :param mocker: a Mocker object to apply patches
-    :param config: Config to pass to the bot
-    :return: Worker
-    """
-    patch_freqtradebot(mocker, config)
-    return Worker(args=None, config=config)
-
-
-def patch_get_signal(freqtrade: FreqtradeBot, value=(True, False)) -> None:
-    """
-    :param mocker: mocker to patch IStrategy class
-    :param value: which value IStrategy.get_signal() must return
-    :return: None
-    """
-    freqtrade.strategy.get_signal = lambda e, s, t: value
-    freqtrade.exchange.refresh_latest_ohlcv = lambda p: None
-
-
-@pytest.fixture(autouse=True)
-def patch_coinmarketcap(mocker) -> None:
-    """
-    Mocker to coinmarketcap to speed up tests
-    :param mocker: mocker to patch coinmarketcap class
-    :return: None
-    """
-
-    tickermock = MagicMock(return_value={'price_usd': 12345.0})
-    listmock = MagicMock(return_value={'data': [{'id': 1, 'name': 'Bitcoin', 'symbol': 'BTC',
-                                                 'website_slug': 'bitcoin'},
-                                                {'id': 1027, 'name': 'Ethereum', 'symbol': 'ETH',
-                                                 'website_slug': 'ethereum'}
-                                                ]})
-    mocker.patch.multiple(
-        'freqtrade.rpc.fiat_convert.Market',
-        ticker=tickermock,
-        listings=listmock,
-
-    )
-
-
-@pytest.fixture(scope='function')
-def init_persistence(default_conf):
-    persistence.init(default_conf['db_url'], default_conf['dry_run'])
-
-
-@pytest.fixture(scope="function")
-def default_conf():
-    """ Returns validated configuration suitable for most tests """
-    configuration = {
-        "max_open_trades": 1,
-        "stake_currency": "BTC",
-        "stake_amount": 0.001,
-        "fiat_display_currency": "USD",
-        "ticker_interval": '5m',
-        "dry_run": True,
-        "minimal_roi": {
-            "40": 0.0,
-            "30": 0.01,
-            "20": 0.02,
-            "0": 0.04
-        },
-        "stoploss": -0.10,
-        "unfilledtimeout": {
-            "buy": 10,
-            "sell": 30
-        },
-        "bid_strategy": {
-            "ask_last_balance": 0.0,
-            "use_order_book": False,
-            "order_book_top": 1,
-            "check_depth_of_market": {
-                "enabled": False,
-                "bids_to_ask_delta": 1
-            }
-        },
-        "ask_strategy": {
-            "use_order_book": False,
-            "order_book_min": 1,
-            "order_book_max": 1
-        },
-        "exchange": {
-            "name": "bittrex",
-            "enabled": True,
-            "key": "key",
-            "secret": "secret",
-            "pair_whitelist": [
-                "ETH/BTC",
-                "LTC/BTC",
-                "XRP/BTC",
-                "NEO/BTC"
-            ],
-            "pair_blacklist": [
-                "DOGE/BTC",
-                "HOT/BTC",
-            ]
-        },
-        "telegram": {
-            "enabled": True,
-            "token": "token",
-            "chat_id": "0"
-        },
-        "initial_state": "running",
-        "db_url": "sqlite://",
-        "verbosity": 3,
-    }
-    return configuration
-
-
-@pytest.fixture
-def update():
-    _update = Update(0)
-    _update.message = Message(0, 0, datetime.utcnow(), Chat(0, 0))
-    return _update
-
-
-@pytest.fixture
-def fee():
-    return MagicMock(return_value=0.0025)
-
-
-@pytest.fixture
-def ticker():
-    return MagicMock(return_value={
-        'bid': 0.00001098,
-        'ask': 0.00001099,
-        'last': 0.00001098,
-    })
-
-
-@pytest.fixture
-def ticker_sell_up():
-    return MagicMock(return_value={
-        'bid': 0.00001172,
-        'ask': 0.00001173,
-        'last': 0.00001172,
-    })
-
-
-@pytest.fixture
-def ticker_sell_down():
-    return MagicMock(return_value={
-        'bid': 0.00001044,
-        'ask': 0.00001043,
-        'last': 0.00001044,
-    })
-
-
-@pytest.fixture
-def markets():
-    return {
-        'ETH/BTC': {
-            'id': 'ethbtc',
-            'symbol': 'ETH/BTC',
-            'base': 'ETH',
-            'quote': 'BTC',
-            'active': True,
-            'precision': {
-                'price': 8,
-                'amount': 8,
-                'cost': 8,
-            },
-            'lot': 0.00000001,
-            'limits': {
-                'amount': {
-                    'min': 0.01,
-                    'max': 1000,
-                },
-                'price': 500000,
-                'cost': {
-                    'min': 1,
-                    'max': 500000,
-                },
-            },
-            'info': '',
-        },
-        'TKN/BTC': {
-            'id': 'tknbtc',
-            'symbol': 'TKN/BTC',
-            'base': 'TKN',
-            'quote': 'BTC',
-            'active': True,
-            'precision': {
-                'price': 8,
-                'amount': 8,
-                'cost': 8,
-            },
-            'lot': 0.00000001,
-            'limits': {
-                'amount': {
-                    'min': 0.01,
-                    'max': 1000,
-                },
-                'price': 500000,
-                'cost': {
-                    'min': 1,
-                    'max': 500000,
-                },
-            },
-            'info': '',
-        },
-        'BLK/BTC': {
-            'id': 'blkbtc',
-            'symbol': 'BLK/BTC',
-            'base': 'BLK',
-            'quote': 'BTC',
-            'active': True,
-            'precision': {
-                'price': 8,
-                'amount': 8,
-                'cost': 8,
-            },
-            'lot': 0.00000001,
-            'limits': {
-                'amount': {
-                    'min': 0.01,
-                    'max': 1000,
-                },
-                'price': 500000,
-                'cost': {
-                    'min': 1,
-                    'max': 500000,
-                },
-            },
-            'info': '',
-        },
-        'LTC/BTC': {
-            'id': 'ltcbtc',
-            'symbol': 'LTC/BTC',
-            'base': 'LTC',
-            'quote': 'BTC',
-            'active': False,
-            'precision': {
-                'price': 8,
-                'amount': 8,
-                'cost': 8,
-            },
-            'lot': 0.00000001,
-            'limits': {
-                'amount': {
-                    'min': 0.01,
-                    'max': 1000,
-                },
-                'price': 500000,
-                'cost': {
-                    'min': 1,
-                    'max': 500000,
-                },
-            },
-            'info': '',
-        },
-        'XRP/BTC': {
-            'id': 'xrpbtc',
-            'symbol': 'XRP/BTC',
-            'base': 'XRP',
-            'quote': 'BTC',
-            'active': False,
-            'precision': {
-                'price': 8,
-                'amount': 8,
-                'cost': 8,
-            },
-            'lot': 0.00000001,
-            'limits': {
-                'amount': {
-                    'min': 0.01,
-                    'max': 1000,
-                },
-                'price': 500000,
-                'cost': {
-                    'min': 1,
-                    'max': 500000,
-                },
-            },
-            'info': '',
-        },
-        'NEO/BTC': {
-            'id': 'neobtc',
-            'symbol': 'NEO/BTC',
-            'base': 'NEO',
-            'quote': 'BTC',
-            'active': False,
-            'precision': {
-                'price': 8,
-                'amount': 8,
-                'cost': 8,
-            },
-            'lot': 0.00000001,
-            'limits': {
-                'amount': {
-                    'min': 0.01,
-                    'max': 1000,
-                },
-                'price': 500000,
-                'cost': {
-                    'min': 1,
-                    'max': 500000,
-                },
-            },
-            'info': '',
-        },
-        'BTT/BTC': {
-            'id': 'BTTBTC',
-            'symbol': 'BTT/BTC',
-            'base': 'BTT',
-            'quote': 'BTC',
-            'active': True,
-            'precision': {
-                'base': 8,
-                'quote': 8,
-                'amount': 0,
-                'price': 8
-            },
-            'limits': {
-                'amount': {
-                    'min': 1.0,
-                    'max': 90000000.0
-                },
-                'price': {
-                    'min': None,
-                    'max': None
-                },
-                'cost': {
-                    'min': 0.001,
-                    'max': None
-                }
-            },
-            'info': "",
-        },
-        'ETH/USDT': {
-            'id': 'USDT-ETH',
-            'symbol': 'ETH/USDT',
-            'base': 'ETH',
-            'quote': 'USDT',
-            'precision': {
-                'amount': 8,
-                'price': 8
-            },
-            'limits': {
-                'amount': {
-                    'min': 0.02214286,
-                    'max': None
-                },
-                'price': {
-                    'min': 1e-08,
-                    'max': None
-                }
-            },
-            'active': True,
-            'info': ""
-        },
-        'LTC/USDT': {
-            'id': 'USDT-LTC',
-            'symbol': 'LTC/USDT',
-            'base': 'LTC',
-            'quote': 'USDT',
-            'active': True,
-            'precision': {
-                'amount': 8,
-                'price': 8
-            },
-            'limits': {
-                'amount': {
-                    'min': 0.06646786,
-                    'max': None
-                },
-                'price': {
-                    'min': 1e-08,
-                    'max': None
-                }
-            },
-            'info': ""
-        }
-    }
-
-
-@pytest.fixture
-def markets_empty():
-    return MagicMock(return_value=[])
-
-
-@pytest.fixture(scope='function')
-def limit_buy_order():
-    return {
-        'id': 'mocked_limit_buy',
-        'type': 'limit',
-        'side': 'buy',
-        'pair': 'mocked',
-        'datetime': arrow.utcnow().isoformat(),
-        'price': 0.00001099,
-        'amount': 90.99181073,
-        'remaining': 0.0,
-        'status': 'closed'
-    }
-
-
-@pytest.fixture(scope='function')
-def market_buy_order():
-    return {
-        'id': 'mocked_market_buy',
-        'type': 'market',
-        'side': 'buy',
-        'pair': 'mocked',
-        'datetime': arrow.utcnow().isoformat(),
-        'price': 0.00004099,
-        'amount': 91.99181073,
-        'remaining': 0.0,
-        'status': 'closed'
-    }
-
-
-@pytest.fixture
-def market_sell_order():
-    return {
-        'id': 'mocked_limit_sell',
-        'type': 'market',
-        'side': 'sell',
-        'pair': 'mocked',
-        'datetime': arrow.utcnow().isoformat(),
-        'price': 0.00004173,
-        'amount': 91.99181073,
-        'remaining': 0.0,
-        'status': 'closed'
-    }
-
-
-@pytest.fixture
-def limit_buy_order_old():
-    return {
-        'id': 'mocked_limit_buy_old',
-        'type': 'limit',
-        'side': 'buy',
-        'pair': 'mocked',
-        'datetime': str(arrow.utcnow().shift(minutes=-601).datetime),
-        'price': 0.00001099,
-        'amount': 90.99181073,
-        'remaining': 90.99181073,
-        'status': 'open'
-    }
-
-
-@pytest.fixture
-def limit_sell_order_old():
-    return {
-        'id': 'mocked_limit_sell_old',
-        'type': 'limit',
-        'side': 'sell',
-        'pair': 'ETH/BTC',
-        'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
-        'price': 0.00001099,
-        'amount': 90.99181073,
-        'remaining': 90.99181073,
-        'status': 'open'
-    }
-
-
-@pytest.fixture
-def limit_buy_order_old_partial():
-    return {
-        'id': 'mocked_limit_buy_old_partial',
-        'type': 'limit',
-        'side': 'buy',
-        'pair': 'ETH/BTC',
-        'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
-        'price': 0.00001099,
-        'amount': 90.99181073,
-        'remaining': 67.99181073,
-        'status': 'open'
-    }
-
-
-@pytest.fixture
-def limit_sell_order():
-    return {
-        'id': 'mocked_limit_sell',
-        'type': 'limit',
-        'side': 'sell',
-        'pair': 'mocked',
-        'datetime': arrow.utcnow().isoformat(),
-        'price': 0.00001173,
-        'amount': 90.99181073,
-        'remaining': 0.0,
-        'status': 'closed'
-    }
-
-
-@pytest.fixture
-def order_book_l2():
-    return MagicMock(return_value={
-        'bids': [
-            [0.043936, 10.442],
-            [0.043935, 31.865],
-            [0.043933, 11.212],
-            [0.043928, 0.088],
-            [0.043925, 10.0],
-            [0.043921, 10.0],
-            [0.04392, 37.64],
-            [0.043899, 0.066],
-            [0.043885, 0.676],
-            [0.04387, 22.758]
-        ],
-        'asks': [
-            [0.043949, 0.346],
-            [0.04395, 0.608],
-            [0.043951, 3.948],
-            [0.043954, 0.288],
-            [0.043958, 9.277],
-            [0.043995, 1.566],
-            [0.044, 0.588],
-            [0.044002, 0.992],
-            [0.044003, 0.095],
-            [0.04402, 37.64]
-        ],
-        'timestamp': None,
-        'datetime': None,
-        'nonce': 288004540
-    })
-
-
-@pytest.fixture
-def ticker_history_list():
-    return [
-        [
-            1511686200000,  # unix timestamp ms
-            8.794e-05,  # open
-            8.948e-05,  # high
-            8.794e-05,  # low
-            8.88e-05,  # close
-            0.0877869,  # volume (in quote currency)
-        ],
-        [
-            1511686500000,
-            8.88e-05,
-            8.942e-05,
-            8.88e-05,
-            8.893e-05,
-            0.05874751,
-        ],
-        [
-            1511686800000,
-            8.891e-05,
-            8.893e-05,
-            8.875e-05,
-            8.877e-05,
-            0.7039405
-        ]
-    ]
-
-
-@pytest.fixture
-def ticker_history(ticker_history_list):
-    return parse_ticker_dataframe(ticker_history_list, "5m", pair="UNITTEST/BTC", fill_missing=True)
-
-
-@pytest.fixture
-def tickers():
-    return MagicMock(return_value={
-        'ETH/BTC': {
-            'symbol': 'ETH/BTC',
-            'timestamp': 1522014806207,
-            'datetime': '2018-03-25T21:53:26.207Z',
-            'high': 0.061697,
-            'low': 0.060531,
-            'bid': 0.061588,
-            'bidVolume': 3.321,
-            'ask': 0.061655,
-            'askVolume': 0.212,
-            'vwap': 0.06105296,
-            'open': 0.060809,
-            'close': 0.060761,
-            'first': None,
-            'last': 0.061588,
-            'change': 1.281,
-            'percentage': None,
-            'average': None,
-            'baseVolume': 111649.001,
-            'quoteVolume': 6816.50176926,
-            'info': {}
-        },
-        'TKN/BTC': {
-            'symbol': 'TKN/BTC',
-            'timestamp': 1522014806169,
-            'datetime': '2018-03-25T21:53:26.169Z',
-            'high': 0.01885,
-            'low': 0.018497,
-            'bid': 0.018799,
-            'bidVolume': 8.38,
-            'ask': 0.018802,
-            'askVolume': 15.0,
-            'vwap': 0.01869197,
-            'open': 0.018585,
-            'close': 0.018573,
-            'last': 0.018799,
-            'baseVolume': 81058.66,
-            'quoteVolume': 2247.48374509,
-        },
-        'BLK/BTC': {
-            'symbol': 'BLK/BTC',
-            'timestamp': 1522014806072,
-            'datetime': '2018-03-25T21:53:26.720Z',
-            'high': 0.007745,
-            'low': 0.007512,
-            'bid': 0.007729,
-            'bidVolume': 0.01,
-            'ask': 0.007743,
-            'askVolume': 21.37,
-            'vwap': 0.00761466,
-            'open': 0.007653,
-            'close': 0.007652,
-            'first': None,
-            'last': 0.007743,
-            'change': 1.176,
-            'percentage': None,
-            'average': None,
-            'baseVolume': 295152.26,
-            'quoteVolume': 1515.14631229,
-            'info': {}
-        },
-        'LTC/BTC': {
-            'symbol': 'LTC/BTC',
-            'timestamp': 1523787258992,
-            'datetime': '2018-04-15T10:14:19.992Z',
-            'high': 0.015978,
-            'low': 0.0157,
-            'bid': 0.015954,
-            'bidVolume': 12.83,
-            'ask': 0.015957,
-            'askVolume': 0.49,
-            'vwap': 0.01581636,
-            'open': 0.015823,
-            'close': 0.01582,
-            'first': None,
-            'last': 0.015951,
-            'change': 0.809,
-            'percentage': None,
-            'average': None,
-            'baseVolume': 88620.68,
-            'quoteVolume': 1401.65697943,
-            'info': {}
-        },
-        'BTT/BTC': {
-            'symbol': 'BTT/BTC',
-            'timestamp': 1550936557206,
-            'datetime': '2019-02-23T15:42:37.206Z',
-            'high': 0.00000026,
-            'low': 0.00000024,
-            'bid': 0.00000024,
-            'bidVolume': 2446894197.0,
-            'ask': 0.00000025,
-            'askVolume': 2447913837.0,
-            'vwap': 0.00000025,
-            'open': 0.00000026,
-            'close': 0.00000024,
-            'last': 0.00000024,
-            'previousClose': 0.00000026,
-            'change': -0.00000002,
-            'percentage': -7.692,
-            'average': None,
-            'baseVolume': 4886464537.0,
-            'quoteVolume': 1215.14489611,
-            'info': {}
-        },
-        'ETH/USDT': {
-            'symbol': 'ETH/USDT',
-            'timestamp': 1522014804118,
-            'datetime': '2018-03-25T21:53:24.118Z',
-            'high': 530.88,
-            'low': 512.0,
-            'bid': 529.73,
-            'bidVolume': 0.2,
-            'ask': 530.21,
-            'askVolume': 0.2464,
-            'vwap': 521.02438405,
-            'open': 527.27,
-            'close': 528.42,
-            'first': None,
-            'last': 530.21,
-            'change': 0.558,
-            'percentage': None,
-            'average': None,
-            'baseVolume': 72300.0659,
-            'quoteVolume': 37670097.3022171,
-            'info': {}
-        },
-        'TKN/USDT': {
-            'symbol': 'TKN/USDT',
-            'timestamp': 1522014806198,
-            'datetime': '2018-03-25T21:53:26.198Z',
-            'high': 8718.0,
-            'low': 8365.77,
-            'bid': 8603.64,
-            'bidVolume': 0.15846,
-            'ask': 8603.67,
-            'askVolume': 0.069147,
-            'vwap': 8536.35621697,
-            'open': 8680.0,
-            'close': 8680.0,
-            'first': None,
-            'last': 8603.67,
-            'change': -0.879,
-            'percentage': None,
-            'average': None,
-            'baseVolume': 30414.604298,
-            'quoteVolume': 259629896.48584127,
-            'info': {}
-        },
-        'BLK/USDT': {
-            'symbol': 'BLK/USDT',
-            'timestamp': 1522014806145,
-            'datetime': '2018-03-25T21:53:26.145Z',
-            'high': 66.95,
-            'low': 63.38,
-            'bid': 66.473,
-            'bidVolume': 4.968,
-            'ask': 66.54,
-            'askVolume': 2.704,
-            'vwap': 65.0526901,
-            'open': 66.43,
-            'close': 66.383,
-            'first': None,
-            'last': 66.5,
-            'change': 0.105,
-            'percentage': None,
-            'average': None,
-            'baseVolume': 294106.204,
-            'quoteVolume': 19132399.743954,
-            'info': {}
-        },
-        'LTC/USDT': {
-            'symbol': 'LTC/USDT',
-            'timestamp': 1523787257812,
-            'datetime': '2018-04-15T10:14:18.812Z',
-            'high': 129.94,
-            'low': 124.0,
-            'bid': 129.28,
-            'bidVolume': 0.03201,
-            'ask': 129.52,
-            'askVolume': 0.14529,
-            'vwap': 126.92838682,
-            'open': 127.0,
-            'close': 127.1,
-            'first': None,
-            'last': 129.28,
-            'change': 1.795,
-            'percentage': None,
-            'average': None,
-            'baseVolume': 59698.79897,
-            'quoteVolume': 29132399.743954,
-            'info': {}
-        }
-    })
-
-
-@pytest.fixture
-def result():
-    with Path('freqtrade/tests/testdata/UNITTEST_BTC-1m.json').open('r') as data_file:
-        return parse_ticker_dataframe(json.load(data_file), '1m', pair="UNITTEST/BTC",
-                                      fill_missing=True)
-
-# FIX:
-# Create an fixture/function
-# that inserts a trade of some type and open-status
-# return the open-order-id
-# See tests in rpc/main that could use this
-
-
-@pytest.fixture(scope="function")
-def trades_for_order():
-    return [{'info': {'id': 34567,
-                      'orderId': 123456,
-                      'price': '0.24544100',
-                      'qty': '8.00000000',
-                      'commission': '0.00800000',
-                      'commissionAsset': 'LTC',
-                      'time': 1521663363189,
-                      'isBuyer': True,
-                      'isMaker': False,
-                      'isBestMatch': True},
-             'timestamp': 1521663363189,
-             'datetime': '2018-03-21T20:16:03.189Z',
-             'symbol': 'LTC/ETH',
-             'id': '34567',
-             'order': '123456',
-             'type': None,
-             'side': 'buy',
-             'price': 0.245441,
-             'cost': 1.963528,
-             'amount': 8.0,
-             'fee': {'cost': 0.008, 'currency': 'LTC'}}]
-
-
-@pytest.fixture(scope="function")
-def trades_for_order2():
-    return [{'info': {'id': 34567,
-                      'orderId': 123456,
-                      'price': '0.24544100',
-                      'qty': '8.00000000',
-                      'commission': '0.00800000',
-                      'commissionAsset': 'LTC',
-                      'time': 1521663363189,
-                      'isBuyer': True,
-                      'isMaker': False,
-                      'isBestMatch': True},
-             'timestamp': 1521663363189,
-             'datetime': '2018-03-21T20:16:03.189Z',
-             'symbol': 'LTC/ETH',
-             'id': '34567',
-             'order': '123456',
-             'type': None,
-             'side': 'buy',
-             'price': 0.245441,
-             'cost': 1.963528,
-             'amount': 4.0,
-             'fee': {'cost': 0.004, 'currency': 'LTC'}},
-            {'info': {'id': 34567,
-                      'orderId': 123456,
-                      'price': '0.24544100',
-                      'qty': '8.00000000',
-                      'commission': '0.00800000',
-                      'commissionAsset': 'LTC',
-                      'time': 1521663363189,
-                      'isBuyer': True,
-                      'isMaker': False,
-                      'isBestMatch': True},
-             'timestamp': 1521663363189,
-             'datetime': '2018-03-21T20:16:03.189Z',
-             'symbol': 'LTC/ETH',
-             'id': '34567',
-             'order': '123456',
-             'type': None,
-             'side': 'buy',
-             'price': 0.245441,
-             'cost': 1.963528,
-             'amount': 4.0,
-             'fee': {'cost': 0.004, 'currency': 'LTC'}}]
-
-
-@pytest.fixture
-def buy_order_fee():
-    return {
-        'id': 'mocked_limit_buy_old',
-        'type': 'limit',
-        'side': 'buy',
-        'pair': 'mocked',
-        'datetime': str(arrow.utcnow().shift(minutes=-601).datetime),
-        'price': 0.245441,
-        'amount': 8.0,
-        'remaining': 90.99181073,
-        'status': 'closed',
-        'fee': None
-    }
-
-
-@pytest.fixture(scope="function")
-def edge_conf(default_conf):
-    conf = deepcopy(default_conf)
-    conf['max_open_trades'] = -1
-    conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
-    conf['edge'] = {
-        "enabled": True,
-        "process_throttle_secs": 1800,
-        "calculate_since_number_of_days": 14,
-        "capital_available_percentage": 0.5,
-        "allowed_risk": 0.01,
-        "stoploss_range_min": -0.01,
-        "stoploss_range_max": -0.1,
-        "stoploss_range_step": -0.01,
-        "maximum_winrate": 0.80,
-        "minimum_expectancy": 0.20,
-        "min_trade_number": 15,
-        "max_trade_duration_minute": 1440,
-        "remove_pumps": False
-    }
-
-    return conf
-
-
-@pytest.fixture
-def rpc_balance():
-    return {
-        'BTC': {
-            'total': 12.0,
-            'free': 12.0,
-            'used': 0.0
-        },
-        'ETH': {
-            'total': 0.0,
-            'free': 0.0,
-            'used': 0.0
-        },
-        'USDT': {
-            'total': 10000.0,
-            'free': 10000.0,
-            'used': 0.0
-        },
-        'LTC': {
-            'total': 10.0,
-            'free': 10.0,
-            'used': 0.0
-        },
-        'XRP': {
-            'total': 1.0,
-            'free': 1.0,
-            'used': 0.0
-            },
-        'EUR': {
-            'total': 10.0,
-            'free': 10.0,
-            'used': 0.0
-        },
-    }
diff --git a/freqtrade/tests/data/test_btanalysis.py b/freqtrade/tests/data/test_btanalysis.py
deleted file mode 100644
index e80840009..000000000
--- a/freqtrade/tests/data/test_btanalysis.py
+++ /dev/null
@@ -1,129 +0,0 @@
-from unittest.mock import MagicMock
-
-import pytest
-from arrow import Arrow
-from pandas import DataFrame, to_datetime
-
-from freqtrade.configuration import Arguments, TimeRange
-from freqtrade.data.btanalysis import (BT_DATA_COLUMNS,
-                                       combine_tickers_with_mean,
-                                       create_cum_profit,
-                                       extract_trades_of_period,
-                                       load_backtest_data, load_trades,
-                                       load_trades_from_db)
-from freqtrade.data.history import (load_data, load_pair_history,
-                                    make_testdata_path)
-from freqtrade.tests.test_persistence import create_mock_trades
-
-
-def test_load_backtest_data():
-
-    filename = make_testdata_path(None) / "backtest-result_test.json"
-    bt_data = load_backtest_data(filename)
-    assert isinstance(bt_data, DataFrame)
-    assert list(bt_data.columns) == BT_DATA_COLUMNS + ["profitabs"]
-    assert len(bt_data) == 179
-
-    # Test loading from string (must yield same result)
-    bt_data2 = load_backtest_data(str(filename))
-    assert bt_data.equals(bt_data2)
-
-    with pytest.raises(ValueError, match=r"File .* does not exist\."):
-        load_backtest_data(str("filename") + "nofile")
-
-
-@pytest.mark.usefixtures("init_persistence")
-def test_load_trades_db(default_conf, fee, mocker):
-
-    create_mock_trades(fee)
-    # remove init so it does not init again
-    init_mock = mocker.patch('freqtrade.persistence.init', MagicMock())
-
-    trades = load_trades_from_db(db_url=default_conf['db_url'])
-    assert init_mock.call_count == 1
-    assert len(trades) == 3
-    assert isinstance(trades, DataFrame)
-    assert "pair" in trades.columns
-    assert "open_time" in trades.columns
-
-
-def test_extract_trades_of_period():
-    pair = "UNITTEST/BTC"
-    timerange = TimeRange(None, 'line', 0, -1000)
-
-    data = load_pair_history(pair=pair, ticker_interval='1m',
-                             datadir=None, timerange=timerange)
-
-    # timerange = 2017-11-14 06:07 - 2017-11-14 22:58:00
-    trades = DataFrame(
-        {'pair': [pair, pair, pair, pair],
-         'profit_percent': [0.0, 0.1, -0.2, -0.5],
-         'profit_abs': [0.0, 1, -2, -5],
-         'open_time': to_datetime([Arrow(2017, 11, 13, 15, 40, 0).datetime,
-                                   Arrow(2017, 11, 14, 9, 41, 0).datetime,
-                                   Arrow(2017, 11, 14, 14, 20, 0).datetime,
-                                   Arrow(2017, 11, 15, 3, 40, 0).datetime,
-                                   ], utc=True
-                                  ),
-         'close_time': to_datetime([Arrow(2017, 11, 13, 16, 40, 0).datetime,
-                                    Arrow(2017, 11, 14, 10, 41, 0).datetime,
-                                    Arrow(2017, 11, 14, 15, 25, 0).datetime,
-                                    Arrow(2017, 11, 15, 3, 55, 0).datetime,
-                                    ], utc=True)
-         })
-    trades1 = extract_trades_of_period(data, trades)
-    # First and last trade are dropped as they are out of range
-    assert len(trades1) == 2
-    assert trades1.iloc[0].open_time == Arrow(2017, 11, 14, 9, 41, 0).datetime
-    assert trades1.iloc[0].close_time == Arrow(2017, 11, 14, 10, 41, 0).datetime
-    assert trades1.iloc[-1].open_time == Arrow(2017, 11, 14, 14, 20, 0).datetime
-    assert trades1.iloc[-1].close_time == Arrow(2017, 11, 14, 15, 25, 0).datetime
-
-
-def test_load_trades(default_conf, mocker):
-    db_mock = mocker.patch("freqtrade.data.btanalysis.load_trades_from_db", MagicMock())
-    bt_mock = mocker.patch("freqtrade.data.btanalysis.load_backtest_data", MagicMock())
-
-    default_conf['trade_source'] = "DB"
-    load_trades(default_conf)
-
-    assert db_mock.call_count == 1
-    assert bt_mock.call_count == 0
-
-    db_mock.reset_mock()
-    bt_mock.reset_mock()
-    default_conf['trade_source'] = "file"
-    default_conf['exportfilename'] = "testfile.json"
-    load_trades(default_conf)
-
-    assert db_mock.call_count == 0
-    assert bt_mock.call_count == 1
-
-
-def test_combine_tickers_with_mean():
-    pairs = ["ETH/BTC", "XLM/BTC"]
-    tickers = load_data(datadir=None,
-                        pairs=pairs,
-                        ticker_interval='5m'
-                        )
-    df = combine_tickers_with_mean(tickers)
-    assert isinstance(df, DataFrame)
-    assert "ETH/BTC" in df.columns
-    assert "XLM/BTC" in df.columns
-    assert "mean" in df.columns
-
-
-def test_create_cum_profit():
-    filename = make_testdata_path(None) / "backtest-result_test.json"
-    bt_data = load_backtest_data(filename)
-    timerange = Arguments.parse_timerange("20180110-20180112")
-
-    df = load_pair_history(pair="POWR/BTC", ticker_interval='5m',
-                           datadir=None, timerange=timerange)
-
-    cum_profits = create_cum_profit(df.set_index('date'),
-                                    bt_data[bt_data["pair"] == 'POWR/BTC'],
-                                    "cum_profits")
-    assert "cum_profits" in cum_profits.columns
-    assert cum_profits.iloc[0]['cum_profits'] == 0
-    assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005
diff --git a/freqtrade/tests/data/test_converter.py b/freqtrade/tests/data/test_converter.py
deleted file mode 100644
index f68224e0e..000000000
--- a/freqtrade/tests/data/test_converter.py
+++ /dev/null
@@ -1,150 +0,0 @@
-# pragma pylint: disable=missing-docstring, C0103
-import logging
-
-from freqtrade.data.converter import parse_ticker_dataframe, ohlcv_fill_up_missing_data
-from freqtrade.data.history import load_pair_history, validate_backtest_data, get_timeframe
-from freqtrade.tests.conftest import log_has
-
-
-def test_dataframe_correct_columns(result):
-    assert result.columns.tolist() == ['date', 'open', 'high', 'low', 'close', 'volume']
-
-
-def test_parse_ticker_dataframe(ticker_history_list, caplog):
-    columns = ['date', 'open', 'high', 'low', 'close', 'volume']
-
-    caplog.set_level(logging.DEBUG)
-    # Test file with BV data
-    dataframe = parse_ticker_dataframe(ticker_history_list, '5m',
-                                       pair="UNITTEST/BTC", fill_missing=True)
-    assert dataframe.columns.tolist() == columns
-    assert log_has('Parsing tickerlist to dataframe', caplog.record_tuples)
-
-
-def test_ohlcv_fill_up_missing_data(caplog):
-    data = load_pair_history(datadir=None,
-                             ticker_interval='1m',
-                             refresh_pairs=False,
-                             pair='UNITTEST/BTC',
-                             fill_up_missing=False)
-    caplog.set_level(logging.DEBUG)
-    data2 = ohlcv_fill_up_missing_data(data, '1m', 'UNITTEST/BTC')
-    assert len(data2) > len(data)
-    # Column names should not change
-    assert (data.columns == data2.columns).all()
-
-    assert log_has(f"Missing data fillup for UNITTEST/BTC: before: "
-                   f"{len(data)} - after: {len(data2)}",
-                   caplog.record_tuples)
-
-    # Test fillup actually fixes invalid backtest data
-    min_date, max_date = get_timeframe({'UNITTEST/BTC': data})
-    assert validate_backtest_data(data, 'UNITTEST/BTC', min_date, max_date, 1)
-    assert not validate_backtest_data(data2, 'UNITTEST/BTC', min_date, max_date, 1)
-
-
-def test_ohlcv_fill_up_missing_data2(caplog):
-    ticker_interval = '5m'
-    ticks = [[
-            1511686200000,  # 8:50:00
-            8.794e-05,  # open
-            8.948e-05,  # high
-            8.794e-05,  # low
-            8.88e-05,  # close
-            2255,  # volume (in quote currency)
-        ],
-        [
-            1511686500000,  # 8:55:00
-            8.88e-05,
-            8.942e-05,
-            8.88e-05,
-            8.893e-05,
-            9911,
-        ],
-        [
-            1511687100000,  # 9:05:00
-            8.891e-05,
-            8.893e-05,
-            8.875e-05,
-            8.877e-05,
-            2251
-        ],
-        [
-            1511687400000,  # 9:10:00
-            8.877e-05,
-            8.883e-05,
-            8.895e-05,
-            8.817e-05,
-            123551
-    ]
-    ]
-
-    # Generate test-data without filling missing
-    data = parse_ticker_dataframe(ticks, ticker_interval, pair="UNITTEST/BTC", fill_missing=False)
-    assert len(data) == 3
-    caplog.set_level(logging.DEBUG)
-    data2 = ohlcv_fill_up_missing_data(data, ticker_interval, "UNITTEST/BTC")
-    assert len(data2) == 4
-    # 3rd candle has been filled
-    row = data2.loc[2, :]
-    assert row['volume'] == 0
-    # close shoult match close of previous candle
-    assert row['close'] == data.loc[1, 'close']
-    assert row['open'] == row['close']
-    assert row['high'] == row['close']
-    assert row['low'] == row['close']
-    # Column names should not change
-    assert (data.columns == data2.columns).all()
-
-    assert log_has(f"Missing data fillup for UNITTEST/BTC: before: "
-                   f"{len(data)} - after: {len(data2)}",
-                   caplog.record_tuples)
-
-
-def test_ohlcv_drop_incomplete(caplog):
-    ticker_interval = '1d'
-    ticks = [[
-            1559750400000,  # 2019-06-04
-            8.794e-05,  # open
-            8.948e-05,  # high
-            8.794e-05,  # low
-            8.88e-05,  # close
-            2255,  # volume (in quote currency)
-        ],
-        [
-            1559836800000,  # 2019-06-05
-            8.88e-05,
-            8.942e-05,
-            8.88e-05,
-            8.893e-05,
-            9911,
-        ],
-        [
-            1559923200000,  # 2019-06-06
-            8.891e-05,
-            8.893e-05,
-            8.875e-05,
-            8.877e-05,
-            2251
-        ],
-        [
-            1560009600000,  # 2019-06-07
-            8.877e-05,
-            8.883e-05,
-            8.895e-05,
-            8.817e-05,
-            123551
-     ]
-    ]
-    caplog.set_level(logging.DEBUG)
-    data = parse_ticker_dataframe(ticks, ticker_interval, pair="UNITTEST/BTC",
-                                  fill_missing=False, drop_incomplete=False)
-    assert len(data) == 4
-    assert not log_has("Dropping last candle", caplog.record_tuples)
-
-    # Drop last candle
-    data = parse_ticker_dataframe(ticks, ticker_interval, pair="UNITTEST/BTC",
-                                  fill_missing=False, drop_incomplete=True)
-    assert len(data) == 3
-
-    assert log_has("Dropping last candle", caplog.record_tuples)
diff --git a/freqtrade/tests/data/test_dataprovider.py b/freqtrade/tests/data/test_dataprovider.py
deleted file mode 100644
index 993f0b59b..000000000
--- a/freqtrade/tests/data/test_dataprovider.py
+++ /dev/null
@@ -1,92 +0,0 @@
-from unittest.mock import MagicMock
-
-from pandas import DataFrame
-
-from freqtrade.data.dataprovider import DataProvider
-from freqtrade.state import RunMode
-from freqtrade.tests.conftest import get_patched_exchange
-
-
-def test_ohlcv(mocker, default_conf, ticker_history):
-    default_conf["runmode"] = RunMode.DRY_RUN
-    ticker_interval = default_conf["ticker_interval"]
-    exchange = get_patched_exchange(mocker, default_conf)
-    exchange._klines[("XRP/BTC", ticker_interval)] = ticker_history
-    exchange._klines[("UNITTEST/BTC", ticker_interval)] = ticker_history
-    dp = DataProvider(default_conf, exchange)
-    assert dp.runmode == RunMode.DRY_RUN
-    assert ticker_history.equals(dp.ohlcv("UNITTEST/BTC", ticker_interval))
-    assert isinstance(dp.ohlcv("UNITTEST/BTC", ticker_interval), DataFrame)
-    assert dp.ohlcv("UNITTEST/BTC", ticker_interval) is not ticker_history
-    assert dp.ohlcv("UNITTEST/BTC", ticker_interval, copy=False) is ticker_history
-    assert not dp.ohlcv("UNITTEST/BTC", ticker_interval).empty
-    assert dp.ohlcv("NONESENSE/AAA", ticker_interval).empty
-
-    # Test with and without parameter
-    assert dp.ohlcv("UNITTEST/BTC", ticker_interval).equals(dp.ohlcv("UNITTEST/BTC"))
-
-    default_conf["runmode"] = RunMode.LIVE
-    dp = DataProvider(default_conf, exchange)
-    assert dp.runmode == RunMode.LIVE
-    assert isinstance(dp.ohlcv("UNITTEST/BTC", ticker_interval), DataFrame)
-
-    default_conf["runmode"] = RunMode.BACKTEST
-    dp = DataProvider(default_conf, exchange)
-    assert dp.runmode == RunMode.BACKTEST
-    assert dp.ohlcv("UNITTEST/BTC", ticker_interval).empty
-
-
-def test_historic_ohlcv(mocker, default_conf, ticker_history):
-
-    historymock = MagicMock(return_value=ticker_history)
-    mocker.patch("freqtrade.data.dataprovider.load_pair_history", historymock)
-
-    # exchange = get_patched_exchange(mocker, default_conf)
-    dp = DataProvider(default_conf, None)
-    data = dp.historic_ohlcv("UNITTEST/BTC", "5m")
-    assert isinstance(data, DataFrame)
-    assert historymock.call_count == 1
-    assert historymock.call_args_list[0][1]["datadir"] is None
-    assert historymock.call_args_list[0][1]["refresh_pairs"] is False
-    assert historymock.call_args_list[0][1]["ticker_interval"] == "5m"
-
-
-def test_available_pairs(mocker, default_conf, ticker_history):
-    exchange = get_patched_exchange(mocker, default_conf)
-
-    ticker_interval = default_conf["ticker_interval"]
-    exchange._klines[("XRP/BTC", ticker_interval)] = ticker_history
-    exchange._klines[("UNITTEST/BTC", ticker_interval)] = ticker_history
-    dp = DataProvider(default_conf, exchange)
-
-    assert len(dp.available_pairs) == 2
-    assert dp.available_pairs == [
-        ("XRP/BTC", ticker_interval),
-        ("UNITTEST/BTC", ticker_interval),
-    ]
-
-
-def test_refresh(mocker, default_conf, ticker_history):
-    refresh_mock = MagicMock()
-    mocker.patch("freqtrade.exchange.Exchange.refresh_latest_ohlcv", refresh_mock)
-
-    exchange = get_patched_exchange(mocker, default_conf, id="binance")
-    ticker_interval = default_conf["ticker_interval"]
-    pairs = [("XRP/BTC", ticker_interval), ("UNITTEST/BTC", ticker_interval)]
-
-    pairs_non_trad = [("ETH/USDT", ticker_interval), ("BTC/TUSD", "1h")]
-
-    dp = DataProvider(default_conf, exchange)
-    dp.refresh(pairs)
-
-    assert refresh_mock.call_count == 1
-    assert len(refresh_mock.call_args[0]) == 1
-    assert len(refresh_mock.call_args[0][0]) == len(pairs)
-    assert refresh_mock.call_args[0][0] == pairs
-
-    refresh_mock.reset_mock()
-    dp.refresh(pairs, pairs_non_trad)
-    assert refresh_mock.call_count == 1
-    assert len(refresh_mock.call_args[0]) == 1
-    assert len(refresh_mock.call_args[0][0]) == len(pairs) + len(pairs_non_trad)
-    assert refresh_mock.call_args[0][0] == pairs + pairs_non_trad
diff --git a/freqtrade/tests/data/test_history.py b/freqtrade/tests/data/test_history.py
deleted file mode 100644
index 424333e99..000000000
--- a/freqtrade/tests/data/test_history.py
+++ /dev/null
@@ -1,584 +0,0 @@
-# pragma pylint: disable=missing-docstring, protected-access, C0103
-
-import json
-import os
-import uuid
-from pathlib import Path
-from shutil import copyfile
-from unittest.mock import MagicMock
-
-import arrow
-import pytest
-from pandas import DataFrame
-
-from freqtrade import OperationalException
-from freqtrade.configuration import TimeRange
-from freqtrade.data import history
-from freqtrade.data.history import (download_pair_history,
-                                    load_cached_data_for_updating,
-                                    load_tickerdata_file, make_testdata_path,
-                                    trim_tickerlist)
-from freqtrade.exchange import timeframe_to_minutes
-from freqtrade.misc import file_dump_json
-from freqtrade.strategy.default_strategy import DefaultStrategy
-from freqtrade.tests.conftest import (get_patched_exchange, log_has,
-                                      patch_exchange)
-
-# Change this if modifying UNITTEST/BTC testdatafile
-_BTC_UNITTEST_LENGTH = 13681
-
-
-def _backup_file(file: str, copy_file: bool = False) -> None:
-    """
-    Backup existing file to avoid deleting the user file
-    :param file: complete path to the file
-    :param touch_file: create an empty file in replacement
-    :return: None
-    """
-    file_swp = file + '.swp'
-    if os.path.isfile(file):
-        os.rename(file, file_swp)
-
-        if copy_file:
-            copyfile(file_swp, file)
-
-
-def _clean_test_file(file: str) -> None:
-    """
-    Backup existing file to avoid deleting the user file
-    :param file: complete path to the file
-    :return: None
-    """
-    file_swp = file + '.swp'
-    # 1. Delete file from the test
-    if os.path.isfile(file):
-        os.remove(file)
-
-    # 2. Rollback to the initial file
-    if os.path.isfile(file_swp):
-        os.rename(file_swp, file)
-
-
-def test_load_data_30min_ticker(mocker, caplog, default_conf) -> None:
-    ld = history.load_pair_history(pair='UNITTEST/BTC', ticker_interval='30m', datadir=None)
-    assert isinstance(ld, DataFrame)
-    assert not log_has(
-        'Download history data for pair: "UNITTEST/BTC", interval: 30m '
-        'and store in None.',
-        caplog.record_tuples
-    )
-
-
-def test_load_data_7min_ticker(mocker, caplog, default_conf) -> None:
-    ld = history.load_pair_history(pair='UNITTEST/BTC', ticker_interval='7m', datadir=None)
-    assert not isinstance(ld, DataFrame)
-    assert ld is None
-    assert log_has(
-        'No history data for pair: "UNITTEST/BTC", interval: 7m. '
-        'Use --refresh-pairs-cached option or download_backtest_data.py '
-        'script to download the data',
-        caplog.record_tuples
-    )
-
-
-def test_load_data_1min_ticker(ticker_history, mocker, caplog) -> None:
-    mocker.patch('freqtrade.exchange.Exchange.get_history', return_value=ticker_history)
-    file = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'UNITTEST_BTC-1m.json')
-    _backup_file(file, copy_file=True)
-    history.load_data(datadir=None, ticker_interval='1m', pairs=['UNITTEST/BTC'])
-    assert os.path.isfile(file) is True
-    assert not log_has(
-        'Download history data for pair: "UNITTEST/BTC", interval: 1m '
-        'and store in None.',
-        caplog.record_tuples
-    )
-    _clean_test_file(file)
-
-
-def test_load_data_with_new_pair_1min(ticker_history_list, mocker, caplog, default_conf) -> None:
-    """
-    Test load_pair_history() with 1 min ticker
-    """
-    mocker.patch('freqtrade.exchange.Exchange.get_history', return_value=ticker_history_list)
-    exchange = get_patched_exchange(mocker, default_conf)
-    file = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-1m.json')
-
-    _backup_file(file)
-    # do not download a new pair if refresh_pairs isn't set
-    history.load_pair_history(datadir=None,
-                              ticker_interval='1m',
-                              refresh_pairs=False,
-                              pair='MEME/BTC')
-    assert os.path.isfile(file) is False
-    assert log_has(
-        'No history data for pair: "MEME/BTC", interval: 1m. '
-        'Use --refresh-pairs-cached option or download_backtest_data.py '
-        'script to download the data',
-        caplog.record_tuples
-    )
-
-    # download a new pair if refresh_pairs is set
-    history.load_pair_history(datadir=None,
-                              ticker_interval='1m',
-                              refresh_pairs=True,
-                              exchange=exchange,
-                              pair='MEME/BTC')
-    assert os.path.isfile(file) is True
-    assert log_has(
-        'Download history data for pair: "MEME/BTC", interval: 1m '
-        'and store in None.',
-        caplog.record_tuples
-    )
-    with pytest.raises(OperationalException, match=r'Exchange needs to be initialized when.*'):
-        history.load_pair_history(datadir=None,
-                                  ticker_interval='1m',
-                                  refresh_pairs=True,
-                                  exchange=None,
-                                  pair='MEME/BTC')
-    _clean_test_file(file)
-
-
-def test_load_data_live(default_conf, mocker, caplog) -> None:
-    refresh_mock = MagicMock()
-    mocker.patch("freqtrade.exchange.Exchange.refresh_latest_ohlcv", refresh_mock)
-    exchange = get_patched_exchange(mocker, default_conf)
-
-    history.load_data(datadir=None, ticker_interval='5m',
-                      pairs=['UNITTEST/BTC', 'UNITTEST2/BTC'],
-                      live=True,
-                      exchange=exchange)
-    assert refresh_mock.call_count == 1
-    assert len(refresh_mock.call_args_list[0][0][0]) == 2
-    assert log_has('Live: Downloading data for all defined pairs ...', caplog.record_tuples)
-
-
-def test_load_data_live_noexchange(default_conf, mocker, caplog) -> None:
-
-    with pytest.raises(OperationalException,
-                       match=r'Exchange needs to be initialized when using live data.'):
-        history.load_data(datadir=None, ticker_interval='5m',
-                          pairs=['UNITTEST/BTC', 'UNITTEST2/BTC'],
-                          exchange=None,
-                          live=True,
-                          )
-
-
-def test_testdata_path() -> None:
-    assert str(Path('freqtrade') / 'tests' / 'testdata') in str(make_testdata_path(None))
-
-
-def test_load_cached_data_for_updating(mocker) -> None:
-    datadir = Path(__file__).parent.parent.joinpath('testdata')
-
-    test_data = None
-    test_filename = datadir.joinpath('UNITTEST_BTC-1m.json')
-    with open(test_filename, "rt") as file:
-        test_data = json.load(file)
-
-    # change now time to test 'line' cases
-    # now = last cached item + 1 hour
-    now_ts = test_data[-1][0] / 1000 + 60 * 60
-    mocker.patch('arrow.utcnow', return_value=arrow.get(now_ts))
-
-    # timeframe starts earlier than the cached data
-    # should fully update data
-    timerange = TimeRange('date', None, test_data[0][0] / 1000 - 1, 0)
-    data, start_ts = load_cached_data_for_updating(test_filename,
-                                                   '1m',
-                                                   timerange)
-    assert data == []
-    assert start_ts == test_data[0][0] - 1000
-
-    # same with 'line' timeframe
-    num_lines = (test_data[-1][0] - test_data[1][0]) / 1000 / 60 + 120
-    data, start_ts = load_cached_data_for_updating(test_filename,
-                                                   '1m',
-                                                   TimeRange(None, 'line', 0, -num_lines))
-    assert data == []
-    assert start_ts < test_data[0][0] - 1
-
-    # timeframe starts in the center of the cached data
-    # should return the chached data w/o the last item
-    timerange = TimeRange('date', None, test_data[0][0] / 1000 + 1, 0)
-    data, start_ts = load_cached_data_for_updating(test_filename,
-                                                   '1m',
-                                                   timerange)
-    assert data == test_data[:-1]
-    assert test_data[-2][0] < start_ts < test_data[-1][0]
-
-    # same with 'line' timeframe
-    num_lines = (test_data[-1][0] - test_data[1][0]) / 1000 / 60 + 30
-    timerange = TimeRange(None, 'line', 0, -num_lines)
-    data, start_ts = load_cached_data_for_updating(test_filename,
-                                                   '1m',
-                                                   timerange)
-    assert data == test_data[:-1]
-    assert test_data[-2][0] < start_ts < test_data[-1][0]
-
-    # timeframe starts after the chached data
-    # should return the chached data w/o the last item
-    timerange = TimeRange('date', None, test_data[-1][0] / 1000 + 1, 0)
-    data, start_ts = load_cached_data_for_updating(test_filename,
-                                                   '1m',
-                                                   timerange)
-    assert data == test_data[:-1]
-    assert test_data[-2][0] < start_ts < test_data[-1][0]
-
-    # same with 'line' timeframe
-    num_lines = 30
-    timerange = TimeRange(None, 'line', 0, -num_lines)
-    data, start_ts = load_cached_data_for_updating(test_filename,
-                                                   '1m',
-                                                   timerange)
-    assert data == test_data[:-1]
-    assert test_data[-2][0] < start_ts < test_data[-1][0]
-
-    # no timeframe is set
-    # should return the chached data w/o the last item
-    num_lines = 30
-    timerange = TimeRange(None, 'line', 0, -num_lines)
-    data, start_ts = load_cached_data_for_updating(test_filename,
-                                                   '1m',
-                                                   timerange)
-    assert data == test_data[:-1]
-    assert test_data[-2][0] < start_ts < test_data[-1][0]
-
-    # no datafile exist
-    # should return timestamp start time
-    timerange = TimeRange('date', None, now_ts - 10000, 0)
-    data, start_ts = load_cached_data_for_updating(test_filename.with_name('unexist'),
-                                                   '1m',
-                                                   timerange)
-    assert data == []
-    assert start_ts == (now_ts - 10000) * 1000
-
-    # same with 'line' timeframe
-    num_lines = 30
-    timerange = TimeRange(None, 'line', 0, -num_lines)
-    data, start_ts = load_cached_data_for_updating(test_filename.with_name('unexist'),
-                                                   '1m',
-                                                   timerange)
-    assert data == []
-    assert start_ts == (now_ts - num_lines * 60) * 1000
-
-    # no datafile exist, no timeframe is set
-    # should return an empty array and None
-    data, start_ts = load_cached_data_for_updating(test_filename.with_name('unexist'),
-                                                   '1m',
-                                                   None)
-    assert data == []
-    assert start_ts is None
-
-
-def test_download_pair_history(ticker_history_list, mocker, default_conf) -> None:
-    mocker.patch('freqtrade.exchange.Exchange.get_history', return_value=ticker_history_list)
-    exchange = get_patched_exchange(mocker, default_conf)
-    file1_1 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-1m.json')
-    file1_5 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-5m.json')
-    file2_1 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'CFI_BTC-1m.json')
-    file2_5 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'CFI_BTC-5m.json')
-
-    _backup_file(file1_1)
-    _backup_file(file1_5)
-    _backup_file(file2_1)
-    _backup_file(file2_5)
-
-    assert os.path.isfile(file1_1) is False
-    assert os.path.isfile(file2_1) is False
-
-    assert download_pair_history(datadir=None, exchange=exchange,
-                                 pair='MEME/BTC',
-                                 ticker_interval='1m')
-    assert download_pair_history(datadir=None, exchange=exchange,
-                                 pair='CFI/BTC',
-                                 ticker_interval='1m')
-    assert not exchange._pairs_last_refresh_time
-    assert os.path.isfile(file1_1) is True
-    assert os.path.isfile(file2_1) is True
-
-    # clean files freshly downloaded
-    _clean_test_file(file1_1)
-    _clean_test_file(file2_1)
-
-    assert os.path.isfile(file1_5) is False
-    assert os.path.isfile(file2_5) is False
-
-    assert download_pair_history(datadir=None, exchange=exchange,
-                                 pair='MEME/BTC',
-                                 ticker_interval='5m')
-    assert download_pair_history(datadir=None, exchange=exchange,
-                                 pair='CFI/BTC',
-                                 ticker_interval='5m')
-    assert not exchange._pairs_last_refresh_time
-    assert os.path.isfile(file1_5) is True
-    assert os.path.isfile(file2_5) is True
-
-    # clean files freshly downloaded
-    _clean_test_file(file1_5)
-    _clean_test_file(file2_5)
-
-
-def test_download_pair_history2(mocker, default_conf) -> None:
-    tick = [
-        [1509836520000, 0.00162008, 0.00162008, 0.00162008, 0.00162008, 108.14853839],
-        [1509836580000, 0.00161, 0.00161, 0.00161, 0.00161, 82.390199]
-    ]
-    json_dump_mock = mocker.patch('freqtrade.misc.file_dump_json', return_value=None)
-    mocker.patch('freqtrade.exchange.Exchange.get_history', return_value=tick)
-    exchange = get_patched_exchange(mocker, default_conf)
-    download_pair_history(None, exchange, pair="UNITTEST/BTC", ticker_interval='1m')
-    download_pair_history(None, exchange, pair="UNITTEST/BTC", ticker_interval='3m')
-    assert json_dump_mock.call_count == 2
-
-
-def test_download_backtesting_data_exception(ticker_history, mocker, caplog, default_conf) -> None:
-    mocker.patch('freqtrade.exchange.Exchange.get_history',
-                 side_effect=Exception('File Error'))
-
-    exchange = get_patched_exchange(mocker, default_conf)
-
-    file1_1 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-1m.json')
-    file1_5 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-5m.json')
-    _backup_file(file1_1)
-    _backup_file(file1_5)
-
-    assert not download_pair_history(datadir=None, exchange=exchange,
-                                     pair='MEME/BTC',
-                                     ticker_interval='1m')
-    # clean files freshly downloaded
-    _clean_test_file(file1_1)
-    _clean_test_file(file1_5)
-    assert log_has(
-        'Failed to download history data for pair: "MEME/BTC", interval: 1m. '
-        'Error: File Error',
-        caplog.record_tuples
-    )
-
-
-def test_load_tickerdata_file() -> None:
-    # 7 does not exist in either format.
-    assert not load_tickerdata_file(None, 'UNITTEST/BTC', '7m')
-    # 1 exists only as a .json
-    tickerdata = load_tickerdata_file(None, 'UNITTEST/BTC', '1m')
-    assert _BTC_UNITTEST_LENGTH == len(tickerdata)
-    # 8 .json is empty and will fail if it's loaded. .json.gz is a copy of 1.json
-    tickerdata = load_tickerdata_file(None, 'UNITTEST/BTC', '8m')
-    assert _BTC_UNITTEST_LENGTH == len(tickerdata)
-
-
-def test_load_partial_missing(caplog) -> None:
-    # Make sure we start fresh - test missing data at start
-    start = arrow.get('2018-01-01T00:00:00')
-    end = arrow.get('2018-01-11T00:00:00')
-    tickerdata = history.load_data(None, '5m', ['UNITTEST/BTC'],
-                                   refresh_pairs=False,
-                                   timerange=TimeRange('date', 'date',
-                                                       start.timestamp, end.timestamp))
-    # timedifference in 5 minutes
-    td = ((end - start).total_seconds() // 60 // 5) + 1
-    assert td != len(tickerdata['UNITTEST/BTC'])
-    start_real = tickerdata['UNITTEST/BTC'].iloc[0, 0]
-    assert log_has(f'Missing data at start for pair '
-                   f'UNITTEST/BTC, data starts at {start_real.strftime("%Y-%m-%d %H:%M:%S")}',
-                   caplog.record_tuples)
-    # Make sure we start fresh - test missing data at end
-    caplog.clear()
-    start = arrow.get('2018-01-10T00:00:00')
-    end = arrow.get('2018-02-20T00:00:00')
-    tickerdata = history.load_data(datadir=None, ticker_interval='5m',
-                                   pairs=['UNITTEST/BTC'], refresh_pairs=False,
-                                   timerange=TimeRange('date', 'date',
-                                                       start.timestamp, end.timestamp))
-    # timedifference in 5 minutes
-    td = ((end - start).total_seconds() // 60 // 5) + 1
-    assert td != len(tickerdata['UNITTEST/BTC'])
-    # Shift endtime with +5 - as last candle is dropped (partial candle)
-    end_real = arrow.get(tickerdata['UNITTEST/BTC'].iloc[-1, 0]).shift(minutes=5)
-    assert log_has(f'Missing data at end for pair '
-                   f'UNITTEST/BTC, data ends at {end_real.strftime("%Y-%m-%d %H:%M:%S")}',
-                   caplog.record_tuples)
-
-
-def test_init(default_conf, mocker) -> None:
-    exchange = get_patched_exchange(mocker, default_conf)
-    assert {} == history.load_data(
-        datadir='',
-        exchange=exchange,
-        pairs=[],
-        refresh_pairs=True,
-        ticker_interval=default_conf['ticker_interval']
-    )
-
-
-def test_trim_tickerlist() -> None:
-    file = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'UNITTEST_BTC-1m.json')
-    with open(file) as data_file:
-        ticker_list = json.load(data_file)
-    ticker_list_len = len(ticker_list)
-
-    # Test the pattern ^(-\d+)$
-    # This pattern uses the latest N elements
-    timerange = TimeRange(None, 'line', 0, -5)
-    ticker = trim_tickerlist(ticker_list, timerange)
-    ticker_len = len(ticker)
-
-    assert ticker_len == 5
-    assert ticker_list[0] is not ticker[0]  # The first element should be different
-    assert ticker_list[-1] is ticker[-1]  # The last element must be the same
-
-    # Test the pattern ^(\d+)-$
-    # This pattern keep X element from the end
-    timerange = TimeRange('line', None, 5, 0)
-    ticker = trim_tickerlist(ticker_list, timerange)
-    ticker_len = len(ticker)
-
-    assert ticker_len == 5
-    assert ticker_list[0] is ticker[0]  # The first element must be the same
-    assert ticker_list[-1] is not ticker[-1]  # The last element should be different
-
-    # Test the pattern ^(\d+)-(\d+)$
-    # This pattern extract a window
-    timerange = TimeRange('index', 'index', 5, 10)
-    ticker = trim_tickerlist(ticker_list, timerange)
-    ticker_len = len(ticker)
-
-    assert ticker_len == 5
-    assert ticker_list[0] is not ticker[0]  # The first element should be different
-    assert ticker_list[5] is ticker[0]  # The list starts at the index 5
-    assert ticker_list[9] is ticker[-1]  # The list ends at the index 9 (5 elements)
-
-    # Test the pattern ^(\d{8})-(\d{8})$
-    # This pattern extract a window between the dates
-    timerange = TimeRange('date', 'date', ticker_list[5][0] / 1000, ticker_list[10][0] / 1000 - 1)
-    ticker = trim_tickerlist(ticker_list, timerange)
-    ticker_len = len(ticker)
-
-    assert ticker_len == 5
-    assert ticker_list[0] is not ticker[0]  # The first element should be different
-    assert ticker_list[5] is ticker[0]  # The list starts at the index 5
-    assert ticker_list[9] is ticker[-1]  # The list ends at the index 9 (5 elements)
-
-    # Test the pattern ^-(\d{8})$
-    # This pattern extracts elements from the start to the date
-    timerange = TimeRange(None, 'date', 0, ticker_list[10][0] / 1000 - 1)
-    ticker = trim_tickerlist(ticker_list, timerange)
-    ticker_len = len(ticker)
-
-    assert ticker_len == 10
-    assert ticker_list[0] is ticker[0]  # The start of the list is included
-    assert ticker_list[9] is ticker[-1]  # The element 10 is not included
-
-    # Test the pattern ^(\d{8})-$
-    # This pattern extracts elements from the date to now
-    timerange = TimeRange('date', None, ticker_list[10][0] / 1000 - 1, None)
-    ticker = trim_tickerlist(ticker_list, timerange)
-    ticker_len = len(ticker)
-
-    assert ticker_len == ticker_list_len - 10
-    assert ticker_list[10] is ticker[0]  # The first element is element #10
-    assert ticker_list[-1] is ticker[-1]  # The last element is the same
-
-    # Test a wrong pattern
-    # This pattern must return the list unchanged
-    timerange = TimeRange(None, None, None, 5)
-    ticker = trim_tickerlist(ticker_list, timerange)
-    ticker_len = len(ticker)
-
-    assert ticker_list_len == ticker_len
-
-    # Test invalid timerange (start after stop)
-    timerange = TimeRange('index', 'index', 10, 5)
-    with pytest.raises(ValueError, match=r'The timerange .* is incorrect'):
-        trim_tickerlist(ticker_list, timerange)
-
-    assert ticker_list_len == ticker_len
-
-    # passing empty list
-    timerange = TimeRange(None, None, None, 5)
-    ticker = trim_tickerlist([], timerange)
-    assert 0 == len(ticker)
-    assert not ticker
-
-
-def test_file_dump_json_tofile() -> None:
-    file = os.path.join(os.path.dirname(__file__), '..', 'testdata',
-                        'test_{id}.json'.format(id=str(uuid.uuid4())))
-    data = {'bar': 'foo'}
-
-    # check the file we will create does not exist
-    assert os.path.isfile(file) is False
-
-    # Create the Json file
-    file_dump_json(file, data)
-
-    # Check the file was create
-    assert os.path.isfile(file) is True
-
-    # Open the Json file created and test the data is in it
-    with open(file) as data_file:
-        json_from_file = json.load(data_file)
-
-    assert 'bar' in json_from_file
-    assert json_from_file['bar'] == 'foo'
-
-    # Remove the file
-    _clean_test_file(file)
-
-
-def test_get_timeframe(default_conf, mocker) -> None:
-    patch_exchange(mocker)
-    strategy = DefaultStrategy(default_conf)
-
-    data = strategy.tickerdata_to_dataframe(
-        history.load_data(
-            datadir=None,
-            ticker_interval='1m',
-            pairs=['UNITTEST/BTC']
-        )
-    )
-    min_date, max_date = history.get_timeframe(data)
-    assert min_date.isoformat() == '2017-11-04T23:02:00+00:00'
-    assert max_date.isoformat() == '2017-11-14T22:58:00+00:00'
-
-
-def test_validate_backtest_data_warn(default_conf, mocker, caplog) -> None:
-    patch_exchange(mocker)
-    strategy = DefaultStrategy(default_conf)
-
-    data = strategy.tickerdata_to_dataframe(
-        history.load_data(
-            datadir=None,
-            ticker_interval='1m',
-            pairs=['UNITTEST/BTC'],
-            fill_up_missing=False
-        )
-    )
-    min_date, max_date = history.get_timeframe(data)
-    caplog.clear()
-    assert history.validate_backtest_data(data['UNITTEST/BTC'], 'UNITTEST/BTC',
-                                          min_date, max_date, timeframe_to_minutes('1m'))
-    assert len(caplog.record_tuples) == 1
-    assert log_has(
-        "UNITTEST/BTC has missing frames: expected 14396, got 13680, that's 716 missing values",
-        caplog.record_tuples)
-
-
-def test_validate_backtest_data(default_conf, mocker, caplog) -> None:
-    patch_exchange(mocker)
-    strategy = DefaultStrategy(default_conf)
-
-    timerange = TimeRange('index', 'index', 200, 250)
-    data = strategy.tickerdata_to_dataframe(
-        history.load_data(
-            datadir=None,
-            ticker_interval='5m',
-            pairs=['UNITTEST/BTC'],
-            timerange=timerange
-        )
-    )
-
-    min_date, max_date = history.get_timeframe(data)
-    caplog.clear()
-    assert not history.validate_backtest_data(data['UNITTEST/BTC'], 'UNITTEST/BTC',
-                                              min_date, max_date, timeframe_to_minutes('5m'))
-    assert len(caplog.record_tuples) == 0
diff --git a/freqtrade/tests/exchange/test_exchange.py b/freqtrade/tests/exchange/test_exchange.py
deleted file mode 100644
index a4f1bca18..000000000
--- a/freqtrade/tests/exchange/test_exchange.py
+++ /dev/null
@@ -1,1525 +0,0 @@
-# pragma pylint: disable=missing-docstring, C0103, bad-continuation, global-statement
-# pragma pylint: disable=protected-access
-import copy
-import logging
-from datetime import datetime
-from random import randint
-from unittest.mock import MagicMock, Mock, PropertyMock
-
-import arrow
-import ccxt
-import pytest
-from pandas import DataFrame
-
-from freqtrade import (DependencyException, OperationalException,
-                       TemporaryError, InvalidOrderException)
-from freqtrade.exchange import Binance, Exchange, Kraken
-from freqtrade.exchange.exchange import API_RETRY_COUNT
-from freqtrade.resolvers.exchange_resolver import ExchangeResolver
-from freqtrade.tests.conftest import get_patched_exchange, log_has, log_has_re
-
-# Make sure to always keep one exchange here which is NOT subclassed!!
-EXCHANGES = ['bittrex', 'binance', 'kraken', ]
-
-
-# Source: https://stackoverflow.com/questions/29881236/how-to-mock-asyncio-coroutines
-def get_mock_coro(return_value):
-    async def mock_coro(*args, **kwargs):
-        return return_value
-
-    return Mock(wraps=mock_coro)
-
-
-def ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
-                           fun, mock_ccxt_fun, **kwargs):
-    with pytest.raises(TemporaryError):
-        api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.NetworkError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        getattr(exchange, fun)(**kwargs)
-    assert api_mock.__dict__[mock_ccxt_fun].call_count == API_RETRY_COUNT + 1
-
-    with pytest.raises(OperationalException):
-        api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.BaseError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        getattr(exchange, fun)(**kwargs)
-    assert api_mock.__dict__[mock_ccxt_fun].call_count == 1
-
-
-async def async_ccxt_exception(mocker, default_conf, api_mock, fun, mock_ccxt_fun, **kwargs):
-    with pytest.raises(TemporaryError):
-        api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.NetworkError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock)
-        await getattr(exchange, fun)(**kwargs)
-    assert api_mock.__dict__[mock_ccxt_fun].call_count == API_RETRY_COUNT + 1
-
-    with pytest.raises(OperationalException):
-        api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.BaseError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock)
-        await getattr(exchange, fun)(**kwargs)
-    assert api_mock.__dict__[mock_ccxt_fun].call_count == 1
-
-
-def test_init(default_conf, mocker, caplog):
-    caplog.set_level(logging.INFO)
-    get_patched_exchange(mocker, default_conf)
-    assert log_has('Instance is running with dry_run enabled', caplog.record_tuples)
-
-
-def test_init_ccxt_kwargs(default_conf, mocker, caplog):
-    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
-    caplog.set_level(logging.INFO)
-    conf = copy.deepcopy(default_conf)
-    conf['exchange']['ccxt_async_config'] = {'aiohttp_trust_env': True}
-    ex = Exchange(conf)
-    assert log_has("Applying additional ccxt config: {'aiohttp_trust_env': True}",
-                   caplog.record_tuples)
-    assert ex._api_async.aiohttp_trust_env
-    assert not ex._api.aiohttp_trust_env
-
-    # Reset logging and config
-    caplog.clear()
-    conf = copy.deepcopy(default_conf)
-    conf['exchange']['ccxt_config'] = {'TestKWARG': 11}
-    ex = Exchange(conf)
-    assert not log_has("Applying additional ccxt config: {'aiohttp_trust_env': True}",
-                       caplog.record_tuples)
-    assert not ex._api_async.aiohttp_trust_env
-    assert hasattr(ex._api, 'TestKWARG')
-    assert ex._api.TestKWARG == 11
-    assert not hasattr(ex._api_async, 'TestKWARG')
-    assert log_has("Applying additional ccxt config: {'TestKWARG': 11}",
-                   caplog.record_tuples)
-
-
-def test_destroy(default_conf, mocker, caplog):
-    caplog.set_level(logging.DEBUG)
-    get_patched_exchange(mocker, default_conf)
-    assert log_has('Exchange object destroyed, closing async loop', caplog.record_tuples)
-
-
-def test_init_exception(default_conf, mocker):
-    default_conf['exchange']['name'] = 'wrong_exchange_name'
-
-    with pytest.raises(
-            OperationalException,
-            match='Exchange {} is not supported'.format(default_conf['exchange']['name'])):
-        Exchange(default_conf)
-
-    default_conf['exchange']['name'] = 'binance'
-    with pytest.raises(
-            OperationalException,
-            match='Exchange {} is not supported'.format(default_conf['exchange']['name'])):
-        mocker.patch("ccxt.binance", MagicMock(side_effect=AttributeError))
-        Exchange(default_conf)
-
-
-def test_exchange_resolver(default_conf, mocker, caplog):
-    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=MagicMock()))
-    mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
-    mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
-    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
-    exchange = ExchangeResolver('Bittrex', default_conf).exchange
-    assert isinstance(exchange, Exchange)
-    assert log_has_re(r"No .* specific subclass found. Using the generic class instead.",
-                      caplog.record_tuples)
-    caplog.clear()
-
-    exchange = ExchangeResolver('kraken', default_conf).exchange
-    assert isinstance(exchange, Exchange)
-    assert isinstance(exchange, Kraken)
-    assert not isinstance(exchange, Binance)
-    assert not log_has_re(r"No .* specific subclass found. Using the generic class instead.",
-                          caplog.record_tuples)
-
-    exchange = ExchangeResolver('binance', default_conf).exchange
-    assert isinstance(exchange, Exchange)
-    assert isinstance(exchange, Binance)
-    assert not isinstance(exchange, Kraken)
-
-    assert not log_has_re(r"No .* specific subclass found. Using the generic class instead.",
-                          caplog.record_tuples)
-
-
-def test_validate_order_time_in_force(default_conf, mocker, caplog):
-    caplog.set_level(logging.INFO)
-    # explicitly test bittrex, exchanges implementing other policies need seperate tests
-    ex = get_patched_exchange(mocker, default_conf, id="bittrex")
-    tif = {
-        "buy": "gtc",
-        "sell": "gtc",
-    }
-
-    ex.validate_order_time_in_force(tif)
-    tif2 = {
-        "buy": "fok",
-        "sell": "ioc",
-    }
-    with pytest.raises(OperationalException, match=r"Time in force.*not supported for .*"):
-        ex.validate_order_time_in_force(tif2)
-
-    # Patch to see if this will pass if the values are in the ft dict
-    ex._ft_has.update({"order_time_in_force": ["gtc", "fok", "ioc"]})
-    ex.validate_order_time_in_force(tif2)
-
-
-def test_symbol_amount_prec(default_conf, mocker):
-    '''
-    Test rounds down to 4 Decimal places
-    '''
-    api_mock = MagicMock()
-    api_mock.load_markets = MagicMock(return_value={
-        'ETH/BTC': '', 'LTC/BTC': '', 'XRP/BTC': '', 'NEO/BTC': ''
-    })
-    mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value='binance'))
-
-    markets = PropertyMock(return_value={'ETH/BTC': {'precision': {'amount': 4}}})
-    type(api_mock).markets = markets
-
-    exchange = get_patched_exchange(mocker, default_conf, api_mock)
-
-    amount = 2.34559
-    pair = 'ETH/BTC'
-    amount = exchange.symbol_amount_prec(pair, amount)
-    assert amount == 2.3455
-
-
-def test_symbol_price_prec(default_conf, mocker):
-    '''
-    Test rounds up to 4 decimal places
-    '''
-    api_mock = MagicMock()
-    api_mock.load_markets = MagicMock(return_value={
-        'ETH/BTC': '', 'LTC/BTC': '', 'XRP/BTC': '', 'NEO/BTC': ''
-    })
-    mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value='binance'))
-
-    markets = PropertyMock(return_value={'ETH/BTC': {'precision': {'price': 4}}})
-    type(api_mock).markets = markets
-
-    exchange = get_patched_exchange(mocker, default_conf, api_mock)
-
-    price = 2.34559
-    pair = 'ETH/BTC'
-    price = exchange.symbol_price_prec(pair, price)
-    assert price == 2.3456
-
-
-def test_set_sandbox(default_conf, mocker):
-    """
-    Test working scenario
-    """
-    api_mock = MagicMock()
-    api_mock.load_markets = MagicMock(return_value={
-        'ETH/BTC': '', 'LTC/BTC': '', 'XRP/BTC': '', 'NEO/BTC': ''
-    })
-    url_mock = PropertyMock(return_value={'test': "api-public.sandbox.gdax.com",
-                                          'api': 'https://api.gdax.com'})
-    type(api_mock).urls = url_mock
-    exchange = get_patched_exchange(mocker, default_conf, api_mock)
-    liveurl = exchange._api.urls['api']
-    default_conf['exchange']['sandbox'] = True
-    exchange.set_sandbox(exchange._api, default_conf['exchange'], 'Logname')
-    assert exchange._api.urls['api'] != liveurl
-
-
-def test_set_sandbox_exception(default_conf, mocker):
-    """
-    Test Fail scenario
-    """
-    api_mock = MagicMock()
-    api_mock.load_markets = MagicMock(return_value={
-        'ETH/BTC': '', 'LTC/BTC': '', 'XRP/BTC': '', 'NEO/BTC': ''
-    })
-    url_mock = PropertyMock(return_value={'api': 'https://api.gdax.com'})
-    type(api_mock).urls = url_mock
-
-    with pytest.raises(OperationalException, match=r'does not provide a sandbox api'):
-        exchange = get_patched_exchange(mocker, default_conf, api_mock)
-        default_conf['exchange']['sandbox'] = True
-        exchange.set_sandbox(exchange._api, default_conf['exchange'], 'Logname')
-
-
-def test__load_async_markets(default_conf, mocker, caplog):
-    exchange = get_patched_exchange(mocker, default_conf)
-    exchange._api_async.load_markets = get_mock_coro(None)
-    exchange._load_async_markets()
-    assert exchange._api_async.load_markets.call_count == 1
-    caplog.set_level(logging.DEBUG)
-
-    exchange._api_async.load_markets = Mock(side_effect=ccxt.BaseError("deadbeef"))
-    exchange._load_async_markets()
-
-    assert log_has('Could not load async markets. Reason: deadbeef',
-                   caplog.record_tuples)
-
-
-def test__load_markets(default_conf, mocker, caplog):
-    caplog.set_level(logging.INFO)
-    api_mock = MagicMock()
-    api_mock.load_markets = MagicMock(side_effect=ccxt.BaseError())
-    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
-    mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
-    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
-    mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
-    Exchange(default_conf)
-    assert log_has('Unable to initialize markets. Reason: ', caplog.record_tuples)
-
-    expected_return = {'ETH/BTC': 'available'}
-    api_mock = MagicMock()
-    api_mock.load_markets = MagicMock(return_value=expected_return)
-    type(api_mock).markets = expected_return
-    default_conf['exchange']['pair_whitelist'] = ['ETH/BTC']
-    ex = get_patched_exchange(mocker, default_conf, api_mock, id="binance")
-    assert ex.markets == expected_return
-
-
-def test__reload_markets(default_conf, mocker, caplog):
-    caplog.set_level(logging.DEBUG)
-    initial_markets = {'ETH/BTC': {}}
-
-    def load_markets(*args, **kwargs):
-        exchange._api.markets = updated_markets
-
-    api_mock = MagicMock()
-    api_mock.load_markets = load_markets
-    type(api_mock).markets = initial_markets
-    default_conf['exchange']['markets_refresh_interval'] = 10
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="binance")
-    exchange._last_markets_refresh = arrow.utcnow().timestamp
-    updated_markets = {'ETH/BTC': {}, "LTC/BTC": {}}
-
-    assert exchange.markets == initial_markets
-
-    # less than 10 minutes have passed, no reload
-    exchange._reload_markets()
-    assert exchange.markets == initial_markets
-
-    # more than 10 minutes have passed, reload is executed
-    exchange._last_markets_refresh = arrow.utcnow().timestamp - 15 * 60
-    exchange._reload_markets()
-    assert exchange.markets == updated_markets
-    assert log_has('Performing scheduled market reload..', caplog.record_tuples)
-
-
-def test__reload_markets_exception(default_conf, mocker, caplog):
-    caplog.set_level(logging.DEBUG)
-
-    api_mock = MagicMock()
-    api_mock.load_markets = MagicMock(side_effect=ccxt.NetworkError)
-    default_conf['exchange']['markets_refresh_interval'] = 10
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="binance")
-
-    # less than 10 minutes have passed, no reload
-    exchange._reload_markets()
-    assert exchange._last_markets_refresh == 0
-    assert log_has_re(r"Could not reload markets.*", caplog.record_tuples)
-
-
-def test_validate_pairs(default_conf, mocker):  # test exchange.validate_pairs directly
-    api_mock = MagicMock()
-    type(api_mock).markets = PropertyMock(return_value={
-        'ETH/BTC': '', 'LTC/BTC': '', 'XRP/BTC': '', 'NEO/BTC': ''
-    })
-    id_mock = PropertyMock(return_value='test_exchange')
-    type(api_mock).id = id_mock
-
-    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
-    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
-    mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
-    Exchange(default_conf)
-
-
-def test_validate_pairs_not_available(default_conf, mocker):
-    api_mock = MagicMock()
-    type(api_mock).markets = PropertyMock(return_value={
-        'XRP/BTC': 'inactive'
-    })
-    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
-    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
-    mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
-
-    with pytest.raises(OperationalException, match=r'not available'):
-        Exchange(default_conf)
-
-
-def test_validate_pairs_exception(default_conf, mocker, caplog):
-    caplog.set_level(logging.INFO)
-    api_mock = MagicMock()
-    mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value='Binance'))
-
-    type(api_mock).markets = PropertyMock(return_value={})
-    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', api_mock)
-    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
-    mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
-
-    with pytest.raises(OperationalException, match=r'Pair ETH/BTC is not available on Binance'):
-        Exchange(default_conf)
-
-    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value={}))
-    Exchange(default_conf)
-    assert log_has('Unable to validate pairs (assuming they are correct).',
-                   caplog.record_tuples)
-
-
-def test_validate_timeframes(default_conf, mocker):
-    default_conf["ticker_interval"] = "5m"
-    api_mock = MagicMock()
-    id_mock = PropertyMock(return_value='test_exchange')
-    type(api_mock).id = id_mock
-    timeframes = PropertyMock(return_value={'1m': '1m',
-                                            '5m': '5m',
-                                            '15m': '15m',
-                                            '1h': '1h'})
-    type(api_mock).timeframes = timeframes
-
-    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
-    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
-    mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
-    Exchange(default_conf)
-
-
-def test_validate_timeframes_failed(default_conf, mocker):
-    default_conf["ticker_interval"] = "3m"
-    api_mock = MagicMock()
-    id_mock = PropertyMock(return_value='test_exchange')
-    type(api_mock).id = id_mock
-    timeframes = PropertyMock(return_value={'1m': '1m',
-                                            '5m': '5m',
-                                            '15m': '15m',
-                                            '1h': '1h'})
-    type(api_mock).timeframes = timeframes
-
-    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
-    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
-    mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
-    with pytest.raises(OperationalException, match=r'Invalid ticker 3m, this Exchange supports.*'):
-        Exchange(default_conf)
-
-
-def test_validate_timeframes_emulated_ohlcv_1(default_conf, mocker):
-    default_conf["ticker_interval"] = "3m"
-    api_mock = MagicMock()
-    id_mock = PropertyMock(return_value='test_exchange')
-    type(api_mock).id = id_mock
-
-    # delete timeframes so magicmock does not autocreate it
-    del api_mock.timeframes
-
-    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
-    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
-    mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
-    with pytest.raises(OperationalException,
-                       match=r'The ccxt library does not provide the list of timeframes '
-                             r'for the exchange ".*" and this exchange '
-                             r'is therefore not supported. *'):
-        Exchange(default_conf)
-
-
-def test_validate_timeframes_emulated_ohlcvi_2(default_conf, mocker):
-    default_conf["ticker_interval"] = "3m"
-    api_mock = MagicMock()
-    id_mock = PropertyMock(return_value='test_exchange')
-    type(api_mock).id = id_mock
-
-    # delete timeframes so magicmock does not autocreate it
-    del api_mock.timeframes
-
-    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
-    mocker.patch('freqtrade.exchange.Exchange._load_markets',
-                 MagicMock(return_value={'timeframes': None}))
-    mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
-    with pytest.raises(OperationalException,
-                       match=r'The ccxt library does not provide the list of timeframes '
-                             r'for the exchange ".*" and this exchange '
-                             r'is therefore not supported. *'):
-        Exchange(default_conf)
-
-
-def test_validate_timeframes_not_in_config(default_conf, mocker):
-    del default_conf["ticker_interval"]
-    api_mock = MagicMock()
-    id_mock = PropertyMock(return_value='test_exchange')
-    type(api_mock).id = id_mock
-    timeframes = PropertyMock(return_value={'1m': '1m',
-                                            '5m': '5m',
-                                            '15m': '15m',
-                                            '1h': '1h'})
-    type(api_mock).timeframes = timeframes
-
-    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
-    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
-    mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
-    Exchange(default_conf)
-
-
-def test_validate_order_types(default_conf, mocker):
-    api_mock = MagicMock()
-
-    type(api_mock).has = PropertyMock(return_value={'createMarketOrder': True})
-    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
-    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
-    mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
-    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
-    mocker.patch('freqtrade.exchange.Exchange.name', 'Bittrex')
-    default_conf['order_types'] = {
-        'buy': 'limit',
-        'sell': 'limit',
-        'stoploss': 'market',
-        'stoploss_on_exchange': False
-    }
-
-    Exchange(default_conf)
-
-    type(api_mock).has = PropertyMock(return_value={'createMarketOrder': False})
-    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
-
-    default_conf['order_types'] = {
-        'buy': 'limit',
-        'sell': 'limit',
-        'stoploss': 'market',
-        'stoploss_on_exchange': 'false'
-    }
-
-    with pytest.raises(OperationalException,
-                       match=r'Exchange .* does not support market orders.'):
-        Exchange(default_conf)
-
-    default_conf['order_types'] = {
-        'buy': 'limit',
-        'sell': 'limit',
-        'stoploss': 'limit',
-        'stoploss_on_exchange': True
-    }
-
-    with pytest.raises(OperationalException,
-                       match=r'On exchange stoploss is not supported for .*'):
-        Exchange(default_conf)
-
-
-def test_validate_order_types_not_in_config(default_conf, mocker):
-    api_mock = MagicMock()
-    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
-    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
-    mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
-    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
-
-    conf = copy.deepcopy(default_conf)
-    Exchange(conf)
-
-
-def test_exchange_has(default_conf, mocker):
-    exchange = get_patched_exchange(mocker, default_conf)
-    assert not exchange.exchange_has('ASDFASDF')
-    api_mock = MagicMock()
-
-    type(api_mock).has = PropertyMock(return_value={'deadbeef': True})
-    exchange = get_patched_exchange(mocker, default_conf, api_mock)
-    assert exchange.exchange_has("deadbeef")
-
-    type(api_mock).has = PropertyMock(return_value={'deadbeef': False})
-    exchange = get_patched_exchange(mocker, default_conf, api_mock)
-    assert not exchange.exchange_has("deadbeef")
-
-
-@pytest.mark.parametrize("side", [
-    ("buy"),
-    ("sell")
-])
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_dry_run_order(default_conf, mocker, side, exchange_name):
-    default_conf['dry_run'] = True
-    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
-
-    order = exchange.dry_run_order(
-        pair='ETH/BTC', ordertype='limit', side=side, amount=1, rate=200)
-    assert 'id' in order
-    assert f'dry_run_{side}_' in order["id"]
-    assert order["side"] == side
-    assert order["type"] == "limit"
-    assert order["pair"] == "ETH/BTC"
-
-
-@pytest.mark.parametrize("side", [
-    ("buy"),
-    ("sell")
-])
-@pytest.mark.parametrize("ordertype,rate,marketprice", [
-    ("market", None, None),
-    ("market", 200, True),
-    ("limit", 200, None),
-    ("stop_loss_limit", 200, None)
-])
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_create_order(default_conf, mocker, side, ordertype, rate, marketprice, exchange_name):
-    api_mock = MagicMock()
-    order_id = 'test_prod_{}_{}'.format(side, randint(0, 10 ** 6))
-    api_mock.options = {} if not marketprice else {"createMarketBuyOrderRequiresPrice": True}
-    api_mock.create_order = MagicMock(return_value={
-        'id': order_id,
-        'info': {
-            'foo': 'bar'
-        }
-    })
-    default_conf['dry_run'] = False
-    mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
-    mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-
-    order = exchange.create_order(
-        pair='ETH/BTC', ordertype=ordertype, side=side, amount=1, rate=200)
-
-    assert 'id' in order
-    assert 'info' in order
-    assert order['id'] == order_id
-    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
-    assert api_mock.create_order.call_args[0][1] == ordertype
-    assert api_mock.create_order.call_args[0][2] == side
-    assert api_mock.create_order.call_args[0][3] == 1
-    assert api_mock.create_order.call_args[0][4] is rate
-
-
-def test_buy_dry_run(default_conf, mocker):
-    default_conf['dry_run'] = True
-    exchange = get_patched_exchange(mocker, default_conf)
-
-    order = exchange.buy(pair='ETH/BTC', ordertype='limit',
-                         amount=1, rate=200, time_in_force='gtc')
-    assert 'id' in order
-    assert 'dry_run_buy_' in order['id']
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_buy_prod(default_conf, mocker, exchange_name):
-    api_mock = MagicMock()
-    order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
-    order_type = 'market'
-    time_in_force = 'gtc'
-    api_mock.options = {}
-    api_mock.create_order = MagicMock(return_value={
-        'id': order_id,
-        'info': {
-            'foo': 'bar'
-        }
-    })
-    default_conf['dry_run'] = False
-    mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
-    mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-
-    order = exchange.buy(pair='ETH/BTC', ordertype=order_type,
-                         amount=1, rate=200, time_in_force=time_in_force)
-
-    assert 'id' in order
-    assert 'info' in order
-    assert order['id'] == order_id
-    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
-    assert api_mock.create_order.call_args[0][1] == order_type
-    assert api_mock.create_order.call_args[0][2] == 'buy'
-    assert api_mock.create_order.call_args[0][3] == 1
-    assert api_mock.create_order.call_args[0][4] is None
-
-    api_mock.create_order.reset_mock()
-    order_type = 'limit'
-    order = exchange.buy(
-        pair='ETH/BTC',
-        ordertype=order_type,
-        amount=1,
-        rate=200,
-        time_in_force=time_in_force)
-    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
-    assert api_mock.create_order.call_args[0][1] == order_type
-    assert api_mock.create_order.call_args[0][2] == 'buy'
-    assert api_mock.create_order.call_args[0][3] == 1
-    assert api_mock.create_order.call_args[0][4] == 200
-
-    # test exception handling
-    with pytest.raises(DependencyException):
-        api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.buy(pair='ETH/BTC', ordertype=order_type,
-                     amount=1, rate=200, time_in_force=time_in_force)
-
-    with pytest.raises(DependencyException):
-        api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.buy(pair='ETH/BTC', ordertype=order_type,
-                     amount=1, rate=200, time_in_force=time_in_force)
-
-    with pytest.raises(TemporaryError):
-        api_mock.create_order = MagicMock(side_effect=ccxt.NetworkError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.buy(pair='ETH/BTC', ordertype=order_type,
-                     amount=1, rate=200, time_in_force=time_in_force)
-
-    with pytest.raises(OperationalException):
-        api_mock.create_order = MagicMock(side_effect=ccxt.BaseError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.buy(pair='ETH/BTC', ordertype=order_type,
-                     amount=1, rate=200, time_in_force=time_in_force)
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_buy_considers_time_in_force(default_conf, mocker, exchange_name):
-    api_mock = MagicMock()
-    order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
-    api_mock.options = {}
-    api_mock.create_order = MagicMock(return_value={
-        'id': order_id,
-        'info': {
-            'foo': 'bar'
-        }
-    })
-    default_conf['dry_run'] = False
-    mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
-    mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-
-    order_type = 'limit'
-    time_in_force = 'ioc'
-
-    order = exchange.buy(pair='ETH/BTC', ordertype=order_type,
-                         amount=1, rate=200, time_in_force=time_in_force)
-
-    assert 'id' in order
-    assert 'info' in order
-    assert order['id'] == order_id
-    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
-    assert api_mock.create_order.call_args[0][1] == order_type
-    assert api_mock.create_order.call_args[0][2] == 'buy'
-    assert api_mock.create_order.call_args[0][3] == 1
-    assert api_mock.create_order.call_args[0][4] == 200
-    assert "timeInForce" in api_mock.create_order.call_args[0][5]
-    assert api_mock.create_order.call_args[0][5]["timeInForce"] == time_in_force
-
-    order_type = 'market'
-    time_in_force = 'ioc'
-
-    order = exchange.buy(pair='ETH/BTC', ordertype=order_type,
-                         amount=1, rate=200, time_in_force=time_in_force)
-
-    assert 'id' in order
-    assert 'info' in order
-    assert order['id'] == order_id
-    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
-    assert api_mock.create_order.call_args[0][1] == order_type
-    assert api_mock.create_order.call_args[0][2] == 'buy'
-    assert api_mock.create_order.call_args[0][3] == 1
-    assert api_mock.create_order.call_args[0][4] is None
-    # Market orders should not send timeInForce!!
-    assert "timeInForce" not in api_mock.create_order.call_args[0][5]
-
-
-def test_sell_dry_run(default_conf, mocker):
-    default_conf['dry_run'] = True
-    exchange = get_patched_exchange(mocker, default_conf)
-
-    order = exchange.sell(pair='ETH/BTC', ordertype='limit', amount=1, rate=200)
-    assert 'id' in order
-    assert 'dry_run_sell_' in order['id']
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_sell_prod(default_conf, mocker, exchange_name):
-    api_mock = MagicMock()
-    order_id = 'test_prod_sell_{}'.format(randint(0, 10 ** 6))
-    order_type = 'market'
-    api_mock.options = {}
-    api_mock.create_order = MagicMock(return_value={
-        'id': order_id,
-        'info': {
-            'foo': 'bar'
-        }
-    })
-    default_conf['dry_run'] = False
-
-    mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
-    mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-
-    order = exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
-
-    assert 'id' in order
-    assert 'info' in order
-    assert order['id'] == order_id
-    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
-    assert api_mock.create_order.call_args[0][1] == order_type
-    assert api_mock.create_order.call_args[0][2] == 'sell'
-    assert api_mock.create_order.call_args[0][3] == 1
-    assert api_mock.create_order.call_args[0][4] is None
-
-    api_mock.create_order.reset_mock()
-    order_type = 'limit'
-    order = exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
-    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
-    assert api_mock.create_order.call_args[0][1] == order_type
-    assert api_mock.create_order.call_args[0][2] == 'sell'
-    assert api_mock.create_order.call_args[0][3] == 1
-    assert api_mock.create_order.call_args[0][4] == 200
-
-    # test exception handling
-    with pytest.raises(DependencyException):
-        api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
-
-    with pytest.raises(DependencyException):
-        api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
-
-    with pytest.raises(TemporaryError):
-        api_mock.create_order = MagicMock(side_effect=ccxt.NetworkError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
-
-    with pytest.raises(OperationalException):
-        api_mock.create_order = MagicMock(side_effect=ccxt.BaseError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_sell_considers_time_in_force(default_conf, mocker, exchange_name):
-    api_mock = MagicMock()
-    order_id = 'test_prod_sell_{}'.format(randint(0, 10 ** 6))
-    api_mock.create_order = MagicMock(return_value={
-        'id': order_id,
-        'info': {
-            'foo': 'bar'
-        }
-    })
-    api_mock.options = {}
-    default_conf['dry_run'] = False
-    mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
-    mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-
-    order_type = 'limit'
-    time_in_force = 'ioc'
-
-    order = exchange.sell(pair='ETH/BTC', ordertype=order_type,
-                          amount=1, rate=200, time_in_force=time_in_force)
-
-    assert 'id' in order
-    assert 'info' in order
-    assert order['id'] == order_id
-    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
-    assert api_mock.create_order.call_args[0][1] == order_type
-    assert api_mock.create_order.call_args[0][2] == 'sell'
-    assert api_mock.create_order.call_args[0][3] == 1
-    assert api_mock.create_order.call_args[0][4] == 200
-    assert "timeInForce" in api_mock.create_order.call_args[0][5]
-    assert api_mock.create_order.call_args[0][5]["timeInForce"] == time_in_force
-
-    order_type = 'market'
-    time_in_force = 'ioc'
-    order = exchange.sell(pair='ETH/BTC', ordertype=order_type,
-                          amount=1, rate=200, time_in_force=time_in_force)
-
-    assert 'id' in order
-    assert 'info' in order
-    assert order['id'] == order_id
-    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
-    assert api_mock.create_order.call_args[0][1] == order_type
-    assert api_mock.create_order.call_args[0][2] == 'sell'
-    assert api_mock.create_order.call_args[0][3] == 1
-    assert api_mock.create_order.call_args[0][4] is None
-    # Market orders should not send timeInForce!!
-    assert "timeInForce" not in api_mock.create_order.call_args[0][5]
-
-
-def test_get_balance_dry_run(default_conf, mocker):
-    default_conf['dry_run'] = True
-
-    exchange = get_patched_exchange(mocker, default_conf)
-    assert exchange.get_balance(currency='BTC') == 999.9
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_get_balance_prod(default_conf, mocker, exchange_name):
-    api_mock = MagicMock()
-    api_mock.fetch_balance = MagicMock(return_value={'BTC': {'free': 123.4}})
-    default_conf['dry_run'] = False
-
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-
-    assert exchange.get_balance(currency='BTC') == 123.4
-
-    with pytest.raises(OperationalException):
-        api_mock.fetch_balance = MagicMock(side_effect=ccxt.BaseError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-
-        exchange.get_balance(currency='BTC')
-
-    with pytest.raises(TemporaryError, match=r'.*balance due to malformed exchange response:.*'):
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        mocker.patch('freqtrade.exchange.Exchange.get_balances', MagicMock(return_value={}))
-        exchange.get_balance(currency='BTC')
-
-
-def test_get_balances_dry_run(default_conf, mocker):
-    default_conf['dry_run'] = True
-    exchange = get_patched_exchange(mocker, default_conf)
-    assert exchange.get_balances() == {}
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_get_balances_prod(default_conf, mocker, exchange_name):
-    balance_item = {
-        'free': 10.0,
-        'total': 10.0,
-        'used': 0.0
-    }
-
-    api_mock = MagicMock()
-    api_mock.fetch_balance = MagicMock(return_value={
-        '1ST': balance_item,
-        '2ST': balance_item,
-        '3ST': balance_item
-    })
-    default_conf['dry_run'] = False
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-    assert len(exchange.get_balances()) == 3
-    assert exchange.get_balances()['1ST']['free'] == 10.0
-    assert exchange.get_balances()['1ST']['total'] == 10.0
-    assert exchange.get_balances()['1ST']['used'] == 0.0
-
-    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
-                           "get_balances", "fetch_balance")
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_get_tickers(default_conf, mocker, exchange_name):
-    api_mock = MagicMock()
-    tick = {'ETH/BTC': {
-          'symbol': 'ETH/BTC',
-          'bid': 0.5,
-          'ask': 1,
-          'last': 42,
-      }, 'BCH/BTC': {
-          'symbol': 'BCH/BTC',
-          'bid': 0.6,
-          'ask': 0.5,
-          'last': 41,
-      }
-      }
-    api_mock.fetch_tickers = MagicMock(return_value=tick)
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-    # retrieve original ticker
-    tickers = exchange.get_tickers()
-
-    assert 'ETH/BTC' in tickers
-    assert 'BCH/BTC' in tickers
-    assert tickers['ETH/BTC']['bid'] == 0.5
-    assert tickers['ETH/BTC']['ask'] == 1
-    assert tickers['BCH/BTC']['bid'] == 0.6
-    assert tickers['BCH/BTC']['ask'] == 0.5
-
-    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
-                           "get_tickers", "fetch_tickers")
-
-    with pytest.raises(OperationalException):
-        api_mock.fetch_tickers = MagicMock(side_effect=ccxt.NotSupported)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.get_tickers()
-
-    api_mock.fetch_tickers = MagicMock(return_value={})
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-    exchange.get_tickers()
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_get_ticker(default_conf, mocker, exchange_name):
-    api_mock = MagicMock()
-    tick = {
-        'symbol': 'ETH/BTC',
-        'bid': 0.00001098,
-        'ask': 0.00001099,
-        'last': 0.0001,
-    }
-    api_mock.fetch_ticker = MagicMock(return_value=tick)
-    api_mock.markets = {'ETH/BTC': {'active': True}}
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-    # retrieve original ticker
-    ticker = exchange.get_ticker(pair='ETH/BTC')
-
-    assert ticker['bid'] == 0.00001098
-    assert ticker['ask'] == 0.00001099
-
-    # change the ticker
-    tick = {
-        'symbol': 'ETH/BTC',
-        'bid': 0.5,
-        'ask': 1,
-        'last': 42,
-    }
-    api_mock.fetch_ticker = MagicMock(return_value=tick)
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-
-    # if not caching the result we should get the same ticker
-    # if not fetching a new result we should get the cached ticker
-    ticker = exchange.get_ticker(pair='ETH/BTC')
-
-    assert api_mock.fetch_ticker.call_count == 1
-    assert ticker['bid'] == 0.5
-    assert ticker['ask'] == 1
-
-    assert 'ETH/BTC' in exchange._cached_ticker
-    assert exchange._cached_ticker['ETH/BTC']['bid'] == 0.5
-    assert exchange._cached_ticker['ETH/BTC']['ask'] == 1
-
-    # Test caching
-    api_mock.fetch_ticker = MagicMock()
-    exchange.get_ticker(pair='ETH/BTC', refresh=False)
-    assert api_mock.fetch_ticker.call_count == 0
-
-    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
-                           "get_ticker", "fetch_ticker",
-                           pair='ETH/BTC', refresh=True)
-
-    api_mock.fetch_ticker = MagicMock(return_value={})
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-    exchange.get_ticker(pair='ETH/BTC', refresh=True)
-
-    with pytest.raises(DependencyException, match=r'Pair XRP/ETH not available'):
-        exchange.get_ticker(pair='XRP/ETH', refresh=True)
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_get_history(default_conf, mocker, caplog, exchange_name):
-    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
-    tick = [
-        [
-            arrow.utcnow().timestamp * 1000,  # unix timestamp ms
-            1,  # open
-            2,  # high
-            3,  # low
-            4,  # close
-            5,  # volume (in quote currency)
-        ]
-    ]
-    pair = 'ETH/BTC'
-
-    async def mock_candle_hist(pair, ticker_interval, since_ms):
-        return pair, ticker_interval, tick
-
-    exchange._async_get_candle_history = Mock(wraps=mock_candle_hist)
-    # one_call calculation * 1.8 should do 2 calls
-    since = 5 * 60 * 500 * 1.8
-    print(f"since = {since}")
-    ret = exchange.get_history(pair, "5m", int((arrow.utcnow().timestamp - since) * 1000))
-
-    assert exchange._async_get_candle_history.call_count == 2
-    # Returns twice the above tick
-    assert len(ret) == 2
-
-
-def test_refresh_latest_ohlcv(mocker, default_conf, caplog) -> None:
-    tick = [
-        [
-            (arrow.utcnow().timestamp - 1) * 1000,  # unix timestamp ms
-            1,  # open
-            2,  # high
-            3,  # low
-            4,  # close
-            5,  # volume (in quote currency)
-        ],
-        [
-            arrow.utcnow().timestamp * 1000,  # unix timestamp ms
-            3,  # open
-            1,  # high
-            4,  # low
-            6,  # close
-            5,  # volume (in quote currency)
-        ]
-    ]
-
-    caplog.set_level(logging.DEBUG)
-    exchange = get_patched_exchange(mocker, default_conf)
-    exchange._api_async.fetch_ohlcv = get_mock_coro(tick)
-
-    pairs = [('IOTA/ETH', '5m'), ('XRP/ETH', '5m')]
-    # empty dicts
-    assert not exchange._klines
-    exchange.refresh_latest_ohlcv(pairs)
-
-    assert log_has(f'Refreshing ohlcv data for {len(pairs)} pairs', caplog.record_tuples)
-    assert exchange._klines
-    assert exchange._api_async.fetch_ohlcv.call_count == 2
-    for pair in pairs:
-        assert isinstance(exchange.klines(pair), DataFrame)
-        assert len(exchange.klines(pair)) > 0
-
-        # klines function should return a different object on each call
-        # if copy is "True"
-        assert exchange.klines(pair) is not exchange.klines(pair)
-        assert exchange.klines(pair) is not exchange.klines(pair, copy=True)
-        assert exchange.klines(pair, copy=True) is not exchange.klines(pair, copy=True)
-        assert exchange.klines(pair, copy=False) is exchange.klines(pair, copy=False)
-
-    # test caching
-    exchange.refresh_latest_ohlcv([('IOTA/ETH', '5m'), ('XRP/ETH', '5m')])
-
-    assert exchange._api_async.fetch_ohlcv.call_count == 2
-    assert log_has(f"Using cached ohlcv data for pair {pairs[0][0]}, interval {pairs[0][1]} ...",
-                   caplog.record_tuples)
-
-
-@pytest.mark.asyncio
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-async def test__async_get_candle_history(default_conf, mocker, caplog, exchange_name):
-    tick = [
-        [
-            arrow.utcnow().timestamp * 1000,  # unix timestamp ms
-            1,  # open
-            2,  # high
-            3,  # low
-            4,  # close
-            5,  # volume (in quote currency)
-        ]
-    ]
-
-    caplog.set_level(logging.DEBUG)
-    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
-    # Monkey-patch async function
-    exchange._api_async.fetch_ohlcv = get_mock_coro(tick)
-
-    pair = 'ETH/BTC'
-    res = await exchange._async_get_candle_history(pair, "5m")
-    assert type(res) is tuple
-    assert len(res) == 3
-    assert res[0] == pair
-    assert res[1] == "5m"
-    assert res[2] == tick
-    assert exchange._api_async.fetch_ohlcv.call_count == 1
-    assert not log_has(f"Using cached ohlcv data for {pair} ...", caplog.record_tuples)
-
-    # exchange = Exchange(default_conf)
-    await async_ccxt_exception(mocker, default_conf, MagicMock(),
-                               "_async_get_candle_history", "fetch_ohlcv",
-                               pair='ABCD/BTC', ticker_interval=default_conf['ticker_interval'])
-
-    api_mock = MagicMock()
-    with pytest.raises(OperationalException, match=r'Could not fetch ticker data*'):
-        api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.BaseError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        await exchange._async_get_candle_history(pair, "5m",
-                                                 (arrow.utcnow().timestamp - 2000) * 1000)
-
-
-@pytest.mark.asyncio
-async def test__async_get_candle_history_empty(default_conf, mocker, caplog):
-    """ Test empty exchange result """
-    tick = []
-
-    caplog.set_level(logging.DEBUG)
-    exchange = get_patched_exchange(mocker, default_conf)
-    # Monkey-patch async function
-    exchange._api_async.fetch_ohlcv = get_mock_coro([])
-
-    exchange = Exchange(default_conf)
-    pair = 'ETH/BTC'
-    res = await exchange._async_get_candle_history(pair, "5m")
-    assert type(res) is tuple
-    assert len(res) == 3
-    assert res[0] == pair
-    assert res[1] == "5m"
-    assert res[2] == tick
-    assert exchange._api_async.fetch_ohlcv.call_count == 1
-
-
-def test_refresh_latest_ohlcv_inv_result(default_conf, mocker, caplog):
-
-    async def mock_get_candle_hist(pair, *args, **kwargs):
-        if pair == 'ETH/BTC':
-            return [[]]
-        else:
-            raise TypeError()
-
-    exchange = get_patched_exchange(mocker, default_conf)
-
-    # Monkey-patch async function with empty result
-    exchange._api_async.fetch_ohlcv = MagicMock(side_effect=mock_get_candle_hist)
-
-    pairs = [("ETH/BTC", "5m"), ("XRP/BTC", "5m")]
-    res = exchange.refresh_latest_ohlcv(pairs)
-    assert exchange._klines
-    assert exchange._api_async.fetch_ohlcv.call_count == 2
-
-    assert type(res) is list
-    assert len(res) == 2
-    # Test that each is in list at least once as order is not guaranteed
-    assert type(res[0]) is tuple or type(res[1]) is tuple
-    assert type(res[0]) is TypeError or type(res[1]) is TypeError
-    assert log_has("Error loading ETH/BTC. Result was [[]].", caplog.record_tuples)
-    assert log_has("Async code raised an exception: TypeError", caplog.record_tuples)
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_get_order_book(default_conf, mocker, order_book_l2, exchange_name):
-    default_conf['exchange']['name'] = exchange_name
-    api_mock = MagicMock()
-
-    api_mock.fetch_l2_order_book = order_book_l2
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-    order_book = exchange.get_order_book(pair='ETH/BTC', limit=10)
-    assert 'bids' in order_book
-    assert 'asks' in order_book
-    assert len(order_book['bids']) == 10
-    assert len(order_book['asks']) == 10
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_get_order_book_exception(default_conf, mocker, exchange_name):
-    api_mock = MagicMock()
-    with pytest.raises(OperationalException):
-        api_mock.fetch_l2_order_book = MagicMock(side_effect=ccxt.NotSupported)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.get_order_book(pair='ETH/BTC', limit=50)
-    with pytest.raises(TemporaryError):
-        api_mock.fetch_l2_order_book = MagicMock(side_effect=ccxt.NetworkError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.get_order_book(pair='ETH/BTC', limit=50)
-    with pytest.raises(OperationalException):
-        api_mock.fetch_l2_order_book = MagicMock(side_effect=ccxt.BaseError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.get_order_book(pair='ETH/BTC', limit=50)
-
-
-def make_fetch_ohlcv_mock(data):
-    def fetch_ohlcv_mock(pair, timeframe, since):
-        if since:
-            assert since > data[-1][0]
-            return []
-        return data
-    return fetch_ohlcv_mock
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-@pytest.mark.asyncio
-async def test___async_get_candle_history_sort(default_conf, mocker, exchange_name):
-    def sort_data(data, key):
-        return sorted(data, key=key)
-
-    # GDAX use-case (real data from GDAX)
-    # This ticker history is ordered DESC (newest first, oldest last)
-    tick = [
-        [1527833100000, 0.07666, 0.07671, 0.07666, 0.07668, 16.65244264],
-        [1527832800000, 0.07662, 0.07666, 0.07662, 0.07666, 1.30051526],
-        [1527832500000, 0.07656, 0.07661, 0.07656, 0.07661, 12.034778840000001],
-        [1527832200000, 0.07658, 0.07658, 0.07655, 0.07656, 0.59780186],
-        [1527831900000, 0.07658, 0.07658, 0.07658, 0.07658, 1.76278136],
-        [1527831600000, 0.07658, 0.07658, 0.07658, 0.07658, 2.22646521],
-        [1527831300000, 0.07655, 0.07657, 0.07655, 0.07657, 1.1753],
-        [1527831000000, 0.07654, 0.07654, 0.07651, 0.07651, 0.8073060299999999],
-        [1527830700000, 0.07652, 0.07652, 0.07651, 0.07652, 10.04822687],
-        [1527830400000, 0.07649, 0.07651, 0.07649, 0.07651, 2.5734867]
-    ]
-    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
-    exchange._api_async.fetch_ohlcv = get_mock_coro(tick)
-    sort_mock = mocker.patch('freqtrade.exchange.exchange.sorted', MagicMock(side_effect=sort_data))
-    # Test the ticker history sort
-    res = await exchange._async_get_candle_history('ETH/BTC', default_conf['ticker_interval'])
-    assert res[0] == 'ETH/BTC'
-    ticks = res[2]
-
-    assert sort_mock.call_count == 1
-    assert ticks[0][0] == 1527830400000
-    assert ticks[0][1] == 0.07649
-    assert ticks[0][2] == 0.07651
-    assert ticks[0][3] == 0.07649
-    assert ticks[0][4] == 0.07651
-    assert ticks[0][5] == 2.5734867
-
-    assert ticks[9][0] == 1527833100000
-    assert ticks[9][1] == 0.07666
-    assert ticks[9][2] == 0.07671
-    assert ticks[9][3] == 0.07666
-    assert ticks[9][4] == 0.07668
-    assert ticks[9][5] == 16.65244264
-
-    # Bittrex use-case (real data from Bittrex)
-    # This ticker history is ordered ASC (oldest first, newest last)
-    tick = [
-        [1527827700000, 0.07659999, 0.0766, 0.07627, 0.07657998, 1.85216924],
-        [1527828000000, 0.07657995, 0.07657995, 0.0763, 0.0763, 26.04051037],
-        [1527828300000, 0.0763, 0.07659998, 0.0763, 0.0764, 10.36434124],
-        [1527828600000, 0.0764, 0.0766, 0.0764, 0.0766, 5.71044773],
-        [1527828900000, 0.0764, 0.07666998, 0.0764, 0.07666998, 47.48888565],
-        [1527829200000, 0.0765, 0.07672999, 0.0765, 0.07672999, 3.37640326],
-        [1527829500000, 0.0766, 0.07675, 0.0765, 0.07675, 8.36203831],
-        [1527829800000, 0.07675, 0.07677999, 0.07620002, 0.076695, 119.22963884],
-        [1527830100000, 0.076695, 0.07671, 0.07624171, 0.07671, 1.80689244],
-        [1527830400000, 0.07671, 0.07674399, 0.07629216, 0.07655213, 2.31452783]
-    ]
-    exchange._api_async.fetch_ohlcv = get_mock_coro(tick)
-    # Reset sort mock
-    sort_mock = mocker.patch('freqtrade.exchange.sorted', MagicMock(side_effect=sort_data))
-    # Test the ticker history sort
-    res = await exchange._async_get_candle_history('ETH/BTC', default_conf['ticker_interval'])
-    assert res[0] == 'ETH/BTC'
-    assert res[1] == default_conf['ticker_interval']
-    ticks = res[2]
-    # Sorted not called again - data is already in order
-    assert sort_mock.call_count == 0
-    assert ticks[0][0] == 1527827700000
-    assert ticks[0][1] == 0.07659999
-    assert ticks[0][2] == 0.0766
-    assert ticks[0][3] == 0.07627
-    assert ticks[0][4] == 0.07657998
-    assert ticks[0][5] == 1.85216924
-
-    assert ticks[9][0] == 1527830400000
-    assert ticks[9][1] == 0.07671
-    assert ticks[9][2] == 0.07674399
-    assert ticks[9][3] == 0.07629216
-    assert ticks[9][4] == 0.07655213
-    assert ticks[9][5] == 2.31452783
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_cancel_order_dry_run(default_conf, mocker, exchange_name):
-    default_conf['dry_run'] = True
-    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
-    assert exchange.cancel_order(order_id='123', pair='TKN/BTC') is None
-
-
-# Ensure that if not dry_run, we should call API
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_cancel_order(default_conf, mocker, exchange_name):
-    default_conf['dry_run'] = False
-    api_mock = MagicMock()
-    api_mock.cancel_order = MagicMock(return_value=123)
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-    assert exchange.cancel_order(order_id='_', pair='TKN/BTC') == 123
-
-    with pytest.raises(InvalidOrderException):
-        api_mock.cancel_order = MagicMock(side_effect=ccxt.InvalidOrder)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.cancel_order(order_id='_', pair='TKN/BTC')
-    assert api_mock.cancel_order.call_count == 1
-
-    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
-                           "cancel_order", "cancel_order",
-                           order_id='_', pair='TKN/BTC')
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_get_order(default_conf, mocker, exchange_name):
-    default_conf['dry_run'] = True
-    order = MagicMock()
-    order.myid = 123
-    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
-    exchange._dry_run_open_orders['X'] = order
-    print(exchange.get_order('X', 'TKN/BTC'))
-    assert exchange.get_order('X', 'TKN/BTC').myid == 123
-
-    default_conf['dry_run'] = False
-    api_mock = MagicMock()
-    api_mock.fetch_order = MagicMock(return_value=456)
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-    assert exchange.get_order('X', 'TKN/BTC') == 456
-
-    with pytest.raises(InvalidOrderException):
-        api_mock.fetch_order = MagicMock(side_effect=ccxt.InvalidOrder)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-        exchange.get_order(order_id='_', pair='TKN/BTC')
-    assert api_mock.fetch_order.call_count == 1
-
-    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
-                           'get_order', 'fetch_order',
-                           order_id='_', pair='TKN/BTC')
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_name(default_conf, mocker, exchange_name):
-    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
-    default_conf['exchange']['name'] = exchange_name
-    exchange = Exchange(default_conf)
-
-    assert exchange.name == exchange_name.title()
-    assert exchange.id == exchange_name
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_get_trades_for_order(default_conf, mocker, exchange_name):
-    order_id = 'ABCD-ABCD'
-    since = datetime(2018, 5, 5)
-    default_conf["dry_run"] = False
-    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
-    api_mock = MagicMock()
-
-    api_mock.fetch_my_trades = MagicMock(return_value=[{'id': 'TTR67E-3PFBD-76IISV',
-                                                        'order': 'ABCD-ABCD',
-                                                        'info': {'pair': 'XLTCZBTC',
-                                                                 'time': 1519860024.4388,
-                                                                 'type': 'buy',
-                                                                 'ordertype': 'limit',
-                                                                 'price': '20.00000',
-                                                                 'cost': '38.62000',
-                                                                 'fee': '0.06179',
-                                                                 'vol': '5',
-                                                                 'id': 'ABCD-ABCD'},
-                                                        'timestamp': 1519860024438,
-                                                        'datetime': '2018-02-28T23:20:24.438Z',
-                                                        'symbol': 'LTC/BTC',
-                                                        'type': 'limit',
-                                                        'side': 'buy',
-                                                        'price': 165.0,
-                                                        'amount': 0.2340606,
-                                                        'fee': {'cost': 0.06179, 'currency': 'BTC'}
-                                                        }])
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-
-    orders = exchange.get_trades_for_order(order_id, 'LTC/BTC', since)
-    assert len(orders) == 1
-    assert orders[0]['price'] == 165
-
-    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
-                           'get_trades_for_order', 'fetch_my_trades',
-                           order_id=order_id, pair='LTC/BTC', since=since)
-
-    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=False))
-    assert exchange.get_trades_for_order(order_id, 'LTC/BTC', since) == []
-
-
-@pytest.mark.parametrize("exchange_name", EXCHANGES)
-def test_get_fee(default_conf, mocker, exchange_name):
-    api_mock = MagicMock()
-    api_mock.calculate_fee = MagicMock(return_value={
-        'type': 'taker',
-        'currency': 'BTC',
-        'rate': 0.025,
-        'cost': 0.05
-    })
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
-
-    assert exchange.get_fee() == 0.025
-
-    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
-                           'get_fee', 'calculate_fee')
-
-
-def test_stoploss_limit_order(default_conf, mocker):
-    api_mock = MagicMock()
-    order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
-    order_type = 'stop_loss_limit'
-
-    api_mock.create_order = MagicMock(return_value={
-        'id': order_id,
-        'info': {
-            'foo': 'bar'
-        }
-    })
-
-    default_conf['dry_run'] = False
-    mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
-    mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
-
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
-
-    with pytest.raises(OperationalException):
-        order = exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=190, rate=200)
-
-    api_mock.create_order.reset_mock()
-
-    order = exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=220, rate=200)
-
-    assert 'id' in order
-    assert 'info' in order
-    assert order['id'] == order_id
-    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
-    assert api_mock.create_order.call_args[0][1] == order_type
-    assert api_mock.create_order.call_args[0][2] == 'sell'
-    assert api_mock.create_order.call_args[0][3] == 1
-    assert api_mock.create_order.call_args[0][4] == 200
-    assert api_mock.create_order.call_args[0][5] == {'stopPrice': 220}
-
-    # test exception handling
-    with pytest.raises(DependencyException):
-        api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock)
-        exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=220, rate=200)
-
-    with pytest.raises(DependencyException):
-        api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock)
-        exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=220, rate=200)
-
-    with pytest.raises(TemporaryError):
-        api_mock.create_order = MagicMock(side_effect=ccxt.NetworkError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock)
-        exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=220, rate=200)
-
-    with pytest.raises(OperationalException):
-        api_mock.create_order = MagicMock(side_effect=ccxt.BaseError)
-        exchange = get_patched_exchange(mocker, default_conf, api_mock)
-        exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=220, rate=200)
-
-
-def test_stoploss_limit_order_dry_run(default_conf, mocker):
-    api_mock = MagicMock()
-    order_type = 'stop_loss_limit'
-    default_conf['dry_run'] = True
-    mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
-    mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
-
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
-
-    with pytest.raises(OperationalException):
-        order = exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=190, rate=200)
-
-    api_mock.create_order.reset_mock()
-
-    order = exchange.stoploss_limit(pair='ETH/BTC', amount=1, stop_price=220, rate=200)
-
-    assert 'id' in order
-    assert 'info' in order
-    assert 'type' in order
-
-    assert order['type'] == order_type
-    assert order['price'] == 220
-    assert order['amount'] == 1
-
-
-def test_merge_ft_has_dict(default_conf, mocker):
-    mocker.patch.multiple('freqtrade.exchange.Exchange',
-                          _init_ccxt=MagicMock(return_value=MagicMock()),
-                          _load_async_markets=MagicMock(),
-                          validate_pairs=MagicMock(),
-                          validate_timeframes=MagicMock())
-    ex = Exchange(default_conf)
-    assert ex._ft_has == Exchange._ft_has_default
-
-    ex = Kraken(default_conf)
-    assert ex._ft_has == Exchange._ft_has_default
-
-    # Binance defines different values
-    ex = Binance(default_conf)
-    assert ex._ft_has != Exchange._ft_has_default
-    assert ex._ft_has['stoploss_on_exchange']
-    assert ex._ft_has['order_time_in_force'] == ['gtc', 'fok', 'ioc']
-
-    conf = copy.deepcopy(default_conf)
-    conf['exchange']['_ft_has_params'] = {"DeadBeef": 20,
-                                          "stoploss_on_exchange": False}
-    # Use settings from configuration (overriding stoploss_on_exchange)
-    ex = Binance(conf)
-    assert ex._ft_has != Exchange._ft_has_default
-    assert not ex._ft_has['stoploss_on_exchange']
-    assert ex._ft_has['DeadBeef'] == 20
-
-
-def test_get_valid_pair_combination(default_conf, mocker, markets):
-    mocker.patch.multiple('freqtrade.exchange.Exchange',
-                          _init_ccxt=MagicMock(return_value=MagicMock()),
-                          _load_async_markets=MagicMock(),
-                          validate_pairs=MagicMock(),
-                          validate_timeframes=MagicMock(),
-                          markets=PropertyMock(return_value=markets))
-    ex = Exchange(default_conf)
-
-    assert ex.get_valid_pair_combination("ETH", "BTC") == "ETH/BTC"
-    assert ex.get_valid_pair_combination("BTC", "ETH") == "ETH/BTC"
-    with pytest.raises(DependencyException, match=r"Could not combine.* to get a valid pair."):
-        ex.get_valid_pair_combination("NOPAIR", "ETH")
diff --git a/freqtrade/tests/exchange/test_kraken.py b/freqtrade/tests/exchange/test_kraken.py
deleted file mode 100644
index 8f476affb..000000000
--- a/freqtrade/tests/exchange/test_kraken.py
+++ /dev/null
@@ -1,69 +0,0 @@
-# pragma pylint: disable=missing-docstring, C0103, bad-continuation, global-statement
-# pragma pylint: disable=protected-access
-from random import randint
-from unittest.mock import MagicMock
-
-from freqtrade.tests.conftest import get_patched_exchange
-
-
-def test_buy_kraken_trading_agreement(default_conf, mocker):
-    api_mock = MagicMock()
-    order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
-    order_type = 'limit'
-    time_in_force = 'ioc'
-    api_mock.options = {}
-    api_mock.create_order = MagicMock(return_value={
-        'id': order_id,
-        'info': {
-            'foo': 'bar'
-        }
-    })
-    default_conf['dry_run'] = False
-
-    mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
-    mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="kraken")
-
-    order = exchange.buy(pair='ETH/BTC', ordertype=order_type,
-                         amount=1, rate=200, time_in_force=time_in_force)
-
-    assert 'id' in order
-    assert 'info' in order
-    assert order['id'] == order_id
-    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
-    assert api_mock.create_order.call_args[0][1] == order_type
-    assert api_mock.create_order.call_args[0][2] == 'buy'
-    assert api_mock.create_order.call_args[0][3] == 1
-    assert api_mock.create_order.call_args[0][4] == 200
-    assert api_mock.create_order.call_args[0][5] == {'timeInForce': 'ioc',
-                                                     'trading_agreement': 'agree'}
-
-
-def test_sell_kraken_trading_agreement(default_conf, mocker):
-    api_mock = MagicMock()
-    order_id = 'test_prod_sell_{}'.format(randint(0, 10 ** 6))
-    order_type = 'market'
-    api_mock.options = {}
-    api_mock.create_order = MagicMock(return_value={
-        'id': order_id,
-        'info': {
-            'foo': 'bar'
-        }
-    })
-    default_conf['dry_run'] = False
-
-    mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
-    mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
-    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="kraken")
-
-    order = exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
-
-    assert 'id' in order
-    assert 'info' in order
-    assert order['id'] == order_id
-    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
-    assert api_mock.create_order.call_args[0][1] == order_type
-    assert api_mock.create_order.call_args[0][2] == 'sell'
-    assert api_mock.create_order.call_args[0][3] == 1
-    assert api_mock.create_order.call_args[0][4] is None
-    assert api_mock.create_order.call_args[0][5] == {'trading_agreement': 'agree'}
diff --git a/freqtrade/tests/optimize/test_backtest_detail.py b/freqtrade/tests/optimize/test_backtest_detail.py
deleted file mode 100644
index 402e22391..000000000
--- a/freqtrade/tests/optimize/test_backtest_detail.py
+++ /dev/null
@@ -1,290 +0,0 @@
-# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, C0330, unused-argument
-import logging
-from unittest.mock import MagicMock
-
-import pytest
-from pandas import DataFrame
-
-from freqtrade.data.history import get_timeframe
-from freqtrade.optimize.backtesting import Backtesting
-from freqtrade.strategy.interface import SellType
-from freqtrade.tests.conftest import patch_exchange
-from freqtrade.tests.optimize import (BTContainer, BTrade,
-                                      _build_backtest_dataframe,
-                                      _get_frame_time_from_offset,
-                                      tests_ticker_interval)
-
-# Test 0 Sell signal sell
-# Test with Stop-loss at 1%
-# TC0: Sell signal in candle 3
-tc0 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
-    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
-    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
-    [2, 4987, 5012, 4986, 4600, 6172, 0, 0],  # exit with stoploss hit
-    [3, 5010, 5000, 4980, 5010, 6172, 0, 1],
-    [4, 5010, 4987, 4977, 4995, 6172, 0, 0],
-    [5, 4995, 4995, 4995, 4950, 6172, 0, 0]],
-    stop_loss=-0.01, roi=1, profit_perc=0.002, use_sell_signal=True,
-    trades=[BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=1, close_tick=4)]
-)
-
-# Test 1 Minus 8% Close
-# Test with Stop-loss at 1%
-# TC1: Stop-Loss Triggered 1% loss
-tc1 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
-    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
-    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
-    [2, 4987, 5012, 4600, 4600, 6172, 0, 0],  # exit with stoploss hit
-    [3, 4975, 5000, 4980, 4977, 6172, 0, 0],
-    [4, 4977, 4987, 4977, 4995, 6172, 0, 0],
-    [5, 4995, 4995, 4995, 4950, 6172, 0, 0]],
-    stop_loss=-0.01, roi=1, profit_perc=-0.01,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
-)
-
-
-# Test 2 Minus 4% Low, minus 1% close
-# Test with Stop-Loss at 3%
-# TC2: Stop-Loss Triggered 3% Loss
-tc2 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
-    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
-    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
-    [2, 4987, 5012, 4962, 4975, 6172, 0, 0],
-    [3, 4975, 5000, 4800, 4962, 6172, 0, 0],  # exit with stoploss hit
-    [4, 4962, 4987, 4937, 4950, 6172, 0, 0],
-    [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
-    stop_loss=-0.03, roi=1, profit_perc=-0.03,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=3)]
-)
-
-
-# Test 3 Candle drops 4%, Recovers 1%.
-#               Entry Criteria Met
-# 	            Candle drops 20%
-# Test with Stop-Loss at 2%
-# TC3: Trade-A: Stop-Loss Triggered 2% Loss
-#          Trade-B: Stop-Loss Triggered 2% Loss
-tc3 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
-    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
-    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
-    [2, 4987, 5012, 4800, 4975, 6172, 0, 0],  # exit with stoploss hit
-    [3, 4975, 5000, 4950, 4962, 6172, 1, 0],
-    [4, 4975, 5000, 4950, 4962, 6172, 0, 0],  # enter trade 2 (signal on last candle)
-    [5, 4962, 4987, 4000, 4000, 6172, 0, 0],  # exit with stoploss hit
-    [6, 4950, 4975, 4975, 4950, 6172, 0, 0]],
-    stop_loss=-0.02, roi=1, profit_perc=-0.04,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2),
-            BTrade(sell_reason=SellType.STOP_LOSS, open_tick=4, close_tick=5)]
-)
-
-# Test 4 Minus 3% / recovery +15%
-# Candle Data for test 3 – Candle drops 3% Closed 15% up
-# Test with Stop-loss at 2% ROI 6%
-# TC4: Stop-Loss Triggered 2% Loss
-tc4 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
-    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
-    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
-    [2, 4987, 5750, 4850, 5750, 6172, 0, 0],  # Exit with stoploss hit
-    [3, 4975, 5000, 4950, 4962, 6172, 0, 0],
-    [4, 4962, 4987, 4937, 4950, 6172, 0, 0],
-    [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
-    stop_loss=-0.02, roi=0.06, profit_perc=-0.02,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
-)
-
-# Test 5 / Drops 0.5% Closes +20%
-# Set stop-loss at 1% ROI 3%
-# TC5: ROI triggers 3% Gain
-tc5 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
-    [0, 5000, 5025, 4980, 4987, 6172, 1, 0],
-    [1, 5000, 5025, 4980, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
-    [2, 4987, 5025, 4975, 4987, 6172, 0, 0],
-    [3, 4975, 6000, 4975, 6000, 6172, 0, 0],  # ROI
-    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
-    [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
-    stop_loss=-0.01, roi=0.03, profit_perc=0.03,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
-)
-
-# Test 6 / Drops 3% / Recovers 6% Positive / Closes 1% positve
-# Set stop-loss at 2% ROI at 5%
-# TC6: Stop-Loss triggers 2% Loss
-tc6 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
-    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
-    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
-    [2, 4987, 5300, 4850, 5050, 6172, 0, 0],  # Exit with stoploss
-    [3, 4975, 5000, 4950, 4962, 6172, 0, 0],
-    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
-    [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
-    stop_loss=-0.02, roi=0.05, profit_perc=-0.02,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
-)
-
-# Test 7 - 6% Positive / 1% Negative / Close 1% Positve
-# Set stop-loss at 2% ROI at 3%
-# TC7: ROI Triggers 3% Gain
-tc7 = BTContainer(data=[
-    # D  O     H     L     C     V    B  S
-    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
-    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],
-    [2, 4987, 5300, 4950, 5050, 6172, 0, 0],
-    [3, 4975, 5000, 4950, 4962, 6172, 0, 0],
-    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
-    [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
-    stop_loss=-0.02, roi=0.03, profit_perc=0.03,
-    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=2)]
-)
-
-
-# Test 8 - trailing_stop should raise so candle 3 causes a stoploss.
-# Set stop-loss at 10%, ROI at 10% (should not apply)
-# TC8: Trailing stoploss - stoploss should be adjusted candle 2
-tc8 = BTContainer(data=[
-    # D   O     H     L    C     V    B  S
-    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5050, 4950, 5000, 6172, 0, 0],
-    [2, 5000, 5250, 4750, 4850, 6172, 0, 0],
-    [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
-    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
-    stop_loss=-0.10, roi=0.10, profit_perc=-0.055, trailing_stop=True,
-    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
-)
-
-
-# Test 9 - trailing_stop should raise - high and low in same candle.
-# Candle Data for test 9
-# Set stop-loss at 10%, ROI at 10% (should not apply)
-# TC9: Trailing stoploss - stoploss should be adjusted candle 3
-tc9 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
-    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5050, 4950, 5000, 6172, 0, 0],
-    [2, 5000, 5050, 4950, 5000, 6172, 0, 0],
-    [3, 5000, 5200, 4550, 4850, 6172, 0, 0],
-    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
-    stop_loss=-0.10, roi=0.10, profit_perc=-0.064, trailing_stop=True,
-    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
-)
-
-# Test 10 - trailing_stop should raise so candle 3 causes a stoploss
-# without applying trailing_stop_positive since stoploss_offset is at 10%.
-# Set stop-loss at 10%, ROI at 10% (should not apply)
-# TC10: Trailing stoploss - stoploss should be adjusted candle 2
-tc10 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
-    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5050, 4950, 5100, 6172, 0, 0],
-    [2, 5100, 5251, 5100, 5100, 6172, 0, 0],
-    [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
-    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
-    stop_loss=-0.10, roi=0.10, profit_perc=-0.1, trailing_stop=True,
-    trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.10,
-    trailing_stop_positive=0.03,
-    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=4)]
-)
-
-# Test 11 - trailing_stop should raise so candle 3 causes a stoploss
-# applying a positive trailing stop of 3% since stop_positive_offset is reached.
-# Set stop-loss at 10%, ROI at 10% (should not apply)
-# TC11: Trailing stoploss - stoploss should be adjusted candle 2,
-tc11 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
-    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5050, 4950, 5100, 6172, 0, 0],
-    [2, 5100, 5251, 5100, 5100, 6172, 0, 0],
-    [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
-    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
-    stop_loss=-0.10, roi=0.10, profit_perc=0.019, trailing_stop=True,
-    trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
-    trailing_stop_positive=0.03,
-    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
-)
-
-# Test 12 - trailing_stop should raise in candle 2 and cause a stoploss in the same candle
-# applying a positive trailing stop of 3% since stop_positive_offset is reached.
-# Set stop-loss at 10%, ROI at 10% (should not apply)
-# TC12: Trailing stoploss - stoploss should be adjusted candle 2,
-tc12 = BTContainer(data=[
-    # D   O     H     L     C    V    B  S
-    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
-    [1, 5000, 5050, 4950, 5100, 6172, 0, 0],
-    [2, 5100, 5251, 4650, 5100, 6172, 0, 0],
-    [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
-    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
-    stop_loss=-0.10, roi=0.10, profit_perc=0.019, trailing_stop=True,
-    trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
-    trailing_stop_positive=0.03,
-    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=2)]
-)
-
-TESTS = [
-    tc0,
-    tc1,
-    tc2,
-    tc3,
-    tc4,
-    tc5,
-    tc6,
-    tc7,
-    tc8,
-    tc9,
-    tc10,
-    tc11,
-    tc12,
-]
-
-
-@pytest.mark.parametrize("data", TESTS)
-def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
-    """
-    run functional tests
-    """
-    default_conf["stoploss"] = data.stop_loss
-    default_conf["minimal_roi"] = {"0": data.roi}
-    default_conf["ticker_interval"] = tests_ticker_interval
-    default_conf["trailing_stop"] = data.trailing_stop
-    default_conf["trailing_only_offset_is_reached"] = data.trailing_only_offset_is_reached
-    # Only add this to configuration If it's necessary
-    if data.trailing_stop_positive:
-        default_conf["trailing_stop_positive"] = data.trailing_stop_positive
-    default_conf["trailing_stop_positive_offset"] = data.trailing_stop_positive_offset
-    default_conf["experimental"] = {"use_sell_signal": data.use_sell_signal}
-
-    mocker.patch("freqtrade.exchange.Exchange.get_fee", MagicMock(return_value=0.0))
-    patch_exchange(mocker)
-    frame = _build_backtest_dataframe(data.data)
-    backtesting = Backtesting(default_conf)
-    backtesting.advise_buy = lambda a, m: frame
-    backtesting.advise_sell = lambda a, m: frame
-    caplog.set_level(logging.DEBUG)
-
-    pair = "UNITTEST/BTC"
-    # Dummy data as we mock the analyze functions
-    data_processed = {pair: DataFrame()}
-    min_date, max_date = get_timeframe({pair: frame})
-    results = backtesting.backtest(
-        {
-            'stake_amount': default_conf['stake_amount'],
-            'processed': data_processed,
-            'max_open_trades': 10,
-            'start_date': min_date,
-            'end_date': max_date,
-        }
-    )
-    print(results.T)
-
-    assert len(results) == len(data.trades)
-    assert round(results["profit_percent"].sum(), 3) == round(data.profit_perc, 3)
-
-    for c, trade in enumerate(data.trades):
-        res = results.iloc[c]
-        assert res.sell_reason == trade.sell_reason
-        assert res.open_time == _get_frame_time_from_offset(trade.open_tick)
-        assert res.close_time == _get_frame_time_from_offset(trade.close_tick)
diff --git a/freqtrade/tests/optimize/test_backtesting.py b/freqtrade/tests/optimize/test_backtesting.py
deleted file mode 100644
index 9304871a8..000000000
--- a/freqtrade/tests/optimize/test_backtesting.py
+++ /dev/null
@@ -1,917 +0,0 @@
-# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
-
-import math
-import random
-from unittest.mock import MagicMock
-
-import numpy as np
-import pandas as pd
-import pytest
-from arrow import Arrow
-
-from freqtrade import DependencyException, constants
-from freqtrade.configuration import TimeRange
-from freqtrade.data import history
-from freqtrade.data.btanalysis import evaluate_result_multi
-from freqtrade.data.converter import parse_ticker_dataframe
-from freqtrade.data.dataprovider import DataProvider
-from freqtrade.data.history import get_timeframe
-from freqtrade.optimize import setup_configuration, start_backtesting
-from freqtrade.optimize.backtesting import Backtesting
-from freqtrade.state import RunMode
-from freqtrade.strategy.default_strategy import DefaultStrategy
-from freqtrade.strategy.interface import SellType
-from freqtrade.tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
-                                      patched_configuration_load_config_file)
-
-
-def trim_dictlist(dict_list, num):
-    new = {}
-    for pair, pair_data in dict_list.items():
-        new[pair] = pair_data[num:].reset_index()
-    return new
-
-
-def load_data_test(what):
-    timerange = TimeRange(None, 'line', 0, -101)
-    pair = history.load_tickerdata_file(None, ticker_interval='1m',
-                                        pair='UNITTEST/BTC', timerange=timerange)
-    datalen = len(pair)
-
-    base = 0.001
-    if what == 'raise':
-        data = [
-            [
-                pair[x][0],  # Keep old dates
-                x * base,  # But replace O,H,L,C
-                x * base + 0.0001,
-                x * base - 0.0001,
-                x * base,
-                pair[x][5],  # Keep old volume
-            ] for x in range(0, datalen)
-        ]
-    if what == 'lower':
-        data = [
-            [
-                pair[x][0],  # Keep old dates
-                1 - x * base,  # But replace O,H,L,C
-                1 - x * base + 0.0001,
-                1 - x * base - 0.0001,
-                1 - x * base,
-                pair[x][5]  # Keep old volume
-            ] for x in range(0, datalen)
-        ]
-    if what == 'sine':
-        hz = 0.1  # frequency
-        data = [
-            [
-                pair[x][0],  # Keep old dates
-                math.sin(x * hz) / 1000 + base,  # But replace O,H,L,C
-                math.sin(x * hz) / 1000 + base + 0.0001,
-                math.sin(x * hz) / 1000 + base - 0.0001,
-                math.sin(x * hz) / 1000 + base,
-                pair[x][5]  # Keep old volume
-            ] for x in range(0, datalen)
-        ]
-    return {'UNITTEST/BTC': parse_ticker_dataframe(data, '1m', pair="UNITTEST/BTC",
-                                                   fill_missing=True)}
-
-
-def simple_backtest(config, contour, num_results, mocker) -> None:
-    patch_exchange(mocker)
-    config['ticker_interval'] = '1m'
-    backtesting = Backtesting(config)
-
-    data = load_data_test(contour)
-    processed = backtesting.strategy.tickerdata_to_dataframe(data)
-    min_date, max_date = get_timeframe(processed)
-    assert isinstance(processed, dict)
-    results = backtesting.backtest(
-        {
-            'stake_amount': config['stake_amount'],
-            'processed': processed,
-            'max_open_trades': 1,
-            'position_stacking': False,
-            'start_date': min_date,
-            'end_date': max_date,
-        }
-    )
-    # results :: <class 'pandas.core.frame.DataFrame'>
-    assert len(results) == num_results
-
-
-def mocked_load_data(datadir, pairs=[], ticker_interval='0m', refresh_pairs=False,
-                     timerange=None, exchange=None, live=False):
-    tickerdata = history.load_tickerdata_file(datadir, 'UNITTEST/BTC', '1m', timerange=timerange)
-    pairdata = {'UNITTEST/BTC': parse_ticker_dataframe(tickerdata, '1m', pair="UNITTEST/BTC",
-                                                       fill_missing=True)}
-    return pairdata
-
-
-# use for mock ccxt.fetch_ohlvc'
-def _load_pair_as_ticks(pair, tickfreq):
-    ticks = history.load_tickerdata_file(None, ticker_interval=tickfreq, pair=pair)
-    ticks = ticks[-201:]
-    return ticks
-
-
-# FIX: fixturize this?
-def _make_backtest_conf(mocker, conf=None, pair='UNITTEST/BTC', record=None):
-    data = history.load_data(datadir=None, ticker_interval='1m', pairs=[pair])
-    data = trim_dictlist(data, -201)
-    patch_exchange(mocker)
-    backtesting = Backtesting(conf)
-    processed = backtesting.strategy.tickerdata_to_dataframe(data)
-    min_date, max_date = get_timeframe(processed)
-    return {
-        'stake_amount': conf['stake_amount'],
-        'processed': processed,
-        'max_open_trades': 10,
-        'position_stacking': False,
-        'record': record,
-        'start_date': min_date,
-        'end_date': max_date,
-    }
-
-
-def _trend(signals, buy_value, sell_value):
-    n = len(signals['low'])
-    buy = np.zeros(n)
-    sell = np.zeros(n)
-    for i in range(0, len(signals['buy'])):
-        if random.random() > 0.5:  # Both buy and sell signals at same timeframe
-            buy[i] = buy_value
-            sell[i] = sell_value
-    signals['buy'] = buy
-    signals['sell'] = sell
-    return signals
-
-
-def _trend_alternate(dataframe=None, metadata=None):
-    signals = dataframe
-    low = signals['low']
-    n = len(low)
-    buy = np.zeros(n)
-    sell = np.zeros(n)
-    for i in range(0, len(buy)):
-        if i % 2 == 0:
-            buy[i] = 1
-        else:
-            sell[i] = 1
-    signals['buy'] = buy
-    signals['sell'] = sell
-    return dataframe
-
-
-# Unit tests
-def test_setup_configuration_without_arguments(mocker, default_conf, caplog) -> None:
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    args = [
-        '--config', 'config.json',
-        '--strategy', 'DefaultStrategy',
-        'backtesting'
-    ]
-
-    config = setup_configuration(get_args(args), RunMode.BACKTEST)
-    assert 'max_open_trades' in config
-    assert 'stake_currency' in config
-    assert 'stake_amount' in config
-    assert 'exchange' in config
-    assert 'pair_whitelist' in config['exchange']
-    assert 'datadir' in config
-    assert log_has(
-        'Using data directory: {} ...'.format(config['datadir']),
-        caplog.record_tuples
-    )
-    assert 'ticker_interval' in config
-    assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog.record_tuples)
-
-    assert 'live' not in config
-    assert not log_has('Parameter -l/--live detected ...', caplog.record_tuples)
-
-    assert 'position_stacking' not in config
-    assert not log_has('Parameter --enable-position-stacking detected ...', caplog.record_tuples)
-
-    assert 'refresh_pairs' not in config
-    assert not log_has('Parameter -r/--refresh-pairs-cached detected ...', caplog.record_tuples)
-
-    assert 'timerange' not in config
-    assert 'export' not in config
-    assert 'runmode' in config
-    assert config['runmode'] == RunMode.BACKTEST
-
-
-def test_setup_bt_configuration_with_arguments(mocker, default_conf, caplog) -> None:
-    patched_configuration_load_config_file(mocker, default_conf)
-    mocker.patch(
-        'freqtrade.configuration.configuration.create_datadir',
-        lambda c, x: x
-    )
-
-    args = [
-        '--config', 'config.json',
-        '--strategy', 'DefaultStrategy',
-        '--datadir', '/foo/bar',
-        'backtesting',
-        '--ticker-interval', '1m',
-        '--live',
-        '--enable-position-stacking',
-        '--disable-max-market-positions',
-        '--refresh-pairs-cached',
-        '--timerange', ':100',
-        '--export', '/bar/foo',
-        '--export-filename', 'foo_bar.json'
-    ]
-
-    config = setup_configuration(get_args(args), RunMode.BACKTEST)
-    assert 'max_open_trades' in config
-    assert 'stake_currency' in config
-    assert 'stake_amount' in config
-    assert 'exchange' in config
-    assert 'pair_whitelist' in config['exchange']
-    assert 'datadir' in config
-    assert config['runmode'] == RunMode.BACKTEST
-
-    assert log_has(
-        'Using data directory: {} ...'.format(config['datadir']),
-        caplog.record_tuples
-    )
-    assert 'ticker_interval' in config
-    assert log_has('Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
-                   caplog.record_tuples)
-
-    assert 'live' in config
-    assert log_has('Parameter -l/--live detected ...', caplog.record_tuples)
-
-    assert 'position_stacking' in config
-    assert log_has('Parameter --enable-position-stacking detected ...', caplog.record_tuples)
-
-    assert 'use_max_market_positions' in config
-    assert log_has('Parameter --disable-max-market-positions detected ...', caplog.record_tuples)
-    assert log_has('max_open_trades set to unlimited ...', caplog.record_tuples)
-
-    assert 'refresh_pairs' in config
-    assert log_has('Parameter -r/--refresh-pairs-cached detected ...', caplog.record_tuples)
-
-    assert 'timerange' in config
-    assert log_has(
-        'Parameter --timerange detected: {} ...'.format(config['timerange']),
-        caplog.record_tuples
-    )
-
-    assert 'export' in config
-    assert log_has(
-        'Parameter --export detected: {} ...'.format(config['export']),
-        caplog.record_tuples
-    )
-    assert 'exportfilename' in config
-    assert log_has(
-        'Storing backtest results to {} ...'.format(config['exportfilename']),
-        caplog.record_tuples
-    )
-
-
-def test_setup_configuration_unlimited_stake_amount(mocker, default_conf, caplog) -> None:
-    default_conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
-
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    args = [
-        '--config', 'config.json',
-        '--strategy', 'DefaultStrategy',
-        'backtesting'
-    ]
-
-    with pytest.raises(DependencyException, match=r'.*stake amount.*'):
-        setup_configuration(get_args(args), RunMode.BACKTEST)
-
-
-def test_start(mocker, fee, default_conf, caplog) -> None:
-    start_mock = MagicMock()
-    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.optimize.backtesting.Backtesting.start', start_mock)
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    args = [
-        '--config', 'config.json',
-        '--strategy', 'DefaultStrategy',
-        'backtesting'
-    ]
-    args = get_args(args)
-    start_backtesting(args)
-    assert log_has(
-        'Starting freqtrade in Backtesting mode',
-        caplog.record_tuples
-    )
-    assert start_mock.call_count == 1
-
-
-ORDER_TYPES = [
-    {
-        'buy': 'limit',
-        'sell': 'limit',
-        'stoploss': 'limit',
-        'stoploss_on_exchange': False
-    },
-    {
-        'buy': 'limit',
-        'sell': 'limit',
-        'stoploss': 'limit',
-        'stoploss_on_exchange': True
-    }]
-
-
-@pytest.mark.parametrize("order_types", ORDER_TYPES)
-def test_backtesting_init(mocker, default_conf, order_types) -> None:
-    """
-    Check that stoploss_on_exchange is set to False while backtesting
-    since backtesting assumes a perfect stoploss anyway.
-    """
-    default_conf["order_types"] = order_types
-    patch_exchange(mocker)
-    get_fee = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
-    backtesting = Backtesting(default_conf)
-    assert backtesting.config == default_conf
-    assert backtesting.ticker_interval == '5m'
-    assert callable(backtesting.strategy.tickerdata_to_dataframe)
-    assert callable(backtesting.advise_buy)
-    assert callable(backtesting.advise_sell)
-    assert isinstance(backtesting.strategy.dp, DataProvider)
-    get_fee.assert_called()
-    assert backtesting.fee == 0.5
-    assert not backtesting.strategy.order_types["stoploss_on_exchange"]
-
-
-def test_tickerdata_to_dataframe_bt(default_conf, mocker) -> None:
-    patch_exchange(mocker)
-    timerange = TimeRange(None, 'line', 0, -100)
-    tick = history.load_tickerdata_file(None, 'UNITTEST/BTC', '1m', timerange=timerange)
-    tickerlist = {'UNITTEST/BTC': parse_ticker_dataframe(tick, '1m', pair="UNITTEST/BTC",
-                                                         fill_missing=True)}
-
-    backtesting = Backtesting(default_conf)
-    data = backtesting.strategy.tickerdata_to_dataframe(tickerlist)
-    assert len(data['UNITTEST/BTC']) == 102
-
-    # Load strategy to compare the result between Backtesting function and strategy are the same
-    strategy = DefaultStrategy(default_conf)
-    data2 = strategy.tickerdata_to_dataframe(tickerlist)
-    assert data['UNITTEST/BTC'].equals(data2['UNITTEST/BTC'])
-
-
-def test_generate_text_table(default_conf, mocker):
-    patch_exchange(mocker)
-    default_conf['max_open_trades'] = 2
-    backtesting = Backtesting(default_conf)
-
-    results = pd.DataFrame(
-        {
-            'pair': ['ETH/BTC', 'ETH/BTC'],
-            'profit_percent': [0.1, 0.2],
-            'profit_abs': [0.2, 0.4],
-            'trade_duration': [10, 30],
-            'profit': [2, 0],
-            'loss': [0, 0]
-        }
-    )
-
-    result_str = (
-        '| pair    |   buy count |   avg profit % |   cum profit % |   '
-        'tot profit BTC |   tot profit % | avg duration   |   profit |   loss |\n'
-        '|:--------|------------:|---------------:|---------------:|'
-        '-----------------:|---------------:|:---------------|---------:|-------:|\n'
-        '| ETH/BTC |           2 |          15.00 |          30.00 |       '
-        '0.60000000 |          15.00 | 0:20:00        |        2 |      0 |\n'
-        '| TOTAL   |           2 |          15.00 |          30.00 |       '
-        '0.60000000 |          15.00 | 0:20:00        |        2 |      0 |'
-    )
-    assert backtesting._generate_text_table(data={'ETH/BTC': {}}, results=results) == result_str
-
-
-def test_generate_text_table_sell_reason(default_conf, mocker):
-    patch_exchange(mocker)
-    backtesting = Backtesting(default_conf)
-
-    results = pd.DataFrame(
-        {
-            'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
-            'profit_percent': [0.1, 0.2, 0.3],
-            'profit_abs': [0.2, 0.4, 0.5],
-            'trade_duration': [10, 30, 10],
-            'profit': [2, 0, 0],
-            'loss': [0, 0, 1],
-            'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
-        }
-    )
-
-    result_str = (
-        '| Sell Reason   |   Count |\n'
-        '|:--------------|--------:|\n'
-        '| roi           |       2 |\n'
-        '| stop_loss     |       1 |'
-    )
-    assert backtesting._generate_text_table_sell_reason(
-        data={'ETH/BTC': {}}, results=results) == result_str
-
-
-def test_generate_text_table_strategyn(default_conf, mocker):
-    """
-    Test Backtesting.generate_text_table_sell_reason() method
-    """
-    patch_exchange(mocker)
-    default_conf['max_open_trades'] = 2
-    backtesting = Backtesting(default_conf)
-    results = {}
-    results['ETH/BTC'] = pd.DataFrame(
-        {
-            'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
-            'profit_percent': [0.1, 0.2, 0.3],
-            'profit_abs': [0.2, 0.4, 0.5],
-            'trade_duration': [10, 30, 10],
-            'profit': [2, 0, 0],
-            'loss': [0, 0, 1],
-            'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
-        }
-    )
-    results['LTC/BTC'] = pd.DataFrame(
-        {
-            'pair': ['LTC/BTC', 'LTC/BTC', 'LTC/BTC'],
-            'profit_percent': [0.4, 0.2, 0.3],
-            'profit_abs': [0.4, 0.4, 0.5],
-            'trade_duration': [15, 30, 15],
-            'profit': [4, 1, 0],
-            'loss': [0, 0, 1],
-            'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
-        }
-    )
-
-    result_str = (
-        '| Strategy   |   buy count |   avg profit % |   cum profit % '
-        '|   tot profit BTC |   tot profit % | avg duration   |   profit |   loss |\n'
-        '|:-----------|------------:|---------------:|---------------:'
-        '|-----------------:|---------------:|:---------------|---------:|-------:|\n'
-        '| ETH/BTC    |           3 |          20.00 |          60.00 '
-        '|       1.10000000 |          30.00 | 0:17:00        |        3 |      0 |\n'
-        '| LTC/BTC    |           3 |          30.00 |          90.00 '
-        '|       1.30000000 |          45.00 | 0:20:00        |        3 |      0 |'
-    )
-    print(backtesting._generate_text_table_strategy(all_results=results))
-    assert backtesting._generate_text_table_strategy(all_results=results) == result_str
-
-
-def test_backtesting_start(default_conf, mocker, caplog) -> None:
-    def get_timeframe(input1):
-        return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59)
-
-    mocker.patch('freqtrade.data.history.load_data', mocked_load_data)
-    mocker.patch('freqtrade.data.history.get_timeframe', get_timeframe)
-    mocker.patch('freqtrade.exchange.Exchange.refresh_latest_ohlcv', MagicMock())
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.optimize.backtesting.Backtesting',
-        backtest=MagicMock(),
-        _generate_text_table=MagicMock(return_value='1'),
-    )
-
-    default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
-    default_conf['ticker_interval'] = '1m'
-    default_conf['live'] = False
-    default_conf['datadir'] = None
-    default_conf['export'] = None
-    default_conf['timerange'] = '-100'
-
-    backtesting = Backtesting(default_conf)
-    backtesting.start()
-    # check the logs, that will contain the backtest result
-    exists = [
-        'Using stake_currency: BTC ...',
-        'Using stake_amount: 0.001 ...',
-        'Backtesting with data from 2017-11-14T21:17:00+00:00 '
-        'up to 2017-11-14T22:59:00+00:00 (0 days)..'
-    ]
-    for line in exists:
-        assert log_has(line, caplog.record_tuples)
-
-
-def test_backtesting_start_no_data(default_conf, mocker, caplog) -> None:
-    def get_timeframe(input1):
-        return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59)
-
-    mocker.patch('freqtrade.data.history.load_data', MagicMock(return_value={}))
-    mocker.patch('freqtrade.data.history.get_timeframe', get_timeframe)
-    mocker.patch('freqtrade.exchange.Exchange.refresh_latest_ohlcv', MagicMock())
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.optimize.backtesting.Backtesting',
-        backtest=MagicMock(),
-        _generate_text_table=MagicMock(return_value='1'),
-    )
-
-    default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
-    default_conf['ticker_interval'] = "1m"
-    default_conf['live'] = False
-    default_conf['datadir'] = None
-    default_conf['export'] = None
-    default_conf['timerange'] = '20180101-20180102'
-
-    backtesting = Backtesting(default_conf)
-    backtesting.start()
-    # check the logs, that will contain the backtest result
-
-    assert log_has('No data found. Terminating.', caplog.record_tuples)
-
-
-def test_backtest(default_conf, fee, mocker) -> None:
-    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
-    patch_exchange(mocker)
-    backtesting = Backtesting(default_conf)
-    pair = 'UNITTEST/BTC'
-    timerange = TimeRange(None, 'line', 0, -201)
-    data = history.load_data(datadir=None, ticker_interval='5m', pairs=['UNITTEST/BTC'],
-                             timerange=timerange)
-    data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
-    min_date, max_date = get_timeframe(data_processed)
-    results = backtesting.backtest(
-        {
-            'stake_amount': default_conf['stake_amount'],
-            'processed': data_processed,
-            'max_open_trades': 10,
-            'position_stacking': False,
-            'start_date': min_date,
-            'end_date': max_date,
-        }
-    )
-    assert not results.empty
-    assert len(results) == 2
-
-    expected = pd.DataFrame(
-        {'pair': [pair, pair],
-         'profit_percent': [0.0, 0.0],
-         'profit_abs': [0.0, 0.0],
-         'open_time': pd.to_datetime([Arrow(2018, 1, 29, 18, 40, 0).datetime,
-                                      Arrow(2018, 1, 30, 3, 30, 0).datetime], utc=True
-                                     ),
-         'close_time': pd.to_datetime([Arrow(2018, 1, 29, 22, 35, 0).datetime,
-                                       Arrow(2018, 1, 30, 4, 10, 0).datetime], utc=True),
-         'open_index': [78, 184],
-         'close_index': [125, 192],
-         'trade_duration': [235, 40],
-         'open_at_end': [False, False],
-         'open_rate': [0.104445, 0.10302485],
-         'close_rate': [0.104969, 0.103541],
-         'sell_reason': [SellType.ROI, SellType.ROI]
-         })
-    pd.testing.assert_frame_equal(results, expected)
-    data_pair = data_processed[pair]
-    for _, t in results.iterrows():
-        ln = data_pair.loc[data_pair["date"] == t["open_time"]]
-        # Check open trade rate alignes to open rate
-        assert ln is not None
-        assert round(ln.iloc[0]["open"], 6) == round(t["open_rate"], 6)
-        # check close trade rate alignes to close rate or is between high and low
-        ln = data_pair.loc[data_pair["date"] == t["close_time"]]
-        assert (round(ln.iloc[0]["open"], 6) == round(t["close_rate"], 6) or
-                round(ln.iloc[0]["low"], 6) < round(
-                t["close_rate"], 6) < round(ln.iloc[0]["high"], 6))
-
-
-def test_backtest_1min_ticker_interval(default_conf, fee, mocker) -> None:
-    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
-    patch_exchange(mocker)
-    backtesting = Backtesting(default_conf)
-
-    # Run a backtesting for an exiting 1min ticker_interval
-    timerange = TimeRange(None, 'line', 0, -200)
-    data = history.load_data(datadir=None, ticker_interval='1m', pairs=['UNITTEST/BTC'],
-                             timerange=timerange)
-    processed = backtesting.strategy.tickerdata_to_dataframe(data)
-    min_date, max_date = get_timeframe(processed)
-    results = backtesting.backtest(
-        {
-            'stake_amount': default_conf['stake_amount'],
-            'processed': processed,
-            'max_open_trades': 1,
-            'position_stacking': False,
-            'start_date': min_date,
-            'end_date': max_date,
-        }
-    )
-    assert not results.empty
-    assert len(results) == 1
-
-
-def test_processed(default_conf, mocker) -> None:
-    patch_exchange(mocker)
-    backtesting = Backtesting(default_conf)
-
-    dict_of_tickerrows = load_data_test('raise')
-    dataframes = backtesting.strategy.tickerdata_to_dataframe(dict_of_tickerrows)
-    dataframe = dataframes['UNITTEST/BTC']
-    cols = dataframe.columns
-    # assert the dataframe got some of the indicator columns
-    for col in ['close', 'high', 'low', 'open', 'date',
-                'ema50', 'ao', 'macd', 'plus_dm']:
-        assert col in cols
-
-
-def test_backtest_pricecontours(default_conf, fee, mocker) -> None:
-    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
-    tests = [['raise', 19], ['lower', 0], ['sine', 18]]
-    # We need to enable sell-signal - otherwise it sells on ROI!!
-    default_conf['experimental'] = {"use_sell_signal": True}
-
-    for [contour, numres] in tests:
-        simple_backtest(default_conf, contour, numres, mocker)
-
-
-def test_backtest_clash_buy_sell(mocker, default_conf):
-    # Override the default buy trend function in our default_strategy
-    def fun(dataframe=None, pair=None):
-        buy_value = 1
-        sell_value = 1
-        return _trend(dataframe, buy_value, sell_value)
-
-    backtest_conf = _make_backtest_conf(mocker, conf=default_conf)
-    backtesting = Backtesting(default_conf)
-    backtesting.advise_buy = fun  # Override
-    backtesting.advise_sell = fun  # Override
-    results = backtesting.backtest(backtest_conf)
-    assert results.empty
-
-
-def test_backtest_only_sell(mocker, default_conf):
-    # Override the default buy trend function in our default_strategy
-    def fun(dataframe=None, pair=None):
-        buy_value = 0
-        sell_value = 1
-        return _trend(dataframe, buy_value, sell_value)
-
-    backtest_conf = _make_backtest_conf(mocker, conf=default_conf)
-    backtesting = Backtesting(default_conf)
-    backtesting.advise_buy = fun  # Override
-    backtesting.advise_sell = fun  # Override
-    results = backtesting.backtest(backtest_conf)
-    assert results.empty
-
-
-def test_backtest_alternate_buy_sell(default_conf, fee, mocker):
-    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
-    mocker.patch('freqtrade.optimize.backtesting.file_dump_json', MagicMock())
-    backtest_conf = _make_backtest_conf(mocker, conf=default_conf, pair='UNITTEST/BTC')
-    # We need to enable sell-signal - otherwise it sells on ROI!!
-    default_conf['experimental'] = {"use_sell_signal": True}
-    default_conf['ticker_interval'] = '1m'
-    backtesting = Backtesting(default_conf)
-    backtesting.advise_buy = _trend_alternate  # Override
-    backtesting.advise_sell = _trend_alternate  # Override
-    results = backtesting.backtest(backtest_conf)
-    backtesting._store_backtest_result("test_.json", results)
-    # 200 candles in backtest data
-    # won't buy on first (shifted by 1)
-    # 100 buys signals
-    assert len(results) == 100
-    # One trade was force-closed at the end
-    assert len(results.loc[results.open_at_end]) == 0
-
-
-@pytest.mark.parametrize("pair", ['ADA/BTC', 'LTC/BTC'])
-@pytest.mark.parametrize("tres", [0, 20, 30])
-def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair):
-
-    def _trend_alternate_hold(dataframe=None, metadata=None):
-        """
-        Buy every xth candle - sell every other xth -2 (hold on to pairs a bit)
-        """
-        if metadata['pair'] in('ETH/BTC', 'LTC/BTC'):
-            multi = 20
-        else:
-            multi = 18
-        dataframe['buy'] = np.where(dataframe.index % multi == 0, 1, 0)
-        dataframe['sell'] = np.where((dataframe.index + multi - 2) % multi == 0, 1, 0)
-        return dataframe
-
-    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
-    patch_exchange(mocker)
-
-    pairs = ['ADA/BTC', 'DASH/BTC', 'ETH/BTC', 'LTC/BTC', 'NXT/BTC']
-    data = history.load_data(datadir=None, ticker_interval='5m', pairs=pairs)
-    # Only use 500 lines to increase performance
-    data = trim_dictlist(data, -500)
-
-    # Remove data for one pair from the beginning of the data
-    data[pair] = data[pair][tres:].reset_index()
-    # We need to enable sell-signal - otherwise it sells on ROI!!
-    default_conf['experimental'] = {"use_sell_signal": True}
-    default_conf['ticker_interval'] = '5m'
-
-    backtesting = Backtesting(default_conf)
-    backtesting.advise_buy = _trend_alternate_hold  # Override
-    backtesting.advise_sell = _trend_alternate_hold  # Override
-
-    data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
-    min_date, max_date = get_timeframe(data_processed)
-    backtest_conf = {
-        'stake_amount': default_conf['stake_amount'],
-        'processed': data_processed,
-        'max_open_trades': 3,
-        'position_stacking': False,
-        'start_date': min_date,
-        'end_date': max_date,
-    }
-
-    results = backtesting.backtest(backtest_conf)
-
-    # Make sure we have parallel trades
-    assert len(evaluate_result_multi(results, '5min', 2)) > 0
-    # make sure we don't have trades with more than configured max_open_trades
-    assert len(evaluate_result_multi(results, '5min', 3)) == 0
-
-    backtest_conf = {
-        'stake_amount': default_conf['stake_amount'],
-        'processed': data_processed,
-        'max_open_trades': 1,
-        'position_stacking': False,
-        'start_date': min_date,
-        'end_date': max_date,
-    }
-    results = backtesting.backtest(backtest_conf)
-    assert len(evaluate_result_multi(results, '5min', 1)) == 0
-
-
-def test_backtest_record(default_conf, fee, mocker):
-    names = []
-    records = []
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
-    mocker.patch(
-        'freqtrade.optimize.backtesting.file_dump_json',
-        new=lambda n, r: (names.append(n), records.append(r))
-    )
-
-    backtesting = Backtesting(default_conf)
-    results = pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
-                                     "UNITTEST/BTC", "UNITTEST/BTC"],
-                            "profit_percent": [0.003312, 0.010801, 0.013803, 0.002780],
-                            "profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
-                            "open_time": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
-                                          Arrow(2017, 11, 14, 21, 36, 00).datetime,
-                                          Arrow(2017, 11, 14, 22, 12, 00).datetime,
-                                          Arrow(2017, 11, 14, 22, 44, 00).datetime],
-                            "close_time": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
-                                           Arrow(2017, 11, 14, 22, 10, 00).datetime,
-                                           Arrow(2017, 11, 14, 22, 43, 00).datetime,
-                                           Arrow(2017, 11, 14, 22, 58, 00).datetime],
-                            "open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
-                            "close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
-                            "open_index": [1, 119, 153, 185],
-                            "close_index": [118, 151, 184, 199],
-                            "trade_duration": [123, 34, 31, 14],
-                            "open_at_end": [False, False, False, True],
-                            "sell_reason": [SellType.ROI, SellType.STOP_LOSS,
-                                            SellType.ROI, SellType.FORCE_SELL]
-                            })
-    backtesting._store_backtest_result("backtest-result.json", results)
-    assert len(results) == 4
-    # Assert file_dump_json was only called once
-    assert names == ['backtest-result.json']
-    records = records[0]
-    # Ensure records are of correct type
-    assert len(records) == 4
-
-    # reset test to test with strategy name
-    names = []
-    records = []
-    backtesting._store_backtest_result("backtest-result.json", results, "DefStrat")
-    assert len(results) == 4
-    # Assert file_dump_json was only called once
-    assert names == ['backtest-result-DefStrat.json']
-    records = records[0]
-    # Ensure records are of correct type
-    assert len(records) == 4
-
-    # ('UNITTEST/BTC', 0.00331158, '1510684320', '1510691700', 0, 117)
-    # Below follows just a typecheck of the schema/type of trade-records
-    oix = None
-    for (pair, profit, date_buy, date_sell, buy_index, dur,
-         openr, closer, open_at_end, sell_reason) in records:
-        assert pair == 'UNITTEST/BTC'
-        assert isinstance(profit, float)
-        # FIX: buy/sell should be converted to ints
-        assert isinstance(date_buy, float)
-        assert isinstance(date_sell, float)
-        assert isinstance(openr, float)
-        assert isinstance(closer, float)
-        assert isinstance(open_at_end, bool)
-        assert isinstance(sell_reason, str)
-        isinstance(buy_index, pd._libs.tslib.Timestamp)
-        if oix:
-            assert buy_index > oix
-        oix = buy_index
-        assert dur > 0
-
-
-def test_backtest_start_live(default_conf, mocker, caplog):
-    default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
-
-    async def load_pairs(pair, timeframe, since):
-        return _load_pair_as_ticks(pair, timeframe)
-
-    api_mock = MagicMock()
-    api_mock.fetch_ohlcv = load_pairs
-
-    patch_exchange(mocker, api_mock)
-    mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', MagicMock())
-    mocker.patch('freqtrade.optimize.backtesting.Backtesting._generate_text_table', MagicMock())
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    args = [
-        '--config', 'config.json',
-        '--strategy', 'DefaultStrategy',
-        '--datadir', 'freqtrade/tests/testdata',
-        'backtesting',
-        '--ticker-interval', '1m',
-        '--live',
-        '--timerange', '-100',
-        '--enable-position-stacking',
-        '--disable-max-market-positions'
-    ]
-    args = get_args(args)
-    start_backtesting(args)
-    # check the logs, that will contain the backtest result
-    exists = [
-        'Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
-        'Parameter -l/--live detected ...',
-        'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
-        'Parameter --timerange detected: -100 ...',
-        'Using data directory: freqtrade/tests/testdata ...',
-        'Using stake_currency: BTC ...',
-        'Using stake_amount: 0.001 ...',
-        'Live: Downloading data for all defined pairs ...',
-        'Backtesting with data from 2017-11-14T19:31:00+00:00 '
-        'up to 2017-11-14T22:58:00+00:00 (0 days)..',
-        'Parameter --enable-position-stacking detected ...'
-    ]
-
-    for line in exists:
-        assert log_has(line, caplog.record_tuples)
-
-
-def test_backtest_start_multi_strat(default_conf, mocker, caplog):
-    default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
-
-    async def load_pairs(pair, timeframe, since):
-        return _load_pair_as_ticks(pair, timeframe)
-    api_mock = MagicMock()
-    api_mock.fetch_ohlcv = load_pairs
-
-    patch_exchange(mocker, api_mock)
-    backtestmock = MagicMock()
-    mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
-    gen_table_mock = MagicMock()
-    mocker.patch('freqtrade.optimize.backtesting.Backtesting._generate_text_table', gen_table_mock)
-    gen_strattable_mock = MagicMock()
-    mocker.patch('freqtrade.optimize.backtesting.Backtesting._generate_text_table_strategy',
-                 gen_strattable_mock)
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    args = [
-        '--config', 'config.json',
-        '--datadir', 'freqtrade/tests/testdata',
-        'backtesting',
-        '--ticker-interval', '1m',
-        '--live',
-        '--timerange', '-100',
-        '--enable-position-stacking',
-        '--disable-max-market-positions',
-        '--strategy-list',
-        'DefaultStrategy',
-        'TestStrategy',
-    ]
-    args = get_args(args)
-    start_backtesting(args)
-    # 2 backtests, 4 tables
-    assert backtestmock.call_count == 2
-    assert gen_table_mock.call_count == 4
-    assert gen_strattable_mock.call_count == 1
-
-    # check the logs, that will contain the backtest result
-    exists = [
-        'Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
-        'Parameter -l/--live detected ...',
-        'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
-        'Parameter --timerange detected: -100 ...',
-        'Using data directory: freqtrade/tests/testdata ...',
-        'Using stake_currency: BTC ...',
-        'Using stake_amount: 0.001 ...',
-        'Live: Downloading data for all defined pairs ...',
-        'Backtesting with data from 2017-11-14T19:31:00+00:00 '
-        'up to 2017-11-14T22:58:00+00:00 (0 days)..',
-        'Parameter --enable-position-stacking detected ...',
-        'Running backtesting for Strategy DefaultStrategy',
-        'Running backtesting for Strategy TestStrategy',
-    ]
-
-    for line in exists:
-        assert log_has(line, caplog.record_tuples)
diff --git a/freqtrade/tests/optimize/test_hyperopt.py b/freqtrade/tests/optimize/test_hyperopt.py
deleted file mode 100644
index a588bab64..000000000
--- a/freqtrade/tests/optimize/test_hyperopt.py
+++ /dev/null
@@ -1,610 +0,0 @@
-# pragma pylint: disable=missing-docstring,W0212,C0103
-import os
-from datetime import datetime
-from unittest.mock import MagicMock
-
-import pandas as pd
-import pytest
-from arrow import Arrow
-from filelock import Timeout
-
-from freqtrade import DependencyException
-from freqtrade.data.converter import parse_ticker_dataframe
-from freqtrade.data.history import load_tickerdata_file
-from freqtrade.optimize import setup_configuration, start_hyperopt
-from freqtrade.optimize.default_hyperopt import DefaultHyperOpts
-from freqtrade.optimize.default_hyperopt_loss import DefaultHyperOptLoss
-from freqtrade.optimize.hyperopt import (HYPEROPT_LOCKFILE, TICKERDATA_PICKLE,
-                                         Hyperopt)
-from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver, HyperOptLossResolver
-from freqtrade.state import RunMode
-from freqtrade.strategy.interface import SellType
-from freqtrade.tests.conftest import (get_args, log_has, log_has_re,
-                                      patch_exchange,
-                                      patched_configuration_load_config_file)
-
-
-@pytest.fixture(scope='function')
-def hyperopt(default_conf, mocker):
-    patch_exchange(mocker)
-    return Hyperopt(default_conf)
-
-
-@pytest.fixture(scope='function')
-def hyperopt_results():
-    return pd.DataFrame(
-        {
-            'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
-            'profit_percent': [0.1, 0.2, 0.3],
-            'profit_abs': [0.2, 0.4, 0.5],
-            'trade_duration': [10, 30, 10],
-            'profit': [2, 0, 0],
-            'loss': [0, 0, 1],
-            'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
-        }
-    )
-
-
-# Functions for recurrent object patching
-def create_trials(mocker, hyperopt) -> None:
-    """
-    When creating trials, mock the hyperopt Trials so that *by default*
-      - we don't create any pickle'd files in the filesystem
-      - we might have a pickle'd file so make sure that we return
-        false when looking for it
-    """
-    hyperopt.trials_file = os.path.join('freqtrade', 'tests', 'optimize', 'ut_trials.pickle')
-
-    mocker.patch('freqtrade.optimize.hyperopt.os.path.exists', return_value=False)
-    mocker.patch('freqtrade.optimize.hyperopt.os.path.getsize', return_value=1)
-    mocker.patch('freqtrade.optimize.hyperopt.os.remove', return_value=True)
-    mocker.patch('freqtrade.optimize.hyperopt.dump', return_value=None)
-
-    return [{'loss': 1, 'result': 'foo', 'params': {}}]
-
-
-def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, caplog) -> None:
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    args = [
-        '--config', 'config.json',
-        'hyperopt'
-    ]
-
-    config = setup_configuration(get_args(args), RunMode.HYPEROPT)
-    assert 'max_open_trades' in config
-    assert 'stake_currency' in config
-    assert 'stake_amount' in config
-    assert 'exchange' in config
-    assert 'pair_whitelist' in config['exchange']
-    assert 'datadir' in config
-    assert log_has(
-        'Using data directory: {} ...'.format(config['datadir']),
-        caplog.record_tuples
-    )
-    assert 'ticker_interval' in config
-    assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog.record_tuples)
-
-    assert 'live' not in config
-    assert not log_has('Parameter -l/--live detected ...', caplog.record_tuples)
-
-    assert 'position_stacking' not in config
-    assert not log_has('Parameter --enable-position-stacking detected ...', caplog.record_tuples)
-
-    assert 'refresh_pairs' not in config
-    assert not log_has('Parameter -r/--refresh-pairs-cached detected ...', caplog.record_tuples)
-
-    assert 'timerange' not in config
-    assert 'runmode' in config
-    assert config['runmode'] == RunMode.HYPEROPT
-
-
-def test_setup_hyperopt_configuration_with_arguments(mocker, default_conf, caplog) -> None:
-    patched_configuration_load_config_file(mocker, default_conf)
-    mocker.patch(
-        'freqtrade.configuration.configuration.create_datadir',
-        lambda c, x: x
-    )
-
-    args = [
-        '--config', 'config.json',
-        '--datadir', '/foo/bar',
-        'hyperopt',
-        '--ticker-interval', '1m',
-        '--timerange', ':100',
-        '--refresh-pairs-cached',
-        '--enable-position-stacking',
-        '--disable-max-market-positions',
-        '--epochs', '1000',
-        '--spaces', 'all',
-        '--print-all'
-    ]
-
-    config = setup_configuration(get_args(args), RunMode.HYPEROPT)
-    assert 'max_open_trades' in config
-    assert 'stake_currency' in config
-    assert 'stake_amount' in config
-    assert 'exchange' in config
-    assert 'pair_whitelist' in config['exchange']
-    assert 'datadir' in config
-    assert config['runmode'] == RunMode.HYPEROPT
-
-    assert log_has(
-        'Using data directory: {} ...'.format(config['datadir']),
-        caplog.record_tuples
-    )
-    assert 'ticker_interval' in config
-    assert log_has('Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
-                   caplog.record_tuples)
-
-    assert 'position_stacking' in config
-    assert log_has('Parameter --enable-position-stacking detected ...', caplog.record_tuples)
-
-    assert 'use_max_market_positions' in config
-    assert log_has('Parameter --disable-max-market-positions detected ...', caplog.record_tuples)
-    assert log_has('max_open_trades set to unlimited ...', caplog.record_tuples)
-
-    assert 'refresh_pairs' in config
-    assert log_has('Parameter -r/--refresh-pairs-cached detected ...', caplog.record_tuples)
-
-    assert 'timerange' in config
-    assert log_has(
-        'Parameter --timerange detected: {} ...'.format(config['timerange']),
-        caplog.record_tuples
-    )
-
-    assert 'epochs' in config
-    assert log_has('Parameter --epochs detected ... Will run Hyperopt with for 1000 epochs ...',
-                   caplog.record_tuples)
-
-    assert 'spaces' in config
-    assert log_has(
-        'Parameter -s/--spaces detected: {}'.format(config['spaces']),
-        caplog.record_tuples
-    )
-    assert 'print_all' in config
-    assert log_has('Parameter --print-all detected ...', caplog.record_tuples)
-
-
-def test_hyperoptresolver(mocker, default_conf, caplog) -> None:
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    hyperopts = DefaultHyperOpts
-    delattr(hyperopts, 'populate_buy_trend')
-    delattr(hyperopts, 'populate_sell_trend')
-    mocker.patch(
-        'freqtrade.resolvers.hyperopt_resolver.HyperOptResolver._load_hyperopt',
-        MagicMock(return_value=hyperopts)
-    )
-    x = HyperOptResolver(default_conf, ).hyperopt
-    assert not hasattr(x, 'populate_buy_trend')
-    assert not hasattr(x, 'populate_sell_trend')
-    assert log_has("Custom Hyperopt does not provide populate_sell_trend. "
-                   "Using populate_sell_trend from DefaultStrategy.", caplog.record_tuples)
-    assert log_has("Custom Hyperopt does not provide populate_buy_trend. "
-                   "Using populate_buy_trend from DefaultStrategy.", caplog.record_tuples)
-    assert hasattr(x, "ticker_interval")
-
-
-def test_hyperoptlossresolver(mocker, default_conf, caplog) -> None:
-
-    hl = DefaultHyperOptLoss
-    mocker.patch(
-        'freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver._load_hyperoptloss',
-        MagicMock(return_value=hl)
-    )
-    x = HyperOptResolver(default_conf, ).hyperopt
-    assert hasattr(x, "populate_indicators")
-    assert hasattr(x, "ticker_interval")
-
-
-def test_start(mocker, default_conf, caplog) -> None:
-    start_mock = MagicMock()
-    patched_configuration_load_config_file(mocker, default_conf)
-    mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
-    patch_exchange(mocker)
-
-    args = [
-        '--config', 'config.json',
-        'hyperopt',
-        '--epochs', '5'
-    ]
-    args = get_args(args)
-    start_hyperopt(args)
-
-    import pprint
-    pprint.pprint(caplog.record_tuples)
-
-    assert log_has(
-        'Starting freqtrade in Hyperopt mode',
-        caplog.record_tuples
-    )
-    assert start_mock.call_count == 1
-
-
-def test_start_no_data(mocker, default_conf, caplog) -> None:
-    patched_configuration_load_config_file(mocker, default_conf)
-    mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock(return_value={}))
-    mocker.patch(
-        'freqtrade.optimize.hyperopt.get_timeframe',
-        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
-    )
-
-    patch_exchange(mocker)
-
-    args = [
-        '--config', 'config.json',
-        'hyperopt',
-        '--epochs', '5'
-    ]
-    args = get_args(args)
-    start_hyperopt(args)
-
-    import pprint
-    pprint.pprint(caplog.record_tuples)
-
-    assert log_has('No data found. Terminating.', caplog.record_tuples)
-
-
-def test_start_failure(mocker, default_conf, caplog) -> None:
-    start_mock = MagicMock()
-    patched_configuration_load_config_file(mocker, default_conf)
-    mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
-    patch_exchange(mocker)
-
-    args = [
-        '--config', 'config.json',
-        '--strategy', 'TestStrategy',
-        'hyperopt',
-        '--epochs', '5'
-    ]
-    args = get_args(args)
-    with pytest.raises(DependencyException):
-        start_hyperopt(args)
-    assert log_has(
-        "Please don't use --strategy for hyperopt.",
-        caplog.record_tuples
-    )
-
-
-def test_start_filelock(mocker, default_conf, caplog) -> None:
-    start_mock = MagicMock(side_effect=Timeout(HYPEROPT_LOCKFILE))
-    patched_configuration_load_config_file(mocker, default_conf)
-    mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
-    patch_exchange(mocker)
-
-    args = [
-        '--config', 'config.json',
-        'hyperopt',
-        '--epochs', '5'
-    ]
-    args = get_args(args)
-    start_hyperopt(args)
-    assert log_has(
-        "Another running instance of freqtrade Hyperopt detected.",
-        caplog.record_tuples
-    )
-
-
-def test_loss_calculation_prefer_correct_trade_count(default_conf, hyperopt_results) -> None:
-    hl = HyperOptLossResolver(default_conf).hyperoptloss
-    correct = hl.hyperopt_loss_function(hyperopt_results, 600)
-    over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100)
-    under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100)
-    assert over > correct
-    assert under > correct
-
-
-def test_loss_calculation_prefer_shorter_trades(default_conf, hyperopt_results) -> None:
-    resultsb = hyperopt_results.copy()
-    resultsb['trade_duration'][1] = 20
-
-    hl = HyperOptLossResolver(default_conf).hyperoptloss
-    longer = hl.hyperopt_loss_function(hyperopt_results, 100)
-    shorter = hl.hyperopt_loss_function(resultsb, 100)
-    assert shorter < longer
-
-
-def test_loss_calculation_has_limited_profit(default_conf, hyperopt_results) -> None:
-    results_over = hyperopt_results.copy()
-    results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
-    results_under = hyperopt_results.copy()
-    results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
-
-    hl = HyperOptLossResolver(default_conf).hyperoptloss
-    correct = hl.hyperopt_loss_function(hyperopt_results, 600)
-    over = hl.hyperopt_loss_function(results_over, 600)
-    under = hl.hyperopt_loss_function(results_under, 600)
-    assert over < correct
-    assert under > correct
-
-
-def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
-    results_over = hyperopt_results.copy()
-    results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
-    results_under = hyperopt_results.copy()
-    results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
-
-    default_conf.update({'hyperopt_loss': 'SharpeHyperOptLoss'})
-    hl = HyperOptLossResolver(default_conf).hyperoptloss
-    correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
-                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
-    over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
-                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
-    under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
-                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
-    assert over < correct
-    assert under > correct
-
-
-def test_log_results_if_loss_improves(hyperopt, capsys) -> None:
-    hyperopt.current_best_loss = 2
-    hyperopt.log_results(
-        {
-            'loss': 1,
-            'current_tries': 1,
-            'total_tries': 2,
-            'result': 'foo.',
-            'initial_point': False
-        }
-    )
-    out, err = capsys.readouterr()
-    assert '    2/2: foo. Objective: 1.00000' in out
-
-
-def test_no_log_if_loss_does_not_improve(hyperopt, caplog) -> None:
-    hyperopt.current_best_loss = 2
-    hyperopt.log_results(
-        {
-            'loss': 3,
-        }
-    )
-    assert caplog.record_tuples == []
-
-
-def test_save_trials_saves_trials(mocker, hyperopt, caplog) -> None:
-    trials = create_trials(mocker, hyperopt)
-    mock_dump = mocker.patch('freqtrade.optimize.hyperopt.dump', return_value=None)
-    hyperopt.trials = trials
-    hyperopt.save_trials()
-
-    trials_file = os.path.join('freqtrade', 'tests', 'optimize', 'ut_trials.pickle')
-    assert log_has(
-        'Saving 1 evaluations to \'{}\''.format(trials_file),
-        caplog.record_tuples
-    )
-    mock_dump.assert_called_once()
-
-
-def test_read_trials_returns_trials_file(mocker, hyperopt, caplog) -> None:
-    trials = create_trials(mocker, hyperopt)
-    mock_load = mocker.patch('freqtrade.optimize.hyperopt.load', return_value=trials)
-    hyperopt_trial = hyperopt.read_trials()
-    trials_file = os.path.join('freqtrade', 'tests', 'optimize', 'ut_trials.pickle')
-    assert log_has(
-        'Reading Trials from \'{}\''.format(trials_file),
-        caplog.record_tuples
-    )
-    assert hyperopt_trial == trials
-    mock_load.assert_called_once()
-
-
-def test_roi_table_generation(hyperopt) -> None:
-    params = {
-        'roi_t1': 5,
-        'roi_t2': 10,
-        'roi_t3': 15,
-        'roi_p1': 1,
-        'roi_p2': 2,
-        'roi_p3': 3,
-    }
-
-    assert hyperopt.custom_hyperopt.generate_roi_table(params) == {0: 6, 15: 3, 25: 1, 30: 0}
-
-
-def test_start_calls_optimizer(mocker, default_conf, caplog) -> None:
-    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
-    mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
-    mocker.patch(
-        'freqtrade.optimize.hyperopt.get_timeframe',
-        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
-    )
-
-    parallel = mocker.patch(
-        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
-        MagicMock(return_value=[{'loss': 1, 'result': 'foo result', 'params': {}}])
-    )
-    patch_exchange(mocker)
-
-    default_conf.update({'config': 'config.json.example',
-                         'epochs': 1,
-                         'timerange': None,
-                         'spaces': 'all',
-                         'hyperopt_jobs': 1, })
-
-    hyperopt = Hyperopt(default_conf)
-    hyperopt.strategy.tickerdata_to_dataframe = MagicMock()
-
-    hyperopt.start()
-    parallel.assert_called_once()
-    assert log_has('Best result:\nfoo result\nwith values:\n', caplog.record_tuples)
-    assert dumper.called
-    # Should be called twice, once for tickerdata, once to save evaluations
-    assert dumper.call_count == 2
-    assert hasattr(hyperopt, "advise_sell")
-    assert hasattr(hyperopt, "advise_buy")
-    assert hasattr(hyperopt, "max_open_trades")
-    assert hyperopt.max_open_trades == default_conf['max_open_trades']
-    assert hasattr(hyperopt, "position_stacking")
-
-
-def test_format_results(hyperopt):
-    # Test with BTC as stake_currency
-    trades = [
-        ('ETH/BTC', 2, 2, 123),
-        ('LTC/BTC', 1, 1, 123),
-        ('XPR/BTC', -1, -2, -246)
-    ]
-    labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration']
-    df = pd.DataFrame.from_records(trades, columns=labels)
-
-    result = hyperopt.format_results(df)
-    assert result.find(' 66.67%')
-    assert result.find('Total profit 1.00000000 BTC')
-    assert result.find('2.0000Σ %')
-
-    # Test with EUR as stake_currency
-    trades = [
-        ('ETH/EUR', 2, 2, 123),
-        ('LTC/EUR', 1, 1, 123),
-        ('XPR/EUR', -1, -2, -246)
-    ]
-    df = pd.DataFrame.from_records(trades, columns=labels)
-    result = hyperopt.format_results(df)
-    assert result.find('Total profit 1.00000000 EUR')
-
-
-def test_has_space(hyperopt):
-    hyperopt.config.update({'spaces': ['buy', 'roi']})
-    assert hyperopt.has_space('roi')
-    assert hyperopt.has_space('buy')
-    assert not hyperopt.has_space('stoploss')
-
-    hyperopt.config.update({'spaces': ['all']})
-    assert hyperopt.has_space('buy')
-
-
-def test_populate_indicators(hyperopt) -> None:
-    tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m')
-    tickerlist = {'UNITTEST/BTC': parse_ticker_dataframe(tick, '1m', pair="UNITTEST/BTC",
-                                                         fill_missing=True)}
-    dataframes = hyperopt.strategy.tickerdata_to_dataframe(tickerlist)
-    dataframe = hyperopt.custom_hyperopt.populate_indicators(dataframes['UNITTEST/BTC'],
-                                                             {'pair': 'UNITTEST/BTC'})
-
-    # Check if some indicators are generated. We will not test all of them
-    assert 'adx' in dataframe
-    assert 'mfi' in dataframe
-    assert 'rsi' in dataframe
-
-
-def test_buy_strategy_generator(hyperopt) -> None:
-    tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m')
-    tickerlist = {'UNITTEST/BTC': parse_ticker_dataframe(tick, '1m', pair="UNITTEST/BTC",
-                                                         fill_missing=True)}
-    dataframes = hyperopt.strategy.tickerdata_to_dataframe(tickerlist)
-    dataframe = hyperopt.custom_hyperopt.populate_indicators(dataframes['UNITTEST/BTC'],
-                                                             {'pair': 'UNITTEST/BTC'})
-
-    populate_buy_trend = hyperopt.custom_hyperopt.buy_strategy_generator(
-        {
-            'adx-value': 20,
-            'fastd-value': 20,
-            'mfi-value': 20,
-            'rsi-value': 20,
-            'adx-enabled': True,
-            'fastd-enabled': True,
-            'mfi-enabled': True,
-            'rsi-enabled': True,
-            'trigger': 'bb_lower'
-        }
-    )
-    result = populate_buy_trend(dataframe, {'pair': 'UNITTEST/BTC'})
-    # Check if some indicators are generated. We will not test all of them
-    assert 'buy' in result
-    assert 1 in result['buy']
-
-
-def test_generate_optimizer(mocker, default_conf) -> None:
-    default_conf.update({'config': 'config.json.example'})
-    default_conf.update({'timerange': None})
-    default_conf.update({'spaces': 'all'})
-    default_conf.update({'hyperopt_min_trades': 1})
-
-    trades = [
-        ('POWR/BTC', 0.023117, 0.000233, 100)
-    ]
-    labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration']
-    backtest_result = pd.DataFrame.from_records(trades, columns=labels)
-
-    mocker.patch(
-        'freqtrade.optimize.hyperopt.Hyperopt.backtest',
-        MagicMock(return_value=backtest_result)
-    )
-    mocker.patch(
-        'freqtrade.optimize.hyperopt.get_timeframe',
-        MagicMock(return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13)))
-    )
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.optimize.hyperopt.load', MagicMock())
-
-    optimizer_param = {
-        'adx-value': 0,
-        'fastd-value': 35,
-        'mfi-value': 0,
-        'rsi-value': 0,
-        'adx-enabled': False,
-        'fastd-enabled': True,
-        'mfi-enabled': False,
-        'rsi-enabled': False,
-        'trigger': 'macd_cross_signal',
-        'sell-adx-value': 0,
-        'sell-fastd-value': 75,
-        'sell-mfi-value': 0,
-        'sell-rsi-value': 0,
-        'sell-adx-enabled': False,
-        'sell-fastd-enabled': True,
-        'sell-mfi-enabled': False,
-        'sell-rsi-enabled': False,
-        'sell-trigger': 'macd_cross_signal',
-        'roi_t1': 60.0,
-        'roi_t2': 30.0,
-        'roi_t3': 20.0,
-        'roi_p1': 0.01,
-        'roi_p2': 0.01,
-        'roi_p3': 0.1,
-        'stoploss': -0.4,
-    }
-    response_expected = {
-        'loss': 1.9840569076926293,
-        'result': '     1 trades. Avg profit  2.31%. Total profit  0.00023300 BTC '
-                  '(   2.31Σ%). Avg duration 100.0 mins.',
-        'params': optimizer_param
-    }
-
-    hyperopt = Hyperopt(default_conf)
-    generate_optimizer_value = hyperopt.generate_optimizer(list(optimizer_param.values()))
-    assert generate_optimizer_value == response_expected
-
-
-def test_clean_hyperopt(mocker, default_conf, caplog):
-    patch_exchange(mocker)
-    default_conf.update({'config': 'config.json.example',
-                         'epochs': 1,
-                         'timerange': None,
-                         'spaces': 'all',
-                         'hyperopt_jobs': 1,
-                         })
-    mocker.patch("freqtrade.optimize.hyperopt.Path.is_file", MagicMock(return_value=True))
-    unlinkmock = mocker.patch("freqtrade.optimize.hyperopt.Path.unlink", MagicMock())
-    Hyperopt(default_conf)
-
-    assert unlinkmock.call_count == 2
-    assert log_has(f"Removing `{TICKERDATA_PICKLE}`.", caplog.record_tuples)
-
-
-def test_continue_hyperopt(mocker, default_conf, caplog):
-    patch_exchange(mocker)
-    default_conf.update({'config': 'config.json.example',
-                         'epochs': 1,
-                         'timerange': None,
-                         'spaces': 'all',
-                         'hyperopt_jobs': 1,
-                         'hyperopt_continue': True
-                         })
-    mocker.patch("freqtrade.optimize.hyperopt.Path.is_file", MagicMock(return_value=True))
-    unlinkmock = mocker.patch("freqtrade.optimize.hyperopt.Path.unlink", MagicMock())
-    Hyperopt(default_conf)
-
-    assert unlinkmock.call_count == 0
-    assert log_has(f"Continuing on previous hyperopt results.", caplog.record_tuples)
diff --git a/freqtrade/tests/pairlist/test_pairlist.py b/freqtrade/tests/pairlist/test_pairlist.py
deleted file mode 100644
index e7439bb51..000000000
--- a/freqtrade/tests/pairlist/test_pairlist.py
+++ /dev/null
@@ -1,176 +0,0 @@
-# pragma pylint: disable=missing-docstring,C0103,protected-access
-
-from unittest.mock import MagicMock, PropertyMock
-
-from freqtrade import OperationalException
-from freqtrade.constants import AVAILABLE_PAIRLISTS
-from freqtrade.resolvers import PairListResolver
-from freqtrade.tests.conftest import get_patched_freqtradebot
-import pytest
-
-# whitelist, blacklist
-
-
-@pytest.fixture(scope="function")
-def whitelist_conf(default_conf):
-    default_conf['stake_currency'] = 'BTC'
-    default_conf['exchange']['pair_whitelist'] = [
-        'ETH/BTC',
-        'TKN/BTC',
-        'TRST/BTC',
-        'SWT/BTC',
-        'BCC/BTC'
-    ]
-    default_conf['exchange']['pair_blacklist'] = [
-        'BLK/BTC'
-    ]
-    default_conf['pairlist'] = {'method': 'StaticPairList',
-                                'config': {'number_assets': 3}
-                                }
-
-    return default_conf
-
-
-def test_load_pairlist_noexist(mocker, markets, default_conf):
-    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
-    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
-    with pytest.raises(OperationalException,
-                       match=r"Impossible to load Pairlist 'NonexistingPairList'. "
-                             r"This class does not exist or contains Python code errors."):
-        PairListResolver('NonexistingPairList', freqtradebot, default_conf).pairlist
-
-
-def test_refresh_market_pair_not_in_whitelist(mocker, markets, whitelist_conf):
-
-    freqtradebot = get_patched_freqtradebot(mocker, whitelist_conf)
-
-    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
-    freqtradebot.pairlists.refresh_pairlist()
-    # List ordered by BaseVolume
-    whitelist = ['ETH/BTC', 'TKN/BTC']
-    # Ensure all except those in whitelist are removed
-    assert set(whitelist) == set(freqtradebot.pairlists.whitelist)
-    # Ensure config dict hasn't been changed
-    assert (whitelist_conf['exchange']['pair_whitelist'] ==
-            freqtradebot.config['exchange']['pair_whitelist'])
-
-
-def test_refresh_pairlists(mocker, markets, whitelist_conf):
-    freqtradebot = get_patched_freqtradebot(mocker, whitelist_conf)
-
-    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
-    freqtradebot.pairlists.refresh_pairlist()
-    # List ordered by BaseVolume
-    whitelist = ['ETH/BTC', 'TKN/BTC']
-    # Ensure all except those in whitelist are removed
-    assert set(whitelist) == set(freqtradebot.pairlists.whitelist)
-    assert whitelist_conf['exchange']['pair_blacklist'] == freqtradebot.pairlists.blacklist
-
-
-def test_refresh_pairlist_dynamic(mocker, markets, tickers, whitelist_conf):
-    whitelist_conf['pairlist'] = {'method': 'VolumePairList',
-                                  'config': {'number_assets': 5}
-                                  }
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        markets=PropertyMock(return_value=markets),
-        get_tickers=tickers,
-        exchange_has=MagicMock(return_value=True)
-    )
-    freqtradebot = get_patched_freqtradebot(mocker, whitelist_conf)
-
-    # argument: use the whitelist dynamically by exchange-volume
-    whitelist = ['ETH/BTC', 'TKN/BTC', 'BTT/BTC']
-    freqtradebot.pairlists.refresh_pairlist()
-
-    assert whitelist == freqtradebot.pairlists.whitelist
-
-    whitelist_conf['pairlist'] = {'method': 'VolumePairList',
-                                  'config': {}
-                                  }
-    with pytest.raises(OperationalException,
-                       match=r'`number_assets` not specified. Please check your configuration '
-                             r'for "pairlist.config.number_assets"'):
-        PairListResolver('VolumePairList', freqtradebot, whitelist_conf).pairlist
-
-
-def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf):
-    freqtradebot = get_patched_freqtradebot(mocker, whitelist_conf)
-    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets_empty))
-
-    # argument: use the whitelist dynamically by exchange-volume
-    whitelist = []
-    whitelist_conf['exchange']['pair_whitelist'] = []
-    freqtradebot.pairlists.refresh_pairlist()
-    pairslist = whitelist_conf['exchange']['pair_whitelist']
-
-    assert set(whitelist) == set(pairslist)
-
-
-@pytest.mark.parametrize("precision_filter,base_currency,key,whitelist_result", [
-    (False, "BTC", "quoteVolume", ['ETH/BTC', 'TKN/BTC', 'BTT/BTC']),
-    (False, "BTC", "bidVolume", ['BTT/BTC', 'TKN/BTC', 'ETH/BTC']),
-    (False, "USDT", "quoteVolume", ['ETH/USDT', 'LTC/USDT']),
-    (False, "ETH", "quoteVolume", []),  # this replaces tests that were removed from test_exchange
-    (True, "BTC", "quoteVolume", ["ETH/BTC", "TKN/BTC"]),
-    (True, "BTC", "bidVolume", ["TKN/BTC", "ETH/BTC"])
-])
-def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, markets, tickers, base_currency, key,
-                                      whitelist_result, precision_filter) -> None:
-    whitelist_conf['pairlist']['method'] = 'VolumePairList'
-    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
-    freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
-    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
-    mocker.patch('freqtrade.exchange.Exchange.get_tickers', tickers)
-    mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, p, r: round(r, 8))
-
-    freqtrade.pairlists._precision_filter = precision_filter
-    freqtrade.config['stake_currency'] = base_currency
-    whitelist = freqtrade.pairlists._gen_pair_whitelist(base_currency=base_currency, key=key)
-    assert whitelist == whitelist_result
-
-
-def test_gen_pair_whitelist_not_supported(mocker, default_conf, tickers) -> None:
-    default_conf['pairlist'] = {'method': 'VolumePairList',
-                                'config': {'number_assets': 10}
-                                }
-    mocker.patch('freqtrade.exchange.Exchange.get_tickers', tickers)
-    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=False))
-
-    with pytest.raises(OperationalException):
-        get_patched_freqtradebot(mocker, default_conf)
-
-
-@pytest.mark.parametrize("pairlist", AVAILABLE_PAIRLISTS)
-def test_pairlist_class(mocker, whitelist_conf, markets, pairlist):
-    whitelist_conf['pairlist']['method'] = pairlist
-    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
-    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
-    freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
-
-    assert freqtrade.pairlists.name == pairlist
-    assert pairlist in freqtrade.pairlists.short_desc()
-    assert isinstance(freqtrade.pairlists.whitelist, list)
-    assert isinstance(freqtrade.pairlists.blacklist, list)
-
-
-@pytest.mark.parametrize("pairlist", AVAILABLE_PAIRLISTS)
-@pytest.mark.parametrize("whitelist,log_message", [
-    (['ETH/BTC', 'TKN/BTC'], ""),
-    (['ETH/BTC', 'TKN/BTC', 'TRX/ETH'], "is not compatible with exchange"),  # TRX/ETH wrong stake
-    (['ETH/BTC', 'TKN/BTC', 'BCH/BTC'], "is not compatible with exchange"),  # BCH/BTC not available
-    (['ETH/BTC', 'TKN/BTC', 'BLK/BTC'], "is not compatible with exchange"),  # BLK/BTC in blacklist
-    (['ETH/BTC', 'TKN/BTC', 'LTC/BTC'], "Market is not active")  # LTC/BTC is inactive
-])
-def test_validate_whitelist(mocker, whitelist_conf, markets, pairlist, whitelist, caplog,
-                            log_message):
-    whitelist_conf['pairlist']['method'] = pairlist
-    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
-    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
-    freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
-    caplog.clear()
-
-    new_whitelist = freqtrade.pairlists._validate_whitelist(whitelist)
-
-    assert set(new_whitelist) == set(['ETH/BTC', 'TKN/BTC'])
-    assert log_message in caplog.text
diff --git a/freqtrade/tests/rpc/test_rpc_apiserver.py b/freqtrade/tests/rpc/test_rpc_apiserver.py
deleted file mode 100644
index bd420ada6..000000000
--- a/freqtrade/tests/rpc/test_rpc_apiserver.py
+++ /dev/null
@@ -1,558 +0,0 @@
-"""
-Unit test file for rpc/api_server.py
-"""
-
-from datetime import datetime
-from unittest.mock import ANY, MagicMock, PropertyMock
-
-import pytest
-from flask import Flask
-from requests.auth import _basic_auth_str
-
-from freqtrade.__init__ import __version__
-from freqtrade.persistence import Trade
-from freqtrade.rpc.api_server import BASE_URI, ApiServer
-from freqtrade.state import State
-from freqtrade.tests.conftest import (get_patched_freqtradebot, log_has,
-                                      patch_get_signal)
-
-
-_TEST_USER = "FreqTrader"
-_TEST_PASS = "SuperSecurePassword1!"
-
-
-@pytest.fixture
-def botclient(default_conf, mocker):
-    default_conf.update({"api_server": {"enabled": True,
-                                        "listen_ip_address": "127.0.0.1",
-                                        "listen_port": "8080",
-                                        "username": _TEST_USER,
-                                        "password": _TEST_PASS,
-                                        }})
-
-    ftbot = get_patched_freqtradebot(mocker, default_conf)
-    mocker.patch('freqtrade.rpc.api_server.ApiServer.run', MagicMock())
-    apiserver = ApiServer(ftbot)
-    yield ftbot, apiserver.app.test_client()
-    # Cleanup ... ?
-
-
-def client_post(client, url, data={}):
-    return client.post(url,
-                       content_type="application/json",
-                       data=data,
-                       headers={'Authorization': _basic_auth_str(_TEST_USER, _TEST_PASS)})
-
-
-def client_get(client, url):
-    return client.get(url, headers={'Authorization': _basic_auth_str(_TEST_USER, _TEST_PASS)})
-
-
-def assert_response(response, expected_code=200):
-    assert response.status_code == expected_code
-    assert response.content_type == "application/json"
-
-
-def test_api_not_found(botclient):
-    ftbot, client = botclient
-
-    rc = client_post(client, f"{BASE_URI}/invalid_url")
-    assert_response(rc, 404)
-    assert rc.json == {"status": "error",
-                       "reason": f"There's no API call for http://localhost{BASE_URI}/invalid_url.",
-                       "code": 404
-                       }
-
-
-def test_api_unauthorized(botclient):
-    ftbot, client = botclient
-    # Don't send user/pass information
-    rc = client.get(f"{BASE_URI}/version")
-    assert_response(rc, 401)
-    assert rc.json == {'error': 'Unauthorized'}
-
-    # Change only username
-    ftbot.config['api_server']['username'] = "Ftrader"
-    rc = client_get(client, f"{BASE_URI}/version")
-    assert_response(rc, 401)
-    assert rc.json == {'error': 'Unauthorized'}
-
-    # Change only password
-    ftbot.config['api_server']['username'] = _TEST_USER
-    ftbot.config['api_server']['password'] = "WrongPassword"
-    rc = client_get(client, f"{BASE_URI}/version")
-    assert_response(rc, 401)
-    assert rc.json == {'error': 'Unauthorized'}
-
-    ftbot.config['api_server']['username'] = "Ftrader"
-    ftbot.config['api_server']['password'] = "WrongPassword"
-
-    rc = client_get(client, f"{BASE_URI}/version")
-    assert_response(rc, 401)
-    assert rc.json == {'error': 'Unauthorized'}
-
-
-def test_api_stop_workflow(botclient):
-    ftbot, client = botclient
-    assert ftbot.state == State.RUNNING
-    rc = client_post(client, f"{BASE_URI}/stop")
-    assert_response(rc)
-    assert rc.json == {'status': 'stopping trader ...'}
-    assert ftbot.state == State.STOPPED
-
-    # Stop bot again
-    rc = client_post(client, f"{BASE_URI}/stop")
-    assert_response(rc)
-    assert rc.json == {'status': 'already stopped'}
-
-    # Start bot
-    rc = client_post(client, f"{BASE_URI}/start")
-    assert_response(rc)
-    assert rc.json == {'status': 'starting trader ...'}
-    assert ftbot.state == State.RUNNING
-
-    # Call start again
-    rc = client_post(client, f"{BASE_URI}/start")
-    assert_response(rc)
-    assert rc.json == {'status': 'already running'}
-
-
-def test_api__init__(default_conf, mocker):
-    """
-    Test __init__() method
-    """
-    mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock())
-    mocker.patch('freqtrade.rpc.api_server.ApiServer.run', MagicMock())
-
-    apiserver = ApiServer(get_patched_freqtradebot(mocker, default_conf))
-    assert apiserver._config == default_conf
-
-
-def test_api_run(default_conf, mocker, caplog):
-    default_conf.update({"api_server": {"enabled": True,
-                                        "listen_ip_address": "127.0.0.1",
-                                        "listen_port": "8080"}})
-    mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock())
-    mocker.patch('freqtrade.rpc.api_server.threading.Thread', MagicMock())
-
-    server_mock = MagicMock()
-    mocker.patch('freqtrade.rpc.api_server.make_server', server_mock)
-
-    apiserver = ApiServer(get_patched_freqtradebot(mocker, default_conf))
-
-    assert apiserver._config == default_conf
-    apiserver.run()
-    assert server_mock.call_count == 1
-    assert server_mock.call_args_list[0][0][0] == "127.0.0.1"
-    assert server_mock.call_args_list[0][0][1] == "8080"
-    assert isinstance(server_mock.call_args_list[0][0][2], Flask)
-    assert hasattr(apiserver, "srv")
-
-    assert log_has("Starting HTTP Server at 127.0.0.1:8080", caplog.record_tuples)
-    assert log_has("Starting Local Rest Server.", caplog.record_tuples)
-
-    # Test binding to public
-    caplog.clear()
-    server_mock.reset_mock()
-    apiserver._config.update({"api_server": {"enabled": True,
-                                             "listen_ip_address": "0.0.0.0",
-                                             "listen_port": "8089",
-                                             "password": "",
-                                             }})
-    apiserver.run()
-
-    assert server_mock.call_count == 1
-    assert server_mock.call_args_list[0][0][0] == "0.0.0.0"
-    assert server_mock.call_args_list[0][0][1] == "8089"
-    assert isinstance(server_mock.call_args_list[0][0][2], Flask)
-    assert log_has("Starting HTTP Server at 0.0.0.0:8089", caplog.record_tuples)
-    assert log_has("Starting Local Rest Server.", caplog.record_tuples)
-    assert log_has("SECURITY WARNING - Local Rest Server listening to external connections",
-                   caplog.record_tuples)
-    assert log_has("SECURITY WARNING - This is insecure please set to your loopback,"
-                   "e.g 127.0.0.1 in config.json",
-                   caplog.record_tuples)
-    assert log_has("SECURITY WARNING - No password for local REST Server defined. "
-                   "Please make sure that this is intentional!",
-                   caplog.record_tuples)
-
-    # Test crashing flask
-    caplog.clear()
-    mocker.patch('freqtrade.rpc.api_server.make_server', MagicMock(side_effect=Exception))
-    apiserver.run()
-    assert log_has("Api server failed to start.", caplog.record_tuples)
-
-
-def test_api_cleanup(default_conf, mocker, caplog):
-    default_conf.update({"api_server": {"enabled": True,
-                                        "listen_ip_address": "127.0.0.1",
-                                        "listen_port": "8080"}})
-    mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock())
-    mocker.patch('freqtrade.rpc.api_server.threading.Thread', MagicMock())
-    mocker.patch('freqtrade.rpc.api_server.make_server', MagicMock())
-
-    apiserver = ApiServer(get_patched_freqtradebot(mocker, default_conf))
-    apiserver.run()
-    stop_mock = MagicMock()
-    stop_mock.shutdown = MagicMock()
-    apiserver.srv = stop_mock
-
-    apiserver.cleanup()
-    assert stop_mock.shutdown.call_count == 1
-    assert log_has("Stopping API Server", caplog.record_tuples)
-
-
-def test_api_reloadconf(botclient):
-    ftbot, client = botclient
-
-    rc = client_post(client, f"{BASE_URI}/reload_conf")
-    assert_response(rc)
-    assert rc.json == {'status': 'reloading config ...'}
-    assert ftbot.state == State.RELOAD_CONF
-
-
-def test_api_stopbuy(botclient):
-    ftbot, client = botclient
-    assert ftbot.config['max_open_trades'] != 0
-
-    rc = client_post(client, f"{BASE_URI}/stopbuy")
-    assert_response(rc)
-    assert rc.json == {'status': 'No more buy will occur from now. Run /reload_conf to reset.'}
-    assert ftbot.config['max_open_trades'] == 0
-
-
-def test_api_balance(botclient, mocker, rpc_balance):
-    ftbot, client = botclient
-
-    def mock_ticker(symbol, refresh):
-        if symbol == 'BTC/USDT':
-            return {
-                'bid': 10000.00,
-                'ask': 10000.00,
-                'last': 10000.00,
-            }
-        elif symbol == 'XRP/BTC':
-            return {
-                'bid': 0.00001,
-                'ask': 0.00001,
-                'last': 0.00001,
-            }
-        return {
-            'bid': 0.1,
-            'ask': 0.1,
-            'last': 0.1,
-        }
-    mocker.patch('freqtrade.exchange.Exchange.get_balances', return_value=rpc_balance)
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker', side_effect=mock_ticker)
-    mocker.patch('freqtrade.exchange.Exchange.get_valid_pair_combination',
-                 side_effect=lambda a, b: f"{a}/{b}")
-
-    rc = client_get(client, f"{BASE_URI}/balance")
-    assert_response(rc)
-    assert "currencies" in rc.json
-    assert len(rc.json["currencies"]) == 5
-    assert rc.json['currencies'][0] == {
-        'currency': 'BTC',
-        'available': 12.0,
-        'balance': 12.0,
-        'pending': 0.0,
-        'est_btc': 12.0,
-    }
-
-
-def test_api_count(botclient, mocker, ticker, fee, markets):
-    ftbot, client = botclient
-    patch_get_signal(ftbot, (True, False))
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_balances=MagicMock(return_value=ticker),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    rc = client_get(client, f"{BASE_URI}/count")
-    assert_response(rc)
-
-    assert rc.json["current"] == 0
-    assert rc.json["max"] == 1.0
-
-    # Create some test data
-    ftbot.create_trade()
-    rc = client_get(client, f"{BASE_URI}/count")
-    assert_response(rc)
-    assert rc.json["current"] == 1.0
-    assert rc.json["max"] == 1.0
-
-
-def test_api_daily(botclient, mocker, ticker, fee, markets):
-    ftbot, client = botclient
-    patch_get_signal(ftbot, (True, False))
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_balances=MagicMock(return_value=ticker),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    rc = client_get(client, f"{BASE_URI}/daily")
-    assert_response(rc)
-    assert len(rc.json) == 7
-    assert rc.json[0][0] == str(datetime.utcnow().date())
-
-
-def test_api_edge_disabled(botclient, mocker, ticker, fee, markets):
-    ftbot, client = botclient
-    patch_get_signal(ftbot, (True, False))
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_balances=MagicMock(return_value=ticker),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    rc = client_get(client, f"{BASE_URI}/edge")
-    assert_response(rc, 502)
-    assert rc.json == {"error": "Error querying _edge: Edge is not enabled."}
-
-
-def test_api_profit(botclient, mocker, ticker, fee, markets, limit_buy_order, limit_sell_order):
-    ftbot, client = botclient
-    patch_get_signal(ftbot, (True, False))
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_balances=MagicMock(return_value=ticker),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-
-    rc = client_get(client, f"{BASE_URI}/profit")
-    assert_response(rc, 502)
-    assert len(rc.json) == 1
-    assert rc.json == {"error": "Error querying _profit: no closed trade"}
-
-    ftbot.create_trade()
-    trade = Trade.query.first()
-
-    # Simulate fulfilled LIMIT_BUY order for trade
-    trade.update(limit_buy_order)
-    rc = client_get(client, f"{BASE_URI}/profit")
-    assert_response(rc, 502)
-    assert rc.json == {"error": "Error querying _profit: no closed trade"}
-
-    trade.update(limit_sell_order)
-
-    trade.close_date = datetime.utcnow()
-    trade.is_open = False
-
-    rc = client_get(client, f"{BASE_URI}/profit")
-    assert_response(rc)
-    assert rc.json == {'avg_duration': '0:00:00',
-                       'best_pair': 'ETH/BTC',
-                       'best_rate': 6.2,
-                       'first_trade_date': 'just now',
-                       'latest_trade_date': 'just now',
-                       'profit_all_coin': 6.217e-05,
-                       'profit_all_fiat': 0,
-                       'profit_all_percent': 6.2,
-                       'profit_closed_coin': 6.217e-05,
-                       'profit_closed_fiat': 0,
-                       'profit_closed_percent': 6.2,
-                       'trade_count': 1
-                       }
-
-
-def test_api_performance(botclient, mocker, ticker, fee):
-    ftbot, client = botclient
-    patch_get_signal(ftbot, (True, False))
-
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=1,
-        exchange='binance',
-        stake_amount=1,
-        open_rate=0.245441,
-        open_order_id="123456",
-        is_open=False,
-        fee_close=fee.return_value,
-        fee_open=fee.return_value,
-        close_rate=0.265441,
-
-    )
-    trade.close_profit = trade.calc_profit_percent()
-    Trade.session.add(trade)
-
-    trade = Trade(
-        pair='XRP/ETH',
-        amount=5,
-        stake_amount=1,
-        exchange='binance',
-        open_rate=0.412,
-        open_order_id="123456",
-        is_open=False,
-        fee_close=fee.return_value,
-        fee_open=fee.return_value,
-        close_rate=0.391
-    )
-    trade.close_profit = trade.calc_profit_percent()
-    Trade.session.add(trade)
-    Trade.session.flush()
-
-    rc = client_get(client, f"{BASE_URI}/performance")
-    assert_response(rc)
-    assert len(rc.json) == 2
-    assert rc.json == [{'count': 1, 'pair': 'LTC/ETH', 'profit': 7.61},
-                       {'count': 1, 'pair': 'XRP/ETH', 'profit': -5.57}]
-
-
-def test_api_status(botclient, mocker, ticker, fee, markets):
-    ftbot, client = botclient
-    patch_get_signal(ftbot, (True, False))
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_balances=MagicMock(return_value=ticker),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-
-    rc = client_get(client, f"{BASE_URI}/status")
-    assert_response(rc, 502)
-    assert rc.json == {'error': 'Error querying _status: no active trade'}
-
-    ftbot.create_trade()
-    rc = client_get(client, f"{BASE_URI}/status")
-    assert_response(rc)
-    assert len(rc.json) == 1
-    assert rc.json == [{'amount': 90.99181074,
-                        'base_currency': 'BTC',
-                        'close_date': None,
-                        'close_date_hum': None,
-                        'close_profit': None,
-                        'close_rate': None,
-                        'current_profit': -0.59,
-                        'current_rate': 1.098e-05,
-                        'initial_stop_loss': 0.0,
-                        'initial_stop_loss_pct': None,
-                        'open_date': ANY,
-                        'open_date_hum': 'just now',
-                        'open_order': '(limit buy rem=0.00000000)',
-                        'open_rate': 1.099e-05,
-                        'pair': 'ETH/BTC',
-                        'stake_amount': 0.001,
-                        'stop_loss': 0.0,
-                        'stop_loss_pct': None,
-                        'trade_id': 1}]
-
-
-def test_api_version(botclient):
-    ftbot, client = botclient
-
-    rc = client_get(client, f"{BASE_URI}/version")
-    assert_response(rc)
-    assert rc.json == {"version": __version__}
-
-
-def test_api_blacklist(botclient, mocker):
-    ftbot, client = botclient
-
-    rc = client_get(client, f"{BASE_URI}/blacklist")
-    assert_response(rc)
-    assert rc.json == {"blacklist": ["DOGE/BTC", "HOT/BTC"],
-                       "length": 2,
-                       "method": "StaticPairList"}
-
-    # Add ETH/BTC to blacklist
-    rc = client_post(client, f"{BASE_URI}/blacklist",
-                     data='{"blacklist": ["ETH/BTC"]}')
-    assert_response(rc)
-    assert rc.json == {"blacklist": ["DOGE/BTC", "HOT/BTC", "ETH/BTC"],
-                       "length": 3,
-                       "method": "StaticPairList"}
-
-
-def test_api_whitelist(botclient):
-    ftbot, client = botclient
-
-    rc = client_get(client, f"{BASE_URI}/whitelist")
-    assert_response(rc)
-    assert rc.json == {"whitelist": ['ETH/BTC', 'LTC/BTC', 'XRP/BTC', 'NEO/BTC'],
-                       "length": 4,
-                       "method": "StaticPairList"}
-
-
-def test_api_forcebuy(botclient, mocker, fee):
-    ftbot, client = botclient
-
-    rc = client_post(client, f"{BASE_URI}/forcebuy",
-                     data='{"pair": "ETH/BTC"}')
-    assert_response(rc, 502)
-    assert rc.json == {"error": "Error querying _forcebuy: Forcebuy not enabled."}
-
-    # enable forcebuy
-    ftbot.config["forcebuy_enable"] = True
-
-    fbuy_mock = MagicMock(return_value=None)
-    mocker.patch("freqtrade.rpc.RPC._rpc_forcebuy", fbuy_mock)
-    rc = client_post(client, f"{BASE_URI}/forcebuy",
-                     data='{"pair": "ETH/BTC"}')
-    assert_response(rc)
-    assert rc.json == {"status": "Error buying pair ETH/BTC."}
-
-    # Test creating trae
-    fbuy_mock = MagicMock(return_value=Trade(
-        pair='ETH/ETH',
-        amount=1,
-        exchange='bittrex',
-        stake_amount=1,
-        open_rate=0.245441,
-        open_order_id="123456",
-        open_date=datetime.utcnow(),
-        is_open=False,
-        fee_close=fee.return_value,
-        fee_open=fee.return_value,
-        close_rate=0.265441,
-    ))
-    mocker.patch("freqtrade.rpc.RPC._rpc_forcebuy", fbuy_mock)
-
-    rc = client_post(client, f"{BASE_URI}/forcebuy",
-                     data='{"pair": "ETH/BTC"}')
-    assert_response(rc)
-    assert rc.json == {'amount': 1,
-                       'close_date': None,
-                       'close_date_hum': None,
-                       'close_rate': 0.265441,
-                       'initial_stop_loss': None,
-                       'initial_stop_loss_pct': None,
-                       'open_date': ANY,
-                       'open_date_hum': 'just now',
-                       'open_rate': 0.245441,
-                       'pair': 'ETH/ETH',
-                       'stake_amount': 1,
-                       'stop_loss': None,
-                       'stop_loss_pct': None,
-                       'trade_id': None}
-
-
-def test_api_forcesell(botclient, mocker, ticker, fee, markets):
-    ftbot, client = botclient
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_balances=MagicMock(return_value=ticker),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    patch_get_signal(ftbot, (True, False))
-
-    rc = client_post(client, f"{BASE_URI}/forcesell",
-                     data='{"tradeid": "1"}')
-    assert_response(rc, 502)
-    assert rc.json == {"error": "Error querying _forcesell: invalid argument"}
-
-    ftbot.create_trade()
-
-    rc = client_post(client, f"{BASE_URI}/forcesell",
-                     data='{"tradeid": "1"}')
-    assert_response(rc)
-    assert rc.json == {'result': 'Created sell order for trade 1.'}
diff --git a/freqtrade/tests/strategy/legacy_strategy.py b/freqtrade/tests/strategy/legacy_strategy.py
deleted file mode 100644
index 2cd13b791..000000000
--- a/freqtrade/tests/strategy/legacy_strategy.py
+++ /dev/null
@@ -1,235 +0,0 @@
-
-# --- Do not remove these libs ---
-from freqtrade.strategy.interface import IStrategy
-from pandas import DataFrame
-# --------------------------------
-
-# Add your lib to import here
-import talib.abstract as ta
-import freqtrade.vendor.qtpylib.indicators as qtpylib
-import numpy  # noqa
-
-
-# This class is a sample. Feel free to customize it.
-class TestStrategyLegacy(IStrategy):
-    """
-    This is a test strategy using the legacy function headers, which will be
-    removed in a future update.
-    Please do not use this as a template, but refer to user_data/strategy/TestStrategy.py
-    for a uptodate version of this template.
-
-    """
-
-    # Minimal ROI designed for the strategy.
-    # This attribute will be overridden if the config file contains "minimal_roi"
-    minimal_roi = {
-        "40": 0.0,
-        "30": 0.01,
-        "20": 0.02,
-        "0": 0.04
-    }
-
-    # Optimal stoploss designed for the strategy
-    # This attribute will be overridden if the config file contains "stoploss"
-    stoploss = -0.10
-
-    # Optimal ticker interval for the strategy
-    ticker_interval = '5m'
-
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
-        """
-        Adds several different TA indicators to the given DataFrame
-
-        Performance Note: For the best performance be frugal on the number of indicators
-        you are using. Let uncomment only the indicator you are using in your strategies
-        or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
-        """
-
-        # Momentum Indicator
-        # ------------------------------------
-
-        # ADX
-        dataframe['adx'] = ta.ADX(dataframe)
-
-        """
-        # Awesome oscillator
-        dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
-
-        # Commodity Channel Index: values Oversold:<-100, Overbought:>100
-        dataframe['cci'] = ta.CCI(dataframe)
-
-        # MACD
-        macd = ta.MACD(dataframe)
-        dataframe['macd'] = macd['macd']
-        dataframe['macdsignal'] = macd['macdsignal']
-        dataframe['macdhist'] = macd['macdhist']
-
-        # MFI
-        dataframe['mfi'] = ta.MFI(dataframe)
-
-        # Minus Directional Indicator / Movement
-        dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
-        dataframe['minus_di'] = ta.MINUS_DI(dataframe)
-
-        # Plus Directional Indicator / Movement
-        dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
-        dataframe['plus_di'] = ta.PLUS_DI(dataframe)
-        dataframe['minus_di'] = ta.MINUS_DI(dataframe)
-
-        # ROC
-        dataframe['roc'] = ta.ROC(dataframe)
-
-        # RSI
-        dataframe['rsi'] = ta.RSI(dataframe)
-
-        # Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
-        rsi = 0.1 * (dataframe['rsi'] - 50)
-        dataframe['fisher_rsi'] = (numpy.exp(2 * rsi) - 1) / (numpy.exp(2 * rsi) + 1)
-
-        # Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
-        dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
-
-        # Stoch
-        stoch = ta.STOCH(dataframe)
-        dataframe['slowd'] = stoch['slowd']
-        dataframe['slowk'] = stoch['slowk']
-
-        # Stoch fast
-        stoch_fast = ta.STOCHF(dataframe)
-        dataframe['fastd'] = stoch_fast['fastd']
-        dataframe['fastk'] = stoch_fast['fastk']
-
-        # Stoch RSI
-        stoch_rsi = ta.STOCHRSI(dataframe)
-        dataframe['fastd_rsi'] = stoch_rsi['fastd']
-        dataframe['fastk_rsi'] = stoch_rsi['fastk']
-        """
-
-        # Overlap Studies
-        # ------------------------------------
-
-        # Bollinger bands
-        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
-        dataframe['bb_lowerband'] = bollinger['lower']
-        dataframe['bb_middleband'] = bollinger['mid']
-        dataframe['bb_upperband'] = bollinger['upper']
-
-        """
-        # EMA - Exponential Moving Average
-        dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3)
-        dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
-        dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
-        dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
-        dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
-
-        # SAR Parabol
-        dataframe['sar'] = ta.SAR(dataframe)
-
-        # SMA - Simple Moving Average
-        dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
-        """
-
-        # TEMA - Triple Exponential Moving Average
-        dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
-
-        # Cycle Indicator
-        # ------------------------------------
-        # Hilbert Transform Indicator - SineWave
-        hilbert = ta.HT_SINE(dataframe)
-        dataframe['htsine'] = hilbert['sine']
-        dataframe['htleadsine'] = hilbert['leadsine']
-
-        # Pattern Recognition - Bullish candlestick patterns
-        # ------------------------------------
-        """
-        # Hammer: values [0, 100]
-        dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
-        # Inverted Hammer: values [0, 100]
-        dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
-        # Dragonfly Doji: values [0, 100]
-        dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
-        # Piercing Line: values [0, 100]
-        dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
-        # Morningstar: values [0, 100]
-        dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
-        # Three White Soldiers: values [0, 100]
-        dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
-        """
-
-        # Pattern Recognition - Bearish candlestick patterns
-        # ------------------------------------
-        """
-        # Hanging Man: values [0, 100]
-        dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
-        # Shooting Star: values [0, 100]
-        dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
-        # Gravestone Doji: values [0, 100]
-        dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
-        # Dark Cloud Cover: values [0, 100]
-        dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
-        # Evening Doji Star: values [0, 100]
-        dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
-        # Evening Star: values [0, 100]
-        dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
-        """
-
-        # Pattern Recognition - Bullish/Bearish candlestick patterns
-        # ------------------------------------
-        """
-        # Three Line Strike: values [0, -100, 100]
-        dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
-        # Spinning Top: values [0, -100, 100]
-        dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
-        # Engulfing: values [0, -100, 100]
-        dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
-        # Harami: values [0, -100, 100]
-        dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
-        # Three Outside Up/Down: values [0, -100, 100]
-        dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
-        # Three Inside Up/Down: values [0, -100, 100]
-        dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
-        """
-
-        # Chart type
-        # ------------------------------------
-        """
-        # Heikinashi stategy
-        heikinashi = qtpylib.heikinashi(dataframe)
-        dataframe['ha_open'] = heikinashi['open']
-        dataframe['ha_close'] = heikinashi['close']
-        dataframe['ha_high'] = heikinashi['high']
-        dataframe['ha_low'] = heikinashi['low']
-        """
-
-        return dataframe
-
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
-        """
-        Based on TA indicators, populates the buy signal for the given dataframe
-        :param dataframe: DataFrame
-        :return: DataFrame with buy column
-        """
-        dataframe.loc[
-            (
-                (dataframe['adx'] > 30) &
-                (dataframe['tema'] <= dataframe['bb_middleband']) &
-                (dataframe['tema'] > dataframe['tema'].shift(1))
-            ),
-            'buy'] = 1
-
-        return dataframe
-
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
-        """
-        Based on TA indicators, populates the sell signal for the given dataframe
-        :param dataframe: DataFrame
-        :return: DataFrame with buy column
-        """
-        dataframe.loc[
-            (
-                (dataframe['adx'] > 70) &
-                (dataframe['tema'] > dataframe['bb_middleband']) &
-                (dataframe['tema'] < dataframe['tema'].shift(1))
-            ),
-            'sell'] = 1
-        return dataframe
diff --git a/freqtrade/tests/strategy/test_interface.py b/freqtrade/tests/strategy/test_interface.py
deleted file mode 100644
index ee8c8ddd4..000000000
--- a/freqtrade/tests/strategy/test_interface.py
+++ /dev/null
@@ -1,295 +0,0 @@
-# pragma pylint: disable=missing-docstring, C0103
-
-import logging
-from unittest.mock import MagicMock
-
-import arrow
-from pandas import DataFrame
-
-from freqtrade.configuration import TimeRange
-from freqtrade.data.converter import parse_ticker_dataframe
-from freqtrade.data.history import load_tickerdata_file
-from freqtrade.persistence import Trade
-from freqtrade.tests.conftest import get_patched_exchange, log_has
-from freqtrade.strategy.default_strategy import DefaultStrategy
-
-# Avoid to reinit the same object again and again
-_STRATEGY = DefaultStrategy(config={})
-
-
-def test_returns_latest_buy_signal(mocker, default_conf, ticker_history):
-    mocker.patch.object(
-        _STRATEGY, 'analyze_ticker',
-        return_value=DataFrame([{'buy': 1, 'sell': 0, 'date': arrow.utcnow()}])
-    )
-    assert _STRATEGY.get_signal('ETH/BTC', '5m', ticker_history) == (True, False)
-
-    mocker.patch.object(
-        _STRATEGY, 'analyze_ticker',
-        return_value=DataFrame([{'buy': 0, 'sell': 1, 'date': arrow.utcnow()}])
-    )
-    assert _STRATEGY.get_signal('ETH/BTC', '5m', ticker_history) == (False, True)
-
-
-def test_returns_latest_sell_signal(mocker, default_conf, ticker_history):
-    mocker.patch.object(
-        _STRATEGY, 'analyze_ticker',
-        return_value=DataFrame([{'sell': 1, 'buy': 0, 'date': arrow.utcnow()}])
-    )
-
-    assert _STRATEGY.get_signal('ETH/BTC', '5m', ticker_history) == (False, True)
-
-    mocker.patch.object(
-        _STRATEGY, 'analyze_ticker',
-        return_value=DataFrame([{'sell': 0, 'buy': 1, 'date': arrow.utcnow()}])
-    )
-    assert _STRATEGY.get_signal('ETH/BTC', '5m', ticker_history) == (True, False)
-
-
-def test_get_signal_empty(default_conf, mocker, caplog):
-    assert (False, False) == _STRATEGY.get_signal('foo', default_conf['ticker_interval'],
-                                                  DataFrame())
-    assert log_has('Empty ticker history for pair foo', caplog.record_tuples)
-    caplog.clear()
-
-    assert (False, False) == _STRATEGY.get_signal('bar', default_conf['ticker_interval'],
-                                                  [])
-    assert log_has('Empty ticker history for pair bar', caplog.record_tuples)
-
-
-def test_get_signal_exception_valueerror(default_conf, mocker, caplog, ticker_history):
-    caplog.set_level(logging.INFO)
-    mocker.patch.object(
-        _STRATEGY, 'analyze_ticker',
-        side_effect=ValueError('xyz')
-    )
-    assert (False, False) == _STRATEGY.get_signal('foo', default_conf['ticker_interval'],
-                                                  ticker_history)
-    assert log_has('Unable to analyze ticker for pair foo: xyz', caplog.record_tuples)
-
-
-def test_get_signal_empty_dataframe(default_conf, mocker, caplog, ticker_history):
-    caplog.set_level(logging.INFO)
-    mocker.patch.object(
-        _STRATEGY, 'analyze_ticker',
-        return_value=DataFrame([])
-    )
-    assert (False, False) == _STRATEGY.get_signal('xyz', default_conf['ticker_interval'],
-                                                  ticker_history)
-    assert log_has('Empty dataframe for pair xyz', caplog.record_tuples)
-
-
-def test_get_signal_old_dataframe(default_conf, mocker, caplog, ticker_history):
-    caplog.set_level(logging.INFO)
-    # default_conf defines a 5m interval. we check interval * 2 + 5m
-    # this is necessary as the last candle is removed (partial candles) by default
-    oldtime = arrow.utcnow().shift(minutes=-16)
-    ticks = DataFrame([{'buy': 1, 'date': oldtime}])
-    mocker.patch.object(
-        _STRATEGY, 'analyze_ticker',
-        return_value=DataFrame(ticks)
-    )
-    assert (False, False) == _STRATEGY.get_signal('xyz', default_conf['ticker_interval'],
-                                                  ticker_history)
-    assert log_has(
-        'Outdated history for pair xyz. Last tick is 16 minutes old',
-        caplog.record_tuples
-    )
-
-
-def test_get_signal_handles_exceptions(mocker, default_conf):
-    exchange = get_patched_exchange(mocker, default_conf)
-    mocker.patch.object(
-        _STRATEGY, 'analyze_ticker',
-        side_effect=Exception('invalid ticker history ')
-    )
-    assert _STRATEGY.get_signal(exchange, 'ETH/BTC', '5m') == (False, False)
-
-
-def test_tickerdata_to_dataframe(default_conf) -> None:
-    strategy = DefaultStrategy(default_conf)
-
-    timerange = TimeRange(None, 'line', 0, -100)
-    tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m', timerange=timerange)
-    tickerlist = {'UNITTEST/BTC': parse_ticker_dataframe(tick, '1m', pair="UNITTEST/BTC",
-                                                         fill_missing=True)}
-    data = strategy.tickerdata_to_dataframe(tickerlist)
-    assert len(data['UNITTEST/BTC']) == 102       # partial candle was removed
-
-
-def test_min_roi_reached(default_conf, fee) -> None:
-
-    # Use list to confirm sequence does not matter
-    min_roi_list = [{20: 0.05, 55: 0.01, 0: 0.1},
-                    {0: 0.1, 20: 0.05, 55: 0.01}]
-    for roi in min_roi_list:
-        strategy = DefaultStrategy(default_conf)
-        strategy.minimal_roi = roi
-        trade = Trade(
-            pair='ETH/BTC',
-            stake_amount=0.001,
-            open_date=arrow.utcnow().shift(hours=-1).datetime,
-            fee_open=fee.return_value,
-            fee_close=fee.return_value,
-            exchange='bittrex',
-            open_rate=1,
-        )
-
-        assert not strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-56).datetime)
-        assert strategy.min_roi_reached(trade, 0.12, arrow.utcnow().shift(minutes=-56).datetime)
-
-        assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-39).datetime)
-        assert strategy.min_roi_reached(trade, 0.06, arrow.utcnow().shift(minutes=-39).datetime)
-
-        assert not strategy.min_roi_reached(trade, -0.01, arrow.utcnow().shift(minutes=-1).datetime)
-        assert strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-1).datetime)
-
-
-def test_min_roi_reached2(default_conf, fee) -> None:
-
-    # test with ROI raising after last interval
-    min_roi_list = [{20: 0.07,
-                     30: 0.05,
-                     55: 0.30,
-                     0: 0.1
-                     },
-                    {0: 0.1,
-                     20: 0.07,
-                     30: 0.05,
-                     55: 0.30
-                     },
-                    ]
-    for roi in min_roi_list:
-        strategy = DefaultStrategy(default_conf)
-        strategy.minimal_roi = roi
-        trade = Trade(
-            pair='ETH/BTC',
-            stake_amount=0.001,
-            open_date=arrow.utcnow().shift(hours=-1).datetime,
-            fee_open=fee.return_value,
-            fee_close=fee.return_value,
-            exchange='bittrex',
-            open_rate=1,
-        )
-
-        assert not strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-56).datetime)
-        assert strategy.min_roi_reached(trade, 0.12, arrow.utcnow().shift(minutes=-56).datetime)
-
-        assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-39).datetime)
-        assert strategy.min_roi_reached(trade, 0.071, arrow.utcnow().shift(minutes=-39).datetime)
-
-        assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-26).datetime)
-        assert strategy.min_roi_reached(trade, 0.06, arrow.utcnow().shift(minutes=-26).datetime)
-
-        # Should not trigger with 20% profit since after 55 minutes only 30% is active.
-        assert not strategy.min_roi_reached(trade, 0.20, arrow.utcnow().shift(minutes=-2).datetime)
-        assert strategy.min_roi_reached(trade, 0.31, arrow.utcnow().shift(minutes=-2).datetime)
-
-
-def test_min_roi_reached3(default_conf, fee) -> None:
-
-    # test for issue #1948
-    min_roi = {20: 0.07,
-               30: 0.05,
-               55: 0.30,
-               }
-    strategy = DefaultStrategy(default_conf)
-    strategy.minimal_roi = min_roi
-    trade = Trade(
-            pair='ETH/BTC',
-            stake_amount=0.001,
-            open_date=arrow.utcnow().shift(hours=-1).datetime,
-            fee_open=fee.return_value,
-            fee_close=fee.return_value,
-            exchange='bittrex',
-            open_rate=1,
-    )
-
-    assert not strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-56).datetime)
-    assert not strategy.min_roi_reached(trade, 0.12, arrow.utcnow().shift(minutes=-56).datetime)
-
-    assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-39).datetime)
-    assert strategy.min_roi_reached(trade, 0.071, arrow.utcnow().shift(minutes=-39).datetime)
-
-    assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-26).datetime)
-    assert strategy.min_roi_reached(trade, 0.06, arrow.utcnow().shift(minutes=-26).datetime)
-
-    # Should not trigger with 20% profit since after 55 minutes only 30% is active.
-    assert not strategy.min_roi_reached(trade, 0.20, arrow.utcnow().shift(minutes=-2).datetime)
-    assert strategy.min_roi_reached(trade, 0.31, arrow.utcnow().shift(minutes=-2).datetime)
-
-
-def test_analyze_ticker_default(ticker_history, mocker, caplog) -> None:
-    caplog.set_level(logging.DEBUG)
-    ind_mock = MagicMock(side_effect=lambda x, meta: x)
-    buy_mock = MagicMock(side_effect=lambda x, meta: x)
-    sell_mock = MagicMock(side_effect=lambda x, meta: x)
-    mocker.patch.multiple(
-        'freqtrade.strategy.interface.IStrategy',
-        advise_indicators=ind_mock,
-        advise_buy=buy_mock,
-        advise_sell=sell_mock,
-
-    )
-    strategy = DefaultStrategy({})
-    strategy.analyze_ticker(ticker_history, {'pair': 'ETH/BTC'})
-    assert ind_mock.call_count == 1
-    assert buy_mock.call_count == 1
-    assert buy_mock.call_count == 1
-
-    assert log_has('TA Analysis Launched', caplog.record_tuples)
-    assert not log_has('Skipping TA Analysis for already analyzed candle',
-                       caplog.record_tuples)
-    caplog.clear()
-
-    strategy.analyze_ticker(ticker_history, {'pair': 'ETH/BTC'})
-    # No analysis happens as process_only_new_candles is true
-    assert ind_mock.call_count == 2
-    assert buy_mock.call_count == 2
-    assert buy_mock.call_count == 2
-    assert log_has('TA Analysis Launched', caplog.record_tuples)
-    assert not log_has('Skipping TA Analysis for already analyzed candle',
-                       caplog.record_tuples)
-
-
-def test_analyze_ticker_skip_analyze(ticker_history, mocker, caplog) -> None:
-    caplog.set_level(logging.DEBUG)
-    ind_mock = MagicMock(side_effect=lambda x, meta: x)
-    buy_mock = MagicMock(side_effect=lambda x, meta: x)
-    sell_mock = MagicMock(side_effect=lambda x, meta: x)
-    mocker.patch.multiple(
-        'freqtrade.strategy.interface.IStrategy',
-        advise_indicators=ind_mock,
-        advise_buy=buy_mock,
-        advise_sell=sell_mock,
-
-    )
-    strategy = DefaultStrategy({})
-    strategy.process_only_new_candles = True
-
-    ret = strategy.analyze_ticker(ticker_history, {'pair': 'ETH/BTC'})
-    assert 'high' in ret.columns
-    assert 'low' in ret.columns
-    assert 'close' in ret.columns
-    assert isinstance(ret, DataFrame)
-    assert ind_mock.call_count == 1
-    assert buy_mock.call_count == 1
-    assert buy_mock.call_count == 1
-    assert log_has('TA Analysis Launched', caplog.record_tuples)
-    assert not log_has('Skipping TA Analysis for already analyzed candle',
-                       caplog.record_tuples)
-    caplog.clear()
-
-    ret = strategy.analyze_ticker(ticker_history, {'pair': 'ETH/BTC'})
-    # No analysis happens as process_only_new_candles is true
-    assert ind_mock.call_count == 1
-    assert buy_mock.call_count == 1
-    assert buy_mock.call_count == 1
-    # only skipped analyze adds buy and sell columns, otherwise it's all mocked
-    assert 'buy' in ret.columns
-    assert 'sell' in ret.columns
-    assert ret['buy'].sum() == 0
-    assert ret['sell'].sum() == 0
-    assert not log_has('TA Analysis Launched', caplog.record_tuples)
-    assert log_has('Skipping TA Analysis for already analyzed candle',
-                   caplog.record_tuples)
diff --git a/freqtrade/tests/strategy/test_strategy.py b/freqtrade/tests/strategy/test_strategy.py
deleted file mode 100644
index 609cc58ff..000000000
--- a/freqtrade/tests/strategy/test_strategy.py
+++ /dev/null
@@ -1,422 +0,0 @@
-# pragma pylint: disable=missing-docstring, protected-access, C0103
-import logging
-import tempfile
-import warnings
-from base64 import urlsafe_b64encode
-from os import path
-from pathlib import Path
-from unittest.mock import Mock
-
-import pytest
-from pandas import DataFrame
-
-from freqtrade import OperationalException
-from freqtrade.resolvers import StrategyResolver
-from freqtrade.strategy import import_strategy
-from freqtrade.strategy.default_strategy import DefaultStrategy
-from freqtrade.strategy.interface import IStrategy
-from freqtrade.tests.conftest import log_has_re
-
-
-def test_import_strategy(caplog):
-    caplog.set_level(logging.DEBUG)
-    default_config = {}
-
-    strategy = DefaultStrategy(default_config)
-    strategy.some_method = lambda *args, **kwargs: 42
-
-    assert strategy.__module__ == 'freqtrade.strategy.default_strategy'
-    assert strategy.some_method() == 42
-
-    imported_strategy = import_strategy(strategy, default_config)
-
-    assert dir(strategy) == dir(imported_strategy)
-
-    assert imported_strategy.__module__ == 'freqtrade.strategy'
-    assert imported_strategy.some_method() == 42
-
-    assert (
-        'freqtrade.strategy',
-        logging.DEBUG,
-        'Imported strategy freqtrade.strategy.default_strategy.DefaultStrategy '
-        'as freqtrade.strategy.DefaultStrategy',
-    ) in caplog.record_tuples
-
-
-def test_search_strategy():
-    default_config = {}
-    default_location = Path(__file__).parent.parent.parent.joinpath('strategy').resolve()
-
-    s, _ = StrategyResolver._search_object(
-        directory=default_location,
-        object_type=IStrategy,
-        kwargs={'config': default_config},
-        object_name='DefaultStrategy'
-    )
-    assert isinstance(s, IStrategy)
-
-    s, _ = StrategyResolver._search_object(
-        directory=default_location,
-        object_type=IStrategy,
-        kwargs={'config': default_config},
-        object_name='NotFoundStrategy'
-    )
-    assert s is None
-
-
-def test_load_strategy(result):
-    resolver = StrategyResolver({'strategy': 'TestStrategy'})
-    assert 'adx' in resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
-
-
-def test_load_strategy_base64(result, caplog):
-    with open("user_data/strategies/test_strategy.py", "rb") as file:
-        encoded_string = urlsafe_b64encode(file.read()).decode("utf-8")
-    resolver = StrategyResolver({'strategy': 'TestStrategy:{}'.format(encoded_string)})
-    assert 'adx' in resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
-    # Make sure strategy was loaded from base64 (using temp directory)!!
-    assert log_has_re(r"Using resolved strategy TestStrategy from '"
-                      + tempfile.gettempdir() + r"/.*/TestStrategy\.py'\.\.\.",
-                      caplog.record_tuples)
-
-
-def test_load_strategy_invalid_directory(result, caplog):
-    resolver = StrategyResolver()
-    extra_dir = Path.cwd() / 'some/path'
-    resolver._load_strategy('TestStrategy', config={}, extra_dir=extra_dir)
-
-    assert log_has_re(r'Path .*' + r'some.*path.*' + r'.* does not exist', caplog.record_tuples)
-
-    assert 'adx' in resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
-
-
-def test_load_not_found_strategy():
-    strategy = StrategyResolver()
-    with pytest.raises(OperationalException,
-                       match=r"Impossible to load Strategy 'NotFoundStrategy'. "
-                             r"This class does not exist or contains Python code errors."):
-        strategy._load_strategy(strategy_name='NotFoundStrategy', config={})
-
-
-def test_load_staticmethod_importerror(mocker, caplog):
-    mocker.patch("freqtrade.resolvers.strategy_resolver.import_strategy", Mock(
-        side_effect=TypeError("can't pickle staticmethod objects")))
-    with pytest.raises(OperationalException,
-                       match=r"Impossible to load Strategy 'DefaultStrategy'. "
-                             r"This class does not exist or contains Python code errors."):
-        StrategyResolver()
-    assert log_has_re(r".*Error: can't pickle staticmethod objects", caplog.record_tuples)
-
-
-def test_strategy(result):
-    config = {'strategy': 'DefaultStrategy'}
-
-    resolver = StrategyResolver(config)
-    metadata = {'pair': 'ETH/BTC'}
-    assert resolver.strategy.minimal_roi[0] == 0.04
-    assert config["minimal_roi"]['0'] == 0.04
-
-    assert resolver.strategy.stoploss == -0.10
-    assert config['stoploss'] == -0.10
-
-    assert resolver.strategy.ticker_interval == '5m'
-    assert config['ticker_interval'] == '5m'
-
-    df_indicators = resolver.strategy.advise_indicators(result, metadata=metadata)
-    assert 'adx' in df_indicators
-
-    dataframe = resolver.strategy.advise_buy(df_indicators, metadata=metadata)
-    assert 'buy' in dataframe.columns
-
-    dataframe = resolver.strategy.advise_sell(df_indicators, metadata=metadata)
-    assert 'sell' in dataframe.columns
-
-
-def test_strategy_override_minimal_roi(caplog):
-    caplog.set_level(logging.INFO)
-    config = {
-        'strategy': 'DefaultStrategy',
-        'minimal_roi': {
-            "0": 0.5
-        }
-    }
-    resolver = StrategyResolver(config)
-
-    assert resolver.strategy.minimal_roi[0] == 0.5
-    assert ('freqtrade.resolvers.strategy_resolver',
-            logging.INFO,
-            "Override strategy 'minimal_roi' with value in config file: {'0': 0.5}."
-            ) in caplog.record_tuples
-
-
-def test_strategy_override_stoploss(caplog):
-    caplog.set_level(logging.INFO)
-    config = {
-        'strategy': 'DefaultStrategy',
-        'stoploss': -0.5
-    }
-    resolver = StrategyResolver(config)
-
-    assert resolver.strategy.stoploss == -0.5
-    assert ('freqtrade.resolvers.strategy_resolver',
-            logging.INFO,
-            "Override strategy 'stoploss' with value in config file: -0.5."
-            ) in caplog.record_tuples
-
-
-def test_strategy_override_trailing_stop(caplog):
-    caplog.set_level(logging.INFO)
-    config = {
-        'strategy': 'DefaultStrategy',
-        'trailing_stop': True
-    }
-    resolver = StrategyResolver(config)
-
-    assert resolver.strategy.trailing_stop
-    assert isinstance(resolver.strategy.trailing_stop, bool)
-    assert ('freqtrade.resolvers.strategy_resolver',
-            logging.INFO,
-            "Override strategy 'trailing_stop' with value in config file: True."
-            ) in caplog.record_tuples
-
-
-def test_strategy_override_trailing_stop_positive(caplog):
-    caplog.set_level(logging.INFO)
-    config = {
-        'strategy': 'DefaultStrategy',
-        'trailing_stop_positive': -0.1,
-        'trailing_stop_positive_offset': -0.2
-
-    }
-    resolver = StrategyResolver(config)
-
-    assert resolver.strategy.trailing_stop_positive == -0.1
-    assert ('freqtrade.resolvers.strategy_resolver',
-            logging.INFO,
-            "Override strategy 'trailing_stop_positive' with value in config file: -0.1."
-            ) in caplog.record_tuples
-
-    assert resolver.strategy.trailing_stop_positive_offset == -0.2
-    assert ('freqtrade.resolvers.strategy_resolver',
-            logging.INFO,
-            "Override strategy 'trailing_stop_positive' with value in config file: -0.1."
-            ) in caplog.record_tuples
-
-
-def test_strategy_override_ticker_interval(caplog):
-    caplog.set_level(logging.INFO)
-
-    config = {
-        'strategy': 'DefaultStrategy',
-        'ticker_interval': 60,
-        'stake_currency': 'ETH'
-    }
-    resolver = StrategyResolver(config)
-
-    assert resolver.strategy.ticker_interval == 60
-    assert resolver.strategy.stake_currency == 'ETH'
-    assert ('freqtrade.resolvers.strategy_resolver',
-            logging.INFO,
-            "Override strategy 'ticker_interval' with value in config file: 60."
-            ) in caplog.record_tuples
-
-
-def test_strategy_override_process_only_new_candles(caplog):
-    caplog.set_level(logging.INFO)
-
-    config = {
-        'strategy': 'DefaultStrategy',
-        'process_only_new_candles': True
-    }
-    resolver = StrategyResolver(config)
-
-    assert resolver.strategy.process_only_new_candles
-    assert ('freqtrade.resolvers.strategy_resolver',
-            logging.INFO,
-            "Override strategy 'process_only_new_candles' with value in config file: True."
-            ) in caplog.record_tuples
-
-
-def test_strategy_override_order_types(caplog):
-    caplog.set_level(logging.INFO)
-
-    order_types = {
-        'buy': 'market',
-        'sell': 'limit',
-        'stoploss': 'limit',
-        'stoploss_on_exchange': True,
-    }
-
-    config = {
-        'strategy': 'DefaultStrategy',
-        'order_types': order_types
-    }
-    resolver = StrategyResolver(config)
-
-    assert resolver.strategy.order_types
-    for method in ['buy', 'sell', 'stoploss', 'stoploss_on_exchange']:
-        assert resolver.strategy.order_types[method] == order_types[method]
-
-    assert ('freqtrade.resolvers.strategy_resolver',
-            logging.INFO,
-            "Override strategy 'order_types' with value in config file:"
-            " {'buy': 'market', 'sell': 'limit', 'stoploss': 'limit',"
-            " 'stoploss_on_exchange': True}."
-            ) in caplog.record_tuples
-
-    config = {
-        'strategy': 'DefaultStrategy',
-        'order_types': {'buy': 'market'}
-    }
-    # Raise error for invalid configuration
-    with pytest.raises(ImportError,
-                       match=r"Impossible to load Strategy 'DefaultStrategy'. "
-                             r"Order-types mapping is incomplete."):
-        StrategyResolver(config)
-
-
-def test_strategy_override_order_tif(caplog):
-    caplog.set_level(logging.INFO)
-
-    order_time_in_force = {
-        'buy': 'fok',
-        'sell': 'gtc',
-    }
-
-    config = {
-        'strategy': 'DefaultStrategy',
-        'order_time_in_force': order_time_in_force
-    }
-    resolver = StrategyResolver(config)
-
-    assert resolver.strategy.order_time_in_force
-    for method in ['buy', 'sell']:
-        assert resolver.strategy.order_time_in_force[method] == order_time_in_force[method]
-
-    assert ('freqtrade.resolvers.strategy_resolver',
-            logging.INFO,
-            "Override strategy 'order_time_in_force' with value in config file:"
-            " {'buy': 'fok', 'sell': 'gtc'}."
-            ) in caplog.record_tuples
-
-    config = {
-        'strategy': 'DefaultStrategy',
-        'order_time_in_force': {'buy': 'fok'}
-    }
-    # Raise error for invalid configuration
-    with pytest.raises(ImportError,
-                       match=r"Impossible to load Strategy 'DefaultStrategy'. "
-                             r"Order-time-in-force mapping is incomplete."):
-        StrategyResolver(config)
-
-
-def test_strategy_override_use_sell_signal(caplog):
-    caplog.set_level(logging.INFO)
-    config = {
-        'strategy': 'DefaultStrategy',
-    }
-    resolver = StrategyResolver(config)
-    assert not resolver.strategy.use_sell_signal
-    assert isinstance(resolver.strategy.use_sell_signal, bool)
-    # must be inserted to configuration
-    assert 'use_sell_signal' in config['experimental']
-    assert not config['experimental']['use_sell_signal']
-
-    config = {
-        'strategy': 'DefaultStrategy',
-        'experimental': {
-            'use_sell_signal': True,
-        },
-    }
-    resolver = StrategyResolver(config)
-
-    assert resolver.strategy.use_sell_signal
-    assert isinstance(resolver.strategy.use_sell_signal, bool)
-    assert ('freqtrade.resolvers.strategy_resolver',
-            logging.INFO,
-            "Override strategy 'use_sell_signal' with value in config file: True."
-            ) in caplog.record_tuples
-
-
-def test_strategy_override_use_sell_profit_only(caplog):
-    caplog.set_level(logging.INFO)
-    config = {
-        'strategy': 'DefaultStrategy',
-    }
-    resolver = StrategyResolver(config)
-    assert not resolver.strategy.sell_profit_only
-    assert isinstance(resolver.strategy.sell_profit_only, bool)
-    # must be inserted to configuration
-    assert 'sell_profit_only' in config['experimental']
-    assert not config['experimental']['sell_profit_only']
-
-    config = {
-        'strategy': 'DefaultStrategy',
-        'experimental': {
-            'sell_profit_only': True,
-        },
-    }
-    resolver = StrategyResolver(config)
-
-    assert resolver.strategy.sell_profit_only
-    assert isinstance(resolver.strategy.sell_profit_only, bool)
-    assert ('freqtrade.resolvers.strategy_resolver',
-            logging.INFO,
-            "Override strategy 'sell_profit_only' with value in config file: True."
-            ) in caplog.record_tuples
-
-
-def test_deprecate_populate_indicators(result):
-    default_location = path.join(path.dirname(path.realpath(__file__)))
-    resolver = StrategyResolver({'strategy': 'TestStrategyLegacy',
-                                 'strategy_path': default_location})
-    with warnings.catch_warnings(record=True) as w:
-        # Cause all warnings to always be triggered.
-        warnings.simplefilter("always")
-        indicators = resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
-        assert len(w) == 1
-        assert issubclass(w[-1].category, DeprecationWarning)
-        assert "deprecated - check out the Sample strategy to see the current function headers!" \
-            in str(w[-1].message)
-
-    with warnings.catch_warnings(record=True) as w:
-        # Cause all warnings to always be triggered.
-        warnings.simplefilter("always")
-        resolver.strategy.advise_buy(indicators, {'pair': 'ETH/BTC'})
-        assert len(w) == 1
-        assert issubclass(w[-1].category, DeprecationWarning)
-        assert "deprecated - check out the Sample strategy to see the current function headers!" \
-            in str(w[-1].message)
-
-    with warnings.catch_warnings(record=True) as w:
-        # Cause all warnings to always be triggered.
-        warnings.simplefilter("always")
-        resolver.strategy.advise_sell(indicators, {'pair': 'ETH_BTC'})
-        assert len(w) == 1
-        assert issubclass(w[-1].category, DeprecationWarning)
-        assert "deprecated - check out the Sample strategy to see the current function headers!" \
-            in str(w[-1].message)
-
-
-def test_call_deprecated_function(result, monkeypatch):
-    default_location = path.join(path.dirname(path.realpath(__file__)))
-    resolver = StrategyResolver({'strategy': 'TestStrategyLegacy',
-                                 'strategy_path': default_location})
-    metadata = {'pair': 'ETH/BTC'}
-
-    # Make sure we are using a legacy function
-    assert resolver.strategy._populate_fun_len == 2
-    assert resolver.strategy._buy_fun_len == 2
-    assert resolver.strategy._sell_fun_len == 2
-
-    indicator_df = resolver.strategy.advise_indicators(result, metadata=metadata)
-    assert isinstance(indicator_df, DataFrame)
-    assert 'adx' in indicator_df.columns
-
-    buydf = resolver.strategy.advise_buy(result, metadata=metadata)
-    assert isinstance(buydf, DataFrame)
-    assert 'buy' in buydf.columns
-
-    selldf = resolver.strategy.advise_sell(result, metadata=metadata)
-    assert isinstance(selldf, DataFrame)
-    assert 'sell' in selldf
diff --git a/freqtrade/tests/test_arguments.py b/freqtrade/tests/test_arguments.py
deleted file mode 100644
index 3de71a621..000000000
--- a/freqtrade/tests/test_arguments.py
+++ /dev/null
@@ -1,207 +0,0 @@
-# pragma pylint: disable=missing-docstring, C0103
-import argparse
-
-import pytest
-
-from freqtrade.configuration import Arguments, TimeRange
-from freqtrade.configuration.arguments import ARGS_DOWNLOADER, ARGS_PLOT_DATAFRAME
-from freqtrade.configuration.arguments import check_int_positive
-
-
-# Parse common command-line-arguments. Used for all tools
-def test_parse_args_none() -> None:
-    arguments = Arguments([], '')
-    assert isinstance(arguments, Arguments)
-    assert isinstance(arguments.parser, argparse.ArgumentParser)
-
-
-def test_parse_args_defaults() -> None:
-    args = Arguments([], '').get_parsed_arg()
-    assert args.config == ['config.json']
-    assert args.strategy_path is None
-    assert args.datadir is None
-    assert args.verbosity == 0
-
-
-def test_parse_args_config() -> None:
-    args = Arguments(['-c', '/dev/null'], '').get_parsed_arg()
-    assert args.config == ['/dev/null']
-
-    args = Arguments(['--config', '/dev/null'], '').get_parsed_arg()
-    assert args.config == ['/dev/null']
-
-    args = Arguments(['--config', '/dev/null',
-                      '--config', '/dev/zero'],
-                     '').get_parsed_arg()
-    assert args.config == ['/dev/null', '/dev/zero']
-
-
-def test_parse_args_db_url() -> None:
-    args = Arguments(['--db-url', 'sqlite:///test.sqlite'], '').get_parsed_arg()
-    assert args.db_url == 'sqlite:///test.sqlite'
-
-
-def test_parse_args_verbose() -> None:
-    args = Arguments(['-v'], '').get_parsed_arg()
-    assert args.verbosity == 1
-
-    args = Arguments(['--verbose'], '').get_parsed_arg()
-    assert args.verbosity == 1
-
-
-def test_common_scripts_options() -> None:
-    arguments = Arguments(['-p', 'ETH/BTC'], '')
-    arguments._build_args(ARGS_DOWNLOADER)
-    args = arguments._parse_args()
-    assert args.pairs == 'ETH/BTC'
-
-
-def test_parse_args_version() -> None:
-    with pytest.raises(SystemExit, match=r'0'):
-        Arguments(['--version'], '').get_parsed_arg()
-
-
-def test_parse_args_invalid() -> None:
-    with pytest.raises(SystemExit, match=r'2'):
-        Arguments(['-c'], '').get_parsed_arg()
-
-
-def test_parse_args_strategy() -> None:
-    args = Arguments(['--strategy', 'SomeStrategy'], '').get_parsed_arg()
-    assert args.strategy == 'SomeStrategy'
-
-
-def test_parse_args_strategy_invalid() -> None:
-    with pytest.raises(SystemExit, match=r'2'):
-        Arguments(['--strategy'], '').get_parsed_arg()
-
-
-def test_parse_args_strategy_path() -> None:
-    args = Arguments(['--strategy-path', '/some/path'], '').get_parsed_arg()
-    assert args.strategy_path == '/some/path'
-
-
-def test_parse_args_strategy_path_invalid() -> None:
-    with pytest.raises(SystemExit, match=r'2'):
-        Arguments(['--strategy-path'], '').get_parsed_arg()
-
-
-def test_parse_timerange_incorrect() -> None:
-    assert TimeRange(None, 'line', 0, -200) == Arguments.parse_timerange('-200')
-    assert TimeRange('line', None, 200, 0) == Arguments.parse_timerange('200-')
-    assert TimeRange('index', 'index', 200, 500) == Arguments.parse_timerange('200-500')
-
-    assert TimeRange('date', None, 1274486400, 0) == Arguments.parse_timerange('20100522-')
-    assert TimeRange(None, 'date', 0, 1274486400) == Arguments.parse_timerange('-20100522')
-    timerange = Arguments.parse_timerange('20100522-20150730')
-    assert timerange == TimeRange('date', 'date', 1274486400, 1438214400)
-
-    # Added test for unix timestamp - BTC genesis date
-    assert TimeRange('date', None, 1231006505, 0) == Arguments.parse_timerange('1231006505-')
-    assert TimeRange(None, 'date', 0, 1233360000) == Arguments.parse_timerange('-1233360000')
-    timerange = Arguments.parse_timerange('1231006505-1233360000')
-    assert TimeRange('date', 'date', 1231006505, 1233360000) == timerange
-
-    # TODO: Find solution for the following case (passing timestamp in ms)
-    timerange = Arguments.parse_timerange('1231006505000-1233360000000')
-    assert TimeRange('date', 'date', 1231006505, 1233360000) != timerange
-
-    with pytest.raises(Exception, match=r'Incorrect syntax.*'):
-        Arguments.parse_timerange('-')
-
-
-def test_parse_args_backtesting_invalid() -> None:
-    with pytest.raises(SystemExit, match=r'2'):
-        Arguments(['backtesting --ticker-interval'], '').get_parsed_arg()
-
-    with pytest.raises(SystemExit, match=r'2'):
-        Arguments(['backtesting --ticker-interval', 'abc'], '').get_parsed_arg()
-
-
-def test_parse_args_backtesting_custom() -> None:
-    args = [
-        '-c', 'test_conf.json',
-        'backtesting',
-        '--live',
-        '--ticker-interval', '1m',
-        '--refresh-pairs-cached',
-        '--strategy-list',
-        'DefaultStrategy',
-        'TestStrategy'
-        ]
-    call_args = Arguments(args, '').get_parsed_arg()
-    assert call_args.config == ['test_conf.json']
-    assert call_args.live is True
-    assert call_args.verbosity == 0
-    assert call_args.subparser == 'backtesting'
-    assert call_args.func is not None
-    assert call_args.ticker_interval == '1m'
-    assert call_args.refresh_pairs is True
-    assert type(call_args.strategy_list) is list
-    assert len(call_args.strategy_list) == 2
-
-
-def test_parse_args_hyperopt_custom() -> None:
-    args = [
-        '-c', 'test_conf.json',
-        'hyperopt',
-        '--epochs', '20',
-        '--spaces', 'buy'
-    ]
-    call_args = Arguments(args, '').get_parsed_arg()
-    assert call_args.config == ['test_conf.json']
-    assert call_args.epochs == 20
-    assert call_args.verbosity == 0
-    assert call_args.subparser == 'hyperopt'
-    assert call_args.spaces == ['buy']
-    assert call_args.func is not None
-
-
-def test_download_data_options() -> None:
-    args = [
-        '--pairs-file', 'file_with_pairs',
-        '--datadir', 'datadir/directory',
-        '--days', '30',
-        '--exchange', 'binance'
-    ]
-    arguments = Arguments(args, '')
-    arguments._build_args(ARGS_DOWNLOADER)
-    args = arguments._parse_args()
-    assert args.pairs_file == 'file_with_pairs'
-    assert args.datadir == 'datadir/directory'
-    assert args.days == 30
-    assert args.exchange == 'binance'
-
-
-def test_plot_dataframe_options() -> None:
-    args = [
-        '--indicators1', 'sma10,sma100',
-        '--indicators2', 'macd,fastd,fastk',
-        '--plot-limit', '30',
-        '-p', 'UNITTEST/BTC',
-    ]
-    arguments = Arguments(args, '')
-    arguments._build_args(ARGS_PLOT_DATAFRAME)
-    pargs = arguments._parse_args()
-    assert pargs.indicators1 == "sma10,sma100"
-    assert pargs.indicators2 == "macd,fastd,fastk"
-    assert pargs.plot_limit == 30
-    assert pargs.pairs == "UNITTEST/BTC"
-
-
-def test_check_int_positive() -> None:
-    assert check_int_positive("3") == 3
-    assert check_int_positive("1") == 1
-    assert check_int_positive("100") == 100
-
-    with pytest.raises(argparse.ArgumentTypeError):
-        check_int_positive("-2")
-
-    with pytest.raises(argparse.ArgumentTypeError):
-        check_int_positive("0")
-
-    with pytest.raises(argparse.ArgumentTypeError):
-        check_int_positive("3.5")
-
-    with pytest.raises(argparse.ArgumentTypeError):
-        check_int_positive("DeadBeef")
diff --git a/freqtrade/tests/test_configuration.py b/freqtrade/tests/test_configuration.py
deleted file mode 100644
index d3567e943..000000000
--- a/freqtrade/tests/test_configuration.py
+++ /dev/null
@@ -1,661 +0,0 @@
-# pragma pylint: disable=missing-docstring, protected-access, invalid-name
-import json
-import logging
-from argparse import Namespace
-from copy import deepcopy
-from unittest.mock import MagicMock
-from pathlib import Path
-
-import pytest
-from jsonschema import Draft4Validator, ValidationError, validate
-
-from freqtrade import OperationalException, constants
-from freqtrade.configuration import Arguments, Configuration
-from freqtrade.configuration.check_exchange import check_exchange
-from freqtrade.configuration.create_datadir import create_datadir
-from freqtrade.configuration.json_schema import validate_config_schema
-from freqtrade.constants import DEFAULT_DB_DRYRUN_URL, DEFAULT_DB_PROD_URL
-from freqtrade.loggers import _set_loggers
-from freqtrade.state import RunMode
-from freqtrade.tests.conftest import (log_has, log_has_re,
-                                      patched_configuration_load_config_file)
-
-
-@pytest.fixture(scope="function")
-def all_conf():
-    config_file = Path(__file__).parents[2] / "config_full.json.example"
-    print(config_file)
-    configuration = Configuration(Namespace())
-    conf = configuration._load_config_file(str(config_file))
-    return conf
-
-
-def test_load_config_invalid_pair(default_conf) -> None:
-    default_conf['exchange']['pair_whitelist'].append('ETH-BTC')
-
-    with pytest.raises(ValidationError, match=r'.*does not match.*'):
-        validate_config_schema(default_conf)
-
-
-def test_load_config_missing_attributes(default_conf) -> None:
-    default_conf.pop('exchange')
-
-    with pytest.raises(ValidationError, match=r'.*\'exchange\' is a required property.*'):
-        validate_config_schema(default_conf)
-
-
-def test_load_config_incorrect_stake_amount(default_conf) -> None:
-    default_conf['stake_amount'] = 'fake'
-
-    with pytest.raises(ValidationError, match=r'.*\'fake\' does not match \'unlimited\'.*'):
-        validate_config_schema(default_conf)
-
-
-def test_load_config_file(default_conf, mocker, caplog) -> None:
-    file_mock = mocker.patch('freqtrade.configuration.configuration.open', mocker.mock_open(
-        read_data=json.dumps(default_conf)
-    ))
-
-    configuration = Configuration(Namespace())
-    validated_conf = configuration._load_config_file('somefile')
-    assert file_mock.call_count == 1
-    assert validated_conf.items() >= default_conf.items()
-
-
-def test_load_config_max_open_trades_zero(default_conf, mocker, caplog) -> None:
-    default_conf['max_open_trades'] = 0
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    args = Arguments([], '').get_parsed_arg()
-    configuration = Configuration(args)
-    validated_conf = configuration.load_config()
-
-    assert validated_conf['max_open_trades'] == 0
-    assert 'internals' in validated_conf
-    assert log_has('Validating configuration ...', caplog.record_tuples)
-
-
-def test_load_config_combine_dicts(default_conf, mocker, caplog) -> None:
-    conf1 = deepcopy(default_conf)
-    conf2 = deepcopy(default_conf)
-    del conf1['exchange']['key']
-    del conf1['exchange']['secret']
-    del conf2['exchange']['name']
-    conf2['exchange']['pair_whitelist'] += ['NANO/BTC']
-
-    config_files = [conf1, conf2]
-
-    configsmock = MagicMock(side_effect=config_files)
-    mocker.patch(
-        'freqtrade.configuration.configuration.Configuration._load_config_file',
-        configsmock
-    )
-
-    arg_list = ['-c', 'test_conf.json', '--config', 'test2_conf.json', ]
-    args = Arguments(arg_list, '').get_parsed_arg()
-    configuration = Configuration(args)
-    validated_conf = configuration.load_config()
-
-    exchange_conf = default_conf['exchange']
-    assert validated_conf['exchange']['name'] == exchange_conf['name']
-    assert validated_conf['exchange']['key'] == exchange_conf['key']
-    assert validated_conf['exchange']['secret'] == exchange_conf['secret']
-    assert validated_conf['exchange']['pair_whitelist'] != conf1['exchange']['pair_whitelist']
-    assert validated_conf['exchange']['pair_whitelist'] == conf2['exchange']['pair_whitelist']
-
-    assert 'internals' in validated_conf
-    assert log_has('Validating configuration ...', caplog.record_tuples)
-
-
-def test_load_config_max_open_trades_minus_one(default_conf, mocker, caplog) -> None:
-    default_conf['max_open_trades'] = -1
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    args = Arguments([], '').get_parsed_arg()
-    configuration = Configuration(args)
-    validated_conf = configuration.load_config()
-
-    assert validated_conf['max_open_trades'] > 999999999
-    assert validated_conf['max_open_trades'] == float('inf')
-    assert log_has('Validating configuration ...', caplog.record_tuples)
-    assert "runmode" in validated_conf
-    assert validated_conf['runmode'] == RunMode.DRY_RUN
-
-
-def test_load_config_file_exception(mocker) -> None:
-    mocker.patch(
-        'freqtrade.configuration.configuration.open',
-        MagicMock(side_effect=FileNotFoundError('File not found'))
-    )
-    configuration = Configuration(Namespace())
-
-    with pytest.raises(OperationalException, match=r'.*Config file "somefile" not found!*'):
-        configuration._load_config_file('somefile')
-
-
-def test_load_config(default_conf, mocker) -> None:
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    args = Arguments([], '').get_parsed_arg()
-    configuration = Configuration(args)
-    validated_conf = configuration.load_config()
-
-    assert validated_conf.get('strategy') == 'DefaultStrategy'
-    assert validated_conf.get('strategy_path') is None
-    assert 'edge' not in validated_conf
-
-
-def test_load_config_with_params(default_conf, mocker) -> None:
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    arglist = [
-        '--strategy', 'TestStrategy',
-        '--strategy-path', '/some/path',
-        '--db-url', 'sqlite:///someurl',
-    ]
-    args = Arguments(arglist, '').get_parsed_arg()
-    configuration = Configuration(args)
-    validated_conf = configuration.load_config()
-
-    assert validated_conf.get('strategy') == 'TestStrategy'
-    assert validated_conf.get('strategy_path') == '/some/path'
-    assert validated_conf.get('db_url') == 'sqlite:///someurl'
-
-    # Test conf provided db_url prod
-    conf = default_conf.copy()
-    conf["dry_run"] = False
-    conf["db_url"] = "sqlite:///path/to/db.sqlite"
-    patched_configuration_load_config_file(mocker, conf)
-
-    arglist = [
-        '--strategy', 'TestStrategy',
-        '--strategy-path', '/some/path'
-    ]
-    args = Arguments(arglist, '').get_parsed_arg()
-
-    configuration = Configuration(args)
-    validated_conf = configuration.load_config()
-    assert validated_conf.get('db_url') == "sqlite:///path/to/db.sqlite"
-
-    # Test conf provided db_url dry_run
-    conf = default_conf.copy()
-    conf["dry_run"] = True
-    conf["db_url"] = "sqlite:///path/to/db.sqlite"
-    patched_configuration_load_config_file(mocker, conf)
-
-    arglist = [
-        '--strategy', 'TestStrategy',
-        '--strategy-path', '/some/path'
-    ]
-    args = Arguments(arglist, '').get_parsed_arg()
-
-    configuration = Configuration(args)
-    validated_conf = configuration.load_config()
-    assert validated_conf.get('db_url') == "sqlite:///path/to/db.sqlite"
-
-    # Test args provided db_url prod
-    conf = default_conf.copy()
-    conf["dry_run"] = False
-    del conf["db_url"]
-    patched_configuration_load_config_file(mocker, conf)
-
-    arglist = [
-        '--strategy', 'TestStrategy',
-        '--strategy-path', '/some/path'
-    ]
-    args = Arguments(arglist, '').get_parsed_arg()
-
-    configuration = Configuration(args)
-    validated_conf = configuration.load_config()
-    assert validated_conf.get('db_url') == DEFAULT_DB_PROD_URL
-    assert "runmode" in validated_conf
-    assert validated_conf['runmode'] == RunMode.LIVE
-
-    # Test args provided db_url dry_run
-    conf = default_conf.copy()
-    conf["dry_run"] = True
-    conf["db_url"] = DEFAULT_DB_PROD_URL
-    patched_configuration_load_config_file(mocker, conf)
-
-    arglist = [
-        '--strategy', 'TestStrategy',
-        '--strategy-path', '/some/path'
-    ]
-    args = Arguments(arglist, '').get_parsed_arg()
-
-    configuration = Configuration(args)
-    validated_conf = configuration.load_config()
-    assert validated_conf.get('db_url') == DEFAULT_DB_DRYRUN_URL
-
-
-def test_load_custom_strategy(default_conf, mocker) -> None:
-    default_conf.update({
-        'strategy': 'CustomStrategy',
-        'strategy_path': '/tmp/strategies',
-    })
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    args = Arguments([], '').get_parsed_arg()
-    configuration = Configuration(args)
-    validated_conf = configuration.load_config()
-
-    assert validated_conf.get('strategy') == 'CustomStrategy'
-    assert validated_conf.get('strategy_path') == '/tmp/strategies'
-
-
-def test_show_info(default_conf, mocker, caplog) -> None:
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    arglist = [
-        '--strategy', 'TestStrategy',
-        '--db-url', 'sqlite:///tmp/testdb',
-    ]
-    args = Arguments(arglist, '').get_parsed_arg()
-
-    configuration = Configuration(args)
-    configuration.get_config()
-
-    assert log_has('Using DB: "sqlite:///tmp/testdb"', caplog.record_tuples)
-    assert log_has('Dry run is enabled', caplog.record_tuples)
-
-
-def test_setup_configuration_without_arguments(mocker, default_conf, caplog) -> None:
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    arglist = [
-        '--config', 'config.json',
-        '--strategy', 'DefaultStrategy',
-        'backtesting'
-    ]
-
-    args = Arguments(arglist, '').get_parsed_arg()
-
-    configuration = Configuration(args)
-    config = configuration.get_config()
-    assert 'max_open_trades' in config
-    assert 'stake_currency' in config
-    assert 'stake_amount' in config
-    assert 'exchange' in config
-    assert 'pair_whitelist' in config['exchange']
-    assert 'datadir' in config
-    assert log_has(
-        'Using data directory: {} ...'.format(config['datadir']),
-        caplog.record_tuples
-    )
-    assert 'ticker_interval' in config
-    assert not log_has('Parameter -i/--ticker-interval detected ...', caplog.record_tuples)
-
-    assert 'live' not in config
-    assert not log_has('Parameter -l/--live detected ...', caplog.record_tuples)
-
-    assert 'position_stacking' not in config
-    assert not log_has('Parameter --enable-position-stacking detected ...', caplog.record_tuples)
-
-    assert 'refresh_pairs' not in config
-    assert not log_has('Parameter -r/--refresh-pairs-cached detected ...', caplog.record_tuples)
-
-    assert 'timerange' not in config
-    assert 'export' not in config
-
-
-def test_setup_configuration_with_arguments(mocker, default_conf, caplog) -> None:
-    patched_configuration_load_config_file(mocker, default_conf)
-    mocker.patch(
-        'freqtrade.configuration.configuration.create_datadir',
-        lambda c, x: x
-    )
-
-    arglist = [
-        '--config', 'config.json',
-        '--strategy', 'DefaultStrategy',
-        '--datadir', '/foo/bar',
-        'backtesting',
-        '--ticker-interval', '1m',
-        '--live',
-        '--enable-position-stacking',
-        '--disable-max-market-positions',
-        '--refresh-pairs-cached',
-        '--timerange', ':100',
-        '--export', '/bar/foo'
-    ]
-
-    args = Arguments(arglist, '').get_parsed_arg()
-
-    configuration = Configuration(args)
-    config = configuration.get_config()
-    assert 'max_open_trades' in config
-    assert 'stake_currency' in config
-    assert 'stake_amount' in config
-    assert 'exchange' in config
-    assert 'pair_whitelist' in config['exchange']
-    assert 'datadir' in config
-    assert log_has(
-        'Using data directory: {} ...'.format(config['datadir']),
-        caplog.record_tuples
-    )
-    assert 'ticker_interval' in config
-    assert log_has('Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
-                   caplog.record_tuples)
-
-    assert 'live' in config
-    assert log_has('Parameter -l/--live detected ...', caplog.record_tuples)
-
-    assert 'position_stacking'in config
-    assert log_has('Parameter --enable-position-stacking detected ...', caplog.record_tuples)
-
-    assert 'use_max_market_positions' in config
-    assert log_has('Parameter --disable-max-market-positions detected ...', caplog.record_tuples)
-    assert log_has('max_open_trades set to unlimited ...', caplog.record_tuples)
-
-    assert 'refresh_pairs'in config
-    assert log_has('Parameter -r/--refresh-pairs-cached detected ...', caplog.record_tuples)
-    assert 'timerange' in config
-    assert log_has(
-        'Parameter --timerange detected: {} ...'.format(config['timerange']),
-        caplog.record_tuples
-    )
-
-    assert 'export' in config
-    assert log_has(
-        'Parameter --export detected: {} ...'.format(config['export']),
-        caplog.record_tuples
-    )
-
-
-def test_setup_configuration_with_stratlist(mocker, default_conf, caplog) -> None:
-    """
-    Test setup_configuration() function
-    """
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    arglist = [
-        '--config', 'config.json',
-        'backtesting',
-        '--ticker-interval', '1m',
-        '--export', '/bar/foo',
-        '--strategy-list',
-        'DefaultStrategy',
-        'TestStrategy'
-    ]
-
-    args = Arguments(arglist, '').get_parsed_arg()
-
-    configuration = Configuration(args, RunMode.BACKTEST)
-    config = configuration.get_config()
-    assert config['runmode'] == RunMode.BACKTEST
-    assert 'max_open_trades' in config
-    assert 'stake_currency' in config
-    assert 'stake_amount' in config
-    assert 'exchange' in config
-    assert 'pair_whitelist' in config['exchange']
-    assert 'datadir' in config
-    assert log_has(
-        'Using data directory: {} ...'.format(config['datadir']),
-        caplog.record_tuples
-    )
-    assert 'ticker_interval' in config
-    assert log_has('Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
-                   caplog.record_tuples)
-
-    assert 'strategy_list' in config
-    assert log_has('Using strategy list of 2 Strategies', caplog.record_tuples)
-
-    assert 'position_stacking' not in config
-
-    assert 'use_max_market_positions' not in config
-
-    assert 'timerange' not in config
-
-    assert 'export' in config
-    assert log_has(
-        'Parameter --export detected: {} ...'.format(config['export']),
-        caplog.record_tuples
-    )
-
-
-def test_hyperopt_with_arguments(mocker, default_conf, caplog) -> None:
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    arglist = [
-        'hyperopt',
-        '--epochs', '10',
-        '--spaces', 'all',
-    ]
-    args = Arguments(arglist, '').get_parsed_arg()
-
-    configuration = Configuration(args, RunMode.HYPEROPT)
-    config = configuration.get_config()
-
-    assert 'epochs' in config
-    assert int(config['epochs']) == 10
-    assert log_has('Parameter --epochs detected ... Will run Hyperopt with for 10 epochs ...',
-                   caplog.record_tuples)
-
-    assert 'spaces' in config
-    assert config['spaces'] == ['all']
-    assert log_has('Parameter -s/--spaces detected: [\'all\']', caplog.record_tuples)
-    assert "runmode" in config
-    assert config['runmode'] == RunMode.HYPEROPT
-
-
-def test_check_exchange(default_conf, caplog) -> None:
-    # Test an officially supported by Freqtrade team exchange
-    default_conf.get('exchange').update({'name': 'BITTREX'})
-    assert check_exchange(default_conf)
-    assert log_has_re(r"Exchange .* is officially supported by the Freqtrade development team\.",
-                      caplog.record_tuples)
-    caplog.clear()
-
-    # Test an officially supported by Freqtrade team exchange
-    default_conf.get('exchange').update({'name': 'binance'})
-    assert check_exchange(default_conf)
-    assert log_has_re(r"Exchange .* is officially supported by the Freqtrade development team\.",
-                      caplog.record_tuples)
-    caplog.clear()
-
-    # Test an available exchange, supported by ccxt
-    default_conf.get('exchange').update({'name': 'kraken'})
-    assert check_exchange(default_conf)
-    assert log_has_re(r"Exchange .* is supported by ccxt and .* not officially supported "
-                      r"by the Freqtrade development team\. .*",
-                      caplog.record_tuples)
-    caplog.clear()
-
-    # Test a 'bad' exchange, which known to have serious problems
-    default_conf.get('exchange').update({'name': 'bitmex'})
-    assert not check_exchange(default_conf)
-    assert log_has_re(r"Exchange .* is known to not work with the bot yet\. "
-                      r"Use it only for development and testing purposes\.",
-                      caplog.record_tuples)
-    caplog.clear()
-
-    # Test a 'bad' exchange with check_for_bad=False
-    default_conf.get('exchange').update({'name': 'bitmex'})
-    assert check_exchange(default_conf, False)
-    assert log_has_re(r"Exchange .* is supported by ccxt and .* not officially supported "
-                      r"by the Freqtrade development team\. .*",
-                      caplog.record_tuples)
-    caplog.clear()
-
-    # Test an invalid exchange
-    default_conf.get('exchange').update({'name': 'unknown_exchange'})
-
-    with pytest.raises(
-        OperationalException,
-        match=r'.*Exchange "unknown_exchange" is not supported by ccxt '
-              r'and therefore not available for the bot.*'
-    ):
-        check_exchange(default_conf)
-
-
-def test_cli_verbose_with_params(default_conf, mocker, caplog) -> None:
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    # Prevent setting loggers
-    mocker.patch('freqtrade.loggers._set_loggers', MagicMock)
-    arglist = ['-vvv']
-    args = Arguments(arglist, '').get_parsed_arg()
-
-    configuration = Configuration(args)
-    validated_conf = configuration.load_config()
-
-    assert validated_conf.get('verbosity') == 3
-    assert log_has('Verbosity set to 3', caplog.record_tuples)
-
-
-def test_set_loggers() -> None:
-    # Reset Logging to Debug, otherwise this fails randomly as it's set globally
-    logging.getLogger('requests').setLevel(logging.DEBUG)
-    logging.getLogger("urllib3").setLevel(logging.DEBUG)
-    logging.getLogger('ccxt.base.exchange').setLevel(logging.DEBUG)
-    logging.getLogger('telegram').setLevel(logging.DEBUG)
-
-    previous_value1 = logging.getLogger('requests').level
-    previous_value2 = logging.getLogger('ccxt.base.exchange').level
-    previous_value3 = logging.getLogger('telegram').level
-
-    _set_loggers()
-
-    value1 = logging.getLogger('requests').level
-    assert previous_value1 is not value1
-    assert value1 is logging.INFO
-
-    value2 = logging.getLogger('ccxt.base.exchange').level
-    assert previous_value2 is not value2
-    assert value2 is logging.INFO
-
-    value3 = logging.getLogger('telegram').level
-    assert previous_value3 is not value3
-    assert value3 is logging.INFO
-
-    _set_loggers(verbosity=2)
-
-    assert logging.getLogger('requests').level is logging.DEBUG
-    assert logging.getLogger('ccxt.base.exchange').level is logging.INFO
-    assert logging.getLogger('telegram').level is logging.INFO
-
-    _set_loggers(verbosity=3)
-
-    assert logging.getLogger('requests').level is logging.DEBUG
-    assert logging.getLogger('ccxt.base.exchange').level is logging.DEBUG
-    assert logging.getLogger('telegram').level is logging.INFO
-
-
-def test_set_logfile(default_conf, mocker):
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    arglist = [
-        '--logfile', 'test_file.log',
-    ]
-    args = Arguments(arglist, '').get_parsed_arg()
-    configuration = Configuration(args)
-    validated_conf = configuration.load_config()
-
-    assert validated_conf['logfile'] == "test_file.log"
-    f = Path("test_file.log")
-    assert f.is_file()
-    f.unlink()
-
-
-def test_load_config_warn_forcebuy(default_conf, mocker, caplog) -> None:
-    default_conf['forcebuy_enable'] = True
-    patched_configuration_load_config_file(mocker, default_conf)
-
-    args = Arguments([], '').get_parsed_arg()
-    configuration = Configuration(args)
-    validated_conf = configuration.load_config()
-
-    assert validated_conf.get('forcebuy_enable')
-    assert log_has('`forcebuy` RPC message enabled.', caplog.record_tuples)
-
-
-def test_validate_default_conf(default_conf) -> None:
-    validate(default_conf, constants.CONF_SCHEMA, Draft4Validator)
-
-
-def test_create_datadir(mocker, default_conf, caplog) -> None:
-    mocker.patch.object(Path, "is_dir", MagicMock(return_value=False))
-    md = mocker.patch.object(Path, 'mkdir', MagicMock())
-
-    create_datadir(default_conf, '/foo/bar')
-    assert md.call_args[1]['parents'] is True
-    assert log_has('Created data directory: /foo/bar', caplog.record_tuples)
-
-
-def test_validate_tsl(default_conf):
-    default_conf['trailing_stop'] = True
-    default_conf['trailing_stop_positive'] = 0
-    default_conf['trailing_stop_positive_offset'] = 0
-
-    default_conf['trailing_only_offset_is_reached'] = True
-    with pytest.raises(OperationalException,
-                       match=r'The config trailing_only_offset_is_reached needs '
-                       'trailing_stop_positive_offset to be more than 0 in your config.'):
-        configuration = Configuration(Namespace())
-        configuration._validate_config_consistency(default_conf)
-
-    default_conf['trailing_stop_positive_offset'] = 0.01
-    default_conf['trailing_stop_positive'] = 0.015
-    with pytest.raises(OperationalException,
-                       match=r'The config trailing_stop_positive_offset needs '
-                       'to be greater than trailing_stop_positive_offset in your config.'):
-        configuration = Configuration(Namespace())
-        configuration._validate_config_consistency(default_conf)
-
-    default_conf['trailing_stop_positive'] = 0.01
-    default_conf['trailing_stop_positive_offset'] = 0.015
-    Configuration(Namespace())
-    configuration._validate_config_consistency(default_conf)
-
-
-def test_load_config_default_exchange(all_conf) -> None:
-    """
-    config['exchange'] subtree has required options in it
-    so it cannot be omitted in the config
-    """
-    del all_conf['exchange']
-
-    assert 'exchange' not in all_conf
-
-    with pytest.raises(ValidationError,
-                       match=r'\'exchange\' is a required property'):
-        validate_config_schema(all_conf)
-
-
-def test_load_config_default_exchange_name(all_conf) -> None:
-    """
-    config['exchange']['name'] option is required
-    so it cannot be omitted in the config
-    """
-    del all_conf['exchange']['name']
-
-    assert 'name' not in all_conf['exchange']
-
-    with pytest.raises(ValidationError,
-                       match=r'\'name\' is a required property'):
-        validate_config_schema(all_conf)
-
-
-@pytest.mark.parametrize("keys", [("exchange", "sandbox", False),
-                                  ("exchange", "key", ""),
-                                  ("exchange", "secret", ""),
-                                  ("exchange", "password", ""),
-                                  ])
-def test_load_config_default_subkeys(all_conf, keys) -> None:
-    """
-    Test for parameters with default values in sub-paths
-    so they can be omitted in the config and the default value
-    should is added to the config.
-    """
-    # Get first level key
-    key = keys[0]
-    # get second level key
-    subkey = keys[1]
-
-    del all_conf[key][subkey]
-
-    assert subkey not in all_conf[key]
-
-    validate_config_schema(all_conf)
-    assert subkey in all_conf[key]
-    assert all_conf[key][subkey] == keys[2]
diff --git a/freqtrade/tests/test_freqtradebot.py b/freqtrade/tests/test_freqtradebot.py
deleted file mode 100644
index 9a22a4f94..000000000
--- a/freqtrade/tests/test_freqtradebot.py
+++ /dev/null
@@ -1,3262 +0,0 @@
-# pragma pylint: disable=missing-docstring, C0103
-# pragma pylint: disable=protected-access, too-many-lines, invalid-name, too-many-arguments
-
-import logging
-import time
-from copy import deepcopy
-from unittest.mock import MagicMock, PropertyMock
-
-import arrow
-import pytest
-import requests
-
-from freqtrade import (DependencyException, InvalidOrderException,
-                       OperationalException, TemporaryError, constants)
-from freqtrade.data.dataprovider import DataProvider
-from freqtrade.freqtradebot import FreqtradeBot
-from freqtrade.persistence import Trade
-from freqtrade.rpc import RPCMessageType
-from freqtrade.state import State
-from freqtrade.strategy.interface import SellCheckTuple, SellType
-from freqtrade.tests.conftest import (get_patched_freqtradebot,
-                                      get_patched_worker, log_has, log_has_re,
-                                      patch_edge, patch_exchange,
-                                      patch_get_signal, patch_wallet)
-from freqtrade.worker import Worker
-
-
-def patch_RPCManager(mocker) -> MagicMock:
-    """
-    This function mock RPC manager to avoid repeating this code in almost every tests
-    :param mocker: mocker to patch RPCManager class
-    :return: RPCManager.send_msg MagicMock to track if this method is called
-    """
-    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
-    rpc_mock = mocker.patch('freqtrade.freqtradebot.RPCManager.send_msg', MagicMock())
-    return rpc_mock
-
-
-# Unit tests
-
-def test_freqtradebot_state(mocker, default_conf, markets) -> None:
-    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    assert freqtrade.state is State.RUNNING
-
-    default_conf.pop('initial_state')
-    freqtrade = FreqtradeBot(default_conf)
-    assert freqtrade.state is State.STOPPED
-
-
-def test_worker_state(mocker, default_conf, markets) -> None:
-    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
-    worker = get_patched_worker(mocker, default_conf)
-    assert worker.state is State.RUNNING
-
-    default_conf.pop('initial_state')
-    worker = Worker(args=None, config=default_conf)
-    assert worker.state is State.STOPPED
-
-
-def test_cleanup(mocker, default_conf, caplog) -> None:
-    mock_cleanup = MagicMock()
-    mocker.patch('freqtrade.persistence.cleanup', mock_cleanup)
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    freqtrade.cleanup()
-    assert log_has('Cleaning up modules ...', caplog.record_tuples)
-    assert mock_cleanup.call_count == 1
-
-
-def test_worker_running(mocker, default_conf, caplog) -> None:
-    mock_throttle = MagicMock()
-    mocker.patch('freqtrade.worker.Worker._throttle', mock_throttle)
-    mocker.patch('freqtrade.persistence.Trade.stoploss_reinitialization', MagicMock())
-
-    worker = get_patched_worker(mocker, default_conf)
-
-    state = worker._worker(old_state=None)
-    assert state is State.RUNNING
-    assert log_has('Changing state to: RUNNING', caplog.record_tuples)
-    assert mock_throttle.call_count == 1
-    # Check strategy is loaded, and received a dataprovider object
-    assert worker.freqtrade.strategy
-    assert worker.freqtrade.strategy.dp
-    assert isinstance(worker.freqtrade.strategy.dp, DataProvider)
-
-
-def test_worker_stopped(mocker, default_conf, caplog) -> None:
-    mock_throttle = MagicMock()
-    mocker.patch('freqtrade.worker.Worker._throttle', mock_throttle)
-    mock_sleep = mocker.patch('time.sleep', return_value=None)
-
-    worker = get_patched_worker(mocker, default_conf)
-    worker.state = State.STOPPED
-    state = worker._worker(old_state=State.RUNNING)
-    assert state is State.STOPPED
-    assert log_has('Changing state to: STOPPED', caplog.record_tuples)
-    assert mock_throttle.call_count == 0
-    assert mock_sleep.call_count == 1
-
-
-def test_throttle(mocker, default_conf, caplog) -> None:
-    def throttled_func():
-        return 42
-
-    caplog.set_level(logging.DEBUG)
-    worker = get_patched_worker(mocker, default_conf)
-
-    start = time.time()
-    result = worker._throttle(throttled_func, min_secs=0.1)
-    end = time.time()
-
-    assert result == 42
-    assert end - start > 0.1
-    assert log_has('Throttling throttled_func for 0.10 seconds', caplog.record_tuples)
-
-    result = worker._throttle(throttled_func, min_secs=-1)
-    assert result == 42
-
-
-def test_throttle_with_assets(mocker, default_conf) -> None:
-    def throttled_func(nb_assets=-1):
-        return nb_assets
-
-    worker = get_patched_worker(mocker, default_conf)
-
-    result = worker._throttle(throttled_func, min_secs=0.1, nb_assets=666)
-    assert result == 666
-
-    result = worker._throttle(throttled_func, min_secs=0.1)
-    assert result == -1
-
-
-def test_get_trade_stake_amount(default_conf, ticker, limit_buy_order, fee, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_balance=MagicMock(return_value=default_conf['stake_amount'] * 2)
-    )
-
-    freqtrade = FreqtradeBot(default_conf)
-
-    result = freqtrade._get_trade_stake_amount('ETH/BTC')
-    assert result == default_conf['stake_amount']
-
-
-def test_get_trade_stake_amount_no_stake_amount(default_conf, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    patch_wallet(mocker, free=default_conf['stake_amount'] * 0.5)
-    freqtrade = FreqtradeBot(default_conf)
-
-    with pytest.raises(DependencyException, match=r'.*stake amount.*'):
-        freqtrade._get_trade_stake_amount('ETH/BTC')
-
-
-def test_get_trade_stake_amount_unlimited_amount(default_conf,
-                                                 ticker,
-                                                 limit_buy_order,
-                                                 fee,
-                                                 markets,
-                                                 mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    patch_wallet(mocker, free=default_conf['stake_amount'])
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        markets=PropertyMock(return_value=markets),
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee
-    )
-
-    conf = deepcopy(default_conf)
-    conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
-    conf['max_open_trades'] = 2
-
-    freqtrade = FreqtradeBot(conf)
-    patch_get_signal(freqtrade)
-
-    # no open trades, order amount should be 'balance / max_open_trades'
-    result = freqtrade._get_trade_stake_amount('ETH/BTC')
-    assert result == default_conf['stake_amount'] / conf['max_open_trades']
-
-    # create one trade, order amount should be 'balance / (max_open_trades - num_open_trades)'
-    freqtrade.create_trade()
-
-    result = freqtrade._get_trade_stake_amount('LTC/BTC')
-    assert result == default_conf['stake_amount'] / (conf['max_open_trades'] - 1)
-
-    # create 2 trades, order amount should be None
-    freqtrade.create_trade()
-
-    result = freqtrade._get_trade_stake_amount('XRP/BTC')
-    assert result is None
-
-    # set max_open_trades = None, so do not trade
-    conf['max_open_trades'] = 0
-    freqtrade = FreqtradeBot(conf)
-    result = freqtrade._get_trade_stake_amount('NEO/BTC')
-    assert result is None
-
-
-def test_edge_called_in_process(mocker, edge_conf) -> None:
-    patch_RPCManager(mocker)
-    patch_edge(mocker)
-
-    def _refresh_whitelist(list):
-        return ['ETH/BTC', 'LTC/BTC', 'XRP/BTC', 'NEO/BTC']
-
-    patch_exchange(mocker)
-    freqtrade = FreqtradeBot(edge_conf)
-    freqtrade.pairlists._validate_whitelist = _refresh_whitelist
-    patch_get_signal(freqtrade)
-    freqtrade.process()
-    assert freqtrade.active_pair_whitelist == ['NEO/BTC', 'LTC/BTC']
-
-
-def test_edge_overrides_stake_amount(mocker, edge_conf) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    patch_edge(mocker)
-    freqtrade = FreqtradeBot(edge_conf)
-
-    assert freqtrade._get_trade_stake_amount('NEO/BTC') == (999.9 * 0.5 * 0.01) / 0.20
-    assert freqtrade._get_trade_stake_amount('LTC/BTC') == (999.9 * 0.5 * 0.01) / 0.21
-
-
-def test_edge_overrides_stoploss(limit_buy_order, fee, markets, caplog, mocker, edge_conf) -> None:
-
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    patch_edge(mocker)
-
-    # Strategy stoploss is -0.1 but Edge imposes a stoploss at -0.2
-    # Thus, if price falls 21%, stoploss should be triggered
-    #
-    # mocking the ticker: price is falling ...
-    buy_price = limit_buy_order['price']
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': buy_price * 0.79,
-            'ask': buy_price * 0.79,
-            'last': buy_price * 0.79
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    #############################################
-
-    # Create a trade with "limit_buy_order" price
-    freqtrade = FreqtradeBot(edge_conf)
-    freqtrade.active_pair_whitelist = ['NEO/BTC']
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-    freqtrade.create_trade()
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    #############################################
-
-    # stoploss shoud be hit
-    assert freqtrade.handle_trade(trade) is True
-    assert log_has('executed sell, reason: SellType.STOP_LOSS', caplog.record_tuples)
-    assert trade.sell_reason == SellType.STOP_LOSS.value
-
-
-def test_edge_should_ignore_strategy_stoploss(limit_buy_order, fee, markets,
-                                              mocker, edge_conf) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    patch_edge(mocker)
-
-    # Strategy stoploss is -0.1 but Edge imposes a stoploss at -0.2
-    # Thus, if price falls 15%, stoploss should not be triggered
-    #
-    # mocking the ticker: price is falling ...
-    buy_price = limit_buy_order['price']
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': buy_price * 0.85,
-            'ask': buy_price * 0.85,
-            'last': buy_price * 0.85
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets),
-    )
-    #############################################
-
-    # Create a trade with "limit_buy_order" price
-    freqtrade = FreqtradeBot(edge_conf)
-    freqtrade.active_pair_whitelist = ['NEO/BTC']
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-    freqtrade.create_trade()
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    #############################################
-
-    # stoploss shoud not be hit
-    assert freqtrade.handle_trade(trade) is False
-
-
-def test_total_open_trades_stakes(mocker, default_conf, ticker,
-                                  limit_buy_order, fee, markets) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    default_conf['stake_amount'] = 0.0000098751
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.create_trade()
-    trade = Trade.query.first()
-
-    assert trade is not None
-    assert trade.stake_amount == 0.0000098751
-    assert trade.is_open
-    assert trade.open_date is not None
-
-    freqtrade.create_trade()
-    trade = Trade.query.order_by(Trade.id.desc()).first()
-
-    assert trade is not None
-    assert trade.stake_amount == 0.0000098751
-    assert trade.is_open
-    assert trade.open_date is not None
-
-    assert Trade.total_open_trades_stakes() == 1.97502e-05
-
-
-def test_get_min_pair_stake_amount(mocker, default_conf) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    freqtrade = FreqtradeBot(default_conf)
-    freqtrade.strategy.stoploss = -0.05
-    markets = {'ETH/BTC': {'symbol': 'ETH/BTC'}}
-    # no pair found
-    mocker.patch(
-        'freqtrade.exchange.Exchange.markets',
-        PropertyMock(return_value=markets)
-    )
-    with pytest.raises(ValueError, match=r'.*get market information.*'):
-        freqtrade._get_min_pair_stake_amount('BNB/BTC', 1)
-
-    # no 'limits' section
-    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1)
-    assert result is None
-
-    # empty 'limits' section
-    markets["ETH/BTC"]["limits"] = {}
-    mocker.patch(
-        'freqtrade.exchange.Exchange.markets',
-        PropertyMock(return_value=markets)
-    )
-    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1)
-    assert result is None
-
-    # no cost Min
-    markets["ETH/BTC"]["limits"] = {
-        'cost': {"min": None},
-        'amount': {}
-    }
-    mocker.patch(
-        'freqtrade.exchange.Exchange.markets',
-        PropertyMock(return_value=markets)
-    )
-    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1)
-    assert result is None
-
-    # no amount Min
-    markets["ETH/BTC"]["limits"] = {
-        'cost': {},
-        'amount': {"min": None}
-    }
-    mocker.patch(
-        'freqtrade.exchange.Exchange.markets',
-        PropertyMock(return_value=markets)
-    )
-    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1)
-    assert result is None
-
-    # empty 'cost'/'amount' section
-    markets["ETH/BTC"]["limits"] = {
-        'cost': {},
-        'amount': {}
-    }
-    mocker.patch(
-        'freqtrade.exchange.Exchange.markets',
-        PropertyMock(return_value=markets)
-    )
-    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1)
-    assert result is None
-
-    # min cost is set
-    markets["ETH/BTC"]["limits"] = {
-        'cost': {'min': 2},
-        'amount': {}
-    }
-    mocker.patch(
-        'freqtrade.exchange.Exchange.markets',
-        PropertyMock(return_value=markets)
-    )
-    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1)
-    assert result == 2 / 0.9
-
-    # min amount is set
-    markets["ETH/BTC"]["limits"] = {
-        'cost': {},
-        'amount': {'min': 2}
-    }
-    mocker.patch(
-        'freqtrade.exchange.Exchange.markets',
-        PropertyMock(return_value=markets)
-    )
-    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 2)
-    assert result == 2 * 2 / 0.9
-
-    # min amount and cost are set (cost is minimal)
-    markets["ETH/BTC"]["limits"] = {
-        'cost': {'min': 2},
-        'amount': {'min': 2}
-    }
-    mocker.patch(
-        'freqtrade.exchange.Exchange.markets',
-        PropertyMock(return_value=markets)
-    )
-    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 2)
-    assert result == min(2, 2 * 2) / 0.9
-
-    # min amount and cost are set (amount is minial)
-    markets["ETH/BTC"]["limits"] = {
-        'cost': {'min': 8},
-        'amount': {'min': 2}
-    }
-    mocker.patch(
-        'freqtrade.exchange.Exchange.markets',
-        PropertyMock(return_value=markets)
-    )
-    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 2)
-    assert result == min(8, 2 * 2) / 0.9
-
-
-def test_create_trade(default_conf, ticker, limit_buy_order, fee, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-
-    # Save state of current whitelist
-    whitelist = deepcopy(default_conf['exchange']['pair_whitelist'])
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    assert trade is not None
-    assert trade.stake_amount == 0.001
-    assert trade.is_open
-    assert trade.open_date is not None
-    assert trade.exchange == 'bittrex'
-
-    # Simulate fulfilled LIMIT_BUY order for trade
-    trade.update(limit_buy_order)
-
-    assert trade.open_rate == 0.00001099
-    assert trade.amount == 90.99181073
-
-    assert whitelist == default_conf['exchange']['pair_whitelist']
-
-
-def test_create_trade_no_stake_amount(default_conf, ticker, limit_buy_order,
-                                      fee, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    patch_wallet(mocker, free=default_conf['stake_amount'] * 0.5)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    with pytest.raises(DependencyException, match=r'.*stake amount.*'):
-        freqtrade.create_trade()
-
-
-def test_create_trade_minimal_amount(default_conf, ticker, limit_buy_order,
-                                     fee, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    buy_mock = MagicMock(return_value={'id': limit_buy_order['id']})
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=buy_mock,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    default_conf['stake_amount'] = 0.0005
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    freqtrade.create_trade()
-    rate, amount = buy_mock.call_args[1]['rate'], buy_mock.call_args[1]['amount']
-    assert rate * amount >= default_conf['stake_amount']
-
-
-def test_create_trade_too_small_stake_amount(default_conf, ticker, limit_buy_order,
-                                             fee, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    buy_mock = MagicMock(return_value={'id': limit_buy_order['id']})
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=buy_mock,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-
-    default_conf['stake_amount'] = 0.000000005
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    assert not freqtrade.create_trade()
-
-
-def test_create_trade_limit_reached(default_conf, ticker, limit_buy_order,
-                                    fee, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_balance=MagicMock(return_value=default_conf['stake_amount']),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    default_conf['max_open_trades'] = 0
-    default_conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
-
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    assert not freqtrade.create_trade()
-    assert freqtrade._get_trade_stake_amount('ETH/BTC') is None
-
-
-def test_create_trade_no_pairs_let(default_conf, ticker, limit_buy_order, fee,
-                                   markets, mocker, caplog) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-
-    default_conf['exchange']['pair_whitelist'] = ["ETH/BTC"]
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    assert freqtrade.create_trade()
-    assert not freqtrade.create_trade()
-    assert log_has("No currency pair in whitelist, but checking to sell open trades.",
-                   caplog.record_tuples)
-
-
-def test_create_trade_no_pairs_in_whitelist(default_conf, ticker, limit_buy_order, fee,
-                                            markets, mocker, caplog) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    default_conf['exchange']['pair_whitelist'] = []
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    assert not freqtrade.create_trade()
-    assert log_has("Whitelist is empty.", caplog.record_tuples)
-
-
-def test_create_trade_no_signal(default_conf, fee, mocker) -> None:
-    default_conf['dry_run'] = True
-
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_balance=MagicMock(return_value=20),
-        get_fee=fee,
-    )
-    default_conf['stake_amount'] = 10
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade, value=(False, False))
-
-    Trade.query = MagicMock()
-    Trade.query.filter = MagicMock()
-    assert not freqtrade.create_trade()
-
-
-def test_process_trade_creation(default_conf, ticker, limit_buy_order,
-                                markets, fee, mocker, caplog) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        markets=PropertyMock(return_value=markets),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_order=MagicMock(return_value=limit_buy_order),
-        get_fee=fee,
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    trades = Trade.query.filter(Trade.is_open.is_(True)).all()
-    assert not trades
-
-    result = freqtrade.process()
-    assert result is True
-
-    trades = Trade.query.filter(Trade.is_open.is_(True)).all()
-    assert len(trades) == 1
-    trade = trades[0]
-    assert trade is not None
-    assert trade.stake_amount == default_conf['stake_amount']
-    assert trade.is_open
-    assert trade.open_date is not None
-    assert trade.exchange == 'bittrex'
-    assert trade.open_rate == 0.00001099
-    assert trade.amount == 90.99181073703367
-
-    assert log_has(
-        'Buy signal found: about create a new trade with stake_amount: 0.001 ...',
-        caplog.record_tuples
-    )
-
-
-def test_process_exchange_failures(default_conf, ticker, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        markets=PropertyMock(return_value=markets),
-        buy=MagicMock(side_effect=TemporaryError)
-    )
-    sleep_mock = mocker.patch('time.sleep', side_effect=lambda _: None)
-
-    worker = Worker(args=None, config=default_conf)
-    patch_get_signal(worker.freqtrade)
-
-    result = worker._process()
-    assert result is False
-    assert sleep_mock.has_calls()
-
-
-def test_process_operational_exception(default_conf, ticker, markets, mocker) -> None:
-    msg_mock = patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        markets=PropertyMock(return_value=markets),
-        buy=MagicMock(side_effect=OperationalException)
-    )
-    worker = Worker(args=None, config=default_conf)
-    patch_get_signal(worker.freqtrade)
-
-    assert worker.state == State.RUNNING
-
-    result = worker._process()
-    assert result is False
-    assert worker.state == State.STOPPED
-    assert 'OperationalException' in msg_mock.call_args_list[-1][0][0]['status']
-
-
-def test_process_trade_handling(
-        default_conf, ticker, limit_buy_order, markets, fee, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        markets=PropertyMock(return_value=markets),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_order=MagicMock(return_value=limit_buy_order),
-        get_fee=fee,
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    trades = Trade.query.filter(Trade.is_open.is_(True)).all()
-    assert not trades
-    result = freqtrade.process()
-    assert result is True
-    trades = Trade.query.filter(Trade.is_open.is_(True)).all()
-    assert len(trades) == 1
-
-    result = freqtrade.process()
-    assert result is False
-
-
-def test_process_trade_no_whitelist_pair(
-        default_conf, ticker, limit_buy_order, markets, fee, mocker) -> None:
-    """ Test process with trade not in pair list """
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        markets=PropertyMock(return_value=markets),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_order=MagicMock(return_value=limit_buy_order),
-        get_fee=fee,
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    pair = 'NOCLUE/BTC'
-    # create open trade not in whitelist
-    Trade.session.add(Trade(
-        pair=pair,
-        stake_amount=0.001,
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-        is_open=True,
-        amount=20,
-        open_rate=0.01,
-        exchange='bittrex',
-    ))
-    Trade.session.add(Trade(
-        pair='ETH/BTC',
-        stake_amount=0.001,
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-        is_open=True,
-        amount=12,
-        open_rate=0.001,
-        exchange='bittrex',
-    ))
-
-    assert pair not in freqtrade.active_pair_whitelist
-    result = freqtrade.process()
-    assert pair in freqtrade.active_pair_whitelist
-    # Make sure each pair is only in the list once
-    assert len(freqtrade.active_pair_whitelist) == len(set(freqtrade.active_pair_whitelist))
-    assert result is True
-
-
-def test_process_informative_pairs_added(default_conf, ticker, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-
-    def _refresh_whitelist(list):
-        return ['ETH/BTC', 'LTC/BTC', 'XRP/BTC', 'NEO/BTC']
-
-    refresh_mock = MagicMock()
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        markets=PropertyMock(return_value=markets),
-        buy=MagicMock(side_effect=TemporaryError),
-        refresh_latest_ohlcv=refresh_mock,
-    )
-    inf_pairs = MagicMock(return_value=[("BTC/ETH", '1m'), ("ETH/USDT", "1h")])
-    mocker.patch('time.sleep', return_value=None)
-
-    freqtrade = FreqtradeBot(default_conf)
-    freqtrade.pairlists._validate_whitelist = _refresh_whitelist
-    freqtrade.strategy.informative_pairs = inf_pairs
-    # patch_get_signal(freqtrade)
-
-    freqtrade.process()
-    assert inf_pairs.call_count == 1
-    assert refresh_mock.call_count == 1
-    assert ("BTC/ETH", "1m") in refresh_mock.call_args[0][0]
-    assert ("ETH/USDT", "1h") in refresh_mock.call_args[0][0]
-    assert ("ETH/BTC", default_conf["ticker_interval"]) in refresh_mock.call_args[0][0]
-
-
-def test_balance_fully_ask_side(mocker, default_conf) -> None:
-    default_conf['bid_strategy']['ask_last_balance'] = 0.0
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(return_value={'ask': 20, 'last': 10}))
-
-    assert freqtrade.get_target_bid('ETH/BTC') == 20
-
-
-def test_balance_fully_last_side(mocker, default_conf) -> None:
-    default_conf['bid_strategy']['ask_last_balance'] = 1.0
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(return_value={'ask': 20, 'last': 10}))
-
-    assert freqtrade.get_target_bid('ETH/BTC') == 10
-
-
-def test_balance_bigger_last_ask(mocker, default_conf) -> None:
-    default_conf['bid_strategy']['ask_last_balance'] = 1.0
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(return_value={'ask': 5, 'last': 10}))
-    assert freqtrade.get_target_bid('ETH/BTC') == 5
-
-
-def test_execute_buy(mocker, default_conf, fee, markets, limit_buy_order) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    freqtrade = FreqtradeBot(default_conf)
-    stake_amount = 2
-    bid = 0.11
-    get_bid = MagicMock(return_value=bid)
-    mocker.patch.multiple(
-        'freqtrade.freqtradebot.FreqtradeBot',
-        get_target_bid=get_bid,
-        _get_min_pair_stake_amount=MagicMock(return_value=1)
-        )
-    buy_mm = MagicMock(return_value={'id': limit_buy_order['id']})
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
-        }),
-        buy=buy_mm,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    pair = 'ETH/BTC'
-    print(buy_mm.call_args_list)
-
-    assert freqtrade.execute_buy(pair, stake_amount)
-    assert get_bid.call_count == 1
-    assert buy_mm.call_count == 1
-    call_args = buy_mm.call_args_list[0][1]
-    assert call_args['pair'] == pair
-    assert call_args['rate'] == bid
-    assert call_args['amount'] == stake_amount / bid
-
-    # Should create an open trade with an open order id
-    # As the order is not fulfilled yet
-    trade = Trade.query.first()
-    assert trade
-    assert trade.is_open is True
-    assert trade.open_order_id == limit_buy_order['id']
-
-    # Test calling with price
-    fix_price = 0.06
-    assert freqtrade.execute_buy(pair, stake_amount, fix_price)
-    # Make sure get_target_bid wasn't called again
-    assert get_bid.call_count == 1
-
-    assert buy_mm.call_count == 2
-    call_args = buy_mm.call_args_list[1][1]
-    assert call_args['pair'] == pair
-    assert call_args['rate'] == fix_price
-    assert call_args['amount'] == stake_amount / fix_price
-
-    # In case of closed order
-    limit_buy_order['status'] = 'closed'
-    limit_buy_order['price'] = 10
-    limit_buy_order['cost'] = 100
-    mocker.patch('freqtrade.exchange.Exchange.buy', MagicMock(return_value=limit_buy_order))
-    assert freqtrade.execute_buy(pair, stake_amount)
-    trade = Trade.query.all()[2]
-    assert trade
-    assert trade.open_order_id is None
-    assert trade.open_rate == 10
-    assert trade.stake_amount == 100
-
-    # In case of rejected or expired order and partially filled
-    limit_buy_order['status'] = 'expired'
-    limit_buy_order['amount'] = 90.99181073
-    limit_buy_order['filled'] = 80.99181073
-    limit_buy_order['remaining'] = 10.00
-    limit_buy_order['price'] = 0.5
-    limit_buy_order['cost'] = 40.495905365
-    mocker.patch('freqtrade.exchange.Exchange.buy', MagicMock(return_value=limit_buy_order))
-    assert freqtrade.execute_buy(pair, stake_amount)
-    trade = Trade.query.all()[3]
-    assert trade
-    assert trade.open_order_id is None
-    assert trade.open_rate == 0.5
-    assert trade.stake_amount == 40.495905365
-
-    # In case of the order is rejected and not filled at all
-    limit_buy_order['status'] = 'rejected'
-    limit_buy_order['amount'] = 90.99181073
-    limit_buy_order['filled'] = 0.0
-    limit_buy_order['remaining'] = 90.99181073
-    limit_buy_order['price'] = 0.5
-    limit_buy_order['cost'] = 0.0
-    mocker.patch('freqtrade.exchange.Exchange.buy', MagicMock(return_value=limit_buy_order))
-    assert not freqtrade.execute_buy(pair, stake_amount)
-
-
-def test_add_stoploss_on_exchange(mocker, default_conf, limit_buy_order) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_trade', MagicMock(return_value=True))
-    mocker.patch('freqtrade.exchange.Exchange.get_order', return_value=limit_buy_order)
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
-    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
-                 return_value=limit_buy_order['amount'])
-
-    stoploss_limit = MagicMock(return_value={'id': 13434334})
-    mocker.patch('freqtrade.exchange.Exchange.stoploss_limit', stoploss_limit)
-
-    freqtrade = FreqtradeBot(default_conf)
-    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
-
-    trade = MagicMock()
-    trade.open_order_id = None
-    trade.stoploss_order_id = None
-    trade.is_open = True
-
-    freqtrade.process_maybe_execute_sell(trade)
-    assert trade.stoploss_order_id == '13434334'
-    assert stoploss_limit.call_count == 1
-    assert trade.is_open is True
-
-
-def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
-                                     markets, limit_buy_order, limit_sell_order) -> None:
-    stoploss_limit = MagicMock(return_value={'id': 13434334})
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        sell=MagicMock(return_value={'id': limit_sell_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets),
-        stoploss_limit=stoploss_limit
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # First case: when stoploss is not yet set but the order is open
-    # should get the stoploss order id immediately
-    # and should return false as no trade actually happened
-    trade = MagicMock()
-    trade.is_open = True
-    trade.open_order_id = None
-    trade.stoploss_order_id = None
-
-    assert freqtrade.handle_stoploss_on_exchange(trade) is False
-    assert stoploss_limit.call_count == 1
-    assert trade.stoploss_order_id == "13434334"
-
-    # Second case: when stoploss is set but it is not yet hit
-    # should do nothing and return false
-    trade.is_open = True
-    trade.open_order_id = None
-    trade.stoploss_order_id = 100
-
-    hanging_stoploss_order = MagicMock(return_value={'status': 'open'})
-    mocker.patch('freqtrade.exchange.Exchange.get_order', hanging_stoploss_order)
-
-    assert freqtrade.handle_stoploss_on_exchange(trade) is False
-    assert trade.stoploss_order_id == 100
-
-    # Third case: when stoploss was set but it was canceled for some reason
-    # should set a stoploss immediately and return False
-    trade.is_open = True
-    trade.open_order_id = None
-    trade.stoploss_order_id = 100
-
-    canceled_stoploss_order = MagicMock(return_value={'status': 'canceled'})
-    mocker.patch('freqtrade.exchange.Exchange.get_order', canceled_stoploss_order)
-    stoploss_limit.reset_mock()
-
-    assert freqtrade.handle_stoploss_on_exchange(trade) is False
-    assert stoploss_limit.call_count == 1
-    assert trade.stoploss_order_id == "13434334"
-
-    # Fourth case: when stoploss is set and it is hit
-    # should unset stoploss_order_id and return true
-    # as a trade actually happened
-    freqtrade.create_trade()
-    trade = Trade.query.first()
-    trade.is_open = True
-    trade.open_order_id = None
-    trade.stoploss_order_id = 100
-    assert trade
-
-    stoploss_order_hit = MagicMock(return_value={
-        'status': 'closed',
-        'type': 'stop_loss_limit',
-        'price': 3,
-        'average': 2
-    })
-    mocker.patch('freqtrade.exchange.Exchange.get_order', stoploss_order_hit)
-    assert freqtrade.handle_stoploss_on_exchange(trade) is True
-    assert log_has('STOP_LOSS_LIMIT is hit for {}.'.format(trade), caplog.record_tuples)
-    assert trade.stoploss_order_id is None
-    assert trade.is_open is False
-
-    mocker.patch(
-        'freqtrade.exchange.Exchange.stoploss_limit',
-        side_effect=DependencyException()
-    )
-    freqtrade.handle_stoploss_on_exchange(trade)
-    assert log_has('Unable to place a stoploss order on exchange: ', caplog.record_tuples)
-
-    # Fifth case: get_order returns InvalidOrder
-    # It should try to add stoploss order
-    trade.stoploss_order_id = 100
-    stoploss_limit.reset_mock()
-    mocker.patch('freqtrade.exchange.Exchange.get_order', side_effect=InvalidOrderException())
-    mocker.patch('freqtrade.exchange.Exchange.stoploss_limit', stoploss_limit)
-    freqtrade.handle_stoploss_on_exchange(trade)
-    assert stoploss_limit.call_count == 1
-
-
-def test_handle_stoploss_on_exchange_trailing(mocker, default_conf, fee, caplog,
-                                              markets, limit_buy_order, limit_sell_order) -> None:
-    # When trailing stoploss is set
-    stoploss_limit = MagicMock(return_value={'id': 13434334})
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        sell=MagicMock(return_value={'id': limit_sell_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets),
-        stoploss_limit=stoploss_limit
-    )
-
-    # enabling TSL
-    default_conf['trailing_stop'] = True
-
-    # disabling ROI
-    default_conf['minimal_roi']['0'] = 999999999
-
-    freqtrade = FreqtradeBot(default_conf)
-
-    # enabling stoploss on exchange
-    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
-
-    # setting stoploss
-    freqtrade.strategy.stoploss = -0.05
-
-    # setting stoploss_on_exchange_interval to 60 seconds
-    freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 60
-
-    patch_get_signal(freqtrade)
-
-    freqtrade.create_trade()
-    trade = Trade.query.first()
-    trade.is_open = True
-    trade.open_order_id = None
-    trade.stoploss_order_id = 100
-
-    stoploss_order_hanging = MagicMock(return_value={
-        'id': 100,
-        'status': 'open',
-        'type': 'stop_loss_limit',
-        'price': 3,
-        'average': 2,
-        'info': {
-            'stopPrice': '0.000011134'
-        }
-    })
-
-    mocker.patch('freqtrade.exchange.Exchange.get_order', stoploss_order_hanging)
-
-    # stoploss initially at 5%
-    assert freqtrade.handle_trade(trade) is False
-    assert freqtrade.handle_stoploss_on_exchange(trade) is False
-
-    # price jumped 2x
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker', MagicMock(return_value={
-        'bid': 0.00002344,
-        'ask': 0.00002346,
-        'last': 0.00002344
-    }))
-
-    cancel_order_mock = MagicMock()
-    stoploss_order_mock = MagicMock()
-    mocker.patch('freqtrade.exchange.Exchange.cancel_order', cancel_order_mock)
-    mocker.patch('freqtrade.exchange.Exchange.stoploss_limit', stoploss_order_mock)
-
-    # stoploss should not be updated as the interval is 60 seconds
-    assert freqtrade.handle_trade(trade) is False
-    assert freqtrade.handle_stoploss_on_exchange(trade) is False
-    cancel_order_mock.assert_not_called()
-    stoploss_order_mock.assert_not_called()
-
-    assert freqtrade.handle_trade(trade) is False
-    assert trade.stop_loss == 0.00002344 * 0.95
-
-    # setting stoploss_on_exchange_interval to 0 seconds
-    freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 0
-
-    assert freqtrade.handle_stoploss_on_exchange(trade) is False
-
-    cancel_order_mock.assert_called_once_with(100, 'ETH/BTC')
-    stoploss_order_mock.assert_called_once_with(amount=85.25149190110828,
-                                                pair='ETH/BTC',
-                                                rate=0.00002344 * 0.95 * 0.99,
-                                                stop_price=0.00002344 * 0.95)
-
-
-def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, caplog,
-                                                    markets, limit_buy_order,
-                                                    limit_sell_order) -> None:
-    # When trailing stoploss is set
-    stoploss_limit = MagicMock(return_value={'id': 13434334})
-    patch_exchange(mocker)
-
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        sell=MagicMock(return_value={'id': limit_sell_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets),
-        stoploss_limit=stoploss_limit
-    )
-
-    # enabling TSL
-    default_conf['trailing_stop'] = True
-
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    # enabling stoploss on exchange
-    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
-
-    # setting stoploss
-    freqtrade.strategy.stoploss = -0.05
-
-    # setting stoploss_on_exchange_interval to 60 seconds
-    freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 60
-    patch_get_signal(freqtrade)
-    freqtrade.create_trade()
-    trade = Trade.query.first()
-    trade.is_open = True
-    trade.open_order_id = None
-    trade.stoploss_order_id = "abcd"
-    trade.stop_loss = 0.2
-    trade.stoploss_last_update = arrow.utcnow().shift(minutes=-601).datetime.replace(tzinfo=None)
-
-    stoploss_order_hanging = {
-        'id': "abcd",
-        'status': 'open',
-        'type': 'stop_loss_limit',
-        'price': 3,
-        'average': 2,
-        'info': {
-            'stopPrice': '0.1'
-        }
-    }
-    mocker.patch('freqtrade.exchange.Exchange.cancel_order', side_effect=InvalidOrderException())
-    mocker.patch('freqtrade.exchange.Exchange.get_order', stoploss_order_hanging)
-    freqtrade.handle_trailing_stoploss_on_exchange(trade, stoploss_order_hanging)
-    assert log_has_re(r"Could not cancel stoploss order abcd for pair ETH/BTC.*",
-                      caplog.record_tuples)
-
-    # Still try to create order
-    assert stoploss_limit.call_count == 1
-
-    # Fail creating stoploss order
-    caplog.clear()
-    cancel_mock = mocker.patch("freqtrade.exchange.Exchange.cancel_order", MagicMock())
-    mocker.patch("freqtrade.exchange.Exchange.stoploss_limit", side_effect=DependencyException())
-    freqtrade.handle_trailing_stoploss_on_exchange(trade, stoploss_order_hanging)
-    assert cancel_mock.call_count == 1
-    assert log_has_re(r"Could create trailing stoploss order for pair ETH/BTC\..*",
-                      caplog.record_tuples)
-
-
-def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog,
-                                              markets, limit_buy_order, limit_sell_order) -> None:
-
-    # When trailing stoploss is set
-    stoploss_limit = MagicMock(return_value={'id': 13434334})
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    patch_edge(mocker)
-
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        sell=MagicMock(return_value={'id': limit_sell_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets),
-        stoploss_limit=stoploss_limit
-    )
-
-    # enabling TSL
-    edge_conf['trailing_stop'] = True
-    edge_conf['trailing_stop_positive'] = 0.01
-    edge_conf['trailing_stop_positive_offset'] = 0.011
-
-    # disabling ROI
-    edge_conf['minimal_roi']['0'] = 999999999
-
-    freqtrade = FreqtradeBot(edge_conf)
-
-    # enabling stoploss on exchange
-    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
-
-    # setting stoploss
-    freqtrade.strategy.stoploss = -0.02
-
-    # setting stoploss_on_exchange_interval to 0 second
-    freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 0
-
-    patch_get_signal(freqtrade)
-
-    freqtrade.active_pair_whitelist = freqtrade.edge.adjust(freqtrade.active_pair_whitelist)
-
-    freqtrade.create_trade()
-    trade = Trade.query.first()
-    trade.is_open = True
-    trade.open_order_id = None
-    trade.stoploss_order_id = 100
-
-    stoploss_order_hanging = MagicMock(return_value={
-        'id': 100,
-        'status': 'open',
-        'type': 'stop_loss_limit',
-        'price': 3,
-        'average': 2,
-        'info': {
-            'stopPrice': '0.000009384'
-        }
-    })
-
-    mocker.patch('freqtrade.exchange.Exchange.get_order', stoploss_order_hanging)
-
-    # stoploss initially at 20% as edge dictated it.
-    assert freqtrade.handle_trade(trade) is False
-    assert freqtrade.handle_stoploss_on_exchange(trade) is False
-    assert trade.stop_loss == 0.000009384
-
-    cancel_order_mock = MagicMock()
-    stoploss_order_mock = MagicMock()
-    mocker.patch('freqtrade.exchange.Exchange.cancel_order', cancel_order_mock)
-    mocker.patch('freqtrade.exchange.Exchange.stoploss_limit', stoploss_order_mock)
-
-    # price goes down 5%
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker', MagicMock(return_value={
-        'bid': 0.00001172 * 0.95,
-        'ask': 0.00001173 * 0.95,
-        'last': 0.00001172 * 0.95
-    }))
-
-    assert freqtrade.handle_trade(trade) is False
-    assert freqtrade.handle_stoploss_on_exchange(trade) is False
-
-    # stoploss should remain the same
-    assert trade.stop_loss == 0.000009384
-
-    # stoploss on exchange should not be canceled
-    cancel_order_mock.assert_not_called()
-
-    # price jumped 2x
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker', MagicMock(return_value={
-        'bid': 0.00002344,
-        'ask': 0.00002346,
-        'last': 0.00002344
-    }))
-
-    assert freqtrade.handle_trade(trade) is False
-    assert freqtrade.handle_stoploss_on_exchange(trade) is False
-
-    # stoploss should be set to 1% as trailing is on
-    assert trade.stop_loss == 0.00002344 * 0.99
-    cancel_order_mock.assert_called_once_with(100, 'NEO/BTC')
-    stoploss_order_mock.assert_called_once_with(amount=2131074.168797954,
-                                                pair='NEO/BTC',
-                                                rate=0.00002344 * 0.99 * 0.99,
-                                                stop_price=0.00002344 * 0.99)
-
-
-def test_process_maybe_execute_buy(mocker, default_conf) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-
-    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.create_trade', MagicMock(return_value=True))
-    assert freqtrade.process_maybe_execute_buy()
-
-    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.create_trade', MagicMock(return_value=False))
-    assert not freqtrade.process_maybe_execute_buy()
-
-
-def test_process_maybe_execute_buy_exception(mocker, default_conf, caplog) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-
-    mocker.patch(
-        'freqtrade.freqtradebot.FreqtradeBot.create_trade',
-        MagicMock(side_effect=DependencyException)
-    )
-    freqtrade.process_maybe_execute_buy()
-    log_has('Unable to create trade:', caplog.record_tuples)
-
-
-def test_process_maybe_execute_sell(mocker, default_conf, limit_buy_order, caplog) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-
-    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_trade', MagicMock(return_value=True))
-    mocker.patch('freqtrade.exchange.Exchange.get_order', return_value=limit_buy_order)
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
-    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
-                 return_value=limit_buy_order['amount'])
-
-    trade = MagicMock()
-    trade.open_order_id = '123'
-    trade.open_fee = 0.001
-    assert not freqtrade.process_maybe_execute_sell(trade)
-    # Test amount not modified by fee-logic
-    assert not log_has(
-        'Applying fee to amount for Trade {} from 90.99181073 to 90.81'.format(trade),
-        caplog.record_tuples
-    )
-
-    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', return_value=90.81)
-    # test amount modified by fee-logic
-    assert not freqtrade.process_maybe_execute_sell(trade)
-
-
-def test_process_maybe_execute_sell_exception(mocker, default_conf,
-                                              limit_buy_order, caplog) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    mocker.patch('freqtrade.exchange.Exchange.get_order', return_value=limit_buy_order)
-
-    trade = MagicMock()
-    trade.open_order_id = '123'
-    trade.open_fee = 0.001
-
-    # Test raise of DependencyException exception
-    mocker.patch(
-        'freqtrade.freqtradebot.FreqtradeBot.update_trade_state',
-        side_effect=DependencyException()
-    )
-    freqtrade.process_maybe_execute_sell(trade)
-    assert log_has('Unable to sell trade: ', caplog.record_tuples)
-
-
-def test_update_trade_state(mocker, default_conf, limit_buy_order, caplog) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-
-    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_trade', MagicMock(return_value=True))
-    mocker.patch('freqtrade.exchange.Exchange.get_order', return_value=limit_buy_order)
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
-    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
-                 return_value=limit_buy_order['amount'])
-
-    trade = Trade()
-    # Mock session away
-    Trade.session = MagicMock()
-    trade.open_order_id = '123'
-    trade.open_fee = 0.001
-    freqtrade.update_trade_state(trade)
-    # Test amount not modified by fee-logic
-    assert not log_has_re(r'Applying fee to .*', caplog.record_tuples)
-    assert trade.open_order_id is None
-    assert trade.amount == limit_buy_order['amount']
-
-    trade.open_order_id = '123'
-    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', return_value=90.81)
-    assert trade.amount != 90.81
-    # test amount modified by fee-logic
-    freqtrade.update_trade_state(trade)
-    assert trade.amount == 90.81
-    assert trade.open_order_id is None
-
-    trade.is_open = True
-    trade.open_order_id = None
-    # Assert we call handle_trade() if trade is feasible for execution
-    freqtrade.update_trade_state(trade)
-
-    assert log_has_re('Found open order for.*', caplog.record_tuples)
-
-
-def test_update_trade_state_withorderdict(default_conf, trades_for_order, limit_buy_order, mocker):
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
-    # get_order should not be called!!
-    mocker.patch('freqtrade.exchange.Exchange.get_order', MagicMock(side_effect=ValueError))
-    patch_exchange(mocker)
-    Trade.session = MagicMock()
-    amount = sum(x['amount'] for x in trades_for_order)
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        open_rate=0.245441,
-        open_order_id="123456",
-        is_open=True,
-    )
-    freqtrade.update_trade_state(trade, limit_buy_order)
-    assert trade.amount != amount
-    assert trade.amount == limit_buy_order['amount']
-
-
-def test_update_trade_state_exception(mocker, default_conf,
-                                      limit_buy_order, caplog) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    mocker.patch('freqtrade.exchange.Exchange.get_order', return_value=limit_buy_order)
-
-    trade = MagicMock()
-    trade.open_order_id = '123'
-    trade.open_fee = 0.001
-
-    # Test raise of OperationalException exception
-    mocker.patch(
-        'freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
-        side_effect=OperationalException()
-    )
-    freqtrade.update_trade_state(trade)
-    assert log_has('Could not update trade amount: ', caplog.record_tuples)
-
-
-def test_update_trade_state_sell(default_conf, trades_for_order, limit_sell_order, mocker):
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
-    # get_order should not be called!!
-    mocker.patch('freqtrade.exchange.Exchange.get_order', MagicMock(side_effect=ValueError))
-    wallet_mock = MagicMock()
-    mocker.patch('freqtrade.wallets.Wallets.update', wallet_mock)
-
-    patch_exchange(mocker)
-    Trade.session = MagicMock()
-    amount = limit_sell_order["amount"]
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    wallet_mock.reset_mock()
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        open_rate=0.245441,
-        fee_open=0.0025,
-        fee_close=0.0025,
-        open_order_id="123456",
-        is_open=True,
-    )
-    freqtrade.update_trade_state(trade, limit_sell_order)
-    assert trade.amount == limit_sell_order['amount']
-    # Wallet needs to be updated after closing a limit-sell order to reenable buying
-    assert wallet_mock.call_count == 1
-    assert not trade.is_open
-
-
-def test_handle_trade(default_conf, limit_buy_order, limit_sell_order,
-                      fee, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        sell=MagicMock(return_value={'id': limit_sell_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    assert trade
-
-    time.sleep(0.01)  # Race condition fix
-    trade.update(limit_buy_order)
-    assert trade.is_open is True
-
-    patch_get_signal(freqtrade, value=(False, True))
-    assert freqtrade.handle_trade(trade) is True
-    assert trade.open_order_id == limit_sell_order['id']
-
-    # Simulate fulfilled LIMIT_SELL order for trade
-    trade.update(limit_sell_order)
-
-    assert trade.close_rate == 0.00001173
-    assert trade.close_profit == 0.06201058
-    assert trade.calc_profit() == 0.00006217
-    assert trade.close_date is not None
-
-
-def test_handle_overlpapping_signals(default_conf, ticker, limit_buy_order,
-                                     fee, markets, mocker) -> None:
-    default_conf.update({'experimental': {'use_sell_signal': True}})
-
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade, value=(True, True))
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-
-    freqtrade.create_trade()
-
-    # Buy and Sell triggering, so doing nothing ...
-    trades = Trade.query.all()
-    nb_trades = len(trades)
-    assert nb_trades == 0
-
-    # Buy is triggering, so buying ...
-    patch_get_signal(freqtrade, value=(True, False))
-    freqtrade.create_trade()
-    trades = Trade.query.all()
-    nb_trades = len(trades)
-    assert nb_trades == 1
-    assert trades[0].is_open is True
-
-    # Buy and Sell are not triggering, so doing nothing ...
-    patch_get_signal(freqtrade, value=(False, False))
-    assert freqtrade.handle_trade(trades[0]) is False
-    trades = Trade.query.all()
-    nb_trades = len(trades)
-    assert nb_trades == 1
-    assert trades[0].is_open is True
-
-    # Buy and Sell are triggering, so doing nothing ...
-    patch_get_signal(freqtrade, value=(True, True))
-    assert freqtrade.handle_trade(trades[0]) is False
-    trades = Trade.query.all()
-    nb_trades = len(trades)
-    assert nb_trades == 1
-    assert trades[0].is_open is True
-
-    # Sell is triggering, guess what : we are Selling!
-    patch_get_signal(freqtrade, value=(False, True))
-    trades = Trade.query.all()
-    assert freqtrade.handle_trade(trades[0]) is True
-
-
-def test_handle_trade_roi(default_conf, ticker, limit_buy_order,
-                          fee, mocker, markets, caplog) -> None:
-    caplog.set_level(logging.DEBUG)
-    default_conf.update({'experimental': {'use_sell_signal': True}})
-
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade, value=(True, False))
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=True)
-
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    trade.is_open = True
-
-    # FIX: sniffing logs, suggest handle_trade should not execute_sell
-    #      instead that responsibility should be moved out of handle_trade(),
-    #      we might just want to check if we are in a sell condition without
-    #      executing
-    # if ROI is reached we must sell
-    patch_get_signal(freqtrade, value=(False, True))
-    assert freqtrade.handle_trade(trade)
-    assert log_has('Required profit reached. Selling..', caplog.record_tuples)
-
-
-def test_handle_trade_experimental(
-        default_conf, ticker, limit_buy_order, fee, mocker, markets, caplog) -> None:
-    caplog.set_level(logging.DEBUG)
-    default_conf.update({'experimental': {'use_sell_signal': True}})
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    trade.is_open = True
-
-    patch_get_signal(freqtrade, value=(False, False))
-    assert not freqtrade.handle_trade(trade)
-
-    patch_get_signal(freqtrade, value=(False, True))
-    assert freqtrade.handle_trade(trade)
-    assert log_has('Sell signal received. Selling..', caplog.record_tuples)
-
-
-def test_close_trade(default_conf, ticker, limit_buy_order, limit_sell_order,
-                     fee, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Create trade and sell it
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    assert trade
-
-    trade.update(limit_buy_order)
-    trade.update(limit_sell_order)
-    assert trade.is_open is False
-
-    with pytest.raises(ValueError, match=r'.*closed trade.*'):
-        freqtrade.handle_trade(trade)
-
-
-def test_check_handle_timedout_buy(default_conf, ticker, limit_buy_order_old, fee, mocker) -> None:
-    rpc_mock = patch_RPCManager(mocker)
-    cancel_order_mock = MagicMock()
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        get_order=MagicMock(return_value=limit_buy_order_old),
-        cancel_order=cancel_order_mock,
-        get_fee=fee
-    )
-    freqtrade = FreqtradeBot(default_conf)
-
-    trade_buy = Trade(
-        pair='ETH/BTC',
-        open_rate=0.00001099,
-        exchange='bittrex',
-        open_order_id='123456789',
-        amount=90.99181073,
-        fee_open=0.0,
-        fee_close=0.0,
-        stake_amount=1,
-        open_date=arrow.utcnow().shift(minutes=-601).datetime,
-        is_open=True
-    )
-
-    Trade.session.add(trade_buy)
-
-    # check it does cancel buy orders over the time limit
-    freqtrade.check_handle_timedout()
-    assert cancel_order_mock.call_count == 1
-    assert rpc_mock.call_count == 1
-    trades = Trade.query.filter(Trade.open_order_id.is_(trade_buy.open_order_id)).all()
-    nb_trades = len(trades)
-    assert nb_trades == 0
-
-
-def test_check_handle_cancelled_buy(default_conf, ticker, limit_buy_order_old,
-                                    fee, mocker, caplog) -> None:
-    """ Handle Buy order cancelled on exchange"""
-    rpc_mock = patch_RPCManager(mocker)
-    cancel_order_mock = MagicMock()
-    patch_exchange(mocker)
-    limit_buy_order_old.update({"status": "canceled"})
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        get_order=MagicMock(return_value=limit_buy_order_old),
-        cancel_order=cancel_order_mock,
-        get_fee=fee
-    )
-    freqtrade = FreqtradeBot(default_conf)
-
-    trade_buy = Trade(
-        pair='ETH/BTC',
-        open_rate=0.00001099,
-        exchange='bittrex',
-        open_order_id='123456789',
-        amount=90.99181073,
-        fee_open=0.0,
-        fee_close=0.0,
-        stake_amount=1,
-        open_date=arrow.utcnow().shift(minutes=-601).datetime,
-        is_open=True
-    )
-
-    Trade.session.add(trade_buy)
-
-    # check it does cancel buy orders over the time limit
-    freqtrade.check_handle_timedout()
-    assert cancel_order_mock.call_count == 0
-    assert rpc_mock.call_count == 1
-    trades = Trade.query.filter(Trade.open_order_id.is_(trade_buy.open_order_id)).all()
-    nb_trades = len(trades)
-    assert nb_trades == 0
-    assert log_has_re("Buy order canceled on Exchange for Trade.*", caplog.record_tuples)
-
-
-def test_check_handle_timedout_buy_exception(default_conf, ticker, limit_buy_order_old,
-                                             fee, mocker) -> None:
-    rpc_mock = patch_RPCManager(mocker)
-    cancel_order_mock = MagicMock()
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        validate_pairs=MagicMock(),
-        get_ticker=ticker,
-        get_order=MagicMock(side_effect=DependencyException),
-        cancel_order=cancel_order_mock,
-        get_fee=fee
-    )
-    freqtrade = FreqtradeBot(default_conf)
-
-    trade_buy = Trade(
-        pair='ETH/BTC',
-        open_rate=0.00001099,
-        exchange='bittrex',
-        open_order_id='123456789',
-        amount=90.99181073,
-        fee_open=0.0,
-        fee_close=0.0,
-        stake_amount=1,
-        open_date=arrow.utcnow().shift(minutes=-601).datetime,
-        is_open=True
-    )
-
-    Trade.session.add(trade_buy)
-
-    # check it does cancel buy orders over the time limit
-    freqtrade.check_handle_timedout()
-    assert cancel_order_mock.call_count == 0
-    assert rpc_mock.call_count == 0
-    trades = Trade.query.filter(Trade.open_order_id.is_(trade_buy.open_order_id)).all()
-    nb_trades = len(trades)
-    assert nb_trades == 1
-
-
-def test_check_handle_timedout_sell(default_conf, ticker, limit_sell_order_old, mocker) -> None:
-    rpc_mock = patch_RPCManager(mocker)
-    cancel_order_mock = MagicMock()
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        get_order=MagicMock(return_value=limit_sell_order_old),
-        cancel_order=cancel_order_mock
-    )
-    freqtrade = FreqtradeBot(default_conf)
-
-    trade_sell = Trade(
-        pair='ETH/BTC',
-        open_rate=0.00001099,
-        exchange='bittrex',
-        open_order_id='123456789',
-        amount=90.99181073,
-        fee_open=0.0,
-        fee_close=0.0,
-        stake_amount=1,
-        open_date=arrow.utcnow().shift(hours=-5).datetime,
-        close_date=arrow.utcnow().shift(minutes=-601).datetime,
-        is_open=False
-    )
-
-    Trade.session.add(trade_sell)
-
-    # check it does cancel sell orders over the time limit
-    freqtrade.check_handle_timedout()
-    assert cancel_order_mock.call_count == 1
-    assert rpc_mock.call_count == 1
-    assert trade_sell.is_open is True
-
-
-def test_check_handle_cancelled_sell(default_conf, ticker, limit_sell_order_old,
-                                     mocker, caplog) -> None:
-    """ Handle sell order cancelled on exchange"""
-    rpc_mock = patch_RPCManager(mocker)
-    cancel_order_mock = MagicMock()
-    limit_sell_order_old.update({"status": "canceled"})
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        get_order=MagicMock(return_value=limit_sell_order_old),
-        cancel_order=cancel_order_mock
-    )
-    freqtrade = FreqtradeBot(default_conf)
-
-    trade_sell = Trade(
-        pair='ETH/BTC',
-        open_rate=0.00001099,
-        exchange='bittrex',
-        open_order_id='123456789',
-        amount=90.99181073,
-        fee_open=0.0,
-        fee_close=0.0,
-        stake_amount=1,
-        open_date=arrow.utcnow().shift(hours=-5).datetime,
-        close_date=arrow.utcnow().shift(minutes=-601).datetime,
-        is_open=False
-    )
-
-    Trade.session.add(trade_sell)
-
-    # check it does cancel sell orders over the time limit
-    freqtrade.check_handle_timedout()
-    assert cancel_order_mock.call_count == 0
-    assert rpc_mock.call_count == 1
-    assert trade_sell.is_open is True
-    assert log_has_re("Sell order canceled on exchange for Trade.*", caplog.record_tuples)
-
-
-def test_check_handle_timedout_partial(default_conf, ticker, limit_buy_order_old_partial,
-                                       mocker) -> None:
-    rpc_mock = patch_RPCManager(mocker)
-    cancel_order_mock = MagicMock()
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        get_order=MagicMock(return_value=limit_buy_order_old_partial),
-        cancel_order=cancel_order_mock
-    )
-    freqtrade = FreqtradeBot(default_conf)
-
-    trade_buy = Trade(
-        pair='ETH/BTC',
-        open_rate=0.00001099,
-        exchange='bittrex',
-        open_order_id='123456789',
-        amount=90.99181073,
-        fee_open=0.0,
-        fee_close=0.0,
-        stake_amount=1,
-        open_date=arrow.utcnow().shift(minutes=-601).datetime,
-        is_open=True
-    )
-
-    Trade.session.add(trade_buy)
-
-    # check it does cancel buy orders over the time limit
-    # note this is for a partially-complete buy order
-    freqtrade.check_handle_timedout()
-    assert cancel_order_mock.call_count == 1
-    assert rpc_mock.call_count == 1
-    trades = Trade.query.filter(Trade.open_order_id.is_(trade_buy.open_order_id)).all()
-    assert len(trades) == 1
-    assert trades[0].amount == 23.0
-    assert trades[0].stake_amount == trade_buy.open_rate * trades[0].amount
-
-
-def test_check_handle_timedout_exception(default_conf, ticker, mocker, caplog) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    cancel_order_mock = MagicMock()
-
-    mocker.patch.multiple(
-        'freqtrade.freqtradebot.FreqtradeBot',
-        handle_timedout_limit_buy=MagicMock(),
-        handle_timedout_limit_sell=MagicMock(),
-    )
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        get_order=MagicMock(side_effect=requests.exceptions.RequestException('Oh snap')),
-        cancel_order=cancel_order_mock
-    )
-    freqtrade = FreqtradeBot(default_conf)
-
-    trade_buy = Trade(
-        pair='ETH/BTC',
-        open_rate=0.00001099,
-        exchange='bittrex',
-        open_order_id='123456789',
-        amount=90.99181073,
-        fee_open=0.0,
-        fee_close=0.0,
-        stake_amount=1,
-        open_date=arrow.utcnow().shift(minutes=-601).datetime,
-        is_open=True
-    )
-
-    Trade.session.add(trade_buy)
-
-    freqtrade.check_handle_timedout()
-    assert log_has_re(r'Cannot query order for Trade\(id=1, pair=ETH/BTC, amount=90.99181073, '
-                      r'open_rate=0.00001099, open_since=10 hours ago\) due to Traceback \(most '
-                      r'recent call last\):\n.*', caplog.record_tuples)
-
-
-def test_handle_timedout_limit_buy(mocker, default_conf) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    cancel_order_mock = MagicMock()
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        cancel_order=cancel_order_mock
-    )
-
-    freqtrade = FreqtradeBot(default_conf)
-
-    Trade.session = MagicMock()
-    trade = MagicMock()
-    order = {'remaining': 1,
-             'amount': 1}
-    assert freqtrade.handle_timedout_limit_buy(trade, order)
-    assert cancel_order_mock.call_count == 1
-    order['amount'] = 2
-    assert not freqtrade.handle_timedout_limit_buy(trade, order)
-    assert cancel_order_mock.call_count == 2
-
-
-def test_handle_timedout_limit_sell(mocker, default_conf) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    cancel_order_mock = MagicMock()
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        cancel_order=cancel_order_mock
-    )
-
-    freqtrade = FreqtradeBot(default_conf)
-
-    trade = MagicMock()
-    order = {'remaining': 1,
-             'amount': 1,
-             'status': "open"}
-    assert freqtrade.handle_timedout_limit_sell(trade, order)
-    assert cancel_order_mock.call_count == 1
-    order['amount'] = 2
-    assert not freqtrade.handle_timedout_limit_sell(trade, order)
-    # Assert cancel_order was not called (callcount remains unchanged)
-    assert cancel_order_mock.call_count == 1
-
-
-def test_execute_sell_up(default_conf, ticker, fee, ticker_sell_up, markets, mocker) -> None:
-    rpc_mock = patch_RPCManager(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        _load_markets=MagicMock(return_value={}),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Create some test data
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    assert trade
-
-    # Increase the price and sell it
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker_sell_up
-    )
-
-    freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'], sell_reason=SellType.ROI)
-
-    assert rpc_mock.call_count == 2
-    last_msg = rpc_mock.call_args_list[-1][0][0]
-    assert {
-        'type': RPCMessageType.SELL_NOTIFICATION,
-        'exchange': 'Bittrex',
-        'pair': 'ETH/BTC',
-        'gain': 'profit',
-        'limit': 1.172e-05,
-        'amount': 90.99181073703367,
-        'order_type': 'limit',
-        'open_rate': 1.099e-05,
-        'current_rate': 1.172e-05,
-        'profit_amount': 6.126e-05,
-        'profit_percent': 0.0611052,
-        'stake_currency': 'BTC',
-        'fiat_currency': 'USD',
-        'sell_reason': SellType.ROI.value
-    } == last_msg
-
-
-def test_execute_sell_down(default_conf, ticker, fee, ticker_sell_down, markets, mocker) -> None:
-    rpc_mock = patch_RPCManager(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        _load_markets=MagicMock(return_value={}),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Create some test data
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    assert trade
-
-    # Decrease the price and sell it
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker_sell_down
-    )
-
-    freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
-                           sell_reason=SellType.STOP_LOSS)
-
-    assert rpc_mock.call_count == 2
-    last_msg = rpc_mock.call_args_list[-1][0][0]
-    assert {
-        'type': RPCMessageType.SELL_NOTIFICATION,
-        'exchange': 'Bittrex',
-        'pair': 'ETH/BTC',
-        'gain': 'loss',
-        'limit': 1.044e-05,
-        'amount': 90.99181073703367,
-        'order_type': 'limit',
-        'open_rate': 1.099e-05,
-        'current_rate': 1.044e-05,
-        'profit_amount': -5.492e-05,
-        'profit_percent': -0.05478342,
-        'stake_currency': 'BTC',
-        'fiat_currency': 'USD',
-        'sell_reason': SellType.STOP_LOSS.value
-    } == last_msg
-
-
-def test_execute_sell_down_stoploss_on_exchange_dry_run(default_conf, ticker, fee,
-                                                        ticker_sell_down,
-                                                        markets, mocker) -> None:
-    rpc_mock = patch_RPCManager(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        _load_markets=MagicMock(return_value={}),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Create some test data
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    assert trade
-
-    # Decrease the price and sell it
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker_sell_down
-    )
-
-    default_conf['dry_run'] = True
-    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
-    # Setting trade stoploss to 0.01
-
-    trade.stop_loss = 0.00001099 * 0.99
-    freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
-                           sell_reason=SellType.STOP_LOSS)
-
-    assert rpc_mock.call_count == 2
-    last_msg = rpc_mock.call_args_list[-1][0][0]
-
-    assert {
-        'type': RPCMessageType.SELL_NOTIFICATION,
-        'exchange': 'Bittrex',
-        'pair': 'ETH/BTC',
-        'gain': 'loss',
-        'limit': 1.08801e-05,
-        'amount': 90.99181073703367,
-        'order_type': 'limit',
-        'open_rate': 1.099e-05,
-        'current_rate': 1.044e-05,
-        'profit_amount': -1.498e-05,
-        'profit_percent': -0.01493766,
-        'stake_currency': 'BTC',
-        'fiat_currency': 'USD',
-        'sell_reason': SellType.STOP_LOSS.value
-
-    } == last_msg
-
-
-def test_execute_sell_sloe_cancel_exception(mocker, default_conf, ticker, fee,
-                                            markets, caplog) -> None:
-    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    mocker.patch('freqtrade.exchange.Exchange.cancel_order', side_effect=InvalidOrderException())
-    sellmock = MagicMock()
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        _load_markets=MagicMock(return_value={}),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets),
-        sell=sellmock
-    )
-
-    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
-    patch_get_signal(freqtrade)
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    Trade.session = MagicMock()
-
-    freqtrade.config['dry_run'] = False
-    trade.stoploss_order_id = "abcd"
-
-    freqtrade.execute_sell(trade=trade, limit=1234,
-                           sell_reason=SellType.STOP_LOSS)
-    assert sellmock.call_count == 1
-    assert log_has('Could not cancel stoploss order abcd', caplog.record_tuples)
-
-
-def test_execute_sell_with_stoploss_on_exchange(default_conf,
-                                                ticker, fee, ticker_sell_up,
-                                                markets, mocker) -> None:
-
-    default_conf['exchange']['name'] = 'binance'
-    rpc_mock = patch_RPCManager(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        _load_markets=MagicMock(return_value={}),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-
-    stoploss_limit = MagicMock(return_value={
-        'id': 123,
-        'info': {
-            'foo': 'bar'
-        }
-    })
-
-    cancel_order = MagicMock(return_value=True)
-
-    mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
-    mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
-    mocker.patch('freqtrade.exchange.Exchange.stoploss_limit', stoploss_limit)
-    mocker.patch('freqtrade.exchange.Exchange.cancel_order', cancel_order)
-
-    freqtrade = FreqtradeBot(default_conf)
-    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
-    patch_get_signal(freqtrade)
-
-    # Create some test data
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    assert trade
-
-    freqtrade.process_maybe_execute_sell(trade)
-
-    # Increase the price and sell it
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker_sell_up
-    )
-
-    freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
-                           sell_reason=SellType.SELL_SIGNAL)
-
-    trade = Trade.query.first()
-    assert trade
-    assert cancel_order.call_count == 1
-    assert rpc_mock.call_count == 2
-
-
-def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf,
-                                                         ticker, fee,
-                                                         limit_buy_order,
-                                                         markets, mocker) -> None:
-    default_conf['exchange']['name'] = 'binance'
-    rpc_mock = patch_RPCManager(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        _load_markets=MagicMock(return_value={}),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-
-    stoploss_limit = MagicMock(return_value={
-        'id': 123,
-        'info': {
-            'foo': 'bar'
-        }
-    })
-
-    mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
-    mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
-    mocker.patch('freqtrade.exchange.Exchange.stoploss_limit', stoploss_limit)
-
-    freqtrade = FreqtradeBot(default_conf)
-    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
-    patch_get_signal(freqtrade)
-
-    # Create some test data
-    freqtrade.create_trade()
-    trade = Trade.query.first()
-    freqtrade.process_maybe_execute_sell(trade)
-    assert trade
-    assert trade.stoploss_order_id == '123'
-    assert trade.open_order_id is None
-
-    # Assuming stoploss on exchnage is hit
-    # stoploss_order_id should become None
-    # and trade should be sold at the price of stoploss
-    stoploss_limit_executed = MagicMock(return_value={
-        "id": "123",
-        "timestamp": 1542707426845,
-        "datetime": "2018-11-20T09:50:26.845Z",
-        "lastTradeTimestamp": None,
-        "symbol": "BTC/USDT",
-        "type": "stop_loss_limit",
-        "side": "sell",
-        "price": 1.08801,
-        "amount": 90.99181074,
-        "cost": 99.0000000032274,
-        "average": 1.08801,
-        "filled": 90.99181074,
-        "remaining": 0.0,
-        "status": "closed",
-        "fee": None,
-        "trades": None
-    })
-    mocker.patch('freqtrade.exchange.Exchange.get_order', stoploss_limit_executed)
-
-    freqtrade.process_maybe_execute_sell(trade)
-    assert trade.stoploss_order_id is None
-    assert trade.is_open is False
-    print(trade.sell_reason)
-    assert trade.sell_reason == SellType.STOPLOSS_ON_EXCHANGE.value
-    assert rpc_mock.call_count == 2
-
-
-def test_execute_sell_without_conf_sell_up(default_conf, ticker, fee,
-                                           ticker_sell_up, markets, mocker) -> None:
-    rpc_mock = patch_RPCManager(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        _load_markets=MagicMock(return_value={}),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Create some test data
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    assert trade
-
-    # Increase the price and sell it
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker_sell_up
-    )
-    freqtrade.config = {}
-
-    freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'], sell_reason=SellType.ROI)
-
-    assert rpc_mock.call_count == 2
-    last_msg = rpc_mock.call_args_list[-1][0][0]
-    assert {
-        'type': RPCMessageType.SELL_NOTIFICATION,
-        'exchange': 'Bittrex',
-        'pair': 'ETH/BTC',
-        'gain': 'profit',
-        'limit': 1.172e-05,
-        'amount': 90.99181073703367,
-        'order_type': 'limit',
-        'open_rate': 1.099e-05,
-        'current_rate': 1.172e-05,
-        'profit_amount': 6.126e-05,
-        'profit_percent': 0.0611052,
-        'sell_reason': SellType.ROI.value
-
-    } == last_msg
-
-
-def test_execute_sell_without_conf_sell_down(default_conf, ticker, fee,
-                                             ticker_sell_down, markets, mocker) -> None:
-    rpc_mock = patch_RPCManager(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        _load_markets=MagicMock(return_value={}),
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Create some test data
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    assert trade
-
-    # Decrease the price and sell it
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker_sell_down
-    )
-
-    freqtrade.config = {}
-    freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
-                           sell_reason=SellType.STOP_LOSS)
-
-    assert rpc_mock.call_count == 2
-    last_msg = rpc_mock.call_args_list[-1][0][0]
-    assert {
-        'type': RPCMessageType.SELL_NOTIFICATION,
-        'exchange': 'Bittrex',
-        'pair': 'ETH/BTC',
-        'gain': 'loss',
-        'limit': 1.044e-05,
-        'amount': 90.99181073703367,
-        'order_type': 'limit',
-        'open_rate': 1.099e-05,
-        'current_rate': 1.044e-05,
-        'profit_amount': -5.492e-05,
-        'profit_percent': -0.05478342,
-        'sell_reason': SellType.STOP_LOSS.value
-    } == last_msg
-
-
-def test_sell_profit_only_enable_profit(default_conf, limit_buy_order,
-                                        fee, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.00002172,
-            'ask': 0.00002173,
-            'last': 0.00002172
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    default_conf['experimental'] = {
-        'use_sell_signal': True,
-        'sell_profit_only': True,
-    }
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    patch_get_signal(freqtrade, value=(False, True))
-    assert freqtrade.handle_trade(trade) is True
-    assert trade.sell_reason == SellType.SELL_SIGNAL.value
-
-
-def test_sell_profit_only_disable_profit(default_conf, limit_buy_order,
-                                         fee, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.00002172,
-            'ask': 0.00002173,
-            'last': 0.00002172
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    default_conf['experimental'] = {
-        'use_sell_signal': True,
-        'sell_profit_only': False,
-    }
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    patch_get_signal(freqtrade, value=(False, True))
-    assert freqtrade.handle_trade(trade) is True
-    assert trade.sell_reason == SellType.SELL_SIGNAL.value
-
-
-def test_sell_profit_only_enable_loss(default_conf, limit_buy_order, fee, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.00000172,
-            'ask': 0.00000173,
-            'last': 0.00000172
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    default_conf['experimental'] = {
-        'use_sell_signal': True,
-        'sell_profit_only': True,
-    }
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.stop_loss_reached = MagicMock(return_value=SellCheckTuple(
-            sell_flag=False, sell_type=SellType.NONE))
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    patch_get_signal(freqtrade, value=(False, True))
-    assert freqtrade.handle_trade(trade) is False
-
-
-def test_sell_profit_only_disable_loss(default_conf, limit_buy_order, fee, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.0000172,
-            'ask': 0.0000173,
-            'last': 0.0000172
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    default_conf['experimental'] = {
-        'use_sell_signal': True,
-        'sell_profit_only': False,
-    }
-
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    patch_get_signal(freqtrade, value=(False, True))
-    assert freqtrade.handle_trade(trade) is True
-    assert trade.sell_reason == SellType.SELL_SIGNAL.value
-
-
-def test_ignore_roi_if_buy_signal(default_conf, limit_buy_order, fee, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.0000172,
-            'ask': 0.0000173,
-            'last': 0.0000172
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    default_conf['experimental'] = {
-        'ignore_roi_if_buy_signal': True
-    }
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=True)
-
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    patch_get_signal(freqtrade, value=(True, True))
-    assert freqtrade.handle_trade(trade) is False
-
-    # Test if buy-signal is absent (should sell due to roi = true)
-    patch_get_signal(freqtrade, value=(False, True))
-    assert freqtrade.handle_trade(trade) is True
-    assert trade.sell_reason == SellType.ROI.value
-
-
-def test_trailing_stop_loss(default_conf, limit_buy_order, fee, markets, caplog, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.00001099,
-            'ask': 0.00001099,
-            'last': 0.00001099
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets),
-    )
-    default_conf['trailing_stop'] = True
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-
-    freqtrade.create_trade()
-    trade = Trade.query.first()
-    assert freqtrade.handle_trade(trade) is False
-
-    # Raise ticker above buy price
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(return_value={
-                     'bid': 0.00001099 * 1.5,
-                     'ask': 0.00001099 * 1.5,
-                     'last': 0.00001099 * 1.5
-                 }))
-
-    # Stoploss should be adjusted
-    assert freqtrade.handle_trade(trade) is False
-
-    # Price fell
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(return_value={
-                     'bid': 0.00001099 * 1.1,
-                     'ask': 0.00001099 * 1.1,
-                     'last': 0.00001099 * 1.1
-                 }))
-
-    caplog.set_level(logging.DEBUG)
-    # Sell as trailing-stop is reached
-    assert freqtrade.handle_trade(trade) is True
-    assert log_has(
-        f'HIT STOP: current price at 0.000012, stop loss is 0.000015, '
-        f'initial stop loss was at 0.000010, trade opened at 0.000011', caplog.record_tuples)
-    assert trade.sell_reason == SellType.TRAILING_STOP_LOSS.value
-
-
-def test_trailing_stop_loss_positive(default_conf, limit_buy_order, fee, markets,
-                                     caplog, mocker) -> None:
-    buy_price = limit_buy_order['price']
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': buy_price - 0.000001,
-            'ask': buy_price - 0.000001,
-            'last': buy_price - 0.000001
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets),
-    )
-    default_conf['trailing_stop'] = True
-    default_conf['trailing_stop_positive'] = 0.01
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    caplog.set_level(logging.DEBUG)
-    # stop-loss not reached
-    assert freqtrade.handle_trade(trade) is False
-
-    # Raise ticker above buy price
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(return_value={
-                     'bid': buy_price + 0.000003,
-                     'ask': buy_price + 0.000003,
-                     'last': buy_price + 0.000003
-                 }))
-    # stop-loss not reached, adjusted stoploss
-    assert freqtrade.handle_trade(trade) is False
-    assert log_has(f'using positive stop loss: 0.01 offset: 0 profit: 0.2666%',
-                   caplog.record_tuples)
-    assert log_has(f'adjusted stop loss', caplog.record_tuples)
-    assert trade.stop_loss == 0.0000138501
-
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(return_value={
-                     'bid': buy_price + 0.000002,
-                     'ask': buy_price + 0.000002,
-                     'last': buy_price + 0.000002
-                 }))
-    # Lower price again (but still positive)
-    assert freqtrade.handle_trade(trade) is True
-    assert log_has(
-        f'HIT STOP: current price at {buy_price + 0.000002:.6f}, '
-        f'stop loss is {trade.stop_loss:.6f}, '
-        f'initial stop loss was at 0.000010, trade opened at 0.000011', caplog.record_tuples)
-
-
-def test_trailing_stop_loss_offset(default_conf, limit_buy_order, fee,
-                                   caplog, mocker, markets) -> None:
-    buy_price = limit_buy_order['price']
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': buy_price - 0.000001,
-            'ask': buy_price - 0.000001,
-            'last': buy_price - 0.000001
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets),
-    )
-
-    default_conf['trailing_stop'] = True
-    default_conf['trailing_stop_positive'] = 0.01
-    default_conf['trailing_stop_positive_offset'] = 0.011
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    caplog.set_level(logging.DEBUG)
-    # stop-loss not reached
-    assert freqtrade.handle_trade(trade) is False
-
-    # Raise ticker above buy price
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(return_value={
-                     'bid': buy_price + 0.000003,
-                     'ask': buy_price + 0.000003,
-                     'last': buy_price + 0.000003
-                 }))
-    # stop-loss not reached, adjusted stoploss
-    assert freqtrade.handle_trade(trade) is False
-    assert log_has(f'using positive stop loss: 0.01 offset: 0.011 profit: 0.2666%',
-                   caplog.record_tuples)
-    assert log_has(f'adjusted stop loss', caplog.record_tuples)
-    assert trade.stop_loss == 0.0000138501
-
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(return_value={
-                     'bid': buy_price + 0.000002,
-                     'ask': buy_price + 0.000002,
-                     'last': buy_price + 0.000002
-                 }))
-    # Lower price again (but still positive)
-    assert freqtrade.handle_trade(trade) is True
-    assert log_has(
-        f'HIT STOP: current price at {buy_price + 0.000002:.6f}, '
-        f'stop loss is {trade.stop_loss:.6f}, '
-        f'initial stop loss was at 0.000010, trade opened at 0.000011', caplog.record_tuples)
-    assert trade.sell_reason == SellType.TRAILING_STOP_LOSS.value
-
-
-def test_tsl_only_offset_reached(default_conf, limit_buy_order, fee,
-                                 caplog, mocker, markets) -> None:
-    buy_price = limit_buy_order['price']
-    # buy_price: 0.00001099
-
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': buy_price,
-            'ask': buy_price,
-            'last': buy_price
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets),
-    )
-
-    default_conf['trailing_stop'] = True
-    default_conf['trailing_stop_positive'] = 0.05
-    default_conf['trailing_stop_positive_offset'] = 0.055
-    default_conf['trailing_only_offset_is_reached'] = True
-
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    caplog.set_level(logging.DEBUG)
-    # stop-loss not reached
-    assert freqtrade.handle_trade(trade) is False
-    assert trade.stop_loss == 0.0000098910
-
-    # Raise ticker above buy price
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(return_value={
-                     'bid': buy_price + 0.0000004,
-                     'ask': buy_price + 0.0000004,
-                     'last': buy_price + 0.0000004
-                 }))
-
-    # stop-loss should not be adjusted as offset is not reached yet
-    assert freqtrade.handle_trade(trade) is False
-
-    assert not log_has(f'adjusted stop loss', caplog.record_tuples)
-    assert trade.stop_loss == 0.0000098910
-
-    # price rises above the offset (rises 12% when the offset is 5.5%)
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(return_value={
-                     'bid': buy_price + 0.0000014,
-                     'ask': buy_price + 0.0000014,
-                     'last': buy_price + 0.0000014
-                 }))
-
-    assert freqtrade.handle_trade(trade) is False
-    assert log_has(f'using positive stop loss: 0.05 offset: 0.055 profit: 0.1218%',
-                   caplog.record_tuples)
-    assert log_has(f'adjusted stop loss', caplog.record_tuples)
-    assert trade.stop_loss == 0.0000117705
-
-
-def test_disable_ignore_roi_if_buy_signal(default_conf, limit_buy_order,
-                                          fee, markets, mocker) -> None:
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.00000172,
-            'ask': 0.00000173,
-            'last': 0.00000172
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    default_conf['experimental'] = {
-        'ignore_roi_if_buy_signal': False
-    }
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.strategy.min_roi_reached = MagicMock(return_value=True)
-
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    # Sell due to min_roi_reached
-    patch_get_signal(freqtrade, value=(True, True))
-    assert freqtrade.handle_trade(trade) is True
-
-    # Test if buy-signal is absent
-    patch_get_signal(freqtrade, value=(False, True))
-    assert freqtrade.handle_trade(trade) is True
-    assert trade.sell_reason == SellType.STOP_LOSS.value
-
-
-def test_get_real_amount_quote(default_conf, trades_for_order, buy_order_fee, caplog, mocker):
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    amount = sum(x['amount'] for x in trades_for_order)
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Amount is reduced by "fee"
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount - (amount * 0.001)
-    assert log_has('Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
-                   'open_rate=0.24544100, open_since=closed) (from 8.0 to 7.992) from Trades',
-                   caplog.record_tuples)
-
-
-def test_get_real_amount_no_trade(default_conf, buy_order_fee, caplog, mocker):
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
-
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    amount = buy_order_fee['amount']
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Amount is reduced by "fee"
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
-    assert log_has('Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
-                   'open_rate=0.24544100, open_since=closed) failed: myTrade-Dict empty found',
-                   caplog.record_tuples)
-
-
-def test_get_real_amount_stake(default_conf, trades_for_order, buy_order_fee, mocker):
-    trades_for_order[0]['fee']['currency'] = 'ETH'
-
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
-    amount = sum(x['amount'] for x in trades_for_order)
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Amount does not change
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
-
-
-def test_get_real_amount_no_currency_in_fee(default_conf, trades_for_order, buy_order_fee, mocker):
-
-    limit_buy_order = deepcopy(buy_order_fee)
-    limit_buy_order['fee'] = {'cost': 0.004, 'currency': None}
-    trades_for_order[0]['fee']['currency'] = None
-
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
-    amount = sum(x['amount'] for x in trades_for_order)
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Amount does not change
-    assert freqtrade.get_real_amount(trade, limit_buy_order) == amount
-
-
-def test_get_real_amount_BNB(default_conf, trades_for_order, buy_order_fee, mocker):
-    trades_for_order[0]['fee']['currency'] = 'BNB'
-    trades_for_order[0]['fee']['cost'] = 0.00094518
-
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
-    amount = sum(x['amount'] for x in trades_for_order)
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Amount does not change
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
-
-
-def test_get_real_amount_multi(default_conf, trades_for_order2, buy_order_fee, caplog, mocker):
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order2)
-    amount = float(sum(x['amount'] for x in trades_for_order2))
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Amount is reduced by "fee"
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount - (amount * 0.001)
-    assert log_has('Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
-                   'open_rate=0.24544100, open_since=closed) (from 8.0 to 7.992) from Trades',
-                   caplog.record_tuples)
-
-
-def test_get_real_amount_fromorder(default_conf, trades_for_order, buy_order_fee, caplog, mocker):
-    limit_buy_order = deepcopy(buy_order_fee)
-    limit_buy_order['fee'] = {'cost': 0.004, 'currency': 'LTC'}
-
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order',
-                 return_value=[trades_for_order])
-    amount = float(sum(x['amount'] for x in trades_for_order))
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Amount is reduced by "fee"
-    assert freqtrade.get_real_amount(trade, limit_buy_order) == amount - 0.004
-    assert log_has('Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
-                   'open_rate=0.24544100, open_since=closed) (from 8.0 to 7.996) from Order',
-                   caplog.record_tuples)
-
-
-def test_get_real_amount_invalid_order(default_conf, trades_for_order, buy_order_fee, mocker):
-    limit_buy_order = deepcopy(buy_order_fee)
-    limit_buy_order['fee'] = {'cost': 0.004}
-
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
-    amount = float(sum(x['amount'] for x in trades_for_order))
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    # Amount does not change
-    assert freqtrade.get_real_amount(trade, limit_buy_order) == amount
-
-
-def test_get_real_amount_invalid(default_conf, trades_for_order, buy_order_fee, mocker):
-    # Remove "Currency" from fee dict
-    trades_for_order[0]['fee'] = {'cost': 0.008}
-
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
-    amount = sum(x['amount'] for x in trades_for_order)
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    # Amount does not change
-    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
-
-
-def test_get_real_amount_open_trade(default_conf, mocker):
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    amount = 12345
-    trade = Trade(
-        pair='LTC/ETH',
-        amount=amount,
-        exchange='binance',
-        open_rate=0.245441,
-        open_order_id="123456"
-    )
-    order = {
-        'id': 'mocked_order',
-        'amount': amount,
-        'status': 'open',
-    }
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    assert freqtrade.get_real_amount(trade, order) == amount
-
-
-def test_order_book_depth_of_market(default_conf, ticker, limit_buy_order, fee, markets, mocker,
-                                    order_book_l2):
-    default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
-    default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 0.1
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.exchange.Exchange.get_order_book', order_book_l2)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-
-    # Save state of current whitelist
-    whitelist = deepcopy(default_conf['exchange']['pair_whitelist'])
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    assert trade is not None
-    assert trade.stake_amount == 0.001
-    assert trade.is_open
-    assert trade.open_date is not None
-    assert trade.exchange == 'bittrex'
-
-    # Simulate fulfilled LIMIT_BUY order for trade
-    trade.update(limit_buy_order)
-
-    assert trade.open_rate == 0.00001099
-    assert whitelist == default_conf['exchange']['pair_whitelist']
-
-
-def test_order_book_depth_of_market_high_delta(default_conf, ticker, limit_buy_order,
-                                               fee, markets, mocker, order_book_l2):
-    default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
-    # delta is 100 which is impossible to reach. hence check_depth_of_market will return false
-    default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 100
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch('freqtrade.exchange.Exchange.get_order_book', order_book_l2)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    # Save state of current whitelist
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    assert trade is None
-
-
-def test_order_book_bid_strategy1(mocker, default_conf, order_book_l2, markets) -> None:
-    """
-    test if function get_target_bid will return the order book price
-    instead of the ask rate
-    """
-    patch_exchange(mocker)
-    ticker_mock = MagicMock(return_value={'ask': 0.045, 'last': 0.046})
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        markets=PropertyMock(return_value=markets),
-        get_order_book=order_book_l2,
-        get_ticker=ticker_mock,
-
-    )
-    default_conf['exchange']['name'] = 'binance'
-    default_conf['bid_strategy']['use_order_book'] = True
-    default_conf['bid_strategy']['order_book_top'] = 2
-    default_conf['bid_strategy']['ask_last_balance'] = 0
-    default_conf['telegram']['enabled'] = False
-
-    freqtrade = FreqtradeBot(default_conf)
-    assert freqtrade.get_target_bid('ETH/BTC') == 0.043935
-    assert ticker_mock.call_count == 0
-
-
-def test_order_book_bid_strategy2(mocker, default_conf, order_book_l2, markets) -> None:
-    """
-    test if function get_target_bid will return the ask rate (since its value is lower)
-    instead of the order book rate (even if enabled)
-    """
-    patch_exchange(mocker)
-    ticker_mock = MagicMock(return_value={'ask': 0.042, 'last': 0.046})
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        markets=PropertyMock(return_value=markets),
-        get_order_book=order_book_l2,
-        get_ticker=ticker_mock,
-
-    )
-    default_conf['exchange']['name'] = 'binance'
-    default_conf['bid_strategy']['use_order_book'] = True
-    default_conf['bid_strategy']['order_book_top'] = 2
-    default_conf['bid_strategy']['ask_last_balance'] = 0
-    default_conf['telegram']['enabled'] = False
-
-    freqtrade = FreqtradeBot(default_conf)
-    # ordrebook shall be used even if tickers would be lower.
-    assert freqtrade.get_target_bid('ETH/BTC', ) != 0.042
-    assert ticker_mock.call_count == 0
-
-
-def test_check_depth_of_market_buy(default_conf, mocker, order_book_l2, markets) -> None:
-    """
-    test check depth of market
-    """
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        markets=PropertyMock(return_value=markets),
-        get_order_book=order_book_l2
-    )
-    default_conf['telegram']['enabled'] = False
-    default_conf['exchange']['name'] = 'binance'
-    default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
-    # delta is 100 which is impossible to reach. hence function will return false
-    default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 100
-    freqtrade = FreqtradeBot(default_conf)
-
-    conf = default_conf['bid_strategy']['check_depth_of_market']
-    assert freqtrade._check_depth_of_market_buy('ETH/BTC', conf) is False
-
-
-def test_order_book_ask_strategy(default_conf, limit_buy_order, limit_sell_order,
-                                 fee, markets, mocker, order_book_l2) -> None:
-    """
-    test order book ask strategy
-    """
-    mocker.patch('freqtrade.exchange.Exchange.get_order_book', order_book_l2)
-    default_conf['exchange']['name'] = 'binance'
-    default_conf['ask_strategy']['use_order_book'] = True
-    default_conf['ask_strategy']['order_book_min'] = 1
-    default_conf['ask_strategy']['order_book_max'] = 2
-    default_conf['telegram']['enabled'] = False
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
-            'ask': 0.00001173,
-            'last': 0.00001172
-        }),
-        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
-        sell=MagicMock(return_value={'id': limit_sell_order['id']}),
-        get_fee=fee,
-        markets=PropertyMock(return_value=markets)
-    )
-    freqtrade = FreqtradeBot(default_conf)
-    patch_get_signal(freqtrade)
-
-    freqtrade.create_trade()
-
-    trade = Trade.query.first()
-    assert trade
-
-    time.sleep(0.01)  # Race condition fix
-    trade.update(limit_buy_order)
-    assert trade.is_open is True
-
-    patch_get_signal(freqtrade, value=(False, True))
-    assert freqtrade.handle_trade(trade) is True
-
-
-def test_get_sell_rate(default_conf, mocker, ticker, order_book_l2) -> None:
-
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_order_book=order_book_l2,
-        get_ticker=ticker,
-    )
-    pair = "ETH/BTC"
-
-    # Test regular mode
-    ft = get_patched_freqtradebot(mocker, default_conf)
-    rate = ft.get_sell_rate(pair, True)
-    assert isinstance(rate, float)
-    assert rate == 0.00001098
-
-    # Test orderbook mode
-    default_conf['ask_strategy']['use_order_book'] = True
-    default_conf['ask_strategy']['order_book_min'] = 1
-    default_conf['ask_strategy']['order_book_max'] = 2
-    ft = get_patched_freqtradebot(mocker, default_conf)
-    rate = ft.get_sell_rate(pair, True)
-    assert isinstance(rate, float)
-    assert rate == 0.043936
-
-
-def test_startup_state(default_conf, mocker):
-    default_conf['pairlist'] = {'method': 'VolumePairList',
-                                'config': {'number_assets': 20}
-                                }
-    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
-    worker = get_patched_worker(mocker, default_conf)
-    assert worker.state is State.RUNNING
-
-
-def test_startup_trade_reinit(default_conf, edge_conf, mocker):
-
-    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
-    reinit_mock = MagicMock()
-    mocker.patch('freqtrade.persistence.Trade.stoploss_reinitialization', reinit_mock)
-
-    ftbot = get_patched_freqtradebot(mocker, default_conf)
-    ftbot.startup()
-    assert reinit_mock.call_count == 1
-
-    reinit_mock.reset_mock()
-
-    ftbot = get_patched_freqtradebot(mocker, edge_conf)
-    ftbot.startup()
-    assert reinit_mock.call_count == 0
diff --git a/freqtrade/tests/test_indicator_helpers.py b/freqtrade/tests/test_indicator_helpers.py
deleted file mode 100644
index 99d6cd79c..000000000
--- a/freqtrade/tests/test_indicator_helpers.py
+++ /dev/null
@@ -1,15 +0,0 @@
-# pragma pylint: disable=missing-docstring
-
-import pandas as pd
-
-from freqtrade.indicator_helpers import went_down, went_up
-
-
-def test_went_up():
-    series = pd.Series([1, 2, 3, 1])
-    assert went_up(series).equals(pd.Series([False, True, True, False]))
-
-
-def test_went_down():
-    series = pd.Series([1, 2, 3, 1])
-    assert went_down(series).equals(pd.Series([False, False, False, True]))
diff --git a/freqtrade/tests/test_misc.py b/freqtrade/tests/test_misc.py
deleted file mode 100644
index 1a6b2a92d..000000000
--- a/freqtrade/tests/test_misc.py
+++ /dev/null
@@ -1,70 +0,0 @@
-# pragma pylint: disable=missing-docstring,C0103
-
-import datetime
-from unittest.mock import MagicMock
-
-from freqtrade.data.converter import parse_ticker_dataframe
-from freqtrade.data.history import pair_data_filename
-from freqtrade.misc import (datesarray_to_datetimearray, file_dump_json,
-                            file_load_json, format_ms_time, shorten_date)
-
-
-def test_shorten_date() -> None:
-    str_data = '1 day, 2 hours, 3 minutes, 4 seconds ago'
-    str_shorten_data = '1 d, 2 h, 3 min, 4 sec ago'
-    assert shorten_date(str_data) == str_shorten_data
-
-
-def test_datesarray_to_datetimearray(ticker_history_list):
-    dataframes = parse_ticker_dataframe(ticker_history_list, "5m", pair="UNITTEST/BTC",
-                                        fill_missing=True)
-    dates = datesarray_to_datetimearray(dataframes['date'])
-
-    assert isinstance(dates[0], datetime.datetime)
-    assert dates[0].year == 2017
-    assert dates[0].month == 11
-    assert dates[0].day == 26
-    assert dates[0].hour == 8
-    assert dates[0].minute == 50
-
-    date_len = len(dates)
-    assert date_len == 2
-
-
-def test_file_dump_json(mocker) -> None:
-    file_open = mocker.patch('freqtrade.misc.open', MagicMock())
-    json_dump = mocker.patch('rapidjson.dump', MagicMock())
-    file_dump_json('somefile', [1, 2, 3])
-    assert file_open.call_count == 1
-    assert json_dump.call_count == 1
-    file_open = mocker.patch('freqtrade.misc.gzip.open', MagicMock())
-    json_dump = mocker.patch('rapidjson.dump', MagicMock())
-    file_dump_json('somefile', [1, 2, 3], True)
-    assert file_open.call_count == 1
-    assert json_dump.call_count == 1
-
-
-def test_file_load_json(mocker) -> None:
-
-    # 7m .json does not exist
-    ret = file_load_json(pair_data_filename(None, 'UNITTEST/BTC', '7m'))
-    assert not ret
-    # 1m json exists (but no .gz exists)
-    ret = file_load_json(pair_data_filename(None, 'UNITTEST/BTC', '1m'))
-    assert ret
-    # 8 .json is empty and will fail if it's loaded. .json.gz is a copy of 1.json
-    ret = file_load_json(pair_data_filename(None, 'UNITTEST/BTC', '8m'))
-    assert ret
-
-
-def test_format_ms_time() -> None:
-    # Date 2018-04-10 18:02:01
-    date_in_epoch_ms = 1523383321000
-    date = format_ms_time(date_in_epoch_ms)
-    assert type(date) is str
-    res = datetime.datetime(2018, 4, 10, 18, 2, 1, tzinfo=datetime.timezone.utc)
-    assert date == res.astimezone(None).strftime('%Y-%m-%dT%H:%M:%S')
-    res = datetime.datetime(2017, 12, 13, 8, 2, 1, tzinfo=datetime.timezone.utc)
-    # Date 2017-12-13 08:02:01
-    date_in_epoch_ms = 1513152121000
-    assert format_ms_time(date_in_epoch_ms) == res.astimezone(None).strftime('%Y-%m-%dT%H:%M:%S')
diff --git a/freqtrade/tests/test_plotting.py b/freqtrade/tests/test_plotting.py
deleted file mode 100644
index 0ebadf720..000000000
--- a/freqtrade/tests/test_plotting.py
+++ /dev/null
@@ -1,268 +0,0 @@
-
-from copy import deepcopy
-from unittest.mock import MagicMock
-
-import plotly.graph_objs as go
-from plotly import tools
-
-from freqtrade.configuration import Arguments, TimeRange
-from freqtrade.data import history
-from freqtrade.data.btanalysis import create_cum_profit, load_backtest_data
-from freqtrade.plot.plotting import (add_indicators, add_profit,
-                                     generate_candlestick_graph,
-                                     generate_plot_filename,
-                                     generate_profit_graph, init_plotscript,
-                                     plot_trades, store_plot_file)
-from freqtrade.strategy.default_strategy import DefaultStrategy
-from freqtrade.tests.conftest import log_has, log_has_re
-
-
-def fig_generating_mock(fig, *args, **kwargs):
-    """ Return Fig - used to mock add_indicators and plot_trades"""
-    return fig
-
-
-def find_trace_in_fig_data(data, search_string: str):
-    matches = (d for d in data if d.name == search_string)
-    return next(matches)
-
-
-def generage_empty_figure():
-    return tools.make_subplots(
-        rows=3,
-        cols=1,
-        shared_xaxes=True,
-        row_width=[1, 1, 4],
-        vertical_spacing=0.0001,
-    )
-
-
-def test_init_plotscript(default_conf, mocker):
-    default_conf['timerange'] = "20180110-20180112"
-    default_conf['trade_source'] = "file"
-    default_conf['ticker_interval'] = "5m"
-    default_conf["datadir"] = history.make_testdata_path(None)
-    default_conf['exportfilename'] = str(
-        history.make_testdata_path(None) / "backtest-result_test.json")
-    ret = init_plotscript(default_conf)
-    assert "tickers" in ret
-    assert "trades" in ret
-    assert "pairs" in ret
-    assert "strategy" in ret
-
-    default_conf['pairs'] = "POWR/BTC,XLM/BTC"
-    ret = init_plotscript(default_conf)
-    assert "tickers" in ret
-    assert "POWR/BTC" in ret["tickers"]
-    assert "XLM/BTC" in ret["tickers"]
-
-
-def test_add_indicators(default_conf, caplog):
-    pair = "UNITTEST/BTC"
-    timerange = TimeRange(None, 'line', 0, -1000)
-
-    data = history.load_pair_history(pair=pair, ticker_interval='1m',
-                                     datadir=None, timerange=timerange)
-    indicators1 = ["ema10"]
-    indicators2 = ["macd"]
-
-    # Generate buy/sell signals and indicators
-    strat = DefaultStrategy(default_conf)
-    data = strat.analyze_ticker(data, {'pair': pair})
-    fig = generage_empty_figure()
-
-    # Row 1
-    fig1 = add_indicators(fig=deepcopy(fig), row=1, indicators=indicators1, data=data)
-    figure = fig1.layout.figure
-    ema10 = find_trace_in_fig_data(figure.data, "ema10")
-    assert isinstance(ema10, go.Scatter)
-    assert ema10.yaxis == "y"
-
-    fig2 = add_indicators(fig=deepcopy(fig), row=3, indicators=indicators2, data=data)
-    figure = fig2.layout.figure
-    macd = find_trace_in_fig_data(figure.data, "macd")
-    assert isinstance(macd, go.Scatter)
-    assert macd.yaxis == "y3"
-
-    # No indicator found
-    fig3 = add_indicators(fig=deepcopy(fig), row=3, indicators=['no_indicator'], data=data)
-    assert fig == fig3
-    assert log_has_re(r'Indicator "no_indicator" ignored\..*', caplog.record_tuples)
-
-
-def test_plot_trades(caplog):
-    fig1 = generage_empty_figure()
-    # nothing happens when no trades are available
-    fig = plot_trades(fig1, None)
-    assert fig == fig1
-    assert log_has("No trades found.", caplog.record_tuples)
-    pair = "ADA/BTC"
-    filename = history.make_testdata_path(None) / "backtest-result_test.json"
-    trades = load_backtest_data(filename)
-    trades = trades.loc[trades['pair'] == pair]
-
-    fig = plot_trades(fig, trades)
-    figure = fig1.layout.figure
-
-    # Check buys - color, should be in first graph, ...
-    trade_buy = find_trace_in_fig_data(figure.data, "trade_buy")
-    assert isinstance(trade_buy, go.Scatter)
-    assert trade_buy.yaxis == 'y'
-    assert len(trades) == len(trade_buy.x)
-    assert trade_buy.marker.color == 'green'
-
-    trade_sell = find_trace_in_fig_data(figure.data, "trade_sell")
-    assert isinstance(trade_sell, go.Scatter)
-    assert trade_sell.yaxis == 'y'
-    assert len(trades) == len(trade_sell.x)
-    assert trade_sell.marker.color == 'red'
-
-
-def test_generate_candlestick_graph_no_signals_no_trades(default_conf, mocker, caplog):
-    row_mock = mocker.patch('freqtrade.plot.plotting.add_indicators',
-                            MagicMock(side_effect=fig_generating_mock))
-    trades_mock = mocker.patch('freqtrade.plot.plotting.plot_trades',
-                               MagicMock(side_effect=fig_generating_mock))
-
-    pair = "UNITTEST/BTC"
-    timerange = TimeRange(None, 'line', 0, -1000)
-    data = history.load_pair_history(pair=pair, ticker_interval='1m',
-                                     datadir=None, timerange=timerange)
-    data['buy'] = 0
-    data['sell'] = 0
-
-    indicators1 = []
-    indicators2 = []
-    fig = generate_candlestick_graph(pair=pair, data=data, trades=None,
-                                     indicators1=indicators1, indicators2=indicators2)
-    assert isinstance(fig, go.Figure)
-    assert fig.layout.title.text == pair
-    figure = fig.layout.figure
-
-    assert len(figure.data) == 2
-    # Candlesticks are plotted first
-    candles = find_trace_in_fig_data(figure.data, "Price")
-    assert isinstance(candles, go.Candlestick)
-
-    volume = find_trace_in_fig_data(figure.data, "Volume")
-    assert isinstance(volume, go.Bar)
-
-    assert row_mock.call_count == 2
-    assert trades_mock.call_count == 1
-
-    assert log_has("No buy-signals found.", caplog.record_tuples)
-    assert log_has("No sell-signals found.", caplog.record_tuples)
-
-
-def test_generate_candlestick_graph_no_trades(default_conf, mocker):
-    row_mock = mocker.patch('freqtrade.plot.plotting.add_indicators',
-                            MagicMock(side_effect=fig_generating_mock))
-    trades_mock = mocker.patch('freqtrade.plot.plotting.plot_trades',
-                               MagicMock(side_effect=fig_generating_mock))
-    pair = 'UNITTEST/BTC'
-    timerange = TimeRange(None, 'line', 0, -1000)
-    data = history.load_pair_history(pair=pair, ticker_interval='1m',
-                                     datadir=None, timerange=timerange)
-
-    # Generate buy/sell signals and indicators
-    strat = DefaultStrategy(default_conf)
-    data = strat.analyze_ticker(data, {'pair': pair})
-
-    indicators1 = []
-    indicators2 = []
-    fig = generate_candlestick_graph(pair=pair, data=data, trades=None,
-                                     indicators1=indicators1, indicators2=indicators2)
-    assert isinstance(fig, go.Figure)
-    assert fig.layout.title.text == pair
-    figure = fig.layout.figure
-
-    assert len(figure.data) == 6
-    # Candlesticks are plotted first
-    candles = find_trace_in_fig_data(figure.data, "Price")
-    assert isinstance(candles, go.Candlestick)
-
-    volume = find_trace_in_fig_data(figure.data, "Volume")
-    assert isinstance(volume, go.Bar)
-
-    buy = find_trace_in_fig_data(figure.data, "buy")
-    assert isinstance(buy, go.Scatter)
-    # All buy-signals should be plotted
-    assert int(data.buy.sum()) == len(buy.x)
-
-    sell = find_trace_in_fig_data(figure.data, "sell")
-    assert isinstance(sell, go.Scatter)
-    # All buy-signals should be plotted
-    assert int(data.sell.sum()) == len(sell.x)
-
-    assert find_trace_in_fig_data(figure.data, "BB lower")
-    assert find_trace_in_fig_data(figure.data, "BB upper")
-
-    assert row_mock.call_count == 2
-    assert trades_mock.call_count == 1
-
-
-def test_generate_Plot_filename():
-    fn = generate_plot_filename("UNITTEST/BTC", "5m")
-    assert fn == "freqtrade-plot-UNITTEST_BTC-5m.html"
-
-
-def test_generate_plot_file(mocker, caplog):
-    fig = generage_empty_figure()
-    plot_mock = mocker.patch("freqtrade.plot.plotting.plot", MagicMock())
-    store_plot_file(fig, filename="freqtrade-plot-UNITTEST_BTC-5m.html")
-
-    assert plot_mock.call_count == 1
-    assert plot_mock.call_args[0][0] == fig
-    assert (plot_mock.call_args_list[0][1]['filename']
-            == "user_data/plots/freqtrade-plot-UNITTEST_BTC-5m.html")
-
-
-def test_add_profit():
-    filename = history.make_testdata_path(None) / "backtest-result_test.json"
-    bt_data = load_backtest_data(filename)
-    timerange = Arguments.parse_timerange("20180110-20180112")
-
-    df = history.load_pair_history(pair="POWR/BTC", ticker_interval='5m',
-                                   datadir=None, timerange=timerange)
-    fig = generage_empty_figure()
-
-    cum_profits = create_cum_profit(df.set_index('date'),
-                                    bt_data[bt_data["pair"] == 'POWR/BTC'],
-                                    "cum_profits")
-
-    fig1 = add_profit(fig, row=2, data=cum_profits, column='cum_profits', name='Profits')
-    figure = fig1.layout.figure
-    profits = find_trace_in_fig_data(figure.data, "Profits")
-    assert isinstance(profits, go.Scattergl)
-    assert profits.yaxis == "y2"
-
-
-def test_generate_profit_graph():
-    filename = history.make_testdata_path(None) / "backtest-result_test.json"
-    trades = load_backtest_data(filename)
-    timerange = Arguments.parse_timerange("20180110-20180112")
-    pairs = ["POWR/BTC", "XLM/BTC"]
-
-    tickers = history.load_data(datadir=None,
-                                pairs=pairs,
-                                ticker_interval='5m',
-                                timerange=timerange
-                                )
-    trades = trades[trades['pair'].isin(pairs)]
-
-    fig = generate_profit_graph(pairs, tickers, trades)
-    assert isinstance(fig, go.Figure)
-
-    assert fig.layout.title.text == "Profit plot"
-    figure = fig.layout.figure
-    assert len(figure.data) == 4
-
-    avgclose = find_trace_in_fig_data(figure.data, "Avg close price")
-    assert isinstance(avgclose, go.Scattergl)
-
-    profit = find_trace_in_fig_data(figure.data, "Profit")
-    assert isinstance(profit, go.Scattergl)
-
-    for pair in pairs:
-        profit_pair = find_trace_in_fig_data(figure.data, f"Profit {pair}")
-        assert isinstance(profit_pair, go.Scattergl)
diff --git a/freqtrade/tests/test_utils.py b/freqtrade/tests/test_utils.py
deleted file mode 100644
index a12b709d7..000000000
--- a/freqtrade/tests/test_utils.py
+++ /dev/null
@@ -1,42 +0,0 @@
-from freqtrade.utils import setup_utils_configuration, start_list_exchanges
-from freqtrade.tests.conftest import get_args
-from freqtrade.state import RunMode
-
-import re
-
-
-def test_setup_utils_configuration():
-    args = [
-        '--config', 'config.json.example',
-    ]
-
-    config = setup_utils_configuration(get_args(args), RunMode.OTHER)
-    assert "exchange" in config
-    assert config['exchange']['dry_run'] is True
-    assert config['exchange']['key'] == ''
-    assert config['exchange']['secret'] == ''
-
-
-def test_list_exchanges(capsys):
-
-    args = [
-        "list-exchanges",
-    ]
-
-    start_list_exchanges(get_args(args))
-    captured = capsys.readouterr()
-    assert re.match(r"Exchanges supported by ccxt and available.*", captured.out)
-    assert re.match(r".*binance,.*", captured.out)
-    assert re.match(r".*bittrex,.*", captured.out)
-
-    # Test with --one-column
-    args = [
-        "list-exchanges",
-        "--one-column",
-    ]
-
-    start_list_exchanges(get_args(args))
-    captured = capsys.readouterr()
-    assert not re.match(r"Exchanges supported by ccxt and available.*", captured.out)
-    assert re.search(r"^binance$", captured.out, re.MULTILINE)
-    assert re.search(r"^bittrex$", captured.out, re.MULTILINE)
diff --git a/freqtrade/tests/testdata/ADA_BTC-1m.json b/freqtrade/tests/testdata/ADA_BTC-1m.json
deleted file mode 100644
index fed55d293..000000000
--- a/freqtrade/tests/testdata/ADA_BTC-1m.json
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/freqtrade/tests/testdata/DASH_BTC-1m.json b/freqtrade/tests/testdata/DASH_BTC-1m.json
deleted file mode 100644
index 631dad0a8..000000000
--- a/freqtrade/tests/testdata/DASH_BTC-1m.json
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/freqtrade/tests/testdata/ETC_BTC-1m.json b/freqtrade/tests/testdata/ETC_BTC-1m.json
deleted file mode 100644
index 29bee485f..000000000
--- a/freqtrade/tests/testdata/ETC_BTC-1m.json
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/freqtrade/tests/testdata/ETH_BTC-1m.json b/freqtrade/tests/testdata/ETH_BTC-1m.json
deleted file mode 100644
index af75fb980..000000000
--- a/freqtrade/tests/testdata/ETH_BTC-1m.json
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/freqtrade/tests/testdata/LTC_BTC-1m.json b/freqtrade/tests/testdata/LTC_BTC-1m.json
deleted file mode 100644
index 0cf8e4d1e..000000000
--- a/freqtrade/tests/testdata/LTC_BTC-1m.json
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/freqtrade/tests/testdata/NXT_BTC-1m.json b/freqtrade/tests/testdata/NXT_BTC-1m.json
deleted file mode 100644
index 7cb900bd1..000000000
--- a/freqtrade/tests/testdata/NXT_BTC-1m.json
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/freqtrade/tests/testdata/POWR_BTC-1m.json b/freqtrade/tests/testdata/POWR_BTC-1m.json
deleted file mode 100644
index 51f695410..000000000
--- a/freqtrade/tests/testdata/POWR_BTC-1m.json
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/freqtrade/tests/testdata/XLM_BTC-1m.json b/freqtrade/tests/testdata/XLM_BTC-1m.json
deleted file mode 100644
index 613fcba53..000000000
--- a/freqtrade/tests/testdata/XLM_BTC-1m.json
+++ /dev/null
@@ -1 +0,0 @@
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4.995e-05, 5.008e-05, 40728.82731784]]
\ No newline at end of file
diff --git a/freqtrade/tests/testdata/XMR_BTC-1m.json b/freqtrade/tests/testdata/XMR_BTC-1m.json
deleted file mode 100644
index 7eb4122e0..000000000
--- a/freqtrade/tests/testdata/XMR_BTC-1m.json
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/freqtrade/tests/testdata/ZEC_BTC-1m.json b/freqtrade/tests/testdata/ZEC_BTC-1m.json
deleted file mode 100644
index 500be88d5..000000000
--- a/freqtrade/tests/testdata/ZEC_BTC-1m.json
+++ /dev/null
@@ -1 +0,0 @@
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\ No newline at end of file
diff --git a/freqtrade/tests/testdata/backtest-result_test.json b/freqtrade/tests/testdata/backtest-result_test.json
deleted file mode 100644
index 8701451dc..000000000
--- a/freqtrade/tests/testdata/backtest-result_test.json
+++ /dev/null
@@ -1 +0,0 @@
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/BTC",-0.0,1516423800.0,1516461300.0,2878,625,0.00270505,0.002718609147869674,false,"roi"],["XMR/BTC",-0.0,1516423800.0,1516431600.0,2878,130,0.03000002,0.030150396040100245,false,"roi"],["ADA/BTC",-0.0,1516438800.0,1516441200.0,2928,40,5.46e-05,5.4873684210526304e-05,false,"roi"],["XMR/BTC",-0.10448878,1516472700.0,1516852200.0,3041,6325,0.03082222,0.027739998000000002,false,"stop_loss"],["ETH/BTC",-0.0,1516487100.0,1516490100.0,3089,50,0.08969999,0.09014961401002504,false,"roi"],["LTC/BTC",0.0,1516503000.0,1516545000.0,3142,700,0.01632501,0.01640683962406015,false,"roi"],["DASH/BTC",-0.0,1516530000.0,1516532400.0,3232,40,0.070538,0.07089157393483708,false,"roi"],["ADA/BTC",-0.0,1516549800.0,1516560300.0,3298,175,5.301e-05,5.3275714285714276e-05,false,"roi"],["XLM/BTC",0.0,1516551600.0,1516554000.0,3304,40,3.955e-05,3.9748245614035085e-05,false,"roi"],["ETC/BTC",0.00997506,1516569300.0,1516571100.0,3363,30,0.00258505,0.002623922932330827,false,"roi"],["XLM/BTC",-0.0,1516569300.0,1516571700.0,3363,40,3.903e-05,3.922563909774435e-05,false,"roi"],["ADA/BTC",-0.0,1516581300.0,1516617300.0,3403,600,5.236e-05,5.262245614035087e-05,false,"roi"],["POWR/BTC",0.0,1516584600.0,1516587000.0,3414,40,9.028e-05,9.073253132832079e-05,false,"roi"],["ETC/BTC",-0.0,1516623900.0,1516631700.0,3545,130,0.002687,0.002700468671679198,false,"roi"],["XLM/BTC",-0.0,1516626900.0,1516629300.0,3555,40,4.168e-05,4.1888922305764405e-05,false,"roi"],["POWR/BTC",0.00997506,1516629600.0,1516631400.0,3564,30,8.821e-05,8.953646616541353e-05,false,"roi"],["ADA/BTC",-0.0,1516636500.0,1516639200.0,3587,45,5.172e-05,5.1979248120300745e-05,false,"roi"],["NXT/BTC",0.01995012,1516637100.0,1516638300.0,3589,20,3.026e-05,3.101839598997494e-05,false,"roi"],["DASH/BTC",0.0,1516650600.0,1516666200.0,3634,260,0.07064,0.07099408521303258,false,"roi"],["LTC/BTC",0.0,1516656300.0,1516658700.0,3653,40,0.01644483,0.01652726022556391,false,"roi"],["XLM/BTC",0.00997506,1516665900.0,1516667700.0,3685,30,4.331e-05,4.3961278195488714e-05,false,"roi"],["NXT/BTC",0.01995012,1516672200.0,1516673700.0,3706,25,3.2e-05,3.2802005012531326e-05,false,"roi"],["ETH/BTC",0.0,1516681500.0,1516684500.0,3737,50,0.09167706,0.09213659413533835,false,"roi"],["DASH/BTC",0.0,1516692900.0,1516698000.0,3775,85,0.0692498,0.06959691679197995,false,"roi"],["NXT/BTC",0.0,1516704600.0,1516712700.0,3814,135,3.182e-05,3.197949874686716e-05,false,"roi"],["ZEC/BTC",-0.0,1516705500.0,1516723500.0,3817,300,0.04088,0.04108491228070175,false,"roi"],["ADA/BTC",-0.0,1516719300.0,1516721700.0,3863,40,5.15e-05,5.175814536340851e-05,false,"roi"],["ETH/BTC",0.0,1516725300.0,1516752300.0,3883,450,0.09071698,0.09117170170426064,false,"roi"],["NXT/BTC",-0.0,1516728300.0,1516733100.0,3893,80,3.128e-05,3.1436791979949865e-05,false,"roi"],["POWR/BTC",-0.0,1516738500.0,1516744800.0,3927,105,9.555e-05,9.602894736842104e-05,false,"roi"],["ZEC/BTC",-0.0,1516746600.0,1516749000.0,3954,40,0.04080001,0.041004521328320796,false,"roi"],["ADA/BTC",-0.0,1516751400.0,1516764900.0,3970,225,5.163e-05,5.1888796992481196e-05,false,"roi"],["ZEC/BTC",0.0,1516753200.0,1516758600.0,3976,90,0.04040781,0.04061035541353383,false,"roi"],["ADA/BTC",-0.0,1516776300.0,1516778700.0,4053,40,5.132e-05,5.157724310776942e-05,false,"roi"],["ADA/BTC",0.03990025,1516803300.0,1516803900.0,4143,10,5.198e-05,5.432496240601503e-05,false,"roi"],["NXT/BTC",-0.0,1516805400.0,1516811700.0,4150,105,3.054e-05,3.069308270676692e-05,false,"roi"],["POWR/BTC",0.0,1516806600.0,1516810500.0,4154,65,9.263e-05,9.309431077694235e-05,false,"roi"],["ADA/BTC",-0.0,1516833600.0,1516836300.0,4244,45,5.514e-05,5.5416390977443596e-05,false,"roi"],["XLM/BTC",0.0,1516841400.0,1516843800.0,4270,40,4.921e-05,4.9456666666666664e-05,false,"roi"],["ETC/BTC",0.0,1516868100.0,1516882500.0,4359,240,0.0026,0.002613032581453634,false,"roi"],["XMR/BTC",-0.0,1516875900.0,1516896900.0,4385,350,0.02799871,0.028139054411027563,false,"roi"],["ZEC/BTC",-0.0,1516878000.0,1516880700.0,4392,45,0.04078902,0.0409934762406015,false,"roi"],["NXT/BTC",-0.0,1516885500.0,1516887900.0,4417,40,2.89e-05,2.904486215538847e-05,false,"roi"],["ZEC/BTC",-0.0,1516886400.0,1516889100.0,4420,45,0.041103,0.041309030075187964,false,"roi"],["XLM/BTC",0.00997506,1516895100.0,1516896900.0,4449,30,5.428e-05,5.5096240601503756e-05,false,"roi"],["XLM/BTC",-0.0,1516902300.0,1516922100.0,4473,330,5.414e-05,5.441137844611528e-05,false,"roi"],["ZEC/BTC",-0.0,1516914900.0,1516917300.0,4515,40,0.04140777,0.0416153277443609,false,"roi"],["ETC/BTC",0.0,1516932300.0,1516934700.0,4573,40,0.00254309,0.002555837318295739,false,"roi"],["ADA/BTC",-0.0,1516935300.0,1516979400.0,4583,735,5.607e-05,5.6351052631578935e-05,false,"roi"],["ETC/BTC",0.0,1516947000.0,1516958700.0,4622,195,0.00253806,0.0025507821052631577,false,"roi"],["ZEC/BTC",-0.0,1516951500.0,1516960500.0,4637,150,0.0415,0.04170802005012531,false,"roi"],["XLM/BTC",0.00997506,1516960500.0,1516962300.0,4667,30,5.321e-05,5.401015037593984e-05,false,"roi"],["XMR/BTC",-0.0,1516982700.0,1516985100.0,4741,40,0.02772046,0.02785940967418546,false,"roi"],["ETH/BTC",0.0,1517009700.0,1517012100.0,4831,40,0.09461341,0.09508766268170425,false,"roi"],["XLM/BTC",-0.0,1517013300.0,1517016600.0,4843,55,5.615e-05,5.643145363408521e-05,false,"roi"],["ADA/BTC",-0.07877175,1517013900.0,1517287500.0,4845,4560,5.556e-05,5.144e-05,true,"force_sell"],["DASH/BTC",-0.0,1517020200.0,1517052300.0,4866,535,0.06900001,0.06934587471177944,false,"roi"],["ETH/BTC",-0.0,1517034300.0,1517036700.0,4913,40,0.09449985,0.09497353345864659,false,"roi"],["ZEC/BTC",-0.04815133,1517046000.0,1517287200.0,4952,4020,0.0410697,0.03928809,true,"force_sell"],["XMR/BTC",-0.0,1517053500.0,1517056200.0,4977,45,0.0285,0.02864285714285714,false,"roi"],["XMR/BTC",-0.0,1517056500.0,1517066700.0,4987,170,0.02866372,0.02880739779448621,false,"roi"],["ETH/BTC",-0.0,1517068200.0,1517071800.0,5026,60,0.095381,0.09585910025062655,false,"roi"],["DASH/BTC",-0.0,1517072700.0,1517075100.0,5041,40,0.06759092,0.06792972160401002,false,"roi"],["ETC/BTC",-0.0,1517096400.0,1517101500.0,5120,85,0.00258501,0.002597967443609022,false,"roi"],["DASH/BTC",-0.0,1517106300.0,1517127000.0,5153,345,0.06698502,0.0673207845112782,false,"roi"],["DASH/BTC",-0.0,1517135100.0,1517157000.0,5249,365,0.0677177,0.06805713709273183,false,"roi"],["XLM/BTC",0.0,1517171700.0,1517175300.0,5371,60,5.215e-05,5.2411403508771925e-05,false,"roi"],["ETC/BTC",0.00997506,1517176800.0,1517178600.0,5388,30,0.00273809,0.002779264285714285,false,"roi"],["ETC/BTC",0.00997506,1517184000.0,1517185800.0,5412,30,0.00274632,0.002787618045112782,false,"roi"],["LTC/BTC",0.0,1517192100.0,1517194800.0,5439,45,0.01622478,0.016306107218045113,false,"roi"],["DASH/BTC",-0.0,1517195100.0,1517197500.0,5449,40,0.069,0.06934586466165413,false,"roi"],["POWR/BTC",-0.0,1517203200.0,1517208900.0,5476,95,8.755e-05,8.798884711779448e-05,false,"roi"],["DASH/BTC",-0.0,1517209200.0,1517253900.0,5496,745,0.06825763,0.06859977350877192,false,"roi"],["DASH/BTC",-0.0,1517255100.0,1517257500.0,5649,40,0.06713892,0.06747545593984962,false,"roi"],["POWR/BTC",-0.0199116,1517268600.0,1517287500.0,5694,315,8.934e-05,8.8e-05,true,"force_sell"]]
\ No newline at end of file
diff --git a/freqtrade/utils.py b/freqtrade/utils.py
deleted file mode 100644
index d550ef43c..000000000
--- a/freqtrade/utils.py
+++ /dev/null
@@ -1,41 +0,0 @@
-import logging
-from argparse import Namespace
-from typing import Any, Dict
-
-from freqtrade.configuration import Configuration
-from freqtrade.exchange import available_exchanges
-from freqtrade.state import RunMode
-
-
-logger = logging.getLogger(__name__)
-
-
-def setup_utils_configuration(args: Namespace, method: RunMode) -> Dict[str, Any]:
-    """
-    Prepare the configuration for utils subcommands
-    :param args: Cli args from Arguments()
-    :return: Configuration
-    """
-    configuration = Configuration(args, method)
-    config = configuration.load_config()
-
-    config['exchange']['dry_run'] = True
-    # Ensure we do not use Exchange credentials
-    config['exchange']['key'] = ''
-    config['exchange']['secret'] = ''
-
-    return config
-
-
-def start_list_exchanges(args: Namespace) -> None:
-    """
-    Print available exchanges
-    :param args: Cli args from Arguments()
-    :return: None
-    """
-
-    if args.print_one_column:
-        print('\n'.join(available_exchanges()))
-    else:
-        print(f"Exchanges supported by ccxt and available for Freqtrade: "
-              f"{', '.join(available_exchanges())}")
diff --git a/freqtrade/vendor/qtpylib/indicators.py b/freqtrade/vendor/qtpylib/indicators.py
index b3b2ac533..4c0fb5b5c 100644
--- a/freqtrade/vendor/qtpylib/indicators.py
+++ b/freqtrade/vendor/qtpylib/indicators.py
@@ -19,14 +19,15 @@
 # limitations under the License.
 #
 
-import warnings
 import sys
+import warnings
 from datetime import datetime, timedelta
 
 import numpy as np
 import pandas as pd
 from pandas.core.base import PandasObject
 
+
 # =============================================
 # check min, python version
 if sys.version_info < (3, 4):
@@ -222,7 +223,7 @@ def crossed(series1, series2, direction=None):
     if isinstance(series1, np.ndarray):
         series1 = pd.Series(series1)
 
-    if isinstance(series2, (float, int, np.ndarray)):
+    if isinstance(series2, (float, int, np.ndarray, np.integer, np.floating)):
         series2 = pd.Series(index=series1.index, data=series2)
 
     if direction is None or direction == "above":
@@ -288,9 +289,9 @@ def rolling_min(series, window=14, min_periods=None):
 def rolling_max(series, window=14, min_periods=None):
     min_periods = window if min_periods is None else min_periods
     try:
-        return series.rolling(window=window, min_periods=min_periods).min()
+        return series.rolling(window=window, min_periods=min_periods).max()
     except Exception as e:  # noqa: F841
-        return pd.Series(series).rolling(window=window, min_periods=min_periods).min()
+        return pd.Series(series).rolling(window=window, min_periods=min_periods).max()
 
 
 # ---------------------------------------------
diff --git a/freqtrade/wallets.py b/freqtrade/wallets.py
index c8ab90276..3680dd416 100644
--- a/freqtrade/wallets.py
+++ b/freqtrade/wallets.py
@@ -2,9 +2,14 @@
 """ Wallet """
 
 import logging
-from typing import Dict, NamedTuple
+from copy import deepcopy
+from typing import Any, Dict, NamedTuple
+
+import arrow
+
 from freqtrade.exchange import Exchange
-from freqtrade import constants
+from freqtrade.persistence import Trade
+
 
 logger = logging.getLogger(__name__)
 
@@ -17,50 +22,70 @@ class Wallet(NamedTuple):
     total: float = 0
 
 
-class Wallets(object):
+class Wallets:
 
     def __init__(self, config: dict, exchange: Exchange) -> None:
         self._config = config
         self._exchange = exchange
         self._wallets: Dict[str, Wallet] = {}
-
+        self.start_cap = config['dry_run_wallet']
+        self._last_wallet_refresh = 0
         self.update()
 
-    def get_free(self, currency) -> float:
-
-        if self._config['dry_run']:
-            return self._config.get('dry_run_wallet', constants.DRY_RUN_WALLET)
-
+    def get_free(self, currency: str) -> float:
         balance = self._wallets.get(currency)
         if balance and balance.free:
             return balance.free
         else:
             return 0
 
-    def get_used(self, currency) -> float:
-
-        if self._config['dry_run']:
-            return self._config.get('dry_run_wallet', constants.DRY_RUN_WALLET)
-
+    def get_used(self, currency: str) -> float:
         balance = self._wallets.get(currency)
         if balance and balance.used:
             return balance.used
         else:
             return 0
 
-    def get_total(self, currency) -> float:
-
-        if self._config['dry_run']:
-            return self._config.get('dry_run_wallet', constants.DRY_RUN_WALLET)
-
+    def get_total(self, currency: str) -> float:
         balance = self._wallets.get(currency)
         if balance and balance.total:
             return balance.total
         else:
             return 0
 
-    def update(self) -> None:
+    def _update_dry(self) -> None:
+        """
+        Update from database in dry-run mode
+        - Apply apply profits of closed trades on top of stake amount
+        - Subtract currently tied up stake_amount in open trades
+        - update balances for currencies currently in trades
+        """
+        # Recreate _wallets to reset closed trade balances
+        _wallets = {}
+        closed_trades = Trade.get_trades(Trade.is_open.is_(False)).all()
+        open_trades = Trade.get_trades(Trade.is_open.is_(True)).all()
+        tot_profit = sum([trade.calc_profit() for trade in closed_trades])
+        tot_in_trades = sum([trade.stake_amount for trade in open_trades])
 
+        current_stake = self.start_cap + tot_profit - tot_in_trades
+        _wallets[self._config['stake_currency']] = Wallet(
+            self._config['stake_currency'],
+            current_stake,
+            0,
+            current_stake
+        )
+
+        for trade in open_trades:
+            curr = self._exchange.get_pair_base_currency(trade.pair)
+            _wallets[curr] = Wallet(
+                curr,
+                trade.amount,
+                0,
+                trade.amount
+            )
+        self._wallets = _wallets
+
+    def _update_live(self) -> None:
         balances = self._exchange.get_balances()
 
         for currency in balances:
@@ -70,5 +95,26 @@ class Wallets(object):
                 balances[currency].get('used', None),
                 balances[currency].get('total', None)
             )
+        # Remove currencies no longer in get_balances output
+        for currency in deepcopy(self._wallets):
+            if currency not in balances:
+                del self._wallets[currency]
 
-        logger.info('Wallets synced.')
+    def update(self, require_update: bool = True) -> None:
+        """
+        Updates wallets from the configured version.
+        By default, updates from the exchange.
+        Update-skipping should only be used for user-invoked /balance calls, since
+        for trading operations, the latest balance is needed.
+        :param require_update: Allow skipping an update if balances were recently refreshed
+        """
+        if (require_update or (self._last_wallet_refresh + 3600 < arrow.utcnow().int_timestamp)):
+            if self._config['dry_run']:
+                self._update_dry()
+            else:
+                self._update_live()
+            logger.info('Wallets synced.')
+            self._last_wallet_refresh = arrow.utcnow().int_timestamp
+
+    def get_all_balances(self) -> Dict[str, Any]:
+        return self._wallets
diff --git a/freqtrade/worker.py b/freqtrade/worker.py
index c224b4ee5..ec9331eef 100755
--- a/freqtrade/worker.py
+++ b/freqtrade/worker.py
@@ -4,40 +4,41 @@ Main Freqtrade worker class.
 import logging
 import time
 import traceback
-from argparse import Namespace
-from typing import Any, Callable, Optional
+from os import getpid
+from typing import Any, Callable, Dict, Optional
+
 import sdnotify
 
-from freqtrade import (constants, OperationalException, TemporaryError,
-                       __version__)
+from freqtrade import __version__, constants
 from freqtrade.configuration import Configuration
+from freqtrade.exceptions import OperationalException, TemporaryError
 from freqtrade.freqtradebot import FreqtradeBot
 from freqtrade.state import State
-from freqtrade.rpc import RPCMessageType
 
 
 logger = logging.getLogger(__name__)
 
 
-class Worker(object):
+class Worker:
     """
     Freqtradebot worker class
     """
 
-    def __init__(self, args: Namespace, config=None) -> None:
+    def __init__(self, args: Dict[str, Any], config: Dict[str, Any] = None) -> None:
         """
         Init all variables and objects the bot needs to work
         """
-        logger.info('Starting worker %s', __version__)
+        logger.info(f"Starting worker {__version__}")
 
         self._args = args
         self._config = config
         self._init(False)
 
+        self.last_throttle_start_time: float = 0
+        self._heartbeat_msg: float = 0
+
         # Tell systemd that we completed initialization phase
-        if self._sd_notify:
-            logger.debug("sd_notify: READY=1")
-            self._sd_notify.notify("READY=1")
+        self._notify("READY=1")
 
     def _init(self, reconfig: bool) -> None:
         """
@@ -50,103 +51,109 @@ class Worker(object):
         # Init the instance of the bot
         self.freqtrade = FreqtradeBot(self._config)
 
-        self._throttle_secs = self._config.get('internals', {}).get(
-            'process_throttle_secs',
-            constants.PROCESS_THROTTLE_SECS
-        )
+        internals_config = self._config.get('internals', {})
+        self._throttle_secs = internals_config.get('process_throttle_secs',
+                                                   constants.PROCESS_THROTTLE_SECS)
+        self._heartbeat_interval = internals_config.get('heartbeat_interval', 60)
 
         self._sd_notify = sdnotify.SystemdNotifier() if \
             self._config.get('internals', {}).get('sd_notify', False) else None
 
-    @property
-    def state(self) -> State:
-        return self.freqtrade.state
-
-    @state.setter
-    def state(self, value: State) -> None:
-        self.freqtrade.state = value
+    def _notify(self, message: str) -> None:
+        """
+        Removes the need to verify in all occurances if sd_notify is enabled
+        :param message: Message to send to systemd if it's enabled.
+        """
+        if self._sd_notify:
+            logger.debug(f"sd_notify: {message}")
+            self._sd_notify.notify(message)
 
     def run(self) -> None:
         state = None
         while True:
             state = self._worker(old_state=state)
-            if state == State.RELOAD_CONF:
+            if state == State.RELOAD_CONFIG:
                 self._reconfigure()
 
-    def _worker(self, old_state: Optional[State], throttle_secs: Optional[float] = None) -> State:
+    def _worker(self, old_state: Optional[State]) -> State:
         """
-        Trading routine that must be run at each loop
+        The main routine that runs each throttling iteration and handles the states.
         :param old_state: the previous service state from the previous call
         :return: current service state
         """
         state = self.freqtrade.state
-        if throttle_secs is None:
-            throttle_secs = self._throttle_secs
 
         # Log state transition
         if state != old_state:
-            self.freqtrade.rpc.send_msg({
-                'type': RPCMessageType.STATUS_NOTIFICATION,
-                'status': f'{state.name.lower()}'
-            })
-            logger.info('Changing state to: %s', state.name)
+            self.freqtrade.notify_status(f'{state.name.lower()}')
+
+            logger.info(f"Changing state to: {state.name}")
             if state == State.RUNNING:
                 self.freqtrade.startup()
 
+            if state == State.STOPPED:
+                self.freqtrade.check_for_open_trades()
+
+            # Reset heartbeat timestamp to log the heartbeat message at
+            # first throttling iteration when the state changes
+            self._heartbeat_msg = 0
+
         if state == State.STOPPED:
             # Ping systemd watchdog before sleeping in the stopped state
-            if self._sd_notify:
-                logger.debug("sd_notify: WATCHDOG=1\\nSTATUS=State: STOPPED.")
-                self._sd_notify.notify("WATCHDOG=1\nSTATUS=State: STOPPED.")
+            self._notify("WATCHDOG=1\nSTATUS=State: STOPPED.")
 
-            time.sleep(throttle_secs)
+            self._throttle(func=self._process_stopped, throttle_secs=self._throttle_secs)
 
         elif state == State.RUNNING:
             # Ping systemd watchdog before throttling
-            if self._sd_notify:
-                logger.debug("sd_notify: WATCHDOG=1\\nSTATUS=State: RUNNING.")
-                self._sd_notify.notify("WATCHDOG=1\nSTATUS=State: RUNNING.")
+            self._notify("WATCHDOG=1\nSTATUS=State: RUNNING.")
 
-            self._throttle(func=self._process, min_secs=throttle_secs)
+            self._throttle(func=self._process_running, throttle_secs=self._throttle_secs)
+
+        if self._heartbeat_interval:
+            now = time.time()
+            if (now - self._heartbeat_msg) > self._heartbeat_interval:
+                logger.info(f"Bot heartbeat. PID={getpid()}, "
+                            f"version='{__version__}', state='{state.name}'")
+                self._heartbeat_msg = now
 
         return state
 
-    def _throttle(self, func: Callable[..., Any], min_secs: float, *args, **kwargs) -> Any:
+    def _throttle(self, func: Callable[..., Any], throttle_secs: float, *args, **kwargs) -> Any:
         """
         Throttles the given callable that it
         takes at least `min_secs` to finish execution.
         :param func: Any callable
-        :param min_secs: minimum execution time in seconds
-        :return: Any
+        :param throttle_secs: throttling interation execution time limit in seconds
+        :return: Any (result of execution of func)
         """
-        start = time.time()
+        self.last_throttle_start_time = time.time()
+        logger.debug("========================================")
         result = func(*args, **kwargs)
-        end = time.time()
-        duration = max(min_secs - (end - start), 0.0)
-        logger.debug('Throttling %s for %.2f seconds', func.__name__, duration)
-        time.sleep(duration)
+        time_passed = time.time() - self.last_throttle_start_time
+        sleep_duration = max(throttle_secs - time_passed, 0.0)
+        logger.debug(f"Throttling with '{func.__name__}()': sleep for {sleep_duration:.2f} s, "
+                     f"last iteration took {time_passed:.2f} s.")
+        time.sleep(sleep_duration)
         return result
 
-    def _process(self) -> bool:
-        state_changed = False
+    def _process_stopped(self) -> None:
+        self.freqtrade.process_stopped()
+
+    def _process_running(self) -> None:
         try:
-            state_changed = self.freqtrade.process()
+            self.freqtrade.process()
         except TemporaryError as error:
             logger.warning(f"Error: {error}, retrying in {constants.RETRY_TIMEOUT} seconds...")
             time.sleep(constants.RETRY_TIMEOUT)
         except OperationalException:
             tb = traceback.format_exc()
             hint = 'Issue `/start` if you think it is safe to restart.'
-            self.freqtrade.rpc.send_msg({
-                'type': RPCMessageType.STATUS_NOTIFICATION,
-                'status': f'OperationalException:\n```\n{tb}```{hint}'
-            })
+
+            self.freqtrade.notify_status(f'OperationalException:\n```\n{tb}```{hint}')
+
             logger.exception('OperationalException. Stopping trader ...')
             self.freqtrade.state = State.STOPPED
-            # TODO: The return value of _process() is not used apart tests
-            # and should (could) be eliminated later. See PR #1689.
-#            state_changed = True
-        return state_changed
 
     def _reconfigure(self) -> None:
         """
@@ -154,9 +161,7 @@ class Worker(object):
         replaces it with the new instance
         """
         # Tell systemd that we initiated reconfiguration
-        if self._sd_notify:
-            logger.debug("sd_notify: RELOADING=1")
-            self._sd_notify.notify("RELOADING=1")
+        self._notify("RELOADING=1")
 
         # Clean up current freqtrade modules
         self.freqtrade.cleanup()
@@ -164,25 +169,15 @@ class Worker(object):
         # Load and validate config and create new instance of the bot
         self._init(True)
 
-        self.freqtrade.rpc.send_msg({
-            'type': RPCMessageType.STATUS_NOTIFICATION,
-            'status': 'config reloaded'
-        })
+        self.freqtrade.notify_status('config reloaded')
 
         # Tell systemd that we completed reconfiguration
-        if self._sd_notify:
-            logger.debug("sd_notify: READY=1")
-            self._sd_notify.notify("READY=1")
+        self._notify("READY=1")
 
     def exit(self) -> None:
         # Tell systemd that we are exiting now
-        if self._sd_notify:
-            logger.debug("sd_notify: STOPPING=1")
-            self._sd_notify.notify("STOPPING=1")
+        self._notify("STOPPING=1")
 
         if self.freqtrade:
-            self.freqtrade.rpc.send_msg({
-                'type': RPCMessageType.STATUS_NOTIFICATION,
-                'status': 'process died'
-            })
+            self.freqtrade.notify_status('process died')
             self.freqtrade.cleanup()
diff --git a/mkdocs.yml b/mkdocs.yml
index b5e759432..8d1ce1cfe 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -1,8 +1,12 @@
 site_name: Freqtrade
 nav:
-    - About: index.md
-    - Installation: installation.md
-    - Installation Docker: docker.md
+    - Home: index.md
+    - Quickstart with Docker: docker_quickstart.md
+    - Installation:
+        - Docker without docker-compose: docker.md
+        - Linux/MacOS/Raspberry: installation.md
+        - Windows: windows_installation.md
+    - Freqtrade Basics: bot-basics.md
     - Configuration: configuration.md
     - Strategy Customization: strategy-customization.md
     - Stoploss: stoploss.md
@@ -11,16 +15,24 @@ nav:
         - Telegram: telegram-usage.md
         - Web Hook: webhook-config.md
         - REST API: rest-api.md
+    - Data Downloading: data-download.md
     - Backtesting: backtesting.md
     - Hyperopt: hyperopt.md
-    - Edge positioning: edge.md
-    - Plotting: plotting.md
-    - Deprecated features: deprecated.md
+    - Edge Positioning: edge.md
+    - Utility Subcommands: utils.md
+    - Exchange-specific Notes: exchanges.md
     - FAQ: faq.md
-    - Data Analysis: data-analysis.md
+    - Data Analysis:
+        - Jupyter Notebooks: data-analysis.md
+        - Strategy analysis: strategy_analysis_example.md
+        - Plotting: plotting.md
     - SQL Cheatsheet: sql_cheatsheet.md
-    - Sandbox testing: sandbox-testing.md
-    - Contributors guide: developer.md
+    - Advanced Post-installation Tasks: advanced-setup.md
+    - Advanced Strategy: strategy-advanced.md
+    - Advanced Hyperopt: advanced-hyperopt.md
+    - Sandbox Testing: sandbox-testing.md
+    - Deprecated Features: deprecated.md
+    - Contributors Guide: developer.md
 theme:
   name: material
   logo: 'images/logo.png'
@@ -28,21 +40,31 @@ theme:
   palette:
     primary: 'blue grey'
     accent: 'tear'
+extra_css:
+  - 'stylesheets/ft.extra.css'
+extra_javascript:
+  - javascripts/config.js
+  - https://polyfill.io/v3/polyfill.min.js?features=es6
+  - https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js
 markdown_extensions:
     - admonition
+    - footnotes
     - codehilite:
         guess_lang: false
     - toc:
         permalink: true
-    - pymdownx.arithmatex
-    - pymdownx.caret
-    - pymdownx.critic
+    - pymdownx.arithmatex:
+        generic: true
     - pymdownx.details
     - pymdownx.inlinehilite
     - pymdownx.magiclink
-    - pymdownx.mark
+    - pymdownx.pathconverter
     - pymdownx.smartsymbols
+    - pymdownx.snippets:
+        base_path: docs
+        check_paths: true
+    - pymdownx.tabbed
     - pymdownx.superfences
     - pymdownx.tasklist:
         custom_checkbox: true
-    - pymdownx.tilde
+    - mdx_truly_sane_lists
diff --git a/requirements-common.txt b/requirements-common.txt
deleted file mode 100644
index 409c979b5..000000000
--- a/requirements-common.txt
+++ /dev/null
@@ -1,32 +0,0 @@
-# requirements without requirements installable via conda
-# mainly used for Raspberry pi installs
-ccxt==1.18.860
-SQLAlchemy==1.3.5
-python-telegram-bot==11.1.0
-arrow==0.14.2
-cachetools==3.1.1
-requests==2.22.0
-urllib3==1.24.2  # pyup: ignore
-wrapt==1.11.2
-scikit-learn==0.21.2
-joblib==0.13.2
-jsonschema==3.0.1
-TA-Lib==0.4.17
-tabulate==0.8.3
-coinmarketcap==5.0.3
-
-# Required for hyperopt
-scikit-optimize==0.5.2
-filelock==3.0.12
-
-# find first, C search in arrays
-py_find_1st==1.1.3
-
-#Load ticker files 30% faster
-python-rapidjson==0.7.2
-
-# Notify systemd
-sdnotify==0.3.2
-
-# Api server
-flask==1.0.3
diff --git a/requirements-dev.txt b/requirements-dev.txt
index 83fec3b8a..e681274c8 100644
--- a/requirements-dev.txt
+++ b/requirements-dev.txt
@@ -1,14 +1,19 @@
 # Include all requirements to run the bot.
 -r requirements.txt
 -r requirements-plot.txt
+-r requirements-hyperopt.txt
 
-flake8==3.7.7
+coveralls==2.2.0
+flake8==3.8.4
 flake8-type-annotations==0.1.0
-flake8-tidy-imports==2.0.0
-pytest==5.0.0
-pytest-mock==1.10.4
-pytest-asyncio==0.10.0
-pytest-cov==2.7.1
+flake8-tidy-imports==4.1.0
+mypy==0.790
+pytest==6.1.2
+pytest-asyncio==0.14.0
+pytest-cov==2.10.1
+pytest-mock==3.3.1
 pytest-random-order==1.0.4
-coveralls==1.8.1
-mypy==0.711
+isort==5.6.4
+
+# Convert jupyter notebooks to markdown documents
+nbconvert==6.0.7
diff --git a/requirements-hyperopt.txt b/requirements-hyperopt.txt
new file mode 100644
index 000000000..7e480b8c9
--- /dev/null
+++ b/requirements-hyperopt.txt
@@ -0,0 +1,10 @@
+# Include all requirements to run the bot.
+-r requirements.txt
+
+# Required for hyperopt
+scipy==1.5.4
+scikit-learn==0.23.2
+scikit-optimize==0.8.1
+filelock==3.0.12
+joblib==0.17.0
+progressbar2==3.53.1
diff --git a/requirements-plot.txt b/requirements-plot.txt
index d4e4fc165..bd40bc0b5 100644
--- a/requirements-plot.txt
+++ b/requirements-plot.txt
@@ -1,5 +1,5 @@
 # Include all requirements to run the bot.
 -r requirements.txt
 
-plotly==3.10.0
+plotly==4.12.0
 
diff --git a/requirements.txt b/requirements.txt
index 52442fb19..7490688d4 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,6 +1,39 @@
-# Load common requirements
--r requirements-common.txt
+numpy==1.19.4
+pandas==1.1.4
 
-numpy==1.16.4
-pandas==0.24.2
-scipy==1.3.0
+ccxt==1.38.13
+aiohttp==3.7.3
+SQLAlchemy==1.3.20
+python-telegram-bot==13.0
+arrow==0.17.0
+cachetools==4.1.1
+requests==2.25.0
+urllib3==1.26.2
+wrapt==1.12.1
+jsonschema==3.2.0
+TA-Lib==0.4.19
+tabulate==0.8.7
+pycoingecko==1.4.0
+jinja2==2.11.2
+tables==3.6.1
+blosc==1.9.2
+
+# find first, C search in arrays
+py_find_1st==1.1.4
+
+# Load ticker files 30% faster
+python-rapidjson==0.9.4
+
+# Notify systemd
+sdnotify==0.3.2
+
+# Api server
+flask==1.1.2
+flask-jwt-extended==3.25.0
+flask-cors==3.0.9
+
+# Support for colorized terminal output
+colorama==0.4.4
+# Building config files interactively
+questionary==1.8.1
+prompt-toolkit==3.0.8
diff --git a/scripts/download_backtest_data.py b/scripts/download_backtest_data.py
deleted file mode 100755
index ed96cec71..000000000
--- a/scripts/download_backtest_data.py
+++ /dev/null
@@ -1,143 +0,0 @@
-#!/usr/bin/env python3
-"""
-This script generates json files with pairs history data
-"""
-import arrow
-import json
-import sys
-from pathlib import Path
-from typing import Any, Dict, List
-
-from freqtrade.configuration import Arguments, TimeRange
-from freqtrade.configuration import Configuration
-from freqtrade.configuration.arguments import ARGS_DOWNLOADER
-from freqtrade.configuration.check_exchange import check_exchange
-from freqtrade.data.history import download_pair_history
-from freqtrade.exchange import Exchange
-from freqtrade.misc import deep_merge_dicts
-
-import logging
-
-logger = logging.getLogger('download_backtest_data')
-
-DEFAULT_DL_PATH = 'user_data/data'
-
-# Do not read the default config if config is not specified
-# in the command line options explicitely
-arguments = Arguments(sys.argv[1:], 'Download backtest data',
-                      no_default_config=True)
-arguments._build_args(optionlist=ARGS_DOWNLOADER)
-args = arguments._parse_args()
-
-# Use bittrex as default exchange
-exchange_name = args.exchange or 'bittrex'
-
-pairs: List = []
-
-configuration = Configuration(args)
-config: Dict[str, Any] = {}
-
-if args.config:
-    # Now expecting a list of config filenames here, not a string
-    for path in args.config:
-        logger.info(f"Using config: {path}...")
-        # Merge config options, overwriting old values
-        config = deep_merge_dicts(configuration._load_config_file(path), config)
-
-    config['stake_currency'] = ''
-    # Ensure we do not use Exchange credentials
-    config['exchange']['dry_run'] = True
-    config['exchange']['key'] = ''
-    config['exchange']['secret'] = ''
-
-    pairs = config['exchange']['pair_whitelist']
-
-    if config.get('ticker_interval'):
-        timeframes = args.timeframes or [config.get('ticker_interval')]
-    else:
-        timeframes = args.timeframes or ['1m', '5m']
-
-else:
-    config = {
-        'stake_currency': '',
-        'dry_run': True,
-        'exchange': {
-            'name': exchange_name,
-            'key': '',
-            'secret': '',
-            'pair_whitelist': [],
-            'ccxt_async_config': {
-                'enableRateLimit': True,
-                'rateLimit': 200
-            }
-        }
-    }
-    timeframes = args.timeframes or ['1m', '5m']
-
-configuration._process_logging_options(config)
-
-if args.config and args.exchange:
-    logger.warning("The --exchange option is ignored, "
-                   "using exchange settings from the configuration file.")
-
-# Check if the exchange set by the user is supported
-check_exchange(config)
-
-configuration._process_datadir_options(config)
-
-dl_path = Path(config['datadir'])
-
-pairs_file = Path(args.pairs_file) if args.pairs_file else dl_path.joinpath('pairs.json')
-
-if not pairs or args.pairs_file:
-    logger.info(f'Reading pairs file "{pairs_file}".')
-    # Download pairs from the pairs file if no config is specified
-    # or if pairs file is specified explicitely
-    if not pairs_file.exists():
-        sys.exit(f'No pairs file found with path "{pairs_file}".')
-
-    with pairs_file.open() as file:
-        pairs = list(set(json.load(file)))
-
-    pairs.sort()
-
-timerange = TimeRange()
-if args.days:
-    time_since = arrow.utcnow().shift(days=-args.days).strftime("%Y%m%d")
-    timerange = arguments.parse_timerange(f'{time_since}-')
-
-logger.info(f'About to download pairs: {pairs}, intervals: {timeframes} to {dl_path}')
-
-pairs_not_available = []
-
-try:
-    # Init exchange
-    exchange = Exchange(config)
-
-    for pair in pairs:
-        if pair not in exchange._api.markets:
-            pairs_not_available.append(pair)
-            logger.info(f"Skipping pair {pair}...")
-            continue
-        for ticker_interval in timeframes:
-            pair_print = pair.replace('/', '_')
-            filename = f'{pair_print}-{ticker_interval}.json'
-            dl_file = dl_path.joinpath(filename)
-            if args.erase and dl_file.exists():
-                logger.info(
-                    f'Deleting existing data for pair {pair}, interval {ticker_interval}.')
-                dl_file.unlink()
-
-            logger.info(f'Downloading pair {pair}, interval {ticker_interval}.')
-            download_pair_history(datadir=dl_path, exchange=exchange,
-                                  pair=pair, ticker_interval=str(ticker_interval),
-                                  timerange=timerange)
-
-except KeyboardInterrupt:
-    sys.exit("SIGINT received, aborting ...")
-
-finally:
-    if pairs_not_available:
-        logger.info(
-            f"Pairs [{','.join(pairs_not_available)}] not available "
-            f"on exchange {config['exchange']['name']}.")
diff --git a/scripts/get_market_pairs.py b/scripts/get_market_pairs.py
deleted file mode 100644
index cd38bf2fa..000000000
--- a/scripts/get_market_pairs.py
+++ /dev/null
@@ -1,103 +0,0 @@
-"""
-This script was adapted from ccxt here:
-https://github.com/ccxt/ccxt/blob/master/examples/py/arbitrage-pairs.py
-"""
-import os
-import sys
-import traceback
-
-root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-sys.path.append(root + '/python')
-
-import ccxt  # noqa: E402
-
-
-def style(s, style):
-    return style + s + '\033[0m'
-
-
-def green(s):
-    return style(s, '\033[92m')
-
-
-def blue(s):
-    return style(s, '\033[94m')
-
-
-def yellow(s):
-    return style(s, '\033[93m')
-
-
-def red(s):
-    return style(s, '\033[91m')
-
-
-def pink(s):
-    return style(s, '\033[95m')
-
-
-def bold(s):
-    return style(s, '\033[1m')
-
-
-def underline(s):
-    return style(s, '\033[4m')
-
-
-def dump(*args):
-    print(' '.join([str(arg) for arg in args]))
-
-
-def print_supported_exchanges():
-    dump('Supported exchanges:', green(', '.join(ccxt.exchanges)))
-
-
-try:
-
-    if len(sys.argv) < 2:
-        dump("Usage: python " + sys.argv[0], green('id'))
-        print_supported_exchanges()
-        sys.exit(1)
-
-    id = sys.argv[1]  # get exchange id from command line arguments
-
-    # check if the exchange is supported by ccxt
-    exchange_found = id in ccxt.exchanges
-
-    if exchange_found:
-        dump('Instantiating', green(id), 'exchange')
-
-        # instantiate the exchange by id
-        exchange = getattr(ccxt, id)({
-            # 'proxy':'https://cors-anywhere.herokuapp.com/',
-        })
-
-        # load all markets from the exchange
-        markets = exchange.load_markets()
-
-        # output a list of all market symbols
-        dump(green(id), 'has', len(exchange.symbols), 'symbols:', exchange.symbols)
-
-        tuples = list(ccxt.Exchange.keysort(markets).items())
-
-        # debug
-        for (k, v) in tuples:
-            print(v)
-
-        # output a table of all markets
-        dump(pink('{:<15} {:<15} {:<15} {:<15}'.format('id', 'symbol', 'base', 'quote')))
-
-        for (k, v) in tuples:
-            dump('{:<15} {:<15} {:<15} {:<15}'.format(v['id'], v['symbol'], v['base'], v['quote']))
-
-    else:
-
-        dump('Exchange ' + red(id) + ' not found')
-        print_supported_exchanges()
-
-except Exception as e:
-    dump('[' + type(e).__name__ + ']', str(e))
-    dump(traceback.format_exc())
-    dump("Usage: python " + sys.argv[0], green('id'))
-    print_supported_exchanges()
-    sys.exit(1)
diff --git a/scripts/plot_dataframe.py b/scripts/plot_dataframe.py
deleted file mode 100755
index 034a6f448..000000000
--- a/scripts/plot_dataframe.py
+++ /dev/null
@@ -1,113 +0,0 @@
-#!/usr/bin/env python3
-"""
-Script to display when the bot will buy on specific pair(s)
-
-Use `python plot_dataframe.py --help` to display the command line arguments
-
-Indicators recommended
-Row 1: sma, ema3, ema5, ema10, ema50
-Row 3: macd, rsi, fisher_rsi, mfi, slowd, slowk, fastd, fastk
-
-Example of usage:
-> python3 scripts/plot_dataframe.py --pairs BTC/EUR,XRP/BTC -d user_data/data/
-  --indicators1 sma,ema3 --indicators2 fastk,fastd
-"""
-import logging
-import sys
-from typing import Any, Dict, List
-
-import pandas as pd
-
-from freqtrade.configuration import Arguments
-from freqtrade.configuration.arguments import ARGS_PLOT_DATAFRAME
-from freqtrade.data.btanalysis import extract_trades_of_period
-from freqtrade.optimize import setup_configuration
-from freqtrade.plot.plotting import (init_plotscript, generate_candlestick_graph,
-                                     store_plot_file,
-                                     generate_plot_filename)
-from freqtrade.state import RunMode
-
-logger = logging.getLogger(__name__)
-
-
-def generate_dataframe(strategy, tickers, pair) -> pd.DataFrame:
-    """
-    Get tickers then Populate strategy indicators and signals, then return the full dataframe
-    :return: the DataFrame of a pair
-    """
-
-    dataframes = strategy.tickerdata_to_dataframe(tickers)
-    dataframe = dataframes[pair]
-    dataframe = strategy.advise_buy(dataframe, {'pair': pair})
-    dataframe = strategy.advise_sell(dataframe, {'pair': pair})
-
-    return dataframe
-
-
-def analyse_and_plot_pairs(config: Dict[str, Any]):
-    """
-    From arguments provided in cli:
-    -Initialise backtest env
-    -Get tickers data
-    -Generate Dafaframes populated with indicators and signals
-    -Load trades excecuted on same periods
-    -Generate Plotly plot objects
-    -Generate plot files
-    :return: None
-    """
-    plot_elements = init_plotscript(config)
-    trades = plot_elements['trades']
-
-    pair_counter = 0
-    for pair, data in plot_elements["tickers"].items():
-        pair_counter += 1
-        logger.info("analyse pair %s", pair)
-        tickers = {}
-        tickers[pair] = data
-        dataframe = generate_dataframe(plot_elements["strategy"], tickers, pair)
-
-        trades_pair = trades.loc[trades['pair'] == pair]
-        trades_pair = extract_trades_of_period(dataframe, trades_pair)
-
-        fig = generate_candlestick_graph(
-            pair=pair,
-            data=dataframe,
-            trades=trades_pair,
-            indicators1=config["indicators1"].split(","),
-            indicators2=config["indicators2"].split(",")
-        )
-
-        store_plot_file(fig, generate_plot_filename(pair, config['ticker_interval']))
-
-    logger.info('End of ploting process %s plots generated', pair_counter)
-
-
-def plot_parse_args(args: List[str]) -> Dict[str, Any]:
-    """
-    Parse args passed to the script
-    :param args: Cli arguments
-    :return: args: Array with all arguments
-    """
-    arguments = Arguments(args, 'Graph dataframe')
-    arguments._build_args(optionlist=ARGS_PLOT_DATAFRAME)
-    parsed_args = arguments._parse_args()
-
-    # Load the configuration
-    config = setup_configuration(parsed_args, RunMode.OTHER)
-    return config
-
-
-def main(sysargv: List[str]) -> None:
-    """
-    This function will initiate the bot and start the trading loop.
-    :return: None
-    """
-    logger.info('Starting Plot Dataframe')
-    analyse_and_plot_pairs(
-        plot_parse_args(sysargv)
-    )
-    exit()
-
-
-if __name__ == '__main__':
-    main(sys.argv[1:])
diff --git a/scripts/plot_profit.py b/scripts/plot_profit.py
deleted file mode 100755
index 4290bca45..000000000
--- a/scripts/plot_profit.py
+++ /dev/null
@@ -1,65 +0,0 @@
-#!/usr/bin/env python3
-"""
-Script to display profits
-
-Use `python plot_profit.py --help` to display the command line arguments
-"""
-import logging
-import sys
-from typing import Any, Dict, List
-
-from freqtrade.configuration import Arguments
-from freqtrade.configuration.arguments import ARGS_PLOT_PROFIT
-from freqtrade.optimize import setup_configuration
-from freqtrade.plot.plotting import init_plotscript, generate_profit_graph, store_plot_file
-from freqtrade.state import RunMode
-
-logger = logging.getLogger(__name__)
-
-
-def plot_profit(config: Dict[str, Any]) -> None:
-    """
-    Plots the total profit for all pairs.
-    Note, the profit calculation isn't realistic.
-    But should be somewhat proportional, and therefor useful
-    in helping out to find a good algorithm.
-    """
-    plot_elements = init_plotscript(config)
-    trades = plot_elements['trades']
-    # Filter trades to relevant pairs
-    trades = trades[trades['pair'].isin(plot_elements["pairs"])]
-
-    # Create an average close price of all the pairs that were involved.
-    # this could be useful to gauge the overall market trend
-    fig = generate_profit_graph(plot_elements["pairs"], plot_elements["tickers"], trades)
-    store_plot_file(fig, filename='freqtrade-profit-plot.html', auto_open=True)
-
-
-def plot_parse_args(args: List[str]) -> Dict[str, Any]:
-    """
-    Parse args passed to the script
-    :param args: Cli arguments
-    :return: args: Array with all arguments
-    """
-    arguments = Arguments(args, 'Graph profits')
-    arguments._build_args(optionlist=ARGS_PLOT_PROFIT)
-    parsed_args = arguments._parse_args()
-
-    # Load the configuration
-    config = setup_configuration(parsed_args, RunMode.OTHER)
-    return config
-
-
-def main(sysargv: List[str]) -> None:
-    """
-    This function will initiate the bot and start the trading loop.
-    :return: None
-    """
-    logger.info('Starting Plot Dataframe')
-    plot_profit(
-        plot_parse_args(sysargv)
-    )
-
-
-if __name__ == '__main__':
-    main(sys.argv[1:])
diff --git a/scripts/rest_client.py b/scripts/rest_client.py
index a46b3ebfb..268e81397 100755
--- a/scripts/rest_client.py
+++ b/scripts/rest_client.py
@@ -8,15 +8,19 @@ so it can be used as a standalone script.
 """
 
 import argparse
+import inspect
 import json
 import logging
-import inspect
-from urllib.parse import urlencode, urlparse, urlunparse
+import re
+import sys
 from pathlib import Path
+from urllib.parse import urlencode, urlparse, urlunparse
 
+import rapidjson
 import requests
 from requests.exceptions import ConnectionError
 
+
 logging.basicConfig(
     level=logging.INFO,
     format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
@@ -59,104 +63,145 @@ class FtRestClient():
     def _get(self, apipath, params: dict = None):
         return self._call("GET", apipath, params=params)
 
+    def _delete(self, apipath, params: dict = None):
+        return self._call("DELETE", apipath, params=params)
+
     def _post(self, apipath, params: dict = None, data: dict = None):
         return self._call("POST", apipath, params=params, data=data)
 
     def start(self):
-        """
-        Start the bot if it's in stopped state.
+        """Start the bot if it's in the stopped state.
+
         :return: json object
         """
         return self._post("start")
 
     def stop(self):
-        """
-        Stop the bot. Use start to restart
+        """Stop the bot. Use `start` to restart.
+
         :return: json object
         """
         return self._post("stop")
 
     def stopbuy(self):
-        """
-        Stop buying (but handle sells gracefully).
-        use reload_conf to reset
+        """Stop buying (but handle sells gracefully). Use `reload_config` to reset.
+
         :return: json object
         """
         return self._post("stopbuy")
 
-    def reload_conf(self):
-        """
-        Reload configuration
+    def reload_config(self):
+        """Reload configuration.
+
         :return: json object
         """
-        return self._post("reload_conf")
+        return self._post("reload_config")
 
     def balance(self):
-        """
-        Get the account balance
+        """Get the account balance.
+
         :return: json object
         """
         return self._get("balance")
 
     def count(self):
-        """
-        Returns the amount of open trades
+        """Return the amount of open trades.
+
         :return: json object
         """
         return self._get("count")
 
-    def daily(self, days=None):
+    def locks(self):
+        """Return current locks
+
+        :return: json object
         """
-        Returns the amount of open trades
+        return self._get("locks")
+
+    def daily(self, days=None):
+        """Return the amount of open trades.
+
         :return: json object
         """
         return self._get("daily", params={"timescale": days} if days else None)
 
     def edge(self):
-        """
-        Returns information about edge
+        """Return information about edge.
+
         :return: json object
         """
         return self._get("edge")
 
     def profit(self):
-        """
-        Returns the profit summary
+        """Return the profit summary.
+
         :return: json object
         """
         return self._get("profit")
 
     def performance(self):
-        """
-        Returns the performance of the different coins
+        """Return the performance of the different coins.
+
         :return: json object
         """
         return self._get("performance")
 
     def status(self):
-        """
-        Get the status of open trades
+        """Get the status of open trades.
+
         :return: json object
         """
         return self._get("status")
 
     def version(self):
-        """
-        Returns the version of the bot
+        """Return the version of the bot.
+
         :return: json object containing the version
         """
         return self._get("version")
 
-    def whitelist(self):
+    def show_config(self):
         """
-        Show the current whitelist
+        Returns part of the configuration, relevant for trading operations.
+        :return: json object containing the version
+        """
+        return self._get("show_config")
+
+    def logs(self, limit=None):
+        """Show latest logs.
+
+        :param limit: Limits log messages to the last <limit> logs. No limit to get all the trades.
+        :return: json object
+        """
+        return self._get("logs", params={"limit": limit} if limit else 0)
+
+    def trades(self, limit=None):
+        """Return trades history.
+
+        :param limit: Limits trades to the X last trades. No limit to get all the trades.
+        :return: json object
+        """
+        return self._get("trades", params={"limit": limit} if limit else 0)
+
+    def delete_trade(self, trade_id):
+        """Delete trade from the database.
+        Tries to close open orders. Requires manual handling of this asset on the exchange.
+
+        :param trade_id: Deletes the trade with this ID from the database.
+        :return: json object
+        """
+        return self._delete("trades/{}".format(trade_id))
+
+    def whitelist(self):
+        """Show the current whitelist.
+
         :return: json object
         """
         return self._get("whitelist")
 
     def blacklist(self, *args):
-        """
-        Show the current blacklist
+        """Show the current blacklist.
+
         :param add: List of coins to add (example: "BNB/BTC")
         :return: json object
         """
@@ -166,8 +211,8 @@ class FtRestClient():
             return self._post("blacklist", data={"blacklist": args})
 
     def forcebuy(self, pair, price=None):
-        """
-        Buy an asset
+        """Buy an asset.
+
         :param pair: Pair to buy (ETH/BTC)
         :param price: Optional - price to buy
         :return: json object of the trade
@@ -178,19 +223,85 @@ class FtRestClient():
         return self._post("forcebuy", data=data)
 
     def forcesell(self, tradeid):
-        """
-        Force-sell a trade
+        """Force-sell a trade.
+
         :param tradeid: Id of the trade (can be received via status command)
         :return: json object
         """
 
         return self._post("forcesell", data={"tradeid": tradeid})
 
+    def strategies(self):
+        """Lists available strategies
+
+        :return: json object
+        """
+        return self._get("strategies")
+
+    def strategy(self, strategy):
+        """Get strategy details
+
+        :param strategy: Strategy class name
+        :return: json object
+        """
+        return self._get(f"strategy/{strategy}")
+
+    def plot_config(self):
+        """Return plot configuration if the strategy defines one.
+
+        :return: json object
+        """
+        return self._get("plot_config")
+
+    def available_pairs(self, timeframe=None, stake_currency=None):
+        """Return available pair (backtest data) based on timeframe / stake_currency selection
+
+        :param timeframe: Only pairs with this timeframe available.
+        :param stake_currency: Only pairs that include this timeframe
+        :return: json object
+        """
+        return self._get("available_pairs", params={
+            "stake_currency": stake_currency if timeframe else '',
+            "timeframe": timeframe if timeframe else '',
+        })
+
+    def pair_candles(self, pair, timeframe, limit=None):
+        """Return live dataframe for <pair><timeframe>.
+
+        :param pair: Pair to get data for
+        :param timeframe: Only pairs with this timeframe available.
+        :param limit: Limit result to the last n candles.
+        :return: json object
+        """
+        return self._get("available_pairs", params={
+            "pair": pair,
+            "timeframe": timeframe,
+            "limit": limit,
+        })
+
+    def pair_history(self, pair, timeframe, strategy, timerange=None):
+        """Return historic, analyzed dataframe
+
+        :param pair: Pair to get data for
+        :param timeframe: Only pairs with this timeframe available.
+        :param strategy: Strategy to analyze and get values for
+        :param timerange: Timerange to get data for (same format than --timerange endpoints)
+        :return: json object
+        """
+        return self._get("pair_history", params={
+            "pair": pair,
+            "timeframe": timeframe,
+            "strategy": strategy,
+            "timerange": timerange if timerange else '',
+        })
+
 
 def add_arguments():
     parser = argparse.ArgumentParser()
     parser.add_argument("command",
-                        help="Positional argument defining the command to execute.")
+                        help="Positional argument defining the command to execute.",
+                        nargs="?"
+                        )
 
     parser.add_argument('--show',
                         help='Show possible methods with this client',
@@ -221,30 +332,35 @@ def load_config(configfile):
     file = Path(configfile)
     if file.is_file():
         with file.open("r") as f:
-            config = json.load(f)
+            config = rapidjson.load(f, parse_mode=rapidjson.PM_COMMENTS |
+                                    rapidjson.PM_TRAILING_COMMAS)
         return config
-    return {}
+    else:
+        logger.warning(f"Could not load config file {file}.")
+        sys.exit(1)
 
 
 def print_commands():
     # Print dynamic help for the different commands using the commands doc-strings
     client = FtRestClient(None)
-    print("Possible commands:")
+    print("Possible commands:\n")
     for x, y in inspect.getmembers(client):
         if not x.startswith('_'):
-            print(f"{x} {getattr(client, x).__doc__}")
+            doc = re.sub(':return:.*', '', getattr(client, x).__doc__, flags=re.MULTILINE).rstrip()
+            print(f"{x}\n\t{doc}\n")
 
 
 def main(args):
 
-    if args.get("help"):
+    if args.get("show"):
         print_commands()
+        sys.exit()
 
-    config = load_config(args["config"])
-    url = config.get("api_server", {}).get("server_url", "127.0.0.1")
-    port = config.get("api_server", {}).get("listen_port", "8080")
-    username = config.get("api_server", {}).get("username")
-    password = config.get("api_server", {}).get("password")
+    config = load_config(args['config'])
+    url = config.get('api_server', {}).get('server_url', '127.0.0.1')
+    port = config.get('api_server', {}).get('listen_port', '8080')
+    username = config.get('api_server', {}).get('username')
+    password = config.get('api_server', {}).get('password')
 
     server_url = f"http://{url}:{port}"
     client = FtRestClient(server_url, username, password)
diff --git a/setup.cfg b/setup.cfg
index 473f50639..be2cd450c 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -2,9 +2,19 @@
 #ignore =
 max-line-length = 100
 max-complexity = 12
+exclude =
+    .git,
+    __pycache__,
+    .eggs,
+    user_data,
+
+[isort]
+line_length=100
+multi_line_output=0
+lines_after_imports=2
 
 [mypy]
 ignore_missing_imports = True
 
-[mypy-freqtrade.tests.*]
+[mypy-tests.*]
 ignore_errors = True
diff --git a/setup.py b/setup.py
index ca2f81d1f..b47427709 100644
--- a/setup.py
+++ b/setup.py
@@ -1,45 +1,103 @@
 from sys import version_info
+
 from setuptools import setup
 
+
 if version_info.major == 3 and version_info.minor < 6 or \
         version_info.major < 3:
     print('Your Python interpreter must be 3.6 or greater!')
     exit(1)
 
-from freqtrade import __version__
+from pathlib import Path  # noqa: E402
 
+from freqtrade import __version__  # noqa: E402
+
+
+readme_file = Path(__file__).parent / "README.md"
+readme_long = "Crypto Trading Bot"
+if readme_file.is_file():
+    readme_long = (Path(__file__).parent / "README.md").read_text()
+
+# Requirements used for submodules
+api = ['flask', 'flask-jwt-extended', 'flask-cors']
+plot = ['plotly>=4.0']
+hyperopt = [
+    'scipy',
+    'scikit-learn',
+    'scikit-optimize>=0.7.0',
+    'filelock',
+    'joblib',
+    'progressbar2',
+    ]
+
+develop = [
+    'coveralls',
+    'flake8',
+    'flake8-type-annotations',
+    'flake8-tidy-imports',
+    'mypy',
+    'pytest',
+    'pytest-asyncio',
+    'pytest-cov',
+    'pytest-mock',
+    'pytest-random-order',
+]
+
+jupyter = [
+    'jupyter',
+    'nbstripout',
+    'ipykernel',
+    'nbconvert',
+    ]
+
+all_extra = api + plot + develop + jupyter + hyperopt
 
 setup(name='freqtrade',
       version=__version__,
       description='Crypto Trading Bot',
+      long_description=readme_long,
+      long_description_content_type="text/markdown",
       url='https://github.com/freqtrade/freqtrade',
-      author='gcarq and contributors',
+      author='Freqtrade Team',
       author_email='michael.egger@tsn.at',
       license='GPLv3',
       packages=['freqtrade'],
       setup_requires=['pytest-runner', 'numpy'],
-      tests_require=['pytest', 'pytest-mock', 'pytest-cov'],
+      tests_require=['pytest', 'pytest-asyncio', 'pytest-cov', 'pytest-mock', ],
       install_requires=[
-          'ccxt',
+          # from requirements.txt
+          'ccxt>=1.24.96',
           'SQLAlchemy',
           'python-telegram-bot',
-          'arrow',
+          'arrow>=0.17.0',
+          'cachetools',
           'requests',
           'urllib3',
           'wrapt',
-          'pandas',
-          'scikit-learn',
-          'scipy',
-          'joblib',
           'jsonschema',
           'TA-Lib',
           'tabulate',
-          'cachetools',
-          'coinmarketcap',
-          'scikit-optimize',
+          'pycoingecko',
+          'py_find_1st',
           'python-rapidjson',
-          'py_find_1st'
+          'sdnotify',
+          'colorama',
+          'jinja2',
+          'questionary',
+          'prompt-toolkit',
+          'numpy',
+          'pandas',
+          'tables',
+          'blosc',
       ],
+      extras_require={
+          'api': api,
+          'dev': all_extra,
+          'plot': plot,
+          'jupyter': jupyter,
+          'hyperopt': hyperopt,
+          'all': all_extra,
+      },
       include_package_data=True,
       zip_safe=False,
       entry_points={
@@ -48,8 +106,13 @@ setup(name='freqtrade',
           ],
       },
       classifiers=[
-          'Programming Language :: Python :: 3.6',
-          'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
-          'Topic :: Office/Business :: Financial :: Investment',
+          'Environment :: Console',
           'Intended Audience :: Science/Research',
+          'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
+          'Programming Language :: Python :: 3.6',
+          'Programming Language :: Python :: 3.7',
+          'Programming Language :: Python :: 3.8',
+          'Operating System :: MacOS',
+          'Operating System :: Unix',
+          'Topic :: Office/Business :: Financial :: Investment',
       ])
diff --git a/setup.sh b/setup.sh
index fe7110ef6..049a6a77e 100755
--- a/setup.sh
+++ b/setup.sh
@@ -11,6 +11,20 @@ function check_installed_pip() {
 
 # Check which python version is installed
 function check_installed_python() {
+    if [ -n "${VIRTUAL_ENV}" ]; then
+        echo "Please deactivate your virtual environment before running setup.sh."
+        echo "You can do this by running 'deactivate'."
+        exit 2
+    fi
+
+    which python3.8
+    if [ $? -eq 0 ]; then
+        echo "using Python 3.8"
+        PYTHON=python3.8
+        check_installed_pip
+        return
+    fi
+
     which python3.7
     if [ $? -eq 0 ]; then
         echo "using Python 3.7"
@@ -37,17 +51,19 @@ function updateenv() {
     echo "-------------------------"
     echo "Updating your virtual env"
     echo "-------------------------"
+    if [ ! -f .env/bin/activate ]; then
+        echo "Something went wrong, no virtual environment found."
+        exit 1
+    fi
     source .env/bin/activate
     echo "pip install in-progress. Please wait..."
-    # Install numpy first to have py_find_1st install clean
-    ${PYTHON} -m pip install --upgrade pip numpy
-    ${PYTHON} -m pip install --upgrade -r requirements.txt
-
+    ${PYTHON} -m pip install --upgrade pip
     read -p "Do you want to install dependencies for dev [y/N]? "
     if [[ $REPLY =~ ^[Yy]$ ]]
     then
         ${PYTHON} -m pip install --upgrade -r requirements-dev.txt
     else
+        ${PYTHON} -m pip install --upgrade -r requirements.txt
         echo "Dev dependencies ignored."
     fi
 
@@ -70,6 +86,10 @@ function install_talib() {
     ./configure --prefix=/usr/local
     make
     sudo make install
+    if [ -x "$(command -v apt-get)" ]; then
+        echo "Updating library path using ldconfig"
+        sudo ldconfig
+    fi
     cd .. && rm -rf ./ta-lib/
     cd ..
 }
@@ -90,7 +110,7 @@ function install_macos() {
 # Install bot Debian_ubuntu
 function install_debian() {
     sudo apt-get update
-    sudo apt-get install build-essential autoconf libtool pkg-config make wget git
+    sudo apt-get install -y build-essential autoconf libtool pkg-config make wget git
     install_talib
 }
 
@@ -100,35 +120,44 @@ function update() {
     updateenv
 }
 
-# Reset Develop or Master branch
+# Reset Develop or Stable branch
 function reset() {
     echo "----------------------------"
     echo "Reseting branch and virtual env"
     echo "----------------------------"
-    if [ "1" == $(git branch -vv |grep -cE "\* develop|\* master") ]
+
+    if [ "1" == $(git branch -vv |grep -cE "\* develop|\* stable") ]
     then
-        if [ -d ".env" ]; then
-          echo "- Delete your previous virtual env"
-          rm -rf .env
-        fi
 
-        git fetch -a
+        read -p "Reset git branch? (This will remove all changes you made!) [y/N]? "
+        if [[ $REPLY =~ ^[Yy]$ ]]; then
 
-        if [ "1" == $(git branch -vv |grep -c "* develop") ]
-        then
-          echo "- Hard resetting of 'develop' branch."
-          git reset --hard origin/develop
-        elif [ "1" == $(git branch -vv |grep -c "* master") ]
-        then
-          echo "- Hard resetting of 'master' branch."
-          git reset --hard origin/master
+            git fetch -a
+
+            if [ "1" == $(git branch -vv |grep -c "* develop") ]
+            then
+                echo "- Hard resetting of 'develop' branch."
+                git reset --hard origin/develop
+            elif [ "1" == $(git branch -vv |grep -c "* stable") ]
+            then
+                echo "- Hard resetting of 'stable' branch."
+                git reset --hard origin/stable
+            fi
         fi
     else
-        echo "Reset ignored because you are not on 'master' or 'develop'."
+        echo "Reset ignored because you are not on 'stable' or 'develop'."
     fi
 
+    if [ -d ".env" ]; then
+        echo "- Delete your previous virtual env"
+        rm -rf .env
+    fi
     echo
     ${PYTHON} -m venv .env
+    if [ $? -ne 0 ]; then
+        echo "Could not create virtual environment. Leaving now"
+        exit 1
+    fi
     updateenv
 }
 
@@ -194,27 +223,8 @@ function config_generator() {
 function config() {
 
     echo "-------------------------"
-    echo "Generating config file"
+    echo "Please use 'freqtrade new-config -c config.json' to generate a new configuration file."
     echo "-------------------------"
-    if [ -f config.json ]
-    then
-    read -p "A config file already exist, do you want to override it [y/N]? "
-    if [[ $REPLY =~ ^[Yy]$ ]]
-    then
-        config_generator
-    else
-        echo "Configuration of config.json ignored."
-    fi
-    else
-        config_generator
-    fi
-
-    echo
-    echo "-------------------------"
-    echo "Config file generated"
-    echo "-------------------------"
-    echo "Edit ./config.json to modify Pair and other configurations."
-    echo
 }
 
 function install() {
@@ -242,7 +252,9 @@ function install() {
     echo "-------------------------"
     echo "Run the bot !"
     echo "-------------------------"
-    echo "You can now use the bot by executing 'source .env/bin/activate; freqtrade'."
+    echo "You can now use the bot by executing 'source .env/bin/activate; freqtrade <subcommand>'."
+    echo "You can see the list of available bot subcommands by executing 'source .env/bin/activate; freqtrade --help'."
+    echo "You verify that freqtrade is installed successfully by running 'source .env/bin/activate; freqtrade --version'."
 }
 
 function plot() {
@@ -258,7 +270,7 @@ function help() {
     echo "usage:"
     echo "	-i,--install    Install freqtrade from scratch"
     echo "	-u,--update     Command git pull to update."
-    echo "	-r,--reset      Hard reset your develop/master branch."
+    echo "	-r,--reset      Hard reset your develop/stable branch."
     echo "	-c,--config     Easy config generator (Will override your existing file)."
     echo "	-p,--plot       Install dependencies for Plotting scripts."
 }
diff --git a/freqtrade/tests/edge/__init__.py b/tests/__init__.py
similarity index 100%
rename from freqtrade/tests/edge/__init__.py
rename to tests/__init__.py
diff --git a/freqtrade/tests/exchange/__init__.py b/tests/commands/__init__.py
similarity index 100%
rename from freqtrade/tests/exchange/__init__.py
rename to tests/commands/__init__.py
diff --git a/tests/commands/test_build_config.py b/tests/commands/test_build_config.py
new file mode 100644
index 000000000..291720f4b
--- /dev/null
+++ b/tests/commands/test_build_config.py
@@ -0,0 +1,114 @@
+from pathlib import Path
+from unittest.mock import MagicMock
+
+import pytest
+import rapidjson
+
+from freqtrade.commands.build_config_commands import (ask_user_config, ask_user_overwrite,
+                                                      start_new_config, validate_is_float,
+                                                      validate_is_int)
+from freqtrade.exceptions import OperationalException
+from tests.conftest import get_args, log_has_re
+
+
+def test_validate_is_float():
+    assert validate_is_float('2.0')
+    assert validate_is_float('2.1')
+    assert validate_is_float('0.1')
+    assert validate_is_float('-0.5')
+    assert not validate_is_float('-0.5e')
+
+
+def test_validate_is_int():
+    assert validate_is_int('2')
+    assert validate_is_int('6')
+    assert validate_is_int('-1')
+    assert validate_is_int('500')
+    assert not validate_is_int('2.0')
+    assert not validate_is_int('2.1')
+    assert not validate_is_int('-2.1')
+    assert not validate_is_int('-ee')
+
+
+@pytest.mark.parametrize('exchange', ['bittrex', 'binance', 'kraken', 'ftx'])
+def test_start_new_config(mocker, caplog, exchange):
+    wt_mock = mocker.patch.object(Path, "write_text", MagicMock())
+    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+    unlink_mock = mocker.patch.object(Path, "unlink", MagicMock())
+    mocker.patch('freqtrade.commands.build_config_commands.ask_user_overwrite', return_value=True)
+
+    sample_selections = {
+        'max_open_trades': 3,
+        'stake_currency': 'USDT',
+        'stake_amount': 100,
+        'fiat_display_currency': 'EUR',
+        'timeframe': '15m',
+        'dry_run': True,
+        'exchange_name': exchange,
+        'exchange_key': 'sampleKey',
+        'exchange_secret': 'Samplesecret',
+        'telegram': False,
+        'telegram_token': 'asdf1244',
+        'telegram_chat_id': '1144444',
+    }
+    mocker.patch('freqtrade.commands.build_config_commands.ask_user_config',
+                 return_value=sample_selections)
+    args = [
+        "new-config",
+        "--config",
+        "coolconfig.json"
+    ]
+    start_new_config(get_args(args))
+
+    assert log_has_re("Writing config to .*", caplog)
+    assert wt_mock.call_count == 1
+    assert unlink_mock.call_count == 1
+    result = rapidjson.loads(wt_mock.call_args_list[0][0][0],
+                             parse_mode=rapidjson.PM_COMMENTS | rapidjson.PM_TRAILING_COMMAS)
+    assert result['exchange']['name'] == exchange
+    assert result['timeframe'] == '15m'
+
+
+def test_start_new_config_exists(mocker, caplog):
+    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+    mocker.patch('freqtrade.commands.build_config_commands.ask_user_overwrite', return_value=False)
+    args = [
+        "new-config",
+        "--config",
+        "coolconfig.json"
+    ]
+    with pytest.raises(OperationalException, match=r"Configuration .* already exists\."):
+        start_new_config(get_args(args))
+
+
+def test_ask_user_overwrite(mocker):
+    """
+    Once https://github.com/tmbo/questionary/issues/35 is implemented, improve this test.
+    """
+    prompt_mock = mocker.patch('freqtrade.commands.build_config_commands.prompt',
+                               return_value={'overwrite': False})
+    assert not ask_user_overwrite(Path('test.json'))
+    assert prompt_mock.call_count == 1
+
+    prompt_mock.reset_mock()
+    prompt_mock = mocker.patch('freqtrade.commands.build_config_commands.prompt',
+                               return_value={'overwrite': True})
+    assert ask_user_overwrite(Path('test.json'))
+    assert prompt_mock.call_count == 1
+
+
+def test_ask_user_config(mocker):
+    """
+    Once https://github.com/tmbo/questionary/issues/35 is implemented, improve this test.
+    """
+    prompt_mock = mocker.patch('freqtrade.commands.build_config_commands.prompt',
+                               return_value={'overwrite': False})
+    answers = ask_user_config()
+    assert isinstance(answers, dict)
+    assert prompt_mock.call_count == 1
+
+    prompt_mock = mocker.patch('freqtrade.commands.build_config_commands.prompt',
+                               return_value={})
+
+    with pytest.raises(OperationalException, match=r"User interrupted interactive questions\."):
+        ask_user_config()
diff --git a/tests/commands/test_commands.py b/tests/commands/test_commands.py
new file mode 100644
index 000000000..26e0c4a79
--- /dev/null
+++ b/tests/commands/test_commands.py
@@ -0,0 +1,1233 @@
+import re
+from pathlib import Path
+from unittest.mock import MagicMock, PropertyMock
+
+import arrow
+import pytest
+
+from freqtrade.commands import (start_convert_data, start_create_userdir, start_download_data,
+                                start_hyperopt_list, start_hyperopt_show, start_list_data,
+                                start_list_exchanges, start_list_hyperopts, start_list_markets,
+                                start_list_strategies, start_list_timeframes, start_new_hyperopt,
+                                start_new_strategy, start_show_trades, start_test_pairlist,
+                                start_trading)
+from freqtrade.configuration import setup_utils_configuration
+from freqtrade.exceptions import OperationalException
+from freqtrade.state import RunMode
+from tests.conftest import (create_mock_trades, get_args, log_has, log_has_re, patch_exchange,
+                            patched_configuration_load_config_file)
+from tests.conftest_trades import MOCK_TRADE_COUNT
+
+
+def test_setup_utils_configuration():
+    args = [
+        'list-exchanges', '--config', 'config.json.example',
+    ]
+
+    config = setup_utils_configuration(get_args(args), RunMode.OTHER)
+    assert "exchange" in config
+    assert config['dry_run'] is True
+    assert config['exchange']['key'] == ''
+    assert config['exchange']['secret'] == ''
+
+
+def test_start_trading_fail(mocker, caplog):
+
+    mocker.patch("freqtrade.worker.Worker.run", MagicMock(side_effect=OperationalException))
+
+    mocker.patch("freqtrade.worker.Worker.__init__", MagicMock(return_value=None))
+
+    exitmock = mocker.patch("freqtrade.worker.Worker.exit", MagicMock())
+    args = [
+        'trade',
+        '-c', 'config.json.example'
+    ]
+    start_trading(get_args(args))
+    assert exitmock.call_count == 1
+
+    exitmock.reset_mock()
+    caplog.clear()
+    mocker.patch("freqtrade.worker.Worker.__init__", MagicMock(side_effect=OperationalException))
+    start_trading(get_args(args))
+    assert exitmock.call_count == 0
+    assert log_has('Fatal exception!', caplog)
+
+
+def test_list_exchanges(capsys):
+
+    args = [
+        "list-exchanges",
+    ]
+
+    start_list_exchanges(get_args(args))
+    captured = capsys.readouterr()
+    assert re.match(r"Exchanges available for Freqtrade.*", captured.out)
+    assert re.match(r".*binance,.*", captured.out)
+    assert re.match(r".*bittrex,.*", captured.out)
+
+    # Test with --one-column
+    args = [
+        "list-exchanges",
+        "--one-column",
+    ]
+
+    start_list_exchanges(get_args(args))
+    captured = capsys.readouterr()
+    assert re.search(r"^binance$", captured.out, re.MULTILINE)
+    assert re.search(r"^bittrex$", captured.out, re.MULTILINE)
+
+    # Test with --all
+    args = [
+        "list-exchanges",
+        "--all",
+    ]
+
+    start_list_exchanges(get_args(args))
+    captured = capsys.readouterr()
+    assert re.match(r"All exchanges supported by the ccxt library.*", captured.out)
+    assert re.match(r".*binance,.*", captured.out)
+    assert re.match(r".*bittrex,.*", captured.out)
+    assert re.match(r".*bitmex,.*", captured.out)
+
+    # Test with --one-column --all
+    args = [
+        "list-exchanges",
+        "--one-column",
+        "--all",
+    ]
+
+    start_list_exchanges(get_args(args))
+    captured = capsys.readouterr()
+    assert re.search(r"^binance$", captured.out, re.MULTILINE)
+    assert re.search(r"^bittrex$", captured.out, re.MULTILINE)
+    assert re.search(r"^bitmex$", captured.out, re.MULTILINE)
+
+
+def test_list_timeframes(mocker, capsys):
+
+    api_mock = MagicMock()
+    api_mock.timeframes = {'1m': 'oneMin',
+                           '5m': 'fiveMin',
+                           '30m': 'thirtyMin',
+                           '1h': 'hour',
+                           '1d': 'day',
+                           }
+    patch_exchange(mocker, api_mock=api_mock)
+    args = [
+        "list-timeframes",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    with pytest.raises(OperationalException,
+                       match=r"This command requires a configured exchange.*"):
+        start_list_timeframes(pargs)
+
+    # Test with --config config.json.example
+    args = [
+        "list-timeframes",
+        '--config', 'config.json.example',
+    ]
+    start_list_timeframes(get_args(args))
+    captured = capsys.readouterr()
+    assert re.match("Timeframes available for the exchange `Bittrex`: "
+                    "1m, 5m, 30m, 1h, 1d",
+                    captured.out)
+
+    # Test with --exchange bittrex
+    args = [
+        "list-timeframes",
+        "--exchange", "bittrex",
+    ]
+    start_list_timeframes(get_args(args))
+    captured = capsys.readouterr()
+    assert re.match("Timeframes available for the exchange `Bittrex`: "
+                    "1m, 5m, 30m, 1h, 1d",
+                    captured.out)
+
+    api_mock.timeframes = {'1m': '1m',
+                           '5m': '5m',
+                           '15m': '15m',
+                           '30m': '30m',
+                           '1h': '1h',
+                           '6h': '6h',
+                           '12h': '12h',
+                           '1d': '1d',
+                           '3d': '3d',
+                           }
+    patch_exchange(mocker, api_mock=api_mock, id='binance')
+    # Test with --exchange binance
+    args = [
+        "list-timeframes",
+        "--exchange", "binance",
+    ]
+    start_list_timeframes(get_args(args))
+    captured = capsys.readouterr()
+    assert re.match("Timeframes available for the exchange `Binance`: "
+                    "1m, 5m, 15m, 30m, 1h, 6h, 12h, 1d, 3d",
+                    captured.out)
+
+    # Test with --one-column
+    args = [
+        "list-timeframes",
+        '--config', 'config.json.example',
+        "--one-column",
+    ]
+    start_list_timeframes(get_args(args))
+    captured = capsys.readouterr()
+    assert re.search(r"^1m$", captured.out, re.MULTILINE)
+    assert re.search(r"^5m$", captured.out, re.MULTILINE)
+    assert re.search(r"^1h$", captured.out, re.MULTILINE)
+    assert re.search(r"^1d$", captured.out, re.MULTILINE)
+
+    # Test with --exchange binance --one-column
+    args = [
+        "list-timeframes",
+        "--exchange", "binance",
+        "--one-column",
+    ]
+    start_list_timeframes(get_args(args))
+    captured = capsys.readouterr()
+    assert re.search(r"^1m$", captured.out, re.MULTILINE)
+    assert re.search(r"^5m$", captured.out, re.MULTILINE)
+    assert re.search(r"^1h$", captured.out, re.MULTILINE)
+    assert re.search(r"^1d$", captured.out, re.MULTILINE)
+
+
+def test_list_markets(mocker, markets, capsys):
+
+    api_mock = MagicMock()
+    api_mock.markets = markets
+    patch_exchange(mocker, api_mock=api_mock)
+
+    # Test with no --config
+    args = [
+        "list-markets",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    with pytest.raises(OperationalException,
+                       match=r"This command requires a configured exchange.*"):
+        start_list_markets(pargs, False)
+
+    # Test with --config config.json.example
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+        "--print-list",
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 10 active markets: "
+            "BLK/BTC, ETH/BTC, ETH/USDT, LTC/BTC, LTC/ETH, LTC/USD, NEO/BTC, "
+            "TKN/BTC, XLTCUSDT, XRP/BTC.\n"
+            in captured.out)
+
+    patch_exchange(mocker, api_mock=api_mock, id="binance")
+    # Test with --exchange
+    args = [
+        "list-markets",
+        "--exchange", "binance"
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_list_markets(pargs, False)
+    captured = capsys.readouterr()
+    assert re.match("\nExchange Binance has 10 active markets:\n",
+                    captured.out)
+
+    patch_exchange(mocker, api_mock=api_mock, id="bittrex")
+    # Test with --all: all markets
+    args = [
+        "list-markets", "--all",
+        '--config', 'config.json.example',
+        "--print-list",
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 12 markets: "
+            "BLK/BTC, BTT/BTC, ETH/BTC, ETH/USDT, LTC/BTC, LTC/ETH, LTC/USD, LTC/USDT, NEO/BTC, "
+            "TKN/BTC, XLTCUSDT, XRP/BTC.\n"
+            in captured.out)
+
+    # Test list-pairs subcommand: active pairs
+    args = [
+        "list-pairs",
+        '--config', 'config.json.example',
+        "--print-list",
+    ]
+    start_list_markets(get_args(args), True)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 9 active pairs: "
+            "BLK/BTC, ETH/BTC, ETH/USDT, LTC/BTC, LTC/ETH, LTC/USD, NEO/BTC, TKN/BTC, XRP/BTC.\n"
+            in captured.out)
+
+    # Test list-pairs subcommand with --all: all pairs
+    args = [
+        "list-pairs", "--all",
+        '--config', 'config.json.example',
+        "--print-list",
+    ]
+    start_list_markets(get_args(args), True)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 11 pairs: "
+            "BLK/BTC, BTT/BTC, ETH/BTC, ETH/USDT, LTC/BTC, LTC/ETH, LTC/USD, LTC/USDT, NEO/BTC, "
+            "TKN/BTC, XRP/BTC.\n"
+            in captured.out)
+
+    # active markets, base=ETH, LTC
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+        "--base", "ETH", "LTC",
+        "--print-list",
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 6 active markets with ETH, LTC as base currencies: "
+            "ETH/BTC, ETH/USDT, LTC/BTC, LTC/ETH, LTC/USD, XLTCUSDT.\n"
+            in captured.out)
+
+    # active markets, base=LTC
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+        "--base", "LTC",
+        "--print-list",
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 4 active markets with LTC as base currency: "
+            "LTC/BTC, LTC/ETH, LTC/USD, XLTCUSDT.\n"
+            in captured.out)
+
+    # active markets, quote=USDT, USD
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+        "--quote", "USDT", "USD",
+        "--print-list",
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 3 active markets with USDT, USD as quote currencies: "
+            "ETH/USDT, LTC/USD, XLTCUSDT.\n"
+            in captured.out)
+
+    # active markets, quote=USDT
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+        "--quote", "USDT",
+        "--print-list",
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 2 active markets with USDT as quote currency: "
+            "ETH/USDT, XLTCUSDT.\n"
+            in captured.out)
+
+    # active markets, base=LTC, quote=USDT
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+        "--base", "LTC", "--quote", "USDT",
+        "--print-list",
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 1 active market with LTC as base currency and "
+            "with USDT as quote currency: XLTCUSDT.\n"
+            in captured.out)
+
+    # active pairs, base=LTC, quote=USDT
+    args = [
+        "list-pairs",
+        '--config', 'config.json.example',
+        "--base", "LTC", "--quote", "USD",
+        "--print-list",
+    ]
+    start_list_markets(get_args(args), True)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 1 active pair with LTC as base currency and "
+            "with USD as quote currency: LTC/USD.\n"
+            in captured.out)
+
+    # active markets, base=LTC, quote=USDT, NONEXISTENT
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+        "--base", "LTC", "--quote", "USDT", "NONEXISTENT",
+        "--print-list",
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 1 active market with LTC as base currency and "
+            "with USDT, NONEXISTENT as quote currencies: XLTCUSDT.\n"
+            in captured.out)
+
+    # active markets, base=LTC, quote=NONEXISTENT
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+        "--base", "LTC", "--quote", "NONEXISTENT",
+        "--print-list",
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 0 active markets with LTC as base currency and "
+            "with NONEXISTENT as quote currency.\n"
+            in captured.out)
+
+    # Test tabular output
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 10 active markets:\n"
+            in captured.out)
+
+    # Test tabular output, no markets found
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+        "--base", "LTC", "--quote", "NONEXISTENT",
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert ("Exchange Bittrex has 0 active markets with LTC as base currency and "
+            "with NONEXISTENT as quote currency.\n"
+            in captured.out)
+
+    # Test --print-json
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+        "--print-json"
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert ('["BLK/BTC","ETH/BTC","ETH/USDT","LTC/BTC","LTC/ETH","LTC/USD","NEO/BTC",'
+            '"TKN/BTC","XLTCUSDT","XRP/BTC"]'
+            in captured.out)
+
+    # Test --print-csv
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+        "--print-csv"
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert ("Id,Symbol,Base,Quote,Active,Is pair" in captured.out)
+    assert ("blkbtc,BLK/BTC,BLK,BTC,True,True" in captured.out)
+    assert ("USD-LTC,LTC/USD,LTC,USD,True,True" in captured.out)
+
+    # Test --one-column
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+        "--one-column"
+    ]
+    start_list_markets(get_args(args), False)
+    captured = capsys.readouterr()
+    assert re.search(r"^BLK/BTC$", captured.out, re.MULTILINE)
+    assert re.search(r"^LTC/USD$", captured.out, re.MULTILINE)
+
+    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(side_effect=ValueError))
+    # Test --one-column
+    args = [
+        "list-markets",
+        '--config', 'config.json.example',
+        "--one-column"
+    ]
+    with pytest.raises(OperationalException, match=r"Cannot get markets.*"):
+        start_list_markets(get_args(args), False)
+
+
+def test_create_datadir_failed(caplog):
+
+    args = [
+        "create-userdir",
+    ]
+    with pytest.raises(SystemExit):
+        start_create_userdir(get_args(args))
+    assert log_has("`create-userdir` requires --userdir to be set.", caplog)
+
+
+def test_create_datadir(caplog, mocker):
+
+    cud = mocker.patch("freqtrade.commands.deploy_commands.create_userdata_dir", MagicMock())
+    csf = mocker.patch("freqtrade.commands.deploy_commands.copy_sample_files", MagicMock())
+    args = [
+        "create-userdir",
+        "--userdir",
+        "/temp/freqtrade/test"
+    ]
+    start_create_userdir(get_args(args))
+
+    assert cud.call_count == 1
+    assert csf.call_count == 1
+
+
+def test_start_new_strategy(mocker, caplog):
+    wt_mock = mocker.patch.object(Path, "write_text", MagicMock())
+    mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+
+    args = [
+        "new-strategy",
+        "--strategy",
+        "CoolNewStrategy"
+    ]
+    start_new_strategy(get_args(args))
+
+    assert wt_mock.call_count == 1
+    assert "CoolNewStrategy" in wt_mock.call_args_list[0][0][0]
+    assert log_has_re("Writing strategy to .*", caplog)
+
+    mocker.patch('freqtrade.commands.deploy_commands.setup_utils_configuration')
+    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+    with pytest.raises(OperationalException,
+                       match=r".* already exists. Please choose another Strategy Name\."):
+        start_new_strategy(get_args(args))
+
+
+def test_start_new_strategy_DefaultStrat(mocker, caplog):
+    args = [
+        "new-strategy",
+        "--strategy",
+        "DefaultStrategy"
+    ]
+    with pytest.raises(OperationalException,
+                       match=r"DefaultStrategy is not allowed as name\."):
+        start_new_strategy(get_args(args))
+
+
+def test_start_new_strategy_no_arg(mocker, caplog):
+    args = [
+        "new-strategy",
+    ]
+    with pytest.raises(OperationalException,
+                       match="`new-strategy` requires --strategy to be set."):
+        start_new_strategy(get_args(args))
+
+
+def test_start_new_hyperopt(mocker, caplog):
+    wt_mock = mocker.patch.object(Path, "write_text", MagicMock())
+    mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+
+    args = [
+        "new-hyperopt",
+        "--hyperopt",
+        "CoolNewhyperopt"
+    ]
+    start_new_hyperopt(get_args(args))
+
+    assert wt_mock.call_count == 1
+    assert "CoolNewhyperopt" in wt_mock.call_args_list[0][0][0]
+    assert log_has_re("Writing hyperopt to .*", caplog)
+
+    mocker.patch('freqtrade.commands.deploy_commands.setup_utils_configuration')
+    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+    with pytest.raises(OperationalException,
+                       match=r".* already exists. Please choose another Hyperopt Name\."):
+        start_new_hyperopt(get_args(args))
+
+
+def test_start_new_hyperopt_DefaultHyperopt(mocker, caplog):
+    args = [
+        "new-hyperopt",
+        "--hyperopt",
+        "DefaultHyperopt"
+    ]
+    with pytest.raises(OperationalException,
+                       match=r"DefaultHyperopt is not allowed as name\."):
+        start_new_hyperopt(get_args(args))
+
+
+def test_start_new_hyperopt_no_arg(mocker, caplog):
+    args = [
+        "new-hyperopt",
+    ]
+    with pytest.raises(OperationalException,
+                       match="`new-hyperopt` requires --hyperopt to be set."):
+        start_new_hyperopt(get_args(args))
+
+
+def test_download_data_keyboardInterrupt(mocker, caplog, markets):
+    dl_mock = mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
+                           MagicMock(side_effect=KeyboardInterrupt))
+    patch_exchange(mocker)
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets)
+    )
+    args = [
+        "download-data",
+        "--exchange", "binance",
+        "--pairs", "ETH/BTC", "XRP/BTC",
+    ]
+    with pytest.raises(SystemExit):
+        start_download_data(get_args(args))
+
+    assert dl_mock.call_count == 1
+
+
+def test_download_data_timerange(mocker, caplog, markets):
+    dl_mock = mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
+                           MagicMock(return_value=["ETH/BTC", "XRP/BTC"]))
+    patch_exchange(mocker)
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets)
+    )
+    args = [
+        "download-data",
+        "--exchange", "binance",
+        "--pairs", "ETH/BTC", "XRP/BTC",
+        "--days", "20",
+        "--timerange", "20200101-"
+    ]
+    with pytest.raises(OperationalException,
+                       match=r"--days and --timerange are mutually.*"):
+        start_download_data(get_args(args))
+    assert dl_mock.call_count == 0
+
+    args = [
+        "download-data",
+        "--exchange", "binance",
+        "--pairs", "ETH/BTC", "XRP/BTC",
+        "--days", "20",
+    ]
+    start_download_data(get_args(args))
+    assert dl_mock.call_count == 1
+    # 20days ago
+    days_ago = arrow.get(arrow.utcnow().shift(days=-20).date()).int_timestamp
+    assert dl_mock.call_args_list[0][1]['timerange'].startts == days_ago
+
+    dl_mock.reset_mock()
+    args = [
+        "download-data",
+        "--exchange", "binance",
+        "--pairs", "ETH/BTC", "XRP/BTC",
+        "--timerange", "20200101-"
+    ]
+    start_download_data(get_args(args))
+    assert dl_mock.call_count == 1
+
+    assert dl_mock.call_args_list[0][1]['timerange'].startts == arrow.Arrow(
+        2020, 1, 1).int_timestamp
+
+
+def test_download_data_no_markets(mocker, caplog):
+    dl_mock = mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
+                           MagicMock(return_value=["ETH/BTC", "XRP/BTC"]))
+    patch_exchange(mocker, id='binance')
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets', PropertyMock(return_value={})
+    )
+    args = [
+        "download-data",
+        "--exchange", "binance",
+        "--pairs", "ETH/BTC", "XRP/BTC",
+        "--days", "20"
+    ]
+    start_download_data(get_args(args))
+    assert dl_mock.call_args[1]['timerange'].starttype == "date"
+    assert log_has("Pairs [ETH/BTC,XRP/BTC] not available on exchange Binance.", caplog)
+
+
+def test_download_data_no_exchange(mocker, caplog):
+    mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
+                 MagicMock(return_value=["ETH/BTC", "XRP/BTC"]))
+    patch_exchange(mocker)
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets', PropertyMock(return_value={})
+    )
+    args = [
+        "download-data",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    with pytest.raises(OperationalException,
+                       match=r"This command requires a configured exchange.*"):
+        start_download_data(pargs)
+
+
+def test_download_data_no_pairs(mocker, caplog):
+
+    mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+
+    mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
+                 MagicMock(return_value=["ETH/BTC", "XRP/BTC"]))
+    patch_exchange(mocker)
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets', PropertyMock(return_value={})
+    )
+    args = [
+        "download-data",
+        "--exchange",
+        "binance",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    with pytest.raises(OperationalException,
+                       match=r"Downloading data requires a list of pairs\..*"):
+        start_download_data(pargs)
+
+
+def test_download_data_trades(mocker, caplog):
+    dl_mock = mocker.patch('freqtrade.commands.data_commands.refresh_backtest_trades_data',
+                           MagicMock(return_value=[]))
+    convert_mock = mocker.patch('freqtrade.commands.data_commands.convert_trades_to_ohlcv',
+                                MagicMock(return_value=[]))
+    patch_exchange(mocker)
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets', PropertyMock(return_value={})
+    )
+    args = [
+        "download-data",
+        "--exchange", "kraken",
+        "--pairs", "ETH/BTC", "XRP/BTC",
+        "--days", "20",
+        "--dl-trades"
+    ]
+    start_download_data(get_args(args))
+    assert dl_mock.call_args[1]['timerange'].starttype == "date"
+    assert dl_mock.call_count == 1
+    assert convert_mock.call_count == 1
+
+
+def test_start_list_strategies(mocker, caplog, capsys):
+
+    args = [
+        "list-strategies",
+        "--strategy-path",
+        str(Path(__file__).parent.parent / "strategy" / "strats"),
+        "-1"
+    ]
+    pargs = get_args(args)
+    # pargs['config'] = None
+    start_list_strategies(pargs)
+    captured = capsys.readouterr()
+    assert "TestStrategyLegacy" in captured.out
+    assert "legacy_strategy.py" not in captured.out
+    assert "DefaultStrategy" in captured.out
+
+    # Test regular output
+    args = [
+        "list-strategies",
+        "--strategy-path",
+        str(Path(__file__).parent.parent / "strategy" / "strats"),
+        '--no-color',
+    ]
+    pargs = get_args(args)
+    # pargs['config'] = None
+    start_list_strategies(pargs)
+    captured = capsys.readouterr()
+    assert "TestStrategyLegacy" in captured.out
+    assert "legacy_strategy.py" in captured.out
+    assert "DefaultStrategy" in captured.out
+
+
+def test_start_list_hyperopts(mocker, caplog, capsys):
+
+    args = [
+        "list-hyperopts",
+        "--hyperopt-path",
+        str(Path(__file__).parent.parent / "optimize" / "hyperopts"),
+        "-1"
+    ]
+    pargs = get_args(args)
+    # pargs['config'] = None
+    start_list_hyperopts(pargs)
+    captured = capsys.readouterr()
+    assert "TestHyperoptLegacy" not in captured.out
+    assert "legacy_hyperopt.py" not in captured.out
+    assert "DefaultHyperOpt" in captured.out
+    assert "test_hyperopt.py" not in captured.out
+
+    # Test regular output
+    args = [
+        "list-hyperopts",
+        "--hyperopt-path",
+        str(Path(__file__).parent.parent / "optimize" / "hyperopts"),
+    ]
+    pargs = get_args(args)
+    # pargs['config'] = None
+    start_list_hyperopts(pargs)
+    captured = capsys.readouterr()
+    assert "TestHyperoptLegacy" not in captured.out
+    assert "legacy_hyperopt.py" not in captured.out
+    assert "DefaultHyperOpt" in captured.out
+
+
+def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
+    patch_exchange(mocker, mock_markets=True)
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          exchange_has=MagicMock(return_value=True),
+                          get_tickers=tickers,
+                          )
+
+    default_conf['pairlists'] = [
+        {
+            "method": "VolumePairList",
+            "number_assets": 5,
+            "sort_key": "quoteVolume",
+        },
+        {"method": "PrecisionFilter"},
+        {"method": "PriceFilter", "low_price_ratio": 0.02},
+    ]
+
+    patched_configuration_load_config_file(mocker, default_conf)
+    args = [
+        'test-pairlist',
+        '-c', 'config.json.example'
+    ]
+
+    start_test_pairlist(get_args(args))
+
+    assert log_has_re(r"^Using resolved pairlist VolumePairList.*", caplog)
+    assert log_has_re(r"^Using resolved pairlist PrecisionFilter.*", caplog)
+    assert log_has_re(r"^Using resolved pairlist PriceFilter.*", caplog)
+    captured = capsys.readouterr()
+    assert re.match(r"Pairs for .*", captured.out)
+    assert re.match("['ETH/BTC', 'TKN/BTC', 'BLK/BTC', 'LTC/BTC', 'XRP/BTC']", captured.out)
+
+    args = [
+        'test-pairlist',
+        '-c', 'config.json.example',
+        '--one-column',
+    ]
+    start_test_pairlist(get_args(args))
+    captured = capsys.readouterr()
+    assert re.match(r"ETH/BTC\nTKN/BTC\nBLK/BTC\nLTC/BTC\nXRP/BTC\n", captured.out)
+
+    args = [
+        'test-pairlist',
+        '-c', 'config.json.example',
+        '--print-json',
+    ]
+    start_test_pairlist(get_args(args))
+    captured = capsys.readouterr()
+    assert re.match(r'Pairs for BTC: \n\["ETH/BTC","TKN/BTC","BLK/BTC","LTC/BTC","XRP/BTC"\]\n',
+                    captured.out)
+
+
+def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results):
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.Hyperopt.load_previous_results',
+        MagicMock(return_value=hyperopt_results)
+    )
+
+    args = [
+        "hyperopt-list",
+        "--no-details",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 1/12", " 2/12", " 3/12", " 4/12", " 5/12",
+                         " 6/12", " 7/12", " 8/12", " 9/12", " 10/12",
+                         " 11/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--best",
+        "--no-details",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 1/12", " 5/12", " 10/12"])
+    assert all(x not in captured.out
+               for x in [" 2/12", " 3/12", " 4/12", " 6/12", " 7/12", " 8/12", " 9/12",
+                         " 11/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--profitable",
+        "--no-details",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 2/12", " 10/12"])
+    assert all(x not in captured.out
+               for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12",
+                         " 11/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--profitable",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 2/12", " 10/12", "Best result:", "Buy hyperspace params",
+                         "Sell hyperspace params", "ROI table", "Stoploss"])
+    assert all(x not in captured.out
+               for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12",
+                         " 11/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--no-details",
+        "--no-color",
+        "--min-trades", "20",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 3/12", " 6/12", " 7/12", " 9/12", " 11/12"])
+    assert all(x not in captured.out
+               for x in [" 1/12", " 2/12", " 4/12", " 5/12", " 8/12", " 10/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--profitable",
+        "--no-details",
+        "--max-trades", "20",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 2/12", " 10/12"])
+    assert all(x not in captured.out
+               for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12",
+                         " 11/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--profitable",
+        "--no-details",
+        "--min-avg-profit", "0.11",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 2/12"])
+    assert all(x not in captured.out
+               for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12",
+                         " 10/12", " 11/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--no-details",
+        "--max-avg-profit", "0.10",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 1/12", " 3/12", " 5/12", " 6/12", " 7/12", " 8/12", " 9/12",
+                         " 11/12"])
+    assert all(x not in captured.out
+               for x in [" 2/12", " 4/12", " 10/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--no-details",
+        "--min-total-profit", "0.4",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 10/12"])
+    assert all(x not in captured.out
+               for x in [" 1/12", " 2/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12",
+                         " 9/12", " 11/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--no-details",
+        "--max-total-profit", "0.4",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 1/12", " 2/12", " 3/12", " 5/12", " 6/12", " 7/12", " 8/12",
+                         " 9/12", " 11/12"])
+    assert all(x not in captured.out
+               for x in [" 4/12", " 10/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--no-details",
+        "--min-objective", "0.1",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 10/12"])
+    assert all(x not in captured.out
+               for x in [" 1/12", " 2/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12", " 8/12",
+                         " 9/12", " 11/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--no-details",
+        "--max-objective", "0.1",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 1/12", " 2/12", " 3/12", " 5/12", " 6/12", " 7/12", " 8/12",
+                         " 9/12", " 11/12"])
+    assert all(x not in captured.out
+               for x in [" 4/12", " 10/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--profitable",
+        "--no-details",
+        "--min-avg-time", "2000",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 10/12"])
+    assert all(x not in captured.out
+               for x in [" 1/12", " 2/12", " 3/12", " 4/12", " 5/12", " 6/12", " 7/12",
+                         " 8/12", " 9/12", " 11/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--no-details",
+        "--max-avg-time", "1500",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    assert all(x in captured.out
+               for x in [" 2/12", " 6/12"])
+    assert all(x not in captured.out
+               for x in [" 1/12", " 3/12", " 4/12", " 5/12", " 7/12", " 8/12"
+                         " 9/12", " 10/12", " 11/12", " 12/12"])
+    args = [
+        "hyperopt-list",
+        "--no-details",
+        "--export-csv", "test_file.csv",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_list(pargs)
+    captured = capsys.readouterr()
+    log_has("CSV file created: test_file.csv", caplog)
+    f = Path("test_file.csv")
+    assert 'Best,1,2,-1.25%,-0.00125625,,-2.51,"3,930.0 m",0.43662' in f.read_text()
+    assert f.is_file()
+    f.unlink()
+
+
+def test_hyperopt_show(mocker, capsys, hyperopt_results):
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.Hyperopt.load_previous_results',
+        MagicMock(return_value=hyperopt_results)
+    )
+
+    args = [
+        "hyperopt-show",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_show(pargs)
+    captured = capsys.readouterr()
+    assert " 12/12" in captured.out
+
+    args = [
+        "hyperopt-show",
+        "--best"
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_show(pargs)
+    captured = capsys.readouterr()
+    assert " 10/12" in captured.out
+
+    args = [
+        "hyperopt-show",
+        "-n", "1"
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_show(pargs)
+    captured = capsys.readouterr()
+    assert " 1/12" in captured.out
+
+    args = [
+        "hyperopt-show",
+        "--best",
+        "-n", "2"
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_show(pargs)
+    captured = capsys.readouterr()
+    assert " 5/12" in captured.out
+
+    args = [
+        "hyperopt-show",
+        "--best",
+        "-n", "-1"
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_hyperopt_show(pargs)
+    captured = capsys.readouterr()
+    assert " 10/12" in captured.out
+
+    args = [
+        "hyperopt-show",
+        "--best",
+        "-n", "-4"
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    with pytest.raises(OperationalException,
+                       match="The index of the epoch to show should be greater than -4."):
+        start_hyperopt_show(pargs)
+
+    args = [
+        "hyperopt-show",
+        "--best",
+        "-n", "4"
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    with pytest.raises(OperationalException,
+                       match="The index of the epoch to show should be less than 4."):
+        start_hyperopt_show(pargs)
+
+
+def test_convert_data(mocker, testdatadir):
+    ohlcv_mock = mocker.patch("freqtrade.commands.data_commands.convert_ohlcv_format")
+    trades_mock = mocker.patch("freqtrade.commands.data_commands.convert_trades_format")
+    args = [
+        "convert-data",
+        "--format-from",
+        "json",
+        "--format-to",
+        "jsongz",
+        "--datadir",
+        str(testdatadir),
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_convert_data(pargs, True)
+    assert trades_mock.call_count == 0
+    assert ohlcv_mock.call_count == 1
+    assert ohlcv_mock.call_args[1]['convert_from'] == 'json'
+    assert ohlcv_mock.call_args[1]['convert_to'] == 'jsongz'
+    assert ohlcv_mock.call_args[1]['erase'] is False
+
+
+def test_convert_data_trades(mocker, testdatadir):
+    ohlcv_mock = mocker.patch("freqtrade.commands.data_commands.convert_ohlcv_format")
+    trades_mock = mocker.patch("freqtrade.commands.data_commands.convert_trades_format")
+    args = [
+        "convert-trade-data",
+        "--format-from",
+        "jsongz",
+        "--format-to",
+        "json",
+        "--datadir",
+        str(testdatadir),
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_convert_data(pargs, False)
+    assert ohlcv_mock.call_count == 0
+    assert trades_mock.call_count == 1
+    assert trades_mock.call_args[1]['convert_from'] == 'jsongz'
+    assert trades_mock.call_args[1]['convert_to'] == 'json'
+    assert trades_mock.call_args[1]['erase'] is False
+
+
+def test_start_list_data(testdatadir, capsys):
+    args = [
+        "list-data",
+        "--data-format-ohlcv",
+        "json",
+        "--datadir",
+        str(testdatadir),
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_list_data(pargs)
+    captured = capsys.readouterr()
+    assert "Found 16 pair / timeframe combinations." in captured.out
+    assert "\n|         Pair |       Timeframe |\n" in captured.out
+    assert "\n| UNITTEST/BTC | 1m, 5m, 8m, 30m |\n" in captured.out
+
+    args = [
+        "list-data",
+        "--data-format-ohlcv",
+        "json",
+        "--pairs", "XRP/ETH",
+        "--datadir",
+        str(testdatadir),
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_list_data(pargs)
+    captured = capsys.readouterr()
+    assert "Found 2 pair / timeframe combinations." in captured.out
+    assert "\n|    Pair |   Timeframe |\n" in captured.out
+    assert "UNITTEST/BTC" not in captured.out
+    assert "\n| XRP/ETH |      1m, 5m |\n" in captured.out
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_show_trades(mocker, fee, capsys, caplog):
+    mocker.patch("freqtrade.persistence.init_db")
+    create_mock_trades(fee)
+    args = [
+        "show-trades",
+        "--db-url",
+        "sqlite:///"
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_show_trades(pargs)
+    assert log_has(f"Printing {MOCK_TRADE_COUNT} Trades: ", caplog)
+    captured = capsys.readouterr()
+    assert "Trade(id=1" in captured.out
+    assert "Trade(id=2" in captured.out
+    assert "Trade(id=3" in captured.out
+    args = [
+        "show-trades",
+        "--db-url",
+        "sqlite:///",
+        "--print-json",
+        "--trade-ids", "1", "2"
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+    start_show_trades(pargs)
+
+    captured = capsys.readouterr()
+    assert log_has("Printing 2 Trades: ", caplog)
+    assert '"trade_id": 1' in captured.out
+    assert '"trade_id": 2' in captured.out
+    assert '"trade_id": 3' not in captured.out
+    args = [
+        "show-trades",
+    ]
+    pargs = get_args(args)
+    pargs['config'] = None
+
+    with pytest.raises(OperationalException, match=r"--db-url is required for this command."):
+        start_show_trades(pargs)
diff --git a/tests/config_test_comments.json b/tests/config_test_comments.json
new file mode 100644
index 000000000..4f201f86c
--- /dev/null
+++ b/tests/config_test_comments.json
@@ -0,0 +1,127 @@
+{
+    /* Single-line C-style comment */
+    "max_open_trades": 3,
+    /*
+     * Multi-line C-style comment
+     */
+    "stake_currency": "BTC",
+    "stake_amount": 0.05,
+    "fiat_display_currency": "USD",             // C++-style comment
+    "amount_reserve_percent" : 0.05,		// And more, tabs before this comment
+    "dry_run": false,
+    "timeframe": "5m",
+    "trailing_stop": false,
+    "trailing_stop_positive": 0.005,
+    "trailing_stop_positive_offset": 0.0051,
+    "trailing_only_offset_is_reached": false,
+    "minimal_roi": {
+        "40":  0.0,
+        "30":  0.01,
+        "20":  0.02,
+        "0":  0.04
+    },
+    "stoploss": -0.10,
+    "unfilledtimeout": {
+        "buy": 10,
+        "sell": 30,				// Trailing comma should also be accepted now
+    },
+    "bid_strategy": {
+        "use_order_book": false,
+        "ask_last_balance": 0.0,
+        "order_book_top": 1,
+        "check_depth_of_market": {
+            "enabled": false,
+            "bids_to_ask_delta": 1
+        }
+    },
+    "ask_strategy":{
+        "use_order_book": false,
+        "order_book_min": 1,
+        "order_book_max": 9
+    },
+    "order_types": {
+        "buy": "limit",
+        "sell": "limit",
+        "stoploss": "market",
+        "stoploss_on_exchange": false,
+        "stoploss_on_exchange_interval": 60
+    },
+    "order_time_in_force": {
+        "buy": "gtc",
+        "sell": "gtc"
+    },
+    "pairlist": {
+        "method": "VolumePairList",
+        "config": {
+            "number_assets": 20,
+            "sort_key": "quoteVolume",
+            "precision_filter": false
+        }
+    },
+    "exchange": {
+        "name": "bittrex",
+        "sandbox": false,
+        "key": "your_exchange_key",
+        "secret": "your_exchange_secret",
+        "password": "",
+        "ccxt_config": {"enableRateLimit": true},
+        "ccxt_async_config": {
+            "enableRateLimit": false,
+            "rateLimit": 500,
+            "aiohttp_trust_env": false
+        },
+        "pair_whitelist": [
+            "ETH/BTC",
+            "LTC/BTC",
+            "ETC/BTC",
+            "DASH/BTC",
+            "ZEC/BTC",
+            "XLM/BTC",
+            "NXT/BTC",
+            "TRX/BTC",
+            "ADA/BTC",
+            "XMR/BTC"
+        ],
+        "pair_blacklist": [
+            "DOGE/BTC"
+        ],
+        "outdated_offset": 5,
+        "markets_refresh_interval": 60
+    },
+    "edge": {
+        "enabled": false,
+        "process_throttle_secs": 3600,
+        "calculate_since_number_of_days": 7,
+        "allowed_risk": 0.01,
+        "stoploss_range_min": -0.01,
+        "stoploss_range_max": -0.1,
+        "stoploss_range_step": -0.01,
+        "minimum_winrate": 0.60,
+        "minimum_expectancy": 0.20,
+        "min_trade_number": 10,
+        "max_trade_duration_minute": 1440,
+        "remove_pumps": false
+    },
+    "telegram": {
+// We can now comment out some settings
+//        "enabled": true,
+        "enabled": false,
+        "token": "your_telegram_token",
+        "chat_id": "your_telegram_chat_id"
+    },
+    "api_server": {
+        "enabled": false,
+        "listen_ip_address": "127.0.0.1",
+        "listen_port": 8080,
+        "username": "freqtrader",
+        "password": "SuperSecurePassword"
+    },
+    "db_url": "sqlite:///tradesv3.sqlite",
+    "initial_state": "running",
+    "forcebuy_enable": false,
+    "internals": {
+        "process_throttle_secs": 5
+    },
+    "strategy": "DefaultStrategy",
+    "strategy_path": "user_data/strategies/"
+}
diff --git a/tests/conftest.py b/tests/conftest.py
new file mode 100644
index 000000000..079a521ed
--- /dev/null
+++ b/tests/conftest.py
@@ -0,0 +1,1884 @@
+# pragma pylint: disable=missing-docstring
+import json
+import logging
+import re
+from copy import deepcopy
+from datetime import datetime
+from functools import reduce
+from pathlib import Path
+from unittest.mock import MagicMock, PropertyMock
+
+import arrow
+import numpy as np
+import pytest
+from telegram import Chat, Message, Update
+
+from freqtrade import constants
+from freqtrade.commands import Arguments
+from freqtrade.data.converter import ohlcv_to_dataframe
+from freqtrade.edge import Edge, PairInfo
+from freqtrade.exchange import Exchange
+from freqtrade.freqtradebot import FreqtradeBot
+from freqtrade.persistence import Trade, init_db
+from freqtrade.resolvers import ExchangeResolver
+from freqtrade.worker import Worker
+from tests.conftest_trades import (mock_trade_1, mock_trade_2, mock_trade_3, mock_trade_4,
+                                   mock_trade_5, mock_trade_6)
+
+
+logging.getLogger('').setLevel(logging.INFO)
+
+
+# Do not mask numpy errors as warnings that no one read, raise the exсeption
+np.seterr(all='raise')
+
+
+def log_has(line, logs):
+    # caplog mocker returns log as a tuple: ('freqtrade.something', logging.WARNING, 'foobar')
+    # and we want to match line against foobar in the tuple
+    return reduce(lambda a, b: a or b,
+                  filter(lambda x: x[2] == line, logs.record_tuples),
+                  False)
+
+
+def log_has_re(line, logs):
+    return reduce(lambda a, b: a or b,
+                  filter(lambda x: re.match(line, x[2]), logs.record_tuples),
+                  False)
+
+
+def get_args(args):
+    return Arguments(args).get_parsed_arg()
+
+
+def patched_configuration_load_config_file(mocker, config) -> None:
+    mocker.patch(
+        'freqtrade.configuration.configuration.load_config_file',
+        lambda *args, **kwargs: config
+    )
+
+
+def patch_exchange(mocker, api_mock=None, id='bittrex', mock_markets=True) -> None:
+    mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock(return_value={}))
+    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
+    mocker.patch('freqtrade.exchange.Exchange.validate_ordertypes', MagicMock())
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency', MagicMock())
+    mocker.patch('freqtrade.exchange.Exchange.id', PropertyMock(return_value=id))
+    mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value=id.title()))
+    mocker.patch('freqtrade.exchange.Exchange.precisionMode', PropertyMock(return_value=2))
+    if mock_markets:
+        mocker.patch('freqtrade.exchange.Exchange.markets',
+                     PropertyMock(return_value=get_markets()))
+
+    if api_mock:
+        mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    else:
+        mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock())
+
+
+def get_patched_exchange(mocker, config, api_mock=None, id='bittrex',
+                         mock_markets=True) -> Exchange:
+    patch_exchange(mocker, api_mock, id, mock_markets)
+    config['exchange']['name'] = id
+    try:
+        exchange = ExchangeResolver.load_exchange(id, config)
+    except ImportError:
+        exchange = Exchange(config)
+    return exchange
+
+
+def patch_wallet(mocker, free=999.9) -> None:
+    mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(
+        return_value=free
+    ))
+
+
+def patch_whitelist(mocker, conf) -> None:
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot._refresh_active_whitelist',
+                 MagicMock(return_value=conf['exchange']['pair_whitelist']))
+
+
+def patch_edge(mocker) -> None:
+    # "ETH/BTC",
+    # "LTC/BTC",
+    # "XRP/BTC",
+    # "NEO/BTC"
+
+    mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
+        return_value={
+            'NEO/BTC': PairInfo(-0.20, 0.66, 3.71, 0.50, 1.71, 10, 25),
+            'LTC/BTC': PairInfo(-0.21, 0.66, 3.71, 0.50, 1.71, 11, 20),
+        }
+    ))
+    mocker.patch('freqtrade.edge.Edge.calculate', MagicMock(return_value=True))
+
+
+def get_patched_edge(mocker, config) -> Edge:
+    patch_edge(mocker)
+    edge = Edge(config)
+    return edge
+
+# Functions for recurrent object patching
+
+
+def patch_freqtradebot(mocker, config) -> None:
+    """
+    This function patch _init_modules() to not call dependencies
+    :param mocker: a Mocker object to apply patches
+    :param config: Config to pass to the bot
+    :return: None
+    """
+    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
+    init_db(config['db_url'])
+    patch_exchange(mocker)
+    mocker.patch('freqtrade.freqtradebot.RPCManager._init', MagicMock())
+    mocker.patch('freqtrade.freqtradebot.RPCManager.send_msg', MagicMock())
+    patch_whitelist(mocker, config)
+
+
+def get_patched_freqtradebot(mocker, config) -> FreqtradeBot:
+    """
+    This function patches _init_modules() to not call dependencies
+    :param mocker: a Mocker object to apply patches
+    :param config: Config to pass to the bot
+    :return: FreqtradeBot
+    """
+    patch_freqtradebot(mocker, config)
+    config['datadir'] = Path(config['datadir'])
+    return FreqtradeBot(config)
+
+
+def get_patched_worker(mocker, config) -> Worker:
+    """
+    This function patches _init_modules() to not call dependencies
+    :param mocker: a Mocker object to apply patches
+    :param config: Config to pass to the bot
+    :return: Worker
+    """
+    patch_freqtradebot(mocker, config)
+    return Worker(args=None, config=config)
+
+
+def patch_get_signal(freqtrade: FreqtradeBot, value=(True, False)) -> None:
+    """
+    :param mocker: mocker to patch IStrategy class
+    :param value: which value IStrategy.get_signal() must return
+    :return: None
+    """
+    freqtrade.strategy.get_signal = lambda e, s, x: value
+    freqtrade.exchange.refresh_latest_ohlcv = lambda p: None
+
+
+def create_mock_trades(fee):
+    """
+    Create some fake trades ...
+    """
+    # Simulate dry_run entries
+    trade = mock_trade_1(fee)
+    Trade.session.add(trade)
+
+    trade = mock_trade_2(fee)
+    Trade.session.add(trade)
+
+    trade = mock_trade_3(fee)
+    Trade.session.add(trade)
+
+    trade = mock_trade_4(fee)
+    Trade.session.add(trade)
+
+    trade = mock_trade_5(fee)
+    Trade.session.add(trade)
+
+    trade = mock_trade_6(fee)
+    Trade.session.add(trade)
+
+
+@pytest.fixture(autouse=True)
+def patch_coingekko(mocker) -> None:
+    """
+    Mocker to coingekko to speed up tests
+    :param mocker: mocker to patch coingekko class
+    :return: None
+    """
+
+    tickermock = MagicMock(return_value={'bitcoin': {'usd': 12345.0}, 'ethereum': {'usd': 12345.0}})
+    listmock = MagicMock(return_value=[{'id': 'bitcoin', 'name': 'Bitcoin', 'symbol': 'btc',
+                                        'website_slug': 'bitcoin'},
+                                       {'id': 'ethereum', 'name': 'Ethereum', 'symbol': 'eth',
+                                        'website_slug': 'ethereum'}
+                                       ])
+    mocker.patch.multiple(
+        'freqtrade.rpc.fiat_convert.CoinGeckoAPI',
+        get_price=tickermock,
+        get_coins_list=listmock,
+
+    )
+
+
+@pytest.fixture(scope='function')
+def init_persistence(default_conf):
+    init_db(default_conf['db_url'], default_conf['dry_run'])
+
+
+@pytest.fixture(scope="function")
+def default_conf(testdatadir):
+    """ Returns validated configuration suitable for most tests """
+    configuration = {
+        "max_open_trades": 1,
+        "stake_currency": "BTC",
+        "stake_amount": 0.001,
+        "fiat_display_currency": "USD",
+        "timeframe": '5m',
+        "dry_run": True,
+        "cancel_open_orders_on_exit": False,
+        "minimal_roi": {
+            "40": 0.0,
+            "30": 0.01,
+            "20": 0.02,
+            "0": 0.04
+        },
+        "stoploss": -0.10,
+        "unfilledtimeout": {
+            "buy": 10,
+            "sell": 30
+        },
+        "bid_strategy": {
+            "ask_last_balance": 0.0,
+            "use_order_book": False,
+            "order_book_top": 1,
+            "check_depth_of_market": {
+                "enabled": False,
+                "bids_to_ask_delta": 1
+            }
+        },
+        "ask_strategy": {
+            "use_order_book": False,
+            "order_book_min": 1,
+            "order_book_max": 1
+        },
+        "exchange": {
+            "name": "bittrex",
+            "enabled": True,
+            "key": "key",
+            "secret": "secret",
+            "pair_whitelist": [
+                "ETH/BTC",
+                "LTC/BTC",
+                "XRP/BTC",
+                "NEO/BTC"
+            ],
+            "pair_blacklist": [
+                "DOGE/BTC",
+                "HOT/BTC",
+            ]
+        },
+        "pairlists": [
+            {"method": "StaticPairList"}
+        ],
+        "telegram": {
+            "enabled": True,
+            "token": "token",
+            "chat_id": "0"
+        },
+        "datadir": str(testdatadir),
+        "initial_state": "running",
+        "db_url": "sqlite://",
+        "user_data_dir": Path("user_data"),
+        "verbosity": 3,
+        "strategy_path": str(Path(__file__).parent / "strategy" / "strats"),
+        "strategy": "DefaultStrategy",
+        "internals": {},
+    }
+    return configuration
+
+
+@pytest.fixture
+def update():
+    _update = Update(0)
+    _update.message = Message(0, datetime.utcnow(), Chat(0, 0))
+    return _update
+
+
+@pytest.fixture
+def fee():
+    return MagicMock(return_value=0.0025)
+
+
+@pytest.fixture
+def ticker():
+    return MagicMock(return_value={
+        'bid': 0.00001098,
+        'ask': 0.00001099,
+        'last': 0.00001098,
+    })
+
+
+@pytest.fixture
+def ticker_sell_up():
+    return MagicMock(return_value={
+        'bid': 0.00001172,
+        'ask': 0.00001173,
+        'last': 0.00001172,
+    })
+
+
+@pytest.fixture
+def ticker_sell_down():
+    return MagicMock(return_value={
+        'bid': 0.00001044,
+        'ask': 0.00001043,
+        'last': 0.00001044,
+    })
+
+
+@pytest.fixture
+def markets():
+    return get_markets()
+
+
+def get_markets():
+    return {
+        'ETH/BTC': {
+            'id': 'ethbtc',
+            'symbol': 'ETH/BTC',
+            'base': 'ETH',
+            'quote': 'BTC',
+            'active': True,
+            'precision': {
+                'price': 8,
+                'amount': 8,
+                'cost': 8,
+            },
+            'lot': 0.00000001,
+            'limits': {
+                'amount': {
+                    'min': 0.01,
+                    'max': 1000,
+                },
+                'price': 500000,
+                'cost': {
+                    'min': 0.0001,
+                    'max': 500000,
+                },
+            },
+            'info': {},
+        },
+        'TKN/BTC': {
+            'id': 'tknbtc',
+            'symbol': 'TKN/BTC',
+            'base': 'TKN',
+            'quote': 'BTC',
+            # According to ccxt, markets without active item set are also active
+            # 'active': True,
+            'precision': {
+                'price': 8,
+                'amount': 8,
+                'cost': 8,
+            },
+            'lot': 0.00000001,
+            'limits': {
+                'amount': {
+                    'min': 0.01,
+                    'max': 1000,
+                },
+                'price': 500000,
+                'cost': {
+                    'min': 0.0001,
+                    'max': 500000,
+                },
+            },
+            'info': {},
+        },
+        'BLK/BTC': {
+            'id': 'blkbtc',
+            'symbol': 'BLK/BTC',
+            'base': 'BLK',
+            'quote': 'BTC',
+            'active': True,
+            'precision': {
+                'price': 8,
+                'amount': 8,
+                'cost': 8,
+            },
+            'lot': 0.00000001,
+            'limits': {
+                'amount': {
+                    'min': 0.01,
+                    'max': 1000,
+                },
+                'price': 500000,
+                'cost': {
+                    'min': 0.0001,
+                    'max': 500000,
+                },
+            },
+            'info': {},
+        },
+        'LTC/BTC': {
+            'id': 'ltcbtc',
+            'symbol': 'LTC/BTC',
+            'base': 'LTC',
+            'quote': 'BTC',
+            'active': True,
+            'precision': {
+                'price': 8,
+                'amount': 8,
+                'cost': 8,
+            },
+            'lot': 0.00000001,
+            'limits': {
+                'amount': {
+                    'min': 0.01,
+                    'max': 1000,
+                },
+                'price': 500000,
+                'cost': {
+                    'min': 0.0001,
+                    'max': 500000,
+                },
+            },
+            'info': {},
+        },
+        'XRP/BTC': {
+            'id': 'xrpbtc',
+            'symbol': 'XRP/BTC',
+            'base': 'XRP',
+            'quote': 'BTC',
+            'active': True,
+            'precision': {
+                'price': 8,
+                'amount': 8,
+                'cost': 8,
+            },
+            'lot': 0.00000001,
+            'limits': {
+                'amount': {
+                    'min': 0.01,
+                    'max': 1000,
+                },
+                'price': 500000,
+                'cost': {
+                    'min': 0.0001,
+                    'max': 500000,
+                },
+            },
+            'info': {},
+        },
+        'NEO/BTC': {
+            'id': 'neobtc',
+            'symbol': 'NEO/BTC',
+            'base': 'NEO',
+            'quote': 'BTC',
+            'active': True,
+            'precision': {
+                'price': 8,
+                'amount': 8,
+                'cost': 8,
+            },
+            'lot': 0.00000001,
+            'limits': {
+                'amount': {
+                    'min': 0.01,
+                    'max': 1000,
+                },
+                'price': 500000,
+                'cost': {
+                    'min': 0.0001,
+                    'max': 500000,
+                },
+            },
+            'info': {},
+        },
+        'BTT/BTC': {
+            'id': 'BTTBTC',
+            'symbol': 'BTT/BTC',
+            'base': 'BTT',
+            'quote': 'BTC',
+            'active': False,
+            'precision': {
+                'base': 8,
+                'quote': 8,
+                'amount': 0,
+                'price': 8
+            },
+            'limits': {
+                'amount': {
+                    'min': 1.0,
+                    'max': 90000000.0
+                },
+                'price': {
+                    'min': None,
+                    'max': None
+                },
+                'cost': {
+                    'min': 0.0001,
+                    'max': None
+                }
+            },
+            'info': {},
+        },
+        'ETH/USDT': {
+            'id': 'USDT-ETH',
+            'symbol': 'ETH/USDT',
+            'base': 'ETH',
+            'quote': 'USDT',
+            'precision': {
+                'amount': 8,
+                'price': 8
+            },
+            'limits': {
+                'amount': {
+                    'min': 0.02214286,
+                    'max': None
+                },
+                'price': {
+                    'min': 1e-08,
+                    'max': None
+                }
+            },
+            'active': True,
+            'info': {},
+        },
+        'LTC/USDT': {
+            'id': 'USDT-LTC',
+            'symbol': 'LTC/USDT',
+            'base': 'LTC',
+            'quote': 'USDT',
+            'active': False,
+            'precision': {
+                'amount': 8,
+                'price': 8
+            },
+            'limits': {
+                'amount': {
+                    'min': 0.06646786,
+                    'max': None
+                },
+                'price': {
+                    'min': 1e-08,
+                    'max': None
+                }
+            },
+            'info': {},
+        },
+        'LTC/USD': {
+            'id': 'USD-LTC',
+            'symbol': 'LTC/USD',
+            'base': 'LTC',
+            'quote': 'USD',
+            'active': True,
+            'precision': {
+                'amount': 8,
+                'price': 8
+            },
+            'limits': {
+                'amount': {
+                    'min': 0.06646786,
+                    'max': None
+                },
+                'price': {
+                    'min': 1e-08,
+                    'max': None
+                }
+            },
+            'info': {},
+        },
+        'XLTCUSDT': {
+            'id': 'xLTCUSDT',
+            'symbol': 'XLTCUSDT',
+            'base': 'LTC',
+            'quote': 'USDT',
+            'active': True,
+            'precision': {
+                'amount': 8,
+                'price': 8
+            },
+            'limits': {
+                'amount': {
+                    'min': 0.06646786,
+                    'max': None
+                },
+                'price': {
+                    'min': 1e-08,
+                    'max': None
+                }
+            },
+            'info': {},
+        },
+        'LTC/ETH': {
+            'id': 'LTCETH',
+            'symbol': 'LTC/ETH',
+            'base': 'LTC',
+            'quote': 'ETH',
+            'active': True,
+            'precision': {
+                'base': 8,
+                'quote': 8,
+                'amount': 3,
+                'price': 5
+            },
+            'limits': {
+                'amount': {
+                    'min': 0.001,
+                    'max': 10000000.0
+                },
+                'price': {
+                    'min': 1e-05,
+                    'max': 1000.0
+                },
+                'cost': {
+                    'min': 0.01,
+                    'max': None
+                }
+            },
+        },
+    }
+
+
+@pytest.fixture
+def shitcoinmarkets(markets):
+    """
+    Fixture with shitcoin markets - used to test filters in pairlists
+    """
+    shitmarkets = deepcopy(markets)
+    shitmarkets.update({
+        'HOT/BTC': {
+            'id': 'HOTBTC',
+            'symbol': 'HOT/BTC',
+            'base': 'HOT',
+            'quote': 'BTC',
+            'active': True,
+            'precision': {
+                'base': 8,
+                'quote': 8,
+                'amount': 0,
+                'price': 8
+            },
+            'limits': {
+                'amount': {
+                    'min': 1.0,
+                    'max': 90000000.0
+                },
+                'price': {
+                    'min': None,
+                    'max': None
+                },
+                'cost': {
+                    'min': 0.001,
+                    'max': None
+                }
+            },
+            'info': {},
+        },
+        'FUEL/BTC': {
+            'id': 'FUELBTC',
+            'symbol': 'FUEL/BTC',
+            'base': 'FUEL',
+            'quote': 'BTC',
+            'active': True,
+            'precision': {
+                'base': 8,
+                'quote': 8,
+                'amount': 0,
+                'price': 8
+            },
+            'limits': {
+                'amount': {
+                    'min': 1.0,
+                    'max': 90000000.0
+                },
+                'price': {
+                    'min': 1e-08,
+                    'max': 1000.0
+                },
+                'cost': {
+                    'min': 0.001,
+                    'max': None
+                }
+            },
+            'info': {},
+        },
+        'NANO/USDT': {
+            "percentage": True,
+            "tierBased": False,
+            "taker": 0.001,
+            "maker": 0.001,
+            "precision": {
+                "base": 8,
+                "quote": 8,
+                "amount": 2,
+                "price": 4
+            },
+            "limits": {
+            },
+            "id": "NANOUSDT",
+            "symbol": "NANO/USDT",
+            "base": "NANO",
+            "quote": "USDT",
+            "baseId": "NANO",
+            "quoteId": "USDT",
+            "info": {},
+            "type": "spot",
+            "spot": True,
+            "future": False,
+            "active": True
+        },
+        'ADAHALF/USDT': {
+            "percentage": True,
+            "tierBased": False,
+            "taker": 0.001,
+            "maker": 0.001,
+            "precision": {
+                "base": 8,
+                "quote": 8,
+                "amount": 2,
+                "price": 4
+            },
+            "limits": {
+            },
+            "id": "ADAHALFUSDT",
+            "symbol": "ADAHALF/USDT",
+            "base": "ADAHALF",
+            "quote": "USDT",
+            "baseId": "ADAHALF",
+            "quoteId": "USDT",
+            "info": {},
+            "type": "spot",
+            "spot": True,
+            "future": False,
+            "active": True
+        },
+        'ADADOUBLE/USDT': {
+            "percentage": True,
+            "tierBased": False,
+            "taker": 0.001,
+            "maker": 0.001,
+            "precision": {
+                "base": 8,
+                "quote": 8,
+                "amount": 2,
+                "price": 4
+            },
+            "limits": {
+            },
+            "id": "ADADOUBLEUSDT",
+            "symbol": "ADADOUBLE/USDT",
+            "base": "ADADOUBLE",
+            "quote": "USDT",
+            "baseId": "ADADOUBLE",
+            "quoteId": "USDT",
+            "info": {},
+            "type": "spot",
+            "spot": True,
+            "future": False,
+            "active": True
+        },
+        })
+    return shitmarkets
+
+
+@pytest.fixture
+def markets_empty():
+    return MagicMock(return_value=[])
+
+
+@pytest.fixture(scope='function')
+def limit_buy_order_open():
+    return {
+        'id': 'mocked_limit_buy',
+        'type': 'limit',
+        'side': 'buy',
+        'symbol': 'mocked',
+        'datetime': arrow.utcnow().isoformat(),
+        'timestamp': arrow.utcnow().int_timestamp,
+        'price': 0.00001099,
+        'amount': 90.99181073,
+        'filled': 0.0,
+        'cost': 0.0009999,
+        'remaining': 90.99181073,
+        'status': 'open'
+    }
+
+
+@pytest.fixture(scope='function')
+def limit_buy_order(limit_buy_order_open):
+    order = deepcopy(limit_buy_order_open)
+    order['status'] = 'closed'
+    order['filled'] = order['amount']
+    order['remaining'] = 0.0
+    return order
+
+
+@pytest.fixture(scope='function')
+def market_buy_order():
+    return {
+        'id': 'mocked_market_buy',
+        'type': 'market',
+        'side': 'buy',
+        'symbol': 'mocked',
+        'datetime': arrow.utcnow().isoformat(),
+        'price': 0.00004099,
+        'amount': 91.99181073,
+        'filled': 91.99181073,
+        'remaining': 0.0,
+        'status': 'closed'
+    }
+
+
+@pytest.fixture
+def market_sell_order():
+    return {
+        'id': 'mocked_limit_sell',
+        'type': 'market',
+        'side': 'sell',
+        'symbol': 'mocked',
+        'datetime': arrow.utcnow().isoformat(),
+        'price': 0.00004173,
+        'amount': 91.99181073,
+        'filled': 91.99181073,
+        'remaining': 0.0,
+        'status': 'closed'
+    }
+
+
+@pytest.fixture
+def limit_buy_order_old():
+    return {
+        'id': 'mocked_limit_buy_old',
+        'type': 'limit',
+        'side': 'buy',
+        'symbol': 'mocked',
+        'datetime': str(arrow.utcnow().shift(minutes=-601).datetime),
+        'price': 0.00001099,
+        'amount': 90.99181073,
+        'filled': 0.0,
+        'remaining': 90.99181073,
+        'status': 'open'
+    }
+
+
+@pytest.fixture
+def limit_sell_order_old():
+    return {
+        'id': 'mocked_limit_sell_old',
+        'type': 'limit',
+        'side': 'sell',
+        'symbol': 'ETH/BTC',
+        'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
+        'price': 0.00001099,
+        'amount': 90.99181073,
+        'filled': 0.0,
+        'remaining': 90.99181073,
+        'status': 'open'
+    }
+
+
+@pytest.fixture
+def limit_buy_order_old_partial():
+    return {
+        'id': 'mocked_limit_buy_old_partial',
+        'type': 'limit',
+        'side': 'buy',
+        'symbol': 'ETH/BTC',
+        'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
+        'price': 0.00001099,
+        'amount': 90.99181073,
+        'filled': 23.0,
+        'remaining': 67.99181073,
+        'status': 'open'
+    }
+
+
+@pytest.fixture
+def limit_buy_order_old_partial_canceled(limit_buy_order_old_partial):
+    res = deepcopy(limit_buy_order_old_partial)
+    res['status'] = 'canceled'
+    res['fee'] = {'cost': 0.023, 'currency': 'ETH'}
+    return res
+
+
+@pytest.fixture(scope='function')
+def limit_buy_order_canceled_empty(request):
+    # Indirect fixture
+    # Documentation:
+    # https://docs.pytest.org/en/latest/example/parametrize.html#apply-indirect-on-particular-arguments
+
+    exchange_name = request.param
+    if exchange_name == 'ftx':
+        return {
+            'info': {},
+            'id': '1234512345',
+            'clientOrderId': None,
+            'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
+            'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
+            'lastTradeTimestamp': None,
+            'symbol': 'LTC/USDT',
+            'type': 'limit',
+            'side': 'buy',
+            'price': 34.3225,
+            'amount': 0.55,
+            'cost': 0.0,
+            'average': None,
+            'filled': 0.0,
+            'remaining': 0.0,
+            'status': 'closed',
+            'fee': None,
+            'trades': None
+        }
+    elif exchange_name == 'kraken':
+        return {
+            'info': {},
+            'id': 'AZNPFF-4AC4N-7MKTAT',
+            'clientOrderId': None,
+            'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
+            'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
+            'lastTradeTimestamp': None,
+            'status': 'canceled',
+            'symbol': 'LTC/USDT',
+            'type': 'limit',
+            'side': 'buy',
+            'price': 34.3225,
+            'cost': 0.0,
+            'amount': 0.55,
+            'filled': 0.0,
+            'average': 0.0,
+            'remaining': 0.55,
+            'fee': {'cost': 0.0, 'rate': None, 'currency': 'USDT'},
+            'trades': []
+        }
+    elif exchange_name == 'binance':
+        return {
+            'info': {},
+            'id': '1234512345',
+            'clientOrderId': 'alb1234123',
+            'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
+            'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
+            'lastTradeTimestamp': None,
+            'symbol': 'LTC/USDT',
+            'type': 'limit',
+            'side': 'buy',
+            'price': 0.016804,
+            'amount': 0.55,
+            'cost': 0.0,
+            'average': None,
+            'filled': 0.0,
+            'remaining': 0.55,
+            'status': 'canceled',
+            'fee': None,
+            'trades': None
+        }
+    else:
+        return {
+            'info': {},
+            'id': '1234512345',
+            'clientOrderId': 'alb1234123',
+            'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
+            'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
+            'lastTradeTimestamp': None,
+            'symbol': 'LTC/USDT',
+            'type': 'limit',
+            'side': 'buy',
+            'price': 0.016804,
+            'amount': 0.55,
+            'cost': 0.0,
+            'average': None,
+            'filled': 0.0,
+            'remaining': 0.55,
+            'status': 'canceled',
+            'fee': None,
+            'trades': None
+        }
+
+
+@pytest.fixture
+def limit_sell_order_open():
+    return {
+        'id': 'mocked_limit_sell',
+        'type': 'limit',
+        'side': 'sell',
+        'pair': 'mocked',
+        'datetime': arrow.utcnow().isoformat(),
+        'timestamp': arrow.utcnow().int_timestamp,
+        'price': 0.00001173,
+        'amount': 90.99181073,
+        'filled': 0.0,
+        'remaining': 90.99181073,
+        'status': 'open'
+    }
+
+
+@pytest.fixture
+def limit_sell_order(limit_sell_order_open):
+    order = deepcopy(limit_sell_order_open)
+    order['remaining'] = 0.0
+    order['filled'] = order['amount']
+    order['status'] = 'closed'
+    return order
+
+
+@pytest.fixture
+def order_book_l2():
+    return MagicMock(return_value={
+        'bids': [
+            [0.043936, 10.442],
+            [0.043935, 31.865],
+            [0.043933, 11.212],
+            [0.043928, 0.088],
+            [0.043925, 10.0],
+            [0.043921, 10.0],
+            [0.04392, 37.64],
+            [0.043899, 0.066],
+            [0.043885, 0.676],
+            [0.04387, 22.758]
+        ],
+        'asks': [
+            [0.043949, 0.346],
+            [0.04395, 0.608],
+            [0.043951, 3.948],
+            [0.043954, 0.288],
+            [0.043958, 9.277],
+            [0.043995, 1.566],
+            [0.044, 0.588],
+            [0.044002, 0.992],
+            [0.044003, 0.095],
+            [0.04402, 37.64]
+        ],
+        'timestamp': None,
+        'datetime': None,
+        'nonce': 288004540
+    })
+
+
+@pytest.fixture
+def ohlcv_history_list():
+    return [
+        [
+            1511686200000,  # unix timestamp ms
+            8.794e-05,      # open
+            8.948e-05,      # high
+            8.794e-05,      # low
+            8.88e-05,       # close
+            0.0877869,      # volume (in quote currency)
+        ],
+        [
+            1511686500000,
+            8.88e-05,
+            8.942e-05,
+            8.88e-05,
+            8.893e-05,
+            0.05874751,
+        ],
+        [
+            1511686800000,
+            8.891e-05,
+            8.893e-05,
+            8.875e-05,
+            8.877e-05,
+            0.7039405
+        ]
+    ]
+
+
+@pytest.fixture
+def ohlcv_history(ohlcv_history_list):
+    return ohlcv_to_dataframe(ohlcv_history_list, "5m", pair="UNITTEST/BTC",
+                              fill_missing=True)
+
+
+@pytest.fixture
+def tickers():
+    return MagicMock(return_value={
+        'ETH/BTC': {
+            'symbol': 'ETH/BTC',
+            'timestamp': 1522014806207,
+            'datetime': '2018-03-25T21:53:26.207Z',
+            'high': 0.061697,
+            'low': 0.060531,
+            'bid': 0.061588,
+            'bidVolume': 3.321,
+            'ask': 0.061655,
+            'askVolume': 0.212,
+            'vwap': 0.06105296,
+            'open': 0.060809,
+            'close': 0.060761,
+            'first': None,
+            'last': 0.061588,
+            'change': 1.281,
+            'percentage': None,
+            'average': None,
+            'baseVolume': 111649.001,
+            'quoteVolume': 6816.50176926,
+            'info': {}
+        },
+        'TKN/BTC': {
+            'symbol': 'TKN/BTC',
+            'timestamp': 1522014806169,
+            'datetime': '2018-03-25T21:53:26.169Z',
+            'high': 0.01885,
+            'low': 0.018497,
+            'bid': 0.018799,
+            'bidVolume': 8.38,
+            'ask': 0.018802,
+            'askVolume': 15.0,
+            'vwap': 0.01869197,
+            'open': 0.018585,
+            'close': 0.018573,
+            'last': 0.018799,
+            'baseVolume': 81058.66,
+            'quoteVolume': 2247.48374509,
+        },
+        'BLK/BTC': {
+            'symbol': 'BLK/BTC',
+            'timestamp': 1522014806072,
+            'datetime': '2018-03-25T21:53:26.720Z',
+            'high': 0.007745,
+            'low': 0.007512,
+            'bid': 0.007729,
+            'bidVolume': 0.01,
+            'ask': 0.007743,
+            'askVolume': 21.37,
+            'vwap': 0.00761466,
+            'open': 0.007653,
+            'close': 0.007652,
+            'first': None,
+            'last': 0.007743,
+            'change': 1.176,
+            'percentage': None,
+            'average': None,
+            'baseVolume': 295152.26,
+            'quoteVolume': 1515.14631229,
+            'info': {}
+        },
+        'LTC/BTC': {
+            'symbol': 'LTC/BTC',
+            'timestamp': 1523787258992,
+            'datetime': '2018-04-15T10:14:19.992Z',
+            'high': 0.015978,
+            'low': 0.0157,
+            'bid': 0.015954,
+            'bidVolume': 12.83,
+            'ask': 0.015957,
+            'askVolume': 0.49,
+            'vwap': 0.01581636,
+            'open': 0.015823,
+            'close': 0.01582,
+            'first': None,
+            'last': 0.015951,
+            'change': 0.809,
+            'percentage': None,
+            'average': None,
+            'baseVolume': 88620.68,
+            'quoteVolume': 1401.65697943,
+            'info': {}
+        },
+        'BTT/BTC': {
+            'symbol': 'BTT/BTC',
+            'timestamp': 1550936557206,
+            'datetime': '2019-02-23T15:42:37.206Z',
+            'high': 0.00000026,
+            'low': 0.00000024,
+            'bid': 0.00000024,
+            'bidVolume': 2446894197.0,
+            'ask': 0.00000025,
+            'askVolume': 2447913837.0,
+            'vwap': 0.00000025,
+            'open': 0.00000026,
+            'close': 0.00000024,
+            'last': 0.00000024,
+            'previousClose': 0.00000026,
+            'change': -0.00000002,
+            'percentage': -7.692,
+            'average': None,
+            'baseVolume': 4886464537.0,
+            'quoteVolume': 1215.14489611,
+            'info': {}
+        },
+        'HOT/BTC': {
+            'symbol': 'HOT/BTC',
+            'timestamp': 1572273518661,
+            'datetime': '2019-10-28T14:38:38.661Z',
+            'high': 0.00000011,
+            'low': 0.00000009,
+            'bid': 0.0000001,
+            'bidVolume': 1476027288.0,
+            'ask': 0.00000011,
+            'askVolume': 820153831.0,
+            'vwap': 0.0000001,
+            'open': 0.00000009,
+            'close': 0.00000011,
+            'last': 0.00000011,
+            'previousClose': 0.00000009,
+            'change': 0.00000002,
+            'percentage': 22.222,
+            'average': None,
+            'baseVolume': 1442290324.0,
+            'quoteVolume': 143.78311994,
+            'info': {}
+        },
+        'FUEL/BTC': {
+            'symbol': 'FUEL/BTC',
+            'timestamp': 1572340250771,
+            'datetime': '2019-10-29T09:10:50.771Z',
+            'high': 0.00000040,
+            'low': 0.00000035,
+            'bid': 0.00000036,
+            'bidVolume': 8932318.0,
+            'ask': 0.00000037,
+            'askVolume': 10140774.0,
+            'vwap': 0.00000037,
+            'open': 0.00000039,
+            'close': 0.00000037,
+            'last': 0.00000037,
+            'previousClose': 0.00000038,
+            'change': -0.00000002,
+            'percentage': -5.128,
+            'average': None,
+            'baseVolume': 168927742.0,
+            'quoteVolume': 62.68220262,
+            'info': {}
+        },
+        'BTC/USDT': {
+            'symbol': 'BTC/USDT',
+            'timestamp': 1573758371399,
+            'datetime': '2019-11-14T19:06:11.399Z',
+            'high': 8800.0,
+            'low': 8582.6,
+            'bid': 8648.16,
+            'bidVolume': 0.238771,
+            'ask': 8648.72,
+            'askVolume': 0.016253,
+            'vwap': 8683.13647806,
+            'open': 8759.7,
+            'close': 8648.72,
+            'last': 8648.72,
+            'previousClose': 8759.67,
+            'change': -110.98,
+            'percentage': -1.267,
+            'average': None,
+            'baseVolume': 35025.943355,
+            'quoteVolume': 304135046.4242901,
+            'info': {}
+        },
+        'ETH/USDT': {
+            'symbol': 'ETH/USDT',
+            'timestamp': 1522014804118,
+            'datetime': '2018-03-25T21:53:24.118Z',
+            'high': 530.88,
+            'low': 512.0,
+            'bid': 529.73,
+            'bidVolume': 0.2,
+            'ask': 530.21,
+            'askVolume': 0.2464,
+            'vwap': 521.02438405,
+            'open': 527.27,
+            'close': 528.42,
+            'first': None,
+            'last': 530.21,
+            'change': 0.558,
+            'percentage': None,
+            'average': None,
+            'baseVolume': 72300.0659,
+            'quoteVolume': 37670097.3022171,
+            'info': {}
+        },
+        'TKN/USDT': {
+            'symbol': 'TKN/USDT',
+            'timestamp': 1522014806198,
+            'datetime': '2018-03-25T21:53:26.198Z',
+            'high': 8718.0,
+            'low': 8365.77,
+            'bid': 8603.64,
+            'bidVolume': 0.15846,
+            'ask': 8603.67,
+            'askVolume': 0.069147,
+            'vwap': 8536.35621697,
+            'open': 8680.0,
+            'close': 8680.0,
+            'first': None,
+            'last': 8603.67,
+            'change': -0.879,
+            'percentage': None,
+            'average': None,
+            'baseVolume': 30414.604298,
+            'quoteVolume': 259629896.48584127,
+            'info': {}
+        },
+        'BLK/USDT': {
+            'symbol': 'BLK/USDT',
+            'timestamp': 1522014806145,
+            'datetime': '2018-03-25T21:53:26.145Z',
+            'high': 66.95,
+            'low': 63.38,
+            'bid': 66.473,
+            'bidVolume': 4.968,
+            'ask': 66.54,
+            'askVolume': 2.704,
+            'vwap': 65.0526901,
+            'open': 66.43,
+            'close': 66.383,
+            'first': None,
+            'last': 66.5,
+            'change': 0.105,
+            'percentage': None,
+            'average': None,
+            'baseVolume': 294106.204,
+            'quoteVolume': 19132399.743954,
+            'info': {}
+        },
+        'LTC/USDT': {
+            'symbol': 'LTC/USDT',
+            'timestamp': 1523787257812,
+            'datetime': '2018-04-15T10:14:18.812Z',
+            'high': 129.94,
+            'low': 124.0,
+            'bid': 129.28,
+            'bidVolume': 0.03201,
+            'ask': 129.52,
+            'askVolume': 0.14529,
+            'vwap': 126.92838682,
+            'open': 127.0,
+            'close': 127.1,
+            'first': None,
+            'last': 129.28,
+            'change': 1.795,
+            'percentage': None,
+            'average': None,
+            'baseVolume': 59698.79897,
+            'quoteVolume': 29132399.743954,
+            'info': {}
+        },
+        'XRP/BTC': {
+            'symbol': 'XRP/BTC',
+            'timestamp': 1573758257534,
+            'datetime': '2019-11-14T19:04:17.534Z',
+            'high': 3.126e-05,
+            'low': 3.061e-05,
+            'bid': 3.093e-05,
+            'bidVolume': 27901.0,
+            'ask': 3.095e-05,
+            'askVolume': 10551.0,
+            'vwap': 3.091e-05,
+            'open': 3.119e-05,
+            'close': 3.094e-05,
+            'last': 3.094e-05,
+            'previousClose': 3.117e-05,
+            'change': -2.5e-07,
+            'percentage': -0.802,
+            'average': None,
+            'baseVolume': 37334921.0,
+            'quoteVolume': 1154.19266394,
+            'info': {}
+        },
+        "NANO/USDT": {
+            "symbol": "NANO/USDT",
+            "timestamp": 1580469388244,
+            "datetime": "2020-01-31T11:16:28.244Z",
+            "high": 0.7519,
+            "low": 0.7154,
+            "bid": 0.7305,
+            "bidVolume": 300.3,
+            "ask": 0.7342,
+            "askVolume": 15.14,
+            "vwap": 0.73645591,
+            "open": 0.7154,
+            "close": 0.7342,
+            "last": 0.7342,
+            "previousClose": 0.7189,
+            "change": 0.0188,
+            "percentage": 2.628,
+            "average": None,
+            "baseVolume": 439472.44,
+            "quoteVolume": 323652.075405,
+            "info": {}
+        },
+        # Example of leveraged pair with incomplete info
+        "ADAHALF/USDT": {
+            "symbol": "ADAHALF/USDT",
+            "timestamp": 1580469388244,
+            "datetime": "2020-01-31T11:16:28.244Z",
+            "high": None,
+            "low": None,
+            "bid": 0.7305,
+            "bidVolume": None,
+            "ask": 0.7342,
+            "askVolume": None,
+            "vwap": None,
+            "open": None,
+            "close": None,
+            "last": None,
+            "previousClose": None,
+            "change": None,
+            "percentage": 2.628,
+            "average": None,
+            "baseVolume": 0.0,
+            "quoteVolume": 0.0,
+            "info": {}
+        },
+        "ADADOUBLE/USDT": {
+            "symbol": "ADADOUBLE/USDT",
+            "timestamp": 1580469388244,
+            "datetime": "2020-01-31T11:16:28.244Z",
+            "high": None,
+            "low": None,
+            "bid": 0.7305,
+            "bidVolume": None,
+            "ask": 0.7342,
+            "askVolume": None,
+            "vwap": None,
+            "open": None,
+            "close": None,
+            "last": 0,
+            "previousClose": None,
+            "change": None,
+            "percentage": 2.628,
+            "average": None,
+            "baseVolume": 0.0,
+            "quoteVolume": 0.0,
+            "info": {}
+        },
+    })
+
+
+@pytest.fixture
+def result(testdatadir):
+    with (testdatadir / 'UNITTEST_BTC-1m.json').open('r') as data_file:
+        return ohlcv_to_dataframe(json.load(data_file), '1m', pair="UNITTEST/BTC",
+                                  fill_missing=True)
+
+
+@pytest.fixture(scope="function")
+def trades_for_order():
+    return [{'info': {'id': 34567,
+                      'orderId': 123456,
+                      'price': '0.24544100',
+                      'qty': '8.00000000',
+                      'commission': '0.00800000',
+                      'commissionAsset': 'LTC',
+                      'time': 1521663363189,
+                      'isBuyer': True,
+                      'isMaker': False,
+                      'isBestMatch': True},
+             'timestamp': 1521663363189,
+             'datetime': '2018-03-21T20:16:03.189Z',
+             'symbol': 'LTC/ETH',
+             'id': '34567',
+             'order': '123456',
+             'type': None,
+             'side': 'buy',
+             'price': 0.245441,
+             'cost': 1.963528,
+             'amount': 8.0,
+             'fee': {'cost': 0.008, 'currency': 'LTC'}}]
+
+
+@pytest.fixture(scope="function")
+def trades_history():
+    return [[1565798389463, '126181329', None, 'buy', 0.019627, 0.04, 0.00078508],
+            [1565798399629, '126181330', None, 'buy', 0.019627, 0.244, 0.004788987999999999],
+            [1565798399752, '126181331', None, 'sell', 0.019626, 0.011, 0.00021588599999999999],
+            [1565798399862, '126181332', None, 'sell', 0.019626, 0.011, 0.00021588599999999999],
+            [1565798399872, '126181333', None, 'sell', 0.019626, 0.011, 0.00021588599999999999]]
+
+
+@pytest.fixture(scope="function")
+def fetch_trades_result():
+    return [{'info': {'a': 126181329,
+                      'p': '0.01962700',
+                      'q': '0.04000000',
+                      'f': 138604155,
+                      'l': 138604155,
+                      'T': 1565798399463,
+                      'm': False,
+                      'M': True},
+             'timestamp': 1565798399463,
+             'datetime': '2019-08-14T15:59:59.463Z',
+             'symbol': 'ETH/BTC',
+             'id': '126181329',
+             'order': None,
+             'type': None,
+             'takerOrMaker': None,
+             'side': 'buy',
+             'price': 0.019627,
+             'amount': 0.04,
+             'cost': 0.00078508,
+             'fee': None},
+            {'info': {'a': 126181330,
+                      'p': '0.01962700',
+                      'q': '0.24400000',
+                      'f': 138604156,
+                      'l': 138604156,
+                      'T': 1565798399629,
+                      'm': False,
+                      'M': True},
+             'timestamp': 1565798399629,
+             'datetime': '2019-08-14T15:59:59.629Z',
+             'symbol': 'ETH/BTC',
+             'id': '126181330',
+             'order': None,
+             'type': None,
+             'takerOrMaker': None,
+             'side': 'buy',
+             'price': 0.019627,
+             'amount': 0.244,
+             'cost': 0.004788987999999999,
+             'fee': None},
+            {'info': {'a': 126181331,
+                      'p': '0.01962600',
+                      'q': '0.01100000',
+                      'f': 138604157,
+                      'l': 138604157,
+                      'T': 1565798399752,
+                      'm': True,
+                      'M': True},
+             'timestamp': 1565798399752,
+             'datetime': '2019-08-14T15:59:59.752Z',
+             'symbol': 'ETH/BTC',
+             'id': '126181331',
+             'order': None,
+             'type': None,
+             'takerOrMaker': None,
+             'side': 'sell',
+             'price': 0.019626,
+             'amount': 0.011,
+             'cost': 0.00021588599999999999,
+             'fee': None},
+            {'info': {'a': 126181332,
+                      'p': '0.01962600',
+                      'q': '0.01100000',
+                      'f': 138604158,
+                      'l': 138604158,
+                      'T': 1565798399862,
+                      'm': True,
+                      'M': True},
+             'timestamp': 1565798399862,
+             'datetime': '2019-08-14T15:59:59.862Z',
+             'symbol': 'ETH/BTC',
+             'id': '126181332',
+             'order': None,
+             'type': None,
+             'takerOrMaker': None,
+             'side': 'sell',
+             'price': 0.019626,
+             'amount': 0.011,
+             'cost': 0.00021588599999999999,
+             'fee': None},
+            {'info': {'a': 126181333,
+                      'p': '0.01952600',
+                      'q': '0.01200000',
+                      'f': 138604158,
+                      'l': 138604158,
+                      'T': 1565798399872,
+                      'm': True,
+                      'M': True},
+             'timestamp': 1565798399872,
+             'datetime': '2019-08-14T15:59:59.872Z',
+             'symbol': 'ETH/BTC',
+             'id': '126181333',
+             'order': None,
+             'type': None,
+             'takerOrMaker': None,
+             'side': 'sell',
+             'price': 0.019626,
+             'amount': 0.011,
+             'cost': 0.00021588599999999999,
+             'fee': None}]
+
+
+@pytest.fixture(scope="function")
+def trades_for_order2():
+    return [{'info': {'id': 34567,
+                      'orderId': 123456,
+                      'price': '0.24544100',
+                      'qty': '8.00000000',
+                      'commission': '0.00800000',
+                      'commissionAsset': 'LTC',
+                      'time': 1521663363189,
+                      'isBuyer': True,
+                      'isMaker': False,
+                      'isBestMatch': True},
+             'timestamp': 1521663363189,
+             'datetime': '2018-03-21T20:16:03.189Z',
+             'symbol': 'LTC/ETH',
+             'id': '34567',
+             'order': '123456',
+             'type': None,
+             'side': 'buy',
+             'price': 0.245441,
+             'cost': 1.963528,
+             'amount': 4.0,
+             'fee': {'cost': 0.004, 'currency': 'LTC'}},
+            {'info': {'id': 34567,
+                      'orderId': 123456,
+                      'price': '0.24544100',
+                      'qty': '8.00000000',
+                      'commission': '0.00800000',
+                      'commissionAsset': 'LTC',
+                      'time': 1521663363189,
+                      'isBuyer': True,
+                      'isMaker': False,
+                      'isBestMatch': True},
+             'timestamp': 1521663363189,
+             'datetime': '2018-03-21T20:16:03.189Z',
+             'symbol': 'LTC/ETH',
+             'id': '34567',
+             'order': '123456',
+             'type': None,
+             'side': 'buy',
+             'price': 0.245441,
+             'cost': 1.963528,
+             'amount': 4.0,
+             'fee': {'cost': 0.004, 'currency': 'LTC'}}]
+
+
+@pytest.fixture
+def buy_order_fee():
+    return {
+        'id': 'mocked_limit_buy_old',
+        'type': 'limit',
+        'side': 'buy',
+        'symbol': 'mocked',
+        'datetime': str(arrow.utcnow().shift(minutes=-601).datetime),
+        'price': 0.245441,
+        'amount': 8.0,
+        'cost': 1.963528,
+        'remaining': 90.99181073,
+        'status': 'closed',
+        'fee': None
+    }
+
+
+@pytest.fixture(scope="function")
+def edge_conf(default_conf):
+    conf = deepcopy(default_conf)
+    conf['max_open_trades'] = -1
+    conf['tradable_balance_ratio'] = 0.5
+    conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
+    conf['edge'] = {
+        "enabled": True,
+        "process_throttle_secs": 1800,
+        "calculate_since_number_of_days": 14,
+        "allowed_risk": 0.01,
+        "stoploss_range_min": -0.01,
+        "stoploss_range_max": -0.1,
+        "stoploss_range_step": -0.01,
+        "maximum_winrate": 0.80,
+        "minimum_expectancy": 0.20,
+        "min_trade_number": 15,
+        "max_trade_duration_minute": 1440,
+        "remove_pumps": False
+    }
+
+    return conf
+
+
+@pytest.fixture
+def rpc_balance():
+    return {
+        'BTC': {
+            'total': 12.0,
+            'free': 12.0,
+            'used': 0.0
+        },
+        'ETH': {
+            'total': 0.0,
+            'free': 0.0,
+            'used': 0.0
+        },
+        'USDT': {
+            'total': 10000.0,
+            'free': 10000.0,
+            'used': 0.0
+        },
+        'LTC': {
+            'total': 10.0,
+            'free': 10.0,
+            'used': 0.0
+        },
+        'XRP': {
+            'total': 0.1,
+            'free': 0.01,
+            'used': 0.0
+            },
+        'EUR': {
+            'total': 10.0,
+            'free': 10.0,
+            'used': 0.0
+        },
+    }
+
+
+@pytest.fixture
+def testdatadir() -> Path:
+    """Return the path where testdata files are stored"""
+    return (Path(__file__).parent / "testdata").resolve()
+
+
+@pytest.fixture(scope="function")
+def import_fails() -> None:
+    # Source of this test-method:
+    # https://stackoverflow.com/questions/2481511/mocking-importerror-in-python
+    import builtins
+    realimport = builtins.__import__
+
+    def mockedimport(name, *args, **kwargs):
+        if name in ["filelock", 'systemd.journal']:
+            raise ImportError(f"No module named '{name}'")
+        return realimport(name, *args, **kwargs)
+
+    builtins.__import__ = mockedimport
+
+    # Run test - then cleanup
+    yield
+
+    # restore previous importfunction
+    builtins.__import__ = realimport
+
+
+@pytest.fixture(scope="function")
+def open_trade():
+    return Trade(
+        pair='ETH/BTC',
+        open_rate=0.00001099,
+        exchange='bittrex',
+        open_order_id='123456789',
+        amount=90.99181073,
+        fee_open=0.0,
+        fee_close=0.0,
+        stake_amount=1,
+        open_date=arrow.utcnow().shift(minutes=-601).datetime,
+        is_open=True
+    )
+
+
+@pytest.fixture
+def hyperopt_results():
+    return [
+        {
+            'loss': 0.4366182531161519,
+            'params_dict': {
+                'mfi-value': 15, 'fastd-value': 20, 'adx-value': 25, 'rsi-value': 28, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 88, 'sell-fastd-value': 97, 'sell-adx-value': 51, 'sell-rsi-value': 67, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper', 'roi_t1': 1190, 'roi_t2': 541, 'roi_t3': 408, 'roi_p1': 0.026035863879169705, 'roi_p2': 0.12508730043628782, 'roi_p3': 0.27766427921605896, 'stoploss': -0.2562930402099556},  # noqa: E501
+            'params_details': {'buy': {'mfi-value': 15, 'fastd-value': 20, 'adx-value': 25, 'rsi-value': 28, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 88, 'sell-fastd-value': 97, 'sell-adx-value': 51, 'sell-rsi-value': 67, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper'}, 'roi': {0: 0.4287874435315165, 408: 0.15112316431545753, 949: 0.026035863879169705, 2139: 0}, 'stoploss': {'stoploss': -0.2562930402099556}},  # noqa: E501
+            'results_metrics': {'trade_count': 2, 'avg_profit': -1.254995, 'total_profit': -0.00125625, 'profit': -2.50999, 'duration': 3930.0},  # noqa: E501
+            'results_explanation': '     2 trades. Avg profit  -1.25%. Total profit -0.00125625 BTC (  -2.51Σ%). Avg duration 3930.0 min.',  # noqa: E501
+            'total_profit': -0.00125625,
+            'current_epoch': 1,
+            'is_initial_point': True,
+            'is_best': True
+        }, {
+            'loss': 20.0,
+            'params_dict': {
+                'mfi-value': 17, 'fastd-value': 38, 'adx-value': 48, 'rsi-value': 22, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 96, 'sell-fastd-value': 68, 'sell-adx-value': 63, 'sell-rsi-value': 81, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal', 'roi_t1': 334, 'roi_t2': 683, 'roi_t3': 140, 'roi_p1': 0.06403981740598495, 'roi_p2': 0.055519840060645045, 'roi_p3': 0.3253712811342459, 'stoploss': -0.338070047333259},  # noqa: E501
+            'params_details': {
+                'buy': {'mfi-value': 17, 'fastd-value': 38, 'adx-value': 48, 'rsi-value': 22, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal'},  # noqa: E501
+                'sell': {'sell-mfi-value': 96, 'sell-fastd-value': 68, 'sell-adx-value': 63, 'sell-rsi-value': 81, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal'},  # noqa: E501
+                'roi': {0: 0.4449309386008759, 140: 0.11955965746663, 823: 0.06403981740598495, 1157: 0},  # noqa: E501
+                'stoploss': {'stoploss': -0.338070047333259}},
+            'results_metrics': {'trade_count': 1, 'avg_profit': 0.12357, 'total_profit': 6.185e-05, 'profit': 0.12357, 'duration': 1200.0},  # noqa: E501
+            'results_explanation': '     1 trades. Avg profit   0.12%. Total profit  0.00006185 BTC (   0.12Σ%). Avg duration 1200.0 min.',  # noqa: E501
+            'total_profit': 6.185e-05,
+            'current_epoch': 2,
+            'is_initial_point': True,
+            'is_best': False
+        }, {
+            'loss': 14.241196856510731,
+            'params_dict': {'mfi-value': 25, 'fastd-value': 16, 'adx-value': 29, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 98, 'sell-fastd-value': 72, 'sell-adx-value': 51, 'sell-rsi-value': 82, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 889, 'roi_t2': 533, 'roi_t3': 263, 'roi_p1': 0.04759065393663096, 'roi_p2': 0.1488819964638463, 'roi_p3': 0.4102801822104605, 'stoploss': -0.05394588767607611},  # noqa: E501
+            'params_details': {'buy': {'mfi-value': 25, 'fastd-value': 16, 'adx-value': 29, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 98, 'sell-fastd-value': 72, 'sell-adx-value': 51, 'sell-rsi-value': 82, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.6067528326109377, 263: 0.19647265040047726, 796: 0.04759065393663096, 1685: 0}, 'stoploss': {'stoploss': -0.05394588767607611}},  # noqa: E501
+            'results_metrics': {'trade_count': 621, 'avg_profit': -0.43883302093397747, 'total_profit': -0.13639474, 'profit': -272.515306, 'duration': 1691.207729468599},  # noqa: E501
+            'results_explanation': '   621 trades. Avg profit  -0.44%. Total profit -0.13639474 BTC (-272.52Σ%). Avg duration 1691.2 min.',  # noqa: E501
+            'total_profit': -0.13639474,
+            'current_epoch': 3,
+            'is_initial_point': True,
+            'is_best': False
+        }, {
+            'loss': 100000,
+            'params_dict': {'mfi-value': 13, 'fastd-value': 35, 'adx-value': 39, 'rsi-value': 29, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': True, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 87, 'sell-fastd-value': 54, 'sell-adx-value': 63, 'sell-rsi-value': 93, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper', 'roi_t1': 1402, 'roi_t2': 676, 'roi_t3': 215, 'roi_p1': 0.06264755784937427, 'roi_p2': 0.14258587851894644, 'roi_p3': 0.20671291201040828, 'stoploss': -0.11818343570194478},  # noqa: E501
+            'params_details': {'buy': {'mfi-value': 13, 'fastd-value': 35, 'adx-value': 39, 'rsi-value': 29, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': True, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 87, 'sell-fastd-value': 54, 'sell-adx-value': 63, 'sell-rsi-value': 93, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper'}, 'roi': {0: 0.411946348378729, 215: 0.2052334363683207, 891: 0.06264755784937427, 2293: 0}, 'stoploss': {'stoploss': -0.11818343570194478}},  # noqa: E501
+            'results_metrics': {'trade_count': 0, 'avg_profit': None, 'total_profit': 0, 'profit': 0.0, 'duration': None},  # noqa: E501
+            'results_explanation': '     0 trades. Avg profit    nan%. Total profit  0.00000000 BTC (   0.00Σ%). Avg duration   nan min.',  # noqa: E501
+            'total_profit': 0, 'current_epoch': 4, 'is_initial_point': True, 'is_best': False
+        }, {
+            'loss': 0.22195522184191518,
+            'params_dict': {'mfi-value': 17, 'fastd-value': 21, 'adx-value': 38, 'rsi-value': 33, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': False, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 87, 'sell-fastd-value': 82, 'sell-adx-value': 78, 'sell-rsi-value': 69, 'sell-mfi-enabled': True, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': False, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 1269, 'roi_t2': 601, 'roi_t3': 444, 'roi_p1': 0.07280999507931168, 'roi_p2': 0.08946698095898986, 'roi_p3': 0.1454876733325284, 'stoploss': -0.18181041180901014},   # noqa: E501
+            'params_details': {'buy': {'mfi-value': 17, 'fastd-value': 21, 'adx-value': 38, 'rsi-value': 33, 'mfi-enabled': True, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': False, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 87, 'sell-fastd-value': 82, 'sell-adx-value': 78, 'sell-rsi-value': 69, 'sell-mfi-enabled': True, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': False, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.3077646493708299, 444: 0.16227697603830155, 1045: 0.07280999507931168, 2314: 0}, 'stoploss': {'stoploss': -0.18181041180901014}},  # noqa: E501
+            'results_metrics': {'trade_count': 14, 'avg_profit': -0.3539515, 'total_profit': -0.002480140000000001, 'profit': -4.955321, 'duration': 3402.8571428571427},  # noqa: E501
+            'results_explanation': '    14 trades. Avg profit  -0.35%. Total profit -0.00248014 BTC (  -4.96Σ%). Avg duration 3402.9 min.',  # noqa: E501
+            'total_profit': -0.002480140000000001,
+            'current_epoch': 5,
+            'is_initial_point': True,
+            'is_best': True
+        }, {
+            'loss': 0.545315889154162,
+            'params_dict': {'mfi-value': 22, 'fastd-value': 43, 'adx-value': 46, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'bb_lower', 'sell-mfi-value': 87, 'sell-fastd-value': 65, 'sell-adx-value': 94, 'sell-rsi-value': 63, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 319, 'roi_t2': 556, 'roi_t3': 216, 'roi_p1': 0.06251955472249589, 'roi_p2': 0.11659519602202795, 'roi_p3': 0.0953744132197762, 'stoploss': -0.024551752215582423},  # noqa: E501
+            'params_details': {'buy': {'mfi-value': 22, 'fastd-value': 43, 'adx-value': 46, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'bb_lower'}, 'sell': {'sell-mfi-value': 87, 'sell-fastd-value': 65, 'sell-adx-value': 94, 'sell-rsi-value': 63, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.2744891639643, 216: 0.17911475074452382, 772: 0.06251955472249589, 1091: 0}, 'stoploss': {'stoploss': -0.024551752215582423}},  # noqa: E501
+            'results_metrics': {'trade_count': 39, 'avg_profit': -0.21400679487179478, 'total_profit': -0.0041773, 'profit': -8.346264999999997, 'duration': 636.9230769230769},  # noqa: E501
+            'results_explanation': '    39 trades. Avg profit  -0.21%. Total profit -0.00417730 BTC (  -8.35Σ%). Avg duration 636.9 min.',  # noqa: E501
+            'total_profit': -0.0041773,
+            'current_epoch': 6,
+            'is_initial_point': True,
+            'is_best': False
+        }, {
+            'loss': 4.713497421432944,
+            'params_dict': {'mfi-value': 13, 'fastd-value': 41, 'adx-value': 21, 'rsi-value': 29, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'bb_lower', 'sell-mfi-value': 99, 'sell-fastd-value': 60, 'sell-adx-value': 81, 'sell-rsi-value': 69, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': False, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 771, 'roi_t2': 620, 'roi_t3': 145, 'roi_p1': 0.0586919200378493, 'roi_p2': 0.04984118697312542, 'roi_p3': 0.37521058680247044, 'stoploss': -0.14613268022709905},  # noqa: E501
+            'params_details': {
+                'buy': {'mfi-value': 13, 'fastd-value': 41, 'adx-value': 21, 'rsi-value': 29, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'bb_lower'}, 'sell': {'sell-mfi-value': 99, 'sell-fastd-value': 60, 'sell-adx-value': 81, 'sell-rsi-value': 69, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': False, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.4837436938134452, 145: 0.10853310701097472, 765: 0.0586919200378493, 1536: 0},  # noqa: E501
+                'stoploss': {'stoploss': -0.14613268022709905}},  # noqa: E501
+            'results_metrics': {'trade_count': 318, 'avg_profit': -0.39833954716981146, 'total_profit': -0.06339929, 'profit': -126.67197600000004, 'duration': 3140.377358490566},  # noqa: E501
+            'results_explanation': '   318 trades. Avg profit  -0.40%. Total profit -0.06339929 BTC (-126.67Σ%). Avg duration 3140.4 min.',  # noqa: E501
+            'total_profit': -0.06339929,
+            'current_epoch': 7,
+            'is_initial_point': True,
+            'is_best': False
+        }, {
+            'loss': 20.0,  # noqa: E501
+            'params_dict': {'mfi-value': 24, 'fastd-value': 43, 'adx-value': 33, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'sar_reversal', 'sell-mfi-value': 89, 'sell-fastd-value': 74, 'sell-adx-value': 70, 'sell-rsi-value': 70, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': False, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal', 'roi_t1': 1149, 'roi_t2': 375, 'roi_t3': 289, 'roi_p1': 0.05571820757172588, 'roi_p2': 0.0606240398618907, 'roi_p3': 0.1729012220156157, 'stoploss': -0.1588514289110401},  # noqa: E501
+            'params_details': {'buy': {'mfi-value': 24, 'fastd-value': 43, 'adx-value': 33, 'rsi-value': 20, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'sar_reversal'}, 'sell': {'sell-mfi-value': 89, 'sell-fastd-value': 74, 'sell-adx-value': 70, 'sell-rsi-value': 70, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': False, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal'}, 'roi': {0: 0.2892434694492323, 289: 0.11634224743361658, 664: 0.05571820757172588, 1813: 0}, 'stoploss': {'stoploss': -0.1588514289110401}},  # noqa: E501
+            'results_metrics': {'trade_count': 1, 'avg_profit': 0.0, 'total_profit': 0.0, 'profit': 0.0, 'duration': 5340.0},  # noqa: E501
+            'results_explanation': '     1 trades. Avg profit   0.00%. Total profit  0.00000000 BTC (   0.00Σ%). Avg duration 5340.0 min.',  # noqa: E501
+            'total_profit': 0.0,
+            'current_epoch': 8,
+            'is_initial_point': True,
+            'is_best': False
+        }, {
+            'loss': 2.4731817780991223,
+            'params_dict': {'mfi-value': 22, 'fastd-value': 20, 'adx-value': 29, 'rsi-value': 40, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'sar_reversal', 'sell-mfi-value': 97, 'sell-fastd-value': 65, 'sell-adx-value': 81, 'sell-rsi-value': 64, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper', 'roi_t1': 1012, 'roi_t2': 584, 'roi_t3': 422, 'roi_p1': 0.036764323603472565, 'roi_p2': 0.10335480573205287, 'roi_p3': 0.10322347377503042, 'stoploss': -0.2780610808108503},  # noqa: E501
+            'params_details': {'buy': {'mfi-value': 22, 'fastd-value': 20, 'adx-value': 29, 'rsi-value': 40, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'sar_reversal'}, 'sell': {'sell-mfi-value': 97, 'sell-fastd-value': 65, 'sell-adx-value': 81, 'sell-rsi-value': 64, 'sell-mfi-enabled': True, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper'}, 'roi': {0: 0.2433426031105559, 422: 0.14011912933552545, 1006: 0.036764323603472565, 2018: 0}, 'stoploss': {'stoploss': -0.2780610808108503}},  # noqa: E501
+            'results_metrics': {'trade_count': 229, 'avg_profit': -0.38433433624454144, 'total_profit': -0.044050070000000004, 'profit': -88.01256299999999, 'duration': 6505.676855895196},  # noqa: E501
+            'results_explanation': '   229 trades. Avg profit  -0.38%. Total profit -0.04405007 BTC ( -88.01Σ%). Avg duration 6505.7 min.',  # noqa: E501
+            'total_profit': -0.044050070000000004,  # noqa: E501
+            'current_epoch': 9,
+            'is_initial_point': True,
+            'is_best': False
+        }, {
+            'loss': -0.2604606005845212,  # noqa: E501
+            'params_dict': {'mfi-value': 23, 'fastd-value': 24, 'adx-value': 22, 'rsi-value': 24, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': True, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 97, 'sell-fastd-value': 70, 'sell-adx-value': 64, 'sell-rsi-value': 80, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal', 'roi_t1': 792, 'roi_t2': 464, 'roi_t3': 215, 'roi_p1': 0.04594053535385903, 'roi_p2': 0.09623192684243963, 'roi_p3': 0.04428219070850663, 'stoploss': -0.16992287161634415},  # noqa: E501
+            'params_details': {'buy': {'mfi-value': 23, 'fastd-value': 24, 'adx-value': 22, 'rsi-value': 24, 'mfi-enabled': False, 'fastd-enabled': False, 'adx-enabled': False, 'rsi-enabled': True, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 97, 'sell-fastd-value': 70, 'sell-adx-value': 64, 'sell-rsi-value': 80, 'sell-mfi-enabled': False, 'sell-fastd-enabled': True, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-sar_reversal'}, 'roi': {0: 0.18645465290480528, 215: 0.14217246219629864, 679: 0.04594053535385903, 1471: 0}, 'stoploss': {'stoploss': -0.16992287161634415}},  # noqa: E501
+            'results_metrics': {'trade_count': 4, 'avg_profit': 0.1080385, 'total_profit': 0.00021629, 'profit': 0.432154, 'duration': 2850.0},  # noqa: E501
+            'results_explanation': '     4 trades. Avg profit   0.11%. Total profit  0.00021629 BTC (   0.43Σ%). Avg duration 2850.0 min.',  # noqa: E501
+            'total_profit': 0.00021629,
+            'current_epoch': 10,
+            'is_initial_point': True,
+            'is_best': True
+        }, {
+            'loss': 4.876465945994304,  # noqa: E501
+            'params_dict': {'mfi-value': 20, 'fastd-value': 32, 'adx-value': 49, 'rsi-value': 23, 'mfi-enabled': True, 'fastd-enabled': True, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'bb_lower', 'sell-mfi-value': 75, 'sell-fastd-value': 56, 'sell-adx-value': 61, 'sell-rsi-value': 62, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal', 'roi_t1': 579, 'roi_t2': 614, 'roi_t3': 273, 'roi_p1': 0.05307643172744114, 'roi_p2': 0.1352282078262871, 'roi_p3': 0.1913307406325751, 'stoploss': -0.25728526022513887},  # noqa: E501
+            'params_details': {'buy': {'mfi-value': 20, 'fastd-value': 32, 'adx-value': 49, 'rsi-value': 23, 'mfi-enabled': True, 'fastd-enabled': True, 'adx-enabled': False, 'rsi-enabled': False, 'trigger': 'bb_lower'}, 'sell': {'sell-mfi-value': 75, 'sell-fastd-value': 56, 'sell-adx-value': 61, 'sell-rsi-value': 62, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-macd_cross_signal'}, 'roi': {0: 0.3796353801863034, 273: 0.18830463955372825, 887: 0.05307643172744114, 1466: 0}, 'stoploss': {'stoploss': -0.25728526022513887}},  # noqa: E501
+            'results_metrics': {'trade_count': 117, 'avg_profit': -1.2698609145299145, 'total_profit': -0.07436117, 'profit': -148.573727, 'duration': 4282.5641025641025},  # noqa: E501
+            'results_explanation': '   117 trades. Avg profit  -1.27%. Total profit -0.07436117 BTC (-148.57Σ%). Avg duration 4282.6 min.',  # noqa: E501
+            'total_profit': -0.07436117,
+            'current_epoch': 11,
+            'is_initial_point': True,
+            'is_best': False
+        }, {
+            'loss': 100000,
+            'params_dict': {'mfi-value': 10, 'fastd-value': 36, 'adx-value': 31, 'rsi-value': 22, 'mfi-enabled': True, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': False, 'trigger': 'sar_reversal', 'sell-mfi-value': 80, 'sell-fastd-value': 71, 'sell-adx-value': 60, 'sell-rsi-value': 85, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper', 'roi_t1': 1156, 'roi_t2': 581, 'roi_t3': 408, 'roi_p1': 0.06860454019988212, 'roi_p2': 0.12473718444931989, 'roi_p3': 0.2896360635226823, 'stoploss': -0.30889015124682806},  # noqa: E501
+            'params_details': {'buy': {'mfi-value': 10, 'fastd-value': 36, 'adx-value': 31, 'rsi-value': 22, 'mfi-enabled': True, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': False, 'trigger': 'sar_reversal'}, 'sell': {'sell-mfi-value': 80, 'sell-fastd-value': 71, 'sell-adx-value': 60, 'sell-rsi-value': 85, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper'}, 'roi': {0: 0.4829777881718843, 408: 0.19334172464920202, 989: 0.06860454019988212, 2145: 0}, 'stoploss': {'stoploss': -0.30889015124682806}},  # noqa: E501
+            'results_metrics': {'trade_count': 0, 'avg_profit': None, 'total_profit': 0, 'profit': 0.0, 'duration': None},  # noqa: E501
+            'results_explanation': '     0 trades. Avg profit    nan%. Total profit  0.00000000 BTC (   0.00Σ%). Avg duration   nan min.',  # noqa: E501
+            'total_profit': 0,
+            'current_epoch': 12,
+            'is_initial_point': True,
+            'is_best': False
+            }
+    ]
diff --git a/tests/conftest_trades.py b/tests/conftest_trades.py
new file mode 100644
index 000000000..78388f022
--- /dev/null
+++ b/tests/conftest_trades.py
@@ -0,0 +1,279 @@
+from freqtrade.persistence.models import Order, Trade
+
+
+MOCK_TRADE_COUNT = 6
+
+
+def mock_order_1():
+    return {
+        'id': '1234',
+        'symbol': 'ETH/BTC',
+        'status': 'closed',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 0.123,
+        'amount': 123.0,
+        'filled': 123.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_trade_1(fee):
+    trade = Trade(
+        pair='ETH/BTC',
+        stake_amount=0.001,
+        amount=123.0,
+        amount_requested=123.0,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.123,
+        exchange='bittrex',
+        open_order_id='dry_run_buy_12345',
+        strategy='DefaultStrategy',
+    )
+    o = Order.parse_from_ccxt_object(mock_order_1(), 'ETH/BTC', 'buy')
+    trade.orders.append(o)
+    return trade
+
+
+def mock_order_2():
+    return {
+        'id': '1235',
+        'symbol': 'ETC/BTC',
+        'status': 'closed',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 0.123,
+        'amount': 123.0,
+        'filled': 123.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_order_2_sell():
+    return {
+        'id': '12366',
+        'symbol': 'ETC/BTC',
+        'status': 'closed',
+        'side': 'sell',
+        'type': 'limit',
+        'price': 0.128,
+        'amount': 123.0,
+        'filled': 123.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_trade_2(fee):
+    """
+    Closed trade...
+    """
+    trade = Trade(
+        pair='ETC/BTC',
+        stake_amount=0.001,
+        amount=123.0,
+        amount_requested=123.0,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.123,
+        close_rate=0.128,
+        close_profit=0.005,
+        exchange='bittrex',
+        is_open=False,
+        open_order_id='dry_run_sell_12345',
+        strategy='DefaultStrategy',
+    )
+    o = Order.parse_from_ccxt_object(mock_order_2(), 'ETC/BTC', 'buy')
+    trade.orders.append(o)
+    o = Order.parse_from_ccxt_object(mock_order_2_sell(), 'ETC/BTC', 'sell')
+    trade.orders.append(o)
+    return trade
+
+
+def mock_order_3():
+    return {
+        'id': '41231a12a',
+        'symbol': 'XRP/BTC',
+        'status': 'closed',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 0.05,
+        'amount': 123.0,
+        'filled': 123.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_order_3_sell():
+    return {
+        'id': '41231a666a',
+        'symbol': 'XRP/BTC',
+        'status': 'closed',
+        'side': 'sell',
+        'type': 'stop_loss_limit',
+        'price': 0.06,
+        'average': 0.06,
+        'amount': 123.0,
+        'filled': 123.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_trade_3(fee):
+    """
+    Closed trade
+    """
+    trade = Trade(
+        pair='XRP/BTC',
+        stake_amount=0.001,
+        amount=123.0,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.05,
+        close_rate=0.06,
+        close_profit=0.01,
+        exchange='bittrex',
+        is_open=False,
+    )
+    o = Order.parse_from_ccxt_object(mock_order_3(), 'XRP/BTC', 'buy')
+    trade.orders.append(o)
+    o = Order.parse_from_ccxt_object(mock_order_3_sell(), 'XRP/BTC', 'sell')
+    trade.orders.append(o)
+    return trade
+
+
+def mock_order_4():
+    return {
+        'id': 'prod_buy_12345',
+        'symbol': 'ETC/BTC',
+        'status': 'open',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 0.123,
+        'amount': 123.0,
+        'filled': 0.0,
+        'remaining': 123.0,
+    }
+
+
+def mock_trade_4(fee):
+    """
+    Simulate prod entry
+    """
+    trade = Trade(
+        pair='ETC/BTC',
+        stake_amount=0.001,
+        amount=123.0,
+        amount_requested=124.0,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.123,
+        exchange='bittrex',
+        open_order_id='prod_buy_12345',
+        strategy='DefaultStrategy',
+    )
+    o = Order.parse_from_ccxt_object(mock_order_4(), 'ETC/BTC', 'buy')
+    trade.orders.append(o)
+    return trade
+
+
+def mock_order_5():
+    return {
+        'id': 'prod_buy_3455',
+        'symbol': 'XRP/BTC',
+        'status': 'closed',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 0.123,
+        'amount': 123.0,
+        'filled': 123.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_order_5_stoploss():
+    return {
+        'id': 'prod_stoploss_3455',
+        'symbol': 'XRP/BTC',
+        'status': 'open',
+        'side': 'sell',
+        'type': 'stop_loss_limit',
+        'price': 0.123,
+        'amount': 123.0,
+        'filled': 0.0,
+        'remaining': 123.0,
+    }
+
+
+def mock_trade_5(fee):
+    """
+    Simulate prod entry with stoploss
+    """
+    trade = Trade(
+        pair='XRP/BTC',
+        stake_amount=0.001,
+        amount=123.0,
+        amount_requested=124.0,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.123,
+        exchange='bittrex',
+        strategy='SampleStrategy',
+        stoploss_order_id='prod_stoploss_3455'
+    )
+    o = Order.parse_from_ccxt_object(mock_order_5(), 'XRP/BTC', 'buy')
+    trade.orders.append(o)
+    o = Order.parse_from_ccxt_object(mock_order_5_stoploss(), 'XRP/BTC', 'stoploss')
+    trade.orders.append(o)
+    return trade
+
+
+def mock_order_6():
+    return {
+        'id': 'prod_buy_6',
+        'symbol': 'LTC/BTC',
+        'status': 'closed',
+        'side': 'buy',
+        'type': 'limit',
+        'price': 0.15,
+        'amount': 2.0,
+        'filled': 2.0,
+        'remaining': 0.0,
+    }
+
+
+def mock_order_6_sell():
+    return {
+        'id': 'prod_sell_6',
+        'symbol': 'LTC/BTC',
+        'status': 'open',
+        'side': 'sell',
+        'type': 'limit',
+        'price': 0.20,
+        'amount': 2.0,
+        'filled': 0.0,
+        'remaining': 2.0,
+    }
+
+
+def mock_trade_6(fee):
+    """
+    Simulate prod entry with open sell order
+    """
+    trade = Trade(
+        pair='LTC/BTC',
+        stake_amount=0.001,
+        amount=2.0,
+        amount_requested=2.0,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.15,
+        exchange='bittrex',
+        strategy='SampleStrategy',
+        open_order_id="prod_sell_6",
+    )
+    o = Order.parse_from_ccxt_object(mock_order_6(), 'LTC/BTC', 'buy')
+    trade.orders.append(o)
+    o = Order.parse_from_ccxt_object(mock_order_6_sell(), 'LTC/BTC', 'sell')
+    trade.orders.append(o)
+    return trade
diff --git a/freqtrade/tests/pairlist/__init__.py b/tests/data/__init__.py
similarity index 100%
rename from freqtrade/tests/pairlist/__init__.py
rename to tests/data/__init__.py
diff --git a/tests/data/test_btanalysis.py b/tests/data/test_btanalysis.py
new file mode 100644
index 000000000..1592fac10
--- /dev/null
+++ b/tests/data/test_btanalysis.py
@@ -0,0 +1,310 @@
+from pathlib import Path
+from unittest.mock import MagicMock
+
+import pytest
+from arrow import Arrow
+from pandas import DataFrame, DateOffset, Timestamp, to_datetime
+
+from freqtrade.configuration import TimeRange
+from freqtrade.constants import LAST_BT_RESULT_FN
+from freqtrade.data.btanalysis import (BT_DATA_COLUMNS, analyze_trade_parallelism,
+                                       calculate_market_change, calculate_max_drawdown,
+                                       combine_dataframes_with_mean, create_cum_profit,
+                                       extract_trades_of_period, get_latest_backtest_filename,
+                                       get_latest_hyperopt_file, load_backtest_data, load_trades,
+                                       load_trades_from_db)
+from freqtrade.data.history import load_data, load_pair_history
+from freqtrade.optimize.backtesting import BacktestResult
+from tests.conftest import create_mock_trades
+from tests.conftest_trades import MOCK_TRADE_COUNT
+
+
+def test_get_latest_backtest_filename(testdatadir, mocker):
+    with pytest.raises(ValueError, match=r"Directory .* does not exist\."):
+        get_latest_backtest_filename(testdatadir / 'does_not_exist')
+
+    with pytest.raises(ValueError,
+                       match=r"Directory .* does not seem to contain .*"):
+        get_latest_backtest_filename(testdatadir.parent)
+
+    res = get_latest_backtest_filename(testdatadir)
+    assert res == 'backtest-result_new.json'
+
+    res = get_latest_backtest_filename(str(testdatadir))
+    assert res == 'backtest-result_new.json'
+
+    mocker.patch("freqtrade.data.btanalysis.json_load", return_value={})
+
+    with pytest.raises(ValueError, match=r"Invalid '.last_result.json' format."):
+        get_latest_backtest_filename(testdatadir)
+
+
+def test_get_latest_hyperopt_file(testdatadir, mocker):
+    res = get_latest_hyperopt_file(testdatadir / 'does_not_exist', 'testfile.pickle')
+    assert res == testdatadir / 'does_not_exist/testfile.pickle'
+
+    res = get_latest_hyperopt_file(testdatadir.parent)
+    assert res == testdatadir.parent / "hyperopt_results.pickle"
+
+    res = get_latest_hyperopt_file(str(testdatadir.parent))
+    assert res == testdatadir.parent / "hyperopt_results.pickle"
+
+
+def test_load_backtest_data_old_format(testdatadir):
+
+    filename = testdatadir / "backtest-result_test.json"
+    bt_data = load_backtest_data(filename)
+    assert isinstance(bt_data, DataFrame)
+    assert list(bt_data.columns) == BT_DATA_COLUMNS + ["profit_abs"]
+    assert len(bt_data) == 179
+
+    # Test loading from string (must yield same result)
+    bt_data2 = load_backtest_data(str(filename))
+    assert bt_data.equals(bt_data2)
+
+    with pytest.raises(ValueError, match=r"File .* does not exist\."):
+        load_backtest_data(str("filename") + "nofile")
+
+
+def test_load_backtest_data_new_format(testdatadir):
+
+    filename = testdatadir / "backtest-result_new.json"
+    bt_data = load_backtest_data(filename)
+    assert isinstance(bt_data, DataFrame)
+    assert set(bt_data.columns) == set(list(BacktestResult._fields) + ["profit_abs"])
+    assert len(bt_data) == 179
+
+    # Test loading from string (must yield same result)
+    bt_data2 = load_backtest_data(str(filename))
+    assert bt_data.equals(bt_data2)
+
+    # Test loading from folder (must yield same result)
+    bt_data3 = load_backtest_data(testdatadir)
+    assert bt_data.equals(bt_data3)
+
+    with pytest.raises(ValueError, match=r"File .* does not exist\."):
+        load_backtest_data(str("filename") + "nofile")
+
+    with pytest.raises(ValueError, match=r"Unknown dataformat."):
+        load_backtest_data(testdatadir / LAST_BT_RESULT_FN)
+
+
+def test_load_backtest_data_multi(testdatadir):
+
+    filename = testdatadir / "backtest-result_multistrat.json"
+    for strategy in ('DefaultStrategy', 'TestStrategy'):
+        bt_data = load_backtest_data(filename, strategy=strategy)
+        assert isinstance(bt_data, DataFrame)
+        assert set(bt_data.columns) == set(list(BacktestResult._fields) + ["profit_abs"])
+        assert len(bt_data) == 179
+
+        # Test loading from string (must yield same result)
+        bt_data2 = load_backtest_data(str(filename), strategy=strategy)
+        assert bt_data.equals(bt_data2)
+
+    with pytest.raises(ValueError, match=r"Strategy XYZ not available in the backtest result\."):
+        load_backtest_data(filename, strategy='XYZ')
+
+    with pytest.raises(ValueError, match=r"Detected backtest result with more than one strategy.*"):
+        load_backtest_data(filename)
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_load_trades_from_db(default_conf, fee, mocker):
+
+    create_mock_trades(fee)
+    # remove init so it does not init again
+    init_mock = mocker.patch('freqtrade.data.btanalysis.init_db', MagicMock())
+
+    trades = load_trades_from_db(db_url=default_conf['db_url'])
+    assert init_mock.call_count == 1
+    assert len(trades) == MOCK_TRADE_COUNT
+    assert isinstance(trades, DataFrame)
+    assert "pair" in trades.columns
+    assert "open_date" in trades.columns
+    assert "profit_percent" in trades.columns
+
+    for col in BT_DATA_COLUMNS:
+        if col not in ['index', 'open_at_end']:
+            assert col in trades.columns
+    trades = load_trades_from_db(db_url=default_conf['db_url'], strategy='DefaultStrategy')
+    assert len(trades) == 3
+    trades = load_trades_from_db(db_url=default_conf['db_url'], strategy='NoneStrategy')
+    assert len(trades) == 0
+
+
+def test_extract_trades_of_period(testdatadir):
+    pair = "UNITTEST/BTC"
+    # 2018-11-14 06:07:00
+    timerange = TimeRange('date', None, 1510639620, 0)
+
+    data = load_pair_history(pair=pair, timeframe='1m',
+                             datadir=testdatadir, timerange=timerange)
+
+    trades = DataFrame(
+        {'pair': [pair, pair, pair, pair],
+         'profit_percent': [0.0, 0.1, -0.2, -0.5],
+         'profit_abs': [0.0, 1, -2, -5],
+         'open_date': to_datetime([Arrow(2017, 11, 13, 15, 40, 0).datetime,
+                                   Arrow(2017, 11, 14, 9, 41, 0).datetime,
+                                   Arrow(2017, 11, 14, 14, 20, 0).datetime,
+                                   Arrow(2017, 11, 15, 3, 40, 0).datetime,
+                                   ], utc=True
+                                  ),
+         'close_date': to_datetime([Arrow(2017, 11, 13, 16, 40, 0).datetime,
+                                    Arrow(2017, 11, 14, 10, 41, 0).datetime,
+                                    Arrow(2017, 11, 14, 15, 25, 0).datetime,
+                                    Arrow(2017, 11, 15, 3, 55, 0).datetime,
+                                    ], utc=True)
+         })
+    trades1 = extract_trades_of_period(data, trades)
+    # First and last trade are dropped as they are out of range
+    assert len(trades1) == 2
+    assert trades1.iloc[0].open_date == Arrow(2017, 11, 14, 9, 41, 0).datetime
+    assert trades1.iloc[0].close_date == Arrow(2017, 11, 14, 10, 41, 0).datetime
+    assert trades1.iloc[-1].open_date == Arrow(2017, 11, 14, 14, 20, 0).datetime
+    assert trades1.iloc[-1].close_date == Arrow(2017, 11, 14, 15, 25, 0).datetime
+
+
+def test_analyze_trade_parallelism(default_conf, mocker, testdatadir):
+    filename = testdatadir / "backtest-result_test.json"
+    bt_data = load_backtest_data(filename)
+
+    res = analyze_trade_parallelism(bt_data, "5m")
+    assert isinstance(res, DataFrame)
+    assert 'open_trades' in res.columns
+    assert res['open_trades'].max() == 3
+    assert res['open_trades'].min() == 0
+
+
+def test_load_trades(default_conf, mocker):
+    db_mock = mocker.patch("freqtrade.data.btanalysis.load_trades_from_db", MagicMock())
+    bt_mock = mocker.patch("freqtrade.data.btanalysis.load_backtest_data", MagicMock())
+
+    load_trades("DB",
+                db_url=default_conf.get('db_url'),
+                exportfilename=default_conf.get('exportfilename'),
+                no_trades=False,
+                strategy="DefaultStrategy",
+                )
+
+    assert db_mock.call_count == 1
+    assert bt_mock.call_count == 0
+
+    db_mock.reset_mock()
+    bt_mock.reset_mock()
+    default_conf['exportfilename'] = Path("testfile.json")
+    load_trades("file",
+                db_url=default_conf.get('db_url'),
+                exportfilename=default_conf.get('exportfilename'),
+                )
+
+    assert db_mock.call_count == 0
+    assert bt_mock.call_count == 1
+
+    db_mock.reset_mock()
+    bt_mock.reset_mock()
+    default_conf['exportfilename'] = "testfile.json"
+    load_trades("file",
+                db_url=default_conf.get('db_url'),
+                exportfilename=default_conf.get('exportfilename'),
+                no_trades=True
+                )
+
+    assert db_mock.call_count == 0
+    assert bt_mock.call_count == 0
+
+
+def test_calculate_market_change(testdatadir):
+    pairs = ["ETH/BTC", "ADA/BTC"]
+    data = load_data(datadir=testdatadir, pairs=pairs, timeframe='5m')
+    result = calculate_market_change(data)
+    assert isinstance(result, float)
+    assert pytest.approx(result) == 0.00955514
+
+
+def test_combine_dataframes_with_mean(testdatadir):
+    pairs = ["ETH/BTC", "ADA/BTC"]
+    data = load_data(datadir=testdatadir, pairs=pairs, timeframe='5m')
+    df = combine_dataframes_with_mean(data)
+    assert isinstance(df, DataFrame)
+    assert "ETH/BTC" in df.columns
+    assert "ADA/BTC" in df.columns
+    assert "mean" in df.columns
+
+
+def test_create_cum_profit(testdatadir):
+    filename = testdatadir / "backtest-result_test.json"
+    bt_data = load_backtest_data(filename)
+    timerange = TimeRange.parse_timerange("20180110-20180112")
+
+    df = load_pair_history(pair="TRX/BTC", timeframe='5m',
+                           datadir=testdatadir, timerange=timerange)
+
+    cum_profits = create_cum_profit(df.set_index('date'),
+                                    bt_data[bt_data["pair"] == 'TRX/BTC'],
+                                    "cum_profits", timeframe="5m")
+    assert "cum_profits" in cum_profits.columns
+    assert cum_profits.iloc[0]['cum_profits'] == 0
+    assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005
+
+
+def test_create_cum_profit1(testdatadir):
+    filename = testdatadir / "backtest-result_test.json"
+    bt_data = load_backtest_data(filename)
+    # Move close-time to "off" the candle, to make sure the logic still works
+    bt_data.loc[:, 'close_date'] = bt_data.loc[:, 'close_date'] + DateOffset(seconds=20)
+    timerange = TimeRange.parse_timerange("20180110-20180112")
+
+    df = load_pair_history(pair="TRX/BTC", timeframe='5m',
+                           datadir=testdatadir, timerange=timerange)
+
+    cum_profits = create_cum_profit(df.set_index('date'),
+                                    bt_data[bt_data["pair"] == 'TRX/BTC'],
+                                    "cum_profits", timeframe="5m")
+    assert "cum_profits" in cum_profits.columns
+    assert cum_profits.iloc[0]['cum_profits'] == 0
+    assert cum_profits.iloc[-1]['cum_profits'] == 0.0798005
+
+    with pytest.raises(ValueError, match='Trade dataframe empty.'):
+        create_cum_profit(df.set_index('date'), bt_data[bt_data["pair"] == 'NOTAPAIR'],
+                          "cum_profits", timeframe="5m")
+
+
+def test_calculate_max_drawdown(testdatadir):
+    filename = testdatadir / "backtest-result_test.json"
+    bt_data = load_backtest_data(filename)
+    drawdown, h, low = calculate_max_drawdown(bt_data)
+    assert isinstance(drawdown, float)
+    assert pytest.approx(drawdown) == 0.21142322
+    assert isinstance(h, Timestamp)
+    assert isinstance(low, Timestamp)
+    assert h == Timestamp('2018-01-24 14:25:00', tz='UTC')
+    assert low == Timestamp('2018-01-30 04:45:00', tz='UTC')
+    with pytest.raises(ValueError, match='Trade dataframe empty.'):
+        drawdown, h, low = calculate_max_drawdown(DataFrame())
+
+
+def test_calculate_max_drawdown2():
+    values = [0.011580, 0.010048, 0.011340, 0.012161, 0.010416, 0.010009, 0.020024,
+              -0.024662, -0.022350, 0.020496, -0.029859, -0.030511, 0.010041, 0.010872,
+              -0.025782, 0.010400, 0.012374, 0.012467, 0.114741, 0.010303, 0.010088,
+              -0.033961, 0.010680, 0.010886, -0.029274, 0.011178, 0.010693, 0.010711]
+
+    dates = [Arrow(2020, 1, 1).shift(days=i) for i in range(len(values))]
+    df = DataFrame(zip(values, dates), columns=['profit', 'open_date'])
+    # sort by profit and reset index
+    df = df.sort_values('profit').reset_index(drop=True)
+    df1 = df.copy()
+    drawdown, h, low = calculate_max_drawdown(df, date_col='open_date', value_col='profit')
+    # Ensure df has not been altered.
+    assert df.equals(df1)
+
+    assert isinstance(drawdown, float)
+    # High must be before low
+    assert h < low
+    assert drawdown == 0.091755
+
+    df = DataFrame(zip(values[:5], dates[:5]), columns=['profit', 'open_date'])
+    with pytest.raises(ValueError, match='No losing trade, therefore no drawdown.'):
+        calculate_max_drawdown(df, date_col='open_date', value_col='profit')
diff --git a/tests/data/test_converter.py b/tests/data/test_converter.py
new file mode 100644
index 000000000..4fdcce4d2
--- /dev/null
+++ b/tests/data/test_converter.py
@@ -0,0 +1,316 @@
+# pragma pylint: disable=missing-docstring, C0103
+import logging
+
+import pytest
+
+from freqtrade.configuration.timerange import TimeRange
+from freqtrade.data.converter import (convert_ohlcv_format, convert_trades_format,
+                                      ohlcv_fill_up_missing_data, ohlcv_to_dataframe,
+                                      trades_dict_to_list, trades_remove_duplicates,
+                                      trades_to_ohlcv, trim_dataframe)
+from freqtrade.data.history import (get_timerange, load_data, load_pair_history,
+                                    validate_backtest_data)
+from tests.conftest import log_has
+from tests.data.test_history import _backup_file, _clean_test_file
+
+
+def test_dataframe_correct_columns(result):
+    assert result.columns.tolist() == ['date', 'open', 'high', 'low', 'close', 'volume']
+
+
+def test_ohlcv_to_dataframe(ohlcv_history_list, caplog):
+    columns = ['date', 'open', 'high', 'low', 'close', 'volume']
+
+    caplog.set_level(logging.DEBUG)
+    # Test file with BV data
+    dataframe = ohlcv_to_dataframe(ohlcv_history_list, '5m', pair="UNITTEST/BTC",
+                                   fill_missing=True)
+    assert dataframe.columns.tolist() == columns
+    assert log_has('Converting candle (OHLCV) data to dataframe for pair UNITTEST/BTC.', caplog)
+
+
+def test_trades_to_ohlcv(ohlcv_history_list, caplog):
+
+    caplog.set_level(logging.DEBUG)
+    with pytest.raises(ValueError, match="Trade-list empty."):
+        trades_to_ohlcv([], '1m')
+
+    trades = [
+        [1570752011620, "13519807", None, "sell", 0.00141342, 23.0, 0.03250866],
+        [1570752011620, "13519808", None, "sell", 0.00141266, 54.0, 0.07628364],
+        [1570752017964, "13519809", None, "sell", 0.00141266, 8.0, 0.01130128]]
+
+    df = trades_to_ohlcv(trades, '1m')
+    assert not df.empty
+    assert len(df) == 1
+    assert 'open' in df.columns
+    assert 'high' in df.columns
+    assert 'low' in df.columns
+    assert 'close' in df.columns
+    assert df.loc[:, 'high'][0] == 0.00141342
+    assert df.loc[:, 'low'][0] == 0.00141266
+
+
+def test_ohlcv_fill_up_missing_data(testdatadir, caplog):
+    data = load_pair_history(datadir=testdatadir,
+                             timeframe='1m',
+                             pair='UNITTEST/BTC',
+                             fill_up_missing=False)
+    caplog.set_level(logging.DEBUG)
+    data2 = ohlcv_fill_up_missing_data(data, '1m', 'UNITTEST/BTC')
+    assert len(data2) > len(data)
+    # Column names should not change
+    assert (data.columns == data2.columns).all()
+
+    assert log_has(f"Missing data fillup for UNITTEST/BTC: before: "
+                   f"{len(data)} - after: {len(data2)}", caplog)
+
+    # Test fillup actually fixes invalid backtest data
+    min_date, max_date = get_timerange({'UNITTEST/BTC': data})
+    assert validate_backtest_data(data, 'UNITTEST/BTC', min_date, max_date, 1)
+    assert not validate_backtest_data(data2, 'UNITTEST/BTC', min_date, max_date, 1)
+
+
+def test_ohlcv_fill_up_missing_data2(caplog):
+    timeframe = '5m'
+    ticks = [[
+            1511686200000,  # 8:50:00
+            8.794e-05,  # open
+            8.948e-05,  # high
+            8.794e-05,  # low
+            8.88e-05,  # close
+            2255,  # volume (in quote currency)
+        ],
+        [
+            1511686500000,  # 8:55:00
+            8.88e-05,
+            8.942e-05,
+            8.88e-05,
+            8.893e-05,
+            9911,
+        ],
+        [
+            1511687100000,  # 9:05:00
+            8.891e-05,
+            8.893e-05,
+            8.875e-05,
+            8.877e-05,
+            2251
+        ],
+        [
+            1511687400000,  # 9:10:00
+            8.877e-05,
+            8.883e-05,
+            8.895e-05,
+            8.817e-05,
+            123551
+    ]
+    ]
+
+    # Generate test-data without filling missing
+    data = ohlcv_to_dataframe(ticks, timeframe, pair="UNITTEST/BTC",
+                              fill_missing=False)
+    assert len(data) == 3
+    caplog.set_level(logging.DEBUG)
+    data2 = ohlcv_fill_up_missing_data(data, timeframe, "UNITTEST/BTC")
+    assert len(data2) == 4
+    # 3rd candle has been filled
+    row = data2.loc[2, :]
+    assert row['volume'] == 0
+    # close shoult match close of previous candle
+    assert row['close'] == data.loc[1, 'close']
+    assert row['open'] == row['close']
+    assert row['high'] == row['close']
+    assert row['low'] == row['close']
+    # Column names should not change
+    assert (data.columns == data2.columns).all()
+
+    assert log_has(f"Missing data fillup for UNITTEST/BTC: before: "
+                   f"{len(data)} - after: {len(data2)}", caplog)
+
+
+def test_ohlcv_drop_incomplete(caplog):
+    timeframe = '1d'
+    ticks = [[
+            1559750400000,  # 2019-06-04
+            8.794e-05,  # open
+            8.948e-05,  # high
+            8.794e-05,  # low
+            8.88e-05,  # close
+            2255,  # volume (in quote currency)
+        ],
+        [
+            1559836800000,  # 2019-06-05
+            8.88e-05,
+            8.942e-05,
+            8.88e-05,
+            8.893e-05,
+            9911,
+        ],
+        [
+            1559923200000,  # 2019-06-06
+            8.891e-05,
+            8.893e-05,
+            8.875e-05,
+            8.877e-05,
+            2251
+        ],
+        [
+            1560009600000,  # 2019-06-07
+            8.877e-05,
+            8.883e-05,
+            8.895e-05,
+            8.817e-05,
+            123551
+     ]
+    ]
+    caplog.set_level(logging.DEBUG)
+    data = ohlcv_to_dataframe(ticks, timeframe, pair="UNITTEST/BTC",
+                              fill_missing=False, drop_incomplete=False)
+    assert len(data) == 4
+    assert not log_has("Dropping last candle", caplog)
+
+    # Drop last candle
+    data = ohlcv_to_dataframe(ticks, timeframe, pair="UNITTEST/BTC",
+                              fill_missing=False, drop_incomplete=True)
+    assert len(data) == 3
+
+    assert log_has("Dropping last candle", caplog)
+
+
+def test_trim_dataframe(testdatadir) -> None:
+    data = load_data(
+        datadir=testdatadir,
+        timeframe='1m',
+        pairs=['UNITTEST/BTC']
+    )['UNITTEST/BTC']
+    min_date = int(data.iloc[0]['date'].timestamp())
+    max_date = int(data.iloc[-1]['date'].timestamp())
+    data_modify = data.copy()
+
+    # Remove first 30 minutes (1800 s)
+    tr = TimeRange('date', None, min_date + 1800, 0)
+    data_modify = trim_dataframe(data_modify, tr)
+    assert not data_modify.equals(data)
+    assert len(data_modify) < len(data)
+    assert len(data_modify) == len(data) - 30
+    assert all(data_modify.iloc[-1] == data.iloc[-1])
+    assert all(data_modify.iloc[0] == data.iloc[30])
+
+    data_modify = data.copy()
+    # Remove last 30 minutes (1800 s)
+    tr = TimeRange(None, 'date', 0, max_date - 1800)
+    data_modify = trim_dataframe(data_modify, tr)
+    assert not data_modify.equals(data)
+    assert len(data_modify) < len(data)
+    assert len(data_modify) == len(data) - 30
+    assert all(data_modify.iloc[0] == data.iloc[0])
+    assert all(data_modify.iloc[-1] == data.iloc[-31])
+
+    data_modify = data.copy()
+    # Remove first 25 and last 30 minutes (1800 s)
+    tr = TimeRange('date', 'date', min_date + 1500, max_date - 1800)
+    data_modify = trim_dataframe(data_modify, tr)
+    assert not data_modify.equals(data)
+    assert len(data_modify) < len(data)
+    assert len(data_modify) == len(data) - 55
+    # first row matches 25th original row
+    assert all(data_modify.iloc[0] == data.iloc[25])
+
+
+def test_trades_remove_duplicates(trades_history):
+    trades_history1 = trades_history * 3
+    assert len(trades_history1) == len(trades_history) * 3
+    res = trades_remove_duplicates(trades_history1)
+    assert len(res) == len(trades_history)
+    for i, t in enumerate(res):
+        assert t == trades_history[i]
+
+
+def test_trades_dict_to_list(fetch_trades_result):
+    res = trades_dict_to_list(fetch_trades_result)
+    assert isinstance(res, list)
+    assert isinstance(res[0], list)
+    for i, t in enumerate(res):
+        assert t[0] == fetch_trades_result[i]['timestamp']
+        assert t[1] == fetch_trades_result[i]['id']
+        assert t[2] == fetch_trades_result[i]['type']
+        assert t[3] == fetch_trades_result[i]['side']
+        assert t[4] == fetch_trades_result[i]['price']
+        assert t[5] == fetch_trades_result[i]['amount']
+        assert t[6] == fetch_trades_result[i]['cost']
+
+
+def test_convert_trades_format(mocker, default_conf, testdatadir):
+    files = [{'old': testdatadir / "XRP_ETH-trades.json.gz",
+              'new': testdatadir / "XRP_ETH-trades.json"},
+             {'old': testdatadir / "XRP_OLD-trades.json.gz",
+              'new': testdatadir / "XRP_OLD-trades.json"},
+             ]
+    for file in files:
+        _backup_file(file['old'], copy_file=True)
+        assert not file['new'].exists()
+
+    default_conf['datadir'] = testdatadir
+
+    convert_trades_format(default_conf, convert_from='jsongz',
+                          convert_to='json', erase=False)
+
+    for file in files:
+        assert file['new'].exists()
+        assert file['old'].exists()
+
+        # Remove original file
+        file['old'].unlink()
+    # Convert back
+    convert_trades_format(default_conf, convert_from='json',
+                          convert_to='jsongz', erase=True)
+    for file in files:
+        assert file['old'].exists()
+        assert not file['new'].exists()
+
+        _clean_test_file(file['old'])
+        if file['new'].exists():
+            file['new'].unlink()
+
+
+def test_convert_ohlcv_format(mocker, default_conf, testdatadir):
+    file1 = testdatadir / "XRP_ETH-5m.json"
+    file1_new = testdatadir / "XRP_ETH-5m.json.gz"
+    file2 = testdatadir / "XRP_ETH-1m.json"
+    file2_new = testdatadir / "XRP_ETH-1m.json.gz"
+    _backup_file(file1, copy_file=True)
+    _backup_file(file2, copy_file=True)
+    default_conf['datadir'] = testdatadir
+    default_conf['pairs'] = ['XRP_ETH']
+    default_conf['timeframes'] = ['1m', '5m']
+
+    assert not file1_new.exists()
+    assert not file2_new.exists()
+
+    convert_ohlcv_format(default_conf, convert_from='json',
+                         convert_to='jsongz', erase=False)
+
+    assert file1_new.exists()
+    assert file2_new.exists()
+    assert file1.exists()
+    assert file2.exists()
+
+    # Remove original files
+    file1.unlink()
+    file2.unlink()
+    # Convert back
+    convert_ohlcv_format(default_conf, convert_from='jsongz',
+                         convert_to='json', erase=True)
+
+    assert file1.exists()
+    assert file2.exists()
+    assert not file1_new.exists()
+    assert not file2_new.exists()
+
+    _clean_test_file(file1)
+    _clean_test_file(file2)
+    if file1_new.exists():
+        file1_new.unlink()
+    if file2_new.exists():
+        file2_new.unlink()
diff --git a/tests/data/test_dataprovider.py b/tests/data/test_dataprovider.py
new file mode 100644
index 000000000..a3c57a77b
--- /dev/null
+++ b/tests/data/test_dataprovider.py
@@ -0,0 +1,248 @@
+from datetime import datetime, timezone
+from unittest.mock import MagicMock
+
+import pytest
+from pandas import DataFrame
+
+from freqtrade.data.dataprovider import DataProvider
+from freqtrade.exceptions import ExchangeError, OperationalException
+from freqtrade.pairlist.pairlistmanager import PairListManager
+from freqtrade.state import RunMode
+from tests.conftest import get_patched_exchange
+
+
+def test_ohlcv(mocker, default_conf, ohlcv_history):
+    default_conf["runmode"] = RunMode.DRY_RUN
+    timeframe = default_conf["timeframe"]
+    exchange = get_patched_exchange(mocker, default_conf)
+    exchange._klines[("XRP/BTC", timeframe)] = ohlcv_history
+    exchange._klines[("UNITTEST/BTC", timeframe)] = ohlcv_history
+
+    dp = DataProvider(default_conf, exchange)
+    assert dp.runmode == RunMode.DRY_RUN
+    assert ohlcv_history.equals(dp.ohlcv("UNITTEST/BTC", timeframe))
+    assert isinstance(dp.ohlcv("UNITTEST/BTC", timeframe), DataFrame)
+    assert dp.ohlcv("UNITTEST/BTC", timeframe) is not ohlcv_history
+    assert dp.ohlcv("UNITTEST/BTC", timeframe, copy=False) is ohlcv_history
+    assert not dp.ohlcv("UNITTEST/BTC", timeframe).empty
+    assert dp.ohlcv("NONESENSE/AAA", timeframe).empty
+
+    # Test with and without parameter
+    assert dp.ohlcv("UNITTEST/BTC", timeframe).equals(dp.ohlcv("UNITTEST/BTC"))
+
+    default_conf["runmode"] = RunMode.LIVE
+    dp = DataProvider(default_conf, exchange)
+    assert dp.runmode == RunMode.LIVE
+    assert isinstance(dp.ohlcv("UNITTEST/BTC", timeframe), DataFrame)
+
+    default_conf["runmode"] = RunMode.BACKTEST
+    dp = DataProvider(default_conf, exchange)
+    assert dp.runmode == RunMode.BACKTEST
+    assert dp.ohlcv("UNITTEST/BTC", timeframe).empty
+
+
+def test_historic_ohlcv(mocker, default_conf, ohlcv_history):
+    historymock = MagicMock(return_value=ohlcv_history)
+    mocker.patch("freqtrade.data.dataprovider.load_pair_history", historymock)
+
+    dp = DataProvider(default_conf, None)
+    data = dp.historic_ohlcv("UNITTEST/BTC", "5m")
+    assert isinstance(data, DataFrame)
+    assert historymock.call_count == 1
+    assert historymock.call_args_list[0][1]["timeframe"] == "5m"
+
+
+def test_historic_ohlcv_dataformat(mocker, default_conf, ohlcv_history):
+    hdf5loadmock = MagicMock(return_value=ohlcv_history)
+    jsonloadmock = MagicMock(return_value=ohlcv_history)
+    mocker.patch("freqtrade.data.history.hdf5datahandler.HDF5DataHandler._ohlcv_load", hdf5loadmock)
+    mocker.patch("freqtrade.data.history.jsondatahandler.JsonDataHandler._ohlcv_load", jsonloadmock)
+
+    default_conf["runmode"] = RunMode.BACKTEST
+    exchange = get_patched_exchange(mocker, default_conf)
+    dp = DataProvider(default_conf, exchange)
+    data = dp.historic_ohlcv("UNITTEST/BTC", "5m")
+    assert isinstance(data, DataFrame)
+    hdf5loadmock.assert_not_called()
+    jsonloadmock.assert_called_once()
+
+    # Swiching to dataformat hdf5
+    hdf5loadmock.reset_mock()
+    jsonloadmock.reset_mock()
+    default_conf["dataformat_ohlcv"] = "hdf5"
+    dp = DataProvider(default_conf, exchange)
+    data = dp.historic_ohlcv("UNITTEST/BTC", "5m")
+    assert isinstance(data, DataFrame)
+    hdf5loadmock.assert_called_once()
+    jsonloadmock.assert_not_called()
+
+
+def test_get_pair_dataframe(mocker, default_conf, ohlcv_history):
+    default_conf["runmode"] = RunMode.DRY_RUN
+    timeframe = default_conf["timeframe"]
+    exchange = get_patched_exchange(mocker, default_conf)
+    exchange._klines[("XRP/BTC", timeframe)] = ohlcv_history
+    exchange._klines[("UNITTEST/BTC", timeframe)] = ohlcv_history
+
+    dp = DataProvider(default_conf, exchange)
+    assert dp.runmode == RunMode.DRY_RUN
+    assert ohlcv_history.equals(dp.get_pair_dataframe("UNITTEST/BTC", timeframe))
+    assert isinstance(dp.get_pair_dataframe("UNITTEST/BTC", timeframe), DataFrame)
+    assert dp.get_pair_dataframe("UNITTEST/BTC", timeframe) is not ohlcv_history
+    assert not dp.get_pair_dataframe("UNITTEST/BTC", timeframe).empty
+    assert dp.get_pair_dataframe("NONESENSE/AAA", timeframe).empty
+
+    # Test with and without parameter
+    assert dp.get_pair_dataframe("UNITTEST/BTC", timeframe)\
+        .equals(dp.get_pair_dataframe("UNITTEST/BTC"))
+
+    default_conf["runmode"] = RunMode.LIVE
+    dp = DataProvider(default_conf, exchange)
+    assert dp.runmode == RunMode.LIVE
+    assert isinstance(dp.get_pair_dataframe("UNITTEST/BTC", timeframe), DataFrame)
+    assert dp.get_pair_dataframe("NONESENSE/AAA", timeframe).empty
+
+    historymock = MagicMock(return_value=ohlcv_history)
+    mocker.patch("freqtrade.data.dataprovider.load_pair_history", historymock)
+    default_conf["runmode"] = RunMode.BACKTEST
+    dp = DataProvider(default_conf, exchange)
+    assert dp.runmode == RunMode.BACKTEST
+    assert isinstance(dp.get_pair_dataframe("UNITTEST/BTC", timeframe), DataFrame)
+    # assert dp.get_pair_dataframe("NONESENSE/AAA", timeframe).empty
+
+
+def test_available_pairs(mocker, default_conf, ohlcv_history):
+    exchange = get_patched_exchange(mocker, default_conf)
+    timeframe = default_conf["timeframe"]
+    exchange._klines[("XRP/BTC", timeframe)] = ohlcv_history
+    exchange._klines[("UNITTEST/BTC", timeframe)] = ohlcv_history
+
+    dp = DataProvider(default_conf, exchange)
+    assert len(dp.available_pairs) == 2
+    assert dp.available_pairs == [("XRP/BTC", timeframe), ("UNITTEST/BTC", timeframe), ]
+
+
+def test_refresh(mocker, default_conf, ohlcv_history):
+    refresh_mock = MagicMock()
+    mocker.patch("freqtrade.exchange.Exchange.refresh_latest_ohlcv", refresh_mock)
+
+    exchange = get_patched_exchange(mocker, default_conf, id="binance")
+    timeframe = default_conf["timeframe"]
+    pairs = [("XRP/BTC", timeframe), ("UNITTEST/BTC", timeframe)]
+
+    pairs_non_trad = [("ETH/USDT", timeframe), ("BTC/TUSD", "1h")]
+
+    dp = DataProvider(default_conf, exchange)
+    dp.refresh(pairs)
+
+    assert refresh_mock.call_count == 1
+    assert len(refresh_mock.call_args[0]) == 1
+    assert len(refresh_mock.call_args[0][0]) == len(pairs)
+    assert refresh_mock.call_args[0][0] == pairs
+
+    refresh_mock.reset_mock()
+    dp.refresh(pairs, pairs_non_trad)
+    assert refresh_mock.call_count == 1
+    assert len(refresh_mock.call_args[0]) == 1
+    assert len(refresh_mock.call_args[0][0]) == len(pairs) + len(pairs_non_trad)
+    assert refresh_mock.call_args[0][0] == pairs + pairs_non_trad
+
+
+def test_orderbook(mocker, default_conf, order_book_l2):
+    api_mock = MagicMock()
+    api_mock.fetch_l2_order_book = order_book_l2
+    exchange = get_patched_exchange(mocker, default_conf, api_mock=api_mock)
+
+    dp = DataProvider(default_conf, exchange)
+    res = dp.orderbook('ETH/BTC', 5)
+    assert order_book_l2.call_count == 1
+    assert order_book_l2.call_args_list[0][0][0] == 'ETH/BTC'
+    assert order_book_l2.call_args_list[0][0][1] >= 5
+
+    assert type(res) is dict
+    assert 'bids' in res
+    assert 'asks' in res
+
+
+def test_market(mocker, default_conf, markets):
+    api_mock = MagicMock()
+    api_mock.markets = markets
+    exchange = get_patched_exchange(mocker, default_conf, api_mock=api_mock)
+
+    dp = DataProvider(default_conf, exchange)
+    res = dp.market('ETH/BTC')
+
+    assert type(res) is dict
+    assert 'symbol' in res
+    assert res['symbol'] == 'ETH/BTC'
+
+    res = dp.market('UNITTEST/BTC')
+    assert res is None
+
+
+def test_ticker(mocker, default_conf, tickers):
+    ticker_mock = MagicMock(return_value=tickers()['ETH/BTC'])
+    mocker.patch("freqtrade.exchange.Exchange.fetch_ticker", ticker_mock)
+    exchange = get_patched_exchange(mocker, default_conf)
+    dp = DataProvider(default_conf, exchange)
+    res = dp.ticker('ETH/BTC')
+    assert type(res) is dict
+    assert 'symbol' in res
+    assert res['symbol'] == 'ETH/BTC'
+
+    ticker_mock = MagicMock(side_effect=ExchangeError('Pair not found'))
+    mocker.patch("freqtrade.exchange.Exchange.fetch_ticker", ticker_mock)
+    exchange = get_patched_exchange(mocker, default_conf)
+    dp = DataProvider(default_conf, exchange)
+    res = dp.ticker('UNITTEST/BTC')
+    assert res == {}
+
+
+def test_current_whitelist(mocker, default_conf, tickers):
+    # patch default conf to volumepairlist
+    default_conf['pairlists'][0] = {'method': 'VolumePairList', "number_assets": 5}
+
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          exchange_has=MagicMock(return_value=True),
+                          get_tickers=tickers)
+    exchange = get_patched_exchange(mocker, default_conf)
+
+    pairlist = PairListManager(exchange, default_conf)
+    dp = DataProvider(default_conf, exchange, pairlist)
+
+    # Simulate volumepairs from exchange.
+    pairlist.refresh_pairlist()
+
+    assert dp.current_whitelist() == pairlist._whitelist
+    # The identity of the 2 lists should be identical
+    assert dp.current_whitelist() is pairlist._whitelist
+
+    with pytest.raises(OperationalException):
+        dp = DataProvider(default_conf, exchange)
+        dp.current_whitelist()
+
+
+def test_get_analyzed_dataframe(mocker, default_conf, ohlcv_history):
+
+    default_conf["runmode"] = RunMode.DRY_RUN
+
+    timeframe = default_conf["timeframe"]
+    exchange = get_patched_exchange(mocker, default_conf)
+
+    dp = DataProvider(default_conf, exchange)
+    dp._set_cached_df("XRP/BTC", timeframe, ohlcv_history)
+    dp._set_cached_df("UNITTEST/BTC", timeframe, ohlcv_history)
+
+    assert dp.runmode == RunMode.DRY_RUN
+    dataframe, time = dp.get_analyzed_dataframe("UNITTEST/BTC", timeframe)
+    assert ohlcv_history.equals(dataframe)
+    assert isinstance(time, datetime)
+
+    dataframe, time = dp.get_analyzed_dataframe("XRP/BTC", timeframe)
+    assert ohlcv_history.equals(dataframe)
+    assert isinstance(time, datetime)
+
+    dataframe, time = dp.get_analyzed_dataframe("NOTHING/BTC", timeframe)
+    assert dataframe.empty
+    assert isinstance(time, datetime)
+    assert time == datetime(1970, 1, 1, tzinfo=timezone.utc)
diff --git a/tests/data/test_history.py b/tests/data/test_history.py
new file mode 100644
index 000000000..905798041
--- /dev/null
+++ b/tests/data/test_history.py
@@ -0,0 +1,855 @@
+# pragma pylint: disable=missing-docstring, protected-access, C0103
+
+import json
+import uuid
+from pathlib import Path
+from shutil import copyfile
+from unittest.mock import MagicMock, PropertyMock
+
+import arrow
+import pytest
+from pandas import DataFrame
+from pandas.testing import assert_frame_equal
+
+from freqtrade.configuration import TimeRange
+from freqtrade.constants import AVAILABLE_DATAHANDLERS
+from freqtrade.data.converter import ohlcv_to_dataframe
+from freqtrade.data.history.hdf5datahandler import HDF5DataHandler
+from freqtrade.data.history.history_utils import (_download_pair_history, _download_trades_history,
+                                                  _load_cached_data_for_updating,
+                                                  convert_trades_to_ohlcv, get_timerange, load_data,
+                                                  load_pair_history, refresh_backtest_ohlcv_data,
+                                                  refresh_backtest_trades_data, refresh_data,
+                                                  validate_backtest_data)
+from freqtrade.data.history.idatahandler import IDataHandler, get_datahandler, get_datahandlerclass
+from freqtrade.data.history.jsondatahandler import JsonDataHandler, JsonGzDataHandler
+from freqtrade.exchange import timeframe_to_minutes
+from freqtrade.misc import file_dump_json
+from freqtrade.resolvers import StrategyResolver
+from tests.conftest import get_patched_exchange, log_has, log_has_re, patch_exchange
+
+
+# Change this if modifying UNITTEST/BTC testdatafile
+_BTC_UNITTEST_LENGTH = 13681
+
+
+def _backup_file(file: Path, copy_file: bool = False) -> None:
+    """
+    Backup existing file to avoid deleting the user file
+    :param file: complete path to the file
+    :param copy_file: keep file in place too.
+    :return: None
+    """
+    file_swp = str(file) + '.swp'
+    if file.is_file():
+        file.rename(file_swp)
+
+        if copy_file:
+            copyfile(file_swp, file)
+
+
+def _clean_test_file(file: Path) -> None:
+    """
+    Backup existing file to avoid deleting the user file
+    :param file: complete path to the file
+    :return: None
+    """
+    file_swp = Path(str(file) + '.swp')
+    # 1. Delete file from the test
+    if file.is_file():
+        file.unlink()
+
+    # 2. Rollback to the initial file
+    if file_swp.is_file():
+        file_swp.rename(file)
+
+
+def test_load_data_30min_timeframe(mocker, caplog, default_conf, testdatadir) -> None:
+    ld = load_pair_history(pair='UNITTEST/BTC', timeframe='30m', datadir=testdatadir)
+    assert isinstance(ld, DataFrame)
+    assert not log_has(
+        'Download history data for pair: "UNITTEST/BTC", timeframe: 30m '
+        'and store in None.', caplog
+    )
+
+
+def test_load_data_7min_timeframe(mocker, caplog, default_conf, testdatadir) -> None:
+    ld = load_pair_history(pair='UNITTEST/BTC', timeframe='7m', datadir=testdatadir)
+    assert isinstance(ld, DataFrame)
+    assert ld.empty
+    assert log_has(
+        'No history data for pair: "UNITTEST/BTC", timeframe: 7m. '
+        'Use `freqtrade download-data` to download the data', caplog
+    )
+
+
+def test_load_data_1min_timeframe(ohlcv_history, mocker, caplog, testdatadir) -> None:
+    mocker.patch('freqtrade.exchange.Exchange.get_historic_ohlcv', return_value=ohlcv_history)
+    file = testdatadir / 'UNITTEST_BTC-1m.json'
+    _backup_file(file, copy_file=True)
+    load_data(datadir=testdatadir, timeframe='1m', pairs=['UNITTEST/BTC'])
+    assert file.is_file()
+    assert not log_has(
+        'Download history data for pair: "UNITTEST/BTC", interval: 1m '
+        'and store in None.', caplog
+    )
+    _clean_test_file(file)
+
+
+def test_load_data_startup_candles(mocker, caplog, default_conf, testdatadir) -> None:
+    ltfmock = mocker.patch(
+        'freqtrade.data.history.jsondatahandler.JsonDataHandler._ohlcv_load',
+        MagicMock(return_value=DataFrame()))
+    timerange = TimeRange('date', None, 1510639620, 0)
+    load_pair_history(pair='UNITTEST/BTC', timeframe='1m',
+                      datadir=testdatadir, timerange=timerange,
+                      startup_candles=20,)
+
+    assert ltfmock.call_count == 1
+    assert ltfmock.call_args_list[0][1]['timerange'] != timerange
+    # startts is 20 minutes earlier
+    assert ltfmock.call_args_list[0][1]['timerange'].startts == timerange.startts - 20 * 60
+
+
+def test_load_data_with_new_pair_1min(ohlcv_history_list, mocker, caplog,
+                                      default_conf, testdatadir) -> None:
+    """
+    Test load_pair_history() with 1 min timeframe
+    """
+    mocker.patch('freqtrade.exchange.Exchange.get_historic_ohlcv', return_value=ohlcv_history_list)
+    exchange = get_patched_exchange(mocker, default_conf)
+    file = testdatadir / 'MEME_BTC-1m.json'
+
+    _backup_file(file)
+    # do not download a new pair if refresh_pairs isn't set
+    load_pair_history(datadir=testdatadir, timeframe='1m', pair='MEME/BTC')
+    assert not file.is_file()
+    assert log_has(
+        'No history data for pair: "MEME/BTC", timeframe: 1m. '
+        'Use `freqtrade download-data` to download the data', caplog
+    )
+
+    # download a new pair if refresh_pairs is set
+    refresh_data(datadir=testdatadir, timeframe='1m', pairs=['MEME/BTC'],
+                 exchange=exchange)
+    load_pair_history(datadir=testdatadir, timeframe='1m', pair='MEME/BTC')
+    assert file.is_file()
+    assert log_has_re(
+        'Download history data for pair: "MEME/BTC", timeframe: 1m '
+        'and store in .*', caplog
+    )
+    _clean_test_file(file)
+
+
+def test_testdata_path(testdatadir) -> None:
+    assert str(Path('tests') / 'testdata') in str(testdatadir)
+
+
+@pytest.mark.parametrize("pair,expected_result", [
+    ("ETH/BTC", 'freqtrade/hello/world/ETH_BTC-5m.json'),
+    ("Fabric Token/ETH", 'freqtrade/hello/world/Fabric_Token_ETH-5m.json'),
+    ("ETHH20", 'freqtrade/hello/world/ETHH20-5m.json'),
+    (".XBTBON2H", 'freqtrade/hello/world/_XBTBON2H-5m.json'),
+    ("ETHUSD.d", 'freqtrade/hello/world/ETHUSD_d-5m.json'),
+    ("ACC_OLD/BTC", 'freqtrade/hello/world/ACC_OLD_BTC-5m.json'),
+])
+def test_json_pair_data_filename(pair, expected_result):
+    fn = JsonDataHandler._pair_data_filename(Path('freqtrade/hello/world'), pair, '5m')
+    assert isinstance(fn, Path)
+    assert fn == Path(expected_result)
+    fn = JsonGzDataHandler._pair_data_filename(Path('freqtrade/hello/world'), pair, '5m')
+    assert isinstance(fn, Path)
+    assert fn == Path(expected_result + '.gz')
+
+
+@pytest.mark.parametrize("pair,expected_result", [
+    ("ETH/BTC", 'freqtrade/hello/world/ETH_BTC-trades.json'),
+    ("Fabric Token/ETH", 'freqtrade/hello/world/Fabric_Token_ETH-trades.json'),
+    ("ETHH20", 'freqtrade/hello/world/ETHH20-trades.json'),
+    (".XBTBON2H", 'freqtrade/hello/world/_XBTBON2H-trades.json'),
+    ("ETHUSD.d", 'freqtrade/hello/world/ETHUSD_d-trades.json'),
+    ("ACC_OLD_BTC", 'freqtrade/hello/world/ACC_OLD_BTC-trades.json'),
+])
+def test_json_pair_trades_filename(pair, expected_result):
+    fn = JsonDataHandler._pair_trades_filename(Path('freqtrade/hello/world'), pair)
+    assert isinstance(fn, Path)
+    assert fn == Path(expected_result)
+
+    fn = JsonGzDataHandler._pair_trades_filename(Path('freqtrade/hello/world'), pair)
+    assert isinstance(fn, Path)
+    assert fn == Path(expected_result + '.gz')
+
+
+def test_load_cached_data_for_updating(mocker, testdatadir) -> None:
+
+    data_handler = get_datahandler(testdatadir, 'json')
+
+    test_data = None
+    test_filename = testdatadir.joinpath('UNITTEST_BTC-1m.json')
+    with open(test_filename, "rt") as file:
+        test_data = json.load(file)
+
+    test_data_df = ohlcv_to_dataframe(test_data, '1m', 'UNITTEST/BTC',
+                                      fill_missing=False, drop_incomplete=False)
+    # now = last cached item + 1 hour
+    now_ts = test_data[-1][0] / 1000 + 60 * 60
+    mocker.patch('arrow.utcnow', return_value=arrow.get(now_ts))
+
+    # timeframe starts earlier than the cached data
+    # should fully update data
+    timerange = TimeRange('date', None, test_data[0][0] / 1000 - 1, 0)
+    data, start_ts = _load_cached_data_for_updating('UNITTEST/BTC', '1m', timerange, data_handler)
+    assert data.empty
+    assert start_ts == test_data[0][0] - 1000
+
+    # timeframe starts in the center of the cached data
+    # should return the chached data w/o the last item
+    timerange = TimeRange('date', None, test_data[0][0] / 1000 + 1, 0)
+    data, start_ts = _load_cached_data_for_updating('UNITTEST/BTC', '1m', timerange, data_handler)
+
+    assert_frame_equal(data, test_data_df.iloc[:-1])
+    assert test_data[-2][0] <= start_ts < test_data[-1][0]
+
+    # timeframe starts after the chached data
+    # should return the chached data w/o the last item
+    timerange = TimeRange('date', None, test_data[-1][0] / 1000 + 100, 0)
+    data, start_ts = _load_cached_data_for_updating('UNITTEST/BTC', '1m', timerange, data_handler)
+    assert_frame_equal(data, test_data_df.iloc[:-1])
+    assert test_data[-2][0] <= start_ts < test_data[-1][0]
+
+    # no datafile exist
+    # should return timestamp start time
+    timerange = TimeRange('date', None, now_ts - 10000, 0)
+    data, start_ts = _load_cached_data_for_updating('NONEXIST/BTC', '1m', timerange, data_handler)
+    assert data.empty
+    assert start_ts == (now_ts - 10000) * 1000
+
+    # no datafile exist, no timeframe is set
+    # should return an empty array and None
+    data, start_ts = _load_cached_data_for_updating('NONEXIST/BTC', '1m', None, data_handler)
+    assert data.empty
+    assert start_ts is None
+
+
+def test_download_pair_history(ohlcv_history_list, mocker, default_conf, testdatadir) -> None:
+    mocker.patch('freqtrade.exchange.Exchange.get_historic_ohlcv', return_value=ohlcv_history_list)
+    exchange = get_patched_exchange(mocker, default_conf)
+    file1_1 = testdatadir / 'MEME_BTC-1m.json'
+    file1_5 = testdatadir / 'MEME_BTC-5m.json'
+    file2_1 = testdatadir / 'CFI_BTC-1m.json'
+    file2_5 = testdatadir / 'CFI_BTC-5m.json'
+
+    _backup_file(file1_1)
+    _backup_file(file1_5)
+    _backup_file(file2_1)
+    _backup_file(file2_5)
+
+    assert not file1_1.is_file()
+    assert not file2_1.is_file()
+
+    assert _download_pair_history(datadir=testdatadir, exchange=exchange,
+                                  pair='MEME/BTC',
+                                  timeframe='1m')
+    assert _download_pair_history(datadir=testdatadir, exchange=exchange,
+                                  pair='CFI/BTC',
+                                  timeframe='1m')
+    assert not exchange._pairs_last_refresh_time
+    assert file1_1.is_file()
+    assert file2_1.is_file()
+
+    # clean files freshly downloaded
+    _clean_test_file(file1_1)
+    _clean_test_file(file2_1)
+
+    assert not file1_5.is_file()
+    assert not file2_5.is_file()
+
+    assert _download_pair_history(datadir=testdatadir, exchange=exchange,
+                                  pair='MEME/BTC',
+                                  timeframe='5m')
+    assert _download_pair_history(datadir=testdatadir, exchange=exchange,
+                                  pair='CFI/BTC',
+                                  timeframe='5m')
+    assert not exchange._pairs_last_refresh_time
+    assert file1_5.is_file()
+    assert file2_5.is_file()
+
+    # clean files freshly downloaded
+    _clean_test_file(file1_5)
+    _clean_test_file(file2_5)
+
+
+def test_download_pair_history2(mocker, default_conf, testdatadir) -> None:
+    tick = [
+        [1509836520000, 0.00162008, 0.00162008, 0.00162008, 0.00162008, 108.14853839],
+        [1509836580000, 0.00161, 0.00161, 0.00161, 0.00161, 82.390199]
+    ]
+    json_dump_mock = mocker.patch(
+        'freqtrade.data.history.jsondatahandler.JsonDataHandler.ohlcv_store',
+        return_value=None)
+    mocker.patch('freqtrade.exchange.Exchange.get_historic_ohlcv', return_value=tick)
+    exchange = get_patched_exchange(mocker, default_conf)
+    _download_pair_history(testdatadir, exchange, pair="UNITTEST/BTC", timeframe='1m')
+    _download_pair_history(testdatadir, exchange, pair="UNITTEST/BTC", timeframe='3m')
+    assert json_dump_mock.call_count == 2
+
+
+def test_download_backtesting_data_exception(ohlcv_history, mocker, caplog,
+                                             default_conf, testdatadir) -> None:
+    mocker.patch('freqtrade.exchange.Exchange.get_historic_ohlcv',
+                 side_effect=Exception('File Error'))
+
+    exchange = get_patched_exchange(mocker, default_conf)
+
+    file1_1 = testdatadir / 'MEME_BTC-1m.json'
+    file1_5 = testdatadir / 'MEME_BTC-5m.json'
+    _backup_file(file1_1)
+    _backup_file(file1_5)
+
+    assert not _download_pair_history(datadir=testdatadir, exchange=exchange,
+                                      pair='MEME/BTC',
+                                      timeframe='1m')
+    # clean files freshly downloaded
+    _clean_test_file(file1_1)
+    _clean_test_file(file1_5)
+    assert log_has(
+        'Failed to download history data for pair: "MEME/BTC", timeframe: 1m. '
+        'Error: File Error', caplog
+    )
+
+
+def test_load_partial_missing(testdatadir, caplog) -> None:
+    # Make sure we start fresh - test missing data at start
+    start = arrow.get('2018-01-01T00:00:00')
+    end = arrow.get('2018-01-11T00:00:00')
+    data = load_data(testdatadir, '5m', ['UNITTEST/BTC'], startup_candles=20,
+                     timerange=TimeRange('date', 'date', start.int_timestamp, end.int_timestamp))
+    assert log_has(
+        'Using indicator startup period: 20 ...', caplog
+    )
+    # timedifference in 5 minutes
+    td = ((end - start).total_seconds() // 60 // 5) + 1
+    assert td != len(data['UNITTEST/BTC'])
+    start_real = data['UNITTEST/BTC'].iloc[0, 0]
+    assert log_has(f'Missing data at start for pair '
+                   f'UNITTEST/BTC, data starts at {start_real.strftime("%Y-%m-%d %H:%M:%S")}',
+                   caplog)
+    # Make sure we start fresh - test missing data at end
+    caplog.clear()
+    start = arrow.get('2018-01-10T00:00:00')
+    end = arrow.get('2018-02-20T00:00:00')
+    data = load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'],
+                     timerange=TimeRange('date', 'date', start.int_timestamp, end.int_timestamp))
+    # timedifference in 5 minutes
+    td = ((end - start).total_seconds() // 60 // 5) + 1
+    assert td != len(data['UNITTEST/BTC'])
+
+    # Shift endtime with +5 - as last candle is dropped (partial candle)
+    end_real = arrow.get(data['UNITTEST/BTC'].iloc[-1, 0]).shift(minutes=5)
+    assert log_has(f'Missing data at end for pair '
+                   f'UNITTEST/BTC, data ends at {end_real.strftime("%Y-%m-%d %H:%M:%S")}',
+                   caplog)
+
+
+def test_init(default_conf, mocker) -> None:
+    assert {} == load_data(
+        datadir=Path(''),
+        pairs=[],
+        timeframe=default_conf['timeframe']
+    )
+
+
+def test_init_with_refresh(default_conf, mocker) -> None:
+    exchange = get_patched_exchange(mocker, default_conf)
+    refresh_data(
+        datadir=Path(''),
+        pairs=[],
+        timeframe=default_conf['timeframe'],
+        exchange=exchange
+    )
+    assert {} == load_data(
+        datadir=Path(''),
+        pairs=[],
+        timeframe=default_conf['timeframe']
+    )
+
+
+def test_file_dump_json_tofile(testdatadir) -> None:
+    file = testdatadir / 'test_{id}.json'.format(id=str(uuid.uuid4()))
+    data = {'bar': 'foo'}
+
+    # check the file we will create does not exist
+    assert not file.is_file()
+
+    # Create the Json file
+    file_dump_json(file, data)
+
+    # Check the file was create
+    assert file.is_file()
+
+    # Open the Json file created and test the data is in it
+    with file.open() as data_file:
+        json_from_file = json.load(data_file)
+
+    assert 'bar' in json_from_file
+    assert json_from_file['bar'] == 'foo'
+
+    # Remove the file
+    _clean_test_file(file)
+
+
+def test_get_timerange(default_conf, mocker, testdatadir) -> None:
+    patch_exchange(mocker)
+
+    default_conf.update({'strategy': 'DefaultStrategy'})
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    data = strategy.ohlcvdata_to_dataframe(
+        load_data(
+            datadir=testdatadir,
+            timeframe='1m',
+            pairs=['UNITTEST/BTC']
+        )
+    )
+    min_date, max_date = get_timerange(data)
+    assert min_date.isoformat() == '2017-11-04T23:02:00+00:00'
+    assert max_date.isoformat() == '2017-11-14T22:58:00+00:00'
+
+
+def test_validate_backtest_data_warn(default_conf, mocker, caplog, testdatadir) -> None:
+    patch_exchange(mocker)
+
+    default_conf.update({'strategy': 'DefaultStrategy'})
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    data = strategy.ohlcvdata_to_dataframe(
+        load_data(
+            datadir=testdatadir,
+            timeframe='1m',
+            pairs=['UNITTEST/BTC'],
+            fill_up_missing=False
+        )
+    )
+    min_date, max_date = get_timerange(data)
+    caplog.clear()
+    assert validate_backtest_data(data['UNITTEST/BTC'], 'UNITTEST/BTC',
+                                  min_date, max_date, timeframe_to_minutes('1m'))
+    assert len(caplog.record_tuples) == 1
+    assert log_has(
+        "UNITTEST/BTC has missing frames: expected 14396, got 13680, that's 716 missing values",
+        caplog)
+
+
+def test_validate_backtest_data(default_conf, mocker, caplog, testdatadir) -> None:
+    patch_exchange(mocker)
+
+    default_conf.update({'strategy': 'DefaultStrategy'})
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    timerange = TimeRange('index', 'index', 200, 250)
+    data = strategy.ohlcvdata_to_dataframe(
+        load_data(
+            datadir=testdatadir,
+            timeframe='5m',
+            pairs=['UNITTEST/BTC'],
+            timerange=timerange
+        )
+    )
+
+    min_date, max_date = get_timerange(data)
+    caplog.clear()
+    assert not validate_backtest_data(data['UNITTEST/BTC'], 'UNITTEST/BTC',
+                                      min_date, max_date, timeframe_to_minutes('5m'))
+    assert len(caplog.record_tuples) == 0
+
+
+def test_refresh_backtest_ohlcv_data(mocker, default_conf, markets, caplog, testdatadir):
+    dl_mock = mocker.patch('freqtrade.data.history.history_utils._download_pair_history',
+                           MagicMock())
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets)
+    )
+    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+    mocker.patch.object(Path, "unlink", MagicMock())
+
+    ex = get_patched_exchange(mocker, default_conf)
+    timerange = TimeRange.parse_timerange("20190101-20190102")
+    refresh_backtest_ohlcv_data(exchange=ex, pairs=["ETH/BTC", "XRP/BTC"],
+                                timeframes=["1m", "5m"], datadir=testdatadir,
+                                timerange=timerange, erase=True
+                                )
+
+    assert dl_mock.call_count == 4
+    assert dl_mock.call_args[1]['timerange'].starttype == 'date'
+
+    assert log_has("Downloading pair ETH/BTC, interval 1m.", caplog)
+
+
+def test_download_data_no_markets(mocker, default_conf, caplog, testdatadir):
+    dl_mock = mocker.patch('freqtrade.data.history.history_utils._download_pair_history',
+                           MagicMock())
+
+    ex = get_patched_exchange(mocker, default_conf)
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets', PropertyMock(return_value={})
+    )
+    timerange = TimeRange.parse_timerange("20190101-20190102")
+    unav_pairs = refresh_backtest_ohlcv_data(exchange=ex, pairs=["BTT/BTC", "LTC/USDT"],
+                                             timeframes=["1m", "5m"],
+                                             datadir=testdatadir,
+                                             timerange=timerange, erase=False
+                                             )
+
+    assert dl_mock.call_count == 0
+    assert "BTT/BTC" in unav_pairs
+    assert "LTC/USDT" in unav_pairs
+    assert log_has("Skipping pair BTT/BTC...", caplog)
+
+
+def test_refresh_backtest_trades_data(mocker, default_conf, markets, caplog, testdatadir):
+    dl_mock = mocker.patch('freqtrade.data.history.history_utils._download_trades_history',
+                           MagicMock())
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets)
+    )
+    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+    mocker.patch.object(Path, "unlink", MagicMock())
+
+    ex = get_patched_exchange(mocker, default_conf)
+    timerange = TimeRange.parse_timerange("20190101-20190102")
+    unavailable_pairs = refresh_backtest_trades_data(exchange=ex,
+                                                     pairs=["ETH/BTC", "XRP/BTC", "XRP/ETH"],
+                                                     datadir=testdatadir,
+                                                     timerange=timerange, erase=True
+                                                     )
+
+    assert dl_mock.call_count == 2
+    assert dl_mock.call_args[1]['timerange'].starttype == 'date'
+
+    assert log_has("Downloading trades for pair ETH/BTC.", caplog)
+    assert unavailable_pairs == ["XRP/ETH"]
+    assert log_has("Skipping pair XRP/ETH...", caplog)
+
+
+def test_download_trades_history(trades_history, mocker, default_conf, testdatadir, caplog) -> None:
+
+    ght_mock = MagicMock(side_effect=lambda pair, *args, **kwargs: (pair, trades_history))
+    mocker.patch('freqtrade.exchange.Exchange.get_historic_trades',
+                 ght_mock)
+    exchange = get_patched_exchange(mocker, default_conf)
+    file1 = testdatadir / 'ETH_BTC-trades.json.gz'
+    data_handler = get_datahandler(testdatadir, data_format='jsongz')
+    _backup_file(file1)
+
+    assert not file1.is_file()
+
+    assert _download_trades_history(data_handler=data_handler, exchange=exchange,
+                                    pair='ETH/BTC')
+    assert log_has("New Amount of trades: 5", caplog)
+    assert file1.is_file()
+
+    ght_mock.reset_mock()
+    since_time = int(trades_history[-3][0] // 1000)
+    since_time2 = int(trades_history[-1][0] // 1000)
+    timerange = TimeRange('date', None, since_time, 0)
+    assert _download_trades_history(data_handler=data_handler, exchange=exchange,
+                                    pair='ETH/BTC', timerange=timerange)
+
+    assert ght_mock.call_count == 1
+    # Check this in seconds - since we had to convert to seconds above too.
+    assert int(ght_mock.call_args_list[0][1]['since'] // 1000) == since_time2 - 5
+    assert ght_mock.call_args_list[0][1]['from_id'] is not None
+
+    # clean files freshly downloaded
+    _clean_test_file(file1)
+
+    mocker.patch('freqtrade.exchange.Exchange.get_historic_trades',
+                 MagicMock(side_effect=ValueError))
+
+    assert not _download_trades_history(data_handler=data_handler, exchange=exchange,
+                                        pair='ETH/BTC')
+    assert log_has_re('Failed to download historic trades for pair: "ETH/BTC".*', caplog)
+
+    file2 = testdatadir / 'XRP_ETH-trades.json.gz'
+
+    _backup_file(file2, True)
+
+    ght_mock.reset_mock()
+    mocker.patch('freqtrade.exchange.Exchange.get_historic_trades',
+                 ght_mock)
+    # Since before first start date
+    since_time = int(trades_history[0][0] // 1000) - 500
+    timerange = TimeRange('date', None, since_time, 0)
+
+    assert _download_trades_history(data_handler=data_handler, exchange=exchange,
+                                    pair='XRP/ETH', timerange=timerange)
+
+    assert ght_mock.call_count == 1
+
+    assert int(ght_mock.call_args_list[0][1]['since'] // 1000) == since_time
+    assert ght_mock.call_args_list[0][1]['from_id'] is None
+    assert log_has_re(r'Start earlier than available data. Redownloading trades for.*', caplog)
+    _clean_test_file(file2)
+
+
+def test_convert_trades_to_ohlcv(mocker, default_conf, testdatadir, caplog):
+
+    pair = 'XRP/ETH'
+    file1 = testdatadir / 'XRP_ETH-1m.json'
+    file5 = testdatadir / 'XRP_ETH-5m.json'
+    # Compare downloaded dataset with converted dataset
+    dfbak_1m = load_pair_history(datadir=testdatadir, timeframe="1m", pair=pair)
+    dfbak_5m = load_pair_history(datadir=testdatadir, timeframe="5m", pair=pair)
+
+    _backup_file(file1, copy_file=True)
+    _backup_file(file5)
+
+    tr = TimeRange.parse_timerange('20191011-20191012')
+
+    convert_trades_to_ohlcv([pair], timeframes=['1m', '5m'],
+                            datadir=testdatadir, timerange=tr, erase=True)
+
+    assert log_has("Deleting existing data for pair XRP/ETH, interval 1m.", caplog)
+    # Load new data
+    df_1m = load_pair_history(datadir=testdatadir, timeframe="1m", pair=pair)
+    df_5m = load_pair_history(datadir=testdatadir, timeframe="5m", pair=pair)
+
+    assert df_1m.equals(dfbak_1m)
+    assert df_5m.equals(dfbak_5m)
+
+    _clean_test_file(file1)
+    _clean_test_file(file5)
+
+    assert not log_has('Could not convert NoDatapair to OHLCV.', caplog)
+
+    convert_trades_to_ohlcv(['NoDatapair'], timeframes=['1m', '5m'],
+                            datadir=testdatadir, timerange=tr, erase=True)
+    assert log_has('Could not convert NoDatapair to OHLCV.', caplog)
+
+
+def test_datahandler_ohlcv_get_pairs(testdatadir):
+    pairs = JsonDataHandler.ohlcv_get_pairs(testdatadir, '5m')
+    # Convert to set to avoid failures due to sorting
+    assert set(pairs) == {'UNITTEST/BTC', 'XLM/BTC', 'ETH/BTC', 'TRX/BTC', 'LTC/BTC',
+                          'XMR/BTC', 'ZEC/BTC', 'ADA/BTC', 'ETC/BTC', 'NXT/BTC',
+                          'DASH/BTC', 'XRP/ETH'}
+
+    pairs = JsonGzDataHandler.ohlcv_get_pairs(testdatadir, '8m')
+    assert set(pairs) == {'UNITTEST/BTC'}
+
+    pairs = HDF5DataHandler.ohlcv_get_pairs(testdatadir, '5m')
+    assert set(pairs) == {'UNITTEST/BTC'}
+
+
+def test_datahandler_ohlcv_get_available_data(testdatadir):
+    paircombs = JsonDataHandler.ohlcv_get_available_data(testdatadir)
+    # Convert to set to avoid failures due to sorting
+    assert set(paircombs) == {('UNITTEST/BTC', '5m'), ('ETH/BTC', '5m'), ('XLM/BTC', '5m'),
+                              ('TRX/BTC', '5m'), ('LTC/BTC', '5m'), ('XMR/BTC', '5m'),
+                              ('ZEC/BTC', '5m'), ('UNITTEST/BTC', '1m'), ('ADA/BTC', '5m'),
+                              ('ETC/BTC', '5m'), ('NXT/BTC', '5m'), ('DASH/BTC', '5m'),
+                              ('XRP/ETH', '1m'), ('XRP/ETH', '5m'), ('UNITTEST/BTC', '30m'),
+                              ('UNITTEST/BTC', '8m')}
+
+    paircombs = JsonGzDataHandler.ohlcv_get_available_data(testdatadir)
+    assert set(paircombs) == {('UNITTEST/BTC', '8m')}
+    paircombs = HDF5DataHandler.ohlcv_get_available_data(testdatadir)
+    assert set(paircombs) == {('UNITTEST/BTC', '5m')}
+
+
+def test_jsondatahandler_trades_get_pairs(testdatadir):
+    pairs = JsonGzDataHandler.trades_get_pairs(testdatadir)
+    # Convert to set to avoid failures due to sorting
+    assert set(pairs) == {'XRP/ETH', 'XRP/OLD'}
+
+
+def test_jsondatahandler_ohlcv_purge(mocker, testdatadir):
+    mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+    unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
+    dh = JsonGzDataHandler(testdatadir)
+    assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m')
+    assert unlinkmock.call_count == 0
+
+    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+    assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m')
+    assert unlinkmock.call_count == 1
+
+
+def test_jsondatahandler_trades_load(testdatadir, caplog):
+    dh = JsonGzDataHandler(testdatadir)
+    logmsg = "Old trades format detected - converting"
+    dh.trades_load('XRP/ETH')
+    assert not log_has(logmsg, caplog)
+
+    # Test conversation is happening
+    dh.trades_load('XRP/OLD')
+    assert log_has(logmsg, caplog)
+
+
+def test_jsondatahandler_trades_purge(mocker, testdatadir):
+    mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+    unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
+    dh = JsonGzDataHandler(testdatadir)
+    assert not dh.trades_purge('UNITTEST/NONEXIST')
+    assert unlinkmock.call_count == 0
+
+    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+    assert dh.trades_purge('UNITTEST/NONEXIST')
+    assert unlinkmock.call_count == 1
+
+
+@pytest.mark.parametrize('datahandler', AVAILABLE_DATAHANDLERS)
+def test_datahandler_ohlcv_append(datahandler, testdatadir, ):
+    dh = get_datahandler(testdatadir, datahandler)
+    with pytest.raises(NotImplementedError):
+        dh.ohlcv_append('UNITTEST/ETH', '5m', DataFrame())
+
+
+@pytest.mark.parametrize('datahandler', AVAILABLE_DATAHANDLERS)
+def test_datahandler_trades_append(datahandler, testdatadir):
+    dh = get_datahandler(testdatadir, datahandler)
+    with pytest.raises(NotImplementedError):
+        dh.trades_append('UNITTEST/ETH', [])
+
+
+def test_hdf5datahandler_trades_get_pairs(testdatadir):
+    pairs = HDF5DataHandler.trades_get_pairs(testdatadir)
+    # Convert to set to avoid failures due to sorting
+    assert set(pairs) == {'XRP/ETH'}
+
+
+def test_hdf5datahandler_trades_load(testdatadir):
+    dh = HDF5DataHandler(testdatadir)
+    trades = dh.trades_load('XRP/ETH')
+    assert isinstance(trades, list)
+
+    trades1 = dh.trades_load('UNITTEST/NONEXIST')
+    assert trades1 == []
+    # data goes from 2019-10-11 - 2019-10-13
+    timerange = TimeRange.parse_timerange('20191011-20191012')
+
+    trades2 = dh._trades_load('XRP/ETH', timerange)
+    assert len(trades) > len(trades2)
+    # Check that ID is None (If it's nan, it's wrong)
+    assert trades2[0][2] is None
+
+    # unfiltered load has trades before starttime
+    assert len([t for t in trades if t[0] < timerange.startts * 1000]) >= 0
+    # filtered list does not have trades before starttime
+    assert len([t for t in trades2 if t[0] < timerange.startts * 1000]) == 0
+    # unfiltered load has trades after endtime
+    assert len([t for t in trades if t[0] > timerange.stopts * 1000]) > 0
+    # filtered list does not have trades after endtime
+    assert len([t for t in trades2 if t[0] > timerange.stopts * 1000]) == 0
+
+
+def test_hdf5datahandler_trades_store(testdatadir):
+    dh = HDF5DataHandler(testdatadir)
+    trades = dh.trades_load('XRP/ETH')
+
+    dh.trades_store('XRP/NEW', trades)
+    file = testdatadir / 'XRP_NEW-trades.h5'
+    assert file.is_file()
+    # Load trades back
+    trades_new = dh.trades_load('XRP/NEW')
+
+    assert len(trades_new) == len(trades)
+    assert trades[0][0] == trades_new[0][0]
+    assert trades[0][1] == trades_new[0][1]
+    # assert trades[0][2] == trades_new[0][2]  # This is nan - so comparison does not make sense
+    assert trades[0][3] == trades_new[0][3]
+    assert trades[0][4] == trades_new[0][4]
+    assert trades[0][5] == trades_new[0][5]
+    assert trades[0][6] == trades_new[0][6]
+    assert trades[-1][0] == trades_new[-1][0]
+    assert trades[-1][1] == trades_new[-1][1]
+    # assert trades[-1][2] == trades_new[-1][2]  # This is nan - so comparison does not make sense
+    assert trades[-1][3] == trades_new[-1][3]
+    assert trades[-1][4] == trades_new[-1][4]
+    assert trades[-1][5] == trades_new[-1][5]
+    assert trades[-1][6] == trades_new[-1][6]
+
+    _clean_test_file(file)
+
+
+def test_hdf5datahandler_trades_purge(mocker, testdatadir):
+    mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+    unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
+    dh = HDF5DataHandler(testdatadir)
+    assert not dh.trades_purge('UNITTEST/NONEXIST')
+    assert unlinkmock.call_count == 0
+
+    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+    assert dh.trades_purge('UNITTEST/NONEXIST')
+    assert unlinkmock.call_count == 1
+
+
+def test_hdf5datahandler_ohlcv_load_and_resave(testdatadir):
+    dh = HDF5DataHandler(testdatadir)
+    ohlcv = dh.ohlcv_load('UNITTEST/BTC', '5m')
+    assert isinstance(ohlcv, DataFrame)
+    assert len(ohlcv) > 0
+
+    file = testdatadir / 'UNITTEST_NEW-5m.h5'
+    assert not file.is_file()
+
+    dh.ohlcv_store('UNITTEST/NEW', '5m', ohlcv)
+    assert file.is_file()
+
+    assert not ohlcv[ohlcv['date'] < '2018-01-15'].empty
+
+    # Data gores from 2018-01-10 - 2018-01-30
+    timerange = TimeRange.parse_timerange('20180115-20180119')
+
+    # Call private function to ensure timerange is filtered in hdf5
+    ohlcv = dh._ohlcv_load('UNITTEST/BTC', '5m', timerange)
+    ohlcv1 = dh._ohlcv_load('UNITTEST/NEW', '5m', timerange)
+    assert len(ohlcv) == len(ohlcv1)
+    assert ohlcv.equals(ohlcv1)
+    assert ohlcv[ohlcv['date'] < '2018-01-15'].empty
+    assert ohlcv[ohlcv['date'] > '2018-01-19'].empty
+
+    _clean_test_file(file)
+
+    # Try loading inexisting file
+    ohlcv = dh.ohlcv_load('UNITTEST/NONEXIST', '5m')
+    assert ohlcv.empty
+
+
+def test_hdf5datahandler_ohlcv_purge(mocker, testdatadir):
+    mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+    unlinkmock = mocker.patch.object(Path, "unlink", MagicMock())
+    dh = HDF5DataHandler(testdatadir)
+    assert not dh.ohlcv_purge('UNITTEST/NONEXIST', '5m')
+    assert unlinkmock.call_count == 0
+
+    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+    assert dh.ohlcv_purge('UNITTEST/NONEXIST', '5m')
+    assert unlinkmock.call_count == 1
+
+
+def test_gethandlerclass():
+    cl = get_datahandlerclass('json')
+    assert cl == JsonDataHandler
+    assert issubclass(cl, IDataHandler)
+    cl = get_datahandlerclass('jsongz')
+    assert cl == JsonGzDataHandler
+    assert issubclass(cl, IDataHandler)
+    assert issubclass(cl, JsonDataHandler)
+    cl = get_datahandlerclass('hdf5')
+    assert cl == HDF5DataHandler
+    assert issubclass(cl, IDataHandler)
+    with pytest.raises(ValueError, match=r"No datahandler for .*"):
+        get_datahandlerclass('DeadBeef')
+
+
+def test_get_datahandler(testdatadir):
+    dh = get_datahandler(testdatadir, 'json')
+    assert type(dh) == JsonDataHandler
+    dh = get_datahandler(testdatadir, 'jsongz')
+    assert type(dh) == JsonGzDataHandler
+    dh1 = get_datahandler(testdatadir, 'jsongz', dh)
+    assert id(dh1) == id(dh)
+
+    dh = get_datahandler(testdatadir, 'hdf5')
+    assert type(dh) == HDF5DataHandler
diff --git a/freqtrade/tests/rpc/__init__.py b/tests/edge/__init__.py
similarity index 100%
rename from freqtrade/tests/rpc/__init__.py
rename to tests/edge/__init__.py
diff --git a/freqtrade/tests/edge/test_edge.py b/tests/edge/test_edge.py
similarity index 57%
rename from freqtrade/tests/edge/test_edge.py
rename to tests/edge/test_edge.py
index 45b8e609e..f25dad35b 100644
--- a/freqtrade/tests/edge/test_edge.py
+++ b/tests/edge/test_edge.py
@@ -10,14 +10,14 @@ import numpy as np
 import pytest
 from pandas import DataFrame, to_datetime
 
-from freqtrade import OperationalException
-from freqtrade.data.converter import parse_ticker_dataframe
+from freqtrade.data.converter import ohlcv_to_dataframe
 from freqtrade.edge import Edge, PairInfo
+from freqtrade.exceptions import OperationalException
 from freqtrade.strategy.interface import SellType
-from freqtrade.tests.conftest import get_patched_freqtradebot, log_has
-from freqtrade.tests.optimize import (BTContainer, BTrade,
-                                      _build_backtest_dataframe,
-                                      _get_frame_time_from_offset)
+from tests.conftest import get_patched_freqtradebot, log_has
+from tests.optimize import (BTContainer, BTrade, _build_backtest_dataframe,
+                            _get_frame_time_from_offset)
+
 
 # Cases to be tested:
 # 1) Open trade should be removed from the end
@@ -27,8 +27,8 @@ from freqtrade.tests.optimize import (BTContainer, BTrade,
 # 5) Stoploss and sell are hit. should sell on stoploss
 ####################################################################
 
-ticker_start_time = arrow.get(2018, 10, 3)
-ticker_interval_in_minute = 60
+tests_start_time = arrow.get(2018, 10, 3)
+timeframe_in_minute = 60
 _ohlc = {'date': 0, 'buy': 1, 'open': 2, 'high': 3, 'low': 4, 'close': 5, 'sell': 6, 'volume': 7}
 
 # Helpers for this test file
@@ -44,13 +44,13 @@ def _validate_ohlc(buy_ohlc_sell_matrice):
 
 def _build_dataframe(buy_ohlc_sell_matrice):
     _validate_ohlc(buy_ohlc_sell_matrice)
-    tickers = []
+    data = []
     for ohlc in buy_ohlc_sell_matrice:
-        ticker = {
-            'date': ticker_start_time.shift(
+        d = {
+            'date': tests_start_time.shift(
                 minutes=(
                     ohlc[0] *
-                    ticker_interval_in_minute)).timestamp *
+                    timeframe_in_minute)).int_timestamp *
             1000,
             'buy': ohlc[1],
             'open': ohlc[2],
@@ -58,9 +58,9 @@ def _build_dataframe(buy_ohlc_sell_matrice):
             'low': ohlc[4],
             'close': ohlc[5],
             'sell': ohlc[6]}
-        tickers.append(ticker)
+        data.append(d)
 
-    frame = DataFrame(tickers)
+    frame = DataFrame(data)
     frame['date'] = to_datetime(frame['date'],
                                 unit='ms',
                                 utc=True,
@@ -70,8 +70,8 @@ def _build_dataframe(buy_ohlc_sell_matrice):
 
 
 def _time_on_candle(number):
-    return np.datetime64(ticker_start_time.shift(
-        minutes=(number * ticker_interval_in_minute)).timestamp * 1000, 'ms')
+    return np.datetime64(tests_start_time.shift(
+        minutes=(number * timeframe_in_minute)).int_timestamp * 1000, 'ms')
 
 
 # End helper functions
@@ -80,7 +80,7 @@ tc0 = BTContainer(data=[
     # D  O     H     L     C     V    B  S
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 1]],  # enter trade (signal on last candle)
-    stop_loss=-0.99, roi=float('inf'), profit_perc=0.00,
+    stop_loss=-0.99, roi={"0": float('inf')}, profit_perc=0.00,
     trades=[]
 )
 
@@ -95,7 +95,7 @@ tc1 = BTContainer(data=[
     [5, 5000, 5025, 4975, 4987, 6172, 0, 1],  # no action
     [6, 5000, 5025, 4975, 4987, 6172, 0, 0],  # should sell
 ],
-    stop_loss=-0.99, roi=float('inf'), profit_perc=0.00,
+    stop_loss=-0.99, roi={"0": float('inf')}, profit_perc=0.00,
     trades=[BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=1, close_tick=2),
             BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=4, close_tick=6)]
 )
@@ -107,7 +107,7 @@ tc2 = BTContainer(data=[
     [1, 5000, 5025, 4600, 4987, 6172, 0, 0],  # enter trade, stoploss hit
     [2, 5000, 5025, 4975, 4987, 6172, 0, 0],
 ],
-    stop_loss=-0.01, roi=float('inf'), profit_perc=-0.01,
+    stop_loss=-0.01, roi={"0": float('inf')}, profit_perc=-0.01,
     trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
 )
 
@@ -118,7 +118,7 @@ tc3 = BTContainer(data=[
     [1, 5000, 5025, 4800, 4987, 6172, 0, 0],  # enter trade, stoploss hit
     [2, 5000, 5025, 4975, 4987, 6172, 0, 0],
 ],
-    stop_loss=-0.03, roi=float('inf'), profit_perc=-0.03,
+    stop_loss=-0.03, roi={"0": float('inf')}, profit_perc=-0.03,
     trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
 )
 
@@ -129,7 +129,7 @@ tc4 = BTContainer(data=[
     [1, 5000, 5025, 4800, 4987, 6172, 0, 1],  # enter trade, stoploss hit, sell signal
     [2, 5000, 5025, 4975, 4987, 6172, 0, 0],
 ],
-    stop_loss=-0.03, roi=float('inf'), profit_perc=-0.03,
+    stop_loss=-0.03, roi={"0": float('inf')}, profit_perc=-0.03,
     trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
 )
 
@@ -156,18 +156,16 @@ def test_edge_results(edge_conf, mocker, caplog, data) -> None:
     trades = edge._find_trades_for_stoploss_range(frame, 'TEST/BTC', [data.stop_loss])
     results = edge._fill_calculable_fields(DataFrame(trades)) if trades else DataFrame()
 
-    print(results)
-
     assert len(trades) == len(data.trades)
 
     if not results.empty:
-        assert round(results["profit_percent"].sum(), 3) == round(data.profit_perc, 3)
+        assert round(results["profit_ratio"].sum(), 3) == round(data.profit_perc, 3)
 
     for c, trade in enumerate(data.trades):
         res = results.iloc[c]
         assert res.exit_type == trade.sell_reason
-        assert arrow.get(res.open_time) == _get_frame_time_from_offset(trade.open_tick)
-        assert arrow.get(res.close_time) == _get_frame_time_from_offset(trade.close_tick)
+        assert res.open_date == _get_frame_time_from_offset(trade.open_tick).replace(tzinfo=None)
+        assert res.close_date == _get_frame_time_from_offset(trade.close_tick).replace(tzinfo=None)
 
 
 def test_adjust(mocker, edge_conf):
@@ -253,19 +251,19 @@ def test_edge_heartbeat_calculate(mocker, edge_conf):
     heartbeat = edge_conf['edge']['process_throttle_secs']
 
     # should not recalculate if heartbeat not reached
-    edge._last_updated = arrow.utcnow().timestamp - heartbeat + 1
+    edge._last_updated = arrow.utcnow().int_timestamp - heartbeat + 1
 
     assert edge.calculate() is False
 
 
-def mocked_load_data(datadir, pairs=[], ticker_interval='0m', refresh_pairs=False,
-                     timerange=None, exchange=None):
+def mocked_load_data(datadir, pairs=[], timeframe='0m',
+                     timerange=None, *args, **kwargs):
     hz = 0.1
     base = 0.001
 
     NEOBTC = [
         [
-            ticker_start_time.shift(minutes=(x * ticker_interval_in_minute)).timestamp * 1000,
+            tests_start_time.shift(minutes=(x * timeframe_in_minute)).int_timestamp * 1000,
             math.sin(x * hz) / 1000 + base,
             math.sin(x * hz) / 1000 + base + 0.0001,
             math.sin(x * hz) / 1000 + base - 0.0001,
@@ -277,7 +275,7 @@ def mocked_load_data(datadir, pairs=[], ticker_interval='0m', refresh_pairs=Fals
     base = 0.002
     LTCBTC = [
         [
-            ticker_start_time.shift(minutes=(x * ticker_interval_in_minute)).timestamp * 1000,
+            tests_start_time.shift(minutes=(x * timeframe_in_minute)).int_timestamp * 1000,
             math.sin(x * hz) / 1000 + base,
             math.sin(x * hz) / 1000 + base + 0.0001,
             math.sin(x * hz) / 1000 + base - 0.0001,
@@ -285,48 +283,50 @@ def mocked_load_data(datadir, pairs=[], ticker_interval='0m', refresh_pairs=Fals
             123.45
         ] for x in range(0, 500)]
 
-    pairdata = {'NEO/BTC': parse_ticker_dataframe(NEOBTC, '1h', pair="NEO/BTC", fill_missing=True),
-                'LTC/BTC': parse_ticker_dataframe(LTCBTC, '1h', pair="LTC/BTC", fill_missing=True)}
+    pairdata = {'NEO/BTC': ohlcv_to_dataframe(NEOBTC, '1h', pair="NEO/BTC",
+                                              fill_missing=True),
+                'LTC/BTC': ohlcv_to_dataframe(LTCBTC, '1h', pair="LTC/BTC",
+                                              fill_missing=True)}
     return pairdata
 
 
 def test_edge_process_downloaded_data(mocker, edge_conf):
-    edge_conf['datadir'] = None
     freqtrade = get_patched_freqtradebot(mocker, edge_conf)
     mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
-    mocker.patch('freqtrade.data.history.load_data', mocked_load_data)
+    mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock())
+    mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data)
     edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
 
     assert edge.calculate()
     assert len(edge._cached_pairs) == 2
-    assert edge._last_updated <= arrow.utcnow().timestamp + 2
+    assert edge._last_updated <= arrow.utcnow().int_timestamp + 2
 
 
 def test_edge_process_no_data(mocker, edge_conf, caplog):
-    edge_conf['datadir'] = None
     freqtrade = get_patched_freqtradebot(mocker, edge_conf)
     mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
-    mocker.patch('freqtrade.data.history.load_data', MagicMock(return_value={}))
+    mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock())
+    mocker.patch('freqtrade.edge.edge_positioning.load_data', MagicMock(return_value={}))
     edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
 
     assert not edge.calculate()
     assert len(edge._cached_pairs) == 0
-    assert log_has("No data found. Edge is stopped ...", caplog.record_tuples)
+    assert log_has("No data found. Edge is stopped ...", caplog)
     assert edge._last_updated == 0
 
 
 def test_edge_process_no_trades(mocker, edge_conf, caplog):
-    edge_conf['datadir'] = None
     freqtrade = get_patched_freqtradebot(mocker, edge_conf)
     mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
-    mocker.patch('freqtrade.data.history.load_data', mocked_load_data)
+    mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock())
+    mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data)
     # Return empty
     mocker.patch('freqtrade.edge.Edge._find_trades_for_stoploss_range', MagicMock(return_value=[]))
     edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
 
     assert not edge.calculate()
     assert len(edge._cached_pairs) == 0
-    assert log_has("No trades found.", caplog.record_tuples)
+    assert log_has("No trades found.", caplog)
 
 
 def test_edge_init_error(mocker, edge_conf,):
@@ -336,12 +336,16 @@ def test_edge_init_error(mocker, edge_conf,):
         get_patched_freqtradebot(mocker, edge_conf)
 
 
-def test_process_expectancy(mocker, edge_conf):
+@pytest.mark.parametrize("fee,risk_reward_ratio,expectancy", [
+    (0.0005, 306.5384615384, 101.5128205128),
+    (0.001, 152.6923076923, 50.2307692308),
+])
+def test_process_expectancy(mocker, edge_conf, fee, risk_reward_ratio, expectancy):
     edge_conf['edge']['min_trade_number'] = 2
     freqtrade = get_patched_freqtradebot(mocker, edge_conf)
 
-    def get_fee():
-        return 0.001
+    def get_fee(*args, **kwargs):
+        return fee
 
     freqtrade.exchange.get_fee = get_fee
     edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
@@ -351,10 +355,8 @@ def test_process_expectancy(mocker, edge_conf):
          'stoploss': -0.9,
          'profit_percent': '',
          'profit_abs': '',
-         'open_time': np.datetime64('2018-10-03T00:05:00.000000000'),
-         'close_time': np.datetime64('2018-10-03T00:10:00.000000000'),
-         'open_index': 1,
-         'close_index': 1,
+         'open_date': np.datetime64('2018-10-03T00:05:00.000000000'),
+         'close_date': np.datetime64('2018-10-03T00:10:00.000000000'),
          'trade_duration': '',
          'open_rate': 17,
          'close_rate': 17,
@@ -364,10 +366,8 @@ def test_process_expectancy(mocker, edge_conf):
          'stoploss': -0.9,
          'profit_percent': '',
          'profit_abs': '',
-         'open_time': np.datetime64('2018-10-03T00:20:00.000000000'),
-         'close_time': np.datetime64('2018-10-03T00:25:00.000000000'),
-         'open_index': 4,
-         'close_index': 4,
+         'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
+         'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
          'trade_duration': '',
          'open_rate': 20,
          'close_rate': 20,
@@ -377,10 +377,8 @@ def test_process_expectancy(mocker, edge_conf):
          'stoploss': -0.9,
          'profit_percent': '',
          'profit_abs': '',
-         'open_time': np.datetime64('2018-10-03T00:30:00.000000000'),
-         'close_time': np.datetime64('2018-10-03T00:40:00.000000000'),
-         'open_index': 6,
-         'close_index': 7,
+         'open_date': np.datetime64('2018-10-03T00:30:00.000000000'),
+         'close_date': np.datetime64('2018-10-03T00:40:00.000000000'),
          'trade_duration': '',
          'open_rate': 26,
          'close_rate': 34,
@@ -395,9 +393,9 @@ def test_process_expectancy(mocker, edge_conf):
     assert 'TEST/BTC' in final
     assert final['TEST/BTC'].stoploss == -0.9
     assert round(final['TEST/BTC'].winrate, 10) == 0.3333333333
-    assert round(final['TEST/BTC'].risk_reward_ratio, 10) == 306.5384615384
+    assert round(final['TEST/BTC'].risk_reward_ratio, 10) == risk_reward_ratio
     assert round(final['TEST/BTC'].required_risk_reward, 10) == 2.0
-    assert round(final['TEST/BTC'].expectancy, 10) == 101.5128205128
+    assert round(final['TEST/BTC'].expectancy, 10) == expectancy
 
     # Pop last item so no trade is profitable
     trades.pop()
@@ -406,3 +404,156 @@ def test_process_expectancy(mocker, edge_conf):
     final = edge._process_expectancy(trades_df)
     assert len(final) == 0
     assert isinstance(final, dict)
+
+
+def test_process_expectancy_remove_pumps(mocker, edge_conf, fee,):
+    edge_conf['edge']['min_trade_number'] = 2
+    edge_conf['edge']['remove_pumps'] = True
+    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
+
+    freqtrade.exchange.get_fee = fee
+    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
+
+    trades = [
+        {'pair': 'TEST/BTC',
+         'stoploss': -0.9,
+         'profit_percent': '',
+         'profit_abs': '',
+         'open_date': np.datetime64('2018-10-03T00:05:00.000000000'),
+         'close_date': np.datetime64('2018-10-03T00:10:00.000000000'),
+         'open_index': 1,
+         'close_index': 1,
+         'trade_duration': '',
+         'open_rate': 17,
+         'close_rate': 15,
+         'exit_type': 'sell_signal'},
+
+        {'pair': 'TEST/BTC',
+         'stoploss': -0.9,
+         'profit_percent': '',
+         'profit_abs': '',
+         'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
+         'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
+         'open_index': 4,
+         'close_index': 4,
+         'trade_duration': '',
+         'open_rate': 20,
+         'close_rate': 10,
+         'exit_type': 'sell_signal'},
+        {'pair': 'TEST/BTC',
+         'stoploss': -0.9,
+         'profit_percent': '',
+         'profit_abs': '',
+         'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
+         'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
+         'open_index': 4,
+         'close_index': 4,
+         'trade_duration': '',
+         'open_rate': 20,
+         'close_rate': 10,
+         'exit_type': 'sell_signal'},
+        {'pair': 'TEST/BTC',
+         'stoploss': -0.9,
+         'profit_percent': '',
+         'profit_abs': '',
+         'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
+         'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
+         'open_index': 4,
+         'close_index': 4,
+         'trade_duration': '',
+         'open_rate': 20,
+         'close_rate': 10,
+         'exit_type': 'sell_signal'},
+        {'pair': 'TEST/BTC',
+         'stoploss': -0.9,
+         'profit_percent': '',
+         'profit_abs': '',
+         'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
+         'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
+         'open_index': 4,
+         'close_index': 4,
+         'trade_duration': '',
+         'open_rate': 20,
+         'close_rate': 10,
+         'exit_type': 'sell_signal'},
+
+        {'pair': 'TEST/BTC',
+         'stoploss': -0.9,
+         'profit_percent': '',
+         'profit_abs': '',
+         'open_date': np.datetime64('2018-10-03T00:30:00.000000000'),
+         'close_date': np.datetime64('2018-10-03T00:40:00.000000000'),
+         'open_index': 6,
+         'close_index': 7,
+         'trade_duration': '',
+         'open_rate': 26,
+         'close_rate': 134,
+         'exit_type': 'sell_signal'}
+    ]
+
+    trades_df = DataFrame(trades)
+    trades_df = edge._fill_calculable_fields(trades_df)
+    final = edge._process_expectancy(trades_df)
+
+    assert 'TEST/BTC' in final
+    assert final['TEST/BTC'].stoploss == -0.9
+    assert final['TEST/BTC'].nb_trades == len(trades_df) - 1
+    assert round(final['TEST/BTC'].winrate, 10) == 0.0
+
+
+def test_process_expectancy_only_wins(mocker, edge_conf, fee,):
+    edge_conf['edge']['min_trade_number'] = 2
+    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
+
+    freqtrade.exchange.get_fee = fee
+    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
+
+    trades = [
+        {'pair': 'TEST/BTC',
+         'stoploss': -0.9,
+         'profit_percent': '',
+         'profit_abs': '',
+         'open_date': np.datetime64('2018-10-03T00:05:00.000000000'),
+         'close_date': np.datetime64('2018-10-03T00:10:00.000000000'),
+         'open_index': 1,
+         'close_index': 1,
+         'trade_duration': '',
+         'open_rate': 15,
+         'close_rate': 17,
+         'exit_type': 'sell_signal'},
+        {'pair': 'TEST/BTC',
+         'stoploss': -0.9,
+         'profit_percent': '',
+         'profit_abs': '',
+         'open_date': np.datetime64('2018-10-03T00:20:00.000000000'),
+         'close_date': np.datetime64('2018-10-03T00:25:00.000000000'),
+         'open_index': 4,
+         'close_index': 4,
+         'trade_duration': '',
+         'open_rate': 10,
+         'close_rate': 20,
+         'exit_type': 'sell_signal'},
+        {'pair': 'TEST/BTC',
+         'stoploss': -0.9,
+         'profit_percent': '',
+         'profit_abs': '',
+         'open_date': np.datetime64('2018-10-03T00:30:00.000000000'),
+         'close_date': np.datetime64('2018-10-03T00:40:00.000000000'),
+         'open_index': 6,
+         'close_index': 7,
+         'trade_duration': '',
+         'open_rate': 26,
+         'close_rate': 134,
+         'exit_type': 'sell_signal'}
+    ]
+
+    trades_df = DataFrame(trades)
+    trades_df = edge._fill_calculable_fields(trades_df)
+    final = edge._process_expectancy(trades_df)
+
+    assert 'TEST/BTC' in final
+    assert final['TEST/BTC'].stoploss == -0.9
+    assert final['TEST/BTC'].nb_trades == len(trades_df)
+    assert round(final['TEST/BTC'].winrate, 10) == 1.0
+    assert round(final['TEST/BTC'].risk_reward_ratio, 10) == float('inf')
+    assert round(final['TEST/BTC'].expectancy, 10) == float('inf')
diff --git a/freqtrade/tests/strategy/__init__.py b/tests/exchange/__init__.py
similarity index 100%
rename from freqtrade/tests/strategy/__init__.py
rename to tests/exchange/__init__.py
diff --git a/tests/exchange/test_binance.py b/tests/exchange/test_binance.py
new file mode 100644
index 000000000..f2b508761
--- /dev/null
+++ b/tests/exchange/test_binance.py
@@ -0,0 +1,107 @@
+from random import randint
+from unittest.mock import MagicMock
+
+import ccxt
+import pytest
+
+from freqtrade.exceptions import DependencyException, InvalidOrderException, OperationalException
+from tests.conftest import get_patched_exchange
+from tests.exchange.test_exchange import ccxt_exceptionhandlers
+
+
+@pytest.mark.parametrize('limitratio,expected', [
+    (None, 220 * 0.99),
+    (0.99, 220 * 0.99),
+    (0.98, 220 * 0.98),
+])
+def test_stoploss_order_binance(default_conf, mocker, limitratio, expected):
+    api_mock = MagicMock()
+    order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
+    order_type = 'stop_loss_limit'
+
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+    default_conf['dry_run'] = False
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
+
+    with pytest.raises(OperationalException):
+        order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=190,
+                                  order_types={'stoploss_on_exchange_limit_ratio': 1.05})
+
+    api_mock.create_order.reset_mock()
+    order_types = {} if limitratio is None else {'stoploss_on_exchange_limit_ratio': limitratio}
+    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types=order_types)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
+    assert api_mock.create_order.call_args_list[0][1]['type'] == order_type
+    assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
+    assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
+    # Price should be 1% below stopprice
+    assert api_mock.create_order.call_args_list[0][1]['price'] == expected
+    assert api_mock.create_order.call_args_list[0][1]['params'] == {'stopPrice': 220}
+
+    # test exception handling
+    with pytest.raises(DependencyException):
+        api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("0 balance"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
+        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+    with pytest.raises(InvalidOrderException):
+        api_mock.create_order = MagicMock(
+            side_effect=ccxt.InvalidOrder("binance Order would trigger immediately."))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
+        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, "binance",
+                           "stoploss", "create_order", retries=1,
+                           pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+
+def test_stoploss_order_dry_run_binance(default_conf, mocker):
+    api_mock = MagicMock()
+    order_type = 'stop_loss_limit'
+    default_conf['dry_run'] = True
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, 'binance')
+
+    with pytest.raises(OperationalException):
+        order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=190,
+                                  order_types={'stoploss_on_exchange_limit_ratio': 1.05})
+
+    api_mock.create_order.reset_mock()
+
+    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+    assert 'id' in order
+    assert 'info' in order
+    assert 'type' in order
+
+    assert order['type'] == order_type
+    assert order['price'] == 220
+    assert order['amount'] == 1
+
+
+def test_stoploss_adjust_binance(mocker, default_conf):
+    exchange = get_patched_exchange(mocker, default_conf, id='binance')
+    order = {
+        'type': 'stop_loss_limit',
+        'price': 1500,
+        'info': {'stopPrice': 1500},
+    }
+    assert exchange.stoploss_adjust(1501, order)
+    assert not exchange.stoploss_adjust(1499, order)
+    # Test with invalid order case
+    order['type'] = 'stop_loss'
+    assert not exchange.stoploss_adjust(1501, order)
diff --git a/tests/exchange/test_exchange.py b/tests/exchange/test_exchange.py
new file mode 100644
index 000000000..e4452a83c
--- /dev/null
+++ b/tests/exchange/test_exchange.py
@@ -0,0 +1,2438 @@
+import copy
+import logging
+from datetime import datetime, timedelta, timezone
+from random import randint
+from unittest.mock import MagicMock, Mock, PropertyMock, patch
+
+import arrow
+import ccxt
+import pytest
+from pandas import DataFrame
+
+from freqtrade.exceptions import (DDosProtection, DependencyException, InvalidOrderException,
+                                  OperationalException, TemporaryError)
+from freqtrade.exchange import Binance, Bittrex, Exchange, Kraken
+from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, API_RETRY_COUNT,
+                                       calculate_backoff)
+from freqtrade.exchange.exchange import (market_is_active, timeframe_to_minutes, timeframe_to_msecs,
+                                         timeframe_to_next_date, timeframe_to_prev_date,
+                                         timeframe_to_seconds)
+from freqtrade.resolvers.exchange_resolver import ExchangeResolver
+from tests.conftest import get_patched_exchange, log_has, log_has_re
+
+
+# Make sure to always keep one exchange here which is NOT subclassed!!
+EXCHANGES = ['bittrex', 'binance', 'kraken', 'ftx']
+
+
+# Source: https://stackoverflow.com/questions/29881236/how-to-mock-asyncio-coroutines
+def get_mock_coro(return_value):
+    async def mock_coro(*args, **kwargs):
+        return return_value
+
+    return Mock(wraps=mock_coro)
+
+
+def ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
+                           fun, mock_ccxt_fun, retries=API_RETRY_COUNT + 1, **kwargs):
+
+    with patch('freqtrade.exchange.common.time.sleep'):
+        with pytest.raises(DDosProtection):
+            api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.DDoSProtection("DDos"))
+            exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+            getattr(exchange, fun)(**kwargs)
+        assert api_mock.__dict__[mock_ccxt_fun].call_count == retries
+
+    with pytest.raises(TemporaryError):
+        api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.NetworkError("DeaDBeef"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        getattr(exchange, fun)(**kwargs)
+    assert api_mock.__dict__[mock_ccxt_fun].call_count == retries
+
+    with pytest.raises(OperationalException):
+        api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.BaseError("DeadBeef"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        getattr(exchange, fun)(**kwargs)
+    assert api_mock.__dict__[mock_ccxt_fun].call_count == 1
+
+
+async def async_ccxt_exception(mocker, default_conf, api_mock, fun, mock_ccxt_fun,
+                               retries=API_RETRY_COUNT + 1, **kwargs):
+
+    with patch('freqtrade.exchange.common.asyncio.sleep', get_mock_coro(None)):
+        with pytest.raises(DDosProtection):
+            api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.DDoSProtection("Dooh"))
+            exchange = get_patched_exchange(mocker, default_conf, api_mock)
+            await getattr(exchange, fun)(**kwargs)
+        assert api_mock.__dict__[mock_ccxt_fun].call_count == retries
+
+    with pytest.raises(TemporaryError):
+        api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.NetworkError("DeadBeef"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock)
+        await getattr(exchange, fun)(**kwargs)
+    assert api_mock.__dict__[mock_ccxt_fun].call_count == retries
+
+    with pytest.raises(OperationalException):
+        api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.BaseError("DeadBeef"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock)
+        await getattr(exchange, fun)(**kwargs)
+    assert api_mock.__dict__[mock_ccxt_fun].call_count == 1
+
+
+def test_init(default_conf, mocker, caplog):
+    caplog.set_level(logging.INFO)
+    get_patched_exchange(mocker, default_conf)
+    assert log_has('Instance is running with dry_run enabled', caplog)
+
+
+def test_init_ccxt_kwargs(default_conf, mocker, caplog):
+    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    caplog.set_level(logging.INFO)
+    conf = copy.deepcopy(default_conf)
+    conf['exchange']['ccxt_async_config'] = {'aiohttp_trust_env': True, 'asyncio_loop': True}
+    ex = Exchange(conf)
+    assert log_has(
+        "Applying additional ccxt config: {'aiohttp_trust_env': True, 'asyncio_loop': True}",
+        caplog)
+    assert ex._api_async.aiohttp_trust_env
+    assert not ex._api.aiohttp_trust_env
+
+    # Reset logging and config
+    caplog.clear()
+    conf = copy.deepcopy(default_conf)
+    conf['exchange']['ccxt_config'] = {'TestKWARG': 11}
+    conf['exchange']['ccxt_sync_config'] = {'TestKWARG44': 11}
+    conf['exchange']['ccxt_async_config'] = {'asyncio_loop': True}
+    asynclogmsg = "Applying additional ccxt config: {'TestKWARG': 11, 'asyncio_loop': True}"
+    ex = Exchange(conf)
+    assert not ex._api_async.aiohttp_trust_env
+    assert hasattr(ex._api, 'TestKWARG')
+    assert ex._api.TestKWARG == 11
+    # ccxt_config is assigned to both sync and async
+    assert not hasattr(ex._api_async, 'TestKWARG44')
+
+    assert hasattr(ex._api_async, 'TestKWARG')
+    assert log_has("Applying additional ccxt config: {'TestKWARG': 11, 'TestKWARG44': 11}", caplog)
+    assert log_has(asynclogmsg, caplog)
+
+
+def test_destroy(default_conf, mocker, caplog):
+    caplog.set_level(logging.DEBUG)
+    get_patched_exchange(mocker, default_conf)
+    assert log_has('Exchange object destroyed, closing async loop', caplog)
+
+
+def test_init_exception(default_conf, mocker):
+    default_conf['exchange']['name'] = 'wrong_exchange_name'
+
+    with pytest.raises(OperationalException,
+                       match=f"Exchange {default_conf['exchange']['name']} is not supported"):
+        Exchange(default_conf)
+
+    default_conf['exchange']['name'] = 'binance'
+    with pytest.raises(OperationalException,
+                       match=f"Exchange {default_conf['exchange']['name']} is not supported"):
+        mocker.patch("ccxt.binance", MagicMock(side_effect=AttributeError))
+        Exchange(default_conf)
+
+    with pytest.raises(OperationalException,
+                       match=r"Initialization of ccxt failed. Reason: DeadBeef"):
+        mocker.patch("ccxt.binance", MagicMock(side_effect=ccxt.BaseError("DeadBeef")))
+        Exchange(default_conf)
+
+
+def test_exchange_resolver(default_conf, mocker, caplog):
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=MagicMock()))
+    mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+
+    exchange = ExchangeResolver.load_exchange('huobi', default_conf)
+    assert isinstance(exchange, Exchange)
+    assert log_has_re(r"No .* specific subclass found. Using the generic class instead.", caplog)
+    caplog.clear()
+
+    exchange = ExchangeResolver.load_exchange('Bittrex', default_conf)
+    assert isinstance(exchange, Exchange)
+    assert isinstance(exchange, Bittrex)
+    assert not log_has_re(r"No .* specific subclass found. Using the generic class instead.",
+                          caplog)
+    caplog.clear()
+
+    exchange = ExchangeResolver.load_exchange('kraken', default_conf)
+    assert isinstance(exchange, Exchange)
+    assert isinstance(exchange, Kraken)
+    assert not isinstance(exchange, Binance)
+    assert not log_has_re(r"No .* specific subclass found. Using the generic class instead.",
+                          caplog)
+
+    exchange = ExchangeResolver.load_exchange('binance', default_conf)
+    assert isinstance(exchange, Exchange)
+    assert isinstance(exchange, Binance)
+    assert not isinstance(exchange, Kraken)
+
+    assert not log_has_re(r"No .* specific subclass found. Using the generic class instead.",
+                          caplog)
+
+    # Test mapping
+    exchange = ExchangeResolver.load_exchange('binanceus', default_conf)
+    assert isinstance(exchange, Exchange)
+    assert isinstance(exchange, Binance)
+    assert not isinstance(exchange, Kraken)
+
+
+def test_validate_order_time_in_force(default_conf, mocker, caplog):
+    caplog.set_level(logging.INFO)
+    # explicitly test bittrex, exchanges implementing other policies need seperate tests
+    ex = get_patched_exchange(mocker, default_conf, id="bittrex")
+    tif = {
+        "buy": "gtc",
+        "sell": "gtc",
+    }
+
+    ex.validate_order_time_in_force(tif)
+    tif2 = {
+        "buy": "fok",
+        "sell": "ioc",
+    }
+    with pytest.raises(OperationalException, match=r"Time in force.*not supported for .*"):
+        ex.validate_order_time_in_force(tif2)
+
+    # Patch to see if this will pass if the values are in the ft dict
+    ex._ft_has.update({"order_time_in_force": ["gtc", "fok", "ioc"]})
+    ex.validate_order_time_in_force(tif2)
+
+
+@pytest.mark.parametrize("amount,precision_mode,precision,expected", [
+    (2.34559, 2, 4, 2.3455),
+    (2.34559, 2, 5, 2.34559),
+    (2.34559, 2, 3, 2.345),
+    (2.9999, 2, 3, 2.999),
+    (2.9909, 2, 3, 2.990),
+    # Tests for Tick-size
+    (2.34559, 4, 0.0001, 2.3455),
+    (2.34559, 4, 0.00001, 2.34559),
+    (2.34559, 4, 0.001, 2.345),
+    (2.9999, 4, 0.001, 2.999),
+    (2.9909, 4, 0.001, 2.990),
+    (2.9909, 4, 0.005, 2.990),
+    (2.9999, 4, 0.005, 2.995),
+])
+def test_amount_to_precision(default_conf, mocker, amount, precision_mode, precision, expected):
+    '''
+    Test rounds down
+    '''
+
+    markets = PropertyMock(return_value={'ETH/BTC': {'precision': {'amount': precision}}})
+
+    exchange = get_patched_exchange(mocker, default_conf, id="binance")
+    # digits counting mode
+    # DECIMAL_PLACES = 2
+    # SIGNIFICANT_DIGITS = 3
+    # TICK_SIZE = 4
+    mocker.patch('freqtrade.exchange.Exchange.precisionMode',
+                 PropertyMock(return_value=precision_mode))
+    mocker.patch('freqtrade.exchange.Exchange.markets', markets)
+
+    pair = 'ETH/BTC'
+    assert exchange.amount_to_precision(pair, amount) == expected
+
+
+@pytest.mark.parametrize("price,precision_mode,precision,expected", [
+    (2.34559, 2, 4, 2.3456),
+    (2.34559, 2, 5, 2.34559),
+    (2.34559, 2, 3, 2.346),
+    (2.9999, 2, 3, 3.000),
+    (2.9909, 2, 3, 2.991),
+    # Tests for Tick_size
+    (2.34559, 4, 0.0001, 2.3456),
+    (2.34559, 4, 0.00001, 2.34559),
+    (2.34559, 4, 0.001, 2.346),
+    (2.9999, 4, 0.001, 3.000),
+    (2.9909, 4, 0.001, 2.991),
+    (2.9909, 4, 0.005, 2.995),
+    (2.9973, 4, 0.005, 3.0),
+    (2.9977, 4, 0.005, 3.0),
+    (234.43, 4, 0.5, 234.5),
+    (234.53, 4, 0.5, 235.0),
+    (0.891534, 4, 0.0001, 0.8916),
+
+])
+def test_price_to_precision(default_conf, mocker, price, precision_mode, precision, expected):
+    '''
+    Test price to precision
+    '''
+    markets = PropertyMock(return_value={'ETH/BTC': {'precision': {'price': precision}}})
+
+    exchange = get_patched_exchange(mocker, default_conf, id="binance")
+    mocker.patch('freqtrade.exchange.Exchange.markets', markets)
+    # digits counting mode
+    # DECIMAL_PLACES = 2
+    # SIGNIFICANT_DIGITS = 3
+    # TICK_SIZE = 4
+    mocker.patch('freqtrade.exchange.Exchange.precisionMode',
+                 PropertyMock(return_value=precision_mode))
+
+    pair = 'ETH/BTC'
+    assert pytest.approx(exchange.price_to_precision(pair, price)) == expected
+
+
+@pytest.mark.parametrize("price,precision_mode,precision,expected", [
+    (2.34559, 2, 4, 0.0001),
+    (2.34559, 2, 5, 0.00001),
+    (2.34559, 2, 3, 0.001),
+    (2.9999, 2, 3, 0.001),
+    (200.0511, 2, 3, 0.001),
+    # Tests for Tick_size
+    (2.34559, 4, 0.0001, 0.0001),
+    (2.34559, 4, 0.00001, 0.00001),
+    (2.34559, 4, 0.0025, 0.0025),
+    (2.9909, 4, 0.0025, 0.0025),
+    (234.43, 4, 0.5, 0.5),
+    (234.43, 4, 0.0025, 0.0025),
+    (234.43, 4, 0.00013, 0.00013),
+
+])
+def test_price_get_one_pip(default_conf, mocker, price, precision_mode, precision, expected):
+    markets = PropertyMock(return_value={'ETH/BTC': {'precision': {'price': precision}}})
+    exchange = get_patched_exchange(mocker, default_conf, id="binance")
+    mocker.patch('freqtrade.exchange.Exchange.markets', markets)
+    mocker.patch('freqtrade.exchange.Exchange.precisionMode',
+                 PropertyMock(return_value=precision_mode))
+    pair = 'ETH/BTC'
+    assert pytest.approx(exchange.price_get_one_pip(pair, price)) == expected
+
+
+def test_set_sandbox(default_conf, mocker):
+    """
+    Test working scenario
+    """
+    api_mock = MagicMock()
+    api_mock.load_markets = MagicMock(return_value={
+        'ETH/BTC': '', 'LTC/BTC': '', 'XRP/BTC': '', 'NEO/BTC': ''
+    })
+    url_mock = PropertyMock(return_value={'test': "api-public.sandbox.gdax.com",
+                                          'api': 'https://api.gdax.com'})
+    type(api_mock).urls = url_mock
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+    liveurl = exchange._api.urls['api']
+    default_conf['exchange']['sandbox'] = True
+    exchange.set_sandbox(exchange._api, default_conf['exchange'], 'Logname')
+    assert exchange._api.urls['api'] != liveurl
+
+
+def test_set_sandbox_exception(default_conf, mocker):
+    """
+    Test Fail scenario
+    """
+    api_mock = MagicMock()
+    api_mock.load_markets = MagicMock(return_value={
+        'ETH/BTC': '', 'LTC/BTC': '', 'XRP/BTC': '', 'NEO/BTC': ''
+    })
+    url_mock = PropertyMock(return_value={'api': 'https://api.gdax.com'})
+    type(api_mock).urls = url_mock
+
+    with pytest.raises(OperationalException, match=r'does not provide a sandbox api'):
+        exchange = get_patched_exchange(mocker, default_conf, api_mock)
+        default_conf['exchange']['sandbox'] = True
+        exchange.set_sandbox(exchange._api, default_conf['exchange'], 'Logname')
+
+
+def test__load_async_markets(default_conf, mocker, caplog):
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange._load_markets')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    exchange = Exchange(default_conf)
+    exchange._api_async.load_markets = get_mock_coro(None)
+    exchange._load_async_markets()
+    assert exchange._api_async.load_markets.call_count == 1
+    caplog.set_level(logging.DEBUG)
+
+    exchange._api_async.load_markets = Mock(side_effect=ccxt.BaseError("deadbeef"))
+    exchange._load_async_markets()
+
+    assert log_has('Could not load async markets. Reason: deadbeef', caplog)
+
+
+def test__load_markets(default_conf, mocker, caplog):
+    caplog.set_level(logging.INFO)
+    api_mock = MagicMock()
+    api_mock.load_markets = MagicMock(side_effect=ccxt.BaseError("SomeError"))
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    Exchange(default_conf)
+    assert log_has('Unable to initialize markets. Reason: SomeError', caplog)
+
+    expected_return = {'ETH/BTC': 'available'}
+    api_mock = MagicMock()
+    api_mock.load_markets = MagicMock(return_value=expected_return)
+    type(api_mock).markets = expected_return
+    default_conf['exchange']['pair_whitelist'] = ['ETH/BTC']
+    ex = get_patched_exchange(mocker, default_conf, api_mock, id="binance", mock_markets=False)
+    assert ex.markets == expected_return
+
+
+def test_reload_markets(default_conf, mocker, caplog):
+    caplog.set_level(logging.DEBUG)
+    initial_markets = {'ETH/BTC': {}}
+
+    def load_markets(*args, **kwargs):
+        exchange._api.markets = updated_markets
+
+    api_mock = MagicMock()
+    api_mock.load_markets = load_markets
+    type(api_mock).markets = initial_markets
+    default_conf['exchange']['markets_refresh_interval'] = 10
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="binance",
+                                    mock_markets=False)
+    exchange._load_async_markets = MagicMock()
+    exchange._last_markets_refresh = arrow.utcnow().int_timestamp
+    updated_markets = {'ETH/BTC': {}, "LTC/BTC": {}}
+
+    assert exchange.markets == initial_markets
+
+    # less than 10 minutes have passed, no reload
+    exchange.reload_markets()
+    assert exchange.markets == initial_markets
+    assert exchange._load_async_markets.call_count == 0
+
+    # more than 10 minutes have passed, reload is executed
+    exchange._last_markets_refresh = arrow.utcnow().int_timestamp - 15 * 60
+    exchange.reload_markets()
+    assert exchange.markets == updated_markets
+    assert exchange._load_async_markets.call_count == 1
+    assert log_has('Performing scheduled market reload..', caplog)
+
+
+def test_reload_markets_exception(default_conf, mocker, caplog):
+    caplog.set_level(logging.DEBUG)
+
+    api_mock = MagicMock()
+    api_mock.load_markets = MagicMock(side_effect=ccxt.NetworkError("LoadError"))
+    default_conf['exchange']['markets_refresh_interval'] = 10
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="binance")
+
+    # less than 10 minutes have passed, no reload
+    exchange.reload_markets()
+    assert exchange._last_markets_refresh == 0
+    assert log_has_re(r"Could not reload markets.*", caplog)
+
+
+@pytest.mark.parametrize("stake_currency", ['ETH', 'BTC', 'USDT'])
+def test_validate_stake_currency(default_conf, stake_currency, mocker, caplog):
+    default_conf['stake_currency'] = stake_currency
+    api_mock = MagicMock()
+    type(api_mock).markets = PropertyMock(return_value={
+        'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'},
+        'XRP/ETH': {'quote': 'ETH'}, 'NEO/USDT': {'quote': 'USDT'},
+    })
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+    Exchange(default_conf)
+
+
+def test_validate_stake_currency_error(default_conf, mocker, caplog):
+    default_conf['stake_currency'] = 'XRP'
+    api_mock = MagicMock()
+    type(api_mock).markets = PropertyMock(return_value={
+        'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'},
+        'XRP/ETH': {'quote': 'ETH'}, 'NEO/USDT': {'quote': 'USDT'},
+    })
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+    with pytest.raises(OperationalException,
+                       match=r'XRP is not available as stake on .*'
+                       'Available currencies are: BTC, ETH, USDT'):
+        Exchange(default_conf)
+
+
+def test_get_quote_currencies(default_conf, mocker):
+    ex = get_patched_exchange(mocker, default_conf)
+
+    assert set(ex.get_quote_currencies()) == set(['USD', 'ETH', 'BTC', 'USDT'])
+
+
+@pytest.mark.parametrize('pair,expected', [
+    ('XRP/BTC', 'BTC'),
+    ('LTC/USD', 'USD'),
+    ('ETH/USDT', 'USDT'),
+    ('XLTCUSDT', 'USDT'),
+    ('XRP/NOCURRENCY', ''),
+])
+def test_get_pair_quote_currency(default_conf, mocker, pair, expected):
+    ex = get_patched_exchange(mocker, default_conf)
+    assert ex.get_pair_quote_currency(pair) == expected
+
+
+@pytest.mark.parametrize('pair,expected', [
+    ('XRP/BTC', 'XRP'),
+    ('LTC/USD', 'LTC'),
+    ('ETH/USDT', 'ETH'),
+    ('XLTCUSDT', 'LTC'),
+    ('XRP/NOCURRENCY', ''),
+])
+def test_get_pair_base_currency(default_conf, mocker, pair, expected):
+    ex = get_patched_exchange(mocker, default_conf)
+    assert ex.get_pair_base_currency(pair) == expected
+
+
+def test_validate_pairs(default_conf, mocker):  # test exchange.validate_pairs directly
+    api_mock = MagicMock()
+    type(api_mock).markets = PropertyMock(return_value={
+        'ETH/BTC': {'quote': 'BTC'},
+        'LTC/BTC': {'quote': 'BTC'},
+        'XRP/BTC': {'quote': 'BTC'},
+        'NEO/BTC': {'quote': 'BTC'},
+    })
+    id_mock = PropertyMock(return_value='test_exchange')
+    type(api_mock).id = id_mock
+
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    Exchange(default_conf)
+
+
+def test_validate_pairs_not_available(default_conf, mocker):
+    api_mock = MagicMock()
+    type(api_mock).markets = PropertyMock(return_value={
+        'XRP/BTC': {'inactive': True}
+    })
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+
+    with pytest.raises(OperationalException, match=r'not available'):
+        Exchange(default_conf)
+
+
+def test_validate_pairs_exception(default_conf, mocker, caplog):
+    caplog.set_level(logging.INFO)
+    api_mock = MagicMock()
+    mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value='Binance'))
+
+    type(api_mock).markets = PropertyMock(return_value={})
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', api_mock)
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+
+    with pytest.raises(OperationalException, match=r'Pair ETH/BTC is not available on Binance'):
+        Exchange(default_conf)
+
+    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value={}))
+    Exchange(default_conf)
+    assert log_has('Unable to validate pairs (assuming they are correct).', caplog)
+
+
+def test_validate_pairs_restricted(default_conf, mocker, caplog):
+    api_mock = MagicMock()
+    type(api_mock).markets = PropertyMock(return_value={
+        'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'},
+        'XRP/BTC': {'quote': 'BTC', 'info': {'IsRestricted': True}},
+        'NEO/BTC': {'quote': 'BTC', 'info': 'TestString'},  # info can also be a string ...
+    })
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+
+    Exchange(default_conf)
+    assert log_has("Pair XRP/BTC is restricted for some users on this exchange."
+                   "Please check if you are impacted by this restriction "
+                   "on the exchange and eventually remove XRP/BTC from your whitelist.", caplog)
+
+
+def test_validate_pairs_stakecompatibility(default_conf, mocker, caplog):
+    api_mock = MagicMock()
+    type(api_mock).markets = PropertyMock(return_value={
+        'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'},
+        'XRP/BTC': {'quote': 'BTC'}, 'NEO/BTC': {'quote': 'BTC'},
+        'HELLO-WORLD': {'quote': 'BTC'},
+    })
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+
+    Exchange(default_conf)
+
+
+def test_validate_pairs_stakecompatibility_downloaddata(default_conf, mocker, caplog):
+    api_mock = MagicMock()
+    default_conf['stake_currency'] = ''
+    type(api_mock).markets = PropertyMock(return_value={
+        'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'},
+        'XRP/BTC': {'quote': 'BTC'}, 'NEO/BTC': {'quote': 'BTC'},
+        'HELLO-WORLD': {'quote': 'BTC'},
+    })
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+
+    Exchange(default_conf)
+
+
+def test_validate_pairs_stakecompatibility_fail(default_conf, mocker, caplog):
+    default_conf['exchange']['pair_whitelist'].append('HELLO-WORLD')
+    api_mock = MagicMock()
+    type(api_mock).markets = PropertyMock(return_value={
+        'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'},
+        'XRP/BTC': {'quote': 'BTC'}, 'NEO/BTC': {'quote': 'BTC'},
+        'HELLO-WORLD': {'quote': 'USDT'},
+    })
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+
+    with pytest.raises(OperationalException, match=r"Stake-currency 'BTC' not compatible with.*"):
+        Exchange(default_conf)
+
+
+@pytest.mark.parametrize("timeframe", [
+    ('5m'), ("1m"), ("15m"), ("1h")
+])
+def test_validate_timeframes(default_conf, mocker, timeframe):
+    default_conf["timeframe"] = timeframe
+    api_mock = MagicMock()
+    id_mock = PropertyMock(return_value='test_exchange')
+    type(api_mock).id = id_mock
+    timeframes = PropertyMock(return_value={'1m': '1m',
+                                            '5m': '5m',
+                                            '15m': '15m',
+                                            '1h': '1h'})
+    type(api_mock).timeframes = timeframes
+
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    Exchange(default_conf)
+
+
+def test_validate_timeframes_failed(default_conf, mocker):
+    default_conf["timeframe"] = "3m"
+    api_mock = MagicMock()
+    id_mock = PropertyMock(return_value='test_exchange')
+    type(api_mock).id = id_mock
+    timeframes = PropertyMock(return_value={'15s': '15s',
+                                            '1m': '1m',
+                                            '5m': '5m',
+                                            '15m': '15m',
+                                            '1h': '1h'})
+    type(api_mock).timeframes = timeframes
+
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
+    with pytest.raises(OperationalException,
+                       match=r"Invalid timeframe '3m'. This exchange supports.*"):
+        Exchange(default_conf)
+    default_conf["timeframe"] = "15s"
+
+    with pytest.raises(OperationalException,
+                       match=r"Timeframes < 1m are currently not supported by Freqtrade."):
+        Exchange(default_conf)
+
+
+def test_validate_timeframes_emulated_ohlcv_1(default_conf, mocker):
+    default_conf["timeframe"] = "3m"
+    api_mock = MagicMock()
+    id_mock = PropertyMock(return_value='test_exchange')
+    type(api_mock).id = id_mock
+
+    # delete timeframes so magicmock does not autocreate it
+    del api_mock.timeframes
+
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    with pytest.raises(OperationalException,
+                       match=r'The ccxt library does not provide the list of timeframes '
+                             r'for the exchange ".*" and this exchange '
+                             r'is therefore not supported. *'):
+        Exchange(default_conf)
+
+
+def test_validate_timeframes_emulated_ohlcvi_2(default_conf, mocker):
+    default_conf["timeframe"] = "3m"
+    api_mock = MagicMock()
+    id_mock = PropertyMock(return_value='test_exchange')
+    type(api_mock).id = id_mock
+
+    # delete timeframes so magicmock does not autocreate it
+    del api_mock.timeframes
+
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange._load_markets',
+                 MagicMock(return_value={'timeframes': None}))
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    with pytest.raises(OperationalException,
+                       match=r'The ccxt library does not provide the list of timeframes '
+                             r'for the exchange ".*" and this exchange '
+                             r'is therefore not supported. *'):
+        Exchange(default_conf)
+
+
+def test_validate_timeframes_not_in_config(default_conf, mocker):
+    del default_conf["timeframe"]
+    api_mock = MagicMock()
+    id_mock = PropertyMock(return_value='test_exchange')
+    type(api_mock).id = id_mock
+    timeframes = PropertyMock(return_value={'1m': '1m',
+                                            '5m': '5m',
+                                            '15m': '15m',
+                                            '1h': '1h'})
+    type(api_mock).timeframes = timeframes
+
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    Exchange(default_conf)
+
+
+def test_validate_order_types(default_conf, mocker):
+    api_mock = MagicMock()
+
+    type(api_mock).has = PropertyMock(return_value={'createMarketOrder': True})
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+    mocker.patch('freqtrade.exchange.Exchange.name', 'Bittrex')
+
+    default_conf['order_types'] = {
+        'buy': 'limit',
+        'sell': 'limit',
+        'stoploss': 'market',
+        'stoploss_on_exchange': False
+    }
+    Exchange(default_conf)
+
+    type(api_mock).has = PropertyMock(return_value={'createMarketOrder': False})
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+
+    default_conf['order_types'] = {
+        'buy': 'limit',
+        'sell': 'limit',
+        'stoploss': 'market',
+        'stoploss_on_exchange': False
+    }
+    with pytest.raises(OperationalException,
+                       match=r'Exchange .* does not support market orders.'):
+        Exchange(default_conf)
+
+    default_conf['order_types'] = {
+        'buy': 'limit',
+        'sell': 'limit',
+        'stoploss': 'limit',
+        'stoploss_on_exchange': True
+    }
+    with pytest.raises(OperationalException,
+                       match=r'On exchange stoploss is not supported for .*'):
+        Exchange(default_conf)
+
+
+def test_validate_order_types_not_in_config(default_conf, mocker):
+    api_mock = MagicMock()
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
+    mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+
+    conf = copy.deepcopy(default_conf)
+    Exchange(conf)
+
+
+def test_validate_required_startup_candles(default_conf, mocker, caplog):
+    api_mock = MagicMock()
+    mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value='Binance'))
+
+    mocker.patch('freqtrade.exchange.Exchange._init_ccxt', api_mock)
+    mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
+    mocker.patch('freqtrade.exchange.Exchange._load_async_markets')
+    mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
+    mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
+
+    default_conf['startup_candle_count'] = 20
+    ex = Exchange(default_conf)
+    assert ex
+    default_conf['startup_candle_count'] = 600
+
+    with pytest.raises(OperationalException, match=r'This strategy requires 600.*'):
+        Exchange(default_conf)
+
+
+def test_exchange_has(default_conf, mocker):
+    exchange = get_patched_exchange(mocker, default_conf)
+    assert not exchange.exchange_has('ASDFASDF')
+    api_mock = MagicMock()
+
+    type(api_mock).has = PropertyMock(return_value={'deadbeef': True})
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+    assert exchange.exchange_has("deadbeef")
+
+    type(api_mock).has = PropertyMock(return_value={'deadbeef': False})
+    exchange = get_patched_exchange(mocker, default_conf, api_mock)
+    assert not exchange.exchange_has("deadbeef")
+
+
+@pytest.mark.parametrize("side", [
+    ("buy"),
+    ("sell")
+])
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_dry_run_order(default_conf, mocker, side, exchange_name):
+    default_conf['dry_run'] = True
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+
+    order = exchange.dry_run_order(
+        pair='ETH/BTC', ordertype='limit', side=side, amount=1, rate=200)
+    assert 'id' in order
+    assert f'dry_run_{side}_' in order["id"]
+    assert order["side"] == side
+    assert order["type"] == "limit"
+    assert order["symbol"] == "ETH/BTC"
+
+
+@pytest.mark.parametrize("side", [
+    ("buy"),
+    ("sell")
+])
+@pytest.mark.parametrize("ordertype,rate,marketprice", [
+    ("market", None, None),
+    ("market", 200, True),
+    ("limit", 200, None),
+    ("stop_loss_limit", 200, None)
+])
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_create_order(default_conf, mocker, side, ordertype, rate, marketprice, exchange_name):
+    api_mock = MagicMock()
+    order_id = 'test_prod_{}_{}'.format(side, randint(0, 10 ** 6))
+    api_mock.options = {} if not marketprice else {"createMarketBuyOrderRequiresPrice": True}
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+    default_conf['dry_run'] = False
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+    order = exchange.create_order(
+        pair='ETH/BTC', ordertype=ordertype, side=side, amount=1, rate=200)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
+    assert api_mock.create_order.call_args[0][1] == ordertype
+    assert api_mock.create_order.call_args[0][2] == side
+    assert api_mock.create_order.call_args[0][3] == 1
+    assert api_mock.create_order.call_args[0][4] is rate
+
+
+def test_buy_dry_run(default_conf, mocker):
+    default_conf['dry_run'] = True
+    exchange = get_patched_exchange(mocker, default_conf)
+
+    order = exchange.buy(pair='ETH/BTC', ordertype='limit',
+                         amount=1, rate=200, time_in_force='gtc')
+    assert 'id' in order
+    assert 'dry_run_buy_' in order['id']
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_buy_prod(default_conf, mocker, exchange_name):
+    api_mock = MagicMock()
+    order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
+    order_type = 'market'
+    time_in_force = 'gtc'
+    api_mock.options = {}
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+    default_conf['dry_run'] = False
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+    order = exchange.buy(pair='ETH/BTC', ordertype=order_type,
+                         amount=1, rate=200, time_in_force=time_in_force)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
+    assert api_mock.create_order.call_args[0][1] == order_type
+    assert api_mock.create_order.call_args[0][2] == 'buy'
+    assert api_mock.create_order.call_args[0][3] == 1
+    assert api_mock.create_order.call_args[0][4] is None
+
+    api_mock.create_order.reset_mock()
+    order_type = 'limit'
+    order = exchange.buy(
+        pair='ETH/BTC',
+        ordertype=order_type,
+        amount=1,
+        rate=200,
+        time_in_force=time_in_force)
+    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
+    assert api_mock.create_order.call_args[0][1] == order_type
+    assert api_mock.create_order.call_args[0][2] == 'buy'
+    assert api_mock.create_order.call_args[0][3] == 1
+    assert api_mock.create_order.call_args[0][4] == 200
+
+    # test exception handling
+    with pytest.raises(DependencyException):
+        api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("Not enough funds"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.buy(pair='ETH/BTC', ordertype=order_type,
+                     amount=1, rate=200, time_in_force=time_in_force)
+
+    with pytest.raises(DependencyException):
+        api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.buy(pair='ETH/BTC', ordertype='limit',
+                     amount=1, rate=200, time_in_force=time_in_force)
+
+    with pytest.raises(DependencyException):
+        api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.buy(pair='ETH/BTC', ordertype='market',
+                     amount=1, rate=200, time_in_force=time_in_force)
+
+    with pytest.raises(TemporaryError):
+        api_mock.create_order = MagicMock(side_effect=ccxt.NetworkError("Network disconnect"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.buy(pair='ETH/BTC', ordertype=order_type,
+                     amount=1, rate=200, time_in_force=time_in_force)
+
+    with pytest.raises(OperationalException):
+        api_mock.create_order = MagicMock(side_effect=ccxt.BaseError("Unknown error"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.buy(pair='ETH/BTC', ordertype=order_type,
+                     amount=1, rate=200, time_in_force=time_in_force)
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_buy_considers_time_in_force(default_conf, mocker, exchange_name):
+    api_mock = MagicMock()
+    order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
+    api_mock.options = {}
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+    default_conf['dry_run'] = False
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+    order_type = 'limit'
+    time_in_force = 'ioc'
+
+    order = exchange.buy(pair='ETH/BTC', ordertype=order_type,
+                         amount=1, rate=200, time_in_force=time_in_force)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
+    assert api_mock.create_order.call_args[0][1] == order_type
+    assert api_mock.create_order.call_args[0][2] == 'buy'
+    assert api_mock.create_order.call_args[0][3] == 1
+    assert api_mock.create_order.call_args[0][4] == 200
+    assert "timeInForce" in api_mock.create_order.call_args[0][5]
+    assert api_mock.create_order.call_args[0][5]["timeInForce"] == time_in_force
+
+    order_type = 'market'
+    time_in_force = 'ioc'
+
+    order = exchange.buy(pair='ETH/BTC', ordertype=order_type,
+                         amount=1, rate=200, time_in_force=time_in_force)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
+    assert api_mock.create_order.call_args[0][1] == order_type
+    assert api_mock.create_order.call_args[0][2] == 'buy'
+    assert api_mock.create_order.call_args[0][3] == 1
+    assert api_mock.create_order.call_args[0][4] is None
+    # Market orders should not send timeInForce!!
+    assert "timeInForce" not in api_mock.create_order.call_args[0][5]
+
+
+def test_sell_dry_run(default_conf, mocker):
+    default_conf['dry_run'] = True
+    exchange = get_patched_exchange(mocker, default_conf)
+
+    order = exchange.sell(pair='ETH/BTC', ordertype='limit', amount=1, rate=200)
+    assert 'id' in order
+    assert 'dry_run_sell_' in order['id']
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_sell_prod(default_conf, mocker, exchange_name):
+    api_mock = MagicMock()
+    order_id = 'test_prod_sell_{}'.format(randint(0, 10 ** 6))
+    order_type = 'market'
+    api_mock.options = {}
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+    default_conf['dry_run'] = False
+
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+    order = exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
+    assert api_mock.create_order.call_args[0][1] == order_type
+    assert api_mock.create_order.call_args[0][2] == 'sell'
+    assert api_mock.create_order.call_args[0][3] == 1
+    assert api_mock.create_order.call_args[0][4] is None
+
+    api_mock.create_order.reset_mock()
+    order_type = 'limit'
+    order = exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
+    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
+    assert api_mock.create_order.call_args[0][1] == order_type
+    assert api_mock.create_order.call_args[0][2] == 'sell'
+    assert api_mock.create_order.call_args[0][3] == 1
+    assert api_mock.create_order.call_args[0][4] == 200
+
+    # test exception handling
+    with pytest.raises(DependencyException):
+        api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("0 balance"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
+
+    with pytest.raises(DependencyException):
+        api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.sell(pair='ETH/BTC', ordertype='limit', amount=1, rate=200)
+
+    # Market orders don't require price, so the behaviour is slightly different
+    with pytest.raises(DependencyException):
+        api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.sell(pair='ETH/BTC', ordertype='market', amount=1, rate=200)
+
+    with pytest.raises(TemporaryError):
+        api_mock.create_order = MagicMock(side_effect=ccxt.NetworkError("No Connection"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
+
+    with pytest.raises(OperationalException):
+        api_mock.create_order = MagicMock(side_effect=ccxt.BaseError("DeadBeef"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_sell_considers_time_in_force(default_conf, mocker, exchange_name):
+    api_mock = MagicMock()
+    order_id = 'test_prod_sell_{}'.format(randint(0, 10 ** 6))
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+    api_mock.options = {}
+    default_conf['dry_run'] = False
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+    order_type = 'limit'
+    time_in_force = 'ioc'
+
+    order = exchange.sell(pair='ETH/BTC', ordertype=order_type,
+                          amount=1, rate=200, time_in_force=time_in_force)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
+    assert api_mock.create_order.call_args[0][1] == order_type
+    assert api_mock.create_order.call_args[0][2] == 'sell'
+    assert api_mock.create_order.call_args[0][3] == 1
+    assert api_mock.create_order.call_args[0][4] == 200
+    assert "timeInForce" in api_mock.create_order.call_args[0][5]
+    assert api_mock.create_order.call_args[0][5]["timeInForce"] == time_in_force
+
+    order_type = 'market'
+    time_in_force = 'ioc'
+    order = exchange.sell(pair='ETH/BTC', ordertype=order_type,
+                          amount=1, rate=200, time_in_force=time_in_force)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
+    assert api_mock.create_order.call_args[0][1] == order_type
+    assert api_mock.create_order.call_args[0][2] == 'sell'
+    assert api_mock.create_order.call_args[0][3] == 1
+    assert api_mock.create_order.call_args[0][4] is None
+    # Market orders should not send timeInForce!!
+    assert "timeInForce" not in api_mock.create_order.call_args[0][5]
+
+
+def test_get_balance_dry_run(default_conf, mocker):
+    default_conf['dry_run'] = True
+    default_conf['dry_run_wallet'] = 999.9
+
+    exchange = get_patched_exchange(mocker, default_conf)
+    assert exchange.get_balance(currency='BTC') == 999.9
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_get_balance_prod(default_conf, mocker, exchange_name):
+    api_mock = MagicMock()
+    api_mock.fetch_balance = MagicMock(return_value={'BTC': {'free': 123.4, 'total': 123.4}})
+    default_conf['dry_run'] = False
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+    assert exchange.get_balance(currency='BTC') == 123.4
+
+    with pytest.raises(OperationalException):
+        api_mock.fetch_balance = MagicMock(side_effect=ccxt.BaseError("Unknown error"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+        exchange.get_balance(currency='BTC')
+
+    with pytest.raises(TemporaryError, match=r'.*balance due to malformed exchange response:.*'):
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        mocker.patch('freqtrade.exchange.Exchange.get_balances', MagicMock(return_value={}))
+        mocker.patch('freqtrade.exchange.Kraken.get_balances', MagicMock(return_value={}))
+        exchange.get_balance(currency='BTC')
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_get_balances_dry_run(default_conf, mocker, exchange_name):
+    default_conf['dry_run'] = True
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    assert exchange.get_balances() == {}
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_get_balances_prod(default_conf, mocker, exchange_name):
+    balance_item = {
+        'free': 10.0,
+        'total': 10.0,
+        'used': 0.0
+    }
+
+    api_mock = MagicMock()
+    api_mock.fetch_balance = MagicMock(return_value={
+        '1ST': balance_item,
+        '2ST': balance_item,
+        '3ST': balance_item
+    })
+    default_conf['dry_run'] = False
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    assert len(exchange.get_balances()) == 3
+    assert exchange.get_balances()['1ST']['free'] == 10.0
+    assert exchange.get_balances()['1ST']['total'] == 10.0
+    assert exchange.get_balances()['1ST']['used'] == 0.0
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
+                           "get_balances", "fetch_balance")
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_get_tickers(default_conf, mocker, exchange_name):
+    api_mock = MagicMock()
+    tick = {'ETH/BTC': {
+        'symbol': 'ETH/BTC',
+        'bid': 0.5,
+        'ask': 1,
+        'last': 42,
+    }, 'BCH/BTC': {
+        'symbol': 'BCH/BTC',
+        'bid': 0.6,
+        'ask': 0.5,
+        'last': 41,
+    }
+    }
+    api_mock.fetch_tickers = MagicMock(return_value=tick)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    # retrieve original ticker
+    tickers = exchange.get_tickers()
+
+    assert 'ETH/BTC' in tickers
+    assert 'BCH/BTC' in tickers
+    assert tickers['ETH/BTC']['bid'] == 0.5
+    assert tickers['ETH/BTC']['ask'] == 1
+    assert tickers['BCH/BTC']['bid'] == 0.6
+    assert tickers['BCH/BTC']['ask'] == 0.5
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
+                           "get_tickers", "fetch_tickers")
+
+    with pytest.raises(OperationalException):
+        api_mock.fetch_tickers = MagicMock(side_effect=ccxt.NotSupported("DeadBeef"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.get_tickers()
+
+    api_mock.fetch_tickers = MagicMock(return_value={})
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    exchange.get_tickers()
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_fetch_ticker(default_conf, mocker, exchange_name):
+    api_mock = MagicMock()
+    tick = {
+        'symbol': 'ETH/BTC',
+        'bid': 0.00001098,
+        'ask': 0.00001099,
+        'last': 0.0001,
+    }
+    api_mock.fetch_ticker = MagicMock(return_value=tick)
+    api_mock.markets = {'ETH/BTC': {'active': True}}
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    # retrieve original ticker
+    ticker = exchange.fetch_ticker(pair='ETH/BTC')
+
+    assert ticker['bid'] == 0.00001098
+    assert ticker['ask'] == 0.00001099
+
+    # change the ticker
+    tick = {
+        'symbol': 'ETH/BTC',
+        'bid': 0.5,
+        'ask': 1,
+        'last': 42,
+    }
+    api_mock.fetch_ticker = MagicMock(return_value=tick)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+    # if not caching the result we should get the same ticker
+    # if not fetching a new result we should get the cached ticker
+    ticker = exchange.fetch_ticker(pair='ETH/BTC')
+
+    assert api_mock.fetch_ticker.call_count == 1
+    assert ticker['bid'] == 0.5
+    assert ticker['ask'] == 1
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
+                           "fetch_ticker", "fetch_ticker",
+                           pair='ETH/BTC')
+
+    api_mock.fetch_ticker = MagicMock(return_value={})
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    exchange.fetch_ticker(pair='ETH/BTC')
+
+    with pytest.raises(DependencyException, match=r'Pair XRP/ETH not available'):
+        exchange.fetch_ticker(pair='XRP/ETH')
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name):
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    ohlcv = [
+        [
+            arrow.utcnow().int_timestamp * 1000,  # unix timestamp ms
+            1,  # open
+            2,  # high
+            3,  # low
+            4,  # close
+            5,  # volume (in quote currency)
+        ]
+    ]
+    pair = 'ETH/BTC'
+
+    async def mock_candle_hist(pair, timeframe, since_ms):
+        return pair, timeframe, ohlcv
+
+    exchange._async_get_candle_history = Mock(wraps=mock_candle_hist)
+    # one_call calculation * 1.8 should do 2 calls
+
+    since = 5 * 60 * exchange._ft_has['ohlcv_candle_limit'] * 1.8
+    ret = exchange.get_historic_ohlcv(pair, "5m", int((
+        arrow.utcnow().int_timestamp - since) * 1000))
+
+    assert exchange._async_get_candle_history.call_count == 2
+    # Returns twice the above OHLCV data
+    assert len(ret) == 2
+
+    caplog.clear()
+
+    async def mock_get_candle_hist_error(pair, *args, **kwargs):
+        raise TimeoutError()
+
+    exchange._async_get_candle_history = MagicMock(side_effect=mock_get_candle_hist_error)
+    ret = exchange.get_historic_ohlcv(pair, "5m", int(
+        (arrow.utcnow().int_timestamp - since) * 1000))
+    assert log_has_re(r"Async code raised an exception: .*", caplog)
+
+
+def test_refresh_latest_ohlcv(mocker, default_conf, caplog) -> None:
+    ohlcv = [
+        [
+            (arrow.utcnow().int_timestamp - 1) * 1000,  # unix timestamp ms
+            1,  # open
+            2,  # high
+            3,  # low
+            4,  # close
+            5,  # volume (in quote currency)
+        ],
+        [
+            arrow.utcnow().int_timestamp * 1000,  # unix timestamp ms
+            3,  # open
+            1,  # high
+            4,  # low
+            6,  # close
+            5,  # volume (in quote currency)
+        ]
+    ]
+
+    caplog.set_level(logging.DEBUG)
+    exchange = get_patched_exchange(mocker, default_conf)
+    exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
+
+    pairs = [('IOTA/ETH', '5m'), ('XRP/ETH', '5m')]
+    # empty dicts
+    assert not exchange._klines
+    exchange.refresh_latest_ohlcv(pairs)
+
+    assert log_has(f'Refreshing candle (OHLCV) data for {len(pairs)} pairs', caplog)
+    assert exchange._klines
+    assert exchange._api_async.fetch_ohlcv.call_count == 2
+    for pair in pairs:
+        assert isinstance(exchange.klines(pair), DataFrame)
+        assert len(exchange.klines(pair)) > 0
+
+        # klines function should return a different object on each call
+        # if copy is "True"
+        assert exchange.klines(pair) is not exchange.klines(pair)
+        assert exchange.klines(pair) is not exchange.klines(pair, copy=True)
+        assert exchange.klines(pair, copy=True) is not exchange.klines(pair, copy=True)
+        assert exchange.klines(pair, copy=False) is exchange.klines(pair, copy=False)
+
+    # test caching
+    exchange.refresh_latest_ohlcv([('IOTA/ETH', '5m'), ('XRP/ETH', '5m')])
+
+    assert exchange._api_async.fetch_ohlcv.call_count == 2
+    assert log_has(f"Using cached candle (OHLCV) data for pair {pairs[0][0]}, "
+                   f"timeframe {pairs[0][1]} ...",
+                   caplog)
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+async def test__async_get_candle_history(default_conf, mocker, caplog, exchange_name):
+    ohlcv = [
+        [
+            arrow.utcnow().int_timestamp * 1000,  # unix timestamp ms
+            1,  # open
+            2,  # high
+            3,  # low
+            4,  # close
+            5,  # volume (in quote currency)
+        ]
+    ]
+
+    caplog.set_level(logging.DEBUG)
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    # Monkey-patch async function
+    exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
+
+    pair = 'ETH/BTC'
+    res = await exchange._async_get_candle_history(pair, "5m")
+    assert type(res) is tuple
+    assert len(res) == 3
+    assert res[0] == pair
+    assert res[1] == "5m"
+    assert res[2] == ohlcv
+    assert exchange._api_async.fetch_ohlcv.call_count == 1
+    assert not log_has(f"Using cached candle (OHLCV) data for {pair} ...", caplog)
+
+    # exchange = Exchange(default_conf)
+    await async_ccxt_exception(mocker, default_conf, MagicMock(),
+                               "_async_get_candle_history", "fetch_ohlcv",
+                               pair='ABCD/BTC', timeframe=default_conf['timeframe'])
+
+    api_mock = MagicMock()
+    with pytest.raises(OperationalException,
+                       match=r'Could not fetch historical candle \(OHLCV\) data.*'):
+        api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.BaseError("Unknown error"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        await exchange._async_get_candle_history(pair, "5m",
+                                                 (arrow.utcnow().int_timestamp - 2000) * 1000)
+
+    with pytest.raises(OperationalException, match=r'Exchange.* does not support fetching '
+                                                   r'historical candle \(OHLCV\) data\..*'):
+        api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.NotSupported("Not supported"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        await exchange._async_get_candle_history(pair, "5m",
+                                                 (arrow.utcnow().int_timestamp - 2000) * 1000)
+
+
+@pytest.mark.asyncio
+async def test__async_get_candle_history_empty(default_conf, mocker, caplog):
+    """ Test empty exchange result """
+    ohlcv = []
+
+    caplog.set_level(logging.DEBUG)
+    exchange = get_patched_exchange(mocker, default_conf)
+    # Monkey-patch async function
+    exchange._api_async.fetch_ohlcv = get_mock_coro([])
+
+    exchange = Exchange(default_conf)
+    pair = 'ETH/BTC'
+    res = await exchange._async_get_candle_history(pair, "5m")
+    assert type(res) is tuple
+    assert len(res) == 3
+    assert res[0] == pair
+    assert res[1] == "5m"
+    assert res[2] == ohlcv
+    assert exchange._api_async.fetch_ohlcv.call_count == 1
+
+
+def test_refresh_latest_ohlcv_inv_result(default_conf, mocker, caplog):
+
+    async def mock_get_candle_hist(pair, *args, **kwargs):
+        if pair == 'ETH/BTC':
+            return [[]]
+        else:
+            raise TypeError()
+
+    exchange = get_patched_exchange(mocker, default_conf)
+
+    # Monkey-patch async function with empty result
+    exchange._api_async.fetch_ohlcv = MagicMock(side_effect=mock_get_candle_hist)
+
+    pairs = [("ETH/BTC", "5m"), ("XRP/BTC", "5m")]
+    res = exchange.refresh_latest_ohlcv(pairs)
+    assert exchange._klines
+    assert exchange._api_async.fetch_ohlcv.call_count == 2
+
+    assert type(res) is list
+    assert len(res) == 2
+    # Test that each is in list at least once as order is not guaranteed
+    assert type(res[0]) is tuple or type(res[1]) is tuple
+    assert type(res[0]) is TypeError or type(res[1]) is TypeError
+    assert log_has("Error loading ETH/BTC. Result was [[]].", caplog)
+    assert log_has("Async code raised an exception: TypeError", caplog)
+
+
+def test_get_next_limit_in_list():
+    limit_range = [5, 10, 20, 50, 100, 500, 1000]
+    assert Exchange.get_next_limit_in_list(1, limit_range) == 5
+    assert Exchange.get_next_limit_in_list(5, limit_range) == 5
+    assert Exchange.get_next_limit_in_list(6, limit_range) == 10
+    assert Exchange.get_next_limit_in_list(9, limit_range) == 10
+    assert Exchange.get_next_limit_in_list(10, limit_range) == 10
+    assert Exchange.get_next_limit_in_list(11, limit_range) == 20
+    assert Exchange.get_next_limit_in_list(19, limit_range) == 20
+    assert Exchange.get_next_limit_in_list(21, limit_range) == 50
+    assert Exchange.get_next_limit_in_list(51, limit_range) == 100
+    assert Exchange.get_next_limit_in_list(1000, limit_range) == 1000
+    # Going over the limit ...
+    assert Exchange.get_next_limit_in_list(1001, limit_range) == 1000
+    assert Exchange.get_next_limit_in_list(2000, limit_range) == 1000
+
+    assert Exchange.get_next_limit_in_list(21, None) == 21
+    assert Exchange.get_next_limit_in_list(100, None) == 100
+    assert Exchange.get_next_limit_in_list(1000, None) == 1000
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_fetch_l2_order_book(default_conf, mocker, order_book_l2, exchange_name):
+    default_conf['exchange']['name'] = exchange_name
+    api_mock = MagicMock()
+
+    api_mock.fetch_l2_order_book = order_book_l2
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    order_book = exchange.fetch_l2_order_book(pair='ETH/BTC', limit=10)
+    assert 'bids' in order_book
+    assert 'asks' in order_book
+    assert len(order_book['bids']) == 10
+    assert len(order_book['asks']) == 10
+    assert api_mock.fetch_l2_order_book.call_args_list[0][0][0] == 'ETH/BTC'
+
+    for val in [1, 5, 10, 12, 20, 50, 100]:
+        api_mock.fetch_l2_order_book.reset_mock()
+
+        order_book = exchange.fetch_l2_order_book(pair='ETH/BTC', limit=val)
+        assert api_mock.fetch_l2_order_book.call_args_list[0][0][0] == 'ETH/BTC'
+        # Not all exchanges support all limits for orderbook
+        if not exchange._ft_has['l2_limit_range'] or val in exchange._ft_has['l2_limit_range']:
+            assert api_mock.fetch_l2_order_book.call_args_list[0][0][1] == val
+        else:
+            next_limit = exchange.get_next_limit_in_list(val, exchange._ft_has['l2_limit_range'])
+            assert api_mock.fetch_l2_order_book.call_args_list[0][0][1] == next_limit
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_fetch_l2_order_book_exception(default_conf, mocker, exchange_name):
+    api_mock = MagicMock()
+    with pytest.raises(OperationalException):
+        api_mock.fetch_l2_order_book = MagicMock(side_effect=ccxt.NotSupported("Not supported"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.fetch_l2_order_book(pair='ETH/BTC', limit=50)
+    with pytest.raises(TemporaryError):
+        api_mock.fetch_l2_order_book = MagicMock(side_effect=ccxt.NetworkError("DeadBeef"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.fetch_l2_order_book(pair='ETH/BTC', limit=50)
+    with pytest.raises(OperationalException):
+        api_mock.fetch_l2_order_book = MagicMock(side_effect=ccxt.BaseError("DeadBeef"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.fetch_l2_order_book(pair='ETH/BTC', limit=50)
+
+
+def make_fetch_ohlcv_mock(data):
+    def fetch_ohlcv_mock(pair, timeframe, since):
+        if since:
+            assert since > data[-1][0]
+            return []
+        return data
+    return fetch_ohlcv_mock
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+@pytest.mark.asyncio
+async def test___async_get_candle_history_sort(default_conf, mocker, exchange_name):
+    def sort_data(data, key):
+        return sorted(data, key=key)
+
+    # GDAX use-case (real data from GDAX)
+    # This OHLCV data is ordered DESC (newest first, oldest last)
+    ohlcv = [
+        [1527833100000, 0.07666, 0.07671, 0.07666, 0.07668, 16.65244264],
+        [1527832800000, 0.07662, 0.07666, 0.07662, 0.07666, 1.30051526],
+        [1527832500000, 0.07656, 0.07661, 0.07656, 0.07661, 12.034778840000001],
+        [1527832200000, 0.07658, 0.07658, 0.07655, 0.07656, 0.59780186],
+        [1527831900000, 0.07658, 0.07658, 0.07658, 0.07658, 1.76278136],
+        [1527831600000, 0.07658, 0.07658, 0.07658, 0.07658, 2.22646521],
+        [1527831300000, 0.07655, 0.07657, 0.07655, 0.07657, 1.1753],
+        [1527831000000, 0.07654, 0.07654, 0.07651, 0.07651, 0.8073060299999999],
+        [1527830700000, 0.07652, 0.07652, 0.07651, 0.07652, 10.04822687],
+        [1527830400000, 0.07649, 0.07651, 0.07649, 0.07651, 2.5734867]
+    ]
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
+    sort_mock = mocker.patch('freqtrade.exchange.exchange.sorted', MagicMock(side_effect=sort_data))
+    # Test the OHLCV data sort
+    res = await exchange._async_get_candle_history('ETH/BTC', default_conf['timeframe'])
+    assert res[0] == 'ETH/BTC'
+    res_ohlcv = res[2]
+
+    assert sort_mock.call_count == 1
+    assert res_ohlcv[0][0] == 1527830400000
+    assert res_ohlcv[0][1] == 0.07649
+    assert res_ohlcv[0][2] == 0.07651
+    assert res_ohlcv[0][3] == 0.07649
+    assert res_ohlcv[0][4] == 0.07651
+    assert res_ohlcv[0][5] == 2.5734867
+
+    assert res_ohlcv[9][0] == 1527833100000
+    assert res_ohlcv[9][1] == 0.07666
+    assert res_ohlcv[9][2] == 0.07671
+    assert res_ohlcv[9][3] == 0.07666
+    assert res_ohlcv[9][4] == 0.07668
+    assert res_ohlcv[9][5] == 16.65244264
+
+    # Bittrex use-case (real data from Bittrex)
+    # This OHLCV data is ordered ASC (oldest first, newest last)
+    ohlcv = [
+        [1527827700000, 0.07659999, 0.0766, 0.07627, 0.07657998, 1.85216924],
+        [1527828000000, 0.07657995, 0.07657995, 0.0763, 0.0763, 26.04051037],
+        [1527828300000, 0.0763, 0.07659998, 0.0763, 0.0764, 10.36434124],
+        [1527828600000, 0.0764, 0.0766, 0.0764, 0.0766, 5.71044773],
+        [1527828900000, 0.0764, 0.07666998, 0.0764, 0.07666998, 47.48888565],
+        [1527829200000, 0.0765, 0.07672999, 0.0765, 0.07672999, 3.37640326],
+        [1527829500000, 0.0766, 0.07675, 0.0765, 0.07675, 8.36203831],
+        [1527829800000, 0.07675, 0.07677999, 0.07620002, 0.076695, 119.22963884],
+        [1527830100000, 0.076695, 0.07671, 0.07624171, 0.07671, 1.80689244],
+        [1527830400000, 0.07671, 0.07674399, 0.07629216, 0.07655213, 2.31452783]
+    ]
+    exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
+    # Reset sort mock
+    sort_mock = mocker.patch('freqtrade.exchange.sorted', MagicMock(side_effect=sort_data))
+    # Test the OHLCV data sort
+    res = await exchange._async_get_candle_history('ETH/BTC', default_conf['timeframe'])
+    assert res[0] == 'ETH/BTC'
+    assert res[1] == default_conf['timeframe']
+    res_ohlcv = res[2]
+    # Sorted not called again - data is already in order
+    assert sort_mock.call_count == 0
+    assert res_ohlcv[0][0] == 1527827700000
+    assert res_ohlcv[0][1] == 0.07659999
+    assert res_ohlcv[0][2] == 0.0766
+    assert res_ohlcv[0][3] == 0.07627
+    assert res_ohlcv[0][4] == 0.07657998
+    assert res_ohlcv[0][5] == 1.85216924
+
+    assert res_ohlcv[9][0] == 1527830400000
+    assert res_ohlcv[9][1] == 0.07671
+    assert res_ohlcv[9][2] == 0.07674399
+    assert res_ohlcv[9][3] == 0.07629216
+    assert res_ohlcv[9][4] == 0.07655213
+    assert res_ohlcv[9][5] == 2.31452783
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+async def test__async_fetch_trades(default_conf, mocker, caplog, exchange_name,
+                                   fetch_trades_result):
+
+    caplog.set_level(logging.DEBUG)
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    # Monkey-patch async function
+    exchange._api_async.fetch_trades = get_mock_coro(fetch_trades_result)
+
+    pair = 'ETH/BTC'
+    res = await exchange._async_fetch_trades(pair, since=None, params=None)
+    assert type(res) is list
+    assert isinstance(res[0], list)
+    assert isinstance(res[1], list)
+
+    assert exchange._api_async.fetch_trades.call_count == 1
+    assert exchange._api_async.fetch_trades.call_args[0][0] == pair
+    assert exchange._api_async.fetch_trades.call_args[1]['limit'] == 1000
+
+    assert log_has_re(f"Fetching trades for pair {pair}, since .*", caplog)
+    caplog.clear()
+    exchange._api_async.fetch_trades.reset_mock()
+    res = await exchange._async_fetch_trades(pair, since=None, params={'from': '123'})
+    assert exchange._api_async.fetch_trades.call_count == 1
+    assert exchange._api_async.fetch_trades.call_args[0][0] == pair
+    assert exchange._api_async.fetch_trades.call_args[1]['limit'] == 1000
+    assert exchange._api_async.fetch_trades.call_args[1]['params'] == {'from': '123'}
+    assert log_has_re(f"Fetching trades for pair {pair}, params: .*", caplog)
+
+    exchange = Exchange(default_conf)
+    await async_ccxt_exception(mocker, default_conf, MagicMock(),
+                               "_async_fetch_trades", "fetch_trades",
+                               pair='ABCD/BTC', since=None)
+
+    api_mock = MagicMock()
+    with pytest.raises(OperationalException, match=r'Could not fetch trade data*'):
+        api_mock.fetch_trades = MagicMock(side_effect=ccxt.BaseError("Unknown error"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        await exchange._async_fetch_trades(pair, since=(arrow.utcnow().int_timestamp - 2000) * 1000)
+
+    with pytest.raises(OperationalException, match=r'Exchange.* does not support fetching '
+                                                   r'historical trade data\..*'):
+        api_mock.fetch_trades = MagicMock(side_effect=ccxt.NotSupported("Not supported"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        await exchange._async_fetch_trades(pair, since=(arrow.utcnow().int_timestamp - 2000) * 1000)
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+async def test__async_get_trade_history_id(default_conf, mocker, caplog, exchange_name,
+                                           trades_history):
+
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    pagination_arg = exchange._trades_pagination_arg
+
+    async def mock_get_trade_hist(pair, *args, **kwargs):
+        if 'since' in kwargs:
+            # Return first 3
+            return trades_history[:-2]
+        elif kwargs.get('params', {}).get(pagination_arg) == trades_history[-3][1]:
+            # Return 2
+            return trades_history[-3:-1]
+        else:
+            # Return last 2
+            return trades_history[-2:]
+    # Monkey-patch async function
+    exchange._async_fetch_trades = MagicMock(side_effect=mock_get_trade_hist)
+
+    pair = 'ETH/BTC'
+    ret = await exchange._async_get_trade_history_id(pair, since=trades_history[0][0],
+                                                     until=trades_history[-1][0]-1)
+    assert type(ret) is tuple
+    assert ret[0] == pair
+    assert type(ret[1]) is list
+    assert len(ret[1]) == len(trades_history)
+    assert exchange._async_fetch_trades.call_count == 3
+    fetch_trades_cal = exchange._async_fetch_trades.call_args_list
+    # first call (using since, not fromId)
+    assert fetch_trades_cal[0][0][0] == pair
+    assert fetch_trades_cal[0][1]['since'] == trades_history[0][0]
+
+    # 2nd call
+    assert fetch_trades_cal[1][0][0] == pair
+    assert 'params' in fetch_trades_cal[1][1]
+    assert exchange._ft_has['trades_pagination_arg'] in fetch_trades_cal[1][1]['params']
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+async def test__async_get_trade_history_time(default_conf, mocker, caplog, exchange_name,
+                                             trades_history):
+
+    caplog.set_level(logging.DEBUG)
+
+    async def mock_get_trade_hist(pair, *args, **kwargs):
+        if kwargs['since'] == trades_history[0][0]:
+            return trades_history[:-1]
+        else:
+            return trades_history[-1:]
+
+    caplog.set_level(logging.DEBUG)
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    # Monkey-patch async function
+    exchange._async_fetch_trades = MagicMock(side_effect=mock_get_trade_hist)
+    pair = 'ETH/BTC'
+    ret = await exchange._async_get_trade_history_time(pair, since=trades_history[0][0],
+                                                       until=trades_history[-1][0]-1)
+    assert type(ret) is tuple
+    assert ret[0] == pair
+    assert type(ret[1]) is list
+    assert len(ret[1]) == len(trades_history)
+    assert exchange._async_fetch_trades.call_count == 2
+    fetch_trades_cal = exchange._async_fetch_trades.call_args_list
+    # first call (using since, not fromId)
+    assert fetch_trades_cal[0][0][0] == pair
+    assert fetch_trades_cal[0][1]['since'] == trades_history[0][0]
+
+    # 2nd call
+    assert fetch_trades_cal[1][0][0] == pair
+    assert fetch_trades_cal[0][1]['since'] == trades_history[0][0]
+    assert log_has_re(r"Stopping because until was reached.*", caplog)
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+async def test__async_get_trade_history_time_empty(default_conf, mocker, caplog, exchange_name,
+                                                   trades_history):
+
+    caplog.set_level(logging.DEBUG)
+
+    async def mock_get_trade_hist(pair, *args, **kwargs):
+        if kwargs['since'] == trades_history[0][0]:
+            return trades_history[:-1]
+        else:
+            return []
+
+    caplog.set_level(logging.DEBUG)
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    # Monkey-patch async function
+    exchange._async_fetch_trades = MagicMock(side_effect=mock_get_trade_hist)
+    pair = 'ETH/BTC'
+    ret = await exchange._async_get_trade_history_time(pair, since=trades_history[0][0],
+                                                       until=trades_history[-1][0]-1)
+    assert type(ret) is tuple
+    assert ret[0] == pair
+    assert type(ret[1]) is list
+    assert len(ret[1]) == len(trades_history) - 1
+    assert exchange._async_fetch_trades.call_count == 2
+    fetch_trades_cal = exchange._async_fetch_trades.call_args_list
+    # first call (using since, not fromId)
+    assert fetch_trades_cal[0][0][0] == pair
+    assert fetch_trades_cal[0][1]['since'] == trades_history[0][0]
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_get_historic_trades(default_conf, mocker, caplog, exchange_name, trades_history):
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+
+    pair = 'ETH/BTC'
+
+    exchange._async_get_trade_history_id = get_mock_coro((pair, trades_history))
+    exchange._async_get_trade_history_time = get_mock_coro((pair, trades_history))
+    ret = exchange.get_historic_trades(pair, since=trades_history[0][0],
+                                       until=trades_history[-1][0])
+
+    # Depending on the exchange, one or the other method should be called
+    assert sum([exchange._async_get_trade_history_id.call_count,
+                exchange._async_get_trade_history_time.call_count]) == 1
+
+    assert len(ret) == 2
+    assert ret[0] == pair
+    assert len(ret[1]) == len(trades_history)
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_get_historic_trades_notsupported(default_conf, mocker, caplog, exchange_name,
+                                          trades_history):
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=False)
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+
+    pair = 'ETH/BTC'
+
+    with pytest.raises(OperationalException,
+                       match="This exchange does not suport downloading Trades."):
+        exchange.get_historic_trades(pair, since=trades_history[0][0],
+                                     until=trades_history[-1][0])
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_cancel_order_dry_run(default_conf, mocker, exchange_name):
+    default_conf['dry_run'] = True
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    assert exchange.cancel_order(order_id='123', pair='TKN/BTC') == {}
+    assert exchange.cancel_stoploss_order(order_id='123', pair='TKN/BTC') == {}
+
+    order = exchange.buy('ETH/BTC', 'limit', 5, 0.55, 'gtc')
+
+    cancel_order = exchange.cancel_order(order_id=order['id'], pair='ETH/BTC')
+    assert order['id'] == cancel_order['id']
+    assert order['amount'] == cancel_order['amount']
+    assert order['symbol'] == cancel_order['symbol']
+    assert cancel_order['status'] == 'canceled'
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+@pytest.mark.parametrize("order,result", [
+    ({'status': 'closed', 'filled': 10}, False),
+    ({'status': 'closed', 'filled': 0.0}, True),
+    ({'status': 'canceled', 'filled': 0.0}, True),
+    ({'status': 'canceled', 'filled': 10.0}, False),
+    ({'status': 'unknown', 'filled': 10.0}, False),
+    ({'result': 'testest123'}, False),
+    ])
+def test_check_order_canceled_empty(mocker, default_conf, exchange_name, order, result):
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    assert exchange.check_order_canceled_empty(order) == result
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+@pytest.mark.parametrize("order,result", [
+    ({'status': 'closed', 'amount': 10, 'fee': {}}, True),
+    ({'status': 'closed', 'amount': 0.0, 'fee': {}}, True),
+    ({'status': 'canceled', 'amount': 0.0, 'fee': {}}, True),
+    ({'status': 'canceled', 'amount': 10.0}, False),
+    ({'amount': 10.0, 'fee': {}}, False),
+    ({'result': 'testest123'}, False),
+    ('hello_world', False),
+])
+def test_is_cancel_order_result_suitable(mocker, default_conf, exchange_name, order, result):
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    assert exchange.is_cancel_order_result_suitable(order) == result
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+@pytest.mark.parametrize("corder,call_corder,call_forder", [
+    ({'status': 'closed', 'amount': 10, 'fee': {}}, 1, 0),
+    ({'amount': 10, 'fee': {}}, 1, 1),
+])
+def test_cancel_order_with_result(default_conf, mocker, exchange_name, corder,
+                                  call_corder, call_forder):
+    default_conf['dry_run'] = False
+    api_mock = MagicMock()
+    api_mock.cancel_order = MagicMock(return_value=corder)
+    api_mock.fetch_order = MagicMock(return_value={})
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    res = exchange.cancel_order_with_result('1234', 'ETH/BTC', 1234)
+    assert isinstance(res, dict)
+    assert api_mock.cancel_order.call_count == call_corder
+    assert api_mock.fetch_order.call_count == call_forder
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_cancel_order_with_result_error(default_conf, mocker, exchange_name, caplog):
+    default_conf['dry_run'] = False
+    api_mock = MagicMock()
+    api_mock.cancel_order = MagicMock(side_effect=ccxt.InvalidOrder("Did not find order"))
+    api_mock.fetch_order = MagicMock(side_effect=ccxt.InvalidOrder("Did not find order"))
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+    res = exchange.cancel_order_with_result('1234', 'ETH/BTC', 1541)
+    assert isinstance(res, dict)
+    assert log_has("Could not cancel order 1234 for ETH/BTC.", caplog)
+    assert log_has("Could not fetch cancelled order 1234.", caplog)
+    assert res['amount'] == 1541
+
+
+# Ensure that if not dry_run, we should call API
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_cancel_order(default_conf, mocker, exchange_name):
+    default_conf['dry_run'] = False
+    api_mock = MagicMock()
+    api_mock.cancel_order = MagicMock(return_value=123)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    assert exchange.cancel_order(order_id='_', pair='TKN/BTC') == 123
+
+    with pytest.raises(InvalidOrderException):
+        api_mock.cancel_order = MagicMock(side_effect=ccxt.InvalidOrder("Did not find order"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.cancel_order(order_id='_', pair='TKN/BTC')
+    assert api_mock.cancel_order.call_count == 1
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
+                           "cancel_order", "cancel_order",
+                           order_id='_', pair='TKN/BTC')
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_cancel_stoploss_order(default_conf, mocker, exchange_name):
+    default_conf['dry_run'] = False
+    api_mock = MagicMock()
+    api_mock.cancel_order = MagicMock(return_value=123)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    assert exchange.cancel_stoploss_order(order_id='_', pair='TKN/BTC') == 123
+
+    with pytest.raises(InvalidOrderException):
+        api_mock.cancel_order = MagicMock(side_effect=ccxt.InvalidOrder("Did not find order"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.cancel_stoploss_order(order_id='_', pair='TKN/BTC')
+    assert api_mock.cancel_order.call_count == 1
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
+                           "cancel_stoploss_order", "cancel_order",
+                           order_id='_', pair='TKN/BTC')
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_fetch_order(default_conf, mocker, exchange_name):
+    default_conf['dry_run'] = True
+    order = MagicMock()
+    order.myid = 123
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    exchange._dry_run_open_orders['X'] = order
+    assert exchange.fetch_order('X', 'TKN/BTC').myid == 123
+
+    with pytest.raises(InvalidOrderException, match=r'Tried to get an invalid dry-run-order.*'):
+        exchange.fetch_order('Y', 'TKN/BTC')
+
+    default_conf['dry_run'] = False
+    api_mock = MagicMock()
+    api_mock.fetch_order = MagicMock(return_value=456)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    assert exchange.fetch_order('X', 'TKN/BTC') == 456
+
+    with pytest.raises(InvalidOrderException):
+        api_mock.fetch_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.fetch_order(order_id='_', pair='TKN/BTC')
+    assert api_mock.fetch_order.call_count == 1
+
+    api_mock.fetch_order = MagicMock(side_effect=ccxt.OrderNotFound("Order not found"))
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    with patch('freqtrade.exchange.common.time.sleep') as tm:
+        with pytest.raises(InvalidOrderException):
+            exchange.fetch_order(order_id='_', pair='TKN/BTC')
+        # Ensure backoff is called
+        assert tm.call_args_list[0][0][0] == 1
+        assert tm.call_args_list[1][0][0] == 2
+        if API_FETCH_ORDER_RETRY_COUNT > 2:
+            assert tm.call_args_list[2][0][0] == 5
+        if API_FETCH_ORDER_RETRY_COUNT > 3:
+            assert tm.call_args_list[3][0][0] == 10
+    assert api_mock.fetch_order.call_count == API_FETCH_ORDER_RETRY_COUNT + 1
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
+                           'fetch_order', 'fetch_order', retries=API_FETCH_ORDER_RETRY_COUNT + 1,
+                           order_id='_', pair='TKN/BTC')
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_fetch_stoploss_order(default_conf, mocker, exchange_name):
+    # Don't test FTX here - that needs a seperate test
+    if exchange_name == 'ftx':
+        return
+    default_conf['dry_run'] = True
+    order = MagicMock()
+    order.myid = 123
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+    exchange._dry_run_open_orders['X'] = order
+    assert exchange.fetch_stoploss_order('X', 'TKN/BTC').myid == 123
+
+    with pytest.raises(InvalidOrderException, match=r'Tried to get an invalid dry-run-order.*'):
+        exchange.fetch_stoploss_order('Y', 'TKN/BTC')
+
+    default_conf['dry_run'] = False
+    api_mock = MagicMock()
+    api_mock.fetch_order = MagicMock(return_value=456)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+    assert exchange.fetch_stoploss_order('X', 'TKN/BTC') == 456
+
+    with pytest.raises(InvalidOrderException):
+        api_mock.fetch_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+        exchange.fetch_stoploss_order(order_id='_', pair='TKN/BTC')
+    assert api_mock.fetch_order.call_count == 1
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
+                           'fetch_stoploss_order', 'fetch_order',
+                           retries=API_FETCH_ORDER_RETRY_COUNT + 1,
+                           order_id='_', pair='TKN/BTC')
+
+
+def test_fetch_order_or_stoploss_order(default_conf, mocker):
+    exchange = get_patched_exchange(mocker, default_conf, id='binance')
+    fetch_order_mock = MagicMock()
+    fetch_stoploss_order_mock = MagicMock()
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          fetch_order=fetch_order_mock,
+                          fetch_stoploss_order=fetch_stoploss_order_mock,
+                          )
+
+    exchange.fetch_order_or_stoploss_order('1234', 'ETH/BTC', False)
+    assert fetch_order_mock.call_count == 1
+    assert fetch_order_mock.call_args_list[0][0][0] == '1234'
+    assert fetch_order_mock.call_args_list[0][0][1] == 'ETH/BTC'
+    assert fetch_stoploss_order_mock.call_count == 0
+
+    fetch_order_mock.reset_mock()
+    fetch_stoploss_order_mock.reset_mock()
+
+    exchange.fetch_order_or_stoploss_order('1234', 'ETH/BTC', True)
+    assert fetch_order_mock.call_count == 0
+    assert fetch_stoploss_order_mock.call_count == 1
+    assert fetch_stoploss_order_mock.call_args_list[0][0][0] == '1234'
+    assert fetch_stoploss_order_mock.call_args_list[0][0][1] == 'ETH/BTC'
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_name(default_conf, mocker, exchange_name):
+    exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
+
+    assert exchange.name == exchange_name.title()
+    assert exchange.id == exchange_name
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_get_trades_for_order(default_conf, mocker, exchange_name):
+
+    order_id = 'ABCD-ABCD'
+    since = datetime(2018, 5, 5, 0, 0, 0)
+    default_conf["dry_run"] = False
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+    api_mock = MagicMock()
+
+    api_mock.fetch_my_trades = MagicMock(return_value=[{'id': 'TTR67E-3PFBD-76IISV',
+                                                        'order': 'ABCD-ABCD',
+                                                        'info': {'pair': 'XLTCZBTC',
+                                                                 'time': 1519860024.4388,
+                                                                 'type': 'buy',
+                                                                 'ordertype': 'limit',
+                                                                 'price': '20.00000',
+                                                                 'cost': '38.62000',
+                                                                 'fee': '0.06179',
+                                                                 'vol': '5',
+                                                                 'id': 'ABCD-ABCD'},
+                                                        'timestamp': 1519860024438,
+                                                        'datetime': '2018-02-28T23:20:24.438Z',
+                                                        'symbol': 'LTC/BTC',
+                                                        'type': 'limit',
+                                                        'side': 'buy',
+                                                        'price': 165.0,
+                                                        'amount': 0.2340606,
+                                                        'fee': {'cost': 0.06179, 'currency': 'BTC'}
+                                                        }])
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+    orders = exchange.get_trades_for_order(order_id, 'LTC/BTC', since)
+    assert len(orders) == 1
+    assert orders[0]['price'] == 165
+    assert api_mock.fetch_my_trades.call_count == 1
+    # since argument should be
+    assert isinstance(api_mock.fetch_my_trades.call_args[0][1], int)
+    assert api_mock.fetch_my_trades.call_args[0][0] == 'LTC/BTC'
+    # Same test twice, hardcoded number and doing the same calculation
+    assert api_mock.fetch_my_trades.call_args[0][1] == 1525478395000
+    assert api_mock.fetch_my_trades.call_args[0][1] == int(since.replace(
+        tzinfo=timezone.utc).timestamp() - 5) * 1000
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
+                           'get_trades_for_order', 'fetch_my_trades',
+                           order_id=order_id, pair='LTC/BTC', since=since)
+
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=False))
+    assert exchange.get_trades_for_order(order_id, 'LTC/BTC', since) == []
+
+
+@pytest.mark.parametrize("exchange_name", EXCHANGES)
+def test_get_fee(default_conf, mocker, exchange_name):
+    api_mock = MagicMock()
+    api_mock.calculate_fee = MagicMock(return_value={
+        'type': 'taker',
+        'currency': 'BTC',
+        'rate': 0.025,
+        'cost': 0.05
+    })
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
+
+    assert exchange.get_fee('ETH/BTC') == 0.025
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
+                           'get_fee', 'calculate_fee', symbol="ETH/BTC")
+
+
+def test_stoploss_order_unsupported_exchange(default_conf, mocker):
+    exchange = get_patched_exchange(mocker, default_conf, 'bittrex')
+    with pytest.raises(OperationalException, match=r"stoploss is not implemented .*"):
+        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+    with pytest.raises(OperationalException, match=r"stoploss is not implemented .*"):
+        exchange.stoploss_adjust(1, {})
+
+
+def test_merge_ft_has_dict(default_conf, mocker):
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          _init_ccxt=MagicMock(return_value=MagicMock()),
+                          _load_async_markets=MagicMock(),
+                          validate_pairs=MagicMock(),
+                          validate_timeframes=MagicMock(),
+                          validate_stakecurrency=MagicMock()
+                          )
+    ex = Exchange(default_conf)
+    assert ex._ft_has == Exchange._ft_has_default
+
+    ex = Kraken(default_conf)
+    assert ex._ft_has != Exchange._ft_has_default
+    assert ex._ft_has['trades_pagination'] == 'id'
+    assert ex._ft_has['trades_pagination_arg'] == 'since'
+
+    # Binance defines different values
+    ex = Binance(default_conf)
+    assert ex._ft_has != Exchange._ft_has_default
+    assert ex._ft_has['stoploss_on_exchange']
+    assert ex._ft_has['order_time_in_force'] == ['gtc', 'fok', 'ioc']
+    assert ex._ft_has['trades_pagination'] == 'id'
+    assert ex._ft_has['trades_pagination_arg'] == 'fromId'
+
+    conf = copy.deepcopy(default_conf)
+    conf['exchange']['_ft_has_params'] = {"DeadBeef": 20,
+                                          "stoploss_on_exchange": False}
+    # Use settings from configuration (overriding stoploss_on_exchange)
+    ex = Binance(conf)
+    assert ex._ft_has != Exchange._ft_has_default
+    assert not ex._ft_has['stoploss_on_exchange']
+    assert ex._ft_has['DeadBeef'] == 20
+
+
+def test_get_valid_pair_combination(default_conf, mocker, markets):
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          _init_ccxt=MagicMock(return_value=MagicMock()),
+                          _load_async_markets=MagicMock(),
+                          validate_pairs=MagicMock(),
+                          validate_timeframes=MagicMock(),
+                          markets=PropertyMock(return_value=markets))
+    ex = Exchange(default_conf)
+
+    assert ex.get_valid_pair_combination("ETH", "BTC") == "ETH/BTC"
+    assert ex.get_valid_pair_combination("BTC", "ETH") == "ETH/BTC"
+    with pytest.raises(DependencyException, match=r"Could not combine.* to get a valid pair."):
+        ex.get_valid_pair_combination("NOPAIR", "ETH")
+
+
+@pytest.mark.parametrize(
+    "base_currencies, quote_currencies, pairs_only, active_only, expected_keys", [
+        # Testing markets (in conftest.py):
+        # 'BLK/BTC':  'active': True
+        # 'BTT/BTC':  'active': True
+        # 'ETH/BTC':  'active': True
+        # 'ETH/USDT': 'active': True
+        # 'LTC/BTC':  'active': False
+        # 'LTC/ETH':  'active': True
+        # 'LTC/USD':  'active': True
+        # 'LTC/USDT': 'active': True
+        # 'NEO/BTC':  'active': False
+        # 'TKN/BTC':  'active'  not set
+        # 'XLTCUSDT': 'active': True, not a pair
+        # 'XRP/BTC':  'active': False
+        # all markets
+        ([], [], False, False,
+         ['BLK/BTC', 'BTT/BTC', 'ETH/BTC', 'ETH/USDT', 'LTC/BTC', 'LTC/ETH', 'LTC/USD',
+          'LTC/USDT', 'NEO/BTC', 'TKN/BTC', 'XLTCUSDT', 'XRP/BTC']),
+        # active markets
+        ([], [], False, True,
+         ['BLK/BTC', 'ETH/BTC', 'ETH/USDT', 'LTC/BTC', 'LTC/ETH', 'LTC/USD', 'NEO/BTC',
+          'TKN/BTC', 'XLTCUSDT', 'XRP/BTC']),
+        # all pairs
+        ([], [], True, False,
+         ['BLK/BTC', 'BTT/BTC', 'ETH/BTC', 'ETH/USDT', 'LTC/BTC', 'LTC/ETH', 'LTC/USD',
+          'LTC/USDT', 'NEO/BTC', 'TKN/BTC', 'XRP/BTC']),
+        # active pairs
+        ([], [], True, True,
+         ['BLK/BTC', 'ETH/BTC', 'ETH/USDT', 'LTC/BTC', 'LTC/ETH', 'LTC/USD', 'NEO/BTC',
+          'TKN/BTC', 'XRP/BTC']),
+        # all markets, base=ETH, LTC
+        (['ETH', 'LTC'], [], False, False,
+         ['ETH/BTC', 'ETH/USDT', 'LTC/BTC', 'LTC/ETH', 'LTC/USD', 'LTC/USDT', 'XLTCUSDT']),
+        # all markets, base=LTC
+        (['LTC'], [], False, False,
+         ['LTC/BTC', 'LTC/ETH', 'LTC/USD', 'LTC/USDT', 'XLTCUSDT']),
+        # all markets, quote=USDT
+        ([], ['USDT'], False, False,
+         ['ETH/USDT', 'LTC/USDT', 'XLTCUSDT']),
+        # all markets, quote=USDT, USD
+        ([], ['USDT', 'USD'], False, False,
+         ['ETH/USDT', 'LTC/USD', 'LTC/USDT', 'XLTCUSDT']),
+        # all markets, base=LTC, quote=USDT
+        (['LTC'], ['USDT'], False, False,
+         ['LTC/USDT', 'XLTCUSDT']),
+        # all pairs, base=LTC, quote=USDT
+        (['LTC'], ['USDT'], True, False,
+         ['LTC/USDT']),
+        # all markets, base=LTC, quote=USDT, NONEXISTENT
+        (['LTC'], ['USDT', 'NONEXISTENT'], False, False,
+         ['LTC/USDT', 'XLTCUSDT']),
+        # all markets, base=LTC, quote=NONEXISTENT
+        (['LTC'], ['NONEXISTENT'], False, False,
+         []),
+    ])
+def test_get_markets(default_conf, mocker, markets,
+                     base_currencies, quote_currencies, pairs_only, active_only,
+                     expected_keys):
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          _init_ccxt=MagicMock(return_value=MagicMock()),
+                          _load_async_markets=MagicMock(),
+                          validate_pairs=MagicMock(),
+                          validate_timeframes=MagicMock(),
+                          markets=PropertyMock(return_value=markets))
+    ex = Exchange(default_conf)
+    pairs = ex.get_markets(base_currencies, quote_currencies, pairs_only, active_only)
+    assert sorted(pairs.keys()) == sorted(expected_keys)
+
+
+def test_get_markets_error(default_conf, mocker):
+    ex = get_patched_exchange(mocker, default_conf)
+    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=None))
+    with pytest.raises(OperationalException, match="Markets were not loaded."):
+        ex.get_markets('LTC', 'USDT', True, False)
+
+
+def test_timeframe_to_minutes():
+    assert timeframe_to_minutes("5m") == 5
+    assert timeframe_to_minutes("10m") == 10
+    assert timeframe_to_minutes("1h") == 60
+    assert timeframe_to_minutes("1d") == 1440
+
+
+def test_timeframe_to_seconds():
+    assert timeframe_to_seconds("5m") == 300
+    assert timeframe_to_seconds("10m") == 600
+    assert timeframe_to_seconds("1h") == 3600
+    assert timeframe_to_seconds("1d") == 86400
+
+
+def test_timeframe_to_msecs():
+    assert timeframe_to_msecs("5m") == 300000
+    assert timeframe_to_msecs("10m") == 600000
+    assert timeframe_to_msecs("1h") == 3600000
+    assert timeframe_to_msecs("1d") == 86400000
+
+
+def test_timeframe_to_prev_date():
+    # 2019-08-12 13:22:08
+    date = datetime.fromtimestamp(1565616128, tz=timezone.utc)
+
+    tf_list = [
+        # 5m -> 2019-08-12 13:20:00
+        ("5m", datetime(2019, 8, 12, 13, 20, 0, tzinfo=timezone.utc)),
+        # 10m -> 2019-08-12 13:20:00
+        ("10m", datetime(2019, 8, 12, 13, 20, 0, tzinfo=timezone.utc)),
+        # 1h -> 2019-08-12 13:00:00
+        ("1h", datetime(2019, 8, 12, 13, 00, 0, tzinfo=timezone.utc)),
+        # 2h -> 2019-08-12 12:00:00
+        ("2h", datetime(2019, 8, 12, 12, 00, 0, tzinfo=timezone.utc)),
+        # 4h -> 2019-08-12 12:00:00
+        ("4h", datetime(2019, 8, 12, 12, 00, 0, tzinfo=timezone.utc)),
+        # 1d -> 2019-08-12 00:00:00
+        ("1d", datetime(2019, 8, 12, 00, 00, 0, tzinfo=timezone.utc)),
+    ]
+    for interval, result in tf_list:
+        assert timeframe_to_prev_date(interval, date) == result
+
+    date = datetime.now(tz=timezone.utc)
+    assert timeframe_to_prev_date("5m") < date
+
+
+def test_timeframe_to_next_date():
+    # 2019-08-12 13:22:08
+    date = datetime.fromtimestamp(1565616128, tz=timezone.utc)
+    tf_list = [
+        # 5m -> 2019-08-12 13:25:00
+        ("5m", datetime(2019, 8, 12, 13, 25, 0, tzinfo=timezone.utc)),
+        # 10m -> 2019-08-12 13:30:00
+        ("10m", datetime(2019, 8, 12, 13, 30, 0, tzinfo=timezone.utc)),
+        # 1h -> 2019-08-12 14:00:00
+        ("1h", datetime(2019, 8, 12, 14, 00, 0, tzinfo=timezone.utc)),
+        # 2h -> 2019-08-12 14:00:00
+        ("2h", datetime(2019, 8, 12, 14, 00, 0, tzinfo=timezone.utc)),
+        # 4h -> 2019-08-12 14:00:00
+        ("4h", datetime(2019, 8, 12, 16, 00, 0, tzinfo=timezone.utc)),
+        # 1d -> 2019-08-13 00:00:00
+        ("1d", datetime(2019, 8, 13, 0, 0, 0, tzinfo=timezone.utc)),
+    ]
+
+    for interval, result in tf_list:
+        assert timeframe_to_next_date(interval, date) == result
+
+    date = datetime.now(tz=timezone.utc)
+    assert timeframe_to_next_date("5m") > date
+
+    date = datetime(2019, 8, 12, 13, 30, 0, tzinfo=timezone.utc)
+    assert timeframe_to_next_date("5m", date) == date + timedelta(minutes=5)
+
+
+@pytest.mark.parametrize("market_symbol,base,quote,exchange,add_dict,expected_result", [
+    ("BTC/USDT", 'BTC', 'USDT', "binance", {}, True),
+    ("USDT/BTC", 'USDT', 'BTC', "binance", {}, True),
+    ("USDT/BTC", 'BTC', 'USDT', "binance", {}, False),  # Reversed currencies
+    ("BTCUSDT", 'BTC', 'USDT', "binance", {}, False),  # No seperating /
+    ("BTCUSDT", None, "USDT", "binance", {}, False),  #
+    ("USDT/BTC", "BTC", None, "binance", {}, False),
+    ("BTCUSDT", "BTC", None, "binance", {}, False),
+    ("BTC/USDT", "BTC", "USDT", "binance", {}, True),
+    ("BTC/USDT", "USDT", "BTC", "binance", {}, False),  # reversed currencies
+    ("BTC/USDT", "BTC", "USD", "binance", {}, False),  # Wrong quote currency
+    ("BTC/", "BTC", 'UNK', "binance", {}, False),
+    ("/USDT", 'UNK', 'USDT', "binance", {}, False),
+    ("BTC/EUR", 'BTC', 'EUR', "kraken", {"darkpool": False}, True),
+    ("EUR/BTC", 'EUR', 'BTC', "kraken", {"darkpool": False}, True),
+    ("EUR/BTC", 'BTC', 'EUR', "kraken", {"darkpool": False}, False),  # Reversed currencies
+    ("BTC/EUR", 'BTC', 'USD', "kraken", {"darkpool": False}, False),  # wrong quote currency
+    ("BTC/EUR", 'BTC', 'EUR', "kraken", {"darkpool": True}, False),  # no darkpools
+    ("BTC/EUR.d", 'BTC', 'EUR', "kraken", {"darkpool": True}, False),  # no darkpools
+    ("BTC/USD", 'BTC', 'USD', "ftx", {'spot': True}, True),
+    ("USD/BTC", 'USD', 'BTC', "ftx", {'spot': True}, True),
+    ("BTC/USD", 'BTC', 'USDT', "ftx", {'spot': True}, False),  # Wrong quote currency
+    ("BTC/USD", 'USD', 'BTC', "ftx", {'spot': True}, False),  # Reversed currencies
+    ("BTC/USD", 'BTC', 'USD', "ftx", {'spot': False}, False),  # Can only trade spot markets
+    ("BTC-PERP", 'BTC', 'USD', "ftx", {'spot': False}, False),  # Can only trade spot markets
+])
+def test_market_is_tradable(mocker, default_conf, market_symbol, base,
+                            quote, add_dict, exchange, expected_result) -> None:
+    ex = get_patched_exchange(mocker, default_conf, id=exchange)
+    market = {
+        'symbol': market_symbol,
+        'base': base,
+        'quote': quote,
+        **(add_dict),
+    }
+    assert ex.market_is_tradable(market) == expected_result
+
+
+@pytest.mark.parametrize("market,expected_result", [
+    ({'symbol': 'ETH/BTC', 'active': True}, True),
+    ({'symbol': 'ETH/BTC', 'active': False}, False),
+    ({'symbol': 'ETH/BTC', }, True),
+])
+def test_market_is_active(market, expected_result) -> None:
+    assert market_is_active(market) == expected_result
+
+
+@pytest.mark.parametrize("order,expected", [
+    ([{'fee'}], False),
+    ({'fee': None}, False),
+    ({'fee': {'currency': 'ETH/BTC'}}, False),
+    ({'fee': {'currency': 'ETH/BTC', 'cost': None}}, False),
+    ({'fee': {'currency': 'ETH/BTC', 'cost': 0.01}}, True),
+])
+def test_order_has_fee(order, expected) -> None:
+    assert Exchange.order_has_fee(order) == expected
+
+
+@pytest.mark.parametrize("order,expected", [
+    ({'symbol': 'ETH/BTC', 'fee': {'currency': 'ETH', 'cost': 0.43}},
+        (0.43, 'ETH', 0.01)),
+    ({'symbol': 'ETH/USDT', 'fee': {'currency': 'USDT', 'cost': 0.01}},
+        (0.01, 'USDT', 0.01)),
+    ({'symbol': 'BTC/USDT', 'fee': {'currency': 'USDT', 'cost': 0.34, 'rate': 0.01}},
+        (0.34, 'USDT', 0.01)),
+])
+def test_extract_cost_curr_rate(mocker, default_conf, order, expected) -> None:
+    mocker.patch('freqtrade.exchange.Exchange.calculate_fee_rate', MagicMock(return_value=0.01))
+    ex = get_patched_exchange(mocker, default_conf)
+    assert ex.extract_cost_curr_rate(order) == expected
+
+
+@pytest.mark.parametrize("order,expected", [
+    # Using base-currency
+    ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
+        'fee': {'currency': 'ETH', 'cost': 0.004, 'rate': None}}, 0.1),
+    ({'symbol': 'ETH/BTC', 'amount': 0.05, 'cost': 0.05,
+        'fee': {'currency': 'ETH', 'cost': 0.004, 'rate': None}}, 0.08),
+    # Using quote currency
+    ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
+        'fee': {'currency': 'BTC', 'cost': 0.005}}, 0.1),
+    ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
+        'fee': {'currency': 'BTC', 'cost': 0.002, 'rate': None}}, 0.04),
+    # Using foreign currency
+    ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
+        'fee': {'currency': 'NEO', 'cost': 0.0012}}, 0.001944),
+    ({'symbol': 'ETH/BTC', 'amount': 2.21, 'cost': 0.02992561,
+        'fee': {'currency': 'NEO', 'cost': 0.00027452}}, 0.00074305),
+    # Rate included in return - return as is
+    ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
+        'fee': {'currency': 'USDT', 'cost': 0.34, 'rate': 0.01}}, 0.01),
+    ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
+        'fee': {'currency': 'USDT', 'cost': 0.34, 'rate': 0.005}}, 0.005),
+    # 0.1% filled - no costs (kraken - #3431)
+    ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.0,
+      'fee': {'currency': 'BTC', 'cost': 0.0, 'rate': None}}, None),
+    ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.0,
+      'fee': {'currency': 'ETH', 'cost': 0.0, 'rate': None}}, 0.0),
+    ({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.0,
+      'fee': {'currency': 'NEO', 'cost': 0.0, 'rate': None}}, None),
+])
+def test_calculate_fee_rate(mocker, default_conf, order, expected) -> None:
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', return_value={'last': 0.081})
+
+    ex = get_patched_exchange(mocker, default_conf)
+    assert ex.calculate_fee_rate(order) == expected
+
+
+@pytest.mark.parametrize('retrycount,max_retries,expected', [
+    (0, 3, 10),
+    (1, 3, 5),
+    (2, 3, 2),
+    (3, 3, 1),
+    (0, 1, 2),
+    (1, 1, 1),
+    (0, 4, 17),
+    (1, 4, 10),
+    (2, 4, 5),
+    (3, 4, 2),
+    (4, 4, 1),
+    (0, 5, 26),
+    (1, 5, 17),
+    (2, 5, 10),
+    (3, 5, 5),
+    (4, 5, 2),
+    (5, 5, 1),
+
+])
+def test_calculate_backoff(retrycount, max_retries, expected):
+    assert calculate_backoff(retrycount, max_retries) == expected
diff --git a/tests/exchange/test_ftx.py b/tests/exchange/test_ftx.py
new file mode 100644
index 000000000..17cfb26fa
--- /dev/null
+++ b/tests/exchange/test_ftx.py
@@ -0,0 +1,158 @@
+from random import randint
+from unittest.mock import MagicMock
+
+import ccxt
+import pytest
+
+from freqtrade.exceptions import DependencyException, InvalidOrderException
+from freqtrade.exchange.common import API_FETCH_ORDER_RETRY_COUNT
+from tests.conftest import get_patched_exchange
+
+from .test_exchange import ccxt_exceptionhandlers
+
+
+STOPLOSS_ORDERTYPE = 'stop'
+
+
+def test_stoploss_order_ftx(default_conf, mocker):
+    api_mock = MagicMock()
+    order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
+
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+
+    default_conf['dry_run'] = False
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, 'ftx')
+
+    # stoploss_on_exchange_limit_ratio is irrelevant for ftx market orders
+    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=190,
+                              order_types={'stoploss_on_exchange_limit_ratio': 1.05})
+
+    assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
+    assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE
+    assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
+    assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
+    assert api_mock.create_order.call_args_list[0][1]['price'] == 190
+    assert 'orderPrice' not in api_mock.create_order.call_args_list[0][1]['params']
+
+    assert api_mock.create_order.call_count == 1
+
+    api_mock.create_order.reset_mock()
+
+    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
+    assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE
+    assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
+    assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
+    assert api_mock.create_order.call_args_list[0][1]['price'] == 220
+    assert 'orderPrice' not in api_mock.create_order.call_args_list[0][1]['params']
+
+    api_mock.create_order.reset_mock()
+    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220,
+                              order_types={'stoploss': 'limit'})
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
+    assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE
+    assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
+    assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
+    assert api_mock.create_order.call_args_list[0][1]['price'] == 220
+    assert 'orderPrice' in api_mock.create_order.call_args_list[0][1]['params']
+    assert api_mock.create_order.call_args_list[0][1]['params']['orderPrice'] == 217.8
+
+    # test exception handling
+    with pytest.raises(DependencyException):
+        api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("0 balance"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, 'ftx')
+        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+    with pytest.raises(InvalidOrderException):
+        api_mock.create_order = MagicMock(
+            side_effect=ccxt.InvalidOrder("ftx Order would trigger immediately."))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, 'ftx')
+        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, "ftx",
+                           "stoploss", "create_order", retries=1,
+                           pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+
+def test_stoploss_order_dry_run_ftx(default_conf, mocker):
+    api_mock = MagicMock()
+    default_conf['dry_run'] = True
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, 'ftx')
+
+    api_mock.create_order.reset_mock()
+
+    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+    assert 'id' in order
+    assert 'info' in order
+    assert 'type' in order
+
+    assert order['type'] == STOPLOSS_ORDERTYPE
+    assert order['price'] == 220
+    assert order['amount'] == 1
+
+
+def test_stoploss_adjust_ftx(mocker, default_conf):
+    exchange = get_patched_exchange(mocker, default_conf, id='ftx')
+    order = {
+        'type': STOPLOSS_ORDERTYPE,
+        'price': 1500,
+    }
+    assert exchange.stoploss_adjust(1501, order)
+    assert not exchange.stoploss_adjust(1499, order)
+    # Test with invalid order case ...
+    order['type'] = 'stop_loss_limit'
+    assert not exchange.stoploss_adjust(1501, order)
+
+
+def test_fetch_stoploss_order(default_conf, mocker):
+    default_conf['dry_run'] = True
+    order = MagicMock()
+    order.myid = 123
+    exchange = get_patched_exchange(mocker, default_conf, id='ftx')
+    exchange._dry_run_open_orders['X'] = order
+    assert exchange.fetch_stoploss_order('X', 'TKN/BTC').myid == 123
+
+    with pytest.raises(InvalidOrderException, match=r'Tried to get an invalid dry-run-order.*'):
+        exchange.fetch_stoploss_order('Y', 'TKN/BTC')
+
+    default_conf['dry_run'] = False
+    api_mock = MagicMock()
+    api_mock.fetch_orders = MagicMock(return_value=[{'id': 'X', 'status': '456'}])
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id='ftx')
+    assert exchange.fetch_stoploss_order('X', 'TKN/BTC')['status'] == '456'
+
+    api_mock.fetch_orders = MagicMock(return_value=[{'id': 'Y', 'status': '456'}])
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id='ftx')
+    with pytest.raises(InvalidOrderException, match=r"Could not get stoploss order for id X"):
+        exchange.fetch_stoploss_order('X', 'TKN/BTC')['status']
+
+    with pytest.raises(InvalidOrderException):
+        api_mock.fetch_orders = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, id='ftx')
+        exchange.fetch_stoploss_order(order_id='_', pair='TKN/BTC')
+    assert api_mock.fetch_orders.call_count == 1
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, 'ftx',
+                           'fetch_stoploss_order', 'fetch_orders',
+                           retries=API_FETCH_ORDER_RETRY_COUNT + 1,
+                           order_id='_', pair='TKN/BTC')
diff --git a/tests/exchange/test_kraken.py b/tests/exchange/test_kraken.py
new file mode 100644
index 000000000..31b79a202
--- /dev/null
+++ b/tests/exchange/test_kraken.py
@@ -0,0 +1,243 @@
+from random import randint
+from unittest.mock import MagicMock
+
+import ccxt
+import pytest
+
+from freqtrade.exceptions import DependencyException, InvalidOrderException
+from tests.conftest import get_patched_exchange
+from tests.exchange.test_exchange import ccxt_exceptionhandlers
+
+
+STOPLOSS_ORDERTYPE = 'stop-loss'
+
+
+def test_buy_kraken_trading_agreement(default_conf, mocker):
+    api_mock = MagicMock()
+    order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
+    order_type = 'limit'
+    time_in_force = 'ioc'
+    api_mock.options = {}
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+    default_conf['dry_run'] = False
+
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="kraken")
+
+    order = exchange.buy(pair='ETH/BTC', ordertype=order_type,
+                         amount=1, rate=200, time_in_force=time_in_force)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
+    assert api_mock.create_order.call_args[0][1] == order_type
+    assert api_mock.create_order.call_args[0][2] == 'buy'
+    assert api_mock.create_order.call_args[0][3] == 1
+    assert api_mock.create_order.call_args[0][4] == 200
+    assert api_mock.create_order.call_args[0][5] == {'timeInForce': 'ioc',
+                                                     'trading_agreement': 'agree'}
+
+
+def test_sell_kraken_trading_agreement(default_conf, mocker):
+    api_mock = MagicMock()
+    order_id = 'test_prod_sell_{}'.format(randint(0, 10 ** 6))
+    order_type = 'market'
+    api_mock.options = {}
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+    default_conf['dry_run'] = False
+
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="kraken")
+
+    order = exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
+    assert api_mock.create_order.call_args[0][1] == order_type
+    assert api_mock.create_order.call_args[0][2] == 'sell'
+    assert api_mock.create_order.call_args[0][3] == 1
+    assert api_mock.create_order.call_args[0][4] is None
+    assert api_mock.create_order.call_args[0][5] == {'trading_agreement': 'agree'}
+
+
+def test_get_balances_prod(default_conf, mocker):
+    balance_item = {
+        'free': None,
+        'total': 10.0,
+        'used': 0.0
+    }
+
+    api_mock = MagicMock()
+    api_mock.fetch_balance = MagicMock(return_value={
+        '1ST': balance_item.copy(),
+        '2ST': balance_item.copy(),
+        '3ST': balance_item.copy(),
+        '4ST': balance_item.copy(),
+    })
+    kraken_open_orders = [{'symbol': '1ST/EUR',
+                           'type': 'limit',
+                           'side': 'sell',
+                           'price': 20,
+                           'cost': 0.0,
+                           'amount': 1.0,
+                           'filled': 0.0,
+                           'average': 0.0,
+                           'remaining': 1.0,
+                           },
+                          {'status': 'open',
+                           'symbol': '2ST/EUR',
+                           'type': 'limit',
+                           'side': 'sell',
+                           'price': 20.0,
+                           'cost': 0.0,
+                           'amount': 2.0,
+                           'filled': 0.0,
+                           'average': 0.0,
+                           'remaining': 2.0,
+                           },
+                          {'status': 'open',
+                           'symbol': '2ST/USD',
+                           'type': 'limit',
+                           'side': 'sell',
+                           'price': 20.0,
+                           'cost': 0.0,
+                           'amount': 2.0,
+                           'filled': 0.0,
+                           'average': 0.0,
+                           'remaining': 2.0,
+                           },
+                          {'status': 'open',
+                           'symbol': 'BTC/3ST',
+                           'type': 'limit',
+                           'side': 'buy',
+                           'price': 20,
+                           'cost': 0.0,
+                           'amount': 3.0,
+                           'filled': 0.0,
+                           'average': 0.0,
+                           'remaining': 3.0,
+                           }]
+    api_mock.fetch_open_orders = MagicMock(return_value=kraken_open_orders)
+    default_conf['dry_run'] = False
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, id="kraken")
+    balances = exchange.get_balances()
+    assert len(balances) == 4
+    assert balances['1ST']['free'] == 9.0
+    assert balances['1ST']['total'] == 10.0
+    assert balances['1ST']['used'] == 1.0
+
+    assert balances['2ST']['free'] == 6.0
+    assert balances['2ST']['total'] == 10.0
+    assert balances['2ST']['used'] == 4.0
+
+    assert balances['3ST']['free'] == 7.0
+    assert balances['3ST']['total'] == 10.0
+    assert balances['3ST']['used'] == 3.0
+
+    assert balances['4ST']['free'] == 10.0
+    assert balances['4ST']['total'] == 10.0
+    assert balances['4ST']['used'] == 0.0
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, "kraken",
+                           "get_balances", "fetch_balance")
+
+
+def test_stoploss_order_kraken(default_conf, mocker):
+    api_mock = MagicMock()
+    order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
+
+    api_mock.create_order = MagicMock(return_value={
+        'id': order_id,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+
+    default_conf['dry_run'] = False
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kraken')
+
+    # stoploss_on_exchange_limit_ratio is irrelevant for kraken market orders
+    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=190,
+                              order_types={'stoploss_on_exchange_limit_ratio': 1.05})
+    assert api_mock.create_order.call_count == 1
+
+    api_mock.create_order.reset_mock()
+
+    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+    assert 'id' in order
+    assert 'info' in order
+    assert order['id'] == order_id
+    assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
+    assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE
+    assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
+    assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
+    assert api_mock.create_order.call_args_list[0][1]['price'] == 220
+    assert api_mock.create_order.call_args_list[0][1]['params'] == {'trading_agreement': 'agree'}
+
+    # test exception handling
+    with pytest.raises(DependencyException):
+        api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("0 balance"))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kraken')
+        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+    with pytest.raises(InvalidOrderException):
+        api_mock.create_order = MagicMock(
+            side_effect=ccxt.InvalidOrder("kraken Order would trigger immediately."))
+        exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kraken')
+        exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+    ccxt_exceptionhandlers(mocker, default_conf, api_mock, "kraken",
+                           "stoploss", "create_order", retries=1,
+                           pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+
+def test_stoploss_order_dry_run_kraken(default_conf, mocker):
+    api_mock = MagicMock()
+    default_conf['dry_run'] = True
+    mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+
+    exchange = get_patched_exchange(mocker, default_conf, api_mock, 'kraken')
+
+    api_mock.create_order.reset_mock()
+
+    order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
+
+    assert 'id' in order
+    assert 'info' in order
+    assert 'type' in order
+
+    assert order['type'] == STOPLOSS_ORDERTYPE
+    assert order['price'] == 220
+    assert order['amount'] == 1
+
+
+def test_stoploss_adjust_kraken(mocker, default_conf):
+    exchange = get_patched_exchange(mocker, default_conf, id='kraken')
+    order = {
+        'type': STOPLOSS_ORDERTYPE,
+        'price': 1500,
+    }
+    assert exchange.stoploss_adjust(1501, order)
+    assert not exchange.stoploss_adjust(1499, order)
+    # Test with invalid order case ...
+    order['type'] = 'stop_loss_limit'
+    assert not exchange.stoploss_adjust(1501, order)
diff --git a/freqtrade/tests/optimize/__init__.py b/tests/optimize/__init__.py
similarity index 69%
rename from freqtrade/tests/optimize/__init__.py
rename to tests/optimize/__init__.py
index 41500051f..306850ff6 100644
--- a/freqtrade/tests/optimize/__init__.py
+++ b/tests/optimize/__init__.py
@@ -1,4 +1,4 @@
-from typing import NamedTuple, List
+from typing import Dict, List, NamedTuple, Optional
 
 import arrow
 from pandas import DataFrame
@@ -6,8 +6,9 @@ from pandas import DataFrame
 from freqtrade.exchange import timeframe_to_minutes
 from freqtrade.strategy.interface import SellType
 
-ticker_start_time = arrow.get(2018, 10, 3)
-tests_ticker_interval = '1h'
+
+tests_start_time = arrow.get(2018, 10, 3)
+tests_timeframe = '1h'
 
 
 class BTrade(NamedTuple):
@@ -23,27 +24,27 @@ class BTContainer(NamedTuple):
     """
     Minimal BacktestContainer defining Backtest inputs and results.
     """
-    data: List[float]
+    data: List[List[float]]
     stop_loss: float
-    roi: float
+    roi: Dict[str, float]
     trades: List[BTrade]
     profit_perc: float
     trailing_stop: bool = False
     trailing_only_offset_is_reached: bool = False
-    trailing_stop_positive: float = None
+    trailing_stop_positive: Optional[float] = None
     trailing_stop_positive_offset: float = 0.0
     use_sell_signal: bool = False
 
 
 def _get_frame_time_from_offset(offset):
-    return ticker_start_time.shift(minutes=(offset * timeframe_to_minutes(tests_ticker_interval))
-                                   ).datetime
+    minutes = offset * timeframe_to_minutes(tests_timeframe)
+    return tests_start_time.shift(minutes=minutes).datetime
 
 
-def _build_backtest_dataframe(ticker_with_signals):
+def _build_backtest_dataframe(data):
     columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'buy', 'sell']
 
-    frame = DataFrame.from_records(ticker_with_signals, columns=columns)
+    frame = DataFrame.from_records(data, columns=columns)
     frame['date'] = frame['date'].apply(_get_frame_time_from_offset)
     # Ensure floats are in place
     for column in ['open', 'high', 'low', 'close', 'volume']:
diff --git a/tests/optimize/conftest.py b/tests/optimize/conftest.py
new file mode 100644
index 000000000..f06b0ecd3
--- /dev/null
+++ b/tests/optimize/conftest.py
@@ -0,0 +1,51 @@
+from copy import deepcopy
+from datetime import datetime
+from pathlib import Path
+
+import pandas as pd
+import pytest
+
+from freqtrade.optimize.hyperopt import Hyperopt
+from freqtrade.strategy.interface import SellType
+from tests.conftest import patch_exchange
+
+
+@pytest.fixture(scope='function')
+def hyperopt_conf(default_conf):
+    hyperconf = deepcopy(default_conf)
+    hyperconf.update({
+        'hyperopt': 'DefaultHyperOpt',
+        'hyperopt_loss': 'ShortTradeDurHyperOptLoss',
+                         'hyperopt_path': str(Path(__file__).parent / 'hyperopts'),
+                         'epochs': 1,
+                         'timerange': None,
+                         'spaces': ['default'],
+                         'hyperopt_jobs': 1,
+    })
+    return hyperconf
+
+
+@pytest.fixture(scope='function')
+def hyperopt(hyperopt_conf, mocker):
+
+    patch_exchange(mocker)
+    return Hyperopt(hyperopt_conf)
+
+
+@pytest.fixture(scope='function')
+def hyperopt_results():
+    return pd.DataFrame(
+        {
+            'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
+            'profit_percent': [-0.1, 0.2, 0.3],
+            'profit_abs': [-0.2, 0.4, 0.6],
+            'trade_duration': [10, 30, 10],
+            'sell_reason': [SellType.STOP_LOSS, SellType.ROI, SellType.ROI],
+            'close_date':
+            [
+                datetime(2019, 1, 1, 9, 26, 3, 478039),
+                datetime(2019, 2, 1, 9, 26, 3, 478039),
+                datetime(2019, 3, 1, 9, 26, 3, 478039)
+            ]
+        }
+    )
diff --git a/freqtrade/optimize/default_hyperopt.py b/tests/optimize/hyperopts/default_hyperopt.py
similarity index 77%
rename from freqtrade/optimize/default_hyperopt.py
rename to tests/optimize/hyperopts/default_hyperopt.py
index ad76ff786..2e2bca3d0 100644
--- a/freqtrade/optimize/default_hyperopt.py
+++ b/tests/optimize/hyperopts/default_hyperopt.py
@@ -5,46 +5,57 @@ from typing import Any, Callable, Dict, List
 
 import talib.abstract as ta
 from pandas import DataFrame
-from skopt.space import Categorical, Dimension, Integer, Real
+from skopt.space import Categorical, Dimension, Integer
 
 import freqtrade.vendor.qtpylib.indicators as qtpylib
 from freqtrade.optimize.hyperopt_interface import IHyperOpt
 
 
-class DefaultHyperOpts(IHyperOpt):
+class DefaultHyperOpt(IHyperOpt):
     """
-    Default hyperopt provided by freqtrade bot.
-    You can override it with your own hyperopt
+    Default hyperopt provided by the Freqtrade bot.
+    You can override it with your own Hyperopt
     """
-
     @staticmethod
     def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Add several indicators needed for buy and sell strategies defined below.
+        """
+        # ADX
         dataframe['adx'] = ta.ADX(dataframe)
+        # MACD
         macd = ta.MACD(dataframe)
         dataframe['macd'] = macd['macd']
         dataframe['macdsignal'] = macd['macdsignal']
+        # MFI
         dataframe['mfi'] = ta.MFI(dataframe)
+        # RSI
         dataframe['rsi'] = ta.RSI(dataframe)
+        # Stochastic Fast
         stoch_fast = ta.STOCHF(dataframe)
         dataframe['fastd'] = stoch_fast['fastd']
+        # Minus-DI
         dataframe['minus_di'] = ta.MINUS_DI(dataframe)
         # Bollinger bands
         bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
         dataframe['bb_lowerband'] = bollinger['lower']
         dataframe['bb_upperband'] = bollinger['upper']
+        # SAR
         dataframe['sar'] = ta.SAR(dataframe)
+
         return dataframe
 
     @staticmethod
     def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
         """
-        Define the buy strategy parameters to be used by hyperopt
+        Define the buy strategy parameters to be used by Hyperopt.
         """
         def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
             """
-            Buy strategy Hyperopt will build and use
+            Buy strategy Hyperopt will build and use.
             """
             conditions = []
+
             # GUARDS AND TRENDS
             if 'mfi-enabled' in params and params['mfi-enabled']:
                 conditions.append(dataframe['mfi'] < params['mfi-value'])
@@ -80,7 +91,7 @@ class DefaultHyperOpts(IHyperOpt):
     @staticmethod
     def indicator_space() -> List[Dimension]:
         """
-        Define your Hyperopt space for searching strategy parameters
+        Define your Hyperopt space for searching buy strategy parameters.
         """
         return [
             Integer(10, 25, name='mfi-value'),
@@ -97,14 +108,14 @@ class DefaultHyperOpts(IHyperOpt):
     @staticmethod
     def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
         """
-        Define the sell strategy parameters to be used by hyperopt
+        Define the sell strategy parameters to be used by Hyperopt.
         """
         def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
             """
-            Sell strategy Hyperopt will build and use
+            Sell strategy Hyperopt will build and use.
             """
-            # print(params)
             conditions = []
+
             # GUARDS AND TRENDS
             if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
                 conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
@@ -140,7 +151,7 @@ class DefaultHyperOpts(IHyperOpt):
     @staticmethod
     def sell_indicator_space() -> List[Dimension]:
         """
-        Define your Hyperopt space for searching sell strategy parameters
+        Define your Hyperopt space for searching sell strategy parameters.
         """
         return [
             Integer(75, 100, name='sell-mfi-value'),
@@ -156,47 +167,11 @@ class DefaultHyperOpts(IHyperOpt):
                          'sell-sar_reversal'], name='sell-trigger')
         ]
 
-    @staticmethod
-    def generate_roi_table(params: Dict) -> Dict[int, float]:
-        """
-        Generate the ROI table that will be used by Hyperopt
-        """
-        roi_table = {}
-        roi_table[0] = params['roi_p1'] + params['roi_p2'] + params['roi_p3']
-        roi_table[params['roi_t3']] = params['roi_p1'] + params['roi_p2']
-        roi_table[params['roi_t3'] + params['roi_t2']] = params['roi_p1']
-        roi_table[params['roi_t3'] + params['roi_t2'] + params['roi_t1']] = 0
-
-        return roi_table
-
-    @staticmethod
-    def stoploss_space() -> List[Dimension]:
-        """
-        Stoploss Value to search
-        """
-        return [
-            Real(-0.5, -0.02, name='stoploss'),
-        ]
-
-    @staticmethod
-    def roi_space() -> List[Dimension]:
-        """
-        Values to search for each ROI steps
-        """
-        return [
-            Integer(10, 120, name='roi_t1'),
-            Integer(10, 60, name='roi_t2'),
-            Integer(10, 40, name='roi_t3'),
-            Real(0.01, 0.04, name='roi_p1'),
-            Real(0.01, 0.07, name='roi_p2'),
-            Real(0.01, 0.20, name='roi_p3'),
-        ]
-
     def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Based on TA indicators. Should be a copy of from strategy
-        must align to populate_indicators in this file
-        Only used when --spaces does not include buy
+        Based on TA indicators. Should be a copy of same method from strategy.
+        Must align to populate_indicators in this file.
+        Only used when --spaces does not include buy space.
         """
         dataframe.loc[
             (
@@ -211,9 +186,9 @@ class DefaultHyperOpts(IHyperOpt):
 
     def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
-        Based on TA indicators. Should be a copy of from strategy
-        must align to populate_indicators in this file
-        Only used when --spaces does not include sell
+        Based on TA indicators. Should be a copy of same method from strategy.
+        Must align to populate_indicators in this file.
+        Only used when --spaces does not include sell space.
         """
         dataframe.loc[
             (
@@ -223,4 +198,5 @@ class DefaultHyperOpts(IHyperOpt):
                 (dataframe['fastd'] > 54)
             ),
             'sell'] = 1
+
         return dataframe
diff --git a/tests/optimize/test_backtest_detail.py b/tests/optimize/test_backtest_detail.py
new file mode 100644
index 000000000..a5de64fe4
--- /dev/null
+++ b/tests/optimize/test_backtest_detail.py
@@ -0,0 +1,400 @@
+# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, C0330, unused-argument
+import logging
+from unittest.mock import MagicMock
+
+import pytest
+
+from freqtrade.data.history import get_timerange
+from freqtrade.optimize.backtesting import Backtesting
+from freqtrade.strategy.interface import SellType
+from tests.conftest import patch_exchange
+from tests.optimize import (BTContainer, BTrade, _build_backtest_dataframe,
+                            _get_frame_time_from_offset, tests_timeframe)
+
+
+# Test 0: Sell with signal sell in candle 3
+# Test with Stop-loss at 1%
+tc0 = BTContainer(data=[
+    # D  O     H     L     C     V    B  S
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
+    [2, 4987, 5012, 4986, 4600, 6172, 0, 0],  # exit with stoploss hit
+    [3, 5010, 5000, 4980, 5010, 6172, 0, 1],
+    [4, 5010, 4987, 4977, 4995, 6172, 0, 0],
+    [5, 4995, 4995, 4995, 4950, 6172, 0, 0]],
+    stop_loss=-0.01, roi={"0": 1}, profit_perc=0.002, use_sell_signal=True,
+    trades=[BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=1, close_tick=4)]
+)
+
+# Test 1: Stop-Loss Triggered 1% loss
+# Test with Stop-loss at 1%
+tc1 = BTContainer(data=[
+    # D  O     H     L     C     V    B  S
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
+    [2, 4987, 5012, 4600, 4600, 6172, 0, 0],  # exit with stoploss hit
+    [3, 4975, 5000, 4980, 4977, 6172, 0, 0],
+    [4, 4977, 4987, 4977, 4995, 6172, 0, 0],
+    [5, 4995, 4995, 4995, 4950, 6172, 0, 0]],
+    stop_loss=-0.01, roi={"0": 1}, profit_perc=-0.01,
+    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
+)
+
+
+# Test 2: Minus 4% Low, minus 1% close
+# Test with Stop-Loss at 3%
+tc2 = BTContainer(data=[
+    # D  O     H     L     C     V    B  S
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
+    [2, 4987, 5012, 4962, 4975, 6172, 0, 0],
+    [3, 4975, 5000, 4800, 4962, 6172, 0, 0],  # exit with stoploss hit
+    [4, 4962, 4987, 4937, 4950, 6172, 0, 0],
+    [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
+    stop_loss=-0.03, roi={"0": 1}, profit_perc=-0.03,
+    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=3)]
+)
+
+
+# Test 3: Multiple trades.
+#         Candle drops 4%, Recovers 1%.
+#         Entry Criteria Met
+#         Candle drops 20%
+#  Trade-A: Stop-Loss Triggered 2% Loss
+#           Trade-B: Stop-Loss Triggered 2% Loss
+tc3 = BTContainer(data=[
+    # D  O     H     L     C     V    B  S
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
+    [2, 4987, 5012, 4800, 4975, 6172, 0, 0],  # exit with stoploss hit
+    [3, 4975, 5000, 4950, 4962, 6172, 1, 0],
+    [4, 4975, 5000, 4950, 4962, 6172, 0, 0],  # enter trade 2 (signal on last candle)
+    [5, 4962, 4987, 4000, 4000, 6172, 0, 0],  # exit with stoploss hit
+    [6, 4950, 4975, 4975, 4950, 6172, 0, 0]],
+    stop_loss=-0.02, roi={"0": 1}, profit_perc=-0.04,
+    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2),
+            BTrade(sell_reason=SellType.STOP_LOSS, open_tick=4, close_tick=5)]
+)
+
+# Test 4: Minus 3% / recovery +15%
+# Candle Data for test 3 – Candle drops 3% Closed 15% up
+# Test with Stop-loss at 2% ROI 6%
+# Stop-Loss Triggered 2% Loss
+tc4 = BTContainer(data=[
+    # D  O     H     L     C     V    B  S
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
+    [2, 4987, 5750, 4850, 5750, 6172, 0, 0],  # Exit with stoploss hit
+    [3, 4975, 5000, 4950, 4962, 6172, 0, 0],
+    [4, 4962, 4987, 4937, 4950, 6172, 0, 0],
+    [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
+    stop_loss=-0.02, roi={"0": 0.06}, profit_perc=-0.02,
+    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
+)
+
+# Test 5: Drops 0.5% Closes +20%, ROI triggers 3% Gain
+# stop-loss: 1%, ROI: 3%
+tc5 = BTContainer(data=[
+    # D  O     H     L     C     V    B  S
+    [0, 5000, 5025, 4980, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4980, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
+    [2, 4987, 5025, 4975, 4987, 6172, 0, 0],
+    [3, 4975, 6000, 4975, 6000, 6172, 0, 0],  # ROI
+    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
+    stop_loss=-0.01, roi={"0": 0.03}, profit_perc=0.03,
+    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
+)
+
+# Test 6: Drops 3% / Recovers 6% Positive / Closes 1% positve, Stop-Loss triggers 2% Loss
+# stop-loss: 2% ROI: 5%
+tc6 = BTContainer(data=[
+    # D  O     H     L     C     V    B  S
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
+    [2, 4987, 5300, 4850, 5050, 6172, 0, 0],  # Exit with stoploss
+    [3, 4975, 5000, 4950, 4962, 6172, 0, 0],
+    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
+    stop_loss=-0.02, roi={"0": 0.05}, profit_perc=-0.02,
+    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
+)
+
+# Test 7: 6% Positive / 1% Negative / Close 1% Positve, ROI Triggers 3% Gain
+# stop-loss: 2% ROI: 3%
+tc7 = BTContainer(data=[
+    # D  O     H     L     C     V    B  S
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],
+    [2, 4987, 5300, 4950, 5050, 6172, 0, 0],
+    [3, 4975, 5000, 4950, 4962, 6172, 0, 0],
+    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
+    stop_loss=-0.02, roi={"0": 0.03}, profit_perc=0.03,
+    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=2)]
+)
+
+
+# Test 8: trailing_stop should raise so candle 3 causes a stoploss.
+# stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted in candle 2
+tc8 = BTContainer(data=[
+    # D   O     H     L    C     V    B  S
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5050, 4950, 5000, 6172, 0, 0],
+    [2, 5000, 5250, 4750, 4850, 6172, 0, 0],
+    [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.055, trailing_stop=True,
+    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
+)
+
+
+# Test 9: trailing_stop should raise - high and low in same candle.
+# stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted in candle 3
+tc9 = BTContainer(data=[
+    # D   O     H     L     C    V    B  S
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5050, 4950, 5000, 6172, 0, 0],
+    [2, 5000, 5050, 4950, 5000, 6172, 0, 0],
+    [3, 5000, 5200, 4550, 4850, 6172, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.064, trailing_stop=True,
+    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
+)
+
+# Test 10: trailing_stop should raise so candle 3 causes a stoploss
+# without applying trailing_stop_positive since stoploss_offset is at 10%.
+# stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted candle 2
+tc10 = BTContainer(data=[
+    # D   O     H     L     C    V    B  S
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5050, 4950, 5100, 6172, 0, 0],
+    [2, 5100, 5251, 5100, 5100, 6172, 0, 0],
+    [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.1, trailing_stop=True,
+    trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.10,
+    trailing_stop_positive=0.03,
+    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=4)]
+)
+
+# Test 11: trailing_stop should raise so candle 3 causes a stoploss
+# applying a positive trailing stop of 3% since stop_positive_offset is reached.
+# stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted candle 2
+tc11 = BTContainer(data=[
+    # D   O     H     L     C    V    B  S
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5050, 4950, 5100, 6172, 0, 0],
+    [2, 5100, 5251, 5100, 5100, 6172, 0, 0],
+    [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10}, profit_perc=0.019, trailing_stop=True,
+    trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
+    trailing_stop_positive=0.03,
+    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
+)
+
+# Test 12: trailing_stop should raise in candle 2 and cause a stoploss in the same candle
+# applying a positive trailing stop of 3% since stop_positive_offset is reached.
+# stop-loss: 10%, ROI: 10% (should not apply), stoploss adjusted candle 2
+tc12 = BTContainer(data=[
+    # D   O     H     L     C    V    B  S
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5050, 4950, 5100, 6172, 0, 0],
+    [2, 5100, 5251, 4650, 5100, 6172, 0, 0],
+    [3, 4850, 5050, 4650, 4750, 6172, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10}, profit_perc=0.019, trailing_stop=True,
+    trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
+    trailing_stop_positive=0.03,
+    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=2)]
+)
+
+# Test 13: Buy and sell ROI on same candle
+# stop-loss: 10% (should not apply), ROI: 1%
+tc13 = BTContainer(data=[
+    # D   O     H     L     C    V    B  S
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5100, 4950, 5100, 6172, 0, 0],
+    [2, 5100, 5251, 4850, 5100, 6172, 0, 0],
+    [3, 4850, 5050, 4850, 4750, 6172, 0, 0],
+    [4, 4750, 4950, 4850, 4750, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.01}, profit_perc=0.01,
+    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=1)]
+)
+
+# Test 14 - Buy and Stoploss on same candle
+# stop-loss: 5%, ROI: 10% (should not apply)
+tc14 = BTContainer(data=[
+    # D   O     H     L     C    V    B  S
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5100, 4600, 5100, 6172, 0, 0],
+    [2, 5100, 5251, 4850, 5100, 6172, 0, 0],
+    [3, 4850, 5050, 4850, 4750, 6172, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
+    stop_loss=-0.05, roi={"0": 0.10}, profit_perc=-0.05,
+    trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
+)
+
+
+# Test 15 - Buy and ROI on same candle, followed by buy and Stoploss on next candle
+# stop-loss: 5%, ROI: 10% (should not apply)
+tc15 = BTContainer(data=[
+    # D   O     H     L     C    V    B  S
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5100, 4900, 5100, 6172, 1, 0],
+    [2, 5100, 5251, 4650, 5100, 6172, 0, 0],
+    [3, 4850, 5050, 4850, 4750, 6172, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
+    stop_loss=-0.05, roi={"0": 0.01}, profit_perc=-0.04,
+    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=1),
+            BTrade(sell_reason=SellType.STOP_LOSS, open_tick=2, close_tick=2)]
+)
+
+# Test 16: Buy, hold for 65 min, then forcesell using roi=-1
+# Causes negative profit even though sell-reason is ROI.
+# stop-loss: 10%, ROI: 10% (should not apply), -100% after 65 minutes (limits trade duration)
+tc16 = BTContainer(data=[
+    # D  O     H     L     C     V    B  S
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],
+    [2, 4987, 5300, 4950, 5050, 6172, 0, 0],
+    [3, 4975, 5000, 4940, 4962, 6172, 0, 0],  # ForceSell on ROI (roi=-1)
+    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10, "65": -1}, profit_perc=-0.012,
+    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
+)
+
+# Test 17: Buy, hold for 120 mins, then forcesell using roi=-1
+# Causes negative profit even though sell-reason is ROI.
+# stop-loss: 10%, ROI: 10% (should not apply), -100% after 100 minutes (limits trade duration)
+# Uses open as sell-rate (special case) - since the roi-time is a multiple of the ticker interval.
+tc17 = BTContainer(data=[
+    # D  O     H     L     C     V    B  S
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],
+    [2, 4987, 5300, 4950, 5050, 6172, 0, 0],
+    [3, 4980, 5000, 4940, 4962, 6172, 0, 0],  # ForceSell on ROI (roi=-1)
+    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10, "120": -1}, profit_perc=-0.004,
+    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
+)
+
+
+# Test 18: Buy, hold for 120 mins, then drop ROI to 1%, causing a sell in candle 3.
+# stop-loss: 10%, ROI: 10% (should not apply), -100% after 100 minutes (limits trade duration)
+# uses open_rate as sell-price
+tc18 = BTContainer(data=[
+    # D  O     H     L     C     V    B  S
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],
+    [2, 4987, 5300, 4950, 5200, 6172, 0, 0],
+    [3, 5200, 5220, 4940, 4962, 6172, 0, 0],  # Sell on ROI (sells on open)
+    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10, "120": 0.01}, profit_perc=0.04,
+    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
+)
+
+# Test 19: Buy, hold for 119 mins, then drop ROI to 1%, causing a sell in candle 3.
+# stop-loss: 10%, ROI: 10% (should not apply), -100% after 100 minutes (limits trade duration)
+# uses calculated ROI (1%) as sell rate, otherwise identical to tc18
+tc19 = BTContainer(data=[
+    # D  O     H     L     C     V    B  S
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],
+    [2, 4987, 5300, 4950, 5200, 6172, 0, 0],
+    [3, 5000, 5300, 4940, 4962, 6172, 0, 0],  # Sell on ROI
+    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [5, 4550, 4975, 4925, 4950, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10, "120": 0.01}, profit_perc=0.01,
+    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
+)
+
+# Test 20: Buy, hold for 119 mins, then drop ROI to 1%, causing a sell in candle 3.
+# stop-loss: 10%, ROI: 10% (should not apply), -100% after 100 minutes (limits trade duration)
+# uses calculated ROI (1%) as sell rate, otherwise identical to tc18
+tc20 = BTContainer(data=[
+    # D  O     H     L     C     V    B  S
+    [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
+    [1, 5000, 5025, 4975, 4987, 6172, 0, 0],
+    [2, 4987, 5300, 4950, 5200, 6172, 0, 0],
+    [3, 5200, 5300, 4940, 4962, 6172, 0, 0],  # Sell on ROI
+    [4, 4962, 4987, 4972, 4950, 6172, 0, 0],
+    [5, 4550, 4975, 4925, 4950, 6172, 0, 0]],
+    stop_loss=-0.10, roi={"0": 0.10, "119": 0.01}, profit_perc=0.01,
+    trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
+)
+
+
+TESTS = [
+    tc0,
+    tc1,
+    tc2,
+    tc3,
+    tc4,
+    tc5,
+    tc6,
+    tc7,
+    tc8,
+    tc9,
+    tc10,
+    tc11,
+    tc12,
+    tc13,
+    tc14,
+    tc15,
+    tc16,
+    tc17,
+    tc18,
+    tc19,
+    tc20,
+]
+
+
+@pytest.mark.parametrize("data", TESTS)
+def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
+    """
+    run functional tests
+    """
+    default_conf["stoploss"] = data.stop_loss
+    default_conf["minimal_roi"] = data.roi
+    default_conf["timeframe"] = tests_timeframe
+    default_conf["trailing_stop"] = data.trailing_stop
+    default_conf["trailing_only_offset_is_reached"] = data.trailing_only_offset_is_reached
+    # Only add this to configuration If it's necessary
+    if data.trailing_stop_positive is not None:
+        default_conf["trailing_stop_positive"] = data.trailing_stop_positive
+    default_conf["trailing_stop_positive_offset"] = data.trailing_stop_positive_offset
+    default_conf["ask_strategy"] = {"use_sell_signal": data.use_sell_signal}
+
+    mocker.patch("freqtrade.exchange.Exchange.get_fee", MagicMock(return_value=0.0))
+    patch_exchange(mocker)
+    frame = _build_backtest_dataframe(data.data)
+    backtesting = Backtesting(default_conf)
+    backtesting.strategy.advise_buy = lambda a, m: frame
+    backtesting.strategy.advise_sell = lambda a, m: frame
+    caplog.set_level(logging.DEBUG)
+
+    pair = "UNITTEST/BTC"
+    # Dummy data as we mock the analyze functions
+    data_processed = {pair: frame.copy()}
+    min_date, max_date = get_timerange({pair: frame})
+    results = backtesting.backtest(
+        processed=data_processed,
+        stake_amount=default_conf['stake_amount'],
+        start_date=min_date,
+        end_date=max_date,
+        max_open_trades=10,
+    )
+
+    assert len(results) == len(data.trades)
+    assert round(results["profit_percent"].sum(), 3) == round(data.profit_perc, 3)
+
+    for c, trade in enumerate(data.trades):
+        res = results.iloc[c]
+        assert res.sell_reason == trade.sell_reason
+        assert res.open_date == _get_frame_time_from_offset(trade.open_tick)
+        assert res.close_date == _get_frame_time_from_offset(trade.close_tick)
diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py
new file mode 100644
index 000000000..45cbea68e
--- /dev/null
+++ b/tests/optimize/test_backtesting.py
@@ -0,0 +1,841 @@
+# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
+
+import random
+from pathlib import Path
+from unittest.mock import MagicMock, PropertyMock
+
+import numpy as np
+import pandas as pd
+import pytest
+from arrow import Arrow
+
+from freqtrade import constants
+from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_backtesting
+from freqtrade.configuration import TimeRange
+from freqtrade.data import history
+from freqtrade.data.btanalysis import BT_DATA_COLUMNS, evaluate_result_multi
+from freqtrade.data.converter import clean_ohlcv_dataframe
+from freqtrade.data.dataprovider import DataProvider
+from freqtrade.data.history import get_timerange
+from freqtrade.exceptions import DependencyException, OperationalException
+from freqtrade.optimize.backtesting import Backtesting
+from freqtrade.resolvers import StrategyResolver
+from freqtrade.state import RunMode
+from freqtrade.strategy.interface import SellType
+from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
+                            patched_configuration_load_config_file)
+
+
+ORDER_TYPES = [
+    {
+        'buy': 'limit',
+        'sell': 'limit',
+        'stoploss': 'limit',
+        'stoploss_on_exchange': False
+    },
+    {
+        'buy': 'limit',
+        'sell': 'limit',
+        'stoploss': 'limit',
+        'stoploss_on_exchange': True
+    }]
+
+
+def trim_dictlist(dict_list, num):
+    new = {}
+    for pair, pair_data in dict_list.items():
+        new[pair] = pair_data[num:].reset_index()
+    return new
+
+
+def load_data_test(what, testdatadir):
+    timerange = TimeRange.parse_timerange('1510694220-1510700340')
+    data = history.load_pair_history(pair='UNITTEST/BTC', datadir=testdatadir,
+                                     timeframe='1m', timerange=timerange,
+                                     drop_incomplete=False,
+                                     fill_up_missing=False)
+
+    base = 0.001
+    if what == 'raise':
+        data.loc[:, 'open'] = data.index * base
+        data.loc[:, 'high'] = data.index * base + 0.0001
+        data.loc[:, 'low'] = data.index * base - 0.0001
+        data.loc[:, 'close'] = data.index * base
+
+    if what == 'lower':
+        data.loc[:, 'open'] = 1 - data.index * base
+        data.loc[:, 'high'] = 1 - data.index * base + 0.0001
+        data.loc[:, 'low'] = 1 - data.index * base - 0.0001
+        data.loc[:, 'close'] = 1 - data.index * base
+
+    if what == 'sine':
+        hz = 0.1  # frequency
+        data.loc[:, 'open'] = np.sin(data.index * hz) / 1000 + base
+        data.loc[:, 'high'] = np.sin(data.index * hz) / 1000 + base + 0.0001
+        data.loc[:, 'low'] = np.sin(data.index * hz) / 1000 + base - 0.0001
+        data.loc[:, 'close'] = np.sin(data.index * hz) / 1000 + base
+
+    return {'UNITTEST/BTC': clean_ohlcv_dataframe(data, timeframe='1m', pair='UNITTEST/BTC',
+                                                  fill_missing=True)}
+
+
+def simple_backtest(config, contour, num_results, mocker, testdatadir) -> None:
+    patch_exchange(mocker)
+    config['timeframe'] = '1m'
+    backtesting = Backtesting(config)
+
+    data = load_data_test(contour, testdatadir)
+    processed = backtesting.strategy.ohlcvdata_to_dataframe(data)
+    min_date, max_date = get_timerange(processed)
+    assert isinstance(processed, dict)
+    results = backtesting.backtest(
+        processed=processed,
+        stake_amount=config['stake_amount'],
+        start_date=min_date,
+        end_date=max_date,
+        max_open_trades=1,
+        position_stacking=False,
+    )
+    # results :: <class 'pandas.core.frame.DataFrame'>
+    assert len(results) == num_results
+
+
+# FIX: fixturize this?
+def _make_backtest_conf(mocker, datadir, conf=None, pair='UNITTEST/BTC'):
+    data = history.load_data(datadir=datadir, timeframe='1m', pairs=[pair])
+    data = trim_dictlist(data, -201)
+    patch_exchange(mocker)
+    backtesting = Backtesting(conf)
+    processed = backtesting.strategy.ohlcvdata_to_dataframe(data)
+    min_date, max_date = get_timerange(processed)
+    return {
+        'processed': processed,
+        'stake_amount': conf['stake_amount'],
+        'start_date': min_date,
+        'end_date': max_date,
+        'max_open_trades': 10,
+        'position_stacking': False,
+    }
+
+
+def _trend(signals, buy_value, sell_value):
+    n = len(signals['low'])
+    buy = np.zeros(n)
+    sell = np.zeros(n)
+    for i in range(0, len(signals['buy'])):
+        if random.random() > 0.5:  # Both buy and sell signals at same timeframe
+            buy[i] = buy_value
+            sell[i] = sell_value
+    signals['buy'] = buy
+    signals['sell'] = sell
+    return signals
+
+
+def _trend_alternate(dataframe=None, metadata=None):
+    signals = dataframe
+    low = signals['low']
+    n = len(low)
+    buy = np.zeros(n)
+    sell = np.zeros(n)
+    for i in range(0, len(buy)):
+        if i % 2 == 0:
+            buy[i] = 1
+        else:
+            sell[i] = 1
+    signals['buy'] = buy
+    signals['sell'] = sell
+    return dataframe
+
+
+# Unit tests
+def test_setup_optimize_configuration_without_arguments(mocker, default_conf, caplog) -> None:
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = [
+        'backtesting',
+        '--config', 'config.json',
+        '--strategy', 'DefaultStrategy',
+    ]
+
+    config = setup_optimize_configuration(get_args(args), RunMode.BACKTEST)
+    assert 'max_open_trades' in config
+    assert 'stake_currency' in config
+    assert 'stake_amount' in config
+    assert 'exchange' in config
+    assert 'pair_whitelist' in config['exchange']
+    assert 'datadir' in config
+    assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
+    assert 'timeframe' in config
+    assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog)
+
+    assert 'position_stacking' not in config
+    assert not log_has('Parameter --enable-position-stacking detected ...', caplog)
+
+    assert 'timerange' not in config
+    assert 'export' not in config
+    assert 'runmode' in config
+    assert config['runmode'] == RunMode.BACKTEST
+
+
+def test_setup_bt_configuration_with_arguments(mocker, default_conf, caplog) -> None:
+    patched_configuration_load_config_file(mocker, default_conf)
+    mocker.patch(
+        'freqtrade.configuration.configuration.create_datadir',
+        lambda c, x: x
+    )
+
+    args = [
+        'backtesting',
+        '--config', 'config.json',
+        '--strategy', 'DefaultStrategy',
+        '--datadir', '/foo/bar',
+        '--timeframe', '1m',
+        '--enable-position-stacking',
+        '--disable-max-market-positions',
+        '--timerange', ':100',
+        '--export', '/bar/foo',
+        '--export-filename', 'foo_bar.json',
+        '--fee', '0',
+    ]
+
+    config = setup_optimize_configuration(get_args(args), RunMode.BACKTEST)
+    assert 'max_open_trades' in config
+    assert 'stake_currency' in config
+    assert 'stake_amount' in config
+    assert 'exchange' in config
+    assert 'pair_whitelist' in config['exchange']
+    assert 'datadir' in config
+    assert config['runmode'] == RunMode.BACKTEST
+
+    assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
+    assert 'timeframe' in config
+    assert log_has('Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
+                   caplog)
+
+    assert 'position_stacking' in config
+    assert log_has('Parameter --enable-position-stacking detected ...', caplog)
+
+    assert 'use_max_market_positions' in config
+    assert log_has('Parameter --disable-max-market-positions detected ...', caplog)
+    assert log_has('max_open_trades set to unlimited ...', caplog)
+
+    assert 'timerange' in config
+    assert log_has('Parameter --timerange detected: {} ...'.format(config['timerange']), caplog)
+
+    assert 'export' in config
+    assert log_has('Parameter --export detected: {} ...'.format(config['export']), caplog)
+    assert 'exportfilename' in config
+    assert isinstance(config['exportfilename'], Path)
+    assert log_has('Storing backtest results to {} ...'.format(config['exportfilename']), caplog)
+
+    assert 'fee' in config
+    assert log_has('Parameter --fee detected, setting fee to: {} ...'.format(config['fee']), caplog)
+
+
+def test_setup_optimize_configuration_unlimited_stake_amount(mocker, default_conf, caplog) -> None:
+    default_conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
+
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = [
+        'backtesting',
+        '--config', 'config.json',
+        '--strategy', 'DefaultStrategy',
+    ]
+
+    with pytest.raises(DependencyException, match=r'.`stake_amount`.*'):
+        setup_optimize_configuration(get_args(args), RunMode.BACKTEST)
+
+
+def test_start(mocker, fee, default_conf, caplog) -> None:
+    start_mock = MagicMock()
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
+    patch_exchange(mocker)
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.start', start_mock)
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = [
+        'backtesting',
+        '--config', 'config.json',
+        '--strategy', 'DefaultStrategy',
+    ]
+    pargs = get_args(args)
+    start_backtesting(pargs)
+    assert log_has('Starting freqtrade in Backtesting mode', caplog)
+    assert start_mock.call_count == 1
+
+
+@pytest.mark.parametrize("order_types", ORDER_TYPES)
+def test_backtesting_init(mocker, default_conf, order_types) -> None:
+    """
+    Check that stoploss_on_exchange is set to False while backtesting
+    since backtesting assumes a perfect stoploss anyway.
+    """
+    default_conf["order_types"] = order_types
+    patch_exchange(mocker)
+    get_fee = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
+    backtesting = Backtesting(default_conf)
+    assert backtesting.config == default_conf
+    assert backtesting.timeframe == '5m'
+    assert callable(backtesting.strategy.ohlcvdata_to_dataframe)
+    assert callable(backtesting.strategy.advise_buy)
+    assert callable(backtesting.strategy.advise_sell)
+    assert isinstance(backtesting.strategy.dp, DataProvider)
+    get_fee.assert_called()
+    assert backtesting.fee == 0.5
+    assert not backtesting.strategy.order_types["stoploss_on_exchange"]
+
+
+def test_backtesting_init_no_timeframe(mocker, default_conf, caplog) -> None:
+    patch_exchange(mocker)
+    del default_conf['timeframe']
+    default_conf['strategy_list'] = ['DefaultStrategy',
+                                     'SampleStrategy']
+
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
+    with pytest.raises(OperationalException):
+        Backtesting(default_conf)
+    log_has("Ticker-interval needs to be set in either configuration "
+            "or as cli argument `--ticker-interval 5m`", caplog)
+
+
+def test_data_with_fee(default_conf, mocker, testdatadir) -> None:
+    patch_exchange(mocker)
+    default_conf['fee'] = 0.1234
+
+    fee_mock = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
+    backtesting = Backtesting(default_conf)
+    assert backtesting.fee == 0.1234
+    assert fee_mock.call_count == 0
+
+    default_conf['fee'] = 0.0
+    backtesting = Backtesting(default_conf)
+    assert backtesting.fee == 0.0
+    assert fee_mock.call_count == 0
+
+
+def test_data_to_dataframe_bt(default_conf, mocker, testdatadir) -> None:
+    patch_exchange(mocker)
+    timerange = TimeRange.parse_timerange('1510694220-1510700340')
+    data = history.load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
+                             fill_up_missing=True)
+    backtesting = Backtesting(default_conf)
+    processed = backtesting.strategy.ohlcvdata_to_dataframe(data)
+    assert len(processed['UNITTEST/BTC']) == 102
+
+    # Load strategy to compare the result between Backtesting function and strategy are the same
+    default_conf.update({'strategy': 'DefaultStrategy'})
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    processed2 = strategy.ohlcvdata_to_dataframe(data)
+    assert processed['UNITTEST/BTC'].equals(processed2['UNITTEST/BTC'])
+
+
+def test_backtesting_start(default_conf, mocker, testdatadir, caplog) -> None:
+    def get_timerange(input1):
+        return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59)
+
+    mocker.patch('freqtrade.data.history.get_timerange', get_timerange)
+    patch_exchange(mocker)
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest')
+    mocker.patch('freqtrade.optimize.backtesting.generate_backtest_stats')
+    mocker.patch('freqtrade.optimize.backtesting.show_backtest_results')
+    mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.whitelist',
+                 PropertyMock(return_value=['UNITTEST/BTC']))
+
+    default_conf['timeframe'] = '1m'
+    default_conf['datadir'] = testdatadir
+    default_conf['export'] = None
+    default_conf['timerange'] = '-1510694220'
+
+    backtesting = Backtesting(default_conf)
+    backtesting.start()
+    # check the logs, that will contain the backtest result
+    exists = [
+        'Using stake_currency: BTC ...',
+        'Using stake_amount: 0.001 ...',
+        'Backtesting with data from 2017-11-14 21:17:00 '
+        'up to 2017-11-14 22:59:00 (0 days)..'
+    ]
+    for line in exists:
+        assert log_has(line, caplog)
+    assert backtesting.strategy.dp._pairlists is not None
+
+
+def test_backtesting_start_no_data(default_conf, mocker, caplog, testdatadir) -> None:
+    def get_timerange(input1):
+        return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59)
+
+    mocker.patch('freqtrade.data.history.history_utils.load_pair_history',
+                 MagicMock(return_value=pd.DataFrame()))
+    mocker.patch('freqtrade.data.history.get_timerange', get_timerange)
+    patch_exchange(mocker)
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest')
+    mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.whitelist',
+                 PropertyMock(return_value=['UNITTEST/BTC']))
+
+    default_conf['timeframe'] = "1m"
+    default_conf['datadir'] = testdatadir
+    default_conf['export'] = None
+    default_conf['timerange'] = '20180101-20180102'
+
+    backtesting = Backtesting(default_conf)
+    with pytest.raises(OperationalException, match='No data found. Terminating.'):
+        backtesting.start()
+
+
+def test_backtesting_no_pair_left(default_conf, mocker, caplog, testdatadir) -> None:
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
+    mocker.patch('freqtrade.data.history.history_utils.load_pair_history',
+                 MagicMock(return_value=pd.DataFrame()))
+    mocker.patch('freqtrade.data.history.get_timerange', get_timerange)
+    patch_exchange(mocker)
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest')
+    mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.whitelist',
+                 PropertyMock(return_value=[]))
+
+    default_conf['timeframe'] = "1m"
+    default_conf['datadir'] = testdatadir
+    default_conf['export'] = None
+    default_conf['timerange'] = '20180101-20180102'
+
+    with pytest.raises(OperationalException, match='No pair in whitelist.'):
+        Backtesting(default_conf)
+
+    default_conf['pairlists'] = [{"method": "VolumePairList", "number_assets": 5}]
+    with pytest.raises(OperationalException, match='VolumePairList not allowed for backtesting.'):
+        Backtesting(default_conf)
+
+
+def test_backtesting_pairlist_list(default_conf, mocker, caplog, testdatadir, tickers) -> None:
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
+    mocker.patch('freqtrade.exchange.Exchange.get_tickers', tickers)
+    mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
+    mocker.patch('freqtrade.data.history.get_timerange', get_timerange)
+    patch_exchange(mocker)
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest')
+    mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.whitelist',
+                 PropertyMock(return_value=['XRP/BTC']))
+    mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.refresh_pairlist')
+
+    default_conf['ticker_interval'] = "1m"
+    default_conf['datadir'] = testdatadir
+    default_conf['export'] = None
+    # Use stoploss from strategy
+    del default_conf['stoploss']
+    default_conf['timerange'] = '20180101-20180102'
+
+    default_conf['pairlists'] = [{"method": "VolumePairList", "number_assets": 5}]
+    with pytest.raises(OperationalException, match='VolumePairList not allowed for backtesting.'):
+        Backtesting(default_conf)
+
+    default_conf['pairlists'] = [{"method": "StaticPairList"}, {"method": "PrecisionFilter"}, ]
+    Backtesting(default_conf)
+
+    # Multiple strategies
+    default_conf['strategy_list'] = ['DefaultStrategy', 'TestStrategyLegacy']
+    with pytest.raises(OperationalException,
+                       match='PrecisionFilter not allowed for backtesting multiple strategies.'):
+        Backtesting(default_conf)
+
+
+def test_backtest(default_conf, fee, mocker, testdatadir) -> None:
+    default_conf['ask_strategy']['use_sell_signal'] = False
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
+    patch_exchange(mocker)
+    backtesting = Backtesting(default_conf)
+    pair = 'UNITTEST/BTC'
+    timerange = TimeRange('date', None, 1517227800, 0)
+    data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'],
+                             timerange=timerange)
+    processed = backtesting.strategy.ohlcvdata_to_dataframe(data)
+    min_date, max_date = get_timerange(processed)
+    results = backtesting.backtest(
+        processed=processed,
+        stake_amount=default_conf['stake_amount'],
+        start_date=min_date,
+        end_date=max_date,
+        max_open_trades=10,
+        position_stacking=False,
+    )
+    assert not results.empty
+    assert len(results) == 2
+
+    expected = pd.DataFrame(
+        {'pair': [pair, pair],
+         'profit_percent': [0.0, 0.0],
+         'profit_abs': [0.0, 0.0],
+         'open_date': pd.to_datetime([Arrow(2018, 1, 29, 18, 40, 0).datetime,
+                                      Arrow(2018, 1, 30, 3, 30, 0).datetime], utc=True
+                                     ),
+         'open_rate': [0.104445, 0.10302485],
+         'open_fee': [0.0025, 0.0025],
+         'close_date': pd.to_datetime([Arrow(2018, 1, 29, 22, 35, 0).datetime,
+                                       Arrow(2018, 1, 30, 4, 10, 0).datetime], utc=True),
+         'close_rate': [0.104969, 0.103541],
+         'close_fee': [0.0025, 0.0025],
+         'amount': [0.00957442, 0.0097064],
+         'trade_duration': [235, 40],
+         'open_at_end': [False, False],
+         'sell_reason': [SellType.ROI, SellType.ROI]
+         })
+    pd.testing.assert_frame_equal(results, expected)
+    data_pair = processed[pair]
+    for _, t in results.iterrows():
+        ln = data_pair.loc[data_pair["date"] == t["open_date"]]
+        # Check open trade rate alignes to open rate
+        assert ln is not None
+        assert round(ln.iloc[0]["open"], 6) == round(t["open_rate"], 6)
+        # check close trade rate alignes to close rate or is between high and low
+        ln = data_pair.loc[data_pair["date"] == t["close_date"]]
+        assert (round(ln.iloc[0]["open"], 6) == round(t["close_rate"], 6) or
+                round(ln.iloc[0]["low"], 6) < round(
+                t["close_rate"], 6) < round(ln.iloc[0]["high"], 6))
+
+
+def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> None:
+    default_conf['ask_strategy']['use_sell_signal'] = False
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
+    patch_exchange(mocker)
+    backtesting = Backtesting(default_conf)
+
+    # Run a backtesting for an exiting 1min timeframe
+    timerange = TimeRange.parse_timerange('1510688220-1510700340')
+    data = history.load_data(datadir=testdatadir, timeframe='1m', pairs=['UNITTEST/BTC'],
+                             timerange=timerange)
+    processed = backtesting.strategy.ohlcvdata_to_dataframe(data)
+    min_date, max_date = get_timerange(processed)
+    results = backtesting.backtest(
+        processed=processed,
+        stake_amount=default_conf['stake_amount'],
+        start_date=min_date,
+        end_date=max_date,
+        max_open_trades=1,
+        position_stacking=False,
+    )
+    assert not results.empty
+    assert len(results) == 1
+
+
+def test_processed(default_conf, mocker, testdatadir) -> None:
+    patch_exchange(mocker)
+    backtesting = Backtesting(default_conf)
+
+    dict_of_tickerrows = load_data_test('raise', testdatadir)
+    dataframes = backtesting.strategy.ohlcvdata_to_dataframe(dict_of_tickerrows)
+    dataframe = dataframes['UNITTEST/BTC']
+    cols = dataframe.columns
+    # assert the dataframe got some of the indicator columns
+    for col in ['close', 'high', 'low', 'open', 'date',
+                'ema10', 'rsi', 'fastd', 'plus_di']:
+        assert col in cols
+
+
+def test_backtest_pricecontours(default_conf, fee, mocker, testdatadir) -> None:
+    # TODO: Evaluate usefullness of this, the patterns and buy-signls are unrealistic
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
+    tests = [['raise', 19], ['lower', 0], ['sine', 35]]
+
+    for [contour, numres] in tests:
+        simple_backtest(default_conf, contour, numres, mocker, testdatadir)
+
+
+def test_backtest_clash_buy_sell(mocker, default_conf, testdatadir):
+    # Override the default buy trend function in our default_strategy
+    def fun(dataframe=None, pair=None):
+        buy_value = 1
+        sell_value = 1
+        return _trend(dataframe, buy_value, sell_value)
+
+    backtest_conf = _make_backtest_conf(mocker, conf=default_conf, datadir=testdatadir)
+    backtesting = Backtesting(default_conf)
+    backtesting.strategy.advise_buy = fun  # Override
+    backtesting.strategy.advise_sell = fun  # Override
+    results = backtesting.backtest(**backtest_conf)
+    assert results.empty
+
+
+def test_backtest_only_sell(mocker, default_conf, testdatadir):
+    # Override the default buy trend function in our default_strategy
+    def fun(dataframe=None, pair=None):
+        buy_value = 0
+        sell_value = 1
+        return _trend(dataframe, buy_value, sell_value)
+
+    backtest_conf = _make_backtest_conf(mocker, conf=default_conf, datadir=testdatadir)
+    backtesting = Backtesting(default_conf)
+    backtesting.strategy.advise_buy = fun  # Override
+    backtesting.strategy.advise_sell = fun  # Override
+    results = backtesting.backtest(**backtest_conf)
+    assert results.empty
+
+
+def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
+    backtest_conf = _make_backtest_conf(mocker, conf=default_conf,
+                                        pair='UNITTEST/BTC', datadir=testdatadir)
+    default_conf['timeframe'] = '1m'
+    backtesting = Backtesting(default_conf)
+    backtesting.strategy.advise_buy = _trend_alternate  # Override
+    backtesting.strategy.advise_sell = _trend_alternate  # Override
+    results = backtesting.backtest(**backtest_conf)
+    # 200 candles in backtest data
+    # won't buy on first (shifted by 1)
+    # 100 buys signals
+    assert len(results) == 100
+    # One trade was force-closed at the end
+    assert len(results.loc[results.open_at_end]) == 0
+
+
+@pytest.mark.parametrize("pair", ['ADA/BTC', 'LTC/BTC'])
+@pytest.mark.parametrize("tres", [0, 20, 30])
+def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir):
+
+    def _trend_alternate_hold(dataframe=None, metadata=None):
+        """
+        Buy every xth candle - sell every other xth -2 (hold on to pairs a bit)
+        """
+        if metadata['pair'] in ('ETH/BTC', 'LTC/BTC'):
+            multi = 20
+        else:
+            multi = 18
+        dataframe['buy'] = np.where(dataframe.index % multi == 0, 1, 0)
+        dataframe['sell'] = np.where((dataframe.index + multi - 2) % multi == 0, 1, 0)
+        return dataframe
+
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
+    patch_exchange(mocker)
+
+    pairs = ['ADA/BTC', 'DASH/BTC', 'ETH/BTC', 'LTC/BTC', 'NXT/BTC']
+    data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=pairs)
+    # Only use 500 lines to increase performance
+    data = trim_dictlist(data, -500)
+
+    # Remove data for one pair from the beginning of the data
+    data[pair] = data[pair][tres:].reset_index()
+    default_conf['timeframe'] = '5m'
+
+    backtesting = Backtesting(default_conf)
+    backtesting.strategy.advise_buy = _trend_alternate_hold  # Override
+    backtesting.strategy.advise_sell = _trend_alternate_hold  # Override
+
+    processed = backtesting.strategy.ohlcvdata_to_dataframe(data)
+    min_date, max_date = get_timerange(processed)
+    backtest_conf = {
+        'processed': processed,
+        'stake_amount': default_conf['stake_amount'],
+        'start_date': min_date,
+        'end_date': max_date,
+        'max_open_trades': 3,
+        'position_stacking': False,
+    }
+
+    results = backtesting.backtest(**backtest_conf)
+
+    # Make sure we have parallel trades
+    assert len(evaluate_result_multi(results, '5m', 2)) > 0
+    # make sure we don't have trades with more than configured max_open_trades
+    assert len(evaluate_result_multi(results, '5m', 3)) == 0
+
+    backtest_conf = {
+        'processed': processed,
+        'stake_amount': default_conf['stake_amount'],
+        'start_date': min_date,
+        'end_date': max_date,
+        'max_open_trades': 1,
+        'position_stacking': False,
+    }
+    results = backtesting.backtest(**backtest_conf)
+    assert len(evaluate_result_multi(results, '5m', 1)) == 0
+
+
+def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
+
+    patch_exchange(mocker)
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest')
+    mocker.patch('freqtrade.optimize.backtesting.generate_backtest_stats')
+    mocker.patch('freqtrade.optimize.backtesting.show_backtest_results')
+    mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.whitelist',
+                 PropertyMock(return_value=['UNITTEST/BTC']))
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = [
+        'backtesting',
+        '--config', 'config.json',
+        '--strategy', 'DefaultStrategy',
+        '--datadir', str(testdatadir),
+        '--timeframe', '1m',
+        '--timerange', '1510694220-1510700340',
+        '--enable-position-stacking',
+        '--disable-max-market-positions'
+    ]
+    args = get_args(args)
+    start_backtesting(args)
+    # check the logs, that will contain the backtest result
+    exists = [
+        'Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
+        'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
+        'Parameter --timerange detected: 1510694220-1510700340 ...',
+        f'Using data directory: {testdatadir} ...',
+        'Using stake_currency: BTC ...',
+        'Using stake_amount: 0.001 ...',
+        'Loading data from 2017-11-14 20:57:00 '
+        'up to 2017-11-14 22:58:00 (0 days)..',
+        'Backtesting with data from 2017-11-14 21:17:00 '
+        'up to 2017-11-14 22:58:00 (0 days)..',
+        'Parameter --enable-position-stacking detected ...'
+    ]
+
+    for line in exists:
+        assert log_has(line, caplog)
+
+
+@pytest.mark.filterwarnings("ignore:deprecated")
+def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
+
+    patch_exchange(mocker)
+    backtestmock = MagicMock(return_value=pd.DataFrame(columns=BT_DATA_COLUMNS + ['profit_abs']))
+    mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.whitelist',
+                 PropertyMock(return_value=['UNITTEST/BTC']))
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
+    text_table_mock = MagicMock()
+    sell_reason_mock = MagicMock()
+    strattable_mock = MagicMock()
+    strat_summary = MagicMock()
+
+    mocker.patch.multiple('freqtrade.optimize.optimize_reports',
+                          text_table_bt_results=text_table_mock,
+                          text_table_strategy=strattable_mock,
+                          generate_pair_metrics=MagicMock(),
+                          generate_sell_reason_stats=sell_reason_mock,
+                          generate_strategy_metrics=strat_summary,
+                          generate_daily_stats=MagicMock(),
+                          )
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = [
+        'backtesting',
+        '--config', 'config.json',
+        '--datadir', str(testdatadir),
+        '--strategy-path', str(Path(__file__).parents[1] / 'strategy/strats'),
+        '--timeframe', '1m',
+        '--timerange', '1510694220-1510700340',
+        '--enable-position-stacking',
+        '--disable-max-market-positions',
+        '--strategy-list',
+        'DefaultStrategy',
+        'TestStrategyLegacy',
+    ]
+    args = get_args(args)
+    start_backtesting(args)
+    # 2 backtests, 4 tables
+    assert backtestmock.call_count == 2
+    assert text_table_mock.call_count == 4
+    assert strattable_mock.call_count == 1
+    assert sell_reason_mock.call_count == 2
+    assert strat_summary.call_count == 1
+
+    # check the logs, that will contain the backtest result
+    exists = [
+        'Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
+        'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
+        'Parameter --timerange detected: 1510694220-1510700340 ...',
+        f'Using data directory: {testdatadir} ...',
+        'Using stake_currency: BTC ...',
+        'Using stake_amount: 0.001 ...',
+        'Loading data from 2017-11-14 20:57:00 '
+        'up to 2017-11-14 22:58:00 (0 days)..',
+        'Backtesting with data from 2017-11-14 21:17:00 '
+        'up to 2017-11-14 22:58:00 (0 days)..',
+        'Parameter --enable-position-stacking detected ...',
+        'Running backtesting for Strategy DefaultStrategy',
+        'Running backtesting for Strategy TestStrategyLegacy',
+    ]
+
+    for line in exists:
+        assert log_has(line, caplog)
+
+
+@pytest.mark.filterwarnings("ignore:deprecated")
+def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdatadir, capsys):
+
+    patch_exchange(mocker)
+    backtestmock = MagicMock(side_effect=[
+        pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC'],
+                      'profit_percent': [0.0, 0.0],
+                      'profit_abs': [0.0, 0.0],
+                      'open_date': pd.to_datetime(['2018-01-29 18:40:00',
+                                                   '2018-01-30 03:30:00', ], utc=True
+                                                  ),
+                      'close_date': pd.to_datetime(['2018-01-29 20:45:00',
+                                                    '2018-01-30 05:35:00', ], utc=True),
+                      'trade_duration': [235, 40],
+                      'open_at_end': [False, False],
+                      'open_rate': [0.104445, 0.10302485],
+                      'close_rate': [0.104969, 0.103541],
+                      'sell_reason': [SellType.ROI, SellType.ROI]
+                      }),
+        pd.DataFrame({'pair': ['XRP/BTC', 'LTC/BTC', 'ETH/BTC'],
+                      'profit_percent': [0.03, 0.01, 0.1],
+                      'profit_abs': [0.01, 0.02, 0.2],
+                      'open_date': pd.to_datetime(['2018-01-29 18:40:00',
+                                                   '2018-01-30 03:30:00',
+                                                   '2018-01-30 05:30:00'], utc=True
+                                                  ),
+                      'close_date': pd.to_datetime(['2018-01-29 20:45:00',
+                                                    '2018-01-30 05:35:00',
+                                                    '2018-01-30 08:30:00'], utc=True),
+                      'trade_duration': [47, 40, 20],
+                      'open_at_end': [False, False, False],
+                      'open_rate': [0.104445, 0.10302485, 0.122541],
+                      'close_rate': [0.104969, 0.103541, 0.123541],
+                      'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
+                      }),
+    ])
+    mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.whitelist',
+                 PropertyMock(return_value=['UNITTEST/BTC']))
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
+
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = [
+        'backtesting',
+        '--config', 'config.json',
+        '--datadir', str(testdatadir),
+        '--strategy-path', str(Path(__file__).parents[1] / 'strategy/strats'),
+        '--timeframe', '1m',
+        '--timerange', '1510694220-1510700340',
+        '--enable-position-stacking',
+        '--disable-max-market-positions',
+        '--strategy-list',
+        'DefaultStrategy',
+        'TestStrategyLegacy',
+    ]
+    args = get_args(args)
+    start_backtesting(args)
+
+    # check the logs, that will contain the backtest result
+    exists = [
+        'Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
+        'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
+        'Parameter --timerange detected: 1510694220-1510700340 ...',
+        f'Using data directory: {testdatadir} ...',
+        'Using stake_currency: BTC ...',
+        'Using stake_amount: 0.001 ...',
+        'Loading data from 2017-11-14 20:57:00 '
+        'up to 2017-11-14 22:58:00 (0 days)..',
+        'Backtesting with data from 2017-11-14 21:17:00 '
+        'up to 2017-11-14 22:58:00 (0 days)..',
+        'Parameter --enable-position-stacking detected ...',
+        'Running backtesting for Strategy DefaultStrategy',
+        'Running backtesting for Strategy TestStrategyLegacy',
+    ]
+
+    for line in exists:
+        assert log_has(line, caplog)
+
+    captured = capsys.readouterr()
+    assert 'BACKTESTING REPORT' in captured.out
+    assert 'SELL REASON STATS' in captured.out
+    assert 'LEFT OPEN TRADES REPORT' in captured.out
+    assert 'STRATEGY SUMMARY' in captured.out
diff --git a/freqtrade/tests/optimize/test_edge_cli.py b/tests/optimize/test_edge_cli.py
similarity index 54%
rename from freqtrade/tests/optimize/test_edge_cli.py
rename to tests/optimize/test_edge_cli.py
index badaa5c45..188b4aa5f 100644
--- a/freqtrade/tests/optimize/test_edge_cli.py
+++ b/tests/optimize/test_edge_cli.py
@@ -3,24 +3,23 @@
 
 from unittest.mock import MagicMock
 
-from freqtrade.edge import PairInfo
-from freqtrade.optimize import setup_configuration, start_edge
+from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_edge
 from freqtrade.optimize.edge_cli import EdgeCli
 from freqtrade.state import RunMode
-from freqtrade.tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
-                                      patched_configuration_load_config_file)
+from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
+                            patched_configuration_load_config_file)
 
 
-def test_setup_configuration_without_arguments(mocker, default_conf, caplog) -> None:
+def test_setup_optimize_configuration_without_arguments(mocker, default_conf, caplog) -> None:
     patched_configuration_load_config_file(mocker, default_conf)
 
     args = [
+        'edge',
         '--config', 'config.json',
         '--strategy', 'DefaultStrategy',
-        'edge'
     ]
 
-    config = setup_configuration(get_args(args), RunMode.EDGE)
+    config = setup_optimize_configuration(get_args(args), RunMode.EDGE)
     assert config['runmode'] == RunMode.EDGE
 
     assert 'max_open_trades' in config
@@ -29,15 +28,9 @@ def test_setup_configuration_without_arguments(mocker, default_conf, caplog) ->
     assert 'exchange' in config
     assert 'pair_whitelist' in config['exchange']
     assert 'datadir' in config
-    assert log_has(
-        'Using data directory: {} ...'.format(config['datadir']),
-        caplog.record_tuples
-    )
-    assert 'ticker_interval' in config
-    assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog.record_tuples)
-
-    assert 'refresh_pairs' not in config
-    assert not log_has('Parameter -r/--refresh-pairs-cached detected ...', caplog.record_tuples)
+    assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
+    assert 'timeframe' in config
+    assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog)
 
     assert 'timerange' not in config
     assert 'stoploss_range' not in config
@@ -51,17 +44,16 @@ def test_setup_edge_configuration_with_arguments(mocker, edge_conf, caplog) -> N
     )
 
     args = [
+        'edge',
         '--config', 'config.json',
         '--strategy', 'DefaultStrategy',
         '--datadir', '/foo/bar',
-        'edge',
-        '--ticker-interval', '1m',
-        '--refresh-pairs-cached',
+        '--timeframe', '1m',
         '--timerange', ':100',
         '--stoplosses=-0.01,-0.10,-0.001'
     ]
 
-    config = setup_configuration(get_args(args), RunMode.EDGE)
+    config = setup_optimize_configuration(get_args(args), RunMode.EDGE)
     assert 'max_open_trades' in config
     assert 'stake_currency' in config
     assert 'stake_amount' in config
@@ -69,21 +61,13 @@ def test_setup_edge_configuration_with_arguments(mocker, edge_conf, caplog) -> N
     assert 'pair_whitelist' in config['exchange']
     assert 'datadir' in config
     assert config['runmode'] == RunMode.EDGE
-    assert log_has(
-        'Using data directory: {} ...'.format(config['datadir']),
-        caplog.record_tuples
-    )
-    assert 'ticker_interval' in config
-    assert log_has('Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
-                   caplog.record_tuples)
+    assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
+    assert 'timeframe' in config
+    assert log_has('Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
+                   caplog)
 
-    assert 'refresh_pairs' in config
-    assert log_has('Parameter -r/--refresh-pairs-cached detected ...', caplog.record_tuples)
     assert 'timerange' in config
-    assert log_has(
-        'Parameter --timerange detected: {} ...'.format(config['timerange']),
-        caplog.record_tuples
-    )
+    assert log_has('Parameter --timerange detected: {} ...'.format(config['timerange']), caplog)
 
 
 def test_start(mocker, fee, edge_conf, caplog) -> None:
@@ -94,16 +78,13 @@ def test_start(mocker, fee, edge_conf, caplog) -> None:
     patched_configuration_load_config_file(mocker, edge_conf)
 
     args = [
+        'edge',
         '--config', 'config.json',
         '--strategy', 'DefaultStrategy',
-        'edge'
     ]
-    args = get_args(args)
-    start_edge(args)
-    assert log_has(
-        'Starting freqtrade in Edge mode',
-        caplog.record_tuples
-    )
+    pargs = get_args(args)
+    start_edge(pargs)
+    assert log_has('Starting freqtrade in Edge mode', caplog)
     assert start_mock.call_count == 1
 
 
@@ -116,14 +97,25 @@ def test_edge_init(mocker, edge_conf) -> None:
     assert callable(edge_cli.edge.calculate)
 
 
-def test_generate_edge_table(edge_conf, mocker):
+def test_edge_init_fee(mocker, edge_conf) -> None:
     patch_exchange(mocker)
+    edge_conf['fee'] = 0.1234
+    edge_conf['stake_amount'] = 20
+    fee_mock = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
     edge_cli = EdgeCli(edge_conf)
+    assert edge_cli.edge.fee == 0.1234
+    assert fee_mock.call_count == 0
 
-    results = {}
-    results['ETH/BTC'] = PairInfo(-0.01, 0.60, 2, 1, 3, 10, 60)
 
-    assert edge_cli._generate_edge_table(results).count(':|') == 7
-    assert edge_cli._generate_edge_table(results).count('| ETH/BTC |') == 1
-    assert edge_cli._generate_edge_table(results).count(
-        '|   risk reward ratio |   required risk reward |   expectancy |') == 1
+def test_edge_start(mocker, edge_conf) -> None:
+    mock_calculate = mocker.patch('freqtrade.edge.edge_positioning.Edge.calculate',
+                                  return_value=True)
+    table_mock = mocker.patch('freqtrade.optimize.edge_cli.generate_edge_table')
+
+    patch_exchange(mocker)
+    edge_conf['stake_amount'] = 20
+
+    edge_cli = EdgeCli(edge_conf)
+    edge_cli.start()
+    assert mock_calculate.call_count == 1
+    assert table_mock.call_count == 1
diff --git a/tests/optimize/test_hyperopt.py b/tests/optimize/test_hyperopt.py
new file mode 100644
index 000000000..82be894d3
--- /dev/null
+++ b/tests/optimize/test_hyperopt.py
@@ -0,0 +1,1081 @@
+# pragma pylint: disable=missing-docstring,W0212,C0103
+import locale
+import logging
+import re
+from datetime import datetime
+from pathlib import Path
+from typing import Dict, List
+from unittest.mock import MagicMock
+
+import pandas as pd
+import pytest
+from arrow import Arrow
+from filelock import Timeout
+
+from freqtrade import constants
+from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_hyperopt
+from freqtrade.data.history import load_data
+from freqtrade.exceptions import DependencyException, OperationalException
+from freqtrade.optimize.hyperopt import Hyperopt
+from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver
+from freqtrade.state import RunMode
+from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
+                            patched_configuration_load_config_file)
+
+from .hyperopts.default_hyperopt import DefaultHyperOpt
+
+
+# Functions for recurrent object patching
+def create_results(mocker, hyperopt, testdatadir) -> List[Dict]:
+    """
+    When creating results, mock the hyperopt so that *by default*
+      - we don't create any pickle'd files in the filesystem
+      - we might have a pickle'd file so make sure that we return
+        false when looking for it
+    """
+    hyperopt.results_file = testdatadir / 'optimize/ut_results.pickle'
+
+    mocker.patch.object(Path, "is_file", MagicMock(return_value=False))
+    stat_mock = MagicMock()
+    stat_mock.st_size = 1
+    mocker.patch.object(Path, "stat", MagicMock(return_value=stat_mock))
+
+    mocker.patch.object(Path, "unlink", MagicMock(return_value=True))
+    mocker.patch('freqtrade.optimize.hyperopt.dump', return_value=None)
+    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
+
+    return [{'loss': 1, 'result': 'foo', 'params': {}, 'is_best': True}]
+
+
+def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, caplog) -> None:
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = [
+        'hyperopt',
+        '--config', 'config.json',
+        '--hyperopt', 'DefaultHyperOpt',
+    ]
+
+    config = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
+    assert 'max_open_trades' in config
+    assert 'stake_currency' in config
+    assert 'stake_amount' in config
+    assert 'exchange' in config
+    assert 'pair_whitelist' in config['exchange']
+    assert 'datadir' in config
+    assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
+    assert 'timeframe' in config
+    assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog)
+
+    assert 'position_stacking' not in config
+    assert not log_has('Parameter --enable-position-stacking detected ...', caplog)
+
+    assert 'timerange' not in config
+    assert 'runmode' in config
+    assert config['runmode'] == RunMode.HYPEROPT
+
+
+def test_setup_hyperopt_configuration_with_arguments(mocker, default_conf, caplog) -> None:
+    patched_configuration_load_config_file(mocker, default_conf)
+    mocker.patch(
+        'freqtrade.configuration.configuration.create_datadir',
+        lambda c, x: x
+    )
+
+    args = [
+        'hyperopt',
+        '--config', 'config.json',
+        '--hyperopt', 'DefaultHyperOpt',
+        '--datadir', '/foo/bar',
+        '--timeframe', '1m',
+        '--timerange', ':100',
+        '--enable-position-stacking',
+        '--disable-max-market-positions',
+        '--epochs', '1000',
+        '--spaces', 'default',
+        '--print-all'
+    ]
+
+    config = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
+    assert 'max_open_trades' in config
+    assert 'stake_currency' in config
+    assert 'stake_amount' in config
+    assert 'exchange' in config
+    assert 'pair_whitelist' in config['exchange']
+    assert 'datadir' in config
+    assert config['runmode'] == RunMode.HYPEROPT
+
+    assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
+    assert 'timeframe' in config
+    assert log_has('Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
+                   caplog)
+
+    assert 'position_stacking' in config
+    assert log_has('Parameter --enable-position-stacking detected ...', caplog)
+
+    assert 'use_max_market_positions' in config
+    assert log_has('Parameter --disable-max-market-positions detected ...', caplog)
+    assert log_has('max_open_trades set to unlimited ...', caplog)
+
+    assert 'timerange' in config
+    assert log_has('Parameter --timerange detected: {} ...'.format(config['timerange']), caplog)
+
+    assert 'epochs' in config
+    assert log_has('Parameter --epochs detected ... Will run Hyperopt with for 1000 epochs ...',
+                   caplog)
+
+    assert 'spaces' in config
+    assert log_has('Parameter -s/--spaces detected: {}'.format(config['spaces']), caplog)
+    assert 'print_all' in config
+    assert log_has('Parameter --print-all detected ...', caplog)
+
+
+def test_setup_hyperopt_configuration_unlimited_stake_amount(mocker, default_conf) -> None:
+    default_conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
+
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = [
+        'hyperopt',
+        '--config', 'config.json',
+        '--hyperopt', 'DefaultHyperOpt',
+    ]
+
+    with pytest.raises(DependencyException, match=r'.`stake_amount`.*'):
+        setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
+
+
+def test_hyperoptresolver(mocker, default_conf, caplog) -> None:
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    hyperopt = DefaultHyperOpt
+    delattr(hyperopt, 'populate_indicators')
+    delattr(hyperopt, 'populate_buy_trend')
+    delattr(hyperopt, 'populate_sell_trend')
+    mocker.patch(
+        'freqtrade.resolvers.hyperopt_resolver.HyperOptResolver.load_object',
+        MagicMock(return_value=hyperopt(default_conf))
+    )
+    default_conf.update({'hyperopt': 'DefaultHyperOpt'})
+    x = HyperOptResolver.load_hyperopt(default_conf)
+    assert not hasattr(x, 'populate_indicators')
+    assert not hasattr(x, 'populate_buy_trend')
+    assert not hasattr(x, 'populate_sell_trend')
+    assert log_has("Hyperopt class does not provide populate_indicators() method. "
+                   "Using populate_indicators from the strategy.", caplog)
+    assert log_has("Hyperopt class does not provide populate_sell_trend() method. "
+                   "Using populate_sell_trend from the strategy.", caplog)
+    assert log_has("Hyperopt class does not provide populate_buy_trend() method. "
+                   "Using populate_buy_trend from the strategy.", caplog)
+    assert hasattr(x, "ticker_interval")  # DEPRECATED
+    assert hasattr(x, "timeframe")
+
+
+def test_hyperoptresolver_wrongname(default_conf) -> None:
+    default_conf.update({'hyperopt': "NonExistingHyperoptClass"})
+
+    with pytest.raises(OperationalException, match=r'Impossible to load Hyperopt.*'):
+        HyperOptResolver.load_hyperopt(default_conf)
+
+
+def test_hyperoptresolver_noname(default_conf):
+    default_conf['hyperopt'] = ''
+    with pytest.raises(OperationalException,
+                       match="No Hyperopt set. Please use `--hyperopt` to specify "
+                             "the Hyperopt class to use."):
+        HyperOptResolver.load_hyperopt(default_conf)
+
+
+def test_start_not_installed(mocker, default_conf, import_fails) -> None:
+    start_mock = MagicMock()
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
+    patch_exchange(mocker)
+
+    args = [
+        'hyperopt',
+        '--config', 'config.json',
+        '--hyperopt', 'DefaultHyperOpt',
+        '--hyperopt-path',
+        str(Path(__file__).parent / "hyperopts"),
+        '--epochs', '5',
+        '--hyperopt-loss', 'SharpeHyperOptLossDaily',
+    ]
+    pargs = get_args(args)
+
+    with pytest.raises(OperationalException, match=r"Please ensure that the hyperopt dependencies"):
+        start_hyperopt(pargs)
+
+
+def test_start(mocker, hyperopt_conf, caplog) -> None:
+    start_mock = MagicMock()
+    patched_configuration_load_config_file(mocker, hyperopt_conf)
+    mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
+    patch_exchange(mocker)
+
+    args = [
+        'hyperopt',
+        '--config', 'config.json',
+        '--hyperopt', 'DefaultHyperOpt',
+        '--hyperopt-loss', 'SharpeHyperOptLossDaily',
+        '--epochs', '5'
+    ]
+    pargs = get_args(args)
+    start_hyperopt(pargs)
+
+    assert log_has('Starting freqtrade in Hyperopt mode', caplog)
+    assert start_mock.call_count == 1
+
+
+def test_start_no_data(mocker, hyperopt_conf) -> None:
+    patched_configuration_load_config_file(mocker, hyperopt_conf)
+    mocker.patch('freqtrade.data.history.load_pair_history', MagicMock(return_value=pd.DataFrame))
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.get_timerange',
+        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
+    )
+
+    patch_exchange(mocker)
+
+    args = [
+        'hyperopt',
+        '--config', 'config.json',
+        '--hyperopt', 'DefaultHyperOpt',
+        '--hyperopt-loss', 'SharpeHyperOptLossDaily',
+        '--epochs', '5'
+    ]
+    pargs = get_args(args)
+    with pytest.raises(OperationalException, match='No data found. Terminating.'):
+        start_hyperopt(pargs)
+
+
+def test_start_filelock(mocker, hyperopt_conf, caplog) -> None:
+    start_mock = MagicMock(side_effect=Timeout(Hyperopt.get_lock_filename(hyperopt_conf)))
+    patched_configuration_load_config_file(mocker, hyperopt_conf)
+    mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
+    patch_exchange(mocker)
+
+    args = [
+        'hyperopt',
+        '--config', 'config.json',
+        '--hyperopt', 'DefaultHyperOpt',
+        '--hyperopt-loss', 'SharpeHyperOptLossDaily',
+        '--epochs', '5'
+    ]
+    pargs = get_args(args)
+    start_hyperopt(pargs)
+    assert log_has("Another running instance of freqtrade Hyperopt detected.", caplog)
+
+
+def test_log_results_if_loss_improves(hyperopt, capsys) -> None:
+    hyperopt.current_best_loss = 2
+    hyperopt.total_epochs = 2
+
+    hyperopt.print_results(
+        {
+            'loss': 1,
+            'results_metrics':
+                {
+                    'trade_count': 1,
+                    'avg_profit': 0.1,
+                    'total_profit': 0.001,
+                    'profit': 1.0,
+                    'duration': 20.0
+                },
+            'total_profit': 0,
+            'current_epoch': 2,  # This starts from 1 (in a human-friendly manner)
+            'is_initial_point': False,
+            'is_best': True
+        }
+    )
+    out, err = capsys.readouterr()
+    assert all(x in out
+               for x in ["Best", "2/2", " 1", "0.10%", "0.00100000 BTC    (1.00%)", "20.0 m"])
+
+
+def test_no_log_if_loss_does_not_improve(hyperopt, caplog) -> None:
+    hyperopt.current_best_loss = 2
+    hyperopt.print_results(
+        {
+            'is_best': False,
+            'loss': 3,
+            'current_epoch': 1,
+        }
+    )
+    assert caplog.record_tuples == []
+
+
+def test_save_results_saves_epochs(mocker, hyperopt, testdatadir, caplog) -> None:
+    epochs = create_results(mocker, hyperopt, testdatadir)
+    mock_dump = mocker.patch('freqtrade.optimize.hyperopt.dump', return_value=None)
+    mock_dump_json = mocker.patch('freqtrade.optimize.hyperopt.file_dump_json', return_value=None)
+    results_file = testdatadir / 'optimize' / 'ut_results.pickle'
+
+    caplog.set_level(logging.DEBUG)
+
+    hyperopt.epochs = epochs
+    hyperopt._save_results()
+    assert log_has(f"1 epoch saved to '{results_file}'.", caplog)
+    mock_dump.assert_called_once()
+    mock_dump_json.assert_called_once()
+
+    hyperopt.epochs = epochs + epochs
+    hyperopt._save_results()
+    assert log_has(f"2 epochs saved to '{results_file}'.", caplog)
+
+
+def test_read_results_returns_epochs(mocker, hyperopt, testdatadir, caplog) -> None:
+    epochs = create_results(mocker, hyperopt, testdatadir)
+    mock_load = mocker.patch('freqtrade.optimize.hyperopt.load', return_value=epochs)
+    results_file = testdatadir / 'optimize' / 'ut_results.pickle'
+    hyperopt_epochs = hyperopt._read_results(results_file)
+    assert log_has(f"Reading epochs from '{results_file}'", caplog)
+    assert hyperopt_epochs == epochs
+    mock_load.assert_called_once()
+
+
+def test_load_previous_results(mocker, hyperopt, testdatadir, caplog) -> None:
+    epochs = create_results(mocker, hyperopt, testdatadir)
+    mock_load = mocker.patch('freqtrade.optimize.hyperopt.load', return_value=epochs)
+    mocker.patch.object(Path, 'is_file', MagicMock(return_value=True))
+    statmock = MagicMock()
+    statmock.st_size = 5
+    # mocker.patch.object(Path, 'stat', MagicMock(return_value=statmock))
+
+    results_file = testdatadir / 'optimize' / 'ut_results.pickle'
+
+    hyperopt_epochs = hyperopt.load_previous_results(results_file)
+
+    assert hyperopt_epochs == epochs
+    mock_load.assert_called_once()
+
+    del epochs[0]['is_best']
+    mock_load = mocker.patch('freqtrade.optimize.hyperopt.load', return_value=epochs)
+
+    with pytest.raises(OperationalException):
+        hyperopt.load_previous_results(results_file)
+
+
+def test_roi_table_generation(hyperopt) -> None:
+    params = {
+        'roi_t1': 5,
+        'roi_t2': 10,
+        'roi_t3': 15,
+        'roi_p1': 1,
+        'roi_p2': 2,
+        'roi_p3': 3,
+    }
+
+    assert hyperopt.custom_hyperopt.generate_roi_table(params) == {0: 6, 15: 3, 25: 1, 30: 0}
+
+
+def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
+    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
+    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
+
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
+                 MagicMock(return_value=(MagicMock(), None)))
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.get_timerange',
+        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
+    )
+
+    parallel = mocker.patch(
+        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
+        MagicMock(return_value=[{
+            'loss': 1, 'results_explanation': 'foo result',
+            'params': {'buy': {}, 'sell': {}, 'roi': {}, 'stoploss': 0.0},
+            'results_metrics':
+            {
+                'trade_count': 1,
+                'avg_profit': 0.1,
+                'total_profit': 0.001,
+                'profit': 1.0,
+                'duration': 20.0
+            },
+        }])
+    )
+    patch_exchange(mocker)
+    # Co-test loading timeframe from strategy
+    del hyperopt_conf['timeframe']
+
+    hyperopt = Hyperopt(hyperopt_conf)
+    hyperopt.backtesting.strategy.ohlcvdata_to_dataframe = MagicMock()
+    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
+
+    hyperopt.start()
+
+    parallel.assert_called_once()
+
+    out, err = capsys.readouterr()
+    assert 'Best result:\n\n*    1/1: foo result Objective: 1.00000\n' in out
+    assert dumper.called
+    # Should be called twice, once for historical candle data, once to save evaluations
+    assert dumper.call_count == 2
+    assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
+    assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
+    assert hasattr(hyperopt, "max_open_trades")
+    assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
+    assert hasattr(hyperopt, "position_stacking")
+
+
+def test_format_results(hyperopt):
+    # Test with BTC as stake_currency
+    trades = [
+        ('ETH/BTC', 2, 2, 123),
+        ('LTC/BTC', 1, 1, 123),
+        ('XPR/BTC', -1, -2, -246)
+    ]
+    labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration']
+    df = pd.DataFrame.from_records(trades, columns=labels)
+    results_metrics = hyperopt._calculate_results_metrics(df)
+    results_explanation = hyperopt._format_results_explanation_string(results_metrics)
+    total_profit = results_metrics['total_profit']
+
+    results = {
+        'loss': 0.0,
+        'params_dict': None,
+        'params_details': None,
+        'results_metrics': results_metrics,
+        'results_explanation': results_explanation,
+        'total_profit': total_profit,
+        'current_epoch': 1,
+        'is_initial_point': True,
+    }
+
+    result = hyperopt._format_explanation_string(results, 1)
+    assert result.find(' 66.67%')
+    assert result.find('Total profit 1.00000000 BTC')
+    assert result.find('2.0000Σ %')
+
+    # Test with EUR as stake_currency
+    trades = [
+        ('ETH/EUR', 2, 2, 123),
+        ('LTC/EUR', 1, 1, 123),
+        ('XPR/EUR', -1, -2, -246)
+    ]
+    df = pd.DataFrame.from_records(trades, columns=labels)
+    results_metrics = hyperopt._calculate_results_metrics(df)
+    results['total_profit'] = results_metrics['total_profit']
+    result = hyperopt._format_explanation_string(results, 1)
+    assert result.find('Total profit 1.00000000 EUR')
+
+
+@pytest.mark.parametrize("spaces, expected_results", [
+    (['buy'],
+     {'buy': True, 'sell': False, 'roi': False, 'stoploss': False, 'trailing': False}),
+    (['sell'],
+     {'buy': False, 'sell': True, 'roi': False, 'stoploss': False, 'trailing': False}),
+    (['roi'],
+     {'buy': False, 'sell': False, 'roi': True, 'stoploss': False, 'trailing': False}),
+    (['stoploss'],
+     {'buy': False, 'sell': False, 'roi': False, 'stoploss': True, 'trailing': False}),
+    (['trailing'],
+     {'buy': False, 'sell': False, 'roi': False, 'stoploss': False, 'trailing': True}),
+    (['buy', 'sell', 'roi', 'stoploss'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
+    (['buy', 'sell', 'roi', 'stoploss', 'trailing'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
+    (['buy', 'roi'],
+     {'buy': True, 'sell': False, 'roi': True, 'stoploss': False, 'trailing': False}),
+    (['all'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
+    (['default'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
+    (['default', 'trailing'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
+    (['all', 'buy'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
+    (['default', 'buy'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
+])
+def test_has_space(hyperopt, spaces, expected_results):
+    for s in ['buy', 'sell', 'roi', 'stoploss', 'trailing']:
+        hyperopt.config.update({'spaces': spaces})
+        assert hyperopt.has_space(s) == expected_results[s]
+
+
+def test_populate_indicators(hyperopt, testdatadir) -> None:
+    data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], fill_up_missing=True)
+    dataframes = hyperopt.backtesting.strategy.ohlcvdata_to_dataframe(data)
+    dataframe = hyperopt.custom_hyperopt.populate_indicators(dataframes['UNITTEST/BTC'],
+                                                             {'pair': 'UNITTEST/BTC'})
+
+    # Check if some indicators are generated. We will not test all of them
+    assert 'adx' in dataframe
+    assert 'mfi' in dataframe
+    assert 'rsi' in dataframe
+
+
+def test_buy_strategy_generator(hyperopt, testdatadir) -> None:
+    data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], fill_up_missing=True)
+    dataframes = hyperopt.backtesting.strategy.ohlcvdata_to_dataframe(data)
+    dataframe = hyperopt.custom_hyperopt.populate_indicators(dataframes['UNITTEST/BTC'],
+                                                             {'pair': 'UNITTEST/BTC'})
+
+    populate_buy_trend = hyperopt.custom_hyperopt.buy_strategy_generator(
+        {
+            'adx-value': 20,
+            'fastd-value': 20,
+            'mfi-value': 20,
+            'rsi-value': 20,
+            'adx-enabled': True,
+            'fastd-enabled': True,
+            'mfi-enabled': True,
+            'rsi-enabled': True,
+            'trigger': 'bb_lower'
+        }
+    )
+    result = populate_buy_trend(dataframe, {'pair': 'UNITTEST/BTC'})
+    # Check if some indicators are generated. We will not test all of them
+    assert 'buy' in result
+    assert 1 in result['buy']
+
+
+def test_sell_strategy_generator(hyperopt, testdatadir) -> None:
+    data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], fill_up_missing=True)
+    dataframes = hyperopt.backtesting.strategy.ohlcvdata_to_dataframe(data)
+    dataframe = hyperopt.custom_hyperopt.populate_indicators(dataframes['UNITTEST/BTC'],
+                                                             {'pair': 'UNITTEST/BTC'})
+
+    populate_sell_trend = hyperopt.custom_hyperopt.sell_strategy_generator(
+        {
+            'sell-adx-value': 20,
+            'sell-fastd-value': 75,
+            'sell-mfi-value': 80,
+            'sell-rsi-value': 20,
+            'sell-adx-enabled': True,
+            'sell-fastd-enabled': True,
+            'sell-mfi-enabled': True,
+            'sell-rsi-enabled': True,
+            'sell-trigger': 'sell-bb_upper'
+        }
+    )
+    result = populate_sell_trend(dataframe, {'pair': 'UNITTEST/BTC'})
+    # Check if some indicators are generated. We will not test all of them
+    print(result)
+    assert 'sell' in result
+    assert 1 in result['sell']
+
+
+def test_generate_optimizer(mocker, hyperopt_conf) -> None:
+    hyperopt_conf.update({'spaces': 'all',
+                          'hyperopt_min_trades': 1,
+                          })
+
+    trades = [
+        ('TRX/BTC', 0.023117, 0.000233, 100)
+    ]
+    labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration']
+    backtest_result = pd.DataFrame.from_records(trades, columns=labels)
+
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.Backtesting.backtest',
+        MagicMock(return_value=backtest_result)
+    )
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.get_timerange',
+        MagicMock(return_value=(Arrow(2017, 12, 10), Arrow(2017, 12, 13)))
+    )
+    patch_exchange(mocker)
+    mocker.patch('freqtrade.optimize.hyperopt.load', MagicMock())
+
+    optimizer_param = {
+        'adx-value': 0,
+        'fastd-value': 35,
+        'mfi-value': 0,
+        'rsi-value': 0,
+        'adx-enabled': False,
+        'fastd-enabled': True,
+        'mfi-enabled': False,
+        'rsi-enabled': False,
+        'trigger': 'macd_cross_signal',
+        'sell-adx-value': 0,
+        'sell-fastd-value': 75,
+        'sell-mfi-value': 0,
+        'sell-rsi-value': 0,
+        'sell-adx-enabled': False,
+        'sell-fastd-enabled': True,
+        'sell-mfi-enabled': False,
+        'sell-rsi-enabled': False,
+        'sell-trigger': 'macd_cross_signal',
+        'roi_t1': 60.0,
+        'roi_t2': 30.0,
+        'roi_t3': 20.0,
+        'roi_p1': 0.01,
+        'roi_p2': 0.01,
+        'roi_p3': 0.1,
+        'stoploss': -0.4,
+        'trailing_stop': True,
+        'trailing_stop_positive': 0.02,
+        'trailing_stop_positive_offset_p1': 0.05,
+        'trailing_only_offset_is_reached': False,
+    }
+    response_expected = {
+        'loss': 1.9840569076926293,
+        'results_explanation': ('     1 trades. 1/0/0 Wins/Draws/Losses. '
+                                'Avg profit   2.31%. Median profit   2.31%. Total profit  '
+                                '0.00023300 BTC (   2.31\N{GREEK CAPITAL LETTER SIGMA}%). '
+                                'Avg duration 100.0 min.'
+                                ).encode(locale.getpreferredencoding(), 'replace').decode('utf-8'),
+        'params_details': {'buy': {'adx-enabled': False,
+                                   'adx-value': 0,
+                                   'fastd-enabled': True,
+                                   'fastd-value': 35,
+                                   'mfi-enabled': False,
+                                   'mfi-value': 0,
+                                   'rsi-enabled': False,
+                                   'rsi-value': 0,
+                                   'trigger': 'macd_cross_signal'},
+                           'roi': {0: 0.12000000000000001,
+                                   20.0: 0.02,
+                                   50.0: 0.01,
+                                   110.0: 0},
+                           'sell': {'sell-adx-enabled': False,
+                                    'sell-adx-value': 0,
+                                    'sell-fastd-enabled': True,
+                                    'sell-fastd-value': 75,
+                                    'sell-mfi-enabled': False,
+                                    'sell-mfi-value': 0,
+                                    'sell-rsi-enabled': False,
+                                    'sell-rsi-value': 0,
+                                    'sell-trigger': 'macd_cross_signal'},
+                           'stoploss': {'stoploss': -0.4},
+                           'trailing': {'trailing_only_offset_is_reached': False,
+                                        'trailing_stop': True,
+                                        'trailing_stop_positive': 0.02,
+                                        'trailing_stop_positive_offset': 0.07}},
+        'params_dict': optimizer_param,
+        'results_metrics': {'avg_profit': 2.3117,
+                            'draws': 0,
+                            'duration': 100.0,
+                            'losses': 0,
+                            'winsdrawslosses': '   1    0    0',
+                            'median_profit': 2.3117,
+                            'profit': 2.3117,
+                            'total_profit': 0.000233,
+                            'trade_count': 1,
+                            'wins': 1},
+        'total_profit': 0.00023300
+    }
+
+    hyperopt = Hyperopt(hyperopt_conf)
+    hyperopt.dimensions = hyperopt.hyperopt_space()
+    generate_optimizer_value = hyperopt.generate_optimizer(list(optimizer_param.values()))
+    assert generate_optimizer_value == response_expected
+
+
+def test_clean_hyperopt(mocker, hyperopt_conf, caplog):
+    patch_exchange(mocker)
+
+    mocker.patch("freqtrade.optimize.hyperopt.Path.is_file", MagicMock(return_value=True))
+    unlinkmock = mocker.patch("freqtrade.optimize.hyperopt.Path.unlink", MagicMock())
+    h = Hyperopt(hyperopt_conf)
+
+    assert unlinkmock.call_count == 2
+    assert log_has(f"Removing `{h.data_pickle_file}`.", caplog)
+
+
+def test_print_json_spaces_all(mocker, hyperopt_conf, capsys) -> None:
+    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
+    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
+
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
+                 MagicMock(return_value=(MagicMock(), None)))
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.get_timerange',
+        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
+    )
+
+    parallel = mocker.patch(
+        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
+        MagicMock(return_value=[{
+            'loss': 1, 'results_explanation': 'foo result', 'params': {},
+            'params_details': {
+                'buy': {'mfi-value': None},
+                'sell': {'sell-mfi-value': None},
+                'roi': {}, 'stoploss': {'stoploss': None},
+                'trailing': {'trailing_stop': None}
+            },
+            'results_metrics':
+            {
+                'trade_count': 1,
+                'avg_profit': 0.1,
+                'total_profit': 0.001,
+                'profit': 1.0,
+                'duration': 20.0
+            }
+        }])
+    )
+    patch_exchange(mocker)
+
+    hyperopt_conf.update({'spaces': 'all',
+                          'hyperopt_jobs': 1,
+                          'print_json': True,
+                          })
+
+    hyperopt = Hyperopt(hyperopt_conf)
+    hyperopt.backtesting.strategy.ohlcvdata_to_dataframe = MagicMock()
+    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
+
+    hyperopt.start()
+
+    parallel.assert_called_once()
+
+    out, err = capsys.readouterr()
+    result_str = (
+        '{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi"'
+        ':{},"stoploss":null,"trailing_stop":null}'
+    )
+    assert result_str in out  # noqa: E501
+    assert dumper.called
+    # Should be called twice, once for historical candle data, once to save evaluations
+    assert dumper.call_count == 2
+
+
+def test_print_json_spaces_default(mocker, hyperopt_conf, capsys) -> None:
+    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
+    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
+                 MagicMock(return_value=(MagicMock(), None)))
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.get_timerange',
+        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
+    )
+
+    parallel = mocker.patch(
+        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
+        MagicMock(return_value=[{
+            'loss': 1, 'results_explanation': 'foo result', 'params': {},
+            'params_details': {
+                'buy': {'mfi-value': None},
+                'sell': {'sell-mfi-value': None},
+                'roi': {}, 'stoploss': {'stoploss': None}
+            },
+            'results_metrics':
+            {
+                'trade_count': 1,
+                'avg_profit': 0.1,
+                'total_profit': 0.001,
+                'profit': 1.0,
+                'duration': 20.0
+            }
+        }])
+    )
+    patch_exchange(mocker)
+
+    hyperopt_conf.update({'print_json': True})
+
+    hyperopt = Hyperopt(hyperopt_conf)
+    hyperopt.backtesting.strategy.ohlcvdata_to_dataframe = MagicMock()
+    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
+
+    hyperopt.start()
+
+    parallel.assert_called_once()
+
+    out, err = capsys.readouterr()
+    assert '{"params":{"mfi-value":null,"sell-mfi-value":null},"minimal_roi":{},"stoploss":null}' in out  # noqa: E501
+    assert dumper.called
+    # Should be called twice, once for historical candle data, once to save evaluations
+    assert dumper.call_count == 2
+
+
+def test_print_json_spaces_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
+    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
+    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
+                 MagicMock(return_value=(MagicMock(), None)))
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.get_timerange',
+        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
+    )
+
+    parallel = mocker.patch(
+        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
+        MagicMock(return_value=[{
+            'loss': 1, 'results_explanation': 'foo result', 'params': {},
+            'params_details': {'roi': {}, 'stoploss': {'stoploss': None}},
+            'results_metrics':
+            {
+                'trade_count': 1,
+                'avg_profit': 0.1,
+                'total_profit': 0.001,
+                'profit': 1.0,
+                'duration': 20.0
+            }
+        }])
+    )
+    patch_exchange(mocker)
+
+    hyperopt_conf.update({'spaces': 'roi stoploss',
+                          'hyperopt_jobs': 1,
+                          'print_json': True,
+                          })
+
+    hyperopt = Hyperopt(hyperopt_conf)
+    hyperopt.backtesting.strategy.ohlcvdata_to_dataframe = MagicMock()
+    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
+
+    hyperopt.start()
+
+    parallel.assert_called_once()
+
+    out, err = capsys.readouterr()
+    assert '{"minimal_roi":{},"stoploss":null}' in out
+    assert dumper.called
+    # Should be called twice, once for historical candle data, once to save evaluations
+    assert dumper.call_count == 2
+
+
+def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> None:
+    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
+    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
+                 MagicMock(return_value=(MagicMock(), None)))
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.get_timerange',
+        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
+    )
+
+    parallel = mocker.patch(
+        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
+        MagicMock(return_value=[{
+            'loss': 1, 'results_explanation': 'foo result', 'params': {'stoploss': 0.0},
+            'results_metrics':
+            {
+                'trade_count': 1,
+                'avg_profit': 0.1,
+                'total_profit': 0.001,
+                'profit': 1.0,
+                'duration': 20.0
+            }
+        }])
+    )
+    patch_exchange(mocker)
+
+    hyperopt_conf.update({'spaces': 'roi stoploss'})
+
+    hyperopt = Hyperopt(hyperopt_conf)
+    hyperopt.backtesting.strategy.ohlcvdata_to_dataframe = MagicMock()
+    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
+
+    del hyperopt.custom_hyperopt.__class__.buy_strategy_generator
+    del hyperopt.custom_hyperopt.__class__.sell_strategy_generator
+    del hyperopt.custom_hyperopt.__class__.indicator_space
+    del hyperopt.custom_hyperopt.__class__.sell_indicator_space
+
+    hyperopt.start()
+
+    parallel.assert_called_once()
+
+    out, err = capsys.readouterr()
+    assert 'Best result:\n\n*    1/1: foo result Objective: 1.00000\n' in out
+    assert dumper.called
+    # Should be called twice, once for historical candle data, once to save evaluations
+    assert dumper.call_count == 2
+    assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
+    assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
+    assert hasattr(hyperopt, "max_open_trades")
+    assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
+    assert hasattr(hyperopt, "position_stacking")
+
+
+def test_simplified_interface_all_failed(mocker, hyperopt_conf) -> None:
+    mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
+    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
+                 MagicMock(return_value=(MagicMock(), None)))
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.get_timerange',
+        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
+    )
+
+    patch_exchange(mocker)
+
+    hyperopt_conf.update({'spaces': 'all', })
+
+    hyperopt = Hyperopt(hyperopt_conf)
+    hyperopt.backtesting.strategy.ohlcvdata_to_dataframe = MagicMock()
+    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
+
+    del hyperopt.custom_hyperopt.__class__.buy_strategy_generator
+    del hyperopt.custom_hyperopt.__class__.sell_strategy_generator
+    del hyperopt.custom_hyperopt.__class__.indicator_space
+    del hyperopt.custom_hyperopt.__class__.sell_indicator_space
+
+    with pytest.raises(OperationalException, match=r"The 'buy' space is included into *"):
+        hyperopt.start()
+
+
+def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
+    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
+    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
+                 MagicMock(return_value=(MagicMock(), None)))
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.get_timerange',
+        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
+    )
+
+    parallel = mocker.patch(
+        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
+        MagicMock(return_value=[{
+            'loss': 1, 'results_explanation': 'foo result', 'params': {},
+            'results_metrics':
+            {
+                'trade_count': 1,
+                'avg_profit': 0.1,
+                'total_profit': 0.001,
+                'profit': 1.0,
+                'duration': 20.0
+            }
+        }])
+    )
+    patch_exchange(mocker)
+
+    hyperopt_conf.update({'spaces': 'buy'})
+
+    hyperopt = Hyperopt(hyperopt_conf)
+    hyperopt.backtesting.strategy.ohlcvdata_to_dataframe = MagicMock()
+    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
+
+    # TODO: sell_strategy_generator() is actually not called because
+    # run_optimizer_parallel() is mocked
+    del hyperopt.custom_hyperopt.__class__.sell_strategy_generator
+    del hyperopt.custom_hyperopt.__class__.sell_indicator_space
+
+    hyperopt.start()
+
+    parallel.assert_called_once()
+
+    out, err = capsys.readouterr()
+    assert 'Best result:\n\n*    1/1: foo result Objective: 1.00000\n' in out
+    assert dumper.called
+    # Should be called twice, once for historical candle data, once to save evaluations
+    assert dumper.call_count == 2
+    assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
+    assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
+    assert hasattr(hyperopt, "max_open_trades")
+    assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
+    assert hasattr(hyperopt, "position_stacking")
+
+
+def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
+    dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
+    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
+                 MagicMock(return_value=(MagicMock(), None)))
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.get_timerange',
+        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
+    )
+
+    parallel = mocker.patch(
+        'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
+        MagicMock(return_value=[{
+            'loss': 1, 'results_explanation': 'foo result', 'params': {},
+            'results_metrics':
+            {
+                'trade_count': 1,
+                'avg_profit': 0.1,
+                'total_profit': 0.001,
+                'profit': 1.0,
+                'duration': 20.0
+            }
+        }])
+    )
+    patch_exchange(mocker)
+
+    hyperopt_conf.update({'spaces': 'sell', })
+
+    hyperopt = Hyperopt(hyperopt_conf)
+    hyperopt.backtesting.strategy.ohlcvdata_to_dataframe = MagicMock()
+    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
+
+    # TODO: buy_strategy_generator() is actually not called because
+    # run_optimizer_parallel() is mocked
+    del hyperopt.custom_hyperopt.__class__.buy_strategy_generator
+    del hyperopt.custom_hyperopt.__class__.indicator_space
+
+    hyperopt.start()
+
+    parallel.assert_called_once()
+
+    out, err = capsys.readouterr()
+    assert 'Best result:\n\n*    1/1: foo result Objective: 1.00000\n' in out
+    assert dumper.called
+    # Should be called twice, once for historical candle data, once to save evaluations
+    assert dumper.call_count == 2
+    assert hasattr(hyperopt.backtesting.strategy, "advise_sell")
+    assert hasattr(hyperopt.backtesting.strategy, "advise_buy")
+    assert hasattr(hyperopt, "max_open_trades")
+    assert hyperopt.max_open_trades == hyperopt_conf['max_open_trades']
+    assert hasattr(hyperopt, "position_stacking")
+
+
+@pytest.mark.parametrize("method,space", [
+    ('buy_strategy_generator', 'buy'),
+    ('indicator_space', 'buy'),
+    ('sell_strategy_generator', 'sell'),
+    ('sell_indicator_space', 'sell'),
+])
+def test_simplified_interface_failed(mocker, hyperopt_conf, method, space) -> None:
+    mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
+    mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
+    mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
+                 MagicMock(return_value=(MagicMock(), None)))
+    mocker.patch(
+        'freqtrade.optimize.hyperopt.get_timerange',
+        MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
+    )
+
+    patch_exchange(mocker)
+
+    hyperopt_conf.update({'spaces': space})
+
+    hyperopt = Hyperopt(hyperopt_conf)
+    hyperopt.backtesting.strategy.ohlcvdata_to_dataframe = MagicMock()
+    hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
+
+    delattr(hyperopt.custom_hyperopt.__class__, method)
+
+    with pytest.raises(OperationalException, match=f"The '{space}' space is included into *"):
+        hyperopt.start()
+
+
+def test_print_epoch_details(capsys):
+    test_result = {
+        'params_details': {
+            'trailing': {
+                'trailing_stop': True,
+                'trailing_stop_positive': 0.02,
+                'trailing_stop_positive_offset': 0.04,
+                'trailing_only_offset_is_reached': True
+            },
+            'roi': {
+                0: 0.18,
+                90: 0.14,
+                225: 0.05,
+                430: 0},
+        },
+        'results_explanation': 'foo result',
+        'is_initial_point': False,
+        'total_profit': 0,
+        'current_epoch': 2,  # This starts from 1 (in a human-friendly manner)
+        'is_best': True
+    }
+
+    Hyperopt.print_epoch_details(test_result, 5, False, no_header=True)
+    captured = capsys.readouterr()
+    assert '# Trailing stop:' in captured.out
+    # re.match(r"Pairs for .*", captured.out)
+    assert re.search(r'^\s+trailing_stop = True$', captured.out, re.MULTILINE)
+    assert re.search(r'^\s+trailing_stop_positive = 0.02$', captured.out, re.MULTILINE)
+    assert re.search(r'^\s+trailing_stop_positive_offset = 0.04$', captured.out, re.MULTILINE)
+    assert re.search(r'^\s+trailing_only_offset_is_reached = True$', captured.out, re.MULTILINE)
+
+    assert '# ROI table:' in captured.out
+    assert re.search(r'^\s+minimal_roi = \{$', captured.out, re.MULTILINE)
+    assert re.search(r'^\s+\"90\"\:\s0.14,\s*$', captured.out, re.MULTILINE)
diff --git a/tests/optimize/test_hyperoptloss.py b/tests/optimize/test_hyperoptloss.py
new file mode 100644
index 000000000..63012ee48
--- /dev/null
+++ b/tests/optimize/test_hyperoptloss.py
@@ -0,0 +1,165 @@
+from datetime import datetime
+from unittest.mock import MagicMock
+
+import pytest
+
+from freqtrade.exceptions import OperationalException
+from freqtrade.optimize.default_hyperopt_loss import ShortTradeDurHyperOptLoss
+from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver
+
+
+def test_hyperoptlossresolver_noname(default_conf):
+    with pytest.raises(OperationalException,
+                       match="No Hyperopt loss set. Please use `--hyperopt-loss` to specify "
+                             "the Hyperopt-Loss class to use."):
+        HyperOptLossResolver.load_hyperoptloss(default_conf)
+
+
+def test_hyperoptlossresolver(mocker, default_conf) -> None:
+
+    hl = ShortTradeDurHyperOptLoss
+    mocker.patch(
+        'freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver.load_object',
+        MagicMock(return_value=hl)
+    )
+    default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'})
+    x = HyperOptLossResolver.load_hyperoptloss(default_conf)
+    assert hasattr(x, "hyperopt_loss_function")
+
+
+def test_hyperoptlossresolver_wrongname(default_conf) -> None:
+    default_conf.update({'hyperopt_loss': "NonExistingLossClass"})
+
+    with pytest.raises(OperationalException, match=r'Impossible to load HyperoptLoss.*'):
+        HyperOptLossResolver.load_hyperoptloss(default_conf)
+
+
+def test_loss_calculation_prefer_correct_trade_count(hyperopt_conf, hyperopt_results) -> None:
+    hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
+    correct = hl.hyperopt_loss_function(hyperopt_results, 600,
+                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
+    over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100,
+                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
+    under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100,
+                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
+    assert over > correct
+    assert under > correct
+
+
+def test_loss_calculation_prefer_shorter_trades(hyperopt_conf, hyperopt_results) -> None:
+    resultsb = hyperopt_results.copy()
+    resultsb.loc[1, 'trade_duration'] = 20
+
+    hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
+    longer = hl.hyperopt_loss_function(hyperopt_results, 100,
+                                       datetime(2019, 1, 1), datetime(2019, 5, 1))
+    shorter = hl.hyperopt_loss_function(resultsb, 100,
+                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
+    assert shorter < longer
+
+
+def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) -> None:
+    results_over = hyperopt_results.copy()
+    results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
+    results_under = hyperopt_results.copy()
+    results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
+
+    hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
+    correct = hl.hyperopt_loss_function(hyperopt_results, 600,
+                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
+    over = hl.hyperopt_loss_function(results_over, 600,
+                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
+    under = hl.hyperopt_loss_function(results_under, 600,
+                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
+    assert over < correct
+    assert under > correct
+
+
+def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
+    results_over = hyperopt_results.copy()
+    results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
+    results_under = hyperopt_results.copy()
+    results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
+
+    default_conf.update({'hyperopt_loss': 'SharpeHyperOptLoss'})
+    hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
+    correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
+                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
+    over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
+                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
+    under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
+                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
+    assert over < correct
+    assert under > correct
+
+
+def test_sharpe_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None:
+    results_over = hyperopt_results.copy()
+    results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
+    results_under = hyperopt_results.copy()
+    results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
+
+    default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'})
+    hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
+    correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
+                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
+    over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
+                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
+    under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
+                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
+    assert over < correct
+    assert under > correct
+
+
+def test_sortino_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
+    results_over = hyperopt_results.copy()
+    results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
+    results_under = hyperopt_results.copy()
+    results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
+
+    default_conf.update({'hyperopt_loss': 'SortinoHyperOptLoss'})
+    hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
+    correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
+                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
+    over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
+                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
+    under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
+                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
+    assert over < correct
+    assert under > correct
+
+
+def test_sortino_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None:
+    results_over = hyperopt_results.copy()
+    results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
+    results_under = hyperopt_results.copy()
+    results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
+
+    default_conf.update({'hyperopt_loss': 'SortinoHyperOptLossDaily'})
+    hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
+    correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
+                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
+    over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
+                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
+    under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
+                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
+    assert over < correct
+    assert under > correct
+
+
+def test_onlyprofit_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
+    results_over = hyperopt_results.copy()
+    results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
+    results_under = hyperopt_results.copy()
+    results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
+
+    default_conf.update({'hyperopt_loss': 'OnlyProfitHyperOptLoss'})
+    hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
+    correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
+                                        datetime(2019, 1, 1), datetime(2019, 5, 1))
+    over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
+                                     datetime(2019, 1, 1), datetime(2019, 5, 1))
+    under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
+                                      datetime(2019, 1, 1), datetime(2019, 5, 1))
+    assert over < correct
+    assert under > correct
diff --git a/tests/optimize/test_optimize_reports.py b/tests/optimize/test_optimize_reports.py
new file mode 100644
index 000000000..d04929164
--- /dev/null
+++ b/tests/optimize/test_optimize_reports.py
@@ -0,0 +1,339 @@
+import re
+from datetime import timedelta
+from pathlib import Path
+
+import pandas as pd
+import pytest
+from arrow import Arrow
+
+from freqtrade.configuration import TimeRange
+from freqtrade.constants import LAST_BT_RESULT_FN
+from freqtrade.data import history
+from freqtrade.data.btanalysis import get_latest_backtest_filename, load_backtest_data
+from freqtrade.edge import PairInfo
+from freqtrade.optimize.optimize_reports import (generate_backtest_stats, generate_daily_stats,
+                                                 generate_edge_table, generate_pair_metrics,
+                                                 generate_sell_reason_stats,
+                                                 generate_strategy_metrics, store_backtest_stats,
+                                                 text_table_bt_results, text_table_sell_reason,
+                                                 text_table_strategy)
+from freqtrade.resolvers.strategy_resolver import StrategyResolver
+from freqtrade.strategy.interface import SellType
+from tests.data.test_history import _backup_file, _clean_test_file
+
+
+def test_text_table_bt_results():
+
+    results = pd.DataFrame(
+        {
+            'pair': ['ETH/BTC', 'ETH/BTC'],
+            'profit_percent': [0.1, 0.2],
+            'profit_abs': [0.2, 0.4],
+            'trade_duration': [10, 30],
+            'wins': [2, 0],
+            'draws': [0, 0],
+            'losses': [0, 0]
+        }
+    )
+
+    result_str = (
+        '|    Pair |   Buys |   Avg Profit % |   Cum Profit % |   Tot Profit BTC |'
+        '   Tot Profit % |   Avg Duration |   Wins |   Draws |   Losses |\n'
+        '|---------+--------+----------------+----------------+------------------+'
+        '----------------+----------------+--------+---------+----------|\n'
+        '| ETH/BTC |      2 |          15.00 |          30.00 |       0.60000000 |'
+        '          15.00 |        0:20:00 |      2 |       0 |        0 |\n'
+        '|   TOTAL |      2 |          15.00 |          30.00 |       0.60000000 |'
+        '          15.00 |        0:20:00 |      2 |       0 |        0 |'
+    )
+
+    pair_results = generate_pair_metrics(data={'ETH/BTC': {}}, stake_currency='BTC',
+                                         max_open_trades=2, results=results)
+    assert text_table_bt_results(pair_results, stake_currency='BTC') == result_str
+
+
+def test_generate_backtest_stats(default_conf, testdatadir):
+    default_conf.update({'strategy': 'DefaultStrategy'})
+    StrategyResolver.load_strategy(default_conf)
+
+    results = {'DefStrat': {
+        'results': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
+                                          "UNITTEST/BTC", "UNITTEST/BTC"],
+                                 "profit_percent": [0.003312, 0.010801, 0.013803, 0.002780],
+                                 "profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
+                                 "open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
+                                               Arrow(2017, 11, 14, 21, 36, 00).datetime,
+                                               Arrow(2017, 11, 14, 22, 12, 00).datetime,
+                                               Arrow(2017, 11, 14, 22, 44, 00).datetime],
+                                 "close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
+                                                Arrow(2017, 11, 14, 22, 10, 00).datetime,
+                                                Arrow(2017, 11, 14, 22, 43, 00).datetime,
+                                                Arrow(2017, 11, 14, 22, 58, 00).datetime],
+                                 "open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
+                                 "close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
+                                 "trade_duration": [123, 34, 31, 14],
+                                 "open_at_end": [False, False, False, True],
+                                 "sell_reason": [SellType.ROI, SellType.STOP_LOSS,
+                                                 SellType.ROI, SellType.FORCE_SELL]
+                                 }),
+        'config': default_conf}
+        }
+    timerange = TimeRange.parse_timerange('1510688220-1510700340')
+    min_date = Arrow.fromtimestamp(1510688220)
+    max_date = Arrow.fromtimestamp(1510700340)
+    btdata = history.load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
+                               fill_up_missing=True)
+
+    stats = generate_backtest_stats(btdata, results, min_date, max_date)
+    assert isinstance(stats, dict)
+    assert 'strategy' in stats
+    assert 'DefStrat' in stats['strategy']
+    assert 'strategy_comparison' in stats
+    strat_stats = stats['strategy']['DefStrat']
+    assert strat_stats['backtest_start'] == min_date.datetime
+    assert strat_stats['backtest_end'] == max_date.datetime
+    assert strat_stats['total_trades'] == len(results['DefStrat']['results'])
+    # Above sample had no loosing trade
+    assert strat_stats['max_drawdown'] == 0.0
+
+    results = {'DefStrat': {
+        'results': pd.DataFrame(
+            {"pair": ["UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC"],
+             "profit_percent": [0.003312, 0.010801, -0.013803, 0.002780],
+             "profit_abs": [0.000003, 0.000011, -0.000014, 0.000003],
+             "open_date": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
+                           Arrow(2017, 11, 14, 21, 36, 00).datetime,
+                           Arrow(2017, 11, 14, 22, 12, 00).datetime,
+                           Arrow(2017, 11, 14, 22, 44, 00).datetime],
+             "close_date": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
+                            Arrow(2017, 11, 14, 22, 10, 00).datetime,
+                            Arrow(2017, 11, 14, 22, 43, 00).datetime,
+                            Arrow(2017, 11, 14, 22, 58, 00).datetime],
+             "open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
+             "close_rate": [0.002546, 0.003014, 0.0032903, 0.003217],
+             "trade_duration": [123, 34, 31, 14],
+             "open_at_end": [False, False, False, True],
+             "sell_reason": [SellType.ROI, SellType.STOP_LOSS,
+                             SellType.ROI, SellType.FORCE_SELL]
+             }),
+        'config': default_conf}
+    }
+
+    assert strat_stats['max_drawdown'] == 0.0
+    assert strat_stats['drawdown_start'] == Arrow.fromtimestamp(0).datetime
+    assert strat_stats['drawdown_end'] == Arrow.fromtimestamp(0).datetime
+    assert strat_stats['drawdown_end_ts'] == 0
+    assert strat_stats['drawdown_start_ts'] == 0
+    assert strat_stats['pairlist'] == ['UNITTEST/BTC']
+
+    # Test storing stats
+    filename = Path(testdatadir / 'btresult.json')
+    filename_last = Path(testdatadir / LAST_BT_RESULT_FN)
+    _backup_file(filename_last, copy_file=True)
+    assert not filename.is_file()
+
+    store_backtest_stats(filename, stats)
+
+    # get real Filename (it's btresult-<date>.json)
+    last_fn = get_latest_backtest_filename(filename_last.parent)
+    assert re.match(r"btresult-.*\.json", last_fn)
+
+    filename1 = (testdatadir / last_fn)
+    assert filename1.is_file()
+    content = filename1.read_text()
+    assert 'max_drawdown' in content
+    assert 'strategy' in content
+    assert 'pairlist' in content
+
+    assert filename_last.is_file()
+
+    _clean_test_file(filename_last)
+    filename1.unlink()
+
+
+def test_store_backtest_stats(testdatadir, mocker):
+
+    dump_mock = mocker.patch('freqtrade.optimize.optimize_reports.file_dump_json')
+
+    store_backtest_stats(testdatadir, {})
+
+    assert dump_mock.call_count == 2
+    assert isinstance(dump_mock.call_args_list[0][0][0], Path)
+    assert str(dump_mock.call_args_list[0][0][0]).startswith(str(testdatadir/'backtest-result'))
+
+    dump_mock.reset_mock()
+    filename = testdatadir / 'testresult.json'
+    store_backtest_stats(filename, {})
+    assert dump_mock.call_count == 2
+    assert isinstance(dump_mock.call_args_list[0][0][0], Path)
+    # result will be testdatadir / testresult-<timestamp>.json
+    assert str(dump_mock.call_args_list[0][0][0]).startswith(str(testdatadir / 'testresult'))
+
+
+def test_generate_pair_metrics():
+
+    results = pd.DataFrame(
+        {
+            'pair': ['ETH/BTC', 'ETH/BTC'],
+            'profit_percent': [0.1, 0.2],
+            'profit_abs': [0.2, 0.4],
+            'trade_duration': [10, 30],
+            'wins': [2, 0],
+            'draws': [0, 0],
+            'losses': [0, 0]
+        }
+    )
+
+    pair_results = generate_pair_metrics(data={'ETH/BTC': {}}, stake_currency='BTC',
+                                         max_open_trades=2, results=results)
+    assert isinstance(pair_results, list)
+    assert len(pair_results) == 2
+    assert pair_results[-1]['key'] == 'TOTAL'
+    assert (
+        pytest.approx(pair_results[-1]['profit_mean_pct']) == pair_results[-1]['profit_mean'] * 100)
+    assert (
+        pytest.approx(pair_results[-1]['profit_sum_pct']) == pair_results[-1]['profit_sum'] * 100)
+
+
+def test_generate_daily_stats(testdatadir):
+
+    filename = testdatadir / "backtest-result_new.json"
+    bt_data = load_backtest_data(filename)
+    res = generate_daily_stats(bt_data)
+    assert isinstance(res, dict)
+    assert round(res['backtest_best_day'], 4) == 0.1796
+    assert round(res['backtest_worst_day'], 4) == -0.1468
+    assert res['winning_days'] == 14
+    assert res['draw_days'] == 4
+    assert res['losing_days'] == 3
+    assert res['winner_holding_avg'] == timedelta(seconds=1440)
+    assert res['loser_holding_avg'] == timedelta(days=1, seconds=21420)
+
+    # Select empty dataframe!
+    res = generate_daily_stats(bt_data.loc[bt_data['open_date'] == '2000-01-01', :])
+    assert isinstance(res, dict)
+    assert round(res['backtest_best_day'], 4) == 0.0
+    assert res['winning_days'] == 0
+    assert res['draw_days'] == 0
+    assert res['losing_days'] == 0
+
+
+def test_text_table_sell_reason():
+
+    results = pd.DataFrame(
+        {
+            'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
+            'profit_percent': [0.1, 0.2, -0.1],
+            'profit_abs': [0.2, 0.4, -0.2],
+            'trade_duration': [10, 30, 10],
+            'wins': [2, 0, 0],
+            'draws': [0, 0, 0],
+            'losses': [0, 0, 1],
+            'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
+        }
+    )
+
+    result_str = (
+        '|   Sell Reason |   Sells |   Wins |   Draws |   Losses |'
+        '   Avg Profit % |   Cum Profit % |   Tot Profit BTC |   Tot Profit % |\n'
+        '|---------------+---------+--------+---------+----------+'
+        '----------------+----------------+------------------+----------------|\n'
+        '|           roi |       2 |      2 |       0 |        0 |'
+        '             15 |             30 |              0.6 |             15 |\n'
+        '|     stop_loss |       1 |      0 |       0 |        1 |'
+        '            -10 |            -10 |             -0.2 |             -5 |'
+    )
+
+    sell_reason_stats = generate_sell_reason_stats(max_open_trades=2,
+                                                   results=results)
+    assert text_table_sell_reason(sell_reason_stats=sell_reason_stats,
+                                  stake_currency='BTC') == result_str
+
+
+def test_generate_sell_reason_stats():
+
+    results = pd.DataFrame(
+        {
+            'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
+            'profit_percent': [0.1, 0.2, -0.1],
+            'profit_abs': [0.2, 0.4, -0.2],
+            'trade_duration': [10, 30, 10],
+            'wins': [2, 0, 0],
+            'draws': [0, 0, 0],
+            'losses': [0, 0, 1],
+            'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
+        }
+    )
+
+    sell_reason_stats = generate_sell_reason_stats(max_open_trades=2,
+                                                   results=results)
+    roi_result = sell_reason_stats[0]
+    assert roi_result['sell_reason'] == 'roi'
+    assert roi_result['trades'] == 2
+    assert pytest.approx(roi_result['profit_mean']) == 0.15
+    assert roi_result['profit_mean_pct'] == round(roi_result['profit_mean'] * 100, 2)
+    assert pytest.approx(roi_result['profit_mean']) == 0.15
+    assert roi_result['profit_mean_pct'] == round(roi_result['profit_mean'] * 100, 2)
+
+    stop_result = sell_reason_stats[1]
+
+    assert stop_result['sell_reason'] == 'stop_loss'
+    assert stop_result['trades'] == 1
+    assert pytest.approx(stop_result['profit_mean']) == -0.1
+    assert stop_result['profit_mean_pct'] == round(stop_result['profit_mean'] * 100, 2)
+    assert pytest.approx(stop_result['profit_mean']) == -0.1
+    assert stop_result['profit_mean_pct'] == round(stop_result['profit_mean'] * 100, 2)
+
+
+def test_text_table_strategy(default_conf):
+    default_conf['max_open_trades'] = 2
+    results = {}
+    results['TestStrategy1'] = {'results': pd.DataFrame(
+        {
+            'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
+            'profit_percent': [0.1, 0.2, 0.3],
+            'profit_abs': [0.2, 0.4, 0.5],
+            'trade_duration': [10, 30, 10],
+            'wins': [2, 0, 0],
+            'draws': [0, 0, 0],
+            'losses': [0, 0, 1],
+            'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
+        }
+    ), 'config': default_conf}
+    results['TestStrategy2'] = {'results': pd.DataFrame(
+        {
+            'pair': ['LTC/BTC', 'LTC/BTC', 'LTC/BTC'],
+            'profit_percent': [0.4, 0.2, 0.3],
+            'profit_abs': [0.4, 0.4, 0.5],
+            'trade_duration': [15, 30, 15],
+            'wins': [4, 1, 0],
+            'draws': [0, 0, 0],
+            'losses': [0, 0, 1],
+            'sell_reason': [SellType.ROI, SellType.ROI, SellType.STOP_LOSS]
+        }
+    ), 'config': default_conf}
+
+    result_str = (
+        '|      Strategy |   Buys |   Avg Profit % |   Cum Profit % |   Tot'
+        ' Profit BTC |   Tot Profit % |   Avg Duration |   Wins |   Draws |   Losses |\n'
+        '|---------------+--------+----------------+----------------+------------------+'
+        '----------------+----------------+--------+---------+----------|\n'
+        '| TestStrategy1 |      3 |          20.00 |          60.00 |       1.10000000 |'
+        '          30.00 |        0:17:00 |      3 |       0 |        0 |\n'
+        '| TestStrategy2 |      3 |          30.00 |          90.00 |       1.30000000 |'
+        '          45.00 |        0:20:00 |      3 |       0 |        0 |'
+    )
+
+    strategy_results = generate_strategy_metrics(all_results=results)
+
+    assert text_table_strategy(strategy_results, 'BTC') == result_str
+
+
+def test_generate_edge_table():
+
+    results = {}
+    results['ETH/BTC'] = PairInfo(-0.01, 0.60, 2, 1, 3, 10, 60)
+    assert generate_edge_table(results).count('+') == 7
+    assert generate_edge_table(results).count('| ETH/BTC |') == 1
+    assert generate_edge_table(results).count(
+        '|   Risk Reward Ratio |   Required Risk Reward |   Expectancy |') == 1
diff --git a/user_data/hyperopts/__init__.py b/tests/pairlist/__init__.py
similarity index 100%
rename from user_data/hyperopts/__init__.py
rename to tests/pairlist/__init__.py
diff --git a/tests/pairlist/test_pairlist.py b/tests/pairlist/test_pairlist.py
new file mode 100644
index 000000000..1f05bef1e
--- /dev/null
+++ b/tests/pairlist/test_pairlist.py
@@ -0,0 +1,646 @@
+# pragma pylint: disable=missing-docstring,C0103,protected-access
+
+from unittest.mock import MagicMock, PropertyMock
+
+import pytest
+
+from freqtrade.constants import AVAILABLE_PAIRLISTS
+from freqtrade.exceptions import OperationalException
+from freqtrade.pairlist.pairlistmanager import PairListManager
+from freqtrade.resolvers import PairListResolver
+from tests.conftest import get_patched_freqtradebot, log_has, log_has_re
+
+
+@pytest.fixture(scope="function")
+def whitelist_conf(default_conf):
+    default_conf['stake_currency'] = 'BTC'
+    default_conf['exchange']['pair_whitelist'] = [
+        'ETH/BTC',
+        'TKN/BTC',
+        'TRST/BTC',
+        'SWT/BTC',
+        'BCC/BTC',
+        'HOT/BTC',
+    ]
+    default_conf['exchange']['pair_blacklist'] = [
+        'BLK/BTC'
+    ]
+    default_conf['pairlists'] = [
+        {
+            "method": "VolumePairList",
+            "number_assets": 5,
+            "sort_key": "quoteVolume",
+        },
+    ]
+    return default_conf
+
+
+@pytest.fixture(scope="function")
+def whitelist_conf_2(default_conf):
+    default_conf['stake_currency'] = 'BTC'
+    default_conf['exchange']['pair_whitelist'] = [
+        'ETH/BTC', 'TKN/BTC', 'BLK/BTC', 'LTC/BTC',
+        'BTT/BTC', 'HOT/BTC', 'FUEL/BTC', 'XRP/BTC'
+    ]
+    default_conf['exchange']['pair_blacklist'] = [
+        'BLK/BTC'
+    ]
+    default_conf['pairlists'] = [
+        # {   "method": "StaticPairList"},
+        {
+            "method": "VolumePairList",
+            "number_assets": 5,
+            "sort_key": "quoteVolume",
+            "refresh_period": 0,
+        },
+    ]
+    return default_conf
+
+
+@pytest.fixture(scope="function")
+def whitelist_conf_3(default_conf):
+    default_conf['stake_currency'] = 'BTC'
+    default_conf['exchange']['pair_whitelist'] = [
+        'ETH/BTC', 'TKN/BTC', 'BLK/BTC', 'LTC/BTC',
+        'BTT/BTC', 'HOT/BTC', 'FUEL/BTC', 'XRP/BTC'
+    ]
+    default_conf['exchange']['pair_blacklist'] = [
+        'BLK/BTC'
+    ]
+    default_conf['pairlists'] = [
+        {
+            "method": "VolumePairList",
+            "number_assets": 5,
+            "sort_key": "quoteVolume",
+            "refresh_period": 0,
+        },
+        {
+            "method": "AgeFilter",
+            "min_days_listed": 2
+        }
+    ]
+    return default_conf
+
+
+@pytest.fixture(scope="function")
+def static_pl_conf(whitelist_conf):
+    whitelist_conf['pairlists'] = [
+        {
+            "method": "StaticPairList",
+        },
+    ]
+    return whitelist_conf
+
+
+def test_log_on_refresh(mocker, static_pl_conf, markets, tickers):
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          markets=PropertyMock(return_value=markets),
+                          exchange_has=MagicMock(return_value=True),
+                          get_tickers=tickers
+                          )
+    freqtrade = get_patched_freqtradebot(mocker, static_pl_conf)
+    logmock = MagicMock()
+    # Assign starting whitelist
+    pl = freqtrade.pairlists._pairlist_handlers[0]
+    pl.log_on_refresh(logmock, 'Hello world')
+    assert logmock.call_count == 1
+    pl.log_on_refresh(logmock, 'Hello world')
+    assert logmock.call_count == 1
+    assert pl._log_cache.currsize == 1
+    assert ('Hello world',) in pl._log_cache._Cache__data
+
+    pl.log_on_refresh(logmock, 'Hello world2')
+    assert logmock.call_count == 2
+    assert pl._log_cache.currsize == 2
+
+
+def test_load_pairlist_noexist(mocker, markets, default_conf):
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
+    plm = PairListManager(freqtrade.exchange, default_conf)
+    with pytest.raises(OperationalException,
+                       match=r"Impossible to load Pairlist 'NonexistingPairList'. "
+                             r"This class does not exist or contains Python code errors."):
+        PairListResolver.load_pairlist('NonexistingPairList', freqtrade.exchange, plm,
+                                       default_conf, {}, 1)
+
+
+def test_refresh_market_pair_not_in_whitelist(mocker, markets, static_pl_conf):
+
+    freqtrade = get_patched_freqtradebot(mocker, static_pl_conf)
+
+    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
+    freqtrade.pairlists.refresh_pairlist()
+    # List ordered by BaseVolume
+    whitelist = ['ETH/BTC', 'TKN/BTC']
+    # Ensure all except those in whitelist are removed
+    assert set(whitelist) == set(freqtrade.pairlists.whitelist)
+    # Ensure config dict hasn't been changed
+    assert (static_pl_conf['exchange']['pair_whitelist'] ==
+            freqtrade.config['exchange']['pair_whitelist'])
+
+
+def test_refresh_static_pairlist(mocker, markets, static_pl_conf):
+    freqtrade = get_patched_freqtradebot(mocker, static_pl_conf)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        exchange_has=MagicMock(return_value=True),
+        markets=PropertyMock(return_value=markets),
+    )
+    freqtrade.pairlists.refresh_pairlist()
+    # List ordered by BaseVolume
+    whitelist = ['ETH/BTC', 'TKN/BTC']
+    # Ensure all except those in whitelist are removed
+    assert set(whitelist) == set(freqtrade.pairlists.whitelist)
+    assert static_pl_conf['exchange']['pair_blacklist'] == freqtrade.pairlists.blacklist
+
+
+def test_refresh_pairlist_dynamic(mocker, shitcoinmarkets, tickers, whitelist_conf):
+
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_tickers=tickers,
+        exchange_has=MagicMock(return_value=True),
+    )
+    freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
+    # Remock markets with shitcoinmarkets since get_patched_freqtradebot uses the markets fixture
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        markets=PropertyMock(return_value=shitcoinmarkets),
+    )
+    # argument: use the whitelist dynamically by exchange-volume
+    whitelist = ['ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'XRP/BTC', 'HOT/BTC']
+    freqtrade.pairlists.refresh_pairlist()
+    assert whitelist == freqtrade.pairlists.whitelist
+
+    whitelist_conf['pairlists'] = [{'method': 'VolumePairList'}]
+    with pytest.raises(OperationalException,
+                       match=r'`number_assets` not specified. Please check your configuration '
+                             r'for "pairlist.config.number_assets"'):
+        PairListManager(freqtrade.exchange, whitelist_conf)
+
+
+def test_refresh_pairlist_dynamic_2(mocker, shitcoinmarkets, tickers, whitelist_conf_2):
+
+    tickers_dict = tickers()
+
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        exchange_has=MagicMock(return_value=True),
+    )
+    # Remove caching of ticker data to emulate changing volume by the time of second call
+    mocker.patch.multiple(
+        'freqtrade.pairlist.pairlistmanager.PairListManager',
+        _get_cached_tickers=MagicMock(return_value=tickers_dict),
+    )
+    freqtrade = get_patched_freqtradebot(mocker, whitelist_conf_2)
+    # Remock markets with shitcoinmarkets since get_patched_freqtradebot uses the markets fixture
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        markets=PropertyMock(return_value=shitcoinmarkets),
+    )
+
+    whitelist = ['ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'XRP/BTC', 'HOT/BTC']
+    freqtrade.pairlists.refresh_pairlist()
+    assert whitelist == freqtrade.pairlists.whitelist
+
+    whitelist = ['FUEL/BTC', 'ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'XRP/BTC']
+    tickers_dict['FUEL/BTC']['quoteVolume'] = 10000.0
+    freqtrade.pairlists.refresh_pairlist()
+    assert whitelist == freqtrade.pairlists.whitelist
+
+
+def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf):
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        exchange_has=MagicMock(return_value=True),
+    )
+    freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
+    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets_empty))
+
+    # argument: use the whitelist dynamically by exchange-volume
+    whitelist = []
+    whitelist_conf['exchange']['pair_whitelist'] = []
+    freqtrade.pairlists.refresh_pairlist()
+    pairslist = whitelist_conf['exchange']['pair_whitelist']
+
+    assert set(whitelist) == set(pairslist)
+
+
+@pytest.mark.parametrize("pairlists,base_currency,whitelist_result", [
+    # VolumePairList only
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"}],
+     "BTC", ['ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'XRP/BTC', 'HOT/BTC']),
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"}],
+     "USDT", ['ETH/USDT', 'NANO/USDT', 'ADAHALF/USDT', 'ADADOUBLE/USDT']),
+    # No pair for ETH, VolumePairList
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"}],
+     "ETH", []),
+    # No pair for ETH, StaticPairList
+    ([{"method": "StaticPairList"}],
+     "ETH", []),
+    # No pair for ETH, all handlers
+    ([{"method": "StaticPairList"},
+      {"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
+      {"method": "AgeFilter", "min_days_listed": 2},
+      {"method": "PrecisionFilter"},
+      {"method": "PriceFilter", "low_price_ratio": 0.03},
+      {"method": "SpreadFilter", "max_spread_ratio": 0.005},
+      {"method": "ShuffleFilter"}],
+     "ETH", []),
+    # AgeFilter and VolumePairList (require 2 days only, all should pass age test)
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
+      {"method": "AgeFilter", "min_days_listed": 2}],
+     "BTC", ['ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'XRP/BTC', 'HOT/BTC']),
+    # AgeFilter and VolumePairList (require 10 days, all should fail age test)
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
+      {"method": "AgeFilter", "min_days_listed": 10}],
+     "BTC", []),
+    # Precisionfilter and quote volume
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
+      {"method": "PrecisionFilter"}],
+     "BTC", ['ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'XRP/BTC']),
+    # PriceFilter and VolumePairList
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
+      {"method": "PriceFilter", "low_price_ratio": 0.03}],
+     "BTC", ['ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'XRP/BTC']),
+    # PriceFilter and VolumePairList
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
+      {"method": "PriceFilter", "low_price_ratio": 0.03}],
+     "USDT", ['ETH/USDT', 'NANO/USDT']),
+    # Hot is removed by precision_filter, Fuel by low_price_ratio, Ripple by min_price.
+    ([{"method": "VolumePairList", "number_assets": 6, "sort_key": "quoteVolume"},
+      {"method": "PrecisionFilter"},
+      {"method": "PriceFilter", "low_price_ratio": 0.02, "min_price": 0.01}],
+     "BTC", ['ETH/BTC', 'TKN/BTC', 'LTC/BTC']),
+    # Hot is removed by precision_filter, Fuel by low_price_ratio, Ethereum by max_price.
+    ([{"method": "VolumePairList", "number_assets": 6, "sort_key": "quoteVolume"},
+      {"method": "PrecisionFilter"},
+      {"method": "PriceFilter", "low_price_ratio": 0.02, "max_price": 0.05}],
+     "BTC", ['TKN/BTC', 'LTC/BTC', 'XRP/BTC']),
+    # HOT and XRP are removed because below 1250 quoteVolume
+    ([{"method": "VolumePairList", "number_assets": 5,
+       "sort_key": "quoteVolume", "min_value": 1250}],
+     "BTC", ['ETH/BTC', 'TKN/BTC', 'LTC/BTC']),
+    # StaticPairlist only
+    ([{"method": "StaticPairList"}],
+     "BTC", ['ETH/BTC', 'TKN/BTC', 'HOT/BTC']),
+    # Static Pairlist before VolumePairList - sorting changes
+    # SpreadFilter
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
+      {"method": "SpreadFilter", "max_spread_ratio": 0.005}],
+     "USDT", ['ETH/USDT']),
+    # ShuffleFilter
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
+      {"method": "ShuffleFilter", "seed": 77}],
+     "USDT", ['ADADOUBLE/USDT', 'ETH/USDT', 'NANO/USDT', 'ADAHALF/USDT']),
+    # ShuffleFilter, other seed
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
+      {"method": "ShuffleFilter", "seed": 42}],
+     "USDT", ['ADAHALF/USDT', 'NANO/USDT', 'ADADOUBLE/USDT', 'ETH/USDT']),
+    # ShuffleFilter, no seed
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
+      {"method": "ShuffleFilter"}],
+     "USDT", 3),  # whitelist_result is integer -- check only length of randomized pairlist
+    # AgeFilter only
+    ([{"method": "AgeFilter", "min_days_listed": 2}],
+     "BTC", 'filter_at_the_beginning'),  # OperationalException expected
+    # PrecisionFilter after StaticPairList
+    ([{"method": "StaticPairList"},
+      {"method": "PrecisionFilter"}],
+     "BTC", ['ETH/BTC', 'TKN/BTC']),
+    # PrecisionFilter only
+    ([{"method": "PrecisionFilter"}],
+     "BTC", 'filter_at_the_beginning'),  # OperationalException expected
+    # PriceFilter after StaticPairList
+    ([{"method": "StaticPairList"},
+      {"method": "PriceFilter", "low_price_ratio": 0.02, "min_price": 0.000001, "max_price": 0.1}],
+     "BTC", ['ETH/BTC', 'TKN/BTC']),
+    # PriceFilter only
+    ([{"method": "PriceFilter", "low_price_ratio": 0.02}],
+     "BTC", 'filter_at_the_beginning'),  # OperationalException expected
+    # ShuffleFilter after StaticPairList
+    ([{"method": "StaticPairList"},
+      {"method": "ShuffleFilter", "seed": 42}],
+     "BTC", ['TKN/BTC', 'ETH/BTC', 'HOT/BTC']),
+    # ShuffleFilter only
+    ([{"method": "ShuffleFilter", "seed": 42}],
+     "BTC", 'filter_at_the_beginning'),  # OperationalException expected
+    # SpreadFilter after StaticPairList
+    ([{"method": "StaticPairList"},
+      {"method": "SpreadFilter", "max_spread_ratio": 0.005}],
+     "BTC", ['ETH/BTC', 'TKN/BTC']),
+    # SpreadFilter only
+    ([{"method": "SpreadFilter", "max_spread_ratio": 0.005}],
+     "BTC", 'filter_at_the_beginning'),  # OperationalException expected
+    # Static Pairlist after VolumePairList, on a non-first position
+    ([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
+      {"method": "StaticPairList"}],
+        "BTC", 'static_in_the_middle'),
+    ([{"method": "VolumePairList", "number_assets": 20, "sort_key": "quoteVolume"},
+      {"method": "PriceFilter", "low_price_ratio": 0.02}],
+        "USDT", ['ETH/USDT', 'NANO/USDT']),
+])
+def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, tickers,
+                                      ohlcv_history_list, pairlists, base_currency,
+                                      whitelist_result, caplog) -> None:
+    whitelist_conf['pairlists'] = pairlists
+    whitelist_conf['stake_currency'] = base_currency
+
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
+
+    if whitelist_result == 'static_in_the_middle':
+        with pytest.raises(OperationalException,
+                           match=r"StaticPairList can only be used in the first position "
+                                 r"in the list of Pairlist Handlers."):
+            freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
+        return
+
+    freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          get_tickers=tickers,
+                          markets=PropertyMock(return_value=shitcoinmarkets)
+                          )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_historic_ohlcv=MagicMock(return_value=ohlcv_history_list),
+    )
+
+    # Set whitelist_result to None if pairlist is invalid and should produce exception
+    if whitelist_result == 'filter_at_the_beginning':
+        with pytest.raises(OperationalException,
+                           match=r"This Pairlist Handler should not be used at the first position "
+                                 r"in the list of Pairlist Handlers."):
+            freqtrade.pairlists.refresh_pairlist()
+    else:
+        freqtrade.pairlists.refresh_pairlist()
+        whitelist = freqtrade.pairlists.whitelist
+
+        assert isinstance(whitelist, list)
+
+        # Verify length of pairlist matches (used for ShuffleFilter without seed)
+        if type(whitelist_result) is list:
+            assert whitelist == whitelist_result
+        else:
+            len(whitelist) == whitelist_result
+
+        for pairlist in pairlists:
+            if pairlist['method'] == 'AgeFilter' and pairlist['min_days_listed'] and \
+                    len(ohlcv_history_list) <= pairlist['min_days_listed']:
+                assert log_has_re(r'^Removed .* from whitelist, because age .* is less than '
+                                  r'.* day.*', caplog)
+            if pairlist['method'] == 'PrecisionFilter' and whitelist_result:
+                assert log_has_re(r'^Removed .* from whitelist, because stop price .* '
+                                  r'would be <= stop limit.*', caplog)
+            if pairlist['method'] == 'PriceFilter' and whitelist_result:
+                assert (log_has_re(r'^Removed .* from whitelist, because 1 unit is .*%$', caplog) or
+                        log_has_re(r'^Removed .* from whitelist, '
+                                   r'because last price < .*%$', caplog) or
+                        log_has_re(r'^Removed .* from whitelist, '
+                                   r'because last price > .*%$', caplog) or
+                        log_has_re(r"^Removed .* from whitelist, because ticker\['last'\] "
+                                   r"is empty.*", caplog))
+            if pairlist['method'] == 'VolumePairList':
+                logmsg = ("DEPRECATED: using any key other than quoteVolume for "
+                          "VolumePairList is deprecated.")
+                if pairlist['sort_key'] != 'quoteVolume':
+                    assert log_has(logmsg, caplog)
+                else:
+                    assert not log_has(logmsg, caplog)
+
+
+def test_PrecisionFilter_error(mocker, whitelist_conf, tickers) -> None:
+    whitelist_conf['pairlists'] = [{"method": "StaticPairList"}, {"method": "PrecisionFilter"}]
+    del whitelist_conf['stoploss']
+
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
+
+    with pytest.raises(OperationalException,
+                       match=r"PrecisionFilter can only work with stoploss defined\..*"):
+        PairListManager(MagicMock, whitelist_conf)
+
+
+def test_gen_pair_whitelist_not_supported(mocker, default_conf, tickers) -> None:
+    default_conf['pairlists'] = [{'method': 'VolumePairList', 'number_assets': 10}]
+
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          get_tickers=tickers,
+                          exchange_has=MagicMock(return_value=False),
+                          )
+
+    with pytest.raises(OperationalException,
+                       match=r'Exchange does not support dynamic whitelist.*'):
+        get_patched_freqtradebot(mocker, default_conf)
+
+
+@pytest.mark.parametrize("pairlist", AVAILABLE_PAIRLISTS)
+def test_pairlist_class(mocker, whitelist_conf, markets, pairlist):
+    whitelist_conf['pairlists'][0]['method'] = pairlist
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          markets=PropertyMock(return_value=markets),
+                          exchange_has=MagicMock(return_value=True)
+                          )
+    freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
+
+    assert freqtrade.pairlists.name_list == [pairlist]
+    assert pairlist in str(freqtrade.pairlists.short_desc())
+    assert isinstance(freqtrade.pairlists.whitelist, list)
+    assert isinstance(freqtrade.pairlists.blacklist, list)
+
+
+@pytest.mark.parametrize("pairlist", AVAILABLE_PAIRLISTS)
+@pytest.mark.parametrize("whitelist,log_message", [
+    (['ETH/BTC', 'TKN/BTC'], ""),
+    # TRX/ETH not in markets
+    (['ETH/BTC', 'TKN/BTC', 'TRX/ETH'], "is not compatible with exchange"),
+    # wrong stake
+    (['ETH/BTC', 'TKN/BTC', 'ETH/USDT'], "is not compatible with your stake currency"),
+    # BCH/BTC not available
+    (['ETH/BTC', 'TKN/BTC', 'BCH/BTC'], "is not compatible with exchange"),
+    # BTT/BTC is inactive
+    (['ETH/BTC', 'TKN/BTC', 'BTT/BTC'], "Market is not active"),
+    # XLTCUSDT is not a valid pair
+    (['ETH/BTC', 'TKN/BTC', 'XLTCUSDT'], "is not tradable with Freqtrade"),
+])
+def test__whitelist_for_active_markets(mocker, whitelist_conf, markets, pairlist, whitelist, caplog,
+                                       log_message, tickers):
+    whitelist_conf['pairlists'][0]['method'] = pairlist
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          markets=PropertyMock(return_value=markets),
+                          exchange_has=MagicMock(return_value=True),
+                          get_tickers=tickers
+                          )
+    freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
+    caplog.clear()
+
+    # Assign starting whitelist
+    pairlist_handler = freqtrade.pairlists._pairlist_handlers[0]
+    new_whitelist = pairlist_handler._whitelist_for_active_markets(whitelist)
+
+    assert set(new_whitelist) == set(['ETH/BTC', 'TKN/BTC'])
+    assert log_message in caplog.text
+
+
+@pytest.mark.parametrize("pairlist", AVAILABLE_PAIRLISTS)
+def test__whitelist_for_active_markets_empty(mocker, whitelist_conf, markets, pairlist, tickers):
+    whitelist_conf['pairlists'][0]['method'] = pairlist
+
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
+
+    freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          markets=PropertyMock(return_value=None),
+                          get_tickers=tickers
+                          )
+    # Assign starting whitelist
+    pairlist_handler = freqtrade.pairlists._pairlist_handlers[0]
+    with pytest.raises(OperationalException, match=r'Markets not loaded.*'):
+        pairlist_handler._whitelist_for_active_markets(['ETH/BTC'])
+
+
+def test_volumepairlist_invalid_sortvalue(mocker, markets, whitelist_conf):
+    whitelist_conf['pairlists'][0].update({"sort_key": "asdf"})
+
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
+    with pytest.raises(OperationalException,
+                       match=r"key asdf not in .*"):
+        get_patched_freqtradebot(mocker, whitelist_conf)
+
+
+def test_volumepairlist_caching(mocker, markets, whitelist_conf, tickers):
+
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          markets=PropertyMock(return_value=markets),
+                          exchange_has=MagicMock(return_value=True),
+                          get_tickers=tickers
+                          )
+    freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
+    assert freqtrade.pairlists._pairlist_handlers[0]._last_refresh == 0
+    assert tickers.call_count == 0
+    freqtrade.pairlists.refresh_pairlist()
+    assert tickers.call_count == 1
+
+    assert freqtrade.pairlists._pairlist_handlers[0]._last_refresh != 0
+    lrf = freqtrade.pairlists._pairlist_handlers[0]._last_refresh
+    freqtrade.pairlists.refresh_pairlist()
+    assert tickers.call_count == 1
+    # Time should not be updated.
+    assert freqtrade.pairlists._pairlist_handlers[0]._last_refresh == lrf
+
+
+def test_agefilter_min_days_listed_too_small(mocker, default_conf, markets, tickers, caplog):
+    default_conf['pairlists'] = [{'method': 'VolumePairList', 'number_assets': 10},
+                                 {'method': 'AgeFilter', 'min_days_listed': -1}]
+
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          markets=PropertyMock(return_value=markets),
+                          exchange_has=MagicMock(return_value=True),
+                          get_tickers=tickers
+                          )
+
+    with pytest.raises(OperationalException,
+                       match=r'AgeFilter requires min_days_listed to be >= 1'):
+        get_patched_freqtradebot(mocker, default_conf)
+
+
+def test_agefilter_min_days_listed_too_large(mocker, default_conf, markets, tickers, caplog):
+    default_conf['pairlists'] = [{'method': 'VolumePairList', 'number_assets': 10},
+                                 {'method': 'AgeFilter', 'min_days_listed': 99999}]
+
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          markets=PropertyMock(return_value=markets),
+                          exchange_has=MagicMock(return_value=True),
+                          get_tickers=tickers
+                          )
+
+    with pytest.raises(OperationalException,
+                       match=r'AgeFilter requires min_days_listed to not exceed '
+                             r'exchange max request size \([0-9]+\)'):
+        get_patched_freqtradebot(mocker, default_conf)
+
+
+def test_agefilter_caching(mocker, markets, whitelist_conf_3, tickers, ohlcv_history_list):
+
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          markets=PropertyMock(return_value=markets),
+                          exchange_has=MagicMock(return_value=True),
+                          get_tickers=tickers
+                          )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_historic_ohlcv=MagicMock(return_value=ohlcv_history_list),
+    )
+
+    freqtrade = get_patched_freqtradebot(mocker, whitelist_conf_3)
+    assert freqtrade.exchange.get_historic_ohlcv.call_count == 0
+    freqtrade.pairlists.refresh_pairlist()
+    assert freqtrade.exchange.get_historic_ohlcv.call_count > 0
+
+    previous_call_count = freqtrade.exchange.get_historic_ohlcv.call_count
+    freqtrade.pairlists.refresh_pairlist()
+    # Should not have increased since first call.
+    assert freqtrade.exchange.get_historic_ohlcv.call_count == previous_call_count
+
+
+@pytest.mark.parametrize("pairlistconfig,desc_expected,exception_expected", [
+    ({"method": "PriceFilter", "low_price_ratio": 0.001, "min_price": 0.00000010,
+      "max_price": 1.0},
+     "[{'PriceFilter': 'PriceFilter - Filtering pairs priced below "
+     "0.1% or below 0.00000010 or above 1.00000000.'}]",
+     None
+     ),
+    ({"method": "PriceFilter", "low_price_ratio": 0.001, "min_price": 0.00000010},
+     "[{'PriceFilter': 'PriceFilter - Filtering pairs priced below 0.1% or below 0.00000010.'}]",
+     None
+     ),
+    ({"method": "PriceFilter", "low_price_ratio": 0.001, "max_price": 1.00010000},
+     "[{'PriceFilter': 'PriceFilter - Filtering pairs priced below 0.1% or above 1.00010000.'}]",
+     None
+     ),
+    ({"method": "PriceFilter", "min_price": 0.00002000},
+     "[{'PriceFilter': 'PriceFilter - Filtering pairs priced below 0.00002000.'}]",
+     None
+     ),
+    ({"method": "PriceFilter"},
+     "[{'PriceFilter': 'PriceFilter - No price filters configured.'}]",
+     None
+     ),
+    ({"method": "PriceFilter", "low_price_ratio": -0.001},
+     None,
+     "PriceFilter requires low_price_ratio to be >= 0"
+     ),  # OperationalException expected
+    ({"method": "PriceFilter", "min_price": -0.00000010},
+     None,
+     "PriceFilter requires min_price to be >= 0"
+     ),  # OperationalException expected
+    ({"method": "PriceFilter", "max_price": -1.00010000},
+     None,
+     "PriceFilter requires max_price to be >= 0"
+     ),  # OperationalException expected
+])
+def test_pricefilter_desc(mocker, whitelist_conf, markets, pairlistconfig,
+                          desc_expected, exception_expected):
+    mocker.patch.multiple('freqtrade.exchange.Exchange',
+                          markets=PropertyMock(return_value=markets),
+                          exchange_has=MagicMock(return_value=True)
+                          )
+    whitelist_conf['pairlists'] = [pairlistconfig]
+
+    if desc_expected is not None:
+        freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
+        short_desc = str(freqtrade.pairlists.short_desc())
+        assert short_desc == desc_expected
+    else:  # OperationalException expected
+        with pytest.raises(OperationalException,
+                           match=exception_expected):
+            freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
+
+
+def test_pairlistmanager_no_pairlist(mocker, markets, whitelist_conf, caplog):
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
+
+    whitelist_conf['pairlists'] = []
+
+    with pytest.raises(OperationalException,
+                       match=r"No Pairlist Handlers defined"):
+        get_patched_freqtradebot(mocker, whitelist_conf)
diff --git a/tests/pairlist/test_pairlocks.py b/tests/pairlist/test_pairlocks.py
new file mode 100644
index 000000000..0b6b89717
--- /dev/null
+++ b/tests/pairlist/test_pairlocks.py
@@ -0,0 +1,82 @@
+from datetime import datetime, timedelta, timezone
+
+import arrow
+import pytest
+
+from freqtrade.persistence import PairLocks
+from freqtrade.persistence.models import PairLock
+
+
+@pytest.mark.parametrize('use_db', (False, True))
+@pytest.mark.usefixtures("init_persistence")
+def test_PairLocks(use_db):
+    PairLocks.timeframe = '5m'
+    # No lock should be present
+    if use_db:
+        assert len(PairLock.query.all()) == 0
+    else:
+        PairLocks.use_db = False
+
+    assert PairLocks.use_db == use_db
+
+    pair = 'ETH/BTC'
+    assert not PairLocks.is_pair_locked(pair)
+    PairLocks.lock_pair(pair, arrow.utcnow().shift(minutes=4).datetime)
+    # ETH/BTC locked for 4 minutes
+    assert PairLocks.is_pair_locked(pair)
+
+    # XRP/BTC should not be locked now
+    pair = 'XRP/BTC'
+    assert not PairLocks.is_pair_locked(pair)
+    # Unlocking a pair that's not locked should not raise an error
+    PairLocks.unlock_pair(pair)
+
+    PairLocks.lock_pair(pair, arrow.utcnow().shift(minutes=4).datetime)
+    assert PairLocks.is_pair_locked(pair)
+
+    # Get both locks from above
+    locks = PairLocks.get_pair_locks(None)
+    assert len(locks) == 2
+
+    # Unlock original pair
+    pair = 'ETH/BTC'
+    PairLocks.unlock_pair(pair)
+    assert not PairLocks.is_pair_locked(pair)
+    assert not PairLocks.is_global_lock()
+
+    pair = 'BTC/USDT'
+    # Lock until 14:30
+    lock_time = datetime(2020, 5, 1, 14, 30, 0, tzinfo=timezone.utc)
+    PairLocks.lock_pair(pair, lock_time)
+
+    assert not PairLocks.is_pair_locked(pair)
+    assert PairLocks.is_pair_locked(pair, lock_time + timedelta(minutes=-10))
+    assert not PairLocks.is_global_lock(lock_time + timedelta(minutes=-10))
+    assert PairLocks.is_pair_locked(pair, lock_time + timedelta(minutes=-50))
+    assert not PairLocks.is_global_lock(lock_time + timedelta(minutes=-50))
+
+    # Should not be locked after time expired
+    assert not PairLocks.is_pair_locked(pair, lock_time + timedelta(minutes=10))
+
+    locks = PairLocks.get_pair_locks(pair, lock_time + timedelta(minutes=-2))
+    assert len(locks) == 1
+    assert 'PairLock' in str(locks[0])
+
+    # Unlock all
+    PairLocks.unlock_pair(pair, lock_time + timedelta(minutes=-2))
+    assert not PairLocks.is_global_lock(lock_time + timedelta(minutes=-50))
+
+    # Global lock
+    PairLocks.lock_pair('*', lock_time)
+    assert PairLocks.is_global_lock(lock_time + timedelta(minutes=-50))
+    # Global lock also locks every pair seperately
+    assert PairLocks.is_pair_locked(pair, lock_time + timedelta(minutes=-50))
+    assert PairLocks.is_pair_locked('XRP/USDT', lock_time + timedelta(minutes=-50))
+
+    if use_db:
+        assert len(PairLock.query.all()) > 0
+    else:
+        # Nothing was pushed to the database
+        assert len(PairLock.query.all()) == 0
+    # Reset use-db variable
+    PairLocks.use_db = True
diff --git a/tests/pytest.sh b/tests/pytest.sh
new file mode 100755
index 000000000..d2ad223e7
--- /dev/null
+++ b/tests/pytest.sh
@@ -0,0 +1,5 @@
+#!/bin/bash
+
+echo "Running Unit tests"
+
+pytest --random-order --cov=freqtrade --cov-config=.coveragerc tests/
diff --git a/user_data/strategies/__init__.py b/tests/rpc/__init__.py
similarity index 100%
rename from user_data/strategies/__init__.py
rename to tests/rpc/__init__.py
diff --git a/freqtrade/tests/rpc/test_fiat_convert.py b/tests/rpc/test_fiat_convert.py
similarity index 78%
rename from freqtrade/tests/rpc/test_fiat_convert.py
rename to tests/rpc/test_fiat_convert.py
index 66870efcc..ed21bc516 100644
--- a/freqtrade/tests/rpc/test_fiat_convert.py
+++ b/tests/rpc/test_fiat_convert.py
@@ -8,7 +8,7 @@ import pytest
 from requests.exceptions import RequestException
 
 from freqtrade.rpc.fiat_convert import CryptoFiat, CryptoToFiatConverter
-from freqtrade.tests.conftest import log_has
+from tests.conftest import log_has, log_has_re
 
 
 def test_pair_convertion_object():
@@ -22,8 +22,8 @@ def test_pair_convertion_object():
     assert pair_convertion.CACHE_DURATION == 6 * 60 * 60
 
     # Check a regular usage
-    assert pair_convertion.crypto_symbol == 'BTC'
-    assert pair_convertion.fiat_symbol == 'USD'
+    assert pair_convertion.crypto_symbol == 'btc'
+    assert pair_convertion.fiat_symbol == 'usd'
     assert pair_convertion.price == 12345.0
     assert pair_convertion.is_expired() is False
 
@@ -57,15 +57,15 @@ def test_fiat_convert_add_pair(mocker):
     fiat_convert._add_pair(crypto_symbol='btc', fiat_symbol='usd', price=12345.0)
     pair_len = len(fiat_convert._pairs)
     assert pair_len == 1
-    assert fiat_convert._pairs[0].crypto_symbol == 'BTC'
-    assert fiat_convert._pairs[0].fiat_symbol == 'USD'
+    assert fiat_convert._pairs[0].crypto_symbol == 'btc'
+    assert fiat_convert._pairs[0].fiat_symbol == 'usd'
     assert fiat_convert._pairs[0].price == 12345.0
 
     fiat_convert._add_pair(crypto_symbol='btc', fiat_symbol='Eur', price=13000.2)
     pair_len = len(fiat_convert._pairs)
     assert pair_len == 2
-    assert fiat_convert._pairs[1].crypto_symbol == 'BTC'
-    assert fiat_convert._pairs[1].fiat_symbol == 'EUR'
+    assert fiat_convert._pairs[1].crypto_symbol == 'btc'
+    assert fiat_convert._pairs[1].fiat_symbol == 'eur'
     assert fiat_convert._pairs[1].price == 13000.2
 
 
@@ -91,7 +91,7 @@ def test_fiat_convert_unsupported_crypto(mocker, caplog):
     mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._cryptomap', return_value=[])
     fiat_convert = CryptoToFiatConverter()
     assert fiat_convert._find_price(crypto_symbol='CRYPTO_123', fiat_symbol='EUR') == 0.0
-    assert log_has('unsupported crypto-symbol CRYPTO_123 - returning 0.0', caplog.record_tuples)
+    assert log_has('unsupported crypto-symbol CRYPTO_123 - returning 0.0', caplog)
 
 
 def test_fiat_convert_get_price(mocker):
@@ -100,15 +100,15 @@ def test_fiat_convert_get_price(mocker):
 
     fiat_convert = CryptoToFiatConverter()
 
-    with pytest.raises(ValueError, match=r'The fiat US DOLLAR is not supported.'):
-        fiat_convert.get_price(crypto_symbol='BTC', fiat_symbol='US Dollar')
+    with pytest.raises(ValueError, match=r'The fiat us dollar is not supported.'):
+        fiat_convert.get_price(crypto_symbol='btc', fiat_symbol='US Dollar')
 
     # Check the value return by the method
     pair_len = len(fiat_convert._pairs)
     assert pair_len == 0
-    assert fiat_convert.get_price(crypto_symbol='BTC', fiat_symbol='USD') == 28000.0
-    assert fiat_convert._pairs[0].crypto_symbol == 'BTC'
-    assert fiat_convert._pairs[0].fiat_symbol == 'USD'
+    assert fiat_convert.get_price(crypto_symbol='btc', fiat_symbol='usd') == 28000.0
+    assert fiat_convert._pairs[0].crypto_symbol == 'btc'
+    assert fiat_convert._pairs[0].fiat_symbol == 'usd'
     assert fiat_convert._pairs[0].price == 28000.0
     assert fiat_convert._pairs[0]._expiration != 0
     assert len(fiat_convert._pairs) == 1
@@ -116,13 +116,13 @@ def test_fiat_convert_get_price(mocker):
     # Verify the cached is used
     fiat_convert._pairs[0].price = 9867.543
     expiration = fiat_convert._pairs[0]._expiration
-    assert fiat_convert.get_price(crypto_symbol='BTC', fiat_symbol='USD') == 9867.543
+    assert fiat_convert.get_price(crypto_symbol='btc', fiat_symbol='usd') == 9867.543
     assert fiat_convert._pairs[0]._expiration == expiration
 
     # Verify the cache expiration
     expiration = time.time() - 2 * 60 * 60
     fiat_convert._pairs[0]._expiration = expiration
-    assert fiat_convert.get_price(crypto_symbol='BTC', fiat_symbol='USD') == 28000.0
+    assert fiat_convert.get_price(crypto_symbol='btc', fiat_symbol='usd') == 28000.0
     assert fiat_convert._pairs[0]._expiration is not expiration
 
 
@@ -143,15 +143,15 @@ def test_loadcryptomap(mocker):
     fiat_convert = CryptoToFiatConverter()
     assert len(fiat_convert._cryptomap) == 2
 
-    assert fiat_convert._cryptomap["BTC"] == "1"
+    assert fiat_convert._cryptomap["btc"] == "bitcoin"
 
 
 def test_fiat_init_network_exception(mocker):
     # Because CryptoToFiatConverter is a Singleton we reset the listings
     listmock = MagicMock(side_effect=RequestException)
     mocker.patch.multiple(
-        'freqtrade.rpc.fiat_convert.Market',
-        listings=listmock,
+        'freqtrade.rpc.fiat_convert.CoinGeckoAPI',
+        get_coins_list=listmock,
     )
     # with pytest.raises(RequestEsxception):
     fiat_convert = CryptoToFiatConverter()
@@ -163,24 +163,24 @@ def test_fiat_init_network_exception(mocker):
 
 
 def test_fiat_convert_without_network(mocker):
-    # Because CryptoToFiatConverter is a Singleton we reset the value of _coinmarketcap
+    # Because CryptoToFiatConverter is a Singleton we reset the value of _coingekko
 
     fiat_convert = CryptoToFiatConverter()
 
-    cmc_temp = CryptoToFiatConverter._coinmarketcap
-    CryptoToFiatConverter._coinmarketcap = None
+    cmc_temp = CryptoToFiatConverter._coingekko
+    CryptoToFiatConverter._coingekko = None
 
-    assert fiat_convert._coinmarketcap is None
-    assert fiat_convert._find_price(crypto_symbol='BTC', fiat_symbol='USD') == 0.0
-    CryptoToFiatConverter._coinmarketcap = cmc_temp
+    assert fiat_convert._coingekko is None
+    assert fiat_convert._find_price(crypto_symbol='btc', fiat_symbol='usd') == 0.0
+    CryptoToFiatConverter._coingekko = cmc_temp
 
 
 def test_fiat_invalid_response(mocker, caplog):
     # Because CryptoToFiatConverter is a Singleton we reset the listings
     listmock = MagicMock(return_value="{'novalidjson':DEADBEEFf}")
     mocker.patch.multiple(
-        'freqtrade.rpc.fiat_convert.Market',
-        listings=listmock,
+        'freqtrade.rpc.fiat_convert.CoinGeckoAPI',
+        get_coins_list=listmock,
     )
     # with pytest.raises(RequestEsxception):
     fiat_convert = CryptoToFiatConverter()
@@ -189,8 +189,8 @@ def test_fiat_invalid_response(mocker, caplog):
 
     length_cryptomap = len(fiat_convert._cryptomap)
     assert length_cryptomap == 0
-    assert log_has('Could not load FIAT Cryptocurrency map for the following problem: TypeError',
-                   caplog.record_tuples)
+    assert log_has_re('Could not load FIAT Cryptocurrency map for the following problem: .*',
+                      caplog)
 
 
 def test_convert_amount(mocker):
@@ -210,3 +210,10 @@ def test_convert_amount(mocker):
         fiat_symbol="BTC"
     )
     assert result == 1.23
+
+    result = fiat_convert.convert_amount(
+        crypto_amount="1.23",
+        crypto_symbol="BTC",
+        fiat_symbol="BTC"
+    )
+    assert result == 1.23
diff --git a/freqtrade/tests/rpc/test_rpc.py b/tests/rpc/test_rpc.py
similarity index 55%
rename from freqtrade/tests/rpc/test_rpc.py
rename to tests/rpc/test_rpc.py
index d273244b0..47e0f763d 100644
--- a/freqtrade/tests/rpc/test_rpc.py
+++ b/tests/rpc/test_rpc.py
@@ -7,14 +7,13 @@ from unittest.mock import ANY, MagicMock, PropertyMock
 import pytest
 from numpy import isnan
 
-from freqtrade import DependencyException, TemporaryError
 from freqtrade.edge import PairInfo
-from freqtrade.freqtradebot import FreqtradeBot
+from freqtrade.exceptions import ExchangeError, InvalidOrderException, TemporaryError
 from freqtrade.persistence import Trade
 from freqtrade.rpc import RPC, RPCException
 from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
 from freqtrade.state import State
-from freqtrade.tests.conftest import patch_exchange, patch_get_signal
+from tests.conftest import create_mock_trades, get_patched_freqtradebot, patch_get_signal
 
 
 # Functions for recurrent object patching
@@ -26,17 +25,15 @@ def prec_satoshi(a, b) -> float:
 
 
 # Unit tests
-def test_rpc_trade_status(default_conf, ticker, fee, markets, mocker) -> None:
+def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        _load_markets=MagicMock(return_value={}),
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(return_value=markets)
     )
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
 
@@ -44,106 +41,196 @@ def test_rpc_trade_status(default_conf, ticker, fee, markets, mocker) -> None:
     with pytest.raises(RPCException, match=r'.*no active trade*'):
         rpc._rpc_trade_status()
 
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
+    trades = Trade.get_open_trades()
+    trades[0].open_order_id = None
+    freqtradebot.exit_positions(trades)
+
     results = rpc._rpc_trade_status()
-    assert {
+    assert results[0] == {
         'trade_id': 1,
         'pair': 'ETH/BTC',
         'base_currency': 'BTC',
         'open_date': ANY,
         'open_date_hum': ANY,
+        'open_timestamp': ANY,
+        'is_open': ANY,
+        'fee_open': ANY,
+        'fee_open_cost': ANY,
+        'fee_open_currency': ANY,
+        'fee_close': fee.return_value,
+        'fee_close_cost': ANY,
+        'fee_close_currency': ANY,
+        'open_rate_requested': ANY,
+        'open_trade_price': 0.0010025,
+        'close_rate_requested': ANY,
+        'sell_reason': ANY,
+        'sell_order_status': ANY,
+        'min_rate': ANY,
+        'max_rate': ANY,
+        'strategy': ANY,
+        'timeframe': 5,
+        'open_order_id': ANY,
         'close_date': None,
         'close_date_hum': None,
-        'open_rate': 1.099e-05,
+        'close_timestamp': None,
+        'open_rate': 1.098e-05,
         'close_rate': None,
-        'current_rate': 1.098e-05,
-        'amount': 90.99181074,
+        'current_rate': 1.099e-05,
+        'amount': 91.07468123,
+        'amount_requested': 91.07468123,
         'stake_amount': 0.001,
         'close_profit': None,
-        'current_profit': -0.59,
-        'stop_loss': 0.0,
-        'initial_stop_loss': 0.0,
-        'initial_stop_loss_pct': None,
-        'stop_loss_pct': None,
-        'open_order': '(limit buy rem=0.00000000)'
-    } == results[0]
+        'close_profit_pct': None,
+        'close_profit_abs': None,
+        'current_profit': -0.00408133,
+        'current_profit_pct': -0.41,
+        'current_profit_abs': -4.09e-06,
+        'profit_ratio': -0.00408133,
+        'profit_pct': -0.41,
+        'profit_abs': -4.09e-06,
+        'stop_loss_abs': 9.882e-06,
+        'stop_loss_pct': -10.0,
+        'stop_loss_ratio': -0.1,
+        'stoploss_order_id': None,
+        'stoploss_last_update': ANY,
+        'stoploss_last_update_timestamp': ANY,
+        'initial_stop_loss_abs': 9.882e-06,
+        'initial_stop_loss_pct': -10.0,
+        'initial_stop_loss_ratio': -0.1,
+        'stoploss_current_dist': -1.1080000000000002e-06,
+        'stoploss_current_dist_ratio': -0.10081893,
+        'stoploss_current_dist_pct': -10.08,
+        'stoploss_entry_dist': -0.00010475,
+        'stoploss_entry_dist_ratio': -0.10448878,
+        'open_order': None,
+        'exchange': 'bittrex',
+    }
 
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(side_effect=DependencyException(f"Pair 'ETH/BTC' not available")))
-    # invalidate ticker cache
-    rpc._freqtrade.exchange._cached_ticker = {}
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_sell_rate',
+                 MagicMock(side_effect=ExchangeError("Pair 'ETH/BTC' not available")))
     results = rpc._rpc_trade_status()
     assert isnan(results[0]['current_profit'])
     assert isnan(results[0]['current_rate'])
-    assert {
+    assert results[0] == {
         'trade_id': 1,
         'pair': 'ETH/BTC',
         'base_currency': 'BTC',
         'open_date': ANY,
         'open_date_hum': ANY,
+        'open_timestamp': ANY,
+        'is_open': ANY,
+        'fee_open': ANY,
+        'fee_open_cost': ANY,
+        'fee_open_currency': ANY,
+        'fee_close': fee.return_value,
+        'fee_close_cost': ANY,
+        'fee_close_currency': ANY,
+        'open_rate_requested': ANY,
+        'open_trade_price': ANY,
+        'close_rate_requested': ANY,
+        'sell_reason': ANY,
+        'sell_order_status': ANY,
+        'min_rate': ANY,
+        'max_rate': ANY,
+        'strategy': ANY,
+        'timeframe': ANY,
+        'open_order_id': ANY,
         'close_date': None,
         'close_date_hum': None,
-        'open_rate': 1.099e-05,
+        'close_timestamp': None,
+        'open_rate': 1.098e-05,
         'close_rate': None,
         'current_rate': ANY,
-        'amount': 90.99181074,
+        'amount': 91.07468123,
+        'amount_requested': 91.07468123,
         'stake_amount': 0.001,
         'close_profit': None,
+        'close_profit_pct': None,
+        'close_profit_abs': None,
         'current_profit': ANY,
-        'stop_loss': 0.0,
-        'initial_stop_loss': 0.0,
-        'initial_stop_loss_pct': None,
-        'stop_loss_pct': None,
-        'open_order': '(limit buy rem=0.00000000)'
-    } == results[0]
+        'current_profit_pct': ANY,
+        'current_profit_abs': ANY,
+        'profit_ratio': ANY,
+        'profit_pct': ANY,
+        'profit_abs': ANY,
+        'stop_loss_abs': 9.882e-06,
+        'stop_loss_pct': -10.0,
+        'stop_loss_ratio': -0.1,
+        'stoploss_order_id': None,
+        'stoploss_last_update': ANY,
+        'stoploss_last_update_timestamp': ANY,
+        'initial_stop_loss_abs': 9.882e-06,
+        'initial_stop_loss_pct': -10.0,
+        'initial_stop_loss_ratio': -0.1,
+        'stoploss_current_dist': ANY,
+        'stoploss_current_dist_ratio': ANY,
+        'stoploss_current_dist_pct': ANY,
+        'stoploss_entry_dist': -0.00010475,
+        'stoploss_entry_dist_ratio': -0.10448878,
+        'open_order': None,
+        'exchange': 'bittrex',
+    }
 
 
-def test_rpc_status_table(default_conf, ticker, fee, markets, mocker) -> None:
-    patch_exchange(mocker)
+def test_rpc_status_table(default_conf, ticker, fee, mocker) -> None:
+    mocker.patch.multiple(
+        'freqtrade.rpc.fiat_convert.CoinGeckoAPI',
+        get_price=MagicMock(return_value={'bitcoin': {'usd': 15000.0}}),
+    )
+    mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(return_value=markets)
     )
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
 
     freqtradebot.state = State.RUNNING
-    with pytest.raises(RPCException, match=r'.*no active order*'):
-        rpc._rpc_status_table()
+    with pytest.raises(RPCException, match=r'.*no active trade*'):
+        rpc._rpc_status_table(default_conf['stake_currency'], 'USD')
 
-    freqtradebot.create_trade()
-    result = rpc._rpc_status_table()
-    assert 'instantly' in result['Since'].all()
-    assert 'ETH/BTC' in result['Pair'].all()
-    assert '-0.59%' in result['Profit'].all()
+    freqtradebot.enter_positions()
 
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(side_effect=DependencyException(f"Pair 'ETH/BTC' not available")))
-    # invalidate ticker cache
-    rpc._freqtrade.exchange._cached_ticker = {}
-    result = rpc._rpc_status_table()
-    assert 'instantly' in result['Since'].all()
-    assert 'ETH/BTC' in result['Pair'].all()
-    assert 'nan%' in result['Profit'].all()
+    result, headers = rpc._rpc_status_table(default_conf['stake_currency'], 'USD')
+    assert "Since" in headers
+    assert "Pair" in headers
+    assert 'instantly' == result[0][2]
+    assert 'ETH/BTC' in result[0][1]
+    assert '-0.41%' == result[0][3]
+    # Test with fiatconvert
+
+    rpc._fiat_converter = CryptoToFiatConverter()
+    result, headers = rpc._rpc_status_table(default_conf['stake_currency'], 'USD')
+    assert "Since" in headers
+    assert "Pair" in headers
+    assert 'instantly' == result[0][2]
+    assert 'ETH/BTC' in result[0][1]
+    assert '-0.41% (-0.06)' == result[0][3]
+
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_sell_rate',
+                 MagicMock(side_effect=ExchangeError("Pair 'ETH/BTC' not available")))
+    result, headers = rpc._rpc_status_table(default_conf['stake_currency'], 'USD')
+    assert 'instantly' == result[0][2]
+    assert 'ETH/BTC' in result[0][1]
+    assert 'nan%' == result[0][3]
 
 
 def test_rpc_daily_profit(default_conf, update, ticker, fee,
                           limit_buy_order, limit_sell_order, markets, mocker) -> None:
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
         markets=PropertyMock(return_value=markets)
     )
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     stake_currency = default_conf['stake_currency']
     fiat_display_currency = default_conf['fiat_display_currency']
@@ -151,7 +238,7 @@ def test_rpc_daily_profit(default_conf, update, ticker, fee,
     rpc = RPC(freqtradebot)
     rpc._fiat_converter = CryptoToFiatConverter()
     # Create some test data
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
     trade = Trade.query.first()
     assert trade
 
@@ -164,39 +251,118 @@ def test_rpc_daily_profit(default_conf, update, ticker, fee,
     # Try valid data
     update.message.text = '/daily 2'
     days = rpc._rpc_daily_profit(7, stake_currency, fiat_display_currency)
-    assert len(days) == 7
-    for day in days:
+    assert len(days['data']) == 7
+    assert days['stake_currency'] == default_conf['stake_currency']
+    assert days['fiat_display_currency'] == default_conf['fiat_display_currency']
+    for day in days['data']:
         # [datetime.date(2018, 1, 11), '0.00000000 BTC', '0.000 USD']
-        assert (day[1] == '0.00000000 BTC' or
-                day[1] == '0.00006217 BTC')
+        assert (day['abs_profit'] == 0.0 or
+                day['abs_profit'] == 0.00006217)
 
-        assert (day[2] == '0.000 USD' or
-                day[2] == '0.933 USD')
+        assert (day['fiat_value'] == 0.0 or
+                day['fiat_value'] == 0.76748865)
     # ensure first day is current date
-    assert str(days[0][0]) == str(datetime.utcnow().date())
+    assert str(days['data'][0]['date']) == str(datetime.utcnow().date())
 
     # Try invalid data
     with pytest.raises(RPCException, match=r'.*must be an integer greater than 0*'):
         rpc._rpc_daily_profit(0, stake_currency, fiat_display_currency)
 
 
-def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
-                              limit_buy_order, limit_sell_order, markets, mocker) -> None:
+def test_rpc_trade_history(mocker, default_conf, markets, fee):
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
-        'freqtrade.rpc.fiat_convert.Market',
-        ticker=MagicMock(return_value={'price_usd': 15000.0}),
+        'freqtrade.exchange.Exchange',
+        markets=PropertyMock(return_value=markets)
+    )
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    create_mock_trades(fee)
+    rpc = RPC(freqtradebot)
+    rpc._fiat_converter = CryptoToFiatConverter()
+    trades = rpc._rpc_trade_history(2)
+    assert len(trades['trades']) == 2
+    assert trades['trades_count'] == 2
+    assert isinstance(trades['trades'][0], dict)
+    assert isinstance(trades['trades'][1], dict)
+
+    trades = rpc._rpc_trade_history(0)
+    assert len(trades['trades']) == 2
+    assert trades['trades_count'] == 2
+    # The first closed trade is for ETC ... sorting is descending
+    assert trades['trades'][-1]['pair'] == 'ETC/BTC'
+    assert trades['trades'][0]['pair'] == 'XRP/BTC'
+
+
+def test_rpc_delete_trade(mocker, default_conf, fee, markets, caplog):
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
+    stoploss_mock = MagicMock()
+    cancel_mock = MagicMock()
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        markets=PropertyMock(return_value=markets),
+        cancel_order=cancel_mock,
+        cancel_stoploss_order=stoploss_mock,
+    )
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    freqtradebot.strategy.order_types['stoploss_on_exchange'] = True
+    create_mock_trades(fee)
+    rpc = RPC(freqtradebot)
+    with pytest.raises(RPCException, match='invalid argument'):
+        rpc._rpc_delete('200')
+
+    trades = Trade.query.all()
+    trades[1].stoploss_order_id = '1234'
+    trades[2].stoploss_order_id = '1234'
+    assert len(trades) > 2
+
+    res = rpc._rpc_delete('1')
+    assert isinstance(res, dict)
+    assert res['result'] == 'success'
+    assert res['trade_id'] == '1'
+    assert res['cancel_order_count'] == 1
+    assert cancel_mock.call_count == 1
+    assert stoploss_mock.call_count == 0
+    cancel_mock.reset_mock()
+    stoploss_mock.reset_mock()
+
+    res = rpc._rpc_delete('2')
+    assert isinstance(res, dict)
+    assert cancel_mock.call_count == 1
+    assert stoploss_mock.call_count == 1
+    assert res['cancel_order_count'] == 2
+
+    stoploss_mock = mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order',
+                                 side_effect=InvalidOrderException)
+
+    res = rpc._rpc_delete('3')
+    assert stoploss_mock.call_count == 1
+    stoploss_mock.reset_mock()
+
+    cancel_mock = mocker.patch('freqtrade.exchange.Exchange.cancel_order',
+                               side_effect=InvalidOrderException)
+
+    res = rpc._rpc_delete('4')
+    assert cancel_mock.call_count == 1
+    assert stoploss_mock.call_count == 0
+
+
+def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
+                              limit_buy_order, limit_sell_order, mocker) -> None:
+    mocker.patch.multiple(
+        'freqtrade.rpc.fiat_convert.CoinGeckoAPI',
+        get_price=MagicMock(return_value={'bitcoin': {'usd': 15000.0}}),
     )
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(return_value=markets)
     )
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     stake_currency = default_conf['stake_currency']
     fiat_display_currency = default_conf['fiat_display_currency']
@@ -204,11 +370,15 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
     rpc = RPC(freqtradebot)
     rpc._fiat_converter = CryptoToFiatConverter()
 
-    with pytest.raises(RPCException, match=r'.*no closed trade*'):
-        rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
+    res = rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
+    assert res['trade_count'] == 0
+    assert res['first_trade_date'] == ''
+    assert res['first_trade_timestamp'] == 0
+    assert res['latest_trade_date'] == ''
+    assert res['latest_trade_timestamp'] == 0
 
     # Create some test data
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
     trade = Trade.query.first()
     # Simulate fulfilled LIMIT_BUY order for trade
     trade.update(limit_buy_order)
@@ -216,13 +386,13 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
     # Update the ticker with a market going up
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker_sell_up
+        fetch_ticker=ticker_sell_up
     )
     trade.update(limit_sell_order)
     trade.close_date = datetime.utcnow()
     trade.is_open = False
 
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
     trade = Trade.query.first()
     # Simulate fulfilled LIMIT_BUY order for trade
     trade.update(limit_buy_order)
@@ -230,7 +400,7 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
     # Update the ticker with a market going up
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker_sell_up
+        fetch_ticker=ticker_sell_up
     )
     trade.update(limit_sell_order)
     trade.close_date = datetime.utcnow()
@@ -240,9 +410,9 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
     assert prec_satoshi(stats['profit_closed_coin'], 6.217e-05)
     assert prec_satoshi(stats['profit_closed_percent'], 6.2)
     assert prec_satoshi(stats['profit_closed_fiat'], 0.93255)
-    assert prec_satoshi(stats['profit_all_coin'], 5.632e-05)
-    assert prec_satoshi(stats['profit_all_percent'], 2.81)
-    assert prec_satoshi(stats['profit_all_fiat'], 0.8448)
+    assert prec_satoshi(stats['profit_all_coin'], 5.802e-05)
+    assert prec_satoshi(stats['profit_all_percent'], 2.89)
+    assert prec_satoshi(stats['profit_all_fiat'], 0.8703)
     assert stats['trade_count'] == 2
     assert stats['first_trade_date'] == 'just now'
     assert stats['latest_trade_date'] == 'just now'
@@ -251,10 +421,8 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
     assert prec_satoshi(stats['best_rate'], 6.2)
 
     # Test non-available pair
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker',
-                 MagicMock(side_effect=DependencyException(f"Pair 'ETH/BTC' not available")))
-    # invalidate ticker cache
-    rpc._freqtrade.exchange._cached_ticker = {}
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_sell_rate',
+                 MagicMock(side_effect=ExchangeError("Pair 'ETH/BTC' not available")))
     stats = rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
     assert stats['trade_count'] == 2
     assert stats['first_trade_date'] == 'just now'
@@ -267,24 +435,22 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
 
 # Test that rpc_trade_statistics can handle trades that lacks
 # trade.open_rate (it is set to None)
-def test_rpc_trade_statistics_closed(mocker, default_conf, ticker, fee, markets,
+def test_rpc_trade_statistics_closed(mocker, default_conf, ticker, fee,
                                      ticker_sell_up, limit_buy_order, limit_sell_order):
-    patch_exchange(mocker)
     mocker.patch.multiple(
-        'freqtrade.rpc.fiat_convert.Market',
-        ticker=MagicMock(return_value={'price_usd': 15000.0}),
+        'freqtrade.rpc.fiat_convert.CoinGeckoAPI',
+        get_price=MagicMock(return_value={'bitcoin': {'usd': 15000.0}}),
     )
     mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._find_price',
                  return_value=15000.0)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(return_value=markets)
     )
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     stake_currency = default_conf['stake_currency']
     fiat_display_currency = default_conf['fiat_display_currency']
@@ -292,14 +458,14 @@ def test_rpc_trade_statistics_closed(mocker, default_conf, ticker, fee, markets,
     rpc = RPC(freqtradebot)
 
     # Create some test data
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
     trade = Trade.query.first()
     # Simulate fulfilled LIMIT_BUY order for trade
     trade.update(limit_buy_order)
     # Update the ticker with a market going up
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker_sell_up,
+        fetch_ticker=ticker_sell_up,
         get_fee=fee
     )
     trade.update(limit_sell_order)
@@ -340,38 +506,26 @@ def test_rpc_balance_handle_error(default_conf, mocker):
     # ETH will be skipped due to mocked Error below
 
     mocker.patch.multiple(
-        'freqtrade.rpc.fiat_convert.Market',
-        ticker=MagicMock(return_value={'price_usd': 15000.0}),
+        'freqtrade.rpc.fiat_convert.CoinGeckoAPI',
+        get_price=MagicMock(return_value={'bitcoin': {'usd': 15000.0}}),
     )
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         get_balances=MagicMock(return_value=mock_balance),
-        get_ticker=MagicMock(side_effect=TemporaryError('Could not load ticker due to xxx'))
+        get_tickers=MagicMock(side_effect=TemporaryError('Could not load ticker due to xxx'))
     )
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
     rpc._fiat_converter = CryptoToFiatConverter()
-
-    result = rpc._rpc_balance(default_conf['fiat_display_currency'])
-    assert prec_satoshi(result['total'], 12)
-    assert prec_satoshi(result['value'], 180000)
-    assert 'USD' == result['symbol']
-    assert result['currencies'] == [{
-        'currency': 'BTC',
-        'available': 10.0,
-        'balance': 12.0,
-        'pending': 2.0,
-        'est_btc': 12.0,
-    }]
-    assert result['total'] == 12.0
+    with pytest.raises(RPCException, match="Error getting current tickers."):
+        rpc._rpc_balance(default_conf['stake_currency'], default_conf['fiat_display_currency'])
 
 
-def test_rpc_balance_handle(default_conf, mocker):
+def test_rpc_balance_handle(default_conf, mocker, tickers):
     mock_balance = {
         'BTC': {
             'free': 10.0,
@@ -383,7 +537,7 @@ def test_rpc_balance_handle(default_conf, mocker):
             'total': 5.0,
             'used': 4.0,
         },
-        'PAX': {
+        'USDT': {
             'free': 5.0,
             'total': 10.0,
             'used': 5.0,
@@ -391,61 +545,63 @@ def test_rpc_balance_handle(default_conf, mocker):
     }
 
     mocker.patch.multiple(
-        'freqtrade.rpc.fiat_convert.Market',
-        ticker=MagicMock(return_value={'price_usd': 15000.0}),
+        'freqtrade.rpc.fiat_convert.CoinGeckoAPI',
+        get_price=MagicMock(return_value={'bitcoin': {'usd': 15000.0}}),
     )
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         get_balances=MagicMock(return_value=mock_balance),
-        get_ticker=MagicMock(
-            side_effect=lambda p, r: {'bid': 100} if p == "BTC/PAX" else {'bid': 0.01}),
+        get_tickers=tickers,
         get_valid_pair_combination=MagicMock(
-            side_effect=lambda a, b: f"{b}/{a}" if a == "PAX" else f"{a}/{b}")
+            side_effect=lambda a, b: f"{b}/{a}" if a == "USDT" else f"{a}/{b}")
     )
-
-    freqtradebot = FreqtradeBot(default_conf)
+    default_conf['dry_run'] = False
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
     rpc._fiat_converter = CryptoToFiatConverter()
 
-    result = rpc._rpc_balance(default_conf['fiat_display_currency'])
-    assert prec_satoshi(result['total'], 12.15)
-    assert prec_satoshi(result['value'], 182250)
+    result = rpc._rpc_balance(default_conf['stake_currency'], default_conf['fiat_display_currency'])
+    assert prec_satoshi(result['total'], 12.309096315)
+    assert prec_satoshi(result['value'], 184636.44472997)
     assert 'USD' == result['symbol']
     assert result['currencies'] == [
         {'currency': 'BTC',
-            'available': 10.0,
-            'balance': 12.0,
-            'pending': 2.0,
-            'est_btc': 12.0,
+         'free': 10.0,
+         'balance': 12.0,
+         'used': 2.0,
+         'est_stake': 12.0,
+         'stake': 'BTC',
          },
-        {'available': 1.0,
+        {'free': 1.0,
          'balance': 5.0,
          'currency': 'ETH',
-         'est_btc': 0.05,
-         'pending': 4.0
+         'est_stake': 0.30794,
+         'used': 4.0,
+         'stake': 'BTC',
+
          },
-        {'available': 5.0,
+        {'free': 5.0,
          'balance': 10.0,
-         'currency': 'PAX',
-         'est_btc': 0.1,
-         'pending': 5.0}
+         'currency': 'USDT',
+         'est_stake': 0.0011563153318162476,
+         'used': 5.0,
+         'stake': 'BTC',
+         }
     ]
-    assert result['total'] == 12.15
+    assert result['total'] == 12.309096315331816
 
 
 def test_rpc_start(mocker, default_conf) -> None:
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock()
+        fetch_ticker=MagicMock()
     )
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
     freqtradebot.state = State.STOPPED
@@ -460,14 +616,13 @@ def test_rpc_start(mocker, default_conf) -> None:
 
 
 def test_rpc_stop(mocker, default_conf) -> None:
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock()
+        fetch_ticker=MagicMock()
     )
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
     freqtradebot.state = State.RUNNING
@@ -483,45 +638,44 @@ def test_rpc_stop(mocker, default_conf) -> None:
 
 
 def test_rpc_stopbuy(mocker, default_conf) -> None:
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=MagicMock()
+        fetch_ticker=MagicMock()
     )
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
     freqtradebot.state = State.RUNNING
 
     assert freqtradebot.config['max_open_trades'] != 0
     result = rpc._rpc_stopbuy()
-    assert {'status': 'No more buy will occur from now. Run /reload_conf to reset.'} == result
+    assert {'status': 'No more buy will occur from now. Run /reload_config to reset.'} == result
     assert freqtradebot.config['max_open_trades'] == 0
 
 
-def test_rpc_forcesell(default_conf, ticker, fee, mocker, markets) -> None:
-    patch_exchange(mocker)
+def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
 
     cancel_order_mock = MagicMock()
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         cancel_order=cancel_order_mock,
-        get_order=MagicMock(
+        fetch_order=MagicMock(
             return_value={
                 'status': 'closed',
                 'type': 'limit',
-                'side': 'buy'
+                'side': 'buy',
+                'filled': 0.0,
             }
         ),
         get_fee=fee,
-        markets=PropertyMock(return_value=markets)
     )
+    mocker.patch('freqtrade.wallets.Wallets.get_free', return_value=1000)
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
 
@@ -536,10 +690,11 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker, markets) -> None:
     msg = rpc._rpc_forcesell('all')
     assert msg == {'result': 'Created sell orders for all open trades.'}
 
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
     msg = rpc._rpc_forcesell('all')
     assert msg == {'result': 'Created sell orders for all open trades.'}
 
+    freqtradebot.enter_positions()
     msg = rpc._rpc_forcesell('1')
     assert msg == {'result': 'Created sell order for trade 1.'}
 
@@ -552,17 +707,26 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker, markets) -> None:
 
     freqtradebot.state = State.RUNNING
     assert cancel_order_mock.call_count == 0
+    freqtradebot.enter_positions()
     # make an limit-buy open trade
     trade = Trade.query.filter(Trade.id == '1').first()
     filled_amount = trade.amount / 2
+    # Fetch order - it's open first, and closed after cancel_order is called.
     mocker.patch(
-        'freqtrade.exchange.Exchange.get_order',
-        return_value={
+        'freqtrade.exchange.Exchange.fetch_order',
+        side_effect=[{
+            'id': '1234',
             'status': 'open',
             'type': 'limit',
             'side': 'buy',
             'filled': filled_amount
-        }
+        }, {
+            'id': '1234',
+            'status': 'closed',
+            'type': 'limit',
+            'side': 'buy',
+            'filled': filled_amount
+        }]
     )
     # check that the trade is called, which is done by ensuring exchange.cancel_order is called
     # and trade amount is updated
@@ -570,12 +734,22 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker, markets) -> None:
     assert cancel_order_mock.call_count == 1
     assert trade.amount == filled_amount
 
-    freqtradebot.create_trade()
+    mocker.patch(
+        'freqtrade.exchange.Exchange.fetch_order',
+        return_value={
+            'status': 'open',
+            'type': 'limit',
+            'side': 'buy',
+            'filled': filled_amount
+        })
+
+    freqtradebot.config['max_open_trades'] = 3
+    freqtradebot.enter_positions()
     trade = Trade.query.filter(Trade.id == '2').first()
     amount = trade.amount
     # make an limit-buy open trade, if there is no 'filled', don't sell it
     mocker.patch(
-        'freqtrade.exchange.Exchange.get_order',
+        'freqtrade.exchange.Exchange.fetch_order',
         return_value={
             'status': 'open',
             'type': 'limit',
@@ -589,40 +763,40 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker, markets) -> None:
     assert cancel_order_mock.call_count == 2
     assert trade.amount == amount
 
-    freqtradebot.create_trade()
     # make an limit-sell open trade
     mocker.patch(
-        'freqtrade.exchange.Exchange.get_order',
+        'freqtrade.exchange.Exchange.fetch_order',
         return_value={
             'status': 'open',
             'type': 'limit',
-            'side': 'sell'
+            'side': 'sell',
+            'amount': amount,
+            'remaining': amount,
+            'filled': 0.0
         }
     )
     msg = rpc._rpc_forcesell('3')
     assert msg == {'result': 'Created sell order for trade 3.'}
     # status quo, no exchange calls
-    assert cancel_order_mock.call_count == 2
+    assert cancel_order_mock.call_count == 3
 
 
 def test_performance_handle(default_conf, ticker, limit_buy_order, fee,
-                            limit_sell_order, markets, mocker) -> None:
-    patch_exchange(mocker)
+                            limit_sell_order, mocker) -> None:
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         get_balances=MagicMock(return_value=ticker),
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(return_value=markets)
     )
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
 
     # Create some test data
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
     trade = Trade.query.first()
     assert trade
 
@@ -641,18 +815,16 @@ def test_performance_handle(default_conf, ticker, limit_buy_order, fee,
     assert prec_satoshi(res[0]['profit'], 6.2)
 
 
-def test_rpc_count(mocker, default_conf, ticker, fee, markets) -> None:
-    patch_exchange(mocker)
+def test_rpc_count(mocker, default_conf, ticker, fee) -> None:
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         get_balances=MagicMock(return_value=ticker),
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(return_value=markets)
     )
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
 
@@ -660,33 +832,31 @@ def test_rpc_count(mocker, default_conf, ticker, fee, markets) -> None:
     assert counts["current"] == 0
 
     # Create some test data
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
     counts = rpc._rpc_count()
     assert counts["current"] == 1
 
 
-def test_rpcforcebuy(mocker, default_conf, ticker, fee, markets, limit_buy_order) -> None:
+def test_rpcforcebuy(mocker, default_conf, ticker, fee, limit_buy_order_open) -> None:
     default_conf['forcebuy_enable'] = True
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
-    buy_mm = MagicMock(return_value={'id': limit_buy_order['id']})
+    buy_mm = MagicMock(return_value=limit_buy_order_open)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         get_balances=MagicMock(return_value=ticker),
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(return_value=markets),
         buy=buy_mm
     )
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
     pair = 'ETH/BTC'
     trade = rpc._rpc_forcebuy(pair, None)
     assert isinstance(trade, Trade)
     assert trade.pair == pair
-    assert trade.open_rate == ticker()['ask']
+    assert trade.open_rate == ticker()['bid']
 
     # Test buy duplicate
     with pytest.raises(RPCException, match=r'position for ETH/BTC already open - id: 1'):
@@ -698,13 +868,14 @@ def test_rpcforcebuy(mocker, default_conf, ticker, fee, markets, limit_buy_order
     assert trade.open_rate == 0.0001
 
     # Test buy pair not with stakes
-    with pytest.raises(RPCException, match=r'Wrong pair selected. Please pairs with stake.*'):
-        rpc._rpc_forcebuy('XRP/ETH', 0.0001)
+    with pytest.raises(RPCException,
+                       match=r'Wrong pair selected. Only pairs with stake-currency.*'):
+        rpc._rpc_forcebuy('LTC/ETH', 0.0001)
     pair = 'XRP/BTC'
 
     # Test not buying
-    default_conf['stake_amount'] = 0.0000001
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    freqtradebot.config['stake_amount'] = 0.0000001
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
     pair = 'TKN/BTC'
@@ -715,10 +886,9 @@ def test_rpcforcebuy(mocker, default_conf, ticker, fee, markets, limit_buy_order
 def test_rpcforcebuy_stopped(mocker, default_conf) -> None:
     default_conf['forcebuy_enable'] = True
     default_conf['initial_state'] = 'stopped'
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
     pair = 'ETH/BTC'
@@ -727,10 +897,9 @@ def test_rpcforcebuy_stopped(mocker, default_conf) -> None:
 
 
 def test_rpcforcebuy_disabled(mocker, default_conf) -> None:
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     rpc = RPC(freqtradebot)
     pair = 'ETH/BTC'
@@ -739,69 +908,81 @@ def test_rpcforcebuy_disabled(mocker, default_conf) -> None:
 
 
 def test_rpc_whitelist(mocker, default_conf) -> None:
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     rpc = RPC(freqtradebot)
     ret = rpc._rpc_whitelist()
-    assert ret['method'] == 'StaticPairList'
+    assert len(ret['method']) == 1
+    assert 'StaticPairList' in ret['method']
     assert ret['whitelist'] == default_conf['exchange']['pair_whitelist']
 
 
 def test_rpc_whitelist_dynamic(mocker, default_conf) -> None:
-    patch_exchange(mocker)
-    default_conf['pairlist'] = {'method': 'VolumePairList',
-                                'config': {'number_assets': 4}
-                                }
+    default_conf['pairlists'] = [{'method': 'VolumePairList',
+                                  'number_assets': 4,
+                                  }]
     mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     rpc = RPC(freqtradebot)
     ret = rpc._rpc_whitelist()
-    assert ret['method'] == 'VolumePairList'
+    assert len(ret['method']) == 1
+    assert 'VolumePairList' in ret['method']
     assert ret['length'] == 4
     assert ret['whitelist'] == default_conf['exchange']['pair_whitelist']
 
 
 def test_rpc_blacklist(mocker, default_conf) -> None:
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     rpc = RPC(freqtradebot)
     ret = rpc._rpc_blacklist(None)
-    assert ret['method'] == 'StaticPairList'
+    assert len(ret['method']) == 1
+    assert 'StaticPairList' in ret['method']
     assert len(ret['blacklist']) == 2
     assert ret['blacklist'] == default_conf['exchange']['pair_blacklist']
     assert ret['blacklist'] == ['DOGE/BTC', 'HOT/BTC']
 
     ret = rpc._rpc_blacklist(["ETH/BTC"])
-    assert ret['method'] == 'StaticPairList'
+    assert 'StaticPairList' in ret['method']
     assert len(ret['blacklist']) == 3
     assert ret['blacklist'] == default_conf['exchange']['pair_blacklist']
     assert ret['blacklist'] == ['DOGE/BTC', 'HOT/BTC', 'ETH/BTC']
 
+    ret = rpc._rpc_blacklist(["ETH/BTC"])
+    assert 'errors' in ret
+    assert isinstance(ret['errors'], dict)
+    assert ret['errors']['ETH/BTC']['error_msg'] == 'Pair ETH/BTC already in pairlist.'
+
+    ret = rpc._rpc_blacklist(["ETH/ETH"])
+    assert 'StaticPairList' in ret['method']
+    assert len(ret['blacklist']) == 3
+    assert ret['blacklist'] == default_conf['exchange']['pair_blacklist']
+    assert ret['blacklist'] == ['DOGE/BTC', 'HOT/BTC', 'ETH/BTC']
+    assert 'errors' in ret
+    assert isinstance(ret['errors'], dict)
+    assert ret['errors']['ETH/ETH']['error_msg'] == 'Pair ETH/ETH does not match stake currency.'
+
 
 def test_rpc_edge_disabled(mocker, default_conf) -> None:
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     rpc = RPC(freqtradebot)
     with pytest.raises(RPCException, match=r'Edge is not enabled.'):
         rpc._rpc_edge()
 
 
 def test_rpc_edge_enabled(mocker, edge_conf) -> None:
-    patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
     mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
         return_value={
             'E/F': PairInfo(-0.02, 0.66, 3.71, 0.50, 1.71, 10, 60),
         }
     ))
-    freqtradebot = FreqtradeBot(edge_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, edge_conf)
 
     rpc = RPC(freqtradebot)
     ret = rpc._rpc_edge()
diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py
new file mode 100644
index 000000000..0dc43474f
--- /dev/null
+++ b/tests/rpc/test_rpc_apiserver.py
@@ -0,0 +1,1011 @@
+"""
+Unit test file for rpc/api_server.py
+"""
+
+from datetime import datetime, timedelta, timezone
+from pathlib import Path
+from unittest.mock import ANY, MagicMock, PropertyMock
+
+import pytest
+from flask import Flask
+from requests.auth import _basic_auth_str
+
+from freqtrade.__init__ import __version__
+from freqtrade.loggers import setup_logging, setup_logging_pre
+from freqtrade.persistence import PairLocks, Trade
+from freqtrade.rpc.api_server import BASE_URI, ApiServer
+from freqtrade.state import RunMode, State
+from tests.conftest import create_mock_trades, get_patched_freqtradebot, log_has, patch_get_signal
+
+
+_TEST_USER = "FreqTrader"
+_TEST_PASS = "SuperSecurePassword1!"
+
+
+@pytest.fixture
+def botclient(default_conf, mocker):
+    setup_logging_pre()
+    setup_logging(default_conf)
+    default_conf['runmode'] = RunMode.DRY_RUN
+    default_conf.update({"api_server": {"enabled": True,
+                                        "listen_ip_address": "127.0.0.1",
+                                        "listen_port": 8080,
+                                        "CORS_origins": ['http://example.com'],
+                                        "username": _TEST_USER,
+                                        "password": _TEST_PASS,
+                                        }})
+
+    ftbot = get_patched_freqtradebot(mocker, default_conf)
+    mocker.patch('freqtrade.rpc.api_server.ApiServer.run', MagicMock())
+    apiserver = ApiServer(ftbot)
+    yield ftbot, apiserver.app.test_client()
+    # Cleanup ... ?
+
+
+def client_post(client, url, data={}):
+    return client.post(url,
+                       content_type="application/json",
+                       data=data,
+                       headers={'Authorization': _basic_auth_str(_TEST_USER, _TEST_PASS),
+                                'Origin': 'http://example.com'})
+
+
+def client_get(client, url):
+    # Add fake Origin to ensure CORS kicks in
+    return client.get(url, headers={'Authorization': _basic_auth_str(_TEST_USER, _TEST_PASS),
+                                    'Origin': 'http://example.com'})
+
+
+def client_delete(client, url):
+    # Add fake Origin to ensure CORS kicks in
+    return client.delete(url, headers={'Authorization': _basic_auth_str(_TEST_USER, _TEST_PASS),
+                                       'Origin': 'http://example.com'})
+
+
+def assert_response(response, expected_code=200, needs_cors=True):
+    assert response.status_code == expected_code
+    assert response.content_type == "application/json"
+    if needs_cors:
+        assert ('Access-Control-Allow-Credentials', 'true') in response.headers._list
+        assert ('Access-Control-Allow-Origin', 'http://example.com') in response.headers._list
+
+
+def test_api_not_found(botclient):
+    ftbot, client = botclient
+
+    rc = client_post(client, f"{BASE_URI}/invalid_url")
+    assert_response(rc, 404)
+    assert rc.json == {"status": "error",
+                       "reason": f"There's no API call for http://localhost{BASE_URI}/invalid_url.",
+                       "code": 404
+                       }
+
+
+def test_api_unauthorized(botclient):
+    ftbot, client = botclient
+    rc = client.get(f"{BASE_URI}/ping")
+    assert_response(rc, needs_cors=False)
+    assert rc.json == {'status': 'pong'}
+
+    # Don't send user/pass information
+    rc = client.get(f"{BASE_URI}/version")
+    assert_response(rc, 401, needs_cors=False)
+    assert rc.json == {'error': 'Unauthorized'}
+
+    # Change only username
+    ftbot.config['api_server']['username'] = 'Ftrader'
+    rc = client_get(client, f"{BASE_URI}/version")
+    assert_response(rc, 401)
+    assert rc.json == {'error': 'Unauthorized'}
+
+    # Change only password
+    ftbot.config['api_server']['username'] = _TEST_USER
+    ftbot.config['api_server']['password'] = 'WrongPassword'
+    rc = client_get(client, f"{BASE_URI}/version")
+    assert_response(rc, 401)
+    assert rc.json == {'error': 'Unauthorized'}
+
+    ftbot.config['api_server']['username'] = 'Ftrader'
+    ftbot.config['api_server']['password'] = 'WrongPassword'
+
+    rc = client_get(client, f"{BASE_URI}/version")
+    assert_response(rc, 401)
+    assert rc.json == {'error': 'Unauthorized'}
+
+
+def test_api_token_login(botclient):
+    ftbot, client = botclient
+    rc = client_post(client, f"{BASE_URI}/token/login")
+    assert_response(rc)
+    assert 'access_token' in rc.json
+    assert 'refresh_token' in rc.json
+
+    # test Authentication is working with JWT tokens too
+    rc = client.get(f"{BASE_URI}/count",
+                    content_type="application/json",
+                    headers={'Authorization': f'Bearer {rc.json["access_token"]}',
+                             'Origin': 'http://example.com'})
+    assert_response(rc)
+
+
+def test_api_token_refresh(botclient):
+    ftbot, client = botclient
+    rc = client_post(client, f"{BASE_URI}/token/login")
+    assert_response(rc)
+    rc = client.post(f"{BASE_URI}/token/refresh",
+                     content_type="application/json",
+                     data=None,
+                     headers={'Authorization': f'Bearer {rc.json["refresh_token"]}',
+                              'Origin': 'http://example.com'})
+    assert_response(rc)
+    assert 'access_token' in rc.json
+    assert 'refresh_token' not in rc.json
+
+
+def test_api_stop_workflow(botclient):
+    ftbot, client = botclient
+    assert ftbot.state == State.RUNNING
+    rc = client_post(client, f"{BASE_URI}/stop")
+    assert_response(rc)
+    assert rc.json == {'status': 'stopping trader ...'}
+    assert ftbot.state == State.STOPPED
+
+    # Stop bot again
+    rc = client_post(client, f"{BASE_URI}/stop")
+    assert_response(rc)
+    assert rc.json == {'status': 'already stopped'}
+
+    # Start bot
+    rc = client_post(client, f"{BASE_URI}/start")
+    assert_response(rc)
+    assert rc.json == {'status': 'starting trader ...'}
+    assert ftbot.state == State.RUNNING
+
+    # Call start again
+    rc = client_post(client, f"{BASE_URI}/start")
+    assert_response(rc)
+    assert rc.json == {'status': 'already running'}
+
+
+def test_api__init__(default_conf, mocker):
+    """
+    Test __init__() method
+    """
+    default_conf.update({"api_server": {"enabled": True,
+                                        "listen_ip_address": "127.0.0.1",
+                                        "listen_port": 8080,
+                                        "username": "TestUser",
+                                        "password": "testPass",
+                                        }})
+    mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock())
+    mocker.patch('freqtrade.rpc.api_server.ApiServer.run', MagicMock())
+
+    apiserver = ApiServer(get_patched_freqtradebot(mocker, default_conf))
+    assert apiserver._config == default_conf
+
+
+def test_api_run(default_conf, mocker, caplog):
+    default_conf.update({"api_server": {"enabled": True,
+                                        "listen_ip_address": "127.0.0.1",
+                                        "listen_port": 8080,
+                                        "username": "TestUser",
+                                        "password": "testPass",
+                                        }})
+    mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock())
+    mocker.patch('freqtrade.rpc.api_server.threading.Thread', MagicMock())
+
+    server_mock = MagicMock()
+    mocker.patch('freqtrade.rpc.api_server.make_server', server_mock)
+
+    apiserver = ApiServer(get_patched_freqtradebot(mocker, default_conf))
+
+    assert apiserver._config == default_conf
+    apiserver.run()
+    assert server_mock.call_count == 1
+    assert server_mock.call_args_list[0][0][0] == "127.0.0.1"
+    assert server_mock.call_args_list[0][0][1] == 8080
+    assert isinstance(server_mock.call_args_list[0][0][2], Flask)
+    assert hasattr(apiserver, "srv")
+
+    assert log_has("Starting HTTP Server at 127.0.0.1:8080", caplog)
+    assert log_has("Starting Local Rest Server.", caplog)
+
+    # Test binding to public
+    caplog.clear()
+    server_mock.reset_mock()
+    apiserver._config.update({"api_server": {"enabled": True,
+                                             "listen_ip_address": "0.0.0.0",
+                                             "listen_port": 8089,
+                                             "password": "",
+                                             }})
+    apiserver.run()
+
+    assert server_mock.call_count == 1
+    assert server_mock.call_args_list[0][0][0] == "0.0.0.0"
+    assert server_mock.call_args_list[0][0][1] == 8089
+    assert isinstance(server_mock.call_args_list[0][0][2], Flask)
+    assert log_has("Starting HTTP Server at 0.0.0.0:8089", caplog)
+    assert log_has("Starting Local Rest Server.", caplog)
+    assert log_has("SECURITY WARNING - Local Rest Server listening to external connections",
+                   caplog)
+    assert log_has("SECURITY WARNING - This is insecure please set to your loopback,"
+                   "e.g 127.0.0.1 in config.json", caplog)
+    assert log_has("SECURITY WARNING - No password for local REST Server defined. "
+                   "Please make sure that this is intentional!", caplog)
+
+    # Test crashing flask
+    caplog.clear()
+    mocker.patch('freqtrade.rpc.api_server.make_server', MagicMock(side_effect=Exception))
+    apiserver.run()
+    assert log_has("Api server failed to start.", caplog)
+
+
+def test_api_cleanup(default_conf, mocker, caplog):
+    default_conf.update({"api_server": {"enabled": True,
+                                        "listen_ip_address": "127.0.0.1",
+                                        "listen_port": 8080,
+                                        "username": "TestUser",
+                                        "password": "testPass",
+                                        }})
+    mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock())
+    mocker.patch('freqtrade.rpc.api_server.threading.Thread', MagicMock())
+    mocker.patch('freqtrade.rpc.api_server.make_server', MagicMock())
+
+    apiserver = ApiServer(get_patched_freqtradebot(mocker, default_conf))
+    apiserver.run()
+    stop_mock = MagicMock()
+    stop_mock.shutdown = MagicMock()
+    apiserver.srv = stop_mock
+
+    apiserver.cleanup()
+    assert stop_mock.shutdown.call_count == 1
+    assert log_has("Stopping API Server", caplog)
+
+
+def test_api_reloadconf(botclient):
+    ftbot, client = botclient
+
+    rc = client_post(client, f"{BASE_URI}/reload_config")
+    assert_response(rc)
+    assert rc.json == {'status': 'Reloading config ...'}
+    assert ftbot.state == State.RELOAD_CONFIG
+
+
+def test_api_stopbuy(botclient):
+    ftbot, client = botclient
+    assert ftbot.config['max_open_trades'] != 0
+
+    rc = client_post(client, f"{BASE_URI}/stopbuy")
+    assert_response(rc)
+    assert rc.json == {'status': 'No more buy will occur from now. Run /reload_config to reset.'}
+    assert ftbot.config['max_open_trades'] == 0
+
+
+def test_api_balance(botclient, mocker, rpc_balance):
+    ftbot, client = botclient
+
+    ftbot.config['dry_run'] = False
+    mocker.patch('freqtrade.exchange.Exchange.get_balances', return_value=rpc_balance)
+    mocker.patch('freqtrade.exchange.Exchange.get_valid_pair_combination',
+                 side_effect=lambda a, b: f"{a}/{b}")
+    ftbot.wallets.update()
+
+    rc = client_get(client, f"{BASE_URI}/balance")
+    assert_response(rc)
+    assert "currencies" in rc.json
+    assert len(rc.json["currencies"]) == 5
+    assert rc.json['currencies'][0] == {
+        'currency': 'BTC',
+        'free': 12.0,
+        'balance': 12.0,
+        'used': 0.0,
+        'est_stake': 12.0,
+        'stake': 'BTC',
+    }
+
+
+def test_api_count(botclient, mocker, ticker, fee, markets):
+    ftbot, client = botclient
+    patch_get_signal(ftbot, (True, False))
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balances=MagicMock(return_value=ticker),
+        fetch_ticker=ticker,
+        get_fee=fee,
+        markets=PropertyMock(return_value=markets)
+    )
+    rc = client_get(client, f"{BASE_URI}/count")
+    assert_response(rc)
+
+    assert rc.json["current"] == 0
+    assert rc.json["max"] == 1.0
+
+    # Create some test data
+    ftbot.enter_positions()
+    rc = client_get(client, f"{BASE_URI}/count")
+    assert_response(rc)
+    assert rc.json["current"] == 1.0
+    assert rc.json["max"] == 1.0
+
+
+def test_api_locks(botclient):
+    ftbot, client = botclient
+
+    rc = client_get(client, f"{BASE_URI}/locks")
+    assert_response(rc)
+
+    assert 'locks' in rc.json
+
+    assert rc.json['lock_count'] == 0
+    assert rc.json['lock_count'] == len(rc.json['locks'])
+
+    PairLocks.lock_pair('ETH/BTC', datetime.now(timezone.utc) + timedelta(minutes=4), 'randreason')
+    PairLocks.lock_pair('XRP/BTC', datetime.now(timezone.utc) + timedelta(minutes=20), 'deadbeef')
+
+    rc = client_get(client, f"{BASE_URI}/locks")
+    assert_response(rc)
+
+    assert rc.json['lock_count'] == 2
+    assert rc.json['lock_count'] == len(rc.json['locks'])
+    assert 'ETH/BTC' in (rc.json['locks'][0]['pair'], rc.json['locks'][1]['pair'])
+    assert 'randreason' in (rc.json['locks'][0]['reason'], rc.json['locks'][1]['reason'])
+    assert 'deadbeef' in (rc.json['locks'][0]['reason'], rc.json['locks'][1]['reason'])
+
+
+def test_api_show_config(botclient, mocker):
+    ftbot, client = botclient
+    patch_get_signal(ftbot, (True, False))
+
+    rc = client_get(client, f"{BASE_URI}/show_config")
+    assert_response(rc)
+    assert 'dry_run' in rc.json
+    assert rc.json['exchange'] == 'bittrex'
+    assert rc.json['timeframe'] == '5m'
+    assert rc.json['timeframe_ms'] == 300000
+    assert rc.json['timeframe_min'] == 5
+    assert rc.json['state'] == 'running'
+    assert not rc.json['trailing_stop']
+    assert 'bid_strategy' in rc.json
+    assert 'ask_strategy' in rc.json
+
+
+def test_api_daily(botclient, mocker, ticker, fee, markets):
+    ftbot, client = botclient
+    patch_get_signal(ftbot, (True, False))
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balances=MagicMock(return_value=ticker),
+        fetch_ticker=ticker,
+        get_fee=fee,
+        markets=PropertyMock(return_value=markets)
+    )
+    rc = client_get(client, f"{BASE_URI}/daily")
+    assert_response(rc)
+    assert len(rc.json['data']) == 7
+    assert rc.json['stake_currency'] == 'BTC'
+    assert rc.json['fiat_display_currency'] == 'USD'
+    assert rc.json['data'][0]['date'] == str(datetime.utcnow().date())
+
+
+def test_api_trades(botclient, mocker, fee, markets):
+    ftbot, client = botclient
+    patch_get_signal(ftbot, (True, False))
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        markets=PropertyMock(return_value=markets)
+    )
+    rc = client_get(client, f"{BASE_URI}/trades")
+    assert_response(rc)
+    assert len(rc.json) == 2
+    assert rc.json['trades_count'] == 0
+
+    create_mock_trades(fee)
+
+    rc = client_get(client, f"{BASE_URI}/trades")
+    assert_response(rc)
+    assert len(rc.json['trades']) == 2
+    assert rc.json['trades_count'] == 2
+    rc = client_get(client, f"{BASE_URI}/trades?limit=1")
+    assert_response(rc)
+    assert len(rc.json['trades']) == 1
+    assert rc.json['trades_count'] == 1
+
+
+def test_api_delete_trade(botclient, mocker, fee, markets):
+    ftbot, client = botclient
+    patch_get_signal(ftbot, (True, False))
+    stoploss_mock = MagicMock()
+    cancel_mock = MagicMock()
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        markets=PropertyMock(return_value=markets),
+        cancel_order=cancel_mock,
+        cancel_stoploss_order=stoploss_mock,
+    )
+    rc = client_delete(client, f"{BASE_URI}/trades/1")
+    # Error - trade won't exist yet.
+    assert_response(rc, 502)
+
+    create_mock_trades(fee)
+    ftbot.strategy.order_types['stoploss_on_exchange'] = True
+    trades = Trade.query.all()
+    trades[1].stoploss_order_id = '1234'
+    assert len(trades) > 2
+
+    rc = client_delete(client, f"{BASE_URI}/trades/1")
+    assert_response(rc)
+    assert rc.json['result_msg'] == 'Deleted trade 1. Closed 1 open orders.'
+    assert len(trades) - 1 == len(Trade.query.all())
+    assert cancel_mock.call_count == 1
+
+    cancel_mock.reset_mock()
+    rc = client_delete(client, f"{BASE_URI}/trades/1")
+    # Trade is gone now.
+    assert_response(rc, 502)
+    assert cancel_mock.call_count == 0
+
+    assert len(trades) - 1 == len(Trade.query.all())
+    rc = client_delete(client, f"{BASE_URI}/trades/2")
+    assert_response(rc)
+    assert rc.json['result_msg'] == 'Deleted trade 2. Closed 2 open orders.'
+    assert len(trades) - 2 == len(Trade.query.all())
+    assert stoploss_mock.call_count == 1
+
+
+def test_api_logs(botclient):
+    ftbot, client = botclient
+    rc = client_get(client, f"{BASE_URI}/logs")
+    assert_response(rc)
+    assert len(rc.json) == 2
+    assert 'logs' in rc.json
+    # Using a fixed comparison here would make this test fail!
+    assert rc.json['log_count'] > 1
+    assert len(rc.json['logs']) == rc.json['log_count']
+
+    assert isinstance(rc.json['logs'][0], list)
+    # date
+    assert isinstance(rc.json['logs'][0][0], str)
+    # created_timestamp
+    assert isinstance(rc.json['logs'][0][1], float)
+    assert isinstance(rc.json['logs'][0][2], str)
+    assert isinstance(rc.json['logs'][0][3], str)
+    assert isinstance(rc.json['logs'][0][4], str)
+
+    rc = client_get(client, f"{BASE_URI}/logs?limit=5")
+    assert_response(rc)
+    assert len(rc.json) == 2
+    assert 'logs' in rc.json
+    # Using a fixed comparison here would make this test fail!
+    assert rc.json['log_count'] == 5
+    assert len(rc.json['logs']) == rc.json['log_count']
+
+
+def test_api_edge_disabled(botclient, mocker, ticker, fee, markets):
+    ftbot, client = botclient
+    patch_get_signal(ftbot, (True, False))
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balances=MagicMock(return_value=ticker),
+        fetch_ticker=ticker,
+        get_fee=fee,
+        markets=PropertyMock(return_value=markets)
+    )
+    rc = client_get(client, f"{BASE_URI}/edge")
+    assert_response(rc, 502)
+    assert rc.json == {"error": "Error querying _edge: Edge is not enabled."}
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_api_profit(botclient, mocker, ticker, fee, markets, limit_buy_order, limit_sell_order):
+    ftbot, client = botclient
+    patch_get_signal(ftbot, (True, False))
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balances=MagicMock(return_value=ticker),
+        fetch_ticker=ticker,
+        get_fee=fee,
+        markets=PropertyMock(return_value=markets)
+    )
+
+    rc = client_get(client, f"{BASE_URI}/profit")
+    assert_response(rc, 200)
+    assert rc.json['trade_count'] == 0
+
+    ftbot.enter_positions()
+    trade = Trade.query.first()
+
+    # Simulate fulfilled LIMIT_BUY order for trade
+    trade.update(limit_buy_order)
+    rc = client_get(client, f"{BASE_URI}/profit")
+    assert_response(rc, 200)
+    # One open trade
+    assert rc.json['trade_count'] == 1
+    assert rc.json['best_pair'] == ''
+    assert rc.json['best_rate'] == 0
+
+    trade = Trade.query.first()
+    trade.update(limit_sell_order)
+
+    trade.close_date = datetime.utcnow()
+    trade.is_open = False
+
+    rc = client_get(client, f"{BASE_URI}/profit")
+    assert_response(rc)
+    assert rc.json == {'avg_duration': '0:00:00',
+                       'best_pair': 'ETH/BTC',
+                       'best_rate': 6.2,
+                       'first_trade_date': 'just now',
+                       'first_trade_timestamp': ANY,
+                       'latest_trade_date': 'just now',
+                       'latest_trade_timestamp': ANY,
+                       'profit_all_coin': 6.217e-05,
+                       'profit_all_fiat': 0.76748865,
+                       'profit_all_percent': 6.2,
+                       'profit_all_percent_mean': 6.2,
+                       'profit_all_ratio_mean': 0.06201058,
+                       'profit_all_percent_sum': 6.2,
+                       'profit_all_ratio_sum': 0.06201058,
+                       'profit_closed_coin': 6.217e-05,
+                       'profit_closed_fiat': 0.76748865,
+                       'profit_closed_percent': 6.2,
+                       'profit_closed_ratio_mean': 0.06201058,
+                       'profit_closed_percent_mean': 6.2,
+                       'profit_closed_ratio_sum': 0.06201058,
+                       'profit_closed_percent_sum': 6.2,
+                       'trade_count': 1,
+                       'closed_trade_count': 1,
+                       'winning_trades': 1,
+                       'losing_trades': 0,
+                       }
+
+
+def test_api_performance(botclient, mocker, ticker, fee):
+    ftbot, client = botclient
+    patch_get_signal(ftbot, (True, False))
+
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=1,
+        exchange='binance',
+        stake_amount=1,
+        open_rate=0.245441,
+        open_order_id="123456",
+        is_open=False,
+        fee_close=fee.return_value,
+        fee_open=fee.return_value,
+        close_rate=0.265441,
+
+    )
+    trade.close_profit = trade.calc_profit_ratio()
+    Trade.session.add(trade)
+
+    trade = Trade(
+        pair='XRP/ETH',
+        amount=5,
+        stake_amount=1,
+        exchange='binance',
+        open_rate=0.412,
+        open_order_id="123456",
+        is_open=False,
+        fee_close=fee.return_value,
+        fee_open=fee.return_value,
+        close_rate=0.391
+    )
+    trade.close_profit = trade.calc_profit_ratio()
+    Trade.session.add(trade)
+    Trade.session.flush()
+
+    rc = client_get(client, f"{BASE_URI}/performance")
+    assert_response(rc)
+    assert len(rc.json) == 2
+    assert rc.json == [{'count': 1, 'pair': 'LTC/ETH', 'profit': 7.61},
+                       {'count': 1, 'pair': 'XRP/ETH', 'profit': -5.57}]
+
+
+def test_api_status(botclient, mocker, ticker, fee, markets):
+    ftbot, client = botclient
+    patch_get_signal(ftbot, (True, False))
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balances=MagicMock(return_value=ticker),
+        fetch_ticker=ticker,
+        get_fee=fee,
+        markets=PropertyMock(return_value=markets)
+    )
+
+    rc = client_get(client, f"{BASE_URI}/status")
+    assert_response(rc, 200)
+    assert rc.json == []
+
+    ftbot.enter_positions()
+    trades = Trade.get_open_trades()
+    trades[0].open_order_id = None
+    ftbot.exit_positions(trades)
+
+    rc = client_get(client, f"{BASE_URI}/status")
+    assert_response(rc)
+    assert len(rc.json) == 1
+    assert rc.json == [{'amount': 91.07468123,
+                        'amount_requested': 91.07468123,
+                        'base_currency': 'BTC',
+                        'close_date': None,
+                        'close_date_hum': None,
+                        'close_timestamp': None,
+                        'close_profit': None,
+                        'close_profit_pct': None,
+                        'close_profit_abs': None,
+                        'close_rate': None,
+                        'current_profit': -0.00408133,
+                        'current_profit_pct': -0.41,
+                        'current_profit_abs': -4.09e-06,
+                        'profit_ratio': -0.00408133,
+                        'profit_pct': -0.41,
+                        'profit_abs': -4.09e-06,
+                        'current_rate': 1.099e-05,
+                        'open_date': ANY,
+                        'open_date_hum': 'just now',
+                        'open_timestamp': ANY,
+                        'open_order': None,
+                        'open_rate': 1.098e-05,
+                        'pair': 'ETH/BTC',
+                        'stake_amount': 0.001,
+                        'stop_loss_abs': 9.882e-06,
+                        'stop_loss_pct': -10.0,
+                        'stop_loss_ratio': -0.1,
+                        'stoploss_order_id': None,
+                        'stoploss_last_update': ANY,
+                        'stoploss_last_update_timestamp': ANY,
+                        'initial_stop_loss_abs': 9.882e-06,
+                        'initial_stop_loss_pct': -10.0,
+                        'initial_stop_loss_ratio': -0.1,
+                        'stoploss_current_dist': -1.1080000000000002e-06,
+                        'stoploss_current_dist_ratio': -0.10081893,
+                        'stoploss_current_dist_pct': -10.08,
+                        'stoploss_entry_dist': -0.00010475,
+                        'stoploss_entry_dist_ratio': -0.10448878,
+                        'trade_id': 1,
+                        'close_rate_requested': None,
+                        'current_rate': 1.099e-05,
+                        'fee_close': 0.0025,
+                        'fee_close_cost': None,
+                        'fee_close_currency': None,
+                        'fee_open': 0.0025,
+                        'fee_open_cost': None,
+                        'fee_open_currency': None,
+                        'open_date': ANY,
+                        'is_open': True,
+                        'max_rate': 1.099e-05,
+                        'min_rate': 1.098e-05,
+                        'open_order_id': None,
+                        'open_rate_requested': 1.098e-05,
+                        'open_trade_price': 0.0010025,
+                        'sell_reason': None,
+                        'sell_order_status': None,
+                        'strategy': 'DefaultStrategy',
+                        'timeframe': 5,
+                        'exchange': 'bittrex',
+                        }]
+
+
+def test_api_version(botclient):
+    ftbot, client = botclient
+
+    rc = client_get(client, f"{BASE_URI}/version")
+    assert_response(rc)
+    assert rc.json == {"version": __version__}
+
+
+def test_api_blacklist(botclient, mocker):
+    ftbot, client = botclient
+
+    rc = client_get(client, f"{BASE_URI}/blacklist")
+    assert_response(rc)
+    assert rc.json == {"blacklist": ["DOGE/BTC", "HOT/BTC"],
+                       "length": 2,
+                       "method": ["StaticPairList"],
+                       "errors": {},
+                       }
+
+    # Add ETH/BTC to blacklist
+    rc = client_post(client, f"{BASE_URI}/blacklist",
+                     data='{"blacklist": ["ETH/BTC"]}')
+    assert_response(rc)
+    assert rc.json == {"blacklist": ["DOGE/BTC", "HOT/BTC", "ETH/BTC"],
+                       "length": 3,
+                       "method": ["StaticPairList"],
+                       "errors": {},
+                       }
+
+
+def test_api_whitelist(botclient):
+    ftbot, client = botclient
+
+    rc = client_get(client, f"{BASE_URI}/whitelist")
+    assert_response(rc)
+    assert rc.json == {"whitelist": ['ETH/BTC', 'LTC/BTC', 'XRP/BTC', 'NEO/BTC'],
+                       "length": 4,
+                       "method": ["StaticPairList"]}
+
+
+def test_api_forcebuy(botclient, mocker, fee):
+    ftbot, client = botclient
+
+    rc = client_post(client, f"{BASE_URI}/forcebuy",
+                     data='{"pair": "ETH/BTC"}')
+    assert_response(rc, 502)
+    assert rc.json == {"error": "Error querying _forcebuy: Forcebuy not enabled."}
+
+    # enable forcebuy
+    ftbot.config['forcebuy_enable'] = True
+
+    fbuy_mock = MagicMock(return_value=None)
+    mocker.patch("freqtrade.rpc.RPC._rpc_forcebuy", fbuy_mock)
+    rc = client_post(client, f"{BASE_URI}/forcebuy",
+                     data='{"pair": "ETH/BTC"}')
+    assert_response(rc)
+    assert rc.json == {"status": "Error buying pair ETH/BTC."}
+
+    # Test creating trae
+    fbuy_mock = MagicMock(return_value=Trade(
+        pair='ETH/ETH',
+        amount=1,
+        amount_requested=1,
+        exchange='bittrex',
+        stake_amount=1,
+        open_rate=0.245441,
+        open_order_id="123456",
+        open_date=datetime.utcnow(),
+        is_open=False,
+        fee_close=fee.return_value,
+        fee_open=fee.return_value,
+        close_rate=0.265441,
+    ))
+    mocker.patch("freqtrade.rpc.RPC._rpc_forcebuy", fbuy_mock)
+
+    rc = client_post(client, f"{BASE_URI}/forcebuy",
+                     data='{"pair": "ETH/BTC"}')
+    assert_response(rc)
+    assert rc.json == {'amount': 1,
+                       'amount_requested': 1,
+                       'trade_id': None,
+                       'close_date': None,
+                       'close_date_hum': None,
+                       'close_timestamp': None,
+                       'close_rate': 0.265441,
+                       'open_date': ANY,
+                       'open_date_hum': 'just now',
+                       'open_timestamp': ANY,
+                       'open_rate': 0.245441,
+                       'pair': 'ETH/ETH',
+                       'stake_amount': 1,
+                       'stop_loss_abs': None,
+                       'stop_loss_pct': None,
+                       'stop_loss_ratio': None,
+                       'stoploss_order_id': None,
+                       'stoploss_last_update': None,
+                       'stoploss_last_update_timestamp': None,
+                       'initial_stop_loss_abs': None,
+                       'initial_stop_loss_pct': None,
+                       'initial_stop_loss_ratio': None,
+                       'close_profit': None,
+                       'close_profit_pct': None,
+                       'close_profit_abs': None,
+                       'close_rate_requested': None,
+                       'profit_ratio': None,
+                       'profit_pct': None,
+                       'profit_abs': None,
+                       'fee_close': 0.0025,
+                       'fee_close_cost': None,
+                       'fee_close_currency': None,
+                       'fee_open': 0.0025,
+                       'fee_open_cost': None,
+                       'fee_open_currency': None,
+                       'is_open': False,
+                       'max_rate': None,
+                       'min_rate': None,
+                       'open_order_id': '123456',
+                       'open_rate_requested': None,
+                       'open_trade_price': 0.24605460,
+                       'sell_reason': None,
+                       'sell_order_status': None,
+                       'strategy': None,
+                       'timeframe': None,
+                       'exchange': 'bittrex',
+                       }
+
+
+def test_api_forcesell(botclient, mocker, ticker, fee, markets):
+    ftbot, client = botclient
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balances=MagicMock(return_value=ticker),
+        fetch_ticker=ticker,
+        get_fee=fee,
+        markets=PropertyMock(return_value=markets)
+    )
+    patch_get_signal(ftbot, (True, False))
+
+    rc = client_post(client, f"{BASE_URI}/forcesell",
+                     data='{"tradeid": "1"}')
+    assert_response(rc, 502)
+    assert rc.json == {"error": "Error querying _forcesell: invalid argument"}
+
+    ftbot.enter_positions()
+
+    rc = client_post(client, f"{BASE_URI}/forcesell",
+                     data='{"tradeid": "1"}')
+    assert_response(rc)
+    assert rc.json == {'result': 'Created sell order for trade 1.'}
+
+
+def test_api_pair_candles(botclient, ohlcv_history):
+    ftbot, client = botclient
+    timeframe = '5m'
+    amount = 2
+
+    # No pair
+    rc = client_get(client,
+                    f"{BASE_URI}/pair_candles?limit={amount}&timeframe={timeframe}")
+    assert_response(rc, 400)
+
+    # No timeframe
+    rc = client_get(client,
+                    f"{BASE_URI}/pair_candles?pair=XRP%2FBTC")
+    assert_response(rc, 400)
+
+    rc = client_get(client,
+                    f"{BASE_URI}/pair_candles?limit={amount}&pair=XRP%2FBTC&timeframe={timeframe}")
+    assert_response(rc)
+    assert 'columns' in rc.json
+    assert 'data_start_ts' in rc.json
+    assert 'data_start' in rc.json
+    assert 'data_stop' in rc.json
+    assert 'data_stop_ts' in rc.json
+    assert len(rc.json['data']) == 0
+    ohlcv_history['sma'] = ohlcv_history['close'].rolling(2).mean()
+    ohlcv_history['buy'] = 0
+    ohlcv_history.loc[1, 'buy'] = 1
+    ohlcv_history['sell'] = 0
+
+    ftbot.dataprovider._set_cached_df("XRP/BTC", timeframe, ohlcv_history)
+
+    rc = client_get(client,
+                    f"{BASE_URI}/pair_candles?limit={amount}&pair=XRP%2FBTC&timeframe={timeframe}")
+    assert_response(rc)
+    assert 'strategy' in rc.json
+    assert rc.json['strategy'] == 'DefaultStrategy'
+    assert 'columns' in rc.json
+    assert 'data_start_ts' in rc.json
+    assert 'data_start' in rc.json
+    assert 'data_stop' in rc.json
+    assert 'data_stop_ts' in rc.json
+    assert rc.json['data_start'] == '2017-11-26 08:50:00+00:00'
+    assert rc.json['data_start_ts'] == 1511686200000
+    assert rc.json['data_stop'] == '2017-11-26 08:55:00+00:00'
+    assert rc.json['data_stop_ts'] == 1511686500000
+    assert isinstance(rc.json['columns'], list)
+    assert rc.json['columns'] == ['date', 'open', 'high',
+                                  'low', 'close', 'volume', 'sma', 'buy', 'sell',
+                                  '__date_ts', '_buy_signal_open', '_sell_signal_open']
+    assert 'pair' in rc.json
+    assert rc.json['pair'] == 'XRP/BTC'
+
+    assert 'data' in rc.json
+    assert len(rc.json['data']) == amount
+
+    assert (rc.json['data'] ==
+            [['2017-11-26 08:50:00', 8.794e-05, 8.948e-05, 8.794e-05, 8.88e-05, 0.0877869,
+              None, 0, 0, 1511686200000, None, None],
+             ['2017-11-26 08:55:00', 8.88e-05, 8.942e-05, 8.88e-05,
+                 8.893e-05, 0.05874751, 8.886500000000001e-05, 1, 0, 1511686500000, 8.88e-05, None]
+             ])
+
+
+def test_api_pair_history(botclient, ohlcv_history):
+    ftbot, client = botclient
+    timeframe = '5m'
+
+    # No pair
+    rc = client_get(client,
+                    f"{BASE_URI}/pair_history?timeframe={timeframe}"
+                    "&timerange=20180111-20180112&strategy=DefaultStrategy")
+    assert_response(rc, 400)
+
+    # No Timeframe
+    rc = client_get(client,
+                    f"{BASE_URI}/pair_history?pair=UNITTEST%2FBTC"
+                    "&timerange=20180111-20180112&strategy=DefaultStrategy")
+    assert_response(rc, 400)
+
+    # No timerange
+    rc = client_get(client,
+                    f"{BASE_URI}/pair_history?pair=UNITTEST%2FBTC&timeframe={timeframe}"
+                    "&strategy=DefaultStrategy")
+    assert_response(rc, 400)
+
+    # No strategy
+    rc = client_get(client,
+                    f"{BASE_URI}/pair_history?pair=UNITTEST%2FBTC&timeframe={timeframe}"
+                    "&timerange=20180111-20180112")
+    assert_response(rc, 400)
+
+    # Working
+    rc = client_get(client,
+                    f"{BASE_URI}/pair_history?pair=UNITTEST%2FBTC&timeframe={timeframe}"
+                    "&timerange=20180111-20180112&strategy=DefaultStrategy")
+    assert_response(rc, 200)
+    assert rc.json['length'] == 289
+    assert len(rc.json['data']) == rc.json['length']
+    assert 'columns' in rc.json
+    assert 'data' in rc.json
+    assert rc.json['pair'] == 'UNITTEST/BTC'
+    assert rc.json['strategy'] == 'DefaultStrategy'
+    assert rc.json['data_start'] == '2018-01-11 00:00:00+00:00'
+    assert rc.json['data_start_ts'] == 1515628800000
+    assert rc.json['data_stop'] == '2018-01-12 00:00:00+00:00'
+    assert rc.json['data_stop_ts'] == 1515715200000
+
+
+def test_api_plot_config(botclient):
+    ftbot, client = botclient
+
+    rc = client_get(client, f"{BASE_URI}/plot_config")
+    assert_response(rc)
+    assert rc.json == {}
+
+    ftbot.strategy.plot_config = {'main_plot': {'sma': {}},
+                                  'subplots': {'RSI': {'rsi': {'color': 'red'}}}}
+    rc = client_get(client, f"{BASE_URI}/plot_config")
+    assert_response(rc)
+    assert rc.json == ftbot.strategy.plot_config
+    assert isinstance(rc.json['main_plot'], dict)
+
+
+def test_api_strategies(botclient):
+    ftbot, client = botclient
+
+    rc = client_get(client, f"{BASE_URI}/strategies")
+
+    assert_response(rc)
+    assert rc.json == {'strategies': ['DefaultStrategy', 'TestStrategyLegacy']}
+
+
+def test_api_strategy(botclient):
+    ftbot, client = botclient
+
+    rc = client_get(client, f"{BASE_URI}/strategy/DefaultStrategy")
+
+    assert_response(rc)
+    assert rc.json['strategy'] == 'DefaultStrategy'
+
+    data = (Path(__file__).parents[1] / "strategy/strats/default_strategy.py").read_text()
+    assert rc.json['code'] == data
+
+    rc = client_get(client, f"{BASE_URI}/strategy/NoStrat")
+    assert_response(rc, 404)
+
+
+def test_list_available_pairs(botclient):
+    ftbot, client = botclient
+
+    rc = client_get(client, f"{BASE_URI}/available_pairs")
+
+    assert_response(rc)
+    assert rc.json['length'] == 12
+    assert isinstance(rc.json['pairs'], list)
+
+    rc = client_get(client, f"{BASE_URI}/available_pairs?timeframe=5m")
+    assert_response(rc)
+    assert rc.json['length'] == 12
+
+    rc = client_get(client, f"{BASE_URI}/available_pairs?stake_currency=ETH")
+    assert_response(rc)
+    assert rc.json['length'] == 1
+    assert rc.json['pairs'] == ['XRP/ETH']
+    assert len(rc.json['pair_interval']) == 2
+
+    rc = client_get(client, f"{BASE_URI}/available_pairs?stake_currency=ETH&timeframe=5m")
+    assert_response(rc)
+    assert rc.json['length'] == 1
+    assert rc.json['pairs'] == ['XRP/ETH']
+    assert len(rc.json['pair_interval']) == 1
diff --git a/freqtrade/tests/rpc/test_rpc_manager.py b/tests/rpc/test_rpc_manager.py
similarity index 78%
rename from freqtrade/tests/rpc/test_rpc_manager.py
rename to tests/rpc/test_rpc_manager.py
index 91fd2297f..4b715fc37 100644
--- a/freqtrade/tests/rpc/test_rpc_manager.py
+++ b/tests/rpc/test_rpc_manager.py
@@ -1,10 +1,10 @@
 # pragma pylint: disable=missing-docstring, C0103
-
 import logging
+import time
 from unittest.mock import MagicMock
 
-from freqtrade.rpc import RPCMessageType, RPCManager
-from freqtrade.tests.conftest import log_has, get_patched_freqtradebot
+from freqtrade.rpc import RPCManager, RPCMessageType
+from tests.conftest import get_patched_freqtradebot, log_has
 
 
 def test__init__(mocker, default_conf) -> None:
@@ -19,7 +19,7 @@ def test_init_telegram_disabled(mocker, default_conf, caplog) -> None:
     default_conf['telegram']['enabled'] = False
     rpc_manager = RPCManager(get_patched_freqtradebot(mocker, default_conf))
 
-    assert not log_has('Enabling rpc.telegram ...', caplog.record_tuples)
+    assert not log_has('Enabling rpc.telegram ...', caplog)
     assert rpc_manager.registered_modules == []
 
 
@@ -28,7 +28,7 @@ def test_init_telegram_enabled(mocker, default_conf, caplog) -> None:
     mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
     rpc_manager = RPCManager(get_patched_freqtradebot(mocker, default_conf))
 
-    assert log_has('Enabling rpc.telegram ...', caplog.record_tuples)
+    assert log_has('Enabling rpc.telegram ...', caplog)
     len_modules = len(rpc_manager.registered_modules)
     assert len_modules == 1
     assert 'telegram' in [mod.name for mod in rpc_manager.registered_modules]
@@ -43,7 +43,7 @@ def test_cleanup_telegram_disabled(mocker, default_conf, caplog) -> None:
     rpc_manager = RPCManager(freqtradebot)
     rpc_manager.cleanup()
 
-    assert not log_has('Cleaning up rpc.telegram ...', caplog.record_tuples)
+    assert not log_has('Cleaning up rpc.telegram ...', caplog)
     assert telegram_mock.call_count == 0
 
 
@@ -59,7 +59,7 @@ def test_cleanup_telegram_enabled(mocker, default_conf, caplog) -> None:
     assert 'telegram' in [mod.name for mod in rpc_manager.registered_modules]
 
     rpc_manager.cleanup()
-    assert log_has('Cleaning up rpc.telegram ...', caplog.record_tuples)
+    assert log_has('Cleaning up rpc.telegram ...', caplog)
     assert 'telegram' not in [mod.name for mod in rpc_manager.registered_modules]
     assert telegram_mock.call_count == 1
 
@@ -75,7 +75,7 @@ def test_send_msg_telegram_disabled(mocker, default_conf, caplog) -> None:
         'status': 'test'
     })
 
-    assert log_has("Sending rpc message: {'type': status, 'status': 'test'}", caplog.record_tuples)
+    assert log_has("Sending rpc message: {'type': status, 'status': 'test'}", caplog)
     assert telegram_mock.call_count == 0
 
 
@@ -90,7 +90,7 @@ def test_send_msg_telegram_enabled(mocker, default_conf, caplog) -> None:
         'status': 'test'
     })
 
-    assert log_has("Sending rpc message: {'type': status, 'status': 'test'}", caplog.record_tuples)
+    assert log_has("Sending rpc message: {'type': status, 'status': 'test'}", caplog)
     assert telegram_mock.call_count == 1
 
 
@@ -100,7 +100,7 @@ def test_init_webhook_disabled(mocker, default_conf, caplog) -> None:
     default_conf['webhook'] = {'enabled': False}
     rpc_manager = RPCManager(get_patched_freqtradebot(mocker, default_conf))
 
-    assert not log_has('Enabling rpc.webhook ...', caplog.record_tuples)
+    assert not log_has('Enabling rpc.webhook ...', caplog)
     assert rpc_manager.registered_modules == []
 
 
@@ -110,11 +110,27 @@ def test_init_webhook_enabled(mocker, default_conf, caplog) -> None:
     default_conf['webhook'] = {'enabled': True, 'url': "https://DEADBEEF.com"}
     rpc_manager = RPCManager(get_patched_freqtradebot(mocker, default_conf))
 
-    assert log_has('Enabling rpc.webhook ...', caplog.record_tuples)
+    assert log_has('Enabling rpc.webhook ...', caplog)
     assert len(rpc_manager.registered_modules) == 1
     assert 'webhook' in [mod.name for mod in rpc_manager.registered_modules]
 
 
+def test_send_msg_webhook_CustomMessagetype(mocker, default_conf, caplog) -> None:
+    caplog.set_level(logging.DEBUG)
+    default_conf['telegram']['enabled'] = False
+    default_conf['webhook'] = {'enabled': True, 'url': "https://DEADBEEF.com"}
+    mocker.patch('freqtrade.rpc.webhook.Webhook.send_msg',
+                 MagicMock(side_effect=NotImplementedError))
+    rpc_manager = RPCManager(get_patched_freqtradebot(mocker, default_conf))
+
+    assert 'webhook' in [mod.name for mod in rpc_manager.registered_modules]
+    rpc_manager.send_msg({'type': RPCMessageType.STARTUP_NOTIFICATION,
+                          'status': 'TestMessage'})
+    assert log_has(
+        "Message type 'startup' not implemented by handler webhook.",
+        caplog)
+
+
 def test_startupmessages_telegram_enabled(mocker, default_conf, caplog) -> None:
     telegram_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
     mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
@@ -144,7 +160,7 @@ def test_init_apiserver_disabled(mocker, default_conf, caplog) -> None:
     default_conf['telegram']['enabled'] = False
     rpc_manager = RPCManager(get_patched_freqtradebot(mocker, default_conf))
 
-    assert not log_has('Enabling rpc.api_server', caplog.record_tuples)
+    assert not log_has('Enabling rpc.api_server', caplog)
     assert rpc_manager.registered_modules == []
     assert run_mock.call_count == 0
 
@@ -157,10 +173,15 @@ def test_init_apiserver_enabled(mocker, default_conf, caplog) -> None:
     default_conf["telegram"]["enabled"] = False
     default_conf["api_server"] = {"enabled": True,
                                   "listen_ip_address": "127.0.0.1",
-                                  "listen_port": "8080"}
+                                  "listen_port": 8080,
+                                  "username": "TestUser",
+                                  "password": "TestPass",
+                                  }
     rpc_manager = RPCManager(get_patched_freqtradebot(mocker, default_conf))
 
-    assert log_has('Enabling rpc.api_server', caplog.record_tuples)
+    # Sleep to allow the thread to start
+    time.sleep(0.5)
+    assert log_has('Enabling rpc.api_server', caplog)
     assert len(rpc_manager.registered_modules) == 1
     assert 'apiserver' in [mod.name for mod in rpc_manager.registered_modules]
     assert run_mock.call_count == 1
diff --git a/freqtrade/tests/rpc/test_rpc_telegram.py b/tests/rpc/test_rpc_telegram.py
similarity index 59%
rename from freqtrade/tests/rpc/test_rpc_telegram.py
rename to tests/rpc/test_rpc_telegram.py
index 1bee5bff3..ace44a34a 100644
--- a/freqtrade/tests/rpc/test_rpc_telegram.py
+++ b/tests/rpc/test_rpc_telegram.py
@@ -6,7 +6,7 @@ import re
 from datetime import datetime
 from random import choice, randint
 from string import ascii_uppercase
-from unittest.mock import MagicMock, PropertyMock
+from unittest.mock import ANY, MagicMock, PropertyMock
 
 import arrow
 import pytest
@@ -14,15 +14,17 @@ from telegram import Chat, Message, Update
 from telegram.error import NetworkError
 
 from freqtrade import __version__
+from freqtrade.constants import CANCEL_REASON
 from freqtrade.edge import PairInfo
 from freqtrade.freqtradebot import FreqtradeBot
-from freqtrade.persistence import Trade
+from freqtrade.loggers import setup_logging
+from freqtrade.persistence import PairLocks, Trade
 from freqtrade.rpc import RPCMessageType
 from freqtrade.rpc.telegram import Telegram, authorized_only
-from freqtrade.state import State
+from freqtrade.state import RunMode, State
 from freqtrade.strategy.interface import SellType
-from freqtrade.tests.conftest import (get_patched_freqtradebot, log_has,
-                                      patch_exchange, patch_get_signal)
+from tests.conftest import (create_mock_trades, get_patched_freqtradebot, log_has, patch_exchange,
+                            patch_get_signal, patch_whitelist)
 
 
 class DummyCls(Telegram):
@@ -60,7 +62,7 @@ def test__init__(default_conf, mocker) -> None:
     assert telegram._config == default_conf
 
 
-def test_init(default_conf, mocker, caplog) -> None:
+def test_telegram_init(default_conf, mocker, caplog) -> None:
     start_polling = MagicMock()
     mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock(return_value=start_polling))
 
@@ -71,15 +73,16 @@ def test_init(default_conf, mocker, caplog) -> None:
     assert start_polling.dispatcher.add_handler.call_count > 0
     assert start_polling.start_polling.call_count == 1
 
-    message_str = "rpc.telegram is listening for following commands: [['status'], ['profit'], " \
-                  "['balance'], ['start'], ['stop'], ['forcesell'], ['forcebuy'], " \
-                  "['performance'], ['daily'], ['count'], ['reload_conf'], " \
-                  "['stopbuy'], ['whitelist'], ['blacklist'], ['edge'], ['help'], ['version']]"
+    message_str = ("rpc.telegram is listening for following commands: [['status'], ['profit'], "
+                   "['balance'], ['start'], ['stop'], ['forcesell'], ['forcebuy'], ['trades'], "
+                   "['delete'], ['performance'], ['daily'], ['count'], ['locks'], "
+                   "['reload_config', 'reload_conf'], ['show_config', 'show_conf'], ['stopbuy'], "
+                   "['whitelist'], ['blacklist'], ['logs'], ['edge'], ['help'], ['version']]")
 
-    assert log_has(message_str, caplog.record_tuples)
+    assert log_has(message_str, caplog)
 
 
-def test_cleanup(default_conf, mocker) -> None:
+def test_cleanup(default_conf, mocker, ) -> None:
     updater_mock = MagicMock()
     updater_mock.stop = MagicMock()
     mocker.patch('freqtrade.rpc.telegram.Updater', updater_mock)
@@ -89,99 +92,58 @@ def test_cleanup(default_conf, mocker) -> None:
     assert telegram._updater.stop.call_count == 1
 
 
-def test_authorized_only(default_conf, mocker, caplog) -> None:
-    patch_exchange(mocker, None)
-
-    chat = Chat(0, 0)
-    update = Update(randint(1, 100))
-    update.message = Message(randint(1, 100), 0, datetime.utcnow(), chat)
+def test_authorized_only(default_conf, mocker, caplog, update) -> None:
+    patch_exchange(mocker)
 
     default_conf['telegram']['enabled'] = False
     bot = FreqtradeBot(default_conf)
     patch_get_signal(bot, (True, False))
     dummy = DummyCls(bot)
-    dummy.dummy_handler(bot=MagicMock(), update=update)
+    dummy.dummy_handler(update=update, context=MagicMock())
     assert dummy.state['called'] is True
-    assert log_has(
-        'Executing handler: dummy_handler for chat_id: 0',
-        caplog.record_tuples
-    )
-    assert not log_has(
-        'Rejected unauthorized message from: 0',
-        caplog.record_tuples
-    )
-    assert not log_has(
-        'Exception occurred within Telegram module',
-        caplog.record_tuples
-    )
+    assert log_has('Executing handler: dummy_handler for chat_id: 0', caplog)
+    assert not log_has('Rejected unauthorized message from: 0', caplog)
+    assert not log_has('Exception occurred within Telegram module', caplog)
 
 
 def test_authorized_only_unauthorized(default_conf, mocker, caplog) -> None:
-    patch_exchange(mocker, None)
+    patch_exchange(mocker)
     chat = Chat(0xdeadbeef, 0)
     update = Update(randint(1, 100))
-    update.message = Message(randint(1, 100), 0, datetime.utcnow(), chat)
+    update.message = Message(randint(1, 100), datetime.utcnow(), chat)
 
     default_conf['telegram']['enabled'] = False
     bot = FreqtradeBot(default_conf)
     patch_get_signal(bot, (True, False))
     dummy = DummyCls(bot)
-    dummy.dummy_handler(bot=MagicMock(), update=update)
+    dummy.dummy_handler(update=update, context=MagicMock())
     assert dummy.state['called'] is False
-    assert not log_has(
-        'Executing handler: dummy_handler for chat_id: 3735928559',
-        caplog.record_tuples
-    )
-    assert log_has(
-        'Rejected unauthorized message from: 3735928559',
-        caplog.record_tuples
-    )
-    assert not log_has(
-        'Exception occurred within Telegram module',
-        caplog.record_tuples
-    )
+    assert not log_has('Executing handler: dummy_handler for chat_id: 3735928559', caplog)
+    assert log_has('Rejected unauthorized message from: 3735928559', caplog)
+    assert not log_has('Exception occurred within Telegram module', caplog)
 
 
-def test_authorized_only_exception(default_conf, mocker, caplog) -> None:
+def test_authorized_only_exception(default_conf, mocker, caplog, update) -> None:
     patch_exchange(mocker)
 
-    update = Update(randint(1, 100))
-    update.message = Message(randint(1, 100), 0, datetime.utcnow(), Chat(0, 0))
-
     default_conf['telegram']['enabled'] = False
 
     bot = FreqtradeBot(default_conf)
     patch_get_signal(bot, (True, False))
     dummy = DummyCls(bot)
 
-    dummy.dummy_exception(bot=MagicMock(), update=update)
+    dummy.dummy_exception(update=update, context=MagicMock())
     assert dummy.state['called'] is False
-    assert not log_has(
-        'Executing handler: dummy_handler for chat_id: 0',
-        caplog.record_tuples
-    )
-    assert not log_has(
-        'Rejected unauthorized message from: 0',
-        caplog.record_tuples
-    )
-    assert log_has(
-        'Exception occurred within Telegram module',
-        caplog.record_tuples
-    )
+    assert not log_has('Executing handler: dummy_handler for chat_id: 0', caplog)
+    assert not log_has('Rejected unauthorized message from: 0', caplog)
+    assert log_has('Exception occurred within Telegram module', caplog)
 
 
-def test_status(default_conf, update, mocker, fee, ticker, markets) -> None:
-    update.message.chat.id = 123
+def test_telegram_status(default_conf, update, mocker) -> None:
+    update.message.chat.id = "123"
     default_conf['telegram']['enabled'] = False
-    default_conf['telegram']['chat_id'] = 123
+    default_conf['telegram']['chat_id'] = "123"
 
-    patch_exchange(mocker)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        get_fee=fee,
-        markets=PropertyMock(markets)
-    )
     msg_mock = MagicMock()
     status_table = MagicMock()
     mocker.patch.multiple(
@@ -200,43 +162,41 @@ def test_status(default_conf, update, mocker, fee, ticker, markets) -> None:
             'current_rate': 1.098e-05,
             'amount': 90.99181074,
             'stake_amount': 90.99181074,
-            'close_profit': None,
-            'current_profit': -0.59,
-            'initial_stop_loss': 1.098e-05,
-            'stop_loss': 1.099e-05,
+            'close_profit_pct': None,
+            'profit': -0.0059,
+            'profit_pct': -0.59,
+            'initial_stop_loss_abs': 1.098e-05,
+            'stop_loss_abs': 1.099e-05,
+            'sell_order_status': None,
             'initial_stop_loss_pct': -0.05,
+            'stoploss_current_dist': 1e-08,
+            'stoploss_current_dist_pct': -0.02,
             'stop_loss_pct': -0.01,
-            'open_order': '(limit buy rem=0.00000000)'
+            'open_order': '(limit buy rem=0.00000000)',
+            'is_open': True
         }]),
         _status_table=status_table,
         _send_msg=msg_mock
     )
-    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
 
-    freqtradebot = FreqtradeBot(default_conf)
-    patch_get_signal(freqtradebot, (True, False))
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     telegram = Telegram(freqtradebot)
 
-    # Create some test data
-    for _ in range(3):
-        freqtradebot.create_trade()
-
-    telegram._status(bot=MagicMock(), update=update)
+    telegram._status(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
 
-    update.message.text = MagicMock()
-    update.message.text.replace = MagicMock(return_value='table 2 3')
-    telegram._status(bot=MagicMock(), update=update)
+    context = MagicMock()
+    # /status table 2 3
+    context.args = ["table", "2", "3"]
+    telegram._status(update=update, context=context)
     assert status_table.call_count == 1
 
 
-def test_status_handle(default_conf, update, ticker, fee, markets, mocker) -> None:
-    patch_exchange(mocker)
+def test_status_handle(default_conf, update, ticker, fee, mocker) -> None:
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(markets)
     )
     msg_mock = MagicMock()
     status_table = MagicMock()
@@ -246,30 +206,30 @@ def test_status_handle(default_conf, update, ticker, fee, markets, mocker) -> No
         _status_table=status_table,
         _send_msg=msg_mock
     )
-    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+
     patch_get_signal(freqtradebot, (True, False))
 
     telegram = Telegram(freqtradebot)
 
     freqtradebot.state = State.STOPPED
     # Status is also enabled when stopped
-    telegram._status(bot=MagicMock(), update=update)
+    telegram._status(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
     assert 'no active trade' in msg_mock.call_args_list[0][0][0]
     msg_mock.reset_mock()
 
     freqtradebot.state = State.RUNNING
-    telegram._status(bot=MagicMock(), update=update)
+    telegram._status(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
     assert 'no active trade' in msg_mock.call_args_list[0][0][0]
     msg_mock.reset_mock()
 
     # Create some test data
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
     # Trigger status while we have a fulfilled order for the open trade
-    telegram._status(bot=MagicMock(), update=update)
+    telegram._status(update=update, context=MagicMock())
 
     # close_rate should not be included in the message as the trade is not closed
     # and no line should be empty
@@ -282,14 +242,11 @@ def test_status_handle(default_conf, update, ticker, fee, markets, mocker) -> No
     assert 'ETH/BTC' in msg_mock.call_args_list[0][0][0]
 
 
-def test_status_table_handle(default_conf, update, ticker, fee, markets, mocker) -> None:
-    patch_exchange(mocker)
+def test_status_table_handle(default_conf, update, ticker, fee, mocker) -> None:
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': 'mocked_order_id'}),
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(markets)
     )
     msg_mock = MagicMock()
     mocker.patch.multiple(
@@ -297,53 +254,51 @@ def test_status_table_handle(default_conf, update, ticker, fee, markets, mocker)
         _init=MagicMock(),
         _send_msg=msg_mock
     )
-    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
 
     default_conf['stake_amount'] = 15.0
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
 
     telegram = Telegram(freqtradebot)
 
     freqtradebot.state = State.STOPPED
     # Status table is also enabled when stopped
-    telegram._status_table(bot=MagicMock(), update=update)
+    telegram._status_table(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
-    assert 'no active order' in msg_mock.call_args_list[0][0][0]
+    assert 'no active trade' in msg_mock.call_args_list[0][0][0]
     msg_mock.reset_mock()
 
     freqtradebot.state = State.RUNNING
-    telegram._status_table(bot=MagicMock(), update=update)
+    telegram._status_table(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
-    assert 'no active order' in msg_mock.call_args_list[0][0][0]
+    assert 'no active trade' in msg_mock.call_args_list[0][0][0]
     msg_mock.reset_mock()
 
     # Create some test data
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
 
-    telegram._status_table(bot=MagicMock(), update=update)
+    telegram._status_table(update=update, context=MagicMock())
 
     text = re.sub('</?pre>', '', msg_mock.call_args_list[-1][0][0])
     line = text.split("\n")
     fields = re.sub('[ ]+', ' ', line[2].strip()).split(' ')
 
     assert int(fields[0]) == 1
-    assert fields[1] == 'ETH/BTC'
+    assert 'ETH/BTC' in fields[1]
     assert msg_mock.call_count == 1
 
 
 def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
-                      limit_sell_order, markets, mocker) -> None:
-    patch_exchange(mocker)
+                      limit_sell_order, mocker) -> None:
+    default_conf['max_open_trades'] = 1
     mocker.patch(
         'freqtrade.rpc.rpc.CryptoToFiatConverter._find_price',
         return_value=15000.0
     )
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(markets)
     )
     msg_mock = MagicMock()
     mocker.patch.multiple(
@@ -351,14 +306,13 @@ def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
         _init=MagicMock(),
         _send_msg=msg_mock
     )
-    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     telegram = Telegram(freqtradebot)
 
     # Create some test data
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
     trade = Trade.query.first()
     assert trade
 
@@ -372,8 +326,10 @@ def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
     trade.is_open = False
 
     # Try valid data
-    update.message.text = '/daily 2'
-    telegram._daily(bot=MagicMock(), update=update)
+    # /daily 2
+    context = MagicMock()
+    context.args = ["2"]
+    telegram._daily(update=update, context=context)
     assert msg_mock.call_count == 1
     assert 'Daily' in msg_mock.call_args_list[0][0][0]
     assert str(datetime.utcnow().date()) in msg_mock.call_args_list[0][0][0]
@@ -384,9 +340,10 @@ def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
 
     # Reset msg_mock
     msg_mock.reset_mock()
+    freqtradebot.config['max_open_trades'] = 2
     # Add two other trades
-    freqtradebot.create_trade()
-    freqtradebot.create_trade()
+    n = freqtradebot.enter_positions()
+    assert n == 2
 
     trades = Trade.query.all()
     for trade in trades:
@@ -395,19 +352,19 @@ def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
         trade.close_date = datetime.utcnow()
         trade.is_open = False
 
-    update.message.text = '/daily 1'
-
-    telegram._daily(bot=MagicMock(), update=update)
+    # /daily 1
+    context = MagicMock()
+    context.args = ["1"]
+    telegram._daily(update=update, context=context)
     assert str('  0.00018651 BTC') in msg_mock.call_args_list[0][0][0]
     assert str('  2.798 USD') in msg_mock.call_args_list[0][0][0]
     assert str('  3 trades') in msg_mock.call_args_list[0][0][0]
 
 
 def test_daily_wrong_input(default_conf, update, ticker, mocker) -> None:
-    patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker
+        fetch_ticker=ticker
     )
     msg_mock = MagicMock()
     mocker.patch.multiple(
@@ -415,37 +372,38 @@ def test_daily_wrong_input(default_conf, update, ticker, mocker) -> None:
         _init=MagicMock(),
         _send_msg=msg_mock
     )
-    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     telegram = Telegram(freqtradebot)
 
     # Try invalid data
     msg_mock.reset_mock()
     freqtradebot.state = State.RUNNING
-    update.message.text = '/daily -2'
-    telegram._daily(bot=MagicMock(), update=update)
+    # /daily -2
+    context = MagicMock()
+    context.args = ["-2"]
+    telegram._daily(update=update, context=context)
     assert msg_mock.call_count == 1
     assert 'must be an integer greater than 0' in msg_mock.call_args_list[0][0][0]
 
     # Try invalid data
     msg_mock.reset_mock()
     freqtradebot.state = State.RUNNING
-    update.message.text = '/daily today'
-    telegram._daily(bot=MagicMock(), update=update)
+    # /daily today
+    context = MagicMock()
+    context.args = ["today"]
+    telegram._daily(update=update, context=context)
     assert str('Daily Profit over the last 7 days') in msg_mock.call_args_list[0][0][0]
 
 
 def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
-                       limit_buy_order, limit_sell_order, markets, mocker) -> None:
-    patch_exchange(mocker)
+                       limit_buy_order, limit_sell_order, mocker) -> None:
     mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(markets)
     )
     msg_mock = MagicMock()
     mocker.patch.multiple(
@@ -453,71 +411,56 @@ def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
         _init=MagicMock(),
         _send_msg=msg_mock
     )
-    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     telegram = Telegram(freqtradebot)
 
-    telegram._profit(bot=MagicMock(), update=update)
+    telegram._profit(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
-    assert 'no closed trade' in msg_mock.call_args_list[0][0][0]
+    assert 'No trades yet.' in msg_mock.call_args_list[0][0][0]
     msg_mock.reset_mock()
 
     # Create some test data
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
     trade = Trade.query.first()
 
     # Simulate fulfilled LIMIT_BUY order for trade
     trade.update(limit_buy_order)
 
-    telegram._profit(bot=MagicMock(), update=update)
+    telegram._profit(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
-    assert 'no closed trade' in msg_mock.call_args_list[-1][0][0]
+    assert 'No closed trade' in msg_mock.call_args_list[-1][0][0]
+    assert '*ROI:* All trades' in msg_mock.call_args_list[-1][0][0]
+    assert ('∙ `-0.00000500 BTC (-0.50%) (-0.5 \N{GREEK CAPITAL LETTER SIGMA}%)`'
+            in msg_mock.call_args_list[-1][0][0])
     msg_mock.reset_mock()
 
     # Update the ticker with a market going up
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker', ticker_sell_up)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', ticker_sell_up)
     trade.update(limit_sell_order)
 
     trade.close_date = datetime.utcnow()
     trade.is_open = False
 
-    telegram._profit(bot=MagicMock(), update=update)
+    telegram._profit(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
-    assert '*ROI:* Close trades' in msg_mock.call_args_list[-1][0][0]
-    assert '∙ `0.00006217 BTC (6.20%)`' in msg_mock.call_args_list[-1][0][0]
+    assert '*ROI:* Closed trades' in msg_mock.call_args_list[-1][0][0]
+    assert ('∙ `0.00006217 BTC (6.20%) (6.2 \N{GREEK CAPITAL LETTER SIGMA}%)`'
+            in msg_mock.call_args_list[-1][0][0])
     assert '∙ `0.933 USD`' in msg_mock.call_args_list[-1][0][0]
     assert '*ROI:* All trades' in msg_mock.call_args_list[-1][0][0]
-    assert '∙ `0.00006217 BTC (6.20%)`' in msg_mock.call_args_list[-1][0][0]
+    assert ('∙ `0.00006217 BTC (6.20%) (6.2 \N{GREEK CAPITAL LETTER SIGMA}%)`'
+            in msg_mock.call_args_list[-1][0][0])
     assert '∙ `0.933 USD`' in msg_mock.call_args_list[-1][0][0]
 
     assert '*Best Performing:* `ETH/BTC: 6.20%`' in msg_mock.call_args_list[-1][0][0]
 
 
-def test_telegram_balance_handle(default_conf, update, mocker, rpc_balance) -> None:
-
-    def mock_ticker(symbol, refresh):
-        if symbol == 'BTC/USDT':
-            return {
-                'bid': 10000.00,
-                'ask': 10000.00,
-                'last': 10000.00,
-            }
-        elif symbol == 'XRP/BTC':
-            return {
-                'bid': 0.00001,
-                'ask': 0.00001,
-                'last': 0.00001,
-            }
-        return {
-            'bid': 0.1,
-            'ask': 0.1,
-            'last': 0.1,
-        }
-
+def test_telegram_balance_handle(default_conf, update, mocker, rpc_balance, tickers) -> None:
+    default_conf['dry_run'] = False
     mocker.patch('freqtrade.exchange.Exchange.get_balances', return_value=rpc_balance)
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker', side_effect=mock_ticker)
+    mocker.patch('freqtrade.exchange.Exchange.get_tickers', tickers)
     mocker.patch('freqtrade.exchange.Exchange.get_valid_pair_combination',
                  side_effect=lambda a, b: f"{a}/{b}")
 
@@ -533,7 +476,7 @@ def test_telegram_balance_handle(default_conf, update, mocker, rpc_balance) -> N
 
     telegram = Telegram(freqtradebot)
 
-    telegram._balance(bot=MagicMock(), update=update)
+    telegram._balance(update=update, context=MagicMock())
     result = msg_mock.call_args_list[0][0][0]
     assert msg_mock.call_count == 1
     assert '*BTC:*' in result
@@ -547,6 +490,7 @@ def test_telegram_balance_handle(default_conf, update, mocker, rpc_balance) -> N
 
 
 def test_balance_handle_empty_response(default_conf, update, mocker) -> None:
+    default_conf['dry_run'] = False
     mocker.patch('freqtrade.exchange.Exchange.get_balances', return_value={})
 
     msg_mock = MagicMock()
@@ -562,7 +506,7 @@ def test_balance_handle_empty_response(default_conf, update, mocker) -> None:
     telegram = Telegram(freqtradebot)
 
     freqtradebot.config['dry_run'] = False
-    telegram._balance(bot=MagicMock(), update=update)
+    telegram._balance(update=update, context=MagicMock())
     result = msg_mock.call_args_list[0][0][0]
     assert msg_mock.call_count == 1
     assert 'All balances are zero.' in result
@@ -583,10 +527,11 @@ def test_balance_handle_empty_response_dry(default_conf, update, mocker) -> None
 
     telegram = Telegram(freqtradebot)
 
-    telegram._balance(bot=MagicMock(), update=update)
+    telegram._balance(update=update, context=MagicMock())
     result = msg_mock.call_args_list[0][0][0]
     assert msg_mock.call_count == 1
-    assert "Running in Dry Run, balances are not available." in result
+    assert "*Warning:* Simulated balances in Dry Mode." in result
+    assert "Starting capital: `1000` BTC" in result
 
 
 def test_balance_handle_too_large_response(default_conf, update, mocker) -> None:
@@ -595,10 +540,11 @@ def test_balance_handle_too_large_response(default_conf, update, mocker) -> None
         curr = choice(ascii_uppercase) + choice(ascii_uppercase) + choice(ascii_uppercase)
         balances.append({
             'currency': curr,
-            'available': 1.0,
-            'pending': 0.5,
+            'free': 1.0,
+            'used': 0.5,
             'balance': i,
-            'est_btc': 1
+            'est_stake': 1,
+            'stake': 'BTC',
         })
     mocker.patch('freqtrade.rpc.rpc.RPC._rpc_balance', return_value={
         'currencies': balances,
@@ -619,7 +565,7 @@ def test_balance_handle_too_large_response(default_conf, update, mocker) -> None
 
     telegram = Telegram(freqtradebot)
 
-    telegram._balance(bot=MagicMock(), update=update)
+    telegram._balance(update=update, context=MagicMock())
     assert msg_mock.call_count > 1
     # Test if wrap happens around 4000 -
     # and each single currency-output is around 120 characters long so we need
@@ -641,7 +587,7 @@ def test_start_handle(default_conf, update, mocker) -> None:
 
     freqtradebot.state = State.STOPPED
     assert freqtradebot.state == State.STOPPED
-    telegram._start(bot=MagicMock(), update=update)
+    telegram._start(update=update, context=MagicMock())
     assert freqtradebot.state == State.RUNNING
     assert msg_mock.call_count == 1
 
@@ -659,7 +605,7 @@ def test_start_handle_already_running(default_conf, update, mocker) -> None:
 
     freqtradebot.state = State.RUNNING
     assert freqtradebot.state == State.RUNNING
-    telegram._start(bot=MagicMock(), update=update)
+    telegram._start(update=update, context=MagicMock())
     assert freqtradebot.state == State.RUNNING
     assert msg_mock.call_count == 1
     assert 'already running' in msg_mock.call_args_list[0][0][0]
@@ -678,7 +624,7 @@ def test_stop_handle(default_conf, update, mocker) -> None:
 
     freqtradebot.state = State.RUNNING
     assert freqtradebot.state == State.RUNNING
-    telegram._stop(bot=MagicMock(), update=update)
+    telegram._stop(update=update, context=MagicMock())
     assert freqtradebot.state == State.STOPPED
     assert msg_mock.call_count == 1
     assert 'stopping trader' in msg_mock.call_args_list[0][0][0]
@@ -697,7 +643,7 @@ def test_stop_handle_already_stopped(default_conf, update, mocker) -> None:
 
     freqtradebot.state = State.STOPPED
     assert freqtradebot.state == State.STOPPED
-    telegram._stop(bot=MagicMock(), update=update)
+    telegram._stop(update=update, context=MagicMock())
     assert freqtradebot.state == State.STOPPED
     assert msg_mock.call_count == 1
     assert 'already stopped' in msg_mock.call_args_list[0][0][0]
@@ -715,14 +661,14 @@ def test_stopbuy_handle(default_conf, update, mocker) -> None:
     telegram = Telegram(freqtradebot)
 
     assert freqtradebot.config['max_open_trades'] != 0
-    telegram._stopbuy(bot=MagicMock(), update=update)
+    telegram._stopbuy(update=update, context=MagicMock())
     assert freqtradebot.config['max_open_trades'] == 0
     assert msg_mock.call_count == 1
-    assert 'No more buy will occur from now. Run /reload_conf to reset.' \
+    assert 'No more buy will occur from now. Run /reload_config to reset.' \
         in msg_mock.call_args_list[0][0][0]
 
 
-def test_reload_conf_handle(default_conf, update, mocker) -> None:
+def test_reload_config_handle(default_conf, update, mocker) -> None:
     msg_mock = MagicMock()
     mocker.patch.multiple(
         'freqtrade.rpc.telegram.Telegram',
@@ -735,24 +681,23 @@ def test_reload_conf_handle(default_conf, update, mocker) -> None:
 
     freqtradebot.state = State.RUNNING
     assert freqtradebot.state == State.RUNNING
-    telegram._reload_conf(bot=MagicMock(), update=update)
-    assert freqtradebot.state == State.RELOAD_CONF
+    telegram._reload_config(update=update, context=MagicMock())
+    assert freqtradebot.state == State.RELOAD_CONFIG
     assert msg_mock.call_count == 1
-    assert 'reloading config' in msg_mock.call_args_list[0][0][0]
+    assert 'Reloading config' in msg_mock.call_args_list[0][0][0]
 
 
-def test_forcesell_handle(default_conf, update, ticker, fee,
-                          ticker_sell_up, markets, mocker) -> None:
+def test_telegram_forcesell_handle(default_conf, update, ticker, fee,
+                                   ticker_sell_up, mocker) -> None:
     mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
     rpc_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
     mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
+    patch_exchange(mocker)
+    patch_whitelist(mocker, default_conf)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        _load_markets=MagicMock(return_value={}),
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(return_value=markets),
-        validate_pairs=MagicMock(return_value={})
     )
 
     freqtradebot = FreqtradeBot(default_conf)
@@ -760,50 +705,55 @@ def test_forcesell_handle(default_conf, update, ticker, fee,
     telegram = Telegram(freqtradebot)
 
     # Create some test data
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
 
     trade = Trade.query.first()
     assert trade
 
     # Increase the price and sell it
-    mocker.patch('freqtrade.exchange.Exchange.get_ticker', ticker_sell_up)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', ticker_sell_up)
 
-    update.message.text = '/forcesell 1'
-    telegram._forcesell(bot=MagicMock(), update=update)
+    # /forcesell 1
+    context = MagicMock()
+    context.args = ["1"]
+    telegram._forcesell(update=update, context=context)
 
-    assert rpc_mock.call_count == 2
+    assert rpc_mock.call_count == 3
     last_msg = rpc_mock.call_args_list[-1][0][0]
     assert {
         'type': RPCMessageType.SELL_NOTIFICATION,
+        'trade_id': 1,
         'exchange': 'Bittrex',
         'pair': 'ETH/BTC',
         'gain': 'profit',
-        'limit': 1.172e-05,
-        'amount': 90.99181073703367,
+        'limit': 1.173e-05,
+        'amount': 91.07468123,
         'order_type': 'limit',
-        'open_rate': 1.099e-05,
-        'current_rate': 1.172e-05,
-        'profit_amount': 6.126e-05,
-        'profit_percent': 0.0611052,
+        'open_rate': 1.098e-05,
+        'current_rate': 1.173e-05,
+        'profit_amount': 6.314e-05,
+        'profit_ratio': 0.0629778,
         'stake_currency': 'BTC',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.FORCE_SELL.value
+        'sell_reason': SellType.FORCE_SELL.value,
+        'open_date': ANY,
+        'close_date': ANY,
     } == last_msg
 
 
-def test_forcesell_down_handle(default_conf, update, ticker, fee,
-                               ticker_sell_down, markets, mocker) -> None:
+def test_telegram_forcesell_down_handle(default_conf, update, ticker, fee,
+                                        ticker_sell_down, mocker) -> None:
     mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._find_price',
                  return_value=15000.0)
     rpc_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
     mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
+    patch_exchange(mocker)
+    patch_whitelist(mocker, default_conf)
+
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        _load_markets=MagicMock(return_value={}),
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(return_value=markets),
-        validate_pairs=MagicMock(return_value={})
     )
 
     freqtradebot = FreqtradeBot(default_conf)
@@ -811,84 +761,93 @@ def test_forcesell_down_handle(default_conf, update, ticker, fee,
     telegram = Telegram(freqtradebot)
 
     # Create some test data
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
 
     # Decrease the price and sell it
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker_sell_down
+        fetch_ticker=ticker_sell_down
     )
 
     trade = Trade.query.first()
     assert trade
 
-    update.message.text = '/forcesell 1'
-    telegram._forcesell(bot=MagicMock(), update=update)
+    # /forcesell 1
+    context = MagicMock()
+    context.args = ["1"]
+    telegram._forcesell(update=update, context=context)
 
-    assert rpc_mock.call_count == 2
+    assert rpc_mock.call_count == 3
 
     last_msg = rpc_mock.call_args_list[-1][0][0]
     assert {
         'type': RPCMessageType.SELL_NOTIFICATION,
+        'trade_id': 1,
         'exchange': 'Bittrex',
         'pair': 'ETH/BTC',
         'gain': 'loss',
-        'limit': 1.044e-05,
-        'amount': 90.99181073703367,
+        'limit': 1.043e-05,
+        'amount': 91.07468123,
         'order_type': 'limit',
-        'open_rate': 1.099e-05,
-        'current_rate': 1.044e-05,
-        'profit_amount': -5.492e-05,
-        'profit_percent': -0.05478342,
+        'open_rate': 1.098e-05,
+        'current_rate': 1.043e-05,
+        'profit_amount': -5.497e-05,
+        'profit_ratio': -0.05482878,
         'stake_currency': 'BTC',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.FORCE_SELL.value
+        'sell_reason': SellType.FORCE_SELL.value,
+        'open_date': ANY,
+        'close_date': ANY,
     } == last_msg
 
 
-def test_forcesell_all_handle(default_conf, update, ticker, fee, markets, mocker) -> None:
+def test_forcesell_all_handle(default_conf, update, ticker, fee, mocker) -> None:
     patch_exchange(mocker)
     mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._find_price',
                  return_value=15000.0)
     rpc_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
     mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
+    patch_whitelist(mocker, default_conf)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(return_value=markets),
-        validate_pairs=MagicMock(return_value={})
     )
-
+    default_conf['max_open_trades'] = 4
     freqtradebot = FreqtradeBot(default_conf)
     patch_get_signal(freqtradebot, (True, False))
     telegram = Telegram(freqtradebot)
 
     # Create some test data
-    for _ in range(4):
-        freqtradebot.create_trade()
+    freqtradebot.enter_positions()
     rpc_mock.reset_mock()
 
-    update.message.text = '/forcesell all'
-    telegram._forcesell(bot=MagicMock(), update=update)
+    # /forcesell all
+    context = MagicMock()
+    context.args = ["all"]
+    telegram._forcesell(update=update, context=context)
 
-    assert rpc_mock.call_count == 4
-    msg = rpc_mock.call_args_list[0][0][0]
+    # Called for each trade 3 times
+    assert rpc_mock.call_count == 8
+    msg = rpc_mock.call_args_list[1][0][0]
     assert {
         'type': RPCMessageType.SELL_NOTIFICATION,
+        'trade_id': 1,
         'exchange': 'Bittrex',
         'pair': 'ETH/BTC',
         'gain': 'loss',
-        'limit': 1.098e-05,
-        'amount': 90.99181073703367,
+        'limit': 1.099e-05,
+        'amount': 91.07468123,
         'order_type': 'limit',
-        'open_rate': 1.099e-05,
-        'current_rate': 1.098e-05,
-        'profit_amount': -5.91e-06,
-        'profit_percent': -0.00589291,
+        'open_rate': 1.098e-05,
+        'current_rate': 1.099e-05,
+        'profit_amount': -4.09e-06,
+        'profit_ratio': -0.00408133,
         'stake_currency': 'BTC',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.FORCE_SELL.value
+        'sell_reason': SellType.FORCE_SELL.value,
+        'open_date': ANY,
+        'close_date': ANY,
     } == msg
 
 
@@ -901,32 +860,36 @@ def test_forcesell_handle_invalid(default_conf, update, mocker) -> None:
         _init=MagicMock(),
         _send_msg=msg_mock
     )
-    patch_exchange(mocker)
 
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     telegram = Telegram(freqtradebot)
 
     # Trader is not running
     freqtradebot.state = State.STOPPED
-    update.message.text = '/forcesell 1'
-    telegram._forcesell(bot=MagicMock(), update=update)
+    # /forcesell 1
+    context = MagicMock()
+    context.args = ["1"]
+    telegram._forcesell(update=update, context=context)
     assert msg_mock.call_count == 1
     assert 'not running' in msg_mock.call_args_list[0][0][0]
 
     # No argument
     msg_mock.reset_mock()
     freqtradebot.state = State.RUNNING
-    update.message.text = '/forcesell'
-    telegram._forcesell(bot=MagicMock(), update=update)
+    context = MagicMock()
+    context.args = []
+    telegram._forcesell(update=update, context=context)
     assert msg_mock.call_count == 1
     assert 'invalid argument' in msg_mock.call_args_list[0][0][0]
 
     # Invalid argument
     msg_mock.reset_mock()
     freqtradebot.state = State.RUNNING
-    update.message.text = '/forcesell 123456'
-    telegram._forcesell(bot=MagicMock(), update=update)
+    # /forcesell 123456
+    context = MagicMock()
+    context.args = ["123456"]
+    telegram._forcesell(update=update, context=context)
     assert msg_mock.call_count == 1
     assert 'invalid argument' in msg_mock.call_args_list[0][0][0]
 
@@ -935,11 +898,10 @@ def test_forcebuy_handle(default_conf, update, markets, mocker) -> None:
     mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
     mocker.patch('freqtrade.rpc.telegram.Telegram._send_msg', MagicMock())
     mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
+    patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        _load_markets=MagicMock(return_value={}),
         markets=PropertyMock(markets),
-        validate_pairs=MagicMock(return_value={})
         )
     fbuy_mock = MagicMock(return_value=None)
     mocker.patch('freqtrade.rpc.RPC._rpc_forcebuy', fbuy_mock)
@@ -948,8 +910,10 @@ def test_forcebuy_handle(default_conf, update, markets, mocker) -> None:
     patch_get_signal(freqtradebot, (True, False))
     telegram = Telegram(freqtradebot)
 
-    update.message.text = '/forcebuy ETH/BTC'
-    telegram._forcebuy(bot=MagicMock(), update=update)
+    # /forcebuy ETH/BTC
+    context = MagicMock()
+    context.args = ["ETH/BTC"]
+    telegram._forcebuy(update=update, context=context)
 
     assert fbuy_mock.call_count == 1
     assert fbuy_mock.call_args_list[0][0][0] == 'ETH/BTC'
@@ -958,8 +922,10 @@ def test_forcebuy_handle(default_conf, update, markets, mocker) -> None:
     # Reset and retry with specified price
     fbuy_mock = MagicMock(return_value=None)
     mocker.patch('freqtrade.rpc.RPC._rpc_forcebuy', fbuy_mock)
-    update.message.text = '/forcebuy ETH/BTC 0.055'
-    telegram._forcebuy(bot=MagicMock(), update=update)
+    # /forcebuy ETH/BTC 0.055
+    context = MagicMock()
+    context.args = ["ETH/BTC", "0.055"]
+    telegram._forcebuy(update=update, context=context)
 
     assert fbuy_mock.call_count == 1
     assert fbuy_mock.call_args_list[0][0][0] == 'ETH/BTC'
@@ -971,26 +937,24 @@ def test_forcebuy_handle_exception(default_conf, update, markets, mocker) -> Non
     mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
     rpc_mock = mocker.patch('freqtrade.rpc.telegram.Telegram._send_msg', MagicMock())
     mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
+    patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        _load_markets=MagicMock(return_value={}),
         markets=PropertyMock(markets),
-        validate_pairs=MagicMock(return_value={})
     )
     freqtradebot = FreqtradeBot(default_conf)
     patch_get_signal(freqtradebot, (True, False))
     telegram = Telegram(freqtradebot)
 
     update.message.text = '/forcebuy ETH/Nonepair'
-    telegram._forcebuy(bot=MagicMock(), update=update)
+    telegram._forcebuy(update=update, context=MagicMock())
 
     assert rpc_mock.call_count == 1
     assert rpc_mock.call_args_list[0][0][0] == 'Forcebuy not enabled.'
 
 
 def test_performance_handle(default_conf, update, ticker, fee,
-                            limit_buy_order, limit_sell_order, markets, mocker) -> None:
-    patch_exchange(mocker)
+                            limit_buy_order, limit_sell_order, mocker) -> None:
     msg_mock = MagicMock()
     mocker.patch.multiple(
         'freqtrade.rpc.telegram.Telegram',
@@ -999,18 +963,15 @@ def test_performance_handle(default_conf, update, ticker, fee,
     )
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
+        fetch_ticker=ticker,
         get_fee=fee,
-        markets=PropertyMock(markets),
-        validate_pairs=MagicMock(return_value={})
     )
-    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     telegram = Telegram(freqtradebot)
 
     # Create some test data
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
     trade = Trade.query.first()
     assert trade
 
@@ -1022,14 +983,13 @@ def test_performance_handle(default_conf, update, ticker, fee,
 
     trade.close_date = datetime.utcnow()
     trade.is_open = False
-    telegram._performance(bot=MagicMock(), update=update)
+    telegram._performance(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
     assert 'Performance' in msg_mock.call_args_list[0][0][0]
     assert '<code>ETH/BTC\t6.20% (1)</code>' in msg_mock.call_args_list[0][0][0]
 
 
-def test_count_handle(default_conf, update, ticker, fee, markets, mocker) -> None:
-    patch_exchange(mocker)
+def test_count_handle(default_conf, update, ticker, fee, mocker) -> None:
     msg_mock = MagicMock()
     mocker.patch.multiple(
         'freqtrade.rpc.telegram.Telegram',
@@ -1038,36 +998,63 @@ def test_count_handle(default_conf, update, ticker, fee, markets, mocker) -> Non
     )
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        get_ticker=ticker,
-        buy=MagicMock(return_value={'id': 'mocked_order_id'}),
-        markets=PropertyMock(markets)
+        fetch_ticker=ticker,
+        get_fee=fee,
     )
-    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
-    freqtradebot = FreqtradeBot(default_conf)
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     patch_get_signal(freqtradebot, (True, False))
     telegram = Telegram(freqtradebot)
 
     freqtradebot.state = State.STOPPED
-    telegram._count(bot=MagicMock(), update=update)
+    telegram._count(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
     assert 'not running' in msg_mock.call_args_list[0][0][0]
     msg_mock.reset_mock()
     freqtradebot.state = State.RUNNING
 
     # Create some test data
-    freqtradebot.create_trade()
+    freqtradebot.enter_positions()
     msg_mock.reset_mock()
-    telegram._count(bot=MagicMock(), update=update)
+    telegram._count(update=update, context=MagicMock())
 
-    msg = '<pre>  current    max    total stake\n---------  -----  -------------\n' \
-          '        1      {}          {}</pre>'\
-        .format(
+    msg = ('<pre>  current    max    total stake\n---------  -----  -------------\n'
+           '        1      {}          {}</pre>').format(
             default_conf['max_open_trades'],
             default_conf['stake_amount']
         )
     assert msg in msg_mock.call_args_list[0][0][0]
 
 
+def test_telegram_lock_handle(default_conf, update, ticker, fee, mocker) -> None:
+    msg_mock = MagicMock()
+    mocker.patch.multiple(
+        'freqtrade.rpc.telegram.Telegram',
+        _init=MagicMock(),
+        _send_msg=msg_mock
+    )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    patch_get_signal(freqtradebot, (True, False))
+    telegram = Telegram(freqtradebot)
+
+    PairLocks.lock_pair('ETH/BTC', arrow.utcnow().shift(minutes=4).datetime, 'randreason')
+    PairLocks.lock_pair('XRP/BTC', arrow.utcnow().shift(minutes=20).datetime, 'deadbeef')
+
+    telegram._locks(update=update, context=MagicMock())
+
+    assert 'Pair' in msg_mock.call_args_list[0][0][0]
+    assert 'Until' in msg_mock.call_args_list[0][0][0]
+    assert 'Reason\n' in msg_mock.call_args_list[0][0][0]
+    assert 'ETH/BTC' in msg_mock.call_args_list[0][0][0]
+    assert 'XRP/BTC' in msg_mock.call_args_list[0][0][0]
+    assert 'deadbeef' in msg_mock.call_args_list[0][0][0]
+    assert 'randreason' in msg_mock.call_args_list[0][0][0]
+
+
 def test_whitelist_static(default_conf, update, mocker) -> None:
     msg_mock = MagicMock()
     mocker.patch.multiple(
@@ -1079,10 +1066,10 @@ def test_whitelist_static(default_conf, update, mocker) -> None:
 
     telegram = Telegram(freqtradebot)
 
-    telegram._whitelist(bot=MagicMock(), update=update)
+    telegram._whitelist(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
-    assert ('Using whitelist `StaticPairList` with 4 pairs\n`ETH/BTC, LTC/BTC, XRP/BTC, NEO/BTC`'
-            in msg_mock.call_args_list[0][0][0])
+    assert ("Using whitelist `['StaticPairList']` with 4 pairs\n"
+            "`ETH/BTC, LTC/BTC, XRP/BTC, NEO/BTC`" in msg_mock.call_args_list[0][0][0])
 
 
 def test_whitelist_dynamic(default_conf, update, mocker) -> None:
@@ -1093,17 +1080,17 @@ def test_whitelist_dynamic(default_conf, update, mocker) -> None:
         _send_msg=msg_mock
     )
     mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
-    default_conf['pairlist'] = {'method': 'VolumePairList',
-                                'config': {'number_assets': 4}
-                                }
+    default_conf['pairlists'] = [{'method': 'VolumePairList',
+                                 'number_assets': 4
+                                  }]
     freqtradebot = get_patched_freqtradebot(mocker, default_conf)
 
     telegram = Telegram(freqtradebot)
 
-    telegram._whitelist(bot=MagicMock(), update=update)
+    telegram._whitelist(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
-    assert ('Using whitelist `VolumePairList` with 4 pairs\n`ETH/BTC, LTC/BTC, XRP/BTC, NEO/BTC`'
-            in msg_mock.call_args_list[0][0][0])
+    assert ("Using whitelist `['VolumePairList']` with 4 pairs\n"
+            "`ETH/BTC, LTC/BTC, XRP/BTC, NEO/BTC`" in msg_mock.call_args_list[0][0][0])
 
 
 def test_blacklist_static(default_conf, update, mocker) -> None:
@@ -1117,18 +1104,68 @@ def test_blacklist_static(default_conf, update, mocker) -> None:
 
     telegram = Telegram(freqtradebot)
 
-    telegram._blacklist(bot=MagicMock(), update=update, args=[])
+    telegram._blacklist(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
     assert ("Blacklist contains 2 pairs\n`DOGE/BTC, HOT/BTC`"
             in msg_mock.call_args_list[0][0][0])
 
     msg_mock.reset_mock()
-    telegram._blacklist(bot=MagicMock(), update=update, args=["ETH/BTC"])
+
+    # /blacklist ETH/BTC
+    context = MagicMock()
+    context.args = ["ETH/BTC"]
+    telegram._blacklist(update=update, context=context)
     assert msg_mock.call_count == 1
     assert ("Blacklist contains 3 pairs\n`DOGE/BTC, HOT/BTC, ETH/BTC`"
             in msg_mock.call_args_list[0][0][0])
     assert freqtradebot.pairlists.blacklist == ["DOGE/BTC", "HOT/BTC", "ETH/BTC"]
 
+    msg_mock.reset_mock()
+    context = MagicMock()
+    context.args = ["ETH/ETH"]
+    telegram._blacklist(update=update, context=context)
+    assert msg_mock.call_count == 2
+    assert ("Error adding `ETH/ETH` to blacklist: `Pair ETH/ETH does not match stake currency.`"
+            in msg_mock.call_args_list[0][0][0])
+
+    assert ("Blacklist contains 3 pairs\n`DOGE/BTC, HOT/BTC, ETH/BTC`"
+            in msg_mock.call_args_list[1][0][0])
+    assert freqtradebot.pairlists.blacklist == ["DOGE/BTC", "HOT/BTC", "ETH/BTC"]
+
+
+def test_telegram_logs(default_conf, update, mocker) -> None:
+    msg_mock = MagicMock()
+    mocker.patch.multiple(
+        'freqtrade.rpc.telegram.Telegram',
+        _init=MagicMock(),
+        _send_msg=msg_mock
+    )
+    setup_logging(default_conf)
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+
+    telegram = Telegram(freqtradebot)
+    context = MagicMock()
+    context.args = []
+    telegram._logs(update=update, context=context)
+    assert msg_mock.call_count == 1
+    assert "freqtrade\\.rpc\\.telegram" in msg_mock.call_args_list[0][0][0]
+
+    msg_mock.reset_mock()
+    context.args = ["1"]
+    telegram._logs(update=update, context=context)
+    assert msg_mock.call_count == 1
+
+    msg_mock.reset_mock()
+    # Test with changed MaxMessageLength
+    mocker.patch('freqtrade.rpc.telegram.MAX_TELEGRAM_MESSAGE_LENGTH', 200)
+    context = MagicMock()
+    context.args = []
+    telegram._logs(update=update, context=context)
+    # Called at least 2 times. Exact times will change with unrelated changes to setup messages
+    # Therefore we don't test for this explicitly.
+    assert msg_mock.call_count >= 2
+
 
 def test_edge_disabled(default_conf, update, mocker) -> None:
     msg_mock = MagicMock()
@@ -1142,7 +1179,7 @@ def test_edge_disabled(default_conf, update, mocker) -> None:
 
     telegram = Telegram(freqtradebot)
 
-    telegram._edge(bot=MagicMock(), update=update)
+    telegram._edge(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
     assert "Edge is not enabled." in msg_mock.call_args_list[0][0][0]
 
@@ -1164,12 +1201,69 @@ def test_edge_enabled(edge_conf, update, mocker) -> None:
 
     telegram = Telegram(freqtradebot)
 
-    telegram._edge(bot=MagicMock(), update=update)
+    telegram._edge(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
     assert '<b>Edge only validated following pairs:</b>\n<pre>' in msg_mock.call_args_list[0][0][0]
     assert 'Pair      Winrate    Expectancy    Stoploss' in msg_mock.call_args_list[0][0][0]
 
 
+def test_telegram_trades(mocker, update, default_conf, fee):
+    msg_mock = MagicMock()
+    mocker.patch.multiple(
+        'freqtrade.rpc.telegram.Telegram',
+        _init=MagicMock(),
+        _send_msg=msg_mock
+    )
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    telegram = Telegram(freqtradebot)
+    context = MagicMock()
+    context.args = []
+
+    telegram._trades(update=update, context=context)
+    assert "<b>0 recent trades</b>:" in msg_mock.call_args_list[0][0][0]
+    assert "<pre>" not in msg_mock.call_args_list[0][0][0]
+
+    msg_mock.reset_mock()
+    create_mock_trades(fee)
+
+    context = MagicMock()
+    context.args = [5]
+    telegram._trades(update=update, context=context)
+    msg_mock.call_count == 1
+    assert "2 recent trades</b>:" in msg_mock.call_args_list[0][0][0]
+    assert "Profit (" in msg_mock.call_args_list[0][0][0]
+    assert "Open Date" in msg_mock.call_args_list[0][0][0]
+    assert "<pre>" in msg_mock.call_args_list[0][0][0]
+
+
+def test_telegram_delete_trade(mocker, update, default_conf, fee):
+    msg_mock = MagicMock()
+    mocker.patch.multiple(
+        'freqtrade.rpc.telegram.Telegram',
+        _init=MagicMock(),
+        _send_msg=msg_mock
+    )
+
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    telegram = Telegram(freqtradebot)
+    context = MagicMock()
+    context.args = []
+
+    telegram._delete_trade(update=update, context=context)
+    assert "invalid argument" in msg_mock.call_args_list[0][0][0]
+
+    msg_mock.reset_mock()
+    create_mock_trades(fee)
+
+    context = MagicMock()
+    context.args = [1]
+    telegram._delete_trade(update=update, context=context)
+    msg_mock.call_count == 1
+    assert "Deleted trade 1." in msg_mock.call_args_list[0][0][0]
+    assert "Please make sure to take care of this asset" in msg_mock.call_args_list[0][0][0]
+
+
 def test_help_handle(default_conf, update, mocker) -> None:
     msg_mock = MagicMock()
     mocker.patch.multiple(
@@ -1181,7 +1275,7 @@ def test_help_handle(default_conf, update, mocker) -> None:
 
     telegram = Telegram(freqtradebot)
 
-    telegram._help(bot=MagicMock(), update=update)
+    telegram._help(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
     assert '*/help:* `This help message`' in msg_mock.call_args_list[0][0][0]
 
@@ -1196,12 +1290,87 @@ def test_version_handle(default_conf, update, mocker) -> None:
     freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     telegram = Telegram(freqtradebot)
 
-    telegram._version(bot=MagicMock(), update=update)
+    telegram._version(update=update, context=MagicMock())
     assert msg_mock.call_count == 1
     assert '*Version:* `{}`'.format(__version__) in msg_mock.call_args_list[0][0][0]
 
 
-def test_send_msg_buy_notification(default_conf, mocker) -> None:
+def test_show_config_handle(default_conf, update, mocker) -> None:
+    msg_mock = MagicMock()
+    mocker.patch.multiple(
+        'freqtrade.rpc.telegram.Telegram',
+        _init=MagicMock(),
+        _send_msg=msg_mock
+    )
+    default_conf['runmode'] = RunMode.DRY_RUN
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    telegram = Telegram(freqtradebot)
+
+    telegram._show_config(update=update, context=MagicMock())
+    assert msg_mock.call_count == 1
+    assert '*Mode:* `{}`'.format('Dry-run') in msg_mock.call_args_list[0][0][0]
+    assert '*Exchange:* `bittrex`' in msg_mock.call_args_list[0][0][0]
+    assert '*Strategy:* `DefaultStrategy`' in msg_mock.call_args_list[0][0][0]
+    assert '*Stoploss:* `-0.1`' in msg_mock.call_args_list[0][0][0]
+
+    msg_mock.reset_mock()
+    freqtradebot.config['trailing_stop'] = True
+    telegram._show_config(update=update, context=MagicMock())
+    assert msg_mock.call_count == 1
+    assert '*Mode:* `{}`'.format('Dry-run') in msg_mock.call_args_list[0][0][0]
+    assert '*Exchange:* `bittrex`' in msg_mock.call_args_list[0][0][0]
+    assert '*Strategy:* `DefaultStrategy`' in msg_mock.call_args_list[0][0][0]
+    assert '*Initial Stoploss:* `-0.1`' in msg_mock.call_args_list[0][0][0]
+
+
+def test_send_msg_buy_notification(default_conf, mocker, caplog) -> None:
+    msg_mock = MagicMock()
+    mocker.patch.multiple(
+        'freqtrade.rpc.telegram.Telegram',
+        _init=MagicMock(),
+        _send_msg=msg_mock
+    )
+    msg = {
+        'type': RPCMessageType.BUY_NOTIFICATION,
+        'exchange': 'Bittrex',
+        'pair': 'ETH/BTC',
+        'limit': 1.099e-05,
+        'order_type': 'limit',
+        'stake_amount': 0.001,
+        'stake_amount_fiat': 0.0,
+        'stake_currency': 'BTC',
+        'fiat_currency': 'USD',
+        'current_rate': 1.099e-05,
+        'amount': 1333.3333333333335,
+        'open_date': arrow.utcnow().shift(hours=-1)
+    }
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    telegram = Telegram(freqtradebot)
+    telegram.send_msg(msg)
+    assert msg_mock.call_args[0][0] \
+        == '\N{LARGE BLUE CIRCLE} *Bittrex:* Buying ETH/BTC\n' \
+           '*Amount:* `1333.33333333`\n' \
+           '*Open Rate:* `0.00001099`\n' \
+           '*Current Rate:* `0.00001099`\n' \
+           '*Total:* `(0.001000 BTC, 12.345 USD)`'
+
+    freqtradebot.config['telegram']['notification_settings'] = {'buy': 'off'}
+    caplog.clear()
+    msg_mock.reset_mock()
+    telegram.send_msg(msg)
+    msg_mock.call_count == 0
+    log_has("Notification 'buy' not sent.", caplog)
+
+    freqtradebot.config['telegram']['notification_settings'] = {'buy': 'silent'}
+    caplog.clear()
+    msg_mock.reset_mock()
+
+    telegram.send_msg(msg)
+    msg_mock.call_count == 1
+    msg_mock.call_args_list[0][1]['disable_notification'] is True
+
+
+def test_send_msg_buy_cancel_notification(default_conf, mocker) -> None:
     msg_mock = MagicMock()
     mocker.patch.multiple(
         'freqtrade.rpc.telegram.Telegram',
@@ -1211,20 +1380,13 @@ def test_send_msg_buy_notification(default_conf, mocker) -> None:
     freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     telegram = Telegram(freqtradebot)
     telegram.send_msg({
-        'type': RPCMessageType.BUY_NOTIFICATION,
+        'type': RPCMessageType.BUY_CANCEL_NOTIFICATION,
         'exchange': 'Bittrex',
         'pair': 'ETH/BTC',
-        'limit': 1.099e-05,
-        'order_type': 'limit',
-        'stake_amount': 0.001,
-        'stake_amount_fiat': 0.0,
-        'stake_currency': 'BTC',
-        'fiat_currency': 'USD'
+        'reason': CANCEL_REASON['TIMEOUT']
     })
-    assert msg_mock.call_args[0][0] \
-        == '*Bittrex:* Buying ETH/BTC\n' \
-           'at rate `0.00001099\n' \
-           '(0.001000 BTC,0.000 USD)`'
+    assert (msg_mock.call_args[0][0] == '\N{WARNING SIGN} *Bittrex:* '
+            'Cancelling open buy Order for ETH/BTC. Reason: cancelled due to timeout.')
 
 
 def test_send_msg_sell_notification(default_conf, mocker) -> None:
@@ -1249,19 +1411,22 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
         'open_rate': 7.5e-05,
         'current_rate': 3.201e-05,
         'profit_amount': -0.05746268,
-        'profit_percent': -0.57405275,
+        'profit_ratio': -0.57405275,
         'stake_currency': 'ETH',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.STOP_LOSS.value
+        'sell_reason': SellType.STOP_LOSS.value,
+        'open_date': arrow.utcnow().shift(hours=-1),
+        'close_date': arrow.utcnow(),
     })
     assert msg_mock.call_args[0][0] \
-        == ('*Binance:* Selling KEY/ETH\n'
-            '*Rate:* `0.00003201`\n'
+        == ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH\n'
             '*Amount:* `1333.33333333`\n'
             '*Open Rate:* `0.00007500`\n'
             '*Current Rate:* `0.00003201`\n'
+            '*Close Rate:* `0.00003201`\n'
             '*Sell Reason:* `stop_loss`\n'
-            '*Profit:* `-57.41%`` (loss: -0.05746268 ETH`` / -24.812 USD)`')
+            '*Duration:* `1:00:00 (60.0 min)`\n'
+            '*Profit:* `-57.41%` `(loss: -0.05746268 ETH / -24.812 USD)`')
 
     msg_mock.reset_mock()
     telegram.send_msg({
@@ -1275,22 +1440,59 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
         'open_rate': 7.5e-05,
         'current_rate': 3.201e-05,
         'profit_amount': -0.05746268,
-        'profit_percent': -0.57405275,
+        'profit_ratio': -0.57405275,
         'stake_currency': 'ETH',
-        'sell_reason': SellType.STOP_LOSS.value
+        'sell_reason': SellType.STOP_LOSS.value,
+        'open_date': arrow.utcnow().shift(days=-1, hours=-2, minutes=-30),
+        'close_date': arrow.utcnow(),
     })
     assert msg_mock.call_args[0][0] \
-        == ('*Binance:* Selling KEY/ETH\n'
-            '*Rate:* `0.00003201`\n'
+        == ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH\n'
             '*Amount:* `1333.33333333`\n'
             '*Open Rate:* `0.00007500`\n'
             '*Current Rate:* `0.00003201`\n'
+            '*Close Rate:* `0.00003201`\n'
             '*Sell Reason:* `stop_loss`\n'
+            '*Duration:* `1 day, 2:30:00 (1590.0 min)`\n'
             '*Profit:* `-57.41%`')
     # Reset singleton function to avoid random breaks
     telegram._fiat_converter.convert_amount = old_convamount
 
 
+def test_send_msg_sell_cancel_notification(default_conf, mocker) -> None:
+    msg_mock = MagicMock()
+    mocker.patch.multiple(
+        'freqtrade.rpc.telegram.Telegram',
+        _init=MagicMock(),
+        _send_msg=msg_mock
+    )
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    telegram = Telegram(freqtradebot)
+    old_convamount = telegram._fiat_converter.convert_amount
+    telegram._fiat_converter.convert_amount = lambda a, b, c: -24.812
+    telegram.send_msg({
+        'type': RPCMessageType.SELL_CANCEL_NOTIFICATION,
+        'exchange': 'Binance',
+        'pair': 'KEY/ETH',
+        'reason': 'Cancelled on exchange'
+    })
+    assert msg_mock.call_args[0][0] \
+        == ('\N{WARNING SIGN} *Binance:* Cancelling Open Sell Order for KEY/ETH. '
+            'Reason: Cancelled on exchange')
+
+    msg_mock.reset_mock()
+    telegram.send_msg({
+        'type': RPCMessageType.SELL_CANCEL_NOTIFICATION,
+        'exchange': 'Binance',
+        'pair': 'KEY/ETH',
+        'reason': 'timeout'
+    })
+    assert msg_mock.call_args[0][0] \
+        == ('\N{WARNING SIGN} *Binance:* Cancelling Open Sell Order for KEY/ETH. Reason: timeout')
+    # Reset singleton function to avoid random breaks
+    telegram._fiat_converter.convert_amount = old_convamount
+
+
 def test_send_msg_status_notification(default_conf, mocker) -> None:
     msg_mock = MagicMock()
     mocker.patch.multiple(
@@ -1320,10 +1522,10 @@ def test_warning_notification(default_conf, mocker) -> None:
         'type': RPCMessageType.WARNING_NOTIFICATION,
         'status': 'message'
     })
-    assert msg_mock.call_args[0][0] == '*Warning:* `message`'
+    assert msg_mock.call_args[0][0] == '\N{WARNING SIGN} *Warning:* `message`'
 
 
-def test_custom_notification(default_conf, mocker) -> None:
+def test_startup_notification(default_conf, mocker) -> None:
     msg_mock = MagicMock()
     mocker.patch.multiple(
         'freqtrade.rpc.telegram.Telegram',
@@ -1333,7 +1535,7 @@ def test_custom_notification(default_conf, mocker) -> None:
     freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     telegram = Telegram(freqtradebot)
     telegram.send_msg({
-        'type': RPCMessageType.CUSTOM_NOTIFICATION,
+        'type': RPCMessageType.STARTUP_NOTIFICATION,
         'status': '*Custom:* `Hello World`'
     })
     assert msg_mock.call_args[0][0] == '*Custom:* `Hello World`'
@@ -1373,12 +1575,16 @@ def test_send_msg_buy_notification_no_fiat(default_conf, mocker) -> None:
         'stake_amount': 0.001,
         'stake_amount_fiat': 0.0,
         'stake_currency': 'BTC',
-        'fiat_currency': None
+        'fiat_currency': None,
+        'current_rate': 1.099e-05,
+        'amount': 1333.3333333333335,
+        'open_date': arrow.utcnow().shift(hours=-1)
     })
-    assert msg_mock.call_args[0][0] \
-        == '*Bittrex:* Buying ETH/BTC\n' \
-           'at rate `0.00001099\n' \
-           '(0.001000 BTC)`'
+    assert msg_mock.call_args[0][0] == ('\N{LARGE BLUE CIRCLE} *Bittrex:* Buying ETH/BTC\n'
+                                        '*Amount:* `1333.33333333`\n'
+                                        '*Open Rate:* `0.00001099`\n'
+                                        '*Current Rate:* `0.00001099`\n'
+                                        '*Total:* `(0.001000 BTC)`')
 
 
 def test_send_msg_sell_notification_no_fiat(default_conf, mocker) -> None:
@@ -1402,19 +1608,44 @@ def test_send_msg_sell_notification_no_fiat(default_conf, mocker) -> None:
         'open_rate': 7.5e-05,
         'current_rate': 3.201e-05,
         'profit_amount': -0.05746268,
-        'profit_percent': -0.57405275,
+        'profit_ratio': -0.57405275,
         'stake_currency': 'ETH',
         'fiat_currency': 'USD',
-        'sell_reason': SellType.STOP_LOSS.value
+        'sell_reason': SellType.STOP_LOSS.value,
+        'open_date': arrow.utcnow().shift(hours=-2, minutes=-35, seconds=-3),
+        'close_date': arrow.utcnow(),
     })
-    assert msg_mock.call_args[0][0] \
-        == '*Binance:* Selling KEY/ETH\n' \
-           '*Rate:* `0.00003201`\n' \
-           '*Amount:* `1333.33333333`\n' \
-           '*Open Rate:* `0.00007500`\n' \
-           '*Current Rate:* `0.00003201`\n' \
-           '*Sell Reason:* `stop_loss`\n' \
-           '*Profit:* `-57.41%`'
+    assert msg_mock.call_args[0][0] == ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH\n'
+                                        '*Amount:* `1333.33333333`\n'
+                                        '*Open Rate:* `0.00007500`\n'
+                                        '*Current Rate:* `0.00003201`\n'
+                                        '*Close Rate:* `0.00003201`\n'
+                                        '*Sell Reason:* `stop_loss`\n'
+                                        '*Duration:* `2:35:03 (155.1 min)`\n'
+                                        '*Profit:* `-57.41%`')
+
+
+@pytest.mark.parametrize('msg,expected', [
+    ({'profit_percent': 20.1, 'sell_reason': 'roi'}, "\N{ROCKET}"),
+    ({'profit_percent': 5.1, 'sell_reason': 'roi'}, "\N{ROCKET}"),
+    ({'profit_percent': 2.56, 'sell_reason': 'roi'}, "\N{EIGHT SPOKED ASTERISK}"),
+    ({'profit_percent': 1.0, 'sell_reason': 'roi'}, "\N{EIGHT SPOKED ASTERISK}"),
+    ({'profit_percent': 0.0, 'sell_reason': 'roi'}, "\N{EIGHT SPOKED ASTERISK}"),
+    ({'profit_percent': -5.0, 'sell_reason': 'stop_loss'}, "\N{WARNING SIGN}"),
+    ({'profit_percent': -2.0, 'sell_reason': 'sell_signal'}, "\N{CROSS MARK}"),
+])
+def test__sell_emoji(default_conf, mocker, msg, expected):
+    del default_conf['fiat_display_currency']
+    msg_mock = MagicMock()
+    mocker.patch.multiple(
+        'freqtrade.rpc.telegram.Telegram',
+        _init=MagicMock(),
+        _send_msg=msg_mock
+    )
+    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    telegram = Telegram(freqtradebot)
+
+    assert telegram._get_sell_emoji(msg) == expected
 
 
 def test__send_msg(default_conf, mocker) -> None:
@@ -1422,9 +1653,11 @@ def test__send_msg(default_conf, mocker) -> None:
     bot = MagicMock()
     freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     telegram = Telegram(freqtradebot)
+    telegram._updater = MagicMock()
+    telegram._updater.bot = bot
 
     telegram._config['telegram']['enabled'] = True
-    telegram._send_msg('test', bot)
+    telegram._send_msg('test')
     assert len(bot.method_calls) == 1
 
 
@@ -1434,13 +1667,12 @@ def test__send_msg_network_error(default_conf, mocker, caplog) -> None:
     bot.send_message = MagicMock(side_effect=NetworkError('Oh snap'))
     freqtradebot = get_patched_freqtradebot(mocker, default_conf)
     telegram = Telegram(freqtradebot)
+    telegram._updater = MagicMock()
+    telegram._updater.bot = bot
 
     telegram._config['telegram']['enabled'] = True
-    telegram._send_msg('test', bot)
+    telegram._send_msg('test')
 
     # Bot should've tried to send it twice
     assert len(bot.method_calls) == 2
-    assert log_has(
-        'Telegram NetworkError: Oh snap! Trying one more time.',
-        caplog.record_tuples
-    )
+    assert log_has('Telegram NetworkError: Oh snap! Trying one more time.', caplog)
diff --git a/freqtrade/tests/rpc/test_rpc_webhook.py b/tests/rpc/test_rpc_webhook.py
similarity index 55%
rename from freqtrade/tests/rpc/test_rpc_webhook.py
rename to tests/rpc/test_rpc_webhook.py
index a2dcd9b31..9256a5316 100644
--- a/freqtrade/tests/rpc/test_rpc_webhook.py
+++ b/tests/rpc/test_rpc_webhook.py
@@ -8,29 +8,39 @@ from requests import RequestException
 from freqtrade.rpc import RPCMessageType
 from freqtrade.rpc.webhook import Webhook
 from freqtrade.strategy.interface import SellType
-from freqtrade.tests.conftest import get_patched_freqtradebot, log_has
+from tests.conftest import get_patched_freqtradebot, log_has
 
 
 def get_webhook_dict() -> dict:
     return {
-          "enabled": True,
-          "url": "https://maker.ifttt.com/trigger/freqtrade_test/with/key/c764udvJ5jfSlswVRukZZ2/",
-          "webhookbuy": {
-              "value1": "Buying {pair}",
-              "value2": "limit {limit:8f}",
-              "value3": "{stake_amount:8f} {stake_currency}"
-          },
-          "webhooksell": {
-              "value1": "Selling {pair}",
-              "value2": "limit {limit:8f}",
-              "value3": "profit: {profit_amount:8f} {stake_currency}"
-          },
-          "webhookstatus": {
-              "value1": "Status: {status}",
-              "value2": "",
-              "value3": ""
-          }
-      }
+        "enabled": True,
+        "url": "https://maker.ifttt.com/trigger/freqtrade_test/with/key/c764udvJ5jfSlswVRukZZ2/",
+        "webhookbuy": {
+            "value1": "Buying {pair}",
+            "value2": "limit {limit:8f}",
+            "value3": "{stake_amount:8f} {stake_currency}"
+        },
+        "webhookbuycancel": {
+            "value1": "Cancelling Open Buy Order for {pair}",
+            "value2": "limit {limit:8f}",
+            "value3": "{stake_amount:8f} {stake_currency}"
+        },
+        "webhooksell": {
+            "value1": "Selling {pair}",
+            "value2": "limit {limit:8f}",
+            "value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})"
+        },
+        "webhooksellcancel": {
+            "value1": "Cancelling Open Sell Order for {pair}",
+            "value2": "limit {limit:8f}",
+            "value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})"
+        },
+        "webhookstatus": {
+            "value1": "Status: {status}",
+            "value2": "",
+            "value3": ""
+        }
+    }
 
 
 def test__init__(mocker, default_conf):
@@ -44,6 +54,9 @@ def test_send_msg(default_conf, mocker):
     msg_mock = MagicMock()
     mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
     webhook = Webhook(get_patched_freqtradebot(mocker, default_conf))
+    # Test buy
+    msg_mock = MagicMock()
+    mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
     msg = {
         'type': RPCMessageType.BUY_NOTIFICATION,
         'exchange': 'Bittrex',
@@ -54,8 +67,6 @@ def test_send_msg(default_conf, mocker):
         'stake_currency': 'BTC',
         'fiat_currency': 'EUR'
     }
-    msg_mock = MagicMock()
-    mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
     webhook.send_msg(msg=msg)
     assert msg_mock.call_count == 1
     assert (msg_mock.call_args[0][0]["value1"] ==
@@ -64,6 +75,27 @@ def test_send_msg(default_conf, mocker):
             default_conf["webhook"]["webhookbuy"]["value2"].format(**msg))
     assert (msg_mock.call_args[0][0]["value3"] ==
             default_conf["webhook"]["webhookbuy"]["value3"].format(**msg))
+    # Test buy cancel
+    msg_mock = MagicMock()
+    mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
+    msg = {
+        'type': RPCMessageType.BUY_CANCEL_NOTIFICATION,
+        'exchange': 'Bittrex',
+        'pair': 'ETH/BTC',
+        'limit': 0.005,
+        'stake_amount': 0.8,
+        'stake_amount_fiat': 500,
+        'stake_currency': 'BTC',
+        'fiat_currency': 'EUR'
+    }
+    webhook.send_msg(msg=msg)
+    assert msg_mock.call_count == 1
+    assert (msg_mock.call_args[0][0]["value1"] ==
+            default_conf["webhook"]["webhookbuycancel"]["value1"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value2"] ==
+            default_conf["webhook"]["webhookbuycancel"]["value2"].format(**msg))
+    assert (msg_mock.call_args[0][0]["value3"] ==
+            default_conf["webhook"]["webhookbuycancel"]["value3"].format(**msg))
     # Test sell
     msg_mock = MagicMock()
     mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
@@ -78,7 +110,7 @@ def test_send_msg(default_conf, mocker):
         'open_rate': 0.004,
         'current_rate': 0.005,
         'profit_amount': 0.001,
-        'profit_percent': 0.20,
+        'profit_ratio': 0.20,
         'stake_currency': 'BTC',
         'sell_reason': SellType.STOP_LOSS.value
     }
@@ -90,32 +122,60 @@ def test_send_msg(default_conf, mocker):
             default_conf["webhook"]["webhooksell"]["value2"].format(**msg))
     assert (msg_mock.call_args[0][0]["value3"] ==
             default_conf["webhook"]["webhooksell"]["value3"].format(**msg))
-
-    # Test notification
-    msg = {
-        'type': RPCMessageType.STATUS_NOTIFICATION,
-        'status': 'Unfilled sell order for BTC cancelled due to timeout'
-    }
+    # Test sell cancel
     msg_mock = MagicMock()
     mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
-    webhook.send_msg(msg)
+    msg = {
+        'type': RPCMessageType.SELL_CANCEL_NOTIFICATION,
+        'exchange': 'Bittrex',
+        'pair': 'ETH/BTC',
+        'gain': "profit",
+        'limit': 0.005,
+        'amount': 0.8,
+        'order_type': 'limit',
+        'open_rate': 0.004,
+        'current_rate': 0.005,
+        'profit_amount': 0.001,
+        'profit_ratio': 0.20,
+        'stake_currency': 'BTC',
+        'sell_reason': SellType.STOP_LOSS.value
+    }
+    webhook.send_msg(msg=msg)
     assert msg_mock.call_count == 1
     assert (msg_mock.call_args[0][0]["value1"] ==
-            default_conf["webhook"]["webhookstatus"]["value1"].format(**msg))
+            default_conf["webhook"]["webhooksellcancel"]["value1"].format(**msg))
     assert (msg_mock.call_args[0][0]["value2"] ==
-            default_conf["webhook"]["webhookstatus"]["value2"].format(**msg))
+            default_conf["webhook"]["webhooksellcancel"]["value2"].format(**msg))
     assert (msg_mock.call_args[0][0]["value3"] ==
-            default_conf["webhook"]["webhookstatus"]["value3"].format(**msg))
+            default_conf["webhook"]["webhooksellcancel"]["value3"].format(**msg))
+    for msgtype in [RPCMessageType.STATUS_NOTIFICATION,
+                    RPCMessageType.WARNING_NOTIFICATION,
+                    RPCMessageType.STARTUP_NOTIFICATION]:
+        # Test notification
+        msg = {
+            'type': msgtype,
+            'status': 'Unfilled sell order for BTC cancelled due to timeout'
+        }
+        msg_mock = MagicMock()
+        mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
+        webhook.send_msg(msg)
+        assert msg_mock.call_count == 1
+        assert (msg_mock.call_args[0][0]["value1"] ==
+                default_conf["webhook"]["webhookstatus"]["value1"].format(**msg))
+        assert (msg_mock.call_args[0][0]["value2"] ==
+                default_conf["webhook"]["webhookstatus"]["value2"].format(**msg))
+        assert (msg_mock.call_args[0][0]["value3"] ==
+                default_conf["webhook"]["webhookstatus"]["value3"].format(**msg))
 
 
 def test_exception_send_msg(default_conf, mocker, caplog):
     default_conf["webhook"] = get_webhook_dict()
-    default_conf["webhook"]["webhookbuy"] = None
+    del default_conf["webhook"]["webhookbuy"]
 
     webhook = Webhook(get_patched_freqtradebot(mocker, default_conf))
     webhook.send_msg({'type': RPCMessageType.BUY_NOTIFICATION})
-    assert log_has(f"Message type {RPCMessageType.BUY_NOTIFICATION} not configured for webhooks",
-                   caplog.record_tuples)
+    assert log_has(f"Message type '{RPCMessageType.BUY_NOTIFICATION}' not configured for webhooks",
+                   caplog)
 
     default_conf["webhook"] = get_webhook_dict()
     default_conf["webhook"]["webhookbuy"]["value1"] = "{DEADBEEF:8f}"
@@ -135,7 +195,7 @@ def test_exception_send_msg(default_conf, mocker, caplog):
     }
     webhook.send_msg(msg)
     assert log_has("Problem calling Webhook. Please check your webhook configuration. "
-                   "Exception: 'DEADBEEF'", caplog.record_tuples)
+                   "Exception: 'DEADBEEF'", caplog)
 
     msg_mock = MagicMock()
     mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock)
@@ -164,4 +224,4 @@ def test__send_msg(default_conf, mocker, caplog):
     post = MagicMock(side_effect=RequestException)
     mocker.patch("freqtrade.rpc.webhook.post", post)
     webhook._send_msg(msg)
-    assert log_has('Could not call webhook url. Exception: ', caplog.record_tuples)
+    assert log_has('Could not call webhook url. Exception: ', caplog)
diff --git a/freqtrade/tests/testdata/UNITTEST_BTC-8m.json b/tests/strategy/__init__.py
similarity index 100%
rename from freqtrade/tests/testdata/UNITTEST_BTC-8m.json
rename to tests/strategy/__init__.py
diff --git a/tests/strategy/strats/default_strategy.py b/tests/strategy/strats/default_strategy.py
new file mode 100644
index 000000000..98842ff7c
--- /dev/null
+++ b/tests/strategy/strats/default_strategy.py
@@ -0,0 +1,156 @@
+# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
+
+import talib.abstract as ta
+from pandas import DataFrame
+
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+from freqtrade.strategy.interface import IStrategy
+
+
+class DefaultStrategy(IStrategy):
+    """
+    Default Strategy provided by freqtrade bot.
+    Please do not modify this strategy, it's  intended for internal use only.
+    Please look at the SampleStrategy in the user_data/strategy directory
+    or strategy repository https://github.com/freqtrade/freqtrade-strategies
+    for samples and inspiration.
+    """
+    INTERFACE_VERSION = 2
+
+    # Minimal ROI designed for the strategy
+    minimal_roi = {
+        "40": 0.0,
+        "30": 0.01,
+        "20": 0.02,
+        "0": 0.04
+    }
+
+    # Optimal stoploss designed for the strategy
+    stoploss = -0.10
+
+    # Optimal ticker interval for the strategy
+    timeframe = '5m'
+
+    # Optional order type mapping
+    order_types = {
+        'buy': 'limit',
+        'sell': 'limit',
+        'stoploss': 'limit',
+        'stoploss_on_exchange': False
+    }
+
+    # Number of candles the strategy requires before producing valid signals
+    startup_candle_count: int = 20
+
+    # Optional time in force for orders
+    order_time_in_force = {
+        'buy': 'gtc',
+        'sell': 'gtc',
+    }
+
+    def informative_pairs(self):
+        """
+        Define additional, informative pair/interval combinations to be cached from the exchange.
+        These pair/interval combinations are non-tradeable, unless they are part
+        of the whitelist as well.
+        For more information, please consult the documentation
+        :return: List of tuples in the format (pair, interval)
+            Sample: return [("ETH/USDT", "5m"),
+                            ("BTC/USDT", "15m"),
+                            ]
+        """
+        return []
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Adds several different TA indicators to the given DataFrame
+
+        Performance Note: For the best performance be frugal on the number of indicators
+        you are using. Let uncomment only the indicator you are using in your strategies
+        or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
+        :param dataframe: Dataframe with data from the exchange
+        :param metadata: Additional information, like the currently traded pair
+        :return: a Dataframe with all mandatory indicators for the strategies
+        """
+
+        # Momentum Indicator
+        # ------------------------------------
+
+        # ADX
+        dataframe['adx'] = ta.ADX(dataframe)
+
+        # MACD
+        macd = ta.MACD(dataframe)
+        dataframe['macd'] = macd['macd']
+        dataframe['macdsignal'] = macd['macdsignal']
+        dataframe['macdhist'] = macd['macdhist']
+
+        # Minus Directional Indicator / Movement
+        dataframe['minus_di'] = ta.MINUS_DI(dataframe)
+
+        # Plus Directional Indicator / Movement
+        dataframe['plus_di'] = ta.PLUS_DI(dataframe)
+
+        # RSI
+        dataframe['rsi'] = ta.RSI(dataframe)
+
+        # Stoch fast
+        stoch_fast = ta.STOCHF(dataframe)
+        dataframe['fastd'] = stoch_fast['fastd']
+        dataframe['fastk'] = stoch_fast['fastk']
+
+        # Bollinger bands
+        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
+        dataframe['bb_lowerband'] = bollinger['lower']
+        dataframe['bb_middleband'] = bollinger['mid']
+        dataframe['bb_upperband'] = bollinger['upper']
+
+        # EMA - Exponential Moving Average
+        dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
+
+        return dataframe
+
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Based on TA indicators, populates the buy signal for the given dataframe
+        :param dataframe: DataFrame
+        :param metadata: Additional information, like the currently traded pair
+        :return: DataFrame with buy column
+        """
+        dataframe.loc[
+            (
+                (dataframe['rsi'] < 35) &
+                (dataframe['fastd'] < 35) &
+                (dataframe['adx'] > 30) &
+                (dataframe['plus_di'] > 0.5)
+            ) |
+            (
+                (dataframe['adx'] > 65) &
+                (dataframe['plus_di'] > 0.5)
+            ),
+            'buy'] = 1
+
+        return dataframe
+
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        """
+        Based on TA indicators, populates the sell signal for the given dataframe
+        :param dataframe: DataFrame
+        :param metadata: Additional information, like the currently traded pair
+        :return: DataFrame with buy column
+        """
+        dataframe.loc[
+            (
+                (
+                    (qtpylib.crossed_above(dataframe['rsi'], 70)) |
+                    (qtpylib.crossed_above(dataframe['fastd'], 70))
+                ) &
+                (dataframe['adx'] > 10) &
+                (dataframe['minus_di'] > 0)
+            ) |
+            (
+                (dataframe['adx'] > 70) &
+                (dataframe['minus_di'] > 0.5)
+            ),
+            'sell'] = 1
+        return dataframe
diff --git a/tests/strategy/strats/failing_strategy.py b/tests/strategy/strats/failing_strategy.py
new file mode 100644
index 000000000..f8eaac3c3
--- /dev/null
+++ b/tests/strategy/strats/failing_strategy.py
@@ -0,0 +1,9 @@
+# The strategy which fails to load due to non-existent dependency
+
+import nonexiting_module  # noqa
+
+from freqtrade.strategy.interface import IStrategy
+
+
+class TestStrategyLegacy(IStrategy):
+    pass
diff --git a/tests/strategy/strats/legacy_strategy.py b/tests/strategy/strats/legacy_strategy.py
new file mode 100644
index 000000000..1e7bb5e1e
--- /dev/null
+++ b/tests/strategy/strats/legacy_strategy.py
@@ -0,0 +1,87 @@
+
+# --- Do not remove these libs ---
+# Add your lib to import here
+import talib.abstract as ta
+from pandas import DataFrame
+
+from freqtrade.strategy.interface import IStrategy
+
+
+# --------------------------------
+
+# This class is a sample. Feel free to customize it.
+class TestStrategyLegacy(IStrategy):
+    """
+    This is a test strategy using the legacy function headers, which will be
+    removed in a future update.
+    Please do not use this as a template, but refer to user_data/strategy/sample_strategy.py
+    for a uptodate version of this template.
+    """
+
+    # Minimal ROI designed for the strategy.
+    # This attribute will be overridden if the config file contains "minimal_roi"
+    minimal_roi = {
+        "40": 0.0,
+        "30": 0.01,
+        "20": 0.02,
+        "0": 0.04
+    }
+
+    # Optimal stoploss designed for the strategy
+    # This attribute will be overridden if the config file contains "stoploss"
+    stoploss = -0.10
+
+    # Optimal ticker interval for the strategy
+    # Keep the legacy value here to test compatibility
+    ticker_interval = '5m'
+
+    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+        """
+        Adds several different TA indicators to the given DataFrame
+
+        Performance Note: For the best performance be frugal on the number of indicators
+        you are using. Let uncomment only the indicator you are using in your strategies
+        or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
+        """
+
+        # Momentum Indicator
+        # ------------------------------------
+
+        # ADX
+        dataframe['adx'] = ta.ADX(dataframe)
+
+        # TEMA - Triple Exponential Moving Average
+        dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
+
+        return dataframe
+
+    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+        """
+        Based on TA indicators, populates the buy signal for the given dataframe
+        :param dataframe: DataFrame
+        :return: DataFrame with buy column
+        """
+        dataframe.loc[
+            (
+                (dataframe['adx'] > 30) &
+                (dataframe['tema'] > dataframe['tema'].shift(1)) &
+                (dataframe['volume'] > 0)
+            ),
+            'buy'] = 1
+
+        return dataframe
+
+    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+        """
+        Based on TA indicators, populates the sell signal for the given dataframe
+        :param dataframe: DataFrame
+        :return: DataFrame with buy column
+        """
+        dataframe.loc[
+            (
+                (dataframe['adx'] > 70) &
+                (dataframe['tema'] < dataframe['tema'].shift(1)) &
+                (dataframe['volume'] > 0)
+            ),
+            'sell'] = 1
+        return dataframe
diff --git a/freqtrade/tests/strategy/test_default_strategy.py b/tests/strategy/test_default_strategy.py
similarity index 61%
rename from freqtrade/tests/strategy/test_default_strategy.py
rename to tests/strategy/test_default_strategy.py
index 74c81882a..1b1648db9 100644
--- a/freqtrade/tests/strategy/test_default_strategy.py
+++ b/tests/strategy/test_default_strategy.py
@@ -1,23 +1,12 @@
-import json
-
-import pytest
 from pandas import DataFrame
 
-from freqtrade.data.converter import parse_ticker_dataframe
-from freqtrade.strategy.default_strategy import DefaultStrategy
-
-
-@pytest.fixture
-def result():
-    with open('freqtrade/tests/testdata/ETH_BTC-1m.json') as data_file:
-        return parse_ticker_dataframe(json.load(data_file), '1m', pair="UNITTEST/BTC",
-                                      fill_missing=True)
+from .strats.default_strategy import DefaultStrategy
 
 
 def test_default_strategy_structure():
     assert hasattr(DefaultStrategy, 'minimal_roi')
     assert hasattr(DefaultStrategy, 'stoploss')
-    assert hasattr(DefaultStrategy, 'ticker_interval')
+    assert hasattr(DefaultStrategy, 'timeframe')
     assert hasattr(DefaultStrategy, 'populate_indicators')
     assert hasattr(DefaultStrategy, 'populate_buy_trend')
     assert hasattr(DefaultStrategy, 'populate_sell_trend')
@@ -29,7 +18,7 @@ def test_default_strategy(result):
     metadata = {'pair': 'ETH/BTC'}
     assert type(strategy.minimal_roi) is dict
     assert type(strategy.stoploss) is float
-    assert type(strategy.ticker_interval) is str
+    assert type(strategy.timeframe) is str
     indicators = strategy.populate_indicators(result, metadata)
     assert type(indicators) is DataFrame
     assert type(strategy.populate_buy_trend(indicators, metadata)) is DataFrame
diff --git a/tests/strategy/test_interface.py b/tests/strategy/test_interface.py
new file mode 100644
index 000000000..7cf9a0624
--- /dev/null
+++ b/tests/strategy/test_interface.py
@@ -0,0 +1,460 @@
+# pragma pylint: disable=missing-docstring, C0103
+import logging
+from datetime import datetime, timedelta, timezone
+from unittest.mock import MagicMock
+
+import arrow
+import pytest
+from pandas import DataFrame
+
+from freqtrade.configuration import TimeRange
+from freqtrade.data.dataprovider import DataProvider
+from freqtrade.data.history import load_data
+from freqtrade.exceptions import StrategyError
+from freqtrade.persistence import PairLocks, Trade
+from freqtrade.resolvers import StrategyResolver
+from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
+from tests.conftest import log_has, log_has_re
+
+from .strats.default_strategy import DefaultStrategy
+
+
+# Avoid to reinit the same object again and again
+_STRATEGY = DefaultStrategy(config={})
+_STRATEGY.dp = DataProvider({}, None, None)
+
+
+def test_returns_latest_signal(mocker, default_conf, ohlcv_history):
+    ohlcv_history.loc[1, 'date'] = arrow.utcnow()
+    # Take a copy to correctly modify the call
+    mocked_history = ohlcv_history.copy()
+    mocked_history['sell'] = 0
+    mocked_history['buy'] = 0
+    mocked_history.loc[1, 'sell'] = 1
+
+    assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (False, True)
+    mocked_history.loc[1, 'sell'] = 0
+    mocked_history.loc[1, 'buy'] = 1
+
+    assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (True, False)
+    mocked_history.loc[1, 'sell'] = 0
+    mocked_history.loc[1, 'buy'] = 0
+
+    assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (False, False)
+
+
+def test_analyze_pair_empty(default_conf, mocker, caplog, ohlcv_history):
+    mocker.patch.object(_STRATEGY.dp, 'ohlcv', return_value=ohlcv_history)
+    mocker.patch.object(
+        _STRATEGY, '_analyze_ticker_internal',
+        return_value=DataFrame([])
+    )
+    mocker.patch.object(_STRATEGY, 'assert_df')
+
+    _STRATEGY.analyze_pair('ETH/BTC')
+
+    assert log_has('Empty dataframe for pair ETH/BTC', caplog)
+
+
+def test_get_signal_empty(default_conf, mocker, caplog):
+    assert (False, False) == _STRATEGY.get_signal('foo', default_conf['timeframe'], DataFrame())
+    assert log_has('Empty candle (OHLCV) data for pair foo', caplog)
+    caplog.clear()
+
+    assert (False, False) == _STRATEGY.get_signal('bar', default_conf['timeframe'], None)
+    assert log_has('Empty candle (OHLCV) data for pair bar', caplog)
+    caplog.clear()
+
+    assert (False, False) == _STRATEGY.get_signal('baz', default_conf['timeframe'], DataFrame([]))
+    assert log_has('Empty candle (OHLCV) data for pair baz', caplog)
+
+
+def test_get_signal_exception_valueerror(default_conf, mocker, caplog, ohlcv_history):
+    caplog.set_level(logging.INFO)
+    mocker.patch.object(_STRATEGY.dp, 'ohlcv', return_value=ohlcv_history)
+    mocker.patch.object(
+        _STRATEGY, '_analyze_ticker_internal',
+        side_effect=ValueError('xyz')
+    )
+    _STRATEGY.analyze_pair('foo')
+    assert log_has_re(r'Strategy caused the following exception: xyz.*', caplog)
+    caplog.clear()
+
+    mocker.patch.object(
+        _STRATEGY, 'analyze_ticker',
+        side_effect=Exception('invalid ticker history ')
+    )
+    _STRATEGY.analyze_pair('foo')
+    assert log_has_re(r'Strategy caused the following exception: xyz.*', caplog)
+
+
+def test_get_signal_old_dataframe(default_conf, mocker, caplog, ohlcv_history):
+    # default_conf defines a 5m interval. we check interval * 2 + 5m
+    # this is necessary as the last candle is removed (partial candles) by default
+    ohlcv_history.loc[1, 'date'] = arrow.utcnow().shift(minutes=-16)
+    # Take a copy to correctly modify the call
+    mocked_history = ohlcv_history.copy()
+    mocked_history['sell'] = 0
+    mocked_history['buy'] = 0
+    mocked_history.loc[1, 'buy'] = 1
+
+    caplog.set_level(logging.INFO)
+    mocker.patch.object(_STRATEGY, 'assert_df')
+
+    assert (False, False) == _STRATEGY.get_signal('xyz', default_conf['timeframe'], mocked_history)
+    assert log_has('Outdated history for pair xyz. Last tick is 16 minutes old', caplog)
+
+
+def test_assert_df_raise(default_conf, mocker, caplog, ohlcv_history):
+    # default_conf defines a 5m interval. we check interval * 2 + 5m
+    # this is necessary as the last candle is removed (partial candles) by default
+    ohlcv_history.loc[1, 'date'] = arrow.utcnow().shift(minutes=-16)
+    # Take a copy to correctly modify the call
+    mocked_history = ohlcv_history.copy()
+    mocked_history['sell'] = 0
+    mocked_history['buy'] = 0
+    mocked_history.loc[1, 'buy'] = 1
+
+    caplog.set_level(logging.INFO)
+    mocker.patch.object(_STRATEGY.dp, 'ohlcv', return_value=ohlcv_history)
+    mocker.patch.object(_STRATEGY.dp, 'get_analyzed_dataframe', return_value=(mocked_history, 0))
+    mocker.patch.object(
+        _STRATEGY, 'assert_df',
+        side_effect=StrategyError('Dataframe returned...')
+    )
+    _STRATEGY.analyze_pair('xyz')
+    assert log_has('Unable to analyze candle (OHLCV) data for pair xyz: Dataframe returned...',
+                   caplog)
+
+
+def test_assert_df(default_conf, mocker, ohlcv_history, caplog):
+    # Ensure it's running when passed correctly
+    _STRATEGY.assert_df(ohlcv_history, len(ohlcv_history),
+                        ohlcv_history.loc[1, 'close'], ohlcv_history.loc[1, 'date'])
+
+    with pytest.raises(StrategyError, match=r"Dataframe returned from strategy.*length\."):
+        _STRATEGY.assert_df(ohlcv_history, len(ohlcv_history) + 1,
+                            ohlcv_history.loc[1, 'close'], ohlcv_history.loc[1, 'date'])
+
+    with pytest.raises(StrategyError,
+                       match=r"Dataframe returned from strategy.*last close price\."):
+        _STRATEGY.assert_df(ohlcv_history, len(ohlcv_history),
+                            ohlcv_history.loc[1, 'close'] + 0.01, ohlcv_history.loc[1, 'date'])
+    with pytest.raises(StrategyError,
+                       match=r"Dataframe returned from strategy.*last date\."):
+        _STRATEGY.assert_df(ohlcv_history, len(ohlcv_history),
+                            ohlcv_history.loc[1, 'close'], ohlcv_history.loc[0, 'date'])
+
+    _STRATEGY.disable_dataframe_checks = True
+    caplog.clear()
+    _STRATEGY.assert_df(ohlcv_history, len(ohlcv_history),
+                        ohlcv_history.loc[1, 'close'], ohlcv_history.loc[0, 'date'])
+    assert log_has_re(r"Dataframe returned from strategy.*last date\.", caplog)
+    # reset to avoid problems in other tests due to test leakage
+    _STRATEGY.disable_dataframe_checks = False
+
+
+def test_ohlcvdata_to_dataframe(default_conf, testdatadir) -> None:
+    default_conf.update({'strategy': 'DefaultStrategy'})
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    timerange = TimeRange.parse_timerange('1510694220-1510700340')
+    data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
+                     fill_up_missing=True)
+    processed = strategy.ohlcvdata_to_dataframe(data)
+    assert len(processed['UNITTEST/BTC']) == 102  # partial candle was removed
+
+
+def test_ohlcvdata_to_dataframe_copy(mocker, default_conf, testdatadir) -> None:
+    default_conf.update({'strategy': 'DefaultStrategy'})
+    strategy = StrategyResolver.load_strategy(default_conf)
+    aimock = mocker.patch('freqtrade.strategy.interface.IStrategy.advise_indicators')
+    timerange = TimeRange.parse_timerange('1510694220-1510700340')
+    data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
+                     fill_up_missing=True)
+    strategy.ohlcvdata_to_dataframe(data)
+    assert aimock.call_count == 1
+    # Ensure that a copy of the dataframe is passed to advice_indicators
+    assert aimock.call_args_list[0][0][0] is not data
+
+
+def test_min_roi_reached(default_conf, fee) -> None:
+
+    # Use list to confirm sequence does not matter
+    min_roi_list = [{20: 0.05, 55: 0.01, 0: 0.1},
+                    {0: 0.1, 20: 0.05, 55: 0.01}]
+    for roi in min_roi_list:
+        default_conf.update({'strategy': 'DefaultStrategy'})
+        strategy = StrategyResolver.load_strategy(default_conf)
+        strategy.minimal_roi = roi
+        trade = Trade(
+            pair='ETH/BTC',
+            stake_amount=0.001,
+            amount=5,
+            open_date=arrow.utcnow().shift(hours=-1).datetime,
+            fee_open=fee.return_value,
+            fee_close=fee.return_value,
+            exchange='bittrex',
+            open_rate=1,
+        )
+
+        assert not strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-56).datetime)
+        assert strategy.min_roi_reached(trade, 0.12, arrow.utcnow().shift(minutes=-56).datetime)
+
+        assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-39).datetime)
+        assert strategy.min_roi_reached(trade, 0.06, arrow.utcnow().shift(minutes=-39).datetime)
+
+        assert not strategy.min_roi_reached(trade, -0.01, arrow.utcnow().shift(minutes=-1).datetime)
+        assert strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-1).datetime)
+
+
+def test_min_roi_reached2(default_conf, fee) -> None:
+
+    # test with ROI raising after last interval
+    min_roi_list = [{20: 0.07,
+                     30: 0.05,
+                     55: 0.30,
+                     0: 0.1
+                     },
+                    {0: 0.1,
+                     20: 0.07,
+                     30: 0.05,
+                     55: 0.30
+                     },
+                    ]
+    for roi in min_roi_list:
+        default_conf.update({'strategy': 'DefaultStrategy'})
+        strategy = StrategyResolver.load_strategy(default_conf)
+        strategy.minimal_roi = roi
+        trade = Trade(
+            pair='ETH/BTC',
+            stake_amount=0.001,
+            amount=5,
+            open_date=arrow.utcnow().shift(hours=-1).datetime,
+            fee_open=fee.return_value,
+            fee_close=fee.return_value,
+            exchange='bittrex',
+            open_rate=1,
+        )
+
+        assert not strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-56).datetime)
+        assert strategy.min_roi_reached(trade, 0.12, arrow.utcnow().shift(minutes=-56).datetime)
+
+        assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-39).datetime)
+        assert strategy.min_roi_reached(trade, 0.071, arrow.utcnow().shift(minutes=-39).datetime)
+
+        assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-26).datetime)
+        assert strategy.min_roi_reached(trade, 0.06, arrow.utcnow().shift(minutes=-26).datetime)
+
+        # Should not trigger with 20% profit since after 55 minutes only 30% is active.
+        assert not strategy.min_roi_reached(trade, 0.20, arrow.utcnow().shift(minutes=-2).datetime)
+        assert strategy.min_roi_reached(trade, 0.31, arrow.utcnow().shift(minutes=-2).datetime)
+
+
+def test_min_roi_reached3(default_conf, fee) -> None:
+
+    # test for issue #1948
+    min_roi = {20: 0.07,
+               30: 0.05,
+               55: 0.30,
+               }
+    default_conf.update({'strategy': 'DefaultStrategy'})
+    strategy = StrategyResolver.load_strategy(default_conf)
+    strategy.minimal_roi = min_roi
+    trade = Trade(
+        pair='ETH/BTC',
+        stake_amount=0.001,
+        amount=5,
+        open_date=arrow.utcnow().shift(hours=-1).datetime,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        exchange='bittrex',
+        open_rate=1,
+    )
+
+    assert not strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-56).datetime)
+    assert not strategy.min_roi_reached(trade, 0.12, arrow.utcnow().shift(minutes=-56).datetime)
+
+    assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-39).datetime)
+    assert strategy.min_roi_reached(trade, 0.071, arrow.utcnow().shift(minutes=-39).datetime)
+
+    assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-26).datetime)
+    assert strategy.min_roi_reached(trade, 0.06, arrow.utcnow().shift(minutes=-26).datetime)
+
+    # Should not trigger with 20% profit since after 55 minutes only 30% is active.
+    assert not strategy.min_roi_reached(trade, 0.20, arrow.utcnow().shift(minutes=-2).datetime)
+    assert strategy.min_roi_reached(trade, 0.31, arrow.utcnow().shift(minutes=-2).datetime)
+
+
+def test_analyze_ticker_default(ohlcv_history, mocker, caplog) -> None:
+    caplog.set_level(logging.DEBUG)
+    ind_mock = MagicMock(side_effect=lambda x, meta: x)
+    buy_mock = MagicMock(side_effect=lambda x, meta: x)
+    sell_mock = MagicMock(side_effect=lambda x, meta: x)
+    mocker.patch.multiple(
+        'freqtrade.strategy.interface.IStrategy',
+        advise_indicators=ind_mock,
+        advise_buy=buy_mock,
+        advise_sell=sell_mock,
+
+    )
+    strategy = DefaultStrategy({})
+    strategy.analyze_ticker(ohlcv_history, {'pair': 'ETH/BTC'})
+    assert ind_mock.call_count == 1
+    assert buy_mock.call_count == 1
+    assert buy_mock.call_count == 1
+
+    assert log_has('TA Analysis Launched', caplog)
+    assert not log_has('Skipping TA Analysis for already analyzed candle', caplog)
+    caplog.clear()
+
+    strategy.analyze_ticker(ohlcv_history, {'pair': 'ETH/BTC'})
+    # No analysis happens as process_only_new_candles is true
+    assert ind_mock.call_count == 2
+    assert buy_mock.call_count == 2
+    assert buy_mock.call_count == 2
+    assert log_has('TA Analysis Launched', caplog)
+    assert not log_has('Skipping TA Analysis for already analyzed candle', caplog)
+
+
+def test__analyze_ticker_internal_skip_analyze(ohlcv_history, mocker, caplog) -> None:
+    caplog.set_level(logging.DEBUG)
+    ind_mock = MagicMock(side_effect=lambda x, meta: x)
+    buy_mock = MagicMock(side_effect=lambda x, meta: x)
+    sell_mock = MagicMock(side_effect=lambda x, meta: x)
+    mocker.patch.multiple(
+        'freqtrade.strategy.interface.IStrategy',
+        advise_indicators=ind_mock,
+        advise_buy=buy_mock,
+        advise_sell=sell_mock,
+
+    )
+    strategy = DefaultStrategy({})
+    strategy.dp = DataProvider({}, None, None)
+    strategy.process_only_new_candles = True
+
+    ret = strategy._analyze_ticker_internal(ohlcv_history, {'pair': 'ETH/BTC'})
+    assert 'high' in ret.columns
+    assert 'low' in ret.columns
+    assert 'close' in ret.columns
+    assert isinstance(ret, DataFrame)
+    assert ind_mock.call_count == 1
+    assert buy_mock.call_count == 1
+    assert buy_mock.call_count == 1
+    assert log_has('TA Analysis Launched', caplog)
+    assert not log_has('Skipping TA Analysis for already analyzed candle', caplog)
+    caplog.clear()
+
+    ret = strategy._analyze_ticker_internal(ohlcv_history, {'pair': 'ETH/BTC'})
+    # No analysis happens as process_only_new_candles is true
+    assert ind_mock.call_count == 1
+    assert buy_mock.call_count == 1
+    assert buy_mock.call_count == 1
+    # only skipped analyze adds buy and sell columns, otherwise it's all mocked
+    assert 'buy' in ret.columns
+    assert 'sell' in ret.columns
+    assert ret['buy'].sum() == 0
+    assert ret['sell'].sum() == 0
+    assert not log_has('TA Analysis Launched', caplog)
+    assert log_has('Skipping TA Analysis for already analyzed candle', caplog)
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_is_pair_locked(default_conf):
+    default_conf.update({'strategy': 'DefaultStrategy'})
+    PairLocks.timeframe = default_conf['timeframe']
+    strategy = StrategyResolver.load_strategy(default_conf)
+    # No lock should be present
+    assert len(PairLocks.get_pair_locks(None)) == 0
+
+    pair = 'ETH/BTC'
+    assert not strategy.is_pair_locked(pair)
+    strategy.lock_pair(pair, arrow.now(timezone.utc).shift(minutes=4).datetime)
+    # ETH/BTC locked for 4 minutes
+    assert strategy.is_pair_locked(pair)
+
+    # XRP/BTC should not be locked now
+    pair = 'XRP/BTC'
+    assert not strategy.is_pair_locked(pair)
+
+    # Unlocking a pair that's not locked should not raise an error
+    strategy.unlock_pair(pair)
+
+    # Unlock original pair
+    pair = 'ETH/BTC'
+    strategy.unlock_pair(pair)
+    assert not strategy.is_pair_locked(pair)
+
+    pair = 'BTC/USDT'
+    # Lock until 14:30
+    lock_time = datetime(2020, 5, 1, 14, 30, 0, tzinfo=timezone.utc)
+    # Subtract 2 seconds, as locking rounds up to the next candle.
+    strategy.lock_pair(pair, lock_time - timedelta(seconds=2))
+
+    assert not strategy.is_pair_locked(pair)
+    # latest candle is from 14:20, lock goes to 14:30
+    assert strategy.is_pair_locked(pair, lock_time + timedelta(minutes=-10))
+    assert strategy.is_pair_locked(pair, lock_time + timedelta(minutes=-50))
+
+    # latest candle is from 14:25 (lock should be lifted)
+    # Since this is the "new candle" available at 14:30
+    assert not strategy.is_pair_locked(pair, lock_time + timedelta(minutes=-4))
+
+    # Should not be locked after time expired
+    assert not strategy.is_pair_locked(pair, lock_time + timedelta(minutes=10))
+
+    # Change timeframe to 15m
+    strategy.timeframe = '15m'
+    # Candle from 14:14 - lock goes until 14:30
+    assert strategy.is_pair_locked(pair, lock_time + timedelta(minutes=-16))
+    assert strategy.is_pair_locked(pair, lock_time + timedelta(minutes=-15, seconds=-2))
+    # Candle from 14:15 - lock goes until 14:30
+    assert not strategy.is_pair_locked(pair, lock_time + timedelta(minutes=-15))
+
+
+def test_is_informative_pairs_callback(default_conf):
+    default_conf.update({'strategy': 'TestStrategyLegacy'})
+    strategy = StrategyResolver.load_strategy(default_conf)
+    # Should return empty
+    # Uses fallback to base implementation
+    assert [] == strategy.informative_pairs()
+
+
+@pytest.mark.parametrize('error', [
+    ValueError, KeyError, Exception,
+])
+def test_strategy_safe_wrapper_error(caplog, error):
+    def failing_method():
+        raise error('This is an error.')
+
+    def working_method(argumentpassedin):
+        return argumentpassedin
+
+    with pytest.raises(StrategyError, match=r'This is an error.'):
+        strategy_safe_wrapper(failing_method, message='DeadBeef')()
+
+    assert log_has_re(r'DeadBeef.*', caplog)
+    ret = strategy_safe_wrapper(failing_method, message='DeadBeef', default_retval=True)()
+
+    assert isinstance(ret, bool)
+    assert ret
+
+    caplog.clear()
+    # Test supressing error
+    ret = strategy_safe_wrapper(failing_method, message='DeadBeef', supress_error=True)()
+    assert log_has_re(r'DeadBeef.*', caplog)
+
+
+@pytest.mark.parametrize('value', [
+    1, 22, 55, True, False, {'a': 1, 'b': '112'},
+    [1, 2, 3, 4], (4, 2, 3, 6)
+])
+def test_strategy_safe_wrapper(value):
+
+    def working_method(argumentpassedin):
+        return argumentpassedin
+
+    ret = strategy_safe_wrapper(working_method, message='DeadBeef')(value)
+
+    assert type(ret) == type(value)
+    assert ret == value
diff --git a/tests/strategy/test_strategy.py b/tests/strategy/test_strategy.py
new file mode 100644
index 000000000..1c692d2da
--- /dev/null
+++ b/tests/strategy/test_strategy.py
@@ -0,0 +1,419 @@
+# pragma pylint: disable=missing-docstring, protected-access, C0103
+import logging
+import warnings
+from base64 import urlsafe_b64encode
+from pathlib import Path
+
+import pytest
+from pandas import DataFrame
+
+from freqtrade.exceptions import OperationalException
+from freqtrade.resolvers import StrategyResolver
+from freqtrade.strategy.interface import IStrategy
+from tests.conftest import log_has, log_has_re
+
+
+def test_search_strategy():
+    default_location = Path(__file__).parent / 'strats'
+
+    s, _ = StrategyResolver._search_object(
+        directory=default_location,
+        object_name='DefaultStrategy',
+        add_source=True,
+    )
+    assert issubclass(s, IStrategy)
+
+    s, _ = StrategyResolver._search_object(
+        directory=default_location,
+        object_name='NotFoundStrategy',
+        add_source=True,
+    )
+    assert s is None
+
+
+def test_search_all_strategies_no_failed():
+    directory = Path(__file__).parent / "strats"
+    strategies = StrategyResolver.search_all_objects(directory, enum_failed=False)
+    assert isinstance(strategies, list)
+    assert len(strategies) == 2
+    assert isinstance(strategies[0], dict)
+
+
+def test_search_all_strategies_with_failed():
+    directory = Path(__file__).parent / "strats"
+    strategies = StrategyResolver.search_all_objects(directory, enum_failed=True)
+    assert isinstance(strategies, list)
+    assert len(strategies) == 3
+    # with enum_failed=True search_all_objects() shall find 2 good strategies
+    # and 1 which fails to load
+    assert len([x for x in strategies if x['class'] is not None]) == 2
+    assert len([x for x in strategies if x['class'] is None]) == 1
+
+
+def test_load_strategy(default_conf, result):
+    default_conf.update({'strategy': 'SampleStrategy',
+                         'strategy_path': str(Path(__file__).parents[2] / 'freqtrade/templates')
+                         })
+    strategy = StrategyResolver.load_strategy(default_conf)
+    assert isinstance(strategy.__source__, str)
+    assert 'class SampleStrategy' in strategy.__source__
+    assert isinstance(strategy.__file__, str)
+    assert 'rsi' in strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
+
+
+def test_load_strategy_base64(result, caplog, default_conf):
+    with (Path(__file__).parents[2] / 'freqtrade/templates/sample_strategy.py').open("rb") as file:
+        encoded_string = urlsafe_b64encode(file.read()).decode("utf-8")
+    default_conf.update({'strategy': 'SampleStrategy:{}'.format(encoded_string)})
+
+    strategy = StrategyResolver.load_strategy(default_conf)
+    assert 'rsi' in strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
+    # Make sure strategy was loaded from base64 (using temp directory)!!
+    assert log_has_re(r"Using resolved strategy SampleStrategy from '"
+                      r".*(/|\\).*(/|\\)SampleStrategy\.py'\.\.\.", caplog)
+
+
+def test_load_strategy_invalid_directory(result, caplog, default_conf):
+    default_conf['strategy'] = 'DefaultStrategy'
+    extra_dir = Path.cwd() / 'some/path'
+    with pytest.raises(OperationalException):
+        StrategyResolver._load_strategy('DefaultStrategy', config=default_conf,
+                                        extra_dir=extra_dir)
+
+    assert log_has_re(r'Path .*' + r'some.*path.*' + r'.* does not exist', caplog)
+
+
+def test_load_not_found_strategy(default_conf):
+    default_conf['strategy'] = 'NotFoundStrategy'
+    with pytest.raises(OperationalException,
+                       match=r"Impossible to load Strategy 'NotFoundStrategy'. "
+                             r"This class does not exist or contains Python code errors."):
+        StrategyResolver.load_strategy(default_conf)
+
+
+def test_load_strategy_noname(default_conf):
+    default_conf['strategy'] = ''
+    with pytest.raises(OperationalException,
+                       match="No strategy set. Please use `--strategy` to specify "
+                             "the strategy class to use."):
+        StrategyResolver.load_strategy(default_conf)
+
+
+def test_strategy(result, default_conf):
+    default_conf.update({'strategy': 'DefaultStrategy'})
+
+    strategy = StrategyResolver.load_strategy(default_conf)
+    metadata = {'pair': 'ETH/BTC'}
+    assert strategy.minimal_roi[0] == 0.04
+    assert default_conf["minimal_roi"]['0'] == 0.04
+
+    assert strategy.stoploss == -0.10
+    assert default_conf['stoploss'] == -0.10
+
+    assert strategy.timeframe == '5m'
+    assert strategy.ticker_interval == '5m'
+    assert default_conf['timeframe'] == '5m'
+
+    df_indicators = strategy.advise_indicators(result, metadata=metadata)
+    assert 'adx' in df_indicators
+
+    dataframe = strategy.advise_buy(df_indicators, metadata=metadata)
+    assert 'buy' in dataframe.columns
+
+    dataframe = strategy.advise_sell(df_indicators, metadata=metadata)
+    assert 'sell' in dataframe.columns
+
+
+def test_strategy_override_minimal_roi(caplog, default_conf):
+    caplog.set_level(logging.INFO)
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+        'minimal_roi': {
+            "0": 0.5
+        }
+    })
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    assert strategy.minimal_roi[0] == 0.5
+    assert log_has("Override strategy 'minimal_roi' with value in config file: {'0': 0.5}.", caplog)
+
+
+def test_strategy_override_stoploss(caplog, default_conf):
+    caplog.set_level(logging.INFO)
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+        'stoploss': -0.5
+    })
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    assert strategy.stoploss == -0.5
+    assert log_has("Override strategy 'stoploss' with value in config file: -0.5.", caplog)
+
+
+def test_strategy_override_trailing_stop(caplog, default_conf):
+    caplog.set_level(logging.INFO)
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+        'trailing_stop': True
+    })
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    assert strategy.trailing_stop
+    assert isinstance(strategy.trailing_stop, bool)
+    assert log_has("Override strategy 'trailing_stop' with value in config file: True.", caplog)
+
+
+def test_strategy_override_trailing_stop_positive(caplog, default_conf):
+    caplog.set_level(logging.INFO)
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+        'trailing_stop_positive': -0.1,
+        'trailing_stop_positive_offset': -0.2
+
+    })
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    assert strategy.trailing_stop_positive == -0.1
+    assert log_has("Override strategy 'trailing_stop_positive' with value in config file: -0.1.",
+                   caplog)
+
+    assert strategy.trailing_stop_positive_offset == -0.2
+    assert log_has("Override strategy 'trailing_stop_positive' with value in config file: -0.1.",
+                   caplog)
+
+
+def test_strategy_override_timeframe(caplog, default_conf):
+    caplog.set_level(logging.INFO)
+
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+        'timeframe': 60,
+        'stake_currency': 'ETH'
+    })
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    assert strategy.timeframe == 60
+    assert strategy.stake_currency == 'ETH'
+    assert log_has("Override strategy 'timeframe' with value in config file: 60.",
+                   caplog)
+
+
+def test_strategy_override_process_only_new_candles(caplog, default_conf):
+    caplog.set_level(logging.INFO)
+
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+        'process_only_new_candles': True
+    })
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    assert strategy.process_only_new_candles
+    assert log_has("Override strategy 'process_only_new_candles' with value in config file: True.",
+                   caplog)
+
+
+def test_strategy_override_order_types(caplog, default_conf):
+    caplog.set_level(logging.INFO)
+
+    order_types = {
+        'buy': 'market',
+        'sell': 'limit',
+        'stoploss': 'limit',
+        'stoploss_on_exchange': True,
+    }
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+        'order_types': order_types
+    })
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    assert strategy.order_types
+    for method in ['buy', 'sell', 'stoploss', 'stoploss_on_exchange']:
+        assert strategy.order_types[method] == order_types[method]
+
+    assert log_has("Override strategy 'order_types' with value in config file:"
+                   " {'buy': 'market', 'sell': 'limit', 'stoploss': 'limit',"
+                   " 'stoploss_on_exchange': True}.", caplog)
+
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+        'order_types': {'buy': 'market'}
+    })
+    # Raise error for invalid configuration
+    with pytest.raises(ImportError,
+                       match=r"Impossible to load Strategy 'DefaultStrategy'. "
+                             r"Order-types mapping is incomplete."):
+        StrategyResolver.load_strategy(default_conf)
+
+
+def test_strategy_override_order_tif(caplog, default_conf):
+    caplog.set_level(logging.INFO)
+
+    order_time_in_force = {
+        'buy': 'fok',
+        'sell': 'gtc',
+    }
+
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+        'order_time_in_force': order_time_in_force
+    })
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    assert strategy.order_time_in_force
+    for method in ['buy', 'sell']:
+        assert strategy.order_time_in_force[method] == order_time_in_force[method]
+
+    assert log_has("Override strategy 'order_time_in_force' with value in config file:"
+                   " {'buy': 'fok', 'sell': 'gtc'}.", caplog)
+
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+        'order_time_in_force': {'buy': 'fok'}
+    })
+    # Raise error for invalid configuration
+    with pytest.raises(ImportError,
+                       match=r"Impossible to load Strategy 'DefaultStrategy'. "
+                             r"Order-time-in-force mapping is incomplete."):
+        StrategyResolver.load_strategy(default_conf)
+
+
+def test_strategy_override_use_sell_signal(caplog, default_conf):
+    caplog.set_level(logging.INFO)
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+    })
+    strategy = StrategyResolver.load_strategy(default_conf)
+    assert strategy.use_sell_signal
+    assert isinstance(strategy.use_sell_signal, bool)
+    # must be inserted to configuration
+    assert 'use_sell_signal' in default_conf['ask_strategy']
+    assert default_conf['ask_strategy']['use_sell_signal']
+
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+        'ask_strategy': {
+            'use_sell_signal': False,
+        },
+    })
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    assert not strategy.use_sell_signal
+    assert isinstance(strategy.use_sell_signal, bool)
+    assert log_has("Override strategy 'use_sell_signal' with value in config file: False.", caplog)
+
+
+def test_strategy_override_use_sell_profit_only(caplog, default_conf):
+    caplog.set_level(logging.INFO)
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+    })
+    strategy = StrategyResolver.load_strategy(default_conf)
+    assert not strategy.sell_profit_only
+    assert isinstance(strategy.sell_profit_only, bool)
+    # must be inserted to configuration
+    assert 'sell_profit_only' in default_conf['ask_strategy']
+    assert not default_conf['ask_strategy']['sell_profit_only']
+
+    default_conf.update({
+        'strategy': 'DefaultStrategy',
+        'ask_strategy': {
+            'sell_profit_only': True,
+        },
+    })
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    assert strategy.sell_profit_only
+    assert isinstance(strategy.sell_profit_only, bool)
+    assert log_has("Override strategy 'sell_profit_only' with value in config file: True.", caplog)
+
+
+@pytest.mark.filterwarnings("ignore:deprecated")
+def test_deprecate_populate_indicators(result, default_conf):
+    default_location = Path(__file__).parent / "strats"
+    default_conf.update({'strategy': 'TestStrategyLegacy',
+                         'strategy_path': default_location})
+    strategy = StrategyResolver.load_strategy(default_conf)
+    with warnings.catch_warnings(record=True) as w:
+        # Cause all warnings to always be triggered.
+        warnings.simplefilter("always")
+        indicators = strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
+        assert len(w) == 1
+        assert issubclass(w[-1].category, DeprecationWarning)
+        assert "deprecated - check out the Sample strategy to see the current function headers!" \
+            in str(w[-1].message)
+
+    with warnings.catch_warnings(record=True) as w:
+        # Cause all warnings to always be triggered.
+        warnings.simplefilter("always")
+        strategy.advise_buy(indicators, {'pair': 'ETH/BTC'})
+        assert len(w) == 1
+        assert issubclass(w[-1].category, DeprecationWarning)
+        assert "deprecated - check out the Sample strategy to see the current function headers!" \
+            in str(w[-1].message)
+
+    with warnings.catch_warnings(record=True) as w:
+        # Cause all warnings to always be triggered.
+        warnings.simplefilter("always")
+        strategy.advise_sell(indicators, {'pair': 'ETH_BTC'})
+        assert len(w) == 1
+        assert issubclass(w[-1].category, DeprecationWarning)
+        assert "deprecated - check out the Sample strategy to see the current function headers!" \
+            in str(w[-1].message)
+
+
+@pytest.mark.filterwarnings("ignore:deprecated")
+def test_call_deprecated_function(result, monkeypatch, default_conf, caplog):
+    default_location = Path(__file__).parent / "strats"
+    del default_conf['timeframe']
+    default_conf.update({'strategy': 'TestStrategyLegacy',
+                         'strategy_path': default_location})
+    strategy = StrategyResolver.load_strategy(default_conf)
+    metadata = {'pair': 'ETH/BTC'}
+
+    # Make sure we are using a legacy function
+    assert strategy._populate_fun_len == 2
+    assert strategy._buy_fun_len == 2
+    assert strategy._sell_fun_len == 2
+    assert strategy.INTERFACE_VERSION == 1
+    assert strategy.timeframe == '5m'
+    assert strategy.ticker_interval == '5m'
+
+    indicator_df = strategy.advise_indicators(result, metadata=metadata)
+    assert isinstance(indicator_df, DataFrame)
+    assert 'adx' in indicator_df.columns
+
+    buydf = strategy.advise_buy(result, metadata=metadata)
+    assert isinstance(buydf, DataFrame)
+    assert 'buy' in buydf.columns
+
+    selldf = strategy.advise_sell(result, metadata=metadata)
+    assert isinstance(selldf, DataFrame)
+    assert 'sell' in selldf
+
+    assert log_has("DEPRECATED: Please migrate to using 'timeframe' instead of 'ticker_interval'.",
+                   caplog)
+
+
+def test_strategy_interface_versioning(result, monkeypatch, default_conf):
+    default_conf.update({'strategy': 'DefaultStrategy'})
+    strategy = StrategyResolver.load_strategy(default_conf)
+    metadata = {'pair': 'ETH/BTC'}
+
+    # Make sure we are using a legacy function
+    assert strategy._populate_fun_len == 3
+    assert strategy._buy_fun_len == 3
+    assert strategy._sell_fun_len == 3
+    assert strategy.INTERFACE_VERSION == 2
+
+    indicator_df = strategy.advise_indicators(result, metadata=metadata)
+    assert isinstance(indicator_df, DataFrame)
+    assert 'adx' in indicator_df.columns
+
+    buydf = strategy.advise_buy(result, metadata=metadata)
+    assert isinstance(buydf, DataFrame)
+    assert 'buy' in buydf.columns
+
+    selldf = strategy.advise_sell(result, metadata=metadata)
+    assert isinstance(selldf, DataFrame)
+    assert 'sell' in selldf
diff --git a/tests/strategy/test_strategy_helpers.py b/tests/strategy/test_strategy_helpers.py
new file mode 100644
index 000000000..1d3e80d24
--- /dev/null
+++ b/tests/strategy/test_strategy_helpers.py
@@ -0,0 +1,88 @@
+import numpy as np
+import pandas as pd
+
+from freqtrade.strategy import merge_informative_pair, timeframe_to_minutes
+
+
+def generate_test_data(timeframe: str, size: int):
+    np.random.seed(42)
+    tf_mins = timeframe_to_minutes(timeframe)
+
+    base = np.random.normal(20, 2, size=size)
+
+    date = pd.period_range('2020-07-05', periods=size, freq=f'{tf_mins}min').to_timestamp()
+    df = pd.DataFrame({
+        'date': date,
+        'open': base,
+        'high': base + np.random.normal(2, 1, size=size),
+        'low': base - np.random.normal(2, 1, size=size),
+        'close': base + np.random.normal(0, 1, size=size),
+        'volume': np.random.normal(200, size=size)
+    }
+    )
+    df = df.dropna()
+    return df
+
+
+def test_merge_informative_pair():
+    data = generate_test_data('15m', 40)
+    informative = generate_test_data('1h', 40)
+
+    result = merge_informative_pair(data, informative, '15m', '1h', ffill=True)
+    assert isinstance(result, pd.DataFrame)
+    assert len(result) == len(data)
+    assert 'date' in result.columns
+    assert result['date'].equals(data['date'])
+    assert 'date_1h' in result.columns
+
+    assert 'open' in result.columns
+    assert 'open_1h' in result.columns
+    assert result['open'].equals(data['open'])
+
+    assert 'close' in result.columns
+    assert 'close_1h' in result.columns
+    assert result['close'].equals(data['close'])
+
+    assert 'volume' in result.columns
+    assert 'volume_1h' in result.columns
+    assert result['volume'].equals(data['volume'])
+
+    # First 4 rows are empty
+    assert result.iloc[0]['date_1h'] is pd.NaT
+    assert result.iloc[1]['date_1h'] is pd.NaT
+    assert result.iloc[2]['date_1h'] is pd.NaT
+    assert result.iloc[3]['date_1h'] is pd.NaT
+    # Next 4 rows contain the starting date (0:00)
+    assert result.iloc[4]['date_1h'] == result.iloc[0]['date']
+    assert result.iloc[5]['date_1h'] == result.iloc[0]['date']
+    assert result.iloc[6]['date_1h'] == result.iloc[0]['date']
+    assert result.iloc[7]['date_1h'] == result.iloc[0]['date']
+    # Next 4 rows contain the next Hourly date original date row 4
+    assert result.iloc[8]['date_1h'] == result.iloc[4]['date']
+
+
+def test_merge_informative_pair_same():
+    data = generate_test_data('15m', 40)
+    informative = generate_test_data('15m', 40)
+
+    result = merge_informative_pair(data, informative, '15m', '15m', ffill=True)
+    assert isinstance(result, pd.DataFrame)
+    assert len(result) == len(data)
+    assert 'date' in result.columns
+    assert result['date'].equals(data['date'])
+    assert 'date_15m' in result.columns
+
+    assert 'open' in result.columns
+    assert 'open_15m' in result.columns
+    assert result['open'].equals(data['open'])
+
+    assert 'close' in result.columns
+    assert 'close_15m' in result.columns
+    assert result['close'].equals(data['close'])
+
+    assert 'volume' in result.columns
+    assert 'volume_15m' in result.columns
+    assert result['volume'].equals(data['volume'])
+
+    # Dates match 1:1
+    assert result['date_15m'].equals(result['date'])
diff --git a/tests/test_arguments.py b/tests/test_arguments.py
new file mode 100644
index 000000000..e2a1ae53c
--- /dev/null
+++ b/tests/test_arguments.py
@@ -0,0 +1,279 @@
+# pragma pylint: disable=missing-docstring, C0103
+import argparse
+from pathlib import Path
+from unittest.mock import MagicMock
+
+import pytest
+
+from freqtrade.commands import Arguments
+from freqtrade.commands.cli_options import check_int_nonzero, check_int_positive
+
+
+# Parse common command-line-arguments. Used for all tools
+def test_parse_args_none() -> None:
+    arguments = Arguments(['trade'])
+    assert isinstance(arguments, Arguments)
+    x = arguments.get_parsed_arg()
+    assert isinstance(x, dict)
+    assert isinstance(arguments.parser, argparse.ArgumentParser)
+
+
+def test_parse_args_defaults(mocker) -> None:
+    mocker.patch.object(Path, 'is_file', MagicMock(side_effect=[False, True]))
+    args = Arguments(['trade']).get_parsed_arg()
+    assert args['config'] == ['config.json']
+    assert args['strategy_path'] is None
+    assert args['datadir'] is None
+    assert args['verbosity'] == 0
+
+
+def test_parse_args_default_userdatadir(mocker) -> None:
+    mocker.patch.object(Path, 'is_file', MagicMock(return_value=True))
+    args = Arguments(['trade']).get_parsed_arg()
+    # configuration defaults to user_data if that is available.
+    assert args['config'] == [str(Path('user_data/config.json'))]
+    assert args['strategy_path'] is None
+    assert args['datadir'] is None
+    assert args['verbosity'] == 0
+
+
+def test_parse_args_userdatadir(mocker) -> None:
+    mocker.patch.object(Path, 'is_file', MagicMock(return_value=True))
+    args = Arguments(['trade', '--user-data-dir', 'user_data']).get_parsed_arg()
+    # configuration defaults to user_data if that is available.
+    assert args['config'] == [str(Path('user_data/config.json'))]
+    assert args['strategy_path'] is None
+    assert args['datadir'] is None
+    assert args['verbosity'] == 0
+
+
+def test_parse_args_config() -> None:
+    args = Arguments(['trade', '-c', '/dev/null']).get_parsed_arg()
+    assert args['config'] == ['/dev/null']
+
+    args = Arguments(['trade', '--config', '/dev/null']).get_parsed_arg()
+    assert args['config'] == ['/dev/null']
+
+    args = Arguments(['trade', '--config', '/dev/null',
+                      '--config', '/dev/zero'],).get_parsed_arg()
+    assert args['config'] == ['/dev/null', '/dev/zero']
+
+
+def test_parse_args_db_url() -> None:
+    args = Arguments(['trade', '--db-url', 'sqlite:///test.sqlite']).get_parsed_arg()
+    assert args['db_url'] == 'sqlite:///test.sqlite'
+
+
+def test_parse_args_verbose() -> None:
+    args = Arguments(['trade', '-v']).get_parsed_arg()
+    assert args['verbosity'] == 1
+
+    args = Arguments(['trade', '--verbose']).get_parsed_arg()
+    assert args['verbosity'] == 1
+
+
+def test_common_scripts_options() -> None:
+    args = Arguments(['download-data', '-p', 'ETH/BTC', 'XRP/BTC']).get_parsed_arg()
+
+    assert args['pairs'] == ['ETH/BTC', 'XRP/BTC']
+    assert 'func' in args
+
+
+def test_parse_args_version() -> None:
+    with pytest.raises(SystemExit, match=r'0'):
+        Arguments(['--version']).get_parsed_arg()
+
+
+def test_parse_args_invalid() -> None:
+    with pytest.raises(SystemExit, match=r'2'):
+        Arguments(['-c']).get_parsed_arg()
+
+
+def test_parse_args_strategy() -> None:
+    args = Arguments(['trade', '--strategy', 'SomeStrategy']).get_parsed_arg()
+    assert args['strategy'] == 'SomeStrategy'
+
+
+def test_parse_args_strategy_invalid() -> None:
+    with pytest.raises(SystemExit, match=r'2'):
+        Arguments(['--strategy']).get_parsed_arg()
+
+
+def test_parse_args_strategy_path() -> None:
+    args = Arguments(['trade', '--strategy-path', '/some/path']).get_parsed_arg()
+    assert args['strategy_path'] == '/some/path'
+
+
+def test_parse_args_strategy_path_invalid() -> None:
+    with pytest.raises(SystemExit, match=r'2'):
+        Arguments(['--strategy-path']).get_parsed_arg()
+
+
+def test_parse_args_backtesting_invalid() -> None:
+    with pytest.raises(SystemExit, match=r'2'):
+        Arguments(['backtesting --ticker-interval']).get_parsed_arg()
+
+    with pytest.raises(SystemExit, match=r'2'):
+        Arguments(['backtesting --ticker-interval', 'abc']).get_parsed_arg()
+
+
+def test_parse_args_backtesting_custom() -> None:
+    args = [
+        'backtesting',
+        '-c', 'test_conf.json',
+        '--ticker-interval', '1m',
+        '--strategy-list',
+        'DefaultStrategy',
+        'SampleStrategy'
+        ]
+    call_args = Arguments(args).get_parsed_arg()
+    assert call_args['config'] == ['test_conf.json']
+    assert call_args['verbosity'] == 0
+    assert call_args['command'] == 'backtesting'
+    assert call_args['func'] is not None
+    assert call_args['timeframe'] == '1m'
+    assert type(call_args['strategy_list']) is list
+    assert len(call_args['strategy_list']) == 2
+
+
+def test_parse_args_hyperopt_custom() -> None:
+    args = [
+        'hyperopt',
+        '-c', 'test_conf.json',
+        '--epochs', '20',
+        '--spaces', 'buy'
+    ]
+    call_args = Arguments(args).get_parsed_arg()
+    assert call_args['config'] == ['test_conf.json']
+    assert call_args['epochs'] == 20
+    assert call_args['verbosity'] == 0
+    assert call_args['command'] == 'hyperopt'
+    assert call_args['spaces'] == ['buy']
+    assert call_args['func'] is not None
+    assert callable(call_args['func'])
+
+
+def test_download_data_options() -> None:
+    args = [
+        'download-data',
+        '--datadir', 'datadir/directory',
+        '--pairs-file', 'file_with_pairs',
+        '--days', '30',
+        '--exchange', 'binance'
+    ]
+    pargs = Arguments(args).get_parsed_arg()
+
+    assert pargs['pairs_file'] == 'file_with_pairs'
+    assert pargs['datadir'] == 'datadir/directory'
+    assert pargs['days'] == 30
+    assert pargs['exchange'] == 'binance'
+
+
+def test_plot_dataframe_options() -> None:
+    args = [
+        'plot-dataframe',
+        '-c', 'config.json.example',
+        '--indicators1', 'sma10', 'sma100',
+        '--indicators2', 'macd', 'fastd', 'fastk',
+        '--plot-limit', '30',
+        '-p', 'UNITTEST/BTC',
+    ]
+    pargs = Arguments(args).get_parsed_arg()
+
+    assert pargs['indicators1'] == ['sma10', 'sma100']
+    assert pargs['indicators2'] == ['macd', 'fastd', 'fastk']
+    assert pargs['plot_limit'] == 30
+    assert pargs['pairs'] == ['UNITTEST/BTC']
+
+
+def test_plot_profit_options() -> None:
+    args = [
+        'plot-profit',
+        '-p', 'UNITTEST/BTC',
+        '--trade-source', 'DB',
+        '--db-url', 'sqlite:///whatever.sqlite',
+    ]
+    pargs = Arguments(args).get_parsed_arg()
+
+    assert pargs['trade_source'] == 'DB'
+    assert pargs['pairs'] == ['UNITTEST/BTC']
+    assert pargs['db_url'] == 'sqlite:///whatever.sqlite'
+
+
+def test_config_notallowed(mocker) -> None:
+    mocker.patch.object(Path, 'is_file', MagicMock(return_value=False))
+    args = [
+        'create-userdir',
+    ]
+    pargs = Arguments(args).get_parsed_arg()
+
+    assert 'config' not in pargs
+
+    # When file exists:
+    mocker.patch.object(Path, 'is_file', MagicMock(return_value=True))
+    args = [
+        'create-userdir',
+    ]
+    pargs = Arguments(args).get_parsed_arg()
+    # config is not added even if it exists, since create-userdir is in the notallowed list
+    assert 'config' not in pargs
+
+
+def test_config_notrequired(mocker) -> None:
+    mocker.patch.object(Path, 'is_file', MagicMock(return_value=False))
+    args = [
+        'download-data',
+    ]
+    pargs = Arguments(args).get_parsed_arg()
+
+    assert pargs['config'] is None
+
+    # When file exists:
+    mocker.patch.object(Path, 'is_file', MagicMock(side_effect=[False, True]))
+    args = [
+        'download-data',
+    ]
+    pargs = Arguments(args).get_parsed_arg()
+    # config is added if it exists
+    assert pargs['config'] == ['config.json']
+
+
+def test_check_int_positive() -> None:
+    assert check_int_positive('3') == 3
+    assert check_int_positive('1') == 1
+    assert check_int_positive('100') == 100
+
+    with pytest.raises(argparse.ArgumentTypeError):
+        check_int_positive('-2')
+
+    with pytest.raises(argparse.ArgumentTypeError):
+        check_int_positive('0')
+
+    with pytest.raises(argparse.ArgumentTypeError):
+        check_int_positive(0)
+
+    with pytest.raises(argparse.ArgumentTypeError):
+        check_int_positive('3.5')
+
+    with pytest.raises(argparse.ArgumentTypeError):
+        check_int_positive('DeadBeef')
+
+
+def test_check_int_nonzero() -> None:
+    assert check_int_nonzero('3') == 3
+    assert check_int_nonzero('1') == 1
+    assert check_int_nonzero('100') == 100
+
+    assert check_int_nonzero('-2') == -2
+
+    with pytest.raises(argparse.ArgumentTypeError):
+        check_int_nonzero('0')
+
+    with pytest.raises(argparse.ArgumentTypeError):
+        check_int_nonzero(0)
+
+    with pytest.raises(argparse.ArgumentTypeError):
+        check_int_nonzero('3.5')
+
+    with pytest.raises(argparse.ArgumentTypeError):
+        check_int_nonzero('DeadBeef')
diff --git a/tests/test_configuration.py b/tests/test_configuration.py
new file mode 100644
index 000000000..7d6c81f74
--- /dev/null
+++ b/tests/test_configuration.py
@@ -0,0 +1,1175 @@
+# pragma pylint: disable=missing-docstring, protected-access, invalid-name
+import json
+import logging
+import sys
+import warnings
+from copy import deepcopy
+from pathlib import Path
+from unittest.mock import MagicMock
+
+import pytest
+from jsonschema import ValidationError
+
+from freqtrade.commands import Arguments
+from freqtrade.configuration import (Configuration, check_exchange, remove_credentials,
+                                     validate_config_consistency)
+from freqtrade.configuration.config_validation import validate_config_schema
+from freqtrade.configuration.deprecated_settings import (check_conflicting_settings,
+                                                         process_deprecated_setting,
+                                                         process_temporary_deprecated_settings)
+from freqtrade.configuration.load_config import load_config_file, log_config_error_range
+from freqtrade.constants import DEFAULT_DB_DRYRUN_URL, DEFAULT_DB_PROD_URL
+from freqtrade.exceptions import OperationalException
+from freqtrade.loggers import _set_loggers, setup_logging, setup_logging_pre
+from freqtrade.state import RunMode
+from tests.conftest import log_has, log_has_re, patched_configuration_load_config_file
+
+
+@pytest.fixture(scope="function")
+def all_conf():
+    config_file = Path(__file__).parents[1] / "config_full.json.example"
+    conf = load_config_file(str(config_file))
+    return conf
+
+
+def test_load_config_missing_attributes(default_conf) -> None:
+    conf = deepcopy(default_conf)
+    conf.pop('exchange')
+
+    with pytest.raises(ValidationError, match=r".*'exchange' is a required property.*"):
+        validate_config_schema(conf)
+
+    conf = deepcopy(default_conf)
+    conf.pop('stake_currency')
+    conf['runmode'] = RunMode.DRY_RUN
+    with pytest.raises(ValidationError, match=r".*'stake_currency' is a required property.*"):
+        validate_config_schema(conf)
+
+
+def test_load_config_incorrect_stake_amount(default_conf) -> None:
+    default_conf['stake_amount'] = 'fake'
+
+    with pytest.raises(ValidationError, match=r".*'fake' does not match 'unlimited'.*"):
+        validate_config_schema(default_conf)
+
+
+def test_load_config_file(default_conf, mocker, caplog) -> None:
+    del default_conf['user_data_dir']
+    file_mock = mocker.patch('freqtrade.configuration.load_config.open', mocker.mock_open(
+        read_data=json.dumps(default_conf)
+    ))
+
+    validated_conf = load_config_file('somefile')
+    assert file_mock.call_count == 1
+    assert validated_conf.items() >= default_conf.items()
+
+
+def test_load_config_file_error(default_conf, mocker, caplog) -> None:
+    del default_conf['user_data_dir']
+    filedata = json.dumps(default_conf).replace(
+        '"stake_amount": 0.001,', '"stake_amount": .001,')
+    mocker.patch('freqtrade.configuration.load_config.open', mocker.mock_open(read_data=filedata))
+    mocker.patch.object(Path, "read_text", MagicMock(return_value=filedata))
+
+    with pytest.raises(OperationalException, match=r".*Please verify the following segment.*"):
+        load_config_file('somefile')
+
+
+def test_load_config_file_error_range(default_conf, mocker, caplog) -> None:
+    del default_conf['user_data_dir']
+    filedata = json.dumps(default_conf).replace(
+        '"stake_amount": 0.001,', '"stake_amount": .001,')
+    mocker.patch.object(Path, "read_text", MagicMock(return_value=filedata))
+
+    x = log_config_error_range('somefile', 'Parse error at offset 64: Invalid value.')
+    assert isinstance(x, str)
+    assert (x == '{"max_open_trades": 1, "stake_currency": "BTC", '
+            '"stake_amount": .001, "fiat_display_currency": "USD", '
+            '"timeframe": "5m", "dry_run": true, "cance')
+
+
+def test__args_to_config(caplog):
+
+    arg_list = ['trade', '--strategy-path', 'TestTest']
+    args = Arguments(arg_list).get_parsed_arg()
+    configuration = Configuration(args)
+    config = {}
+    with warnings.catch_warnings(record=True) as w:
+        warnings.simplefilter("always")
+        # No warnings ...
+        configuration._args_to_config(config, argname="strategy_path", logstring="DeadBeef")
+        assert len(w) == 0
+        assert log_has("DeadBeef", caplog)
+        assert config['strategy_path'] == "TestTest"
+
+    configuration = Configuration(args)
+    config = {}
+    with warnings.catch_warnings(record=True) as w:
+        warnings.simplefilter("always")
+        # Deprecation warnings!
+        configuration._args_to_config(config, argname="strategy_path", logstring="DeadBeef",
+                                      deprecated_msg="Going away soon!")
+        assert len(w) == 1
+        assert issubclass(w[-1].category, DeprecationWarning)
+        assert "DEPRECATED: Going away soon!" in str(w[-1].message)
+        assert log_has("DeadBeef", caplog)
+        assert config['strategy_path'] == "TestTest"
+
+
+def test_load_config_max_open_trades_zero(default_conf, mocker, caplog) -> None:
+    default_conf['max_open_trades'] = 0
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = Arguments(['trade']).get_parsed_arg()
+    configuration = Configuration(args)
+    validated_conf = configuration.load_config()
+
+    assert validated_conf['max_open_trades'] == 0
+    assert 'internals' in validated_conf
+
+
+def test_load_config_combine_dicts(default_conf, mocker, caplog) -> None:
+    conf1 = deepcopy(default_conf)
+    conf2 = deepcopy(default_conf)
+    del conf1['exchange']['key']
+    del conf1['exchange']['secret']
+    del conf2['exchange']['name']
+    conf2['exchange']['pair_whitelist'] += ['NANO/BTC']
+
+    config_files = [conf1, conf2]
+
+    configsmock = MagicMock(side_effect=config_files)
+    mocker.patch(
+        'freqtrade.configuration.configuration.load_config_file',
+        configsmock
+    )
+
+    arg_list = ['trade', '-c', 'test_conf.json', '--config', 'test2_conf.json', ]
+    args = Arguments(arg_list).get_parsed_arg()
+    configuration = Configuration(args)
+    validated_conf = configuration.load_config()
+
+    exchange_conf = default_conf['exchange']
+    assert validated_conf['exchange']['name'] == exchange_conf['name']
+    assert validated_conf['exchange']['key'] == exchange_conf['key']
+    assert validated_conf['exchange']['secret'] == exchange_conf['secret']
+    assert validated_conf['exchange']['pair_whitelist'] != conf1['exchange']['pair_whitelist']
+    assert validated_conf['exchange']['pair_whitelist'] == conf2['exchange']['pair_whitelist']
+
+    assert 'internals' in validated_conf
+
+
+def test_from_config(default_conf, mocker, caplog) -> None:
+    conf1 = deepcopy(default_conf)
+    conf2 = deepcopy(default_conf)
+    del conf1['exchange']['key']
+    del conf1['exchange']['secret']
+    del conf2['exchange']['name']
+    conf2['exchange']['pair_whitelist'] += ['NANO/BTC']
+    conf2['fiat_display_currency'] = "EUR"
+    config_files = [conf1, conf2]
+    mocker.patch('freqtrade.configuration.configuration.create_datadir', lambda c, x: x)
+
+    configsmock = MagicMock(side_effect=config_files)
+    mocker.patch('freqtrade.configuration.configuration.load_config_file', configsmock)
+
+    validated_conf = Configuration.from_files(['test_conf.json', 'test2_conf.json'])
+
+    exchange_conf = default_conf['exchange']
+    assert validated_conf['exchange']['name'] == exchange_conf['name']
+    assert validated_conf['exchange']['key'] == exchange_conf['key']
+    assert validated_conf['exchange']['secret'] == exchange_conf['secret']
+    assert validated_conf['exchange']['pair_whitelist'] != conf1['exchange']['pair_whitelist']
+    assert validated_conf['exchange']['pair_whitelist'] == conf2['exchange']['pair_whitelist']
+    assert validated_conf['fiat_display_currency'] == "EUR"
+    assert 'internals' in validated_conf
+    assert isinstance(validated_conf['user_data_dir'], Path)
+
+
+def test_print_config(default_conf, mocker, caplog) -> None:
+    conf1 = deepcopy(default_conf)
+    # Delete non-json elements from default_conf
+    del conf1['user_data_dir']
+    config_files = [conf1]
+
+    configsmock = MagicMock(side_effect=config_files)
+    mocker.patch('freqtrade.configuration.configuration.create_datadir', lambda c, x: x)
+    mocker.patch('freqtrade.configuration.configuration.load_config_file', configsmock)
+
+    validated_conf = Configuration.from_files(['test_conf.json'])
+
+    assert isinstance(validated_conf['user_data_dir'], Path)
+    assert "user_data_dir" in validated_conf
+    assert "original_config" in validated_conf
+    assert isinstance(json.dumps(validated_conf['original_config']), str)
+
+
+def test_load_config_max_open_trades_minus_one(default_conf, mocker, caplog) -> None:
+    default_conf['max_open_trades'] = -1
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = Arguments(['trade']).get_parsed_arg()
+    configuration = Configuration(args)
+    validated_conf = configuration.load_config()
+
+    assert validated_conf['max_open_trades'] > 999999999
+    assert validated_conf['max_open_trades'] == float('inf')
+    assert "runmode" in validated_conf
+    assert validated_conf['runmode'] == RunMode.DRY_RUN
+
+
+def test_load_config_file_exception(mocker) -> None:
+    mocker.patch(
+        'freqtrade.configuration.configuration.open',
+        MagicMock(side_effect=FileNotFoundError('File not found'))
+    )
+
+    with pytest.raises(OperationalException, match=r'.*Config file "somefile" not found!*'):
+        load_config_file('somefile')
+
+
+def test_load_config(default_conf, mocker) -> None:
+    del default_conf['strategy_path']
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = Arguments(['trade']).get_parsed_arg()
+    configuration = Configuration(args)
+    validated_conf = configuration.load_config()
+
+    assert validated_conf.get('strategy_path') is None
+    assert 'edge' not in validated_conf
+
+
+def test_load_config_with_params(default_conf, mocker) -> None:
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    arglist = [
+        'trade',
+        '--strategy', 'TestStrategy',
+        '--strategy-path', '/some/path',
+        '--db-url', 'sqlite:///someurl',
+    ]
+    args = Arguments(arglist).get_parsed_arg()
+    configuration = Configuration(args)
+    validated_conf = configuration.load_config()
+
+    assert validated_conf.get('strategy') == 'TestStrategy'
+    assert validated_conf.get('strategy_path') == '/some/path'
+    assert validated_conf.get('db_url') == 'sqlite:///someurl'
+
+    # Test conf provided db_url prod
+    conf = default_conf.copy()
+    conf["dry_run"] = False
+    conf["db_url"] = "sqlite:///path/to/db.sqlite"
+    patched_configuration_load_config_file(mocker, conf)
+
+    arglist = [
+        'trade',
+        '--strategy', 'TestStrategy',
+        '--strategy-path', '/some/path'
+    ]
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args)
+    validated_conf = configuration.load_config()
+    assert validated_conf.get('db_url') == "sqlite:///path/to/db.sqlite"
+
+    # Test conf provided db_url dry_run
+    conf = default_conf.copy()
+    conf["dry_run"] = True
+    conf["db_url"] = "sqlite:///path/to/db.sqlite"
+    patched_configuration_load_config_file(mocker, conf)
+
+    arglist = [
+        'trade',
+        '--strategy', 'TestStrategy',
+        '--strategy-path', '/some/path'
+    ]
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args)
+    validated_conf = configuration.load_config()
+    assert validated_conf.get('db_url') == "sqlite:///path/to/db.sqlite"
+
+    # Test args provided db_url prod
+    conf = default_conf.copy()
+    conf["dry_run"] = False
+    del conf["db_url"]
+    patched_configuration_load_config_file(mocker, conf)
+
+    arglist = [
+        'trade',
+        '--strategy', 'TestStrategy',
+        '--strategy-path', '/some/path'
+    ]
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args)
+    validated_conf = configuration.load_config()
+    assert validated_conf.get('db_url') == DEFAULT_DB_PROD_URL
+    assert "runmode" in validated_conf
+    assert validated_conf['runmode'] == RunMode.LIVE
+
+    # Test args provided db_url dry_run
+    conf = default_conf.copy()
+    conf["dry_run"] = True
+    conf["db_url"] = DEFAULT_DB_PROD_URL
+    patched_configuration_load_config_file(mocker, conf)
+
+    arglist = [
+        'trade',
+        '--strategy', 'TestStrategy',
+        '--strategy-path', '/some/path'
+    ]
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args)
+    validated_conf = configuration.load_config()
+    assert validated_conf.get('db_url') == DEFAULT_DB_DRYRUN_URL
+
+
+@pytest.mark.parametrize("config_value,expected,arglist", [
+    (True, True, ['trade', '--dry-run']),  # Leave config untouched
+    (False, True, ['trade', '--dry-run']),  # Override config untouched
+    (False, False, ['trade']),  # Leave config untouched
+    (True, True, ['trade']),  # Leave config untouched
+])
+def test_load_dry_run(default_conf, mocker, config_value, expected, arglist) -> None:
+
+    default_conf['dry_run'] = config_value
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    configuration = Configuration(Arguments(arglist).get_parsed_arg())
+    validated_conf = configuration.load_config()
+
+    assert validated_conf['dry_run'] is expected
+    assert validated_conf['runmode'] == (RunMode.DRY_RUN if expected else RunMode.LIVE)
+
+
+def test_load_custom_strategy(default_conf, mocker) -> None:
+    default_conf.update({
+        'strategy': 'CustomStrategy',
+        'strategy_path': '/tmp/strategies',
+    })
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = Arguments(['trade']).get_parsed_arg()
+    configuration = Configuration(args)
+    validated_conf = configuration.load_config()
+
+    assert validated_conf.get('strategy') == 'CustomStrategy'
+    assert validated_conf.get('strategy_path') == '/tmp/strategies'
+
+
+def test_show_info(default_conf, mocker, caplog) -> None:
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    arglist = [
+        'trade',
+        '--strategy', 'TestStrategy',
+        '--db-url', 'sqlite:///tmp/testdb',
+    ]
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args)
+    configuration.get_config()
+
+    assert log_has('Using DB: "sqlite:///tmp/testdb"', caplog)
+    assert log_has('Dry run is enabled', caplog)
+
+
+def test_setup_configuration_without_arguments(mocker, default_conf, caplog) -> None:
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    arglist = [
+        'backtesting',
+        '--config', 'config.json',
+        '--strategy', 'DefaultStrategy',
+    ]
+
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args)
+    config = configuration.get_config()
+    assert 'max_open_trades' in config
+    assert 'stake_currency' in config
+    assert 'stake_amount' in config
+    assert 'exchange' in config
+    assert 'pair_whitelist' in config['exchange']
+    assert 'datadir' in config
+    assert 'user_data_dir' in config
+    assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
+    assert 'timeframe' in config
+    assert not log_has('Parameter -i/--timeframe detected ...', caplog)
+
+    assert 'position_stacking' not in config
+    assert not log_has('Parameter --enable-position-stacking detected ...', caplog)
+
+    assert 'timerange' not in config
+    assert 'export' not in config
+
+
+def test_setup_configuration_with_arguments(mocker, default_conf, caplog) -> None:
+    patched_configuration_load_config_file(mocker, default_conf)
+    mocker.patch(
+        'freqtrade.configuration.configuration.create_datadir',
+        lambda c, x: x
+    )
+    mocker.patch(
+        'freqtrade.configuration.configuration.create_userdata_dir',
+        lambda x, *args, **kwargs: Path(x)
+    )
+    arglist = [
+        'backtesting',
+        '--config', 'config.json',
+        '--strategy', 'DefaultStrategy',
+        '--datadir', '/foo/bar',
+        '--userdir', "/tmp/freqtrade",
+        '--ticker-interval', '1m',
+        '--enable-position-stacking',
+        '--disable-max-market-positions',
+        '--timerange', ':100',
+        '--export', '/bar/foo'
+    ]
+
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args)
+    config = configuration.get_config()
+    assert 'max_open_trades' in config
+    assert 'stake_currency' in config
+    assert 'stake_amount' in config
+    assert 'exchange' in config
+    assert 'pair_whitelist' in config['exchange']
+    assert 'datadir' in config
+    assert log_has('Using data directory: {} ...'.format("/foo/bar"), caplog)
+    assert log_has('Using user-data directory: {} ...'.format(Path("/tmp/freqtrade")), caplog)
+    assert 'user_data_dir' in config
+
+    assert 'timeframe' in config
+    assert log_has('Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
+                   caplog)
+
+    assert 'position_stacking' in config
+    assert log_has('Parameter --enable-position-stacking detected ...', caplog)
+
+    assert 'use_max_market_positions' in config
+    assert log_has('Parameter --disable-max-market-positions detected ...', caplog)
+    assert log_has('max_open_trades set to unlimited ...', caplog)
+
+    assert 'timerange' in config
+    assert log_has('Parameter --timerange detected: {} ...'.format(config['timerange']), caplog)
+
+    assert 'export' in config
+    assert log_has('Parameter --export detected: {} ...'.format(config['export']), caplog)
+
+
+def test_setup_configuration_with_stratlist(mocker, default_conf, caplog) -> None:
+    """
+    Test setup_configuration() function
+    """
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    arglist = [
+        'backtesting',
+        '--config', 'config.json',
+        '--ticker-interval', '1m',
+        '--export', '/bar/foo',
+        '--strategy-list',
+        'DefaultStrategy',
+        'TestStrategy'
+    ]
+
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args, RunMode.BACKTEST)
+    config = configuration.get_config()
+    assert config['runmode'] == RunMode.BACKTEST
+    assert 'max_open_trades' in config
+    assert 'stake_currency' in config
+    assert 'stake_amount' in config
+    assert 'exchange' in config
+    assert 'pair_whitelist' in config['exchange']
+    assert 'datadir' in config
+    assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
+    assert 'timeframe' in config
+    assert log_has('Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
+                   caplog)
+
+    assert 'strategy_list' in config
+    assert log_has('Using strategy list of 2 strategies', caplog)
+
+    assert 'position_stacking' not in config
+
+    assert 'use_max_market_positions' not in config
+
+    assert 'timerange' not in config
+
+    assert 'export' in config
+    assert log_has('Parameter --export detected: {} ...'.format(config['export']), caplog)
+
+
+def test_hyperopt_with_arguments(mocker, default_conf, caplog) -> None:
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    arglist = [
+        'hyperopt',
+        '--epochs', '10',
+        '--spaces', 'all',
+    ]
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args, RunMode.HYPEROPT)
+    config = configuration.get_config()
+
+    assert 'epochs' in config
+    assert int(config['epochs']) == 10
+    assert log_has('Parameter --epochs detected ... Will run Hyperopt with for 10 epochs ...',
+                   caplog)
+
+    assert 'spaces' in config
+    assert config['spaces'] == ['all']
+    assert log_has("Parameter -s/--spaces detected: ['all']", caplog)
+    assert "runmode" in config
+    assert config['runmode'] == RunMode.HYPEROPT
+
+
+def test_check_exchange(default_conf, caplog) -> None:
+    # Test an officially supported by Freqtrade team exchange
+    default_conf['runmode'] = RunMode.DRY_RUN
+    default_conf.get('exchange').update({'name': 'BITTREX'})
+    assert check_exchange(default_conf)
+    assert log_has_re(r"Exchange .* is officially supported by the Freqtrade development team\.",
+                      caplog)
+    caplog.clear()
+
+    # Test an officially supported by Freqtrade team exchange
+    default_conf.get('exchange').update({'name': 'binance'})
+    assert check_exchange(default_conf)
+    assert log_has_re(r"Exchange .* is officially supported by the Freqtrade development team\.",
+                      caplog)
+    caplog.clear()
+
+    # Test an available exchange, supported by ccxt
+    default_conf.get('exchange').update({'name': 'huobipro'})
+    assert check_exchange(default_conf)
+    assert log_has_re(r"Exchange .* is known to the the ccxt library, available for the bot, "
+                      r"but not officially supported "
+                      r"by the Freqtrade development team\. .*", caplog)
+    caplog.clear()
+
+    # Test a 'bad' exchange, which known to have serious problems
+    default_conf.get('exchange').update({'name': 'bitmex'})
+    with pytest.raises(OperationalException,
+                       match=r"Exchange .* is known to not work with the bot yet.*"):
+        check_exchange(default_conf)
+    caplog.clear()
+
+    # Test a 'bad' exchange with check_for_bad=False
+    default_conf.get('exchange').update({'name': 'bitmex'})
+    assert check_exchange(default_conf, False)
+    assert log_has_re(r"Exchange .* is known to the the ccxt library, available for the bot, "
+                      r"but not officially supported "
+                      r"by the Freqtrade development team\. .*", caplog)
+    caplog.clear()
+
+    # Test an invalid exchange
+    default_conf.get('exchange').update({'name': 'unknown_exchange'})
+    with pytest.raises(
+        OperationalException,
+        match=r'Exchange "unknown_exchange" is not known to the ccxt library '
+              r'and therefore not available for the bot.*'
+    ):
+        check_exchange(default_conf)
+
+    # Test no exchange...
+    default_conf.get('exchange').update({'name': ''})
+    default_conf['runmode'] = RunMode.PLOT
+    assert check_exchange(default_conf)
+
+    # Test no exchange...
+    default_conf.get('exchange').update({'name': ''})
+    default_conf['runmode'] = RunMode.UTIL_EXCHANGE
+    with pytest.raises(OperationalException,
+                       match=r'This command requires a configured exchange.*'):
+        check_exchange(default_conf)
+
+
+def test_remove_credentials(default_conf, caplog) -> None:
+    conf = deepcopy(default_conf)
+    conf['dry_run'] = False
+    remove_credentials(conf)
+
+    assert conf['dry_run'] is True
+    assert conf['exchange']['key'] == ''
+    assert conf['exchange']['secret'] == ''
+    assert conf['exchange']['password'] == ''
+    assert conf['exchange']['uid'] == ''
+
+
+def test_cli_verbose_with_params(default_conf, mocker, caplog) -> None:
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    # Prevent setting loggers
+    mocker.patch('freqtrade.loggers._set_loggers', MagicMock)
+    arglist = ['trade', '-vvv']
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args)
+    validated_conf = configuration.load_config()
+
+    assert validated_conf.get('verbosity') == 3
+    assert log_has('Verbosity set to 3', caplog)
+
+
+def test_set_loggers() -> None:
+    # Reset Logging to Debug, otherwise this fails randomly as it's set globally
+    logging.getLogger('requests').setLevel(logging.DEBUG)
+    logging.getLogger("urllib3").setLevel(logging.DEBUG)
+    logging.getLogger('ccxt.base.exchange').setLevel(logging.DEBUG)
+    logging.getLogger('telegram').setLevel(logging.DEBUG)
+
+    previous_value1 = logging.getLogger('requests').level
+    previous_value2 = logging.getLogger('ccxt.base.exchange').level
+    previous_value3 = logging.getLogger('telegram').level
+
+    _set_loggers()
+
+    value1 = logging.getLogger('requests').level
+    assert previous_value1 is not value1
+    assert value1 is logging.INFO
+
+    value2 = logging.getLogger('ccxt.base.exchange').level
+    assert previous_value2 is not value2
+    assert value2 is logging.INFO
+
+    value3 = logging.getLogger('telegram').level
+    assert previous_value3 is not value3
+    assert value3 is logging.INFO
+
+    _set_loggers(verbosity=2)
+
+    assert logging.getLogger('requests').level is logging.DEBUG
+    assert logging.getLogger('ccxt.base.exchange').level is logging.INFO
+    assert logging.getLogger('telegram').level is logging.INFO
+    assert logging.getLogger('werkzeug').level is logging.INFO
+
+    _set_loggers(verbosity=3, api_verbosity='error')
+
+    assert logging.getLogger('requests').level is logging.DEBUG
+    assert logging.getLogger('ccxt.base.exchange').level is logging.DEBUG
+    assert logging.getLogger('telegram').level is logging.INFO
+    assert logging.getLogger('werkzeug').level is logging.ERROR
+
+
+@pytest.mark.skipif(sys.platform == "win32", reason="does not run on windows")
+def test_set_loggers_syslog(mocker):
+    logger = logging.getLogger()
+    orig_handlers = logger.handlers
+    logger.handlers = []
+
+    config = {'verbosity': 2,
+              'logfile': 'syslog:/dev/log',
+              }
+
+    setup_logging_pre()
+    setup_logging(config)
+    assert len(logger.handlers) == 3
+    assert [x for x in logger.handlers if type(x) == logging.handlers.SysLogHandler]
+    assert [x for x in logger.handlers if type(x) == logging.StreamHandler]
+    assert [x for x in logger.handlers if type(x) == logging.handlers.BufferingHandler]
+    # reset handlers to not break pytest
+    logger.handlers = orig_handlers
+
+
+@pytest.mark.skip(reason="systemd is not installed on every system, so we're not testing this.")
+def test_set_loggers_journald(mocker):
+    logger = logging.getLogger()
+    orig_handlers = logger.handlers
+    logger.handlers = []
+
+    config = {'verbosity': 2,
+              'logfile': 'journald',
+              }
+
+    setup_logging(config)
+    assert len(logger.handlers) == 2
+    assert [x for x in logger.handlers if type(x).__name__ == "JournaldLogHandler"]
+    assert [x for x in logger.handlers if type(x) == logging.StreamHandler]
+    # reset handlers to not break pytest
+    logger.handlers = orig_handlers
+
+
+def test_set_loggers_journald_importerror(mocker, import_fails):
+    logger = logging.getLogger()
+    orig_handlers = logger.handlers
+    logger.handlers = []
+
+    config = {'verbosity': 2,
+              'logfile': 'journald',
+              }
+    with pytest.raises(OperationalException,
+                       match=r'You need the systemd python package.*'):
+        setup_logging(config)
+    logger.handlers = orig_handlers
+
+
+def test_set_logfile(default_conf, mocker):
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    arglist = [
+        'trade', '--logfile', 'test_file.log',
+    ]
+    args = Arguments(arglist).get_parsed_arg()
+    configuration = Configuration(args)
+    validated_conf = configuration.load_config()
+
+    assert validated_conf['logfile'] == "test_file.log"
+    f = Path("test_file.log")
+    assert f.is_file()
+    try:
+        f.unlink()
+    except Exception:
+        pass
+
+
+def test_load_config_warn_forcebuy(default_conf, mocker, caplog) -> None:
+    default_conf['forcebuy_enable'] = True
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = Arguments(['trade']).get_parsed_arg()
+    configuration = Configuration(args)
+    validated_conf = configuration.load_config()
+
+    assert validated_conf.get('forcebuy_enable')
+    assert log_has('`forcebuy` RPC message enabled.', caplog)
+
+
+def test_validate_default_conf(default_conf) -> None:
+    # Validate via our validator - we allow setting defaults!
+    validate_config_schema(default_conf)
+
+
+def test_validate_max_open_trades(default_conf):
+    default_conf['max_open_trades'] = float('inf')
+    default_conf['stake_amount'] = 'unlimited'
+    with pytest.raises(OperationalException, match='`max_open_trades` and `stake_amount` '
+                                                   'cannot both be unlimited.'):
+        validate_config_consistency(default_conf)
+
+
+def test_validate_tsl(default_conf):
+    default_conf['stoploss'] = 0.0
+    with pytest.raises(OperationalException, match='The config stoploss needs to be different '
+                                                   'from 0 to avoid problems with sell orders.'):
+        validate_config_consistency(default_conf)
+    default_conf['stoploss'] = -0.10
+
+    default_conf['trailing_stop'] = True
+    default_conf['trailing_stop_positive'] = 0
+    default_conf['trailing_stop_positive_offset'] = 0
+
+    default_conf['trailing_only_offset_is_reached'] = True
+    with pytest.raises(OperationalException,
+                       match=r'The config trailing_only_offset_is_reached needs '
+                       'trailing_stop_positive_offset to be more than 0 in your config.'):
+        validate_config_consistency(default_conf)
+
+    default_conf['trailing_stop_positive_offset'] = 0.01
+    default_conf['trailing_stop_positive'] = 0.015
+    with pytest.raises(OperationalException,
+                       match=r'The config trailing_stop_positive_offset needs '
+                       'to be greater than trailing_stop_positive in your config.'):
+        validate_config_consistency(default_conf)
+
+    default_conf['trailing_stop_positive'] = 0.01
+    default_conf['trailing_stop_positive_offset'] = 0.015
+    validate_config_consistency(default_conf)
+
+    # 0 trailing stop positive - results in "Order would trigger immediately"
+    default_conf['trailing_stop_positive'] = 0
+    default_conf['trailing_stop_positive_offset'] = 0.02
+    default_conf['trailing_only_offset_is_reached'] = False
+    with pytest.raises(OperationalException,
+                       match='The config trailing_stop_positive needs to be different from 0 '
+                       'to avoid problems with sell orders'):
+        validate_config_consistency(default_conf)
+
+
+def test_validate_edge(edge_conf):
+    edge_conf.update({"pairlist": {
+        "method": "VolumePairList",
+    }})
+
+    with pytest.raises(OperationalException,
+                       match="Edge and VolumePairList are incompatible, "
+                       "Edge will override whatever pairs VolumePairlist selects."):
+        validate_config_consistency(edge_conf)
+
+    edge_conf.update({"pairlist": {
+        "method": "StaticPairList",
+    }})
+    validate_config_consistency(edge_conf)
+
+
+def test_validate_whitelist(default_conf):
+    default_conf['runmode'] = RunMode.DRY_RUN
+    # Test regular case - has whitelist and uses StaticPairlist
+    validate_config_consistency(default_conf)
+    conf = deepcopy(default_conf)
+    del conf['exchange']['pair_whitelist']
+    # Test error case
+    with pytest.raises(OperationalException,
+                       match="StaticPairList requires pair_whitelist to be set."):
+
+        validate_config_consistency(conf)
+
+    conf = deepcopy(default_conf)
+
+    conf.update({"pairlists": [{
+        "method": "VolumePairList",
+    }]})
+    # Dynamic whitelist should not care about pair_whitelist
+    validate_config_consistency(conf)
+    del conf['exchange']['pair_whitelist']
+
+    validate_config_consistency(conf)
+
+
+def test_load_config_test_comments() -> None:
+    """
+    Load config with comments
+    """
+    config_file = Path(__file__).parents[0] / "config_test_comments.json"
+    conf = load_config_file(str(config_file))
+
+    assert conf
+
+
+def test_load_config_default_exchange(all_conf) -> None:
+    """
+    config['exchange'] subtree has required options in it
+    so it cannot be omitted in the config
+    """
+    del all_conf['exchange']
+
+    assert 'exchange' not in all_conf
+
+    with pytest.raises(ValidationError,
+                       match=r"'exchange' is a required property"):
+        validate_config_schema(all_conf)
+
+
+def test_load_config_default_exchange_name(all_conf) -> None:
+    """
+    config['exchange']['name'] option is required
+    so it cannot be omitted in the config
+    """
+    del all_conf['exchange']['name']
+
+    assert 'name' not in all_conf['exchange']
+
+    with pytest.raises(ValidationError,
+                       match=r"'name' is a required property"):
+        validate_config_schema(all_conf)
+
+
+def test_load_config_stoploss_exchange_limit_ratio(all_conf) -> None:
+    all_conf['order_types']['stoploss_on_exchange_limit_ratio'] = 1.15
+
+    with pytest.raises(ValidationError,
+                       match=r"1.15 is greater than the maximum"):
+        validate_config_schema(all_conf)
+
+
+@pytest.mark.parametrize("keys", [("exchange", "sandbox", False),
+                                  ("exchange", "key", ""),
+                                  ("exchange", "secret", ""),
+                                  ("exchange", "password", ""),
+                                  ])
+def test_load_config_default_subkeys(all_conf, keys) -> None:
+    """
+    Test for parameters with default values in sub-paths
+    so they can be omitted in the config and the default value
+    should is added to the config.
+    """
+    # Get first level key
+    key = keys[0]
+    # get second level key
+    subkey = keys[1]
+
+    del all_conf[key][subkey]
+
+    assert subkey not in all_conf[key]
+
+    validate_config_schema(all_conf)
+    assert subkey in all_conf[key]
+    assert all_conf[key][subkey] == keys[2]
+
+
+def test_pairlist_resolving():
+    arglist = [
+        'download-data',
+        '--pairs', 'ETH/BTC', 'XRP/BTC',
+        '--exchange', 'binance'
+    ]
+
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args, RunMode.OTHER)
+    config = configuration.get_config()
+
+    assert config['pairs'] == ['ETH/BTC', 'XRP/BTC']
+    assert config['exchange']['name'] == 'binance'
+
+
+def test_pairlist_resolving_with_config(mocker, default_conf):
+    patched_configuration_load_config_file(mocker, default_conf)
+    arglist = [
+        'download-data',
+        '--config', 'config.json',
+    ]
+
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args)
+    config = configuration.get_config()
+
+    assert config['pairs'] == default_conf['exchange']['pair_whitelist']
+    assert config['exchange']['name'] == default_conf['exchange']['name']
+
+    # Override pairs
+    arglist = [
+        'download-data',
+        '--config', 'config.json',
+        '--pairs', 'ETH/BTC', 'XRP/BTC',
+    ]
+
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args)
+    config = configuration.get_config()
+
+    assert config['pairs'] == ['ETH/BTC', 'XRP/BTC']
+    assert config['exchange']['name'] == default_conf['exchange']['name']
+
+
+def test_pairlist_resolving_with_config_pl(mocker, default_conf):
+    patched_configuration_load_config_file(mocker, default_conf)
+    load_mock = mocker.patch("freqtrade.configuration.configuration.json_load",
+                             MagicMock(return_value=['XRP/BTC', 'ETH/BTC']))
+    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+    mocker.patch.object(Path, "open", MagicMock(return_value=MagicMock()))
+
+    arglist = [
+        'download-data',
+        '--config', 'config.json',
+        '--pairs-file', 'pairs.json',
+    ]
+
+    args = Arguments(arglist).get_parsed_arg()
+
+    configuration = Configuration(args)
+    config = configuration.get_config()
+
+    assert load_mock.call_count == 1
+    assert config['pairs'] == ['ETH/BTC', 'XRP/BTC']
+    assert config['exchange']['name'] == default_conf['exchange']['name']
+
+
+def test_pairlist_resolving_with_config_pl_not_exists(mocker, default_conf):
+    patched_configuration_load_config_file(mocker, default_conf)
+    mocker.patch("freqtrade.configuration.configuration.json_load",
+                 MagicMock(return_value=['XRP/BTC', 'ETH/BTC']))
+    mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+
+    arglist = [
+        'download-data',
+        '--config', 'config.json',
+        '--pairs-file', 'pairs.json',
+    ]
+
+    args = Arguments(arglist).get_parsed_arg()
+
+    with pytest.raises(OperationalException, match=r"No pairs file found with path.*"):
+        configuration = Configuration(args)
+        configuration.get_config()
+
+
+def test_pairlist_resolving_fallback(mocker):
+    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+    mocker.patch.object(Path, "open", MagicMock(return_value=MagicMock()))
+    mocker.patch("freqtrade.configuration.configuration.json_load",
+                 MagicMock(return_value=['XRP/BTC', 'ETH/BTC']))
+    arglist = [
+        'download-data',
+        '--exchange', 'binance'
+    ]
+
+    args = Arguments(arglist).get_parsed_arg()
+    # Fix flaky tests if config.json exists
+    args['config'] = None
+
+    configuration = Configuration(args, RunMode.OTHER)
+    config = configuration.get_config()
+
+    assert config['pairs'] == ['ETH/BTC', 'XRP/BTC']
+    assert config['exchange']['name'] == 'binance'
+    assert config['datadir'] == Path.cwd() / "user_data/data/binance"
+
+
+@pytest.mark.parametrize("setting", [
+        ("ask_strategy", "use_sell_signal", True,
+         "experimental", "use_sell_signal", False),
+        ("ask_strategy", "sell_profit_only", False,
+         "experimental", "sell_profit_only", True),
+        ("ask_strategy", "ignore_roi_if_buy_signal", False,
+         "experimental", "ignore_roi_if_buy_signal", True),
+    ])
+def test_process_temporary_deprecated_settings(mocker, default_conf, setting, caplog):
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    # Create sections for new and deprecated settings
+    # (they may not exist in the config)
+    default_conf[setting[0]] = {}
+    default_conf[setting[3]] = {}
+    # Assign new setting
+    default_conf[setting[0]][setting[1]] = setting[2]
+    # Assign deprecated setting
+    default_conf[setting[3]][setting[4]] = setting[5]
+
+    # New and deprecated settings are conflicting ones
+    with pytest.raises(OperationalException, match=r'DEPRECATED'):
+        process_temporary_deprecated_settings(default_conf)
+
+    caplog.clear()
+
+    # Delete new setting
+    del default_conf[setting[0]][setting[1]]
+
+    process_temporary_deprecated_settings(default_conf)
+    assert log_has_re('DEPRECATED', caplog)
+    # The value of the new setting shall have been set to the
+    # value of the deprecated one
+    assert default_conf[setting[0]][setting[1]] == setting[5]
+
+
+def test_process_deprecated_setting_edge(mocker, edge_conf, caplog):
+    patched_configuration_load_config_file(mocker, edge_conf)
+    edge_conf.update({'edge': {
+        'enabled': True,
+        'capital_available_percentage': 0.5,
+    }})
+
+    with pytest.raises(OperationalException,
+                       match=r"DEPRECATED.*Using 'edge.capital_available_percentage'*"):
+        process_temporary_deprecated_settings(edge_conf)
+
+
+def test_check_conflicting_settings(mocker, default_conf, caplog):
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    # Create sections for new and deprecated settings
+    # (they may not exist in the config)
+    default_conf['sectionA'] = {}
+    default_conf['sectionB'] = {}
+    # Assign new setting
+    default_conf['sectionA']['new_setting'] = 'valA'
+    # Assign deprecated setting
+    default_conf['sectionB']['deprecated_setting'] = 'valB'
+
+    # New and deprecated settings are conflicting ones
+    with pytest.raises(OperationalException, match=r'DEPRECATED'):
+        check_conflicting_settings(default_conf,
+                                   'sectionA', 'new_setting',
+                                   'sectionB', 'deprecated_setting')
+
+    caplog.clear()
+
+    # Delete new setting (deprecated exists)
+    del default_conf['sectionA']['new_setting']
+    check_conflicting_settings(default_conf,
+                               'sectionA', 'new_setting',
+                               'sectionB', 'deprecated_setting')
+    assert not log_has_re('DEPRECATED', caplog)
+    assert 'new_setting' not in default_conf['sectionA']
+
+    caplog.clear()
+
+    # Assign new setting
+    default_conf['sectionA']['new_setting'] = 'valA'
+    # Delete deprecated setting
+    del default_conf['sectionB']['deprecated_setting']
+    check_conflicting_settings(default_conf,
+                               'sectionA', 'new_setting',
+                               'sectionB', 'deprecated_setting')
+    assert not log_has_re('DEPRECATED', caplog)
+    assert default_conf['sectionA']['new_setting'] == 'valA'
+
+
+def test_process_deprecated_setting(mocker, default_conf, caplog):
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    # Create sections for new and deprecated settings
+    # (they may not exist in the config)
+    default_conf['sectionA'] = {}
+    default_conf['sectionB'] = {}
+    # Assign new setting
+    default_conf['sectionA']['new_setting'] = 'valA'
+    # Assign deprecated setting
+    default_conf['sectionB']['deprecated_setting'] = 'valB'
+
+    # Both new and deprecated settings exists
+    process_deprecated_setting(default_conf,
+                               'sectionA', 'new_setting',
+                               'sectionB', 'deprecated_setting')
+    assert log_has_re('DEPRECATED', caplog)
+    # The value of the new setting shall have been set to the
+    # value of the deprecated one
+    assert default_conf['sectionA']['new_setting'] == 'valB'
+
+    caplog.clear()
+
+    # Delete new setting (deprecated exists)
+    del default_conf['sectionA']['new_setting']
+    process_deprecated_setting(default_conf,
+                               'sectionA', 'new_setting',
+                               'sectionB', 'deprecated_setting')
+    assert log_has_re('DEPRECATED', caplog)
+    # The value of the new setting shall have been set to the
+    # value of the deprecated one
+    assert default_conf['sectionA']['new_setting'] == 'valB'
+
+    caplog.clear()
+
+    # Assign new setting
+    default_conf['sectionA']['new_setting'] = 'valA'
+    # Delete deprecated setting
+    del default_conf['sectionB']['deprecated_setting']
+    process_deprecated_setting(default_conf,
+                               'sectionA', 'new_setting',
+                               'sectionB', 'deprecated_setting')
+    assert not log_has_re('DEPRECATED', caplog)
+    assert default_conf['sectionA']['new_setting'] == 'valA'
+
+
+def test_process_deprecated_ticker_interval(mocker, default_conf, caplog):
+    message = "DEPRECATED: Please use 'timeframe' instead of 'ticker_interval."
+    config = deepcopy(default_conf)
+    process_temporary_deprecated_settings(config)
+    assert not log_has(message, caplog)
+
+    del config['timeframe']
+    config['ticker_interval'] = '15m'
+    process_temporary_deprecated_settings(config)
+    assert log_has(message, caplog)
+    assert config['ticker_interval'] == '15m'
+
+    config = deepcopy(default_conf)
+    # Have both timeframe and ticker interval in config
+    # Can also happen when using ticker_interval in configuration, and --timeframe as cli argument
+    config['timeframe'] = '5m'
+    config['ticker_interval'] = '4h'
+    with pytest.raises(OperationalException,
+                       match=r"Both 'timeframe' and 'ticker_interval' detected."):
+        process_temporary_deprecated_settings(config)
diff --git a/tests/test_directory_operations.py b/tests/test_directory_operations.py
new file mode 100644
index 000000000..a8058c514
--- /dev/null
+++ b/tests/test_directory_operations.py
@@ -0,0 +1,90 @@
+# pragma pylint: disable=missing-docstring, protected-access, invalid-name
+from pathlib import Path
+from unittest.mock import MagicMock
+
+import pytest
+
+from freqtrade.configuration.directory_operations import (copy_sample_files, create_datadir,
+                                                          create_userdata_dir)
+from freqtrade.exceptions import OperationalException
+from tests.conftest import log_has, log_has_re
+
+
+def test_create_datadir(mocker, default_conf, caplog) -> None:
+    mocker.patch.object(Path, "is_dir", MagicMock(return_value=False))
+    md = mocker.patch.object(Path, 'mkdir', MagicMock())
+
+    create_datadir(default_conf, '/foo/bar')
+    assert md.call_args[1]['parents'] is True
+    assert log_has('Created data directory: /foo/bar', caplog)
+
+
+def test_create_userdata_dir(mocker, default_conf, caplog) -> None:
+    mocker.patch.object(Path, "is_dir", MagicMock(return_value=False))
+    md = mocker.patch.object(Path, 'mkdir', MagicMock())
+
+    x = create_userdata_dir('/tmp/bar', create_dir=True)
+    assert md.call_count == 9
+    assert md.call_args[1]['parents'] is False
+    assert log_has(f'Created user-data directory: {Path("/tmp/bar")}', caplog)
+    assert isinstance(x, Path)
+    assert str(x) == str(Path("/tmp/bar"))
+
+
+def test_create_userdata_dir_exists(mocker, default_conf, caplog) -> None:
+    mocker.patch.object(Path, "is_dir", MagicMock(return_value=True))
+    md = mocker.patch.object(Path, 'mkdir', MagicMock())
+
+    create_userdata_dir('/tmp/bar')
+    assert md.call_count == 0
+
+
+def test_create_userdata_dir_exists_exception(mocker, default_conf, caplog) -> None:
+    mocker.patch.object(Path, "is_dir", MagicMock(return_value=False))
+    md = mocker.patch.object(Path, 'mkdir', MagicMock())
+
+    with pytest.raises(OperationalException,
+                       match=r'Directory `.{1,2}tmp.{1,2}bar` does not exist.*'):
+        create_userdata_dir('/tmp/bar',  create_dir=False)
+    assert md.call_count == 0
+
+
+def test_copy_sample_files(mocker, default_conf, caplog) -> None:
+    mocker.patch.object(Path, "is_dir", MagicMock(return_value=True))
+    mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+    copymock = mocker.patch('shutil.copy', MagicMock())
+
+    copy_sample_files(Path('/tmp/bar'))
+    assert copymock.call_count == 5
+    assert copymock.call_args_list[0][0][1] == str(
+        Path('/tmp/bar') / 'strategies/sample_strategy.py')
+    assert copymock.call_args_list[1][0][1] == str(
+        Path('/tmp/bar') / 'hyperopts/sample_hyperopt_advanced.py')
+    assert copymock.call_args_list[2][0][1] == str(
+        Path('/tmp/bar') / 'hyperopts/sample_hyperopt_loss.py')
+    assert copymock.call_args_list[3][0][1] == str(
+        Path('/tmp/bar') / 'hyperopts/sample_hyperopt.py')
+    assert copymock.call_args_list[4][0][1] == str(
+        Path('/tmp/bar') / 'notebooks/strategy_analysis_example.ipynb')
+
+
+def test_copy_sample_files_errors(mocker, default_conf, caplog) -> None:
+    mocker.patch.object(Path, "is_dir", MagicMock(return_value=False))
+    mocker.patch.object(Path, "exists", MagicMock(return_value=False))
+    mocker.patch('shutil.copy', MagicMock())
+    with pytest.raises(OperationalException,
+                       match=r"Directory `.{1,2}tmp.{1,2}bar` does not exist\."):
+        copy_sample_files(Path('/tmp/bar'))
+
+    mocker.patch.object(Path, "is_dir", MagicMock(side_effect=[True, False]))
+
+    with pytest.raises(OperationalException,
+                       match=r"Directory `.{1,2}tmp.{1,2}bar.{1,2}strategies` does not exist\."):
+        copy_sample_files(Path('/tmp/bar'))
+    mocker.patch.object(Path, "is_dir", MagicMock(return_value=True))
+    mocker.patch.object(Path, "exists", MagicMock(return_value=True))
+    copy_sample_files(Path('/tmp/bar'))
+    assert log_has_re(r"File `.*` exists already, not deploying sample file\.", caplog)
+    caplog.clear()
+    copy_sample_files(Path('/tmp/bar'), overwrite=True)
+    assert log_has_re(r"File `.*` exists already, overwriting\.", caplog)
diff --git a/tests/test_docs.sh b/tests/test_docs.sh
new file mode 100755
index 000000000..09e142b99
--- /dev/null
+++ b/tests/test_docs.sh
@@ -0,0 +1,12 @@
+#!/bin/bash
+# Test Documentation boxes -
+# !!! <TYPE>: is not allowed!
+# !!! <TYPE> "title" - Title needs to be quoted!
+grep -Er '^!{3}\s\S+:|^!{3}\s\S+\s[^"]' docs/*
+
+if  [ $? -ne 0 ]; then
+    echo "Docs test success."
+    exit 0
+fi
+echo "Docs test failed."
+exit 1
diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py
new file mode 100644
index 000000000..1f5b3ecaa
--- /dev/null
+++ b/tests/test_freqtradebot.py
@@ -0,0 +1,4476 @@
+# pragma pylint: disable=missing-docstring, C0103
+# pragma pylint: disable=protected-access, too-many-lines, invalid-name, too-many-arguments
+
+import logging
+import time
+from copy import deepcopy
+from math import isclose
+from unittest.mock import ANY, MagicMock, PropertyMock
+
+import arrow
+import pytest
+
+from freqtrade.constants import CANCEL_REASON, MATH_CLOSE_PREC, UNLIMITED_STAKE_AMOUNT
+from freqtrade.exceptions import (DependencyException, ExchangeError, InsufficientFundsError,
+                                  InvalidOrderException, OperationalException, PricingError,
+                                  TemporaryError)
+from freqtrade.freqtradebot import FreqtradeBot
+from freqtrade.persistence import Order, Trade
+from freqtrade.persistence.models import PairLock
+from freqtrade.rpc import RPCMessageType
+from freqtrade.state import RunMode, State
+from freqtrade.strategy.interface import SellCheckTuple, SellType
+from freqtrade.worker import Worker
+from tests.conftest import (create_mock_trades, get_patched_freqtradebot, get_patched_worker,
+                            log_has, log_has_re, patch_edge, patch_exchange, patch_get_signal,
+                            patch_wallet, patch_whitelist)
+from tests.conftest_trades import (MOCK_TRADE_COUNT, mock_order_1, mock_order_2, mock_order_2_sell,
+                                   mock_order_3, mock_order_3_sell, mock_order_4,
+                                   mock_order_5_stoploss, mock_order_6_sell)
+
+
+def patch_RPCManager(mocker) -> MagicMock:
+    """
+    This function mock RPC manager to avoid repeating this code in almost every tests
+    :param mocker: mocker to patch RPCManager class
+    :return: RPCManager.send_msg MagicMock to track if this method is called
+    """
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
+    rpc_mock = mocker.patch('freqtrade.freqtradebot.RPCManager.send_msg', MagicMock())
+    return rpc_mock
+
+
+# Unit tests
+
+def test_freqtradebot_state(mocker, default_conf, markets) -> None:
+    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    assert freqtrade.state is State.RUNNING
+
+    default_conf.pop('initial_state')
+    freqtrade = FreqtradeBot(default_conf)
+    assert freqtrade.state is State.STOPPED
+
+
+def test_process_stopped(mocker, default_conf) -> None:
+
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    coo_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.cancel_all_open_orders')
+    freqtrade.process_stopped()
+    assert coo_mock.call_count == 0
+
+    default_conf['cancel_open_orders_on_exit'] = True
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade.process_stopped()
+    assert coo_mock.call_count == 1
+
+
+def test_bot_cleanup(mocker, default_conf, caplog) -> None:
+    mock_cleanup = mocker.patch('freqtrade.freqtradebot.cleanup_db')
+    coo_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.cancel_all_open_orders')
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade.cleanup()
+    assert log_has('Cleaning up modules ...', caplog)
+    assert mock_cleanup.call_count == 1
+    assert coo_mock.call_count == 0
+
+    freqtrade.config['cancel_open_orders_on_exit'] = True
+    freqtrade.cleanup()
+    assert coo_mock.call_count == 1
+
+
+def test_order_dict_dry_run(default_conf, mocker, caplog) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balance=MagicMock(return_value=default_conf['stake_amount'] * 2)
+    )
+    conf = default_conf.copy()
+    conf['runmode'] = RunMode.DRY_RUN
+    conf['order_types'] = {
+        'buy': 'market',
+        'sell': 'limit',
+        'stoploss': 'limit',
+        'stoploss_on_exchange': True,
+    }
+
+    freqtrade = FreqtradeBot(conf)
+    assert freqtrade.strategy.order_types['stoploss_on_exchange']
+
+    caplog.clear()
+    # is left untouched
+    conf = default_conf.copy()
+    conf['runmode'] = RunMode.DRY_RUN
+    conf['order_types'] = {
+        'buy': 'market',
+        'sell': 'limit',
+        'stoploss': 'limit',
+        'stoploss_on_exchange': False,
+    }
+    freqtrade = FreqtradeBot(conf)
+    assert not freqtrade.strategy.order_types['stoploss_on_exchange']
+    assert not log_has_re(".*stoploss_on_exchange .* dry-run", caplog)
+
+
+def test_order_dict_live(default_conf, mocker, caplog) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balance=MagicMock(return_value=default_conf['stake_amount'] * 2)
+    )
+    conf = default_conf.copy()
+    conf['runmode'] = RunMode.LIVE
+    conf['order_types'] = {
+        'buy': 'market',
+        'sell': 'limit',
+        'stoploss': 'limit',
+        'stoploss_on_exchange': True,
+    }
+
+    freqtrade = FreqtradeBot(conf)
+    assert not log_has_re(".*stoploss_on_exchange .* dry-run", caplog)
+    assert freqtrade.strategy.order_types['stoploss_on_exchange']
+
+    caplog.clear()
+    # is left untouched
+    conf = default_conf.copy()
+    conf['runmode'] = RunMode.LIVE
+    conf['order_types'] = {
+        'buy': 'market',
+        'sell': 'limit',
+        'stoploss': 'limit',
+        'stoploss_on_exchange': False,
+    }
+    freqtrade = FreqtradeBot(conf)
+    assert not freqtrade.strategy.order_types['stoploss_on_exchange']
+    assert not log_has_re(".*stoploss_on_exchange .* dry-run", caplog)
+
+
+def test_get_trade_stake_amount(default_conf, ticker, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balance=MagicMock(return_value=default_conf['stake_amount'] * 2)
+    )
+
+    freqtrade = FreqtradeBot(default_conf)
+
+    result = freqtrade.get_trade_stake_amount('ETH/BTC')
+    assert result == default_conf['stake_amount']
+
+
+@pytest.mark.parametrize("amend_last,wallet,max_open,lsamr,expected", [
+                        (False, 0.002, 2, 0.5, [0.001, None]),
+                        (True, 0.002, 2, 0.5, [0.001, 0.00098]),
+                        (False, 0.003, 3, 0.5, [0.001, 0.001, None]),
+                        (True, 0.003, 3, 0.5, [0.001, 0.001, 0.00097]),
+                        (False, 0.0022, 3, 0.5, [0.001, 0.001, None]),
+                        (True, 0.0022, 3, 0.5, [0.001, 0.001, 0.0]),
+                        (True, 0.0027, 3, 0.5, [0.001, 0.001, 0.000673]),
+                        (True, 0.0022, 3, 1, [0.001, 0.001, 0.0]),
+                        ])
+def test_check_available_stake_amount(default_conf, ticker, mocker, fee, limit_buy_order_open,
+                                      amend_last, wallet, max_open, lsamr, expected) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_balance=MagicMock(return_value=default_conf['stake_amount'] * 2),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee
+    )
+    default_conf['dry_run_wallet'] = wallet
+
+    default_conf['amend_last_stake_amount'] = amend_last
+    default_conf['last_stake_amount_min_ratio'] = lsamr
+
+    freqtrade = FreqtradeBot(default_conf)
+
+    for i in range(0, max_open):
+
+        if expected[i] is not None:
+            limit_buy_order_open['id'] = str(i)
+            result = freqtrade.get_trade_stake_amount('ETH/BTC')
+            assert pytest.approx(result) == expected[i]
+            freqtrade.execute_buy('ETH/BTC', result)
+        else:
+            with pytest.raises(DependencyException):
+                freqtrade.get_trade_stake_amount('ETH/BTC')
+
+
+def test_get_trade_stake_amount_no_stake_amount(default_conf, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    patch_wallet(mocker, free=default_conf['stake_amount'] * 0.5)
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    with pytest.raises(DependencyException, match=r'.*stake amount.*'):
+        freqtrade.get_trade_stake_amount('ETH/BTC')
+
+
+@pytest.mark.parametrize("balance_ratio,result1", [
+                        (1, 0.005),
+                        (0.99, 0.00495),
+                        (0.50, 0.0025),
+                        ])
+def test_get_trade_stake_amount_unlimited_amount(default_conf, ticker, balance_ratio, result1,
+                                                 limit_buy_order_open, fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee
+    )
+
+    conf = deepcopy(default_conf)
+    conf['stake_amount'] = UNLIMITED_STAKE_AMOUNT
+    conf['dry_run_wallet'] = 0.01
+    conf['max_open_trades'] = 2
+    conf['tradable_balance_ratio'] = balance_ratio
+
+    freqtrade = FreqtradeBot(conf)
+    patch_get_signal(freqtrade)
+
+    # no open trades, order amount should be 'balance / max_open_trades'
+    result = freqtrade.get_trade_stake_amount('ETH/BTC')
+    assert result == result1
+
+    # create one trade, order amount should be 'balance / (max_open_trades - num_open_trades)'
+    freqtrade.execute_buy('ETH/BTC', result)
+
+    result = freqtrade.get_trade_stake_amount('LTC/BTC')
+    assert result == result1
+
+    # create 2 trades, order amount should be None
+    freqtrade.execute_buy('LTC/BTC', result)
+
+    result = freqtrade.get_trade_stake_amount('XRP/BTC')
+    assert result == 0
+
+    # set max_open_trades = None, so do not trade
+    conf['max_open_trades'] = 0
+    freqtrade = FreqtradeBot(conf)
+    result = freqtrade.get_trade_stake_amount('NEO/BTC')
+    assert result == 0
+
+
+def test_edge_called_in_process(mocker, edge_conf) -> None:
+    patch_RPCManager(mocker)
+    patch_edge(mocker)
+
+    def _refresh_whitelist(list):
+        return ['ETH/BTC', 'LTC/BTC', 'XRP/BTC', 'NEO/BTC']
+
+    patch_exchange(mocker)
+    freqtrade = FreqtradeBot(edge_conf)
+    freqtrade.pairlists._validate_whitelist = _refresh_whitelist
+    patch_get_signal(freqtrade)
+    freqtrade.process()
+    assert freqtrade.active_pair_whitelist == ['NEO/BTC', 'LTC/BTC']
+
+
+def test_edge_overrides_stake_amount(mocker, edge_conf) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    patch_edge(mocker)
+    edge_conf['dry_run_wallet'] = 999.9
+    freqtrade = FreqtradeBot(edge_conf)
+
+    assert freqtrade.get_trade_stake_amount('NEO/BTC') == (999.9 * 0.5 * 0.01) / 0.20
+    assert freqtrade.get_trade_stake_amount('LTC/BTC') == (999.9 * 0.5 * 0.01) / 0.21
+
+
+def test_edge_overrides_stoploss(limit_buy_order, fee, caplog, mocker, edge_conf) -> None:
+
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    patch_edge(mocker)
+    edge_conf['max_open_trades'] = float('inf')
+
+    # Strategy stoploss is -0.1 but Edge imposes a stoploss at -0.2
+    # Thus, if price falls 21%, stoploss should be triggered
+    #
+    # mocking the ticker: price is falling ...
+    buy_price = limit_buy_order['price']
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': buy_price * 0.79,
+            'ask': buy_price * 0.79,
+            'last': buy_price * 0.79
+        }),
+        get_fee=fee,
+    )
+    #############################################
+
+    # Create a trade with "limit_buy_order" price
+    freqtrade = FreqtradeBot(edge_conf)
+    freqtrade.active_pair_whitelist = ['NEO/BTC']
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
+    freqtrade.enter_positions()
+    trade = Trade.query.first()
+    trade.update(limit_buy_order)
+    #############################################
+
+    # stoploss shoud be hit
+    assert freqtrade.handle_trade(trade) is True
+    assert log_has('Executing Sell for NEO/BTC. Reason: stop_loss', caplog)
+    assert trade.sell_reason == SellType.STOP_LOSS.value
+
+
+def test_edge_should_ignore_strategy_stoploss(limit_buy_order, fee,
+                                              mocker, edge_conf) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    patch_edge(mocker)
+    edge_conf['max_open_trades'] = float('inf')
+
+    # Strategy stoploss is -0.1 but Edge imposes a stoploss at -0.2
+    # Thus, if price falls 15%, stoploss should not be triggered
+    #
+    # mocking the ticker: price is falling ...
+    buy_price = limit_buy_order['price']
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': buy_price * 0.85,
+            'ask': buy_price * 0.85,
+            'last': buy_price * 0.85
+        }),
+        get_fee=fee,
+    )
+    #############################################
+
+    # Create a trade with "limit_buy_order" price
+    freqtrade = FreqtradeBot(edge_conf)
+    freqtrade.active_pair_whitelist = ['NEO/BTC']
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
+    freqtrade.enter_positions()
+    trade = Trade.query.first()
+    trade.update(limit_buy_order)
+    #############################################
+
+    # stoploss shoud not be hit
+    assert freqtrade.handle_trade(trade) is False
+
+
+def test_total_open_trades_stakes(mocker, default_conf, ticker, fee) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    default_conf['stake_amount'] = 0.00098751
+    default_conf['max_open_trades'] = 2
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.enter_positions()
+    trade = Trade.query.first()
+
+    assert trade is not None
+    assert trade.stake_amount == 0.00098751
+    assert trade.is_open
+    assert trade.open_date is not None
+
+    freqtrade.enter_positions()
+    trade = Trade.query.order_by(Trade.id.desc()).first()
+
+    assert trade is not None
+    assert trade.stake_amount == 0.00098751
+    assert trade.is_open
+    assert trade.open_date is not None
+
+    assert Trade.total_open_trades_stakes() == 1.97502e-03
+
+
+def test_get_min_pair_stake_amount(mocker, default_conf) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    freqtrade = FreqtradeBot(default_conf)
+    freqtrade.strategy.stoploss = -0.05
+    markets = {'ETH/BTC': {'symbol': 'ETH/BTC'}}
+
+    # no pair found
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets',
+        PropertyMock(return_value=markets)
+    )
+    with pytest.raises(ValueError, match=r'.*get market information.*'):
+        freqtrade._get_min_pair_stake_amount('BNB/BTC', 1)
+
+    # no 'limits' section
+    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1)
+    assert result is None
+
+    # empty 'limits' section
+    markets["ETH/BTC"]["limits"] = {}
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets',
+        PropertyMock(return_value=markets)
+    )
+    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1)
+    assert result is None
+
+    # no cost Min
+    markets["ETH/BTC"]["limits"] = {
+        'cost': {"min": None},
+        'amount': {}
+    }
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets',
+        PropertyMock(return_value=markets)
+    )
+    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1)
+    assert result is None
+
+    # no amount Min
+    markets["ETH/BTC"]["limits"] = {
+        'cost': {},
+        'amount': {"min": None}
+    }
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets',
+        PropertyMock(return_value=markets)
+    )
+    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1)
+    assert result is None
+
+    # empty 'cost'/'amount' section
+    markets["ETH/BTC"]["limits"] = {
+        'cost': {},
+        'amount': {}
+    }
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets',
+        PropertyMock(return_value=markets)
+    )
+    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1)
+    assert result is None
+
+    # min cost is set
+    markets["ETH/BTC"]["limits"] = {
+        'cost': {'min': 2},
+        'amount': {}
+    }
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets',
+        PropertyMock(return_value=markets)
+    )
+    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 1)
+    assert result == 2 / 0.9
+
+    # min amount is set
+    markets["ETH/BTC"]["limits"] = {
+        'cost': {},
+        'amount': {'min': 2}
+    }
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets',
+        PropertyMock(return_value=markets)
+    )
+    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 2)
+    assert result == 2 * 2 / 0.9
+
+    # min amount and cost are set (cost is minimal)
+    markets["ETH/BTC"]["limits"] = {
+        'cost': {'min': 2},
+        'amount': {'min': 2}
+    }
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets',
+        PropertyMock(return_value=markets)
+    )
+    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 2)
+    assert result == max(2, 2 * 2) / 0.9
+
+    # min amount and cost are set (amount is minial)
+    markets["ETH/BTC"]["limits"] = {
+        'cost': {'min': 8},
+        'amount': {'min': 2}
+    }
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets',
+        PropertyMock(return_value=markets)
+    )
+    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 2)
+    assert result == max(8, 2 * 2) / 0.9
+
+
+def test_get_min_pair_stake_amount_real_data(mocker, default_conf) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    freqtrade = FreqtradeBot(default_conf)
+    freqtrade.strategy.stoploss = -0.05
+    markets = {'ETH/BTC': {'symbol': 'ETH/BTC'}}
+
+    # Real Binance data
+    markets["ETH/BTC"]["limits"] = {
+        'cost': {'min': 0.0001},
+        'amount': {'min': 0.001}
+    }
+    mocker.patch(
+        'freqtrade.exchange.Exchange.markets',
+        PropertyMock(return_value=markets)
+    )
+    result = freqtrade._get_min_pair_stake_amount('ETH/BTC', 0.020405)
+    assert round(result, 8) == round(max(0.0001, 0.001 * 0.020405) / 0.9, 8)
+
+
+def test_create_trade(default_conf, ticker, limit_buy_order, fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+
+    # Save state of current whitelist
+    whitelist = deepcopy(default_conf['exchange']['pair_whitelist'])
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.create_trade('ETH/BTC')
+
+    trade = Trade.query.first()
+    assert trade is not None
+    assert trade.stake_amount == 0.001
+    assert trade.is_open
+    assert trade.open_date is not None
+    assert trade.exchange == 'bittrex'
+
+    # Simulate fulfilled LIMIT_BUY order for trade
+    trade.update(limit_buy_order)
+
+    assert trade.open_rate == 0.00001099
+    assert trade.amount == 90.99181073
+
+    assert whitelist == default_conf['exchange']['pair_whitelist']
+
+
+def test_create_trade_no_stake_amount(default_conf, ticker, limit_buy_order,
+                                      fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    patch_wallet(mocker, free=default_conf['stake_amount'] * 0.5)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    with pytest.raises(DependencyException, match=r'.*stake amount.*'):
+        freqtrade.create_trade('ETH/BTC')
+
+
+def test_create_trade_minimal_amount(default_conf, ticker, limit_buy_order_open,
+                                     fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    buy_mock = MagicMock(return_value=limit_buy_order_open)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=buy_mock,
+        get_fee=fee,
+    )
+    default_conf['stake_amount'] = 0.0005
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    freqtrade.create_trade('ETH/BTC')
+    rate, amount = buy_mock.call_args[1]['rate'], buy_mock.call_args[1]['amount']
+    assert rate * amount <= default_conf['stake_amount']
+
+
+def test_create_trade_too_small_stake_amount(default_conf, ticker, limit_buy_order_open,
+                                             fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    buy_mock = MagicMock(return_value=limit_buy_order_open)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=buy_mock,
+        get_fee=fee,
+    )
+
+    freqtrade = FreqtradeBot(default_conf)
+    freqtrade.config['stake_amount'] = 0.000000005
+
+    patch_get_signal(freqtrade)
+
+    assert not freqtrade.create_trade('ETH/BTC')
+
+
+def test_create_trade_limit_reached(default_conf, ticker, limit_buy_order_open,
+                                    fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_balance=MagicMock(return_value=default_conf['stake_amount']),
+        get_fee=fee,
+    )
+    default_conf['max_open_trades'] = 0
+    default_conf['stake_amount'] = UNLIMITED_STAKE_AMOUNT
+
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    assert not freqtrade.create_trade('ETH/BTC')
+    assert freqtrade.get_trade_stake_amount('ETH/BTC') == 0
+
+
+def test_enter_positions_no_pairs_left(default_conf, ticker, limit_buy_order_open, fee,
+                                       mocker, caplog) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+
+    default_conf['exchange']['pair_whitelist'] = ["ETH/BTC"]
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    n = freqtrade.enter_positions()
+    assert n == 1
+    assert not log_has_re(r"No currency pair in active pair whitelist.*", caplog)
+    n = freqtrade.enter_positions()
+    assert n == 0
+    assert log_has_re(r"No currency pair in active pair whitelist.*", caplog)
+
+
+def test_enter_positions_no_pairs_in_whitelist(default_conf, ticker, limit_buy_order, fee,
+                                               mocker, caplog) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
+        get_fee=fee,
+    )
+    default_conf['exchange']['pair_whitelist'] = []
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    n = freqtrade.enter_positions()
+    assert n == 0
+    assert log_has("Active pair whitelist is empty.", caplog)
+
+
+def test_create_trade_no_signal(default_conf, fee, mocker) -> None:
+    default_conf['dry_run'] = True
+
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        get_balance=MagicMock(return_value=20),
+        get_fee=fee,
+    )
+    default_conf['stake_amount'] = 10
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade, value=(False, False))
+
+    Trade.query = MagicMock()
+    Trade.query.filter = MagicMock()
+    assert not freqtrade.create_trade('ETH/BTC')
+
+
+@pytest.mark.parametrize("max_open", range(0, 5))
+@pytest.mark.parametrize("tradable_balance_ratio,modifier", [(1.0, 1), (0.99, 0.8), (0.5, 0.5)])
+def test_create_trades_multiple_trades(default_conf, ticker, fee, mocker, limit_buy_order_open,
+                                       max_open, tradable_balance_ratio, modifier) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    default_conf['max_open_trades'] = max_open
+    default_conf['tradable_balance_ratio'] = tradable_balance_ratio
+    default_conf['dry_run_wallet'] = 0.001 * max_open
+
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    n = freqtrade.enter_positions()
+    trades = Trade.get_open_trades()
+    # Expected trades should be max_open * a modified value
+    # depending on the configured tradable_balance
+    assert n == max(int(max_open * modifier), 0)
+    assert len(trades) == max(int(max_open * modifier), 0)
+
+
+def test_create_trades_preopen(default_conf, ticker, fee, mocker, limit_buy_order_open) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    default_conf['max_open_trades'] = 4
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    # Create 2 existing trades
+    freqtrade.execute_buy('ETH/BTC', default_conf['stake_amount'])
+    freqtrade.execute_buy('NEO/BTC', default_conf['stake_amount'])
+
+    assert len(Trade.get_open_trades()) == 2
+    # Change order_id for new orders
+    limit_buy_order_open['id'] = '123444'
+
+    # Create 2 new trades using create_trades
+    assert freqtrade.create_trade('ETH/BTC')
+    assert freqtrade.create_trade('NEO/BTC')
+
+    trades = Trade.get_open_trades()
+    assert len(trades) == 4
+
+
+def test_process_trade_creation(default_conf, ticker, limit_buy_order, limit_buy_order_open,
+                                fee, mocker, caplog) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        fetch_order=MagicMock(return_value=limit_buy_order),
+        get_fee=fee,
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    trades = Trade.query.filter(Trade.is_open.is_(True)).all()
+    assert not trades
+
+    freqtrade.process()
+
+    trades = Trade.query.filter(Trade.is_open.is_(True)).all()
+    assert len(trades) == 1
+    trade = trades[0]
+    assert trade is not None
+    assert trade.stake_amount == default_conf['stake_amount']
+    assert trade.is_open
+    assert trade.open_date is not None
+    assert trade.exchange == 'bittrex'
+    assert trade.open_rate == 0.00001098
+    assert trade.amount == 91.07468123
+
+    assert log_has(
+        'Buy signal found: about create a new trade with stake_amount: 0.001 ...', caplog
+    )
+
+
+def test_process_exchange_failures(default_conf, ticker, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(side_effect=TemporaryError)
+    )
+    sleep_mock = mocker.patch('time.sleep', side_effect=lambda _: None)
+
+    worker = Worker(args=None, config=default_conf)
+    patch_get_signal(worker.freqtrade)
+
+    worker._process_running()
+    assert sleep_mock.has_calls()
+
+
+def test_process_operational_exception(default_conf, ticker, mocker) -> None:
+    msg_mock = patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(side_effect=OperationalException)
+    )
+    worker = Worker(args=None, config=default_conf)
+    patch_get_signal(worker.freqtrade)
+
+    assert worker.freqtrade.state == State.RUNNING
+
+    worker._process_running()
+    assert worker.freqtrade.state == State.STOPPED
+    assert 'OperationalException' in msg_mock.call_args_list[-1][0][0]['status']
+
+
+def test_process_trade_handling(default_conf, ticker, limit_buy_order_open, fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        fetch_order=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    trades = Trade.query.filter(Trade.is_open.is_(True)).all()
+    assert not trades
+    freqtrade.process()
+
+    trades = Trade.query.filter(Trade.is_open.is_(True)).all()
+    assert len(trades) == 1
+
+    # Nothing happened ...
+    freqtrade.process()
+    assert len(trades) == 1
+
+
+def test_process_trade_no_whitelist_pair(default_conf, ticker, limit_buy_order,
+                                         fee, mocker) -> None:
+    """ Test process with trade not in pair list """
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
+        fetch_order=MagicMock(return_value=limit_buy_order),
+        get_fee=fee,
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    pair = 'BLK/BTC'
+    # Ensure the pair is not in the whitelist!
+    assert pair not in default_conf['exchange']['pair_whitelist']
+
+    # create open trade not in whitelist
+    Trade.session.add(Trade(
+        pair=pair,
+        stake_amount=0.001,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        is_open=True,
+        amount=20,
+        open_rate=0.01,
+        exchange='bittrex',
+    ))
+    Trade.session.add(Trade(
+        pair='ETH/BTC',
+        stake_amount=0.001,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        is_open=True,
+        amount=12,
+        open_rate=0.001,
+        exchange='bittrex',
+    ))
+
+    assert pair not in freqtrade.active_pair_whitelist
+    freqtrade.process()
+    assert pair in freqtrade.active_pair_whitelist
+    # Make sure each pair is only in the list once
+    assert len(freqtrade.active_pair_whitelist) == len(set(freqtrade.active_pair_whitelist))
+
+
+def test_process_informative_pairs_added(default_conf, ticker, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+
+    def _refresh_whitelist(list):
+        return ['ETH/BTC', 'LTC/BTC', 'XRP/BTC', 'NEO/BTC']
+
+    refresh_mock = MagicMock()
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(side_effect=TemporaryError),
+        refresh_latest_ohlcv=refresh_mock,
+    )
+    inf_pairs = MagicMock(return_value=[("BTC/ETH", '1m'), ("ETH/USDT", "1h")])
+    mocker.patch('freqtrade.strategy.interface.IStrategy.get_signal', return_value=(False, False))
+    mocker.patch('time.sleep', return_value=None)
+
+    freqtrade = FreqtradeBot(default_conf)
+    freqtrade.pairlists._validate_whitelist = _refresh_whitelist
+    freqtrade.strategy.informative_pairs = inf_pairs
+    # patch_get_signal(freqtrade)
+
+    freqtrade.process()
+    assert inf_pairs.call_count == 1
+    assert refresh_mock.call_count == 1
+    assert ("BTC/ETH", "1m") in refresh_mock.call_args[0][0]
+    assert ("ETH/USDT", "1h") in refresh_mock.call_args[0][0]
+    assert ("ETH/BTC", default_conf["timeframe"]) in refresh_mock.call_args[0][0]
+
+
+@pytest.mark.parametrize("side,ask,bid,last,last_ab,expected", [
+    ('ask', 20, 19, 10, 0.0, 20),  # Full ask side
+    ('ask', 20, 19, 10, 1.0, 10),  # Full last side
+    ('ask', 20, 19, 10, 0.5, 15),  # Between ask and last
+    ('ask', 20, 19, 10, 0.7, 13),  # Between ask and last
+    ('ask', 20, 19, 10, 0.3, 17),  # Between ask and last
+    ('ask', 5, 6, 10, 1.0, 5),  # last bigger than ask
+    ('ask', 5, 6, 10, 0.5, 5),  # last bigger than ask
+    ('ask', 10, 20, None, 0.5, 10),  # last not available - uses ask
+    ('ask', 4, 5, None, 0.5, 4),  # last not available - uses ask
+    ('ask', 4, 5, None, 1, 4),  # last not available - uses ask
+    ('ask', 4, 5, None, 0, 4),  # last not available - uses ask
+    ('bid', 10, 20, 10, 0.0, 20),  # Full bid side
+    ('bid', 10, 20, 10, 1.0, 10),  # Full last side
+    ('bid', 10, 20, 10, 0.5, 15),  # Between bid and last
+    ('bid', 10, 20, 10, 0.7, 13),  # Between bid and last
+    ('bid', 10, 20, 10, 0.3, 17),  # Between bid and last
+    ('bid', 4, 5, 10, 1.0, 5),  # last bigger than bid
+    ('bid', 4, 5, 10, 0.5, 5),  # last bigger than bid
+    ('bid', 10, 20, None, 0.5, 20),  # last not available - uses bid
+    ('bid', 4, 5, None, 0.5, 5),  # last not available - uses bid
+    ('bid', 4, 5, None, 1, 5),  # last not available - uses bid
+    ('bid', 4, 5, None, 0, 5),  # last not available - uses bid
+])
+def test_get_buy_rate(mocker, default_conf, caplog, side, ask, bid,
+                      last, last_ab, expected) -> None:
+    caplog.set_level(logging.DEBUG)
+    default_conf['bid_strategy']['ask_last_balance'] = last_ab
+    default_conf['bid_strategy']['price_side'] = side
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
+                 MagicMock(return_value={'ask': ask, 'last': last, 'bid': bid}))
+
+    assert freqtrade.get_buy_rate('ETH/BTC', True) == expected
+    assert not log_has("Using cached buy rate for ETH/BTC.", caplog)
+
+    assert freqtrade.get_buy_rate('ETH/BTC', False) == expected
+    assert log_has("Using cached buy rate for ETH/BTC.", caplog)
+    # Running a 2nd time with Refresh on!
+    caplog.clear()
+    assert freqtrade.get_buy_rate('ETH/BTC', True) == expected
+    assert not log_has("Using cached buy rate for ETH/BTC.", caplog)
+
+
+def test_execute_buy(mocker, default_conf, fee, limit_buy_order, limit_buy_order_open) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    freqtrade = FreqtradeBot(default_conf)
+    freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=False)
+    stake_amount = 2
+    bid = 0.11
+    buy_rate_mock = MagicMock(return_value=bid)
+    mocker.patch.multiple(
+        'freqtrade.freqtradebot.FreqtradeBot',
+        get_buy_rate=buy_rate_mock,
+        _get_min_pair_stake_amount=MagicMock(return_value=1)
+    )
+    buy_mm = MagicMock(return_value=limit_buy_order_open)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00001172,
+            'ask': 0.00001173,
+            'last': 0.00001172
+        }),
+        buy=buy_mm,
+        get_fee=fee,
+    )
+    pair = 'ETH/BTC'
+
+    assert not freqtrade.execute_buy(pair, stake_amount)
+    assert buy_rate_mock.call_count == 1
+    assert buy_mm.call_count == 0
+    assert freqtrade.strategy.confirm_trade_entry.call_count == 1
+    buy_rate_mock.reset_mock()
+
+    limit_buy_order_open['id'] = '22'
+    freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=True)
+    assert freqtrade.execute_buy(pair, stake_amount)
+    assert buy_rate_mock.call_count == 1
+    assert buy_mm.call_count == 1
+    call_args = buy_mm.call_args_list[0][1]
+    assert call_args['pair'] == pair
+    assert call_args['rate'] == bid
+    assert call_args['amount'] == round(stake_amount / bid, 8)
+    buy_rate_mock.reset_mock()
+
+    # Should create an open trade with an open order id
+    # As the order is not fulfilled yet
+    trade = Trade.query.first()
+    assert trade
+    assert trade.is_open is True
+    assert trade.open_order_id == '22'
+
+    # Test calling with price
+    limit_buy_order_open['id'] = '33'
+    fix_price = 0.06
+    assert freqtrade.execute_buy(pair, stake_amount, fix_price)
+    # Make sure get_buy_rate wasn't called again
+    assert buy_rate_mock.call_count == 0
+
+    assert buy_mm.call_count == 2
+    call_args = buy_mm.call_args_list[1][1]
+    assert call_args['pair'] == pair
+    assert call_args['rate'] == fix_price
+    assert call_args['amount'] == round(stake_amount / fix_price, 8)
+
+    # In case of closed order
+    limit_buy_order['status'] = 'closed'
+    limit_buy_order['price'] = 10
+    limit_buy_order['cost'] = 100
+    limit_buy_order['id'] = '444'
+
+    mocker.patch('freqtrade.exchange.Exchange.buy', MagicMock(return_value=limit_buy_order))
+    assert freqtrade.execute_buy(pair, stake_amount)
+    trade = Trade.query.all()[2]
+    assert trade
+    assert trade.open_order_id is None
+    assert trade.open_rate == 10
+    assert trade.stake_amount == 100
+
+    # In case of rejected or expired order and partially filled
+    limit_buy_order['status'] = 'expired'
+    limit_buy_order['amount'] = 90.99181073
+    limit_buy_order['filled'] = 80.99181073
+    limit_buy_order['remaining'] = 10.00
+    limit_buy_order['price'] = 0.5
+    limit_buy_order['cost'] = 40.495905365
+    limit_buy_order['id'] = '555'
+    mocker.patch('freqtrade.exchange.Exchange.buy', MagicMock(return_value=limit_buy_order))
+    assert freqtrade.execute_buy(pair, stake_amount)
+    trade = Trade.query.all()[3]
+    assert trade
+    assert trade.open_order_id == '555'
+    assert trade.open_rate == 0.5
+    assert trade.stake_amount == 40.495905365
+
+    # In case of the order is rejected and not filled at all
+    limit_buy_order['status'] = 'rejected'
+    limit_buy_order['amount'] = 90.99181073
+    limit_buy_order['filled'] = 0.0
+    limit_buy_order['remaining'] = 90.99181073
+    limit_buy_order['price'] = 0.5
+    limit_buy_order['cost'] = 0.0
+    limit_buy_order['id'] = '66'
+    mocker.patch('freqtrade.exchange.Exchange.buy', MagicMock(return_value=limit_buy_order))
+    assert not freqtrade.execute_buy(pair, stake_amount)
+
+
+def test_execute_buy_confirm_error(mocker, default_conf, fee, limit_buy_order) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    mocker.patch.multiple(
+        'freqtrade.freqtradebot.FreqtradeBot',
+        get_buy_rate=MagicMock(return_value=0.11),
+        _get_min_pair_stake_amount=MagicMock(return_value=1)
+    )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00001172,
+            'ask': 0.00001173,
+            'last': 0.00001172
+        }),
+        buy=MagicMock(return_value=limit_buy_order),
+        get_fee=fee,
+    )
+    stake_amount = 2
+    pair = 'ETH/BTC'
+
+    freqtrade.strategy.confirm_trade_entry = MagicMock(side_effect=ValueError)
+    assert freqtrade.execute_buy(pair, stake_amount)
+
+    limit_buy_order['id'] = '222'
+    freqtrade.strategy.confirm_trade_entry = MagicMock(side_effect=Exception)
+    assert freqtrade.execute_buy(pair, stake_amount)
+
+    limit_buy_order['id'] = '2223'
+    freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=True)
+    assert freqtrade.execute_buy(pair, stake_amount)
+
+    freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=False)
+    assert not freqtrade.execute_buy(pair, stake_amount)
+
+
+def test_add_stoploss_on_exchange(mocker, default_conf, limit_buy_order) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_trade', MagicMock(return_value=True))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=limit_buy_order)
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
+                 return_value=limit_buy_order['amount'])
+
+    stoploss = MagicMock(return_value={'id': 13434334})
+    mocker.patch('freqtrade.exchange.Exchange.stoploss', stoploss)
+
+    freqtrade = FreqtradeBot(default_conf)
+    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
+
+    trade = MagicMock()
+    trade.open_order_id = None
+    trade.stoploss_order_id = None
+    trade.is_open = True
+    trades = [trade]
+
+    freqtrade.exit_positions(trades)
+    assert trade.stoploss_order_id == '13434334'
+    assert stoploss.call_count == 1
+    assert trade.is_open is True
+
+
+def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
+                                     limit_buy_order, limit_sell_order) -> None:
+    stoploss = MagicMock(return_value={'id': 13434334})
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00001172,
+            'ask': 0.00001173,
+            'last': 0.00001172
+        }),
+        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
+        sell=MagicMock(return_value={'id': limit_sell_order['id']}),
+        get_fee=fee,
+        stoploss=stoploss
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    # First case: when stoploss is not yet set but the order is open
+    # should get the stoploss order id immediately
+    # and should return false as no trade actually happened
+    trade = MagicMock()
+    trade.is_open = True
+    trade.open_order_id = None
+    trade.stoploss_order_id = None
+
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+    assert stoploss.call_count == 1
+    assert trade.stoploss_order_id == "13434334"
+
+    # Second case: when stoploss is set but it is not yet hit
+    # should do nothing and return false
+    trade.is_open = True
+    trade.open_order_id = None
+    trade.stoploss_order_id = 100
+
+    hanging_stoploss_order = MagicMock(return_value={'status': 'open'})
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', hanging_stoploss_order)
+
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+    assert trade.stoploss_order_id == 100
+
+    # Third case: when stoploss was set but it was canceled for some reason
+    # should set a stoploss immediately and return False
+    caplog.clear()
+    trade.is_open = True
+    trade.open_order_id = None
+    trade.stoploss_order_id = 100
+
+    canceled_stoploss_order = MagicMock(return_value={'status': 'canceled'})
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', canceled_stoploss_order)
+    stoploss.reset_mock()
+
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+    assert stoploss.call_count == 1
+    assert trade.stoploss_order_id == "13434334"
+
+    # Fourth case: when stoploss is set and it is hit
+    # should unset stoploss_order_id and return true
+    # as a trade actually happened
+    caplog.clear()
+    freqtrade.enter_positions()
+    trade = Trade.query.first()
+    trade.is_open = True
+    trade.open_order_id = None
+    trade.stoploss_order_id = 100
+    assert trade
+
+    stoploss_order_hit = MagicMock(return_value={
+        'id': 100,
+        'status': 'closed',
+        'type': 'stop_loss_limit',
+        'price': 3,
+        'average': 2,
+        'amount': limit_buy_order['amount'],
+    })
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', stoploss_order_hit)
+    assert freqtrade.handle_stoploss_on_exchange(trade) is True
+    assert log_has_re(r'STOP_LOSS_LIMIT is hit for Trade\(id=1, .*\)\.', caplog)
+    assert trade.stoploss_order_id is None
+    assert trade.is_open is False
+
+    mocker.patch(
+        'freqtrade.exchange.Exchange.stoploss',
+        side_effect=ExchangeError()
+    )
+    trade.is_open = True
+    freqtrade.handle_stoploss_on_exchange(trade)
+    assert log_has('Unable to place a stoploss order on exchange.', caplog)
+    assert trade.stoploss_order_id is None
+
+    # Fifth case: fetch_order returns InvalidOrder
+    # It should try to add stoploss order
+    trade.stoploss_order_id = 100
+    stoploss.reset_mock()
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order',
+                 side_effect=InvalidOrderException())
+    mocker.patch('freqtrade.exchange.Exchange.stoploss', stoploss)
+    freqtrade.handle_stoploss_on_exchange(trade)
+    assert stoploss.call_count == 1
+
+    # Sixth case: Closed Trade
+    # Should not create new order
+    trade.stoploss_order_id = None
+    trade.is_open = False
+    stoploss.reset_mock()
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order')
+    mocker.patch('freqtrade.exchange.Exchange.stoploss', stoploss)
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+    assert stoploss.call_count == 0
+
+
+def test_handle_sle_cancel_cant_recreate(mocker, default_conf, fee, caplog,
+                                         limit_buy_order, limit_sell_order) -> None:
+    # Sixth case: stoploss order was cancelled but couldn't create new one
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00001172,
+            'ask': 0.00001173,
+            'last': 0.00001172
+        }),
+        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
+        sell=MagicMock(return_value={'id': limit_sell_order['id']}),
+        get_fee=fee,
+        fetch_stoploss_order=MagicMock(return_value={'status': 'canceled', 'id': 100}),
+        stoploss=MagicMock(side_effect=ExchangeError()),
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    freqtrade.enter_positions()
+    trade = Trade.query.first()
+    trade.is_open = True
+    trade.open_order_id = None
+    trade.stoploss_order_id = 100
+    assert trade
+
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+    assert log_has_re(r'Stoploss order was cancelled, but unable to recreate one.*', caplog)
+    assert trade.stoploss_order_id is None
+    assert trade.is_open is True
+
+
+def test_create_stoploss_order_invalid_order(mocker, default_conf, caplog, fee,
+                                             limit_buy_order_open, limit_sell_order):
+    rpc_mock = patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    sell_mock = MagicMock(return_value={'id': limit_sell_order['id']})
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00001172,
+            'ask': 0.00001173,
+            'last': 0.00001172
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        sell=sell_mock,
+        get_fee=fee,
+        fetch_order=MagicMock(return_value={'status': 'canceled'}),
+        stoploss=MagicMock(side_effect=InvalidOrderException()),
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
+
+    freqtrade.enter_positions()
+    trade = Trade.query.first()
+    caplog.clear()
+    freqtrade.create_stoploss_order(trade, 200)
+    assert trade.stoploss_order_id is None
+    assert trade.sell_reason == SellType.EMERGENCY_SELL.value
+    assert log_has("Unable to place a stoploss order on exchange. ", caplog)
+    assert log_has("Selling the trade forcefully", caplog)
+
+    # Should call a market sell
+    assert sell_mock.call_count == 1
+    assert sell_mock.call_args[1]['ordertype'] == 'market'
+    assert sell_mock.call_args[1]['pair'] == trade.pair
+    assert sell_mock.call_args[1]['amount'] == trade.amount
+
+    # Rpc is sending first buy, then sell
+    assert rpc_mock.call_count == 2
+    assert rpc_mock.call_args_list[1][0][0]['sell_reason'] == SellType.EMERGENCY_SELL.value
+    assert rpc_mock.call_args_list[1][0][0]['order_type'] == 'market'
+
+
+def test_create_stoploss_order_insufficient_funds(mocker, default_conf, caplog, fee,
+                                                  limit_buy_order_open, limit_sell_order):
+    sell_mock = MagicMock(return_value={'id': limit_sell_order['id']})
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    mock_insuf = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_insufficient_funds')
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00001172,
+            'ask': 0.00001173,
+            'last': 0.00001172
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        sell=sell_mock,
+        get_fee=fee,
+        fetch_order=MagicMock(return_value={'status': 'canceled'}),
+        stoploss=MagicMock(side_effect=InsufficientFundsError()),
+    )
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
+
+    freqtrade.enter_positions()
+    trade = Trade.query.first()
+    caplog.clear()
+    freqtrade.create_stoploss_order(trade, 200)
+    # stoploss_orderid was empty before
+    assert trade.stoploss_order_id is None
+    assert mock_insuf.call_count == 1
+    mock_insuf.reset_mock()
+
+    trade.stoploss_order_id = 'stoploss_orderid'
+    freqtrade.create_stoploss_order(trade, 200)
+    # No change to stoploss-orderid
+    assert trade.stoploss_order_id == 'stoploss_orderid'
+    assert mock_insuf.call_count == 1
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_handle_stoploss_on_exchange_trailing(mocker, default_conf, fee,
+                                              limit_buy_order, limit_sell_order) -> None:
+    # When trailing stoploss is set
+    stoploss = MagicMock(return_value={'id': 13434334})
+    patch_RPCManager(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00001172,
+            'ask': 0.00001173,
+            'last': 0.00001172
+        }),
+        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
+        sell=MagicMock(return_value={'id': limit_sell_order['id']}),
+        get_fee=fee,
+        stoploss=stoploss,
+        stoploss_adjust=MagicMock(return_value=True),
+    )
+
+    # enabling TSL
+    default_conf['trailing_stop'] = True
+
+    # disabling ROI
+    default_conf['minimal_roi']['0'] = 999999999
+
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    # enabling stoploss on exchange
+    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
+
+    # setting stoploss
+    freqtrade.strategy.stoploss = -0.05
+
+    # setting stoploss_on_exchange_interval to 60 seconds
+    freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 60
+
+    patch_get_signal(freqtrade)
+
+    freqtrade.enter_positions()
+    trade = Trade.query.first()
+    trade.is_open = True
+    trade.open_order_id = None
+    trade.stoploss_order_id = 100
+
+    stoploss_order_hanging = MagicMock(return_value={
+        'id': 100,
+        'status': 'open',
+        'type': 'stop_loss_limit',
+        'price': 3,
+        'average': 2,
+        'info': {
+            'stopPrice': '0.000011134'
+        }
+    })
+
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', stoploss_order_hanging)
+
+    # stoploss initially at 5%
+    assert freqtrade.handle_trade(trade) is False
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+
+    # price jumped 2x
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', MagicMock(return_value={
+        'bid': 0.00002344,
+        'ask': 0.00002346,
+        'last': 0.00002344
+    }))
+
+    cancel_order_mock = MagicMock()
+    stoploss_order_mock = MagicMock(return_value={'id': 13434334})
+    mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order', cancel_order_mock)
+    mocker.patch('freqtrade.exchange.Exchange.stoploss', stoploss_order_mock)
+
+    # stoploss should not be updated as the interval is 60 seconds
+    assert freqtrade.handle_trade(trade) is False
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+    cancel_order_mock.assert_not_called()
+    stoploss_order_mock.assert_not_called()
+
+    assert freqtrade.handle_trade(trade) is False
+    assert trade.stop_loss == 0.00002346 * 0.95
+
+    # setting stoploss_on_exchange_interval to 0 seconds
+    freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 0
+
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+
+    cancel_order_mock.assert_called_once_with(100, 'ETH/BTC')
+    stoploss_order_mock.assert_called_once_with(amount=85.32423208,
+                                                pair='ETH/BTC',
+                                                order_types=freqtrade.strategy.order_types,
+                                                stop_price=0.00002346 * 0.95)
+
+    # price fell below stoploss, so dry-run sells trade.
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', MagicMock(return_value={
+        'bid': 0.00002144,
+        'ask': 0.00002146,
+        'last': 0.00002144
+    }))
+    assert freqtrade.handle_trade(trade) is True
+
+
+def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, caplog,
+                                                    limit_buy_order, limit_sell_order) -> None:
+    # When trailing stoploss is set
+    stoploss = MagicMock(return_value={'id': 13434334})
+    patch_exchange(mocker)
+
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00001172,
+            'ask': 0.00001173,
+            'last': 0.00001172
+        }),
+        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
+        sell=MagicMock(return_value={'id': limit_sell_order['id']}),
+        get_fee=fee,
+        stoploss=stoploss,
+        stoploss_adjust=MagicMock(return_value=True),
+    )
+
+    # enabling TSL
+    default_conf['trailing_stop'] = True
+
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    # enabling stoploss on exchange
+    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
+
+    # setting stoploss
+    freqtrade.strategy.stoploss = -0.05
+
+    # setting stoploss_on_exchange_interval to 60 seconds
+    freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 60
+    patch_get_signal(freqtrade)
+    freqtrade.enter_positions()
+    trade = Trade.query.first()
+    trade.is_open = True
+    trade.open_order_id = None
+    trade.stoploss_order_id = "abcd"
+    trade.stop_loss = 0.2
+    trade.stoploss_last_update = arrow.utcnow().shift(minutes=-601).datetime.replace(tzinfo=None)
+
+    stoploss_order_hanging = {
+        'id': "abcd",
+        'status': 'open',
+        'type': 'stop_loss_limit',
+        'price': 3,
+        'average': 2,
+        'info': {
+            'stopPrice': '0.1'
+        }
+    }
+    mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order',
+                 side_effect=InvalidOrderException())
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', stoploss_order_hanging)
+    freqtrade.handle_trailing_stoploss_on_exchange(trade, stoploss_order_hanging)
+    assert log_has_re(r"Could not cancel stoploss order abcd for pair ETH/BTC.*", caplog)
+
+    # Still try to create order
+    assert stoploss.call_count == 1
+
+    # Fail creating stoploss order
+    caplog.clear()
+    cancel_mock = mocker.patch("freqtrade.exchange.Exchange.cancel_stoploss_order", MagicMock())
+    mocker.patch("freqtrade.exchange.Exchange.stoploss", side_effect=ExchangeError())
+    freqtrade.handle_trailing_stoploss_on_exchange(trade, stoploss_order_hanging)
+    assert cancel_mock.call_count == 1
+    assert log_has_re(r"Could not create trailing stoploss order for pair ETH/BTC\..*", caplog)
+
+
+def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog,
+                                              limit_buy_order, limit_sell_order) -> None:
+
+    # When trailing stoploss is set
+    stoploss = MagicMock(return_value={'id': 13434334})
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    patch_edge(mocker)
+    edge_conf['max_open_trades'] = float('inf')
+    edge_conf['dry_run_wallet'] = 999.9
+    edge_conf['exchange']['name'] = 'binance'
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00001172,
+            'ask': 0.00001173,
+            'last': 0.00001172
+        }),
+        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
+        sell=MagicMock(return_value={'id': limit_sell_order['id']}),
+        get_fee=fee,
+        stoploss=stoploss,
+    )
+
+    # enabling TSL
+    edge_conf['trailing_stop'] = True
+    edge_conf['trailing_stop_positive'] = 0.01
+    edge_conf['trailing_stop_positive_offset'] = 0.011
+
+    # disabling ROI
+    edge_conf['minimal_roi']['0'] = 999999999
+
+    freqtrade = FreqtradeBot(edge_conf)
+
+    # enabling stoploss on exchange
+    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
+
+    # setting stoploss
+    freqtrade.strategy.stoploss = -0.02
+
+    # setting stoploss_on_exchange_interval to 0 seconds
+    freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 0
+
+    patch_get_signal(freqtrade)
+
+    freqtrade.active_pair_whitelist = freqtrade.edge.adjust(freqtrade.active_pair_whitelist)
+
+    freqtrade.enter_positions()
+    trade = Trade.query.first()
+    trade.is_open = True
+    trade.open_order_id = None
+    trade.stoploss_order_id = 100
+
+    stoploss_order_hanging = MagicMock(return_value={
+        'id': 100,
+        'status': 'open',
+        'type': 'stop_loss_limit',
+        'price': 3,
+        'average': 2,
+        'info': {
+            'stopPrice': '0.000009384'
+        }
+    })
+
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', stoploss_order_hanging)
+
+    # stoploss initially at 20% as edge dictated it.
+    assert freqtrade.handle_trade(trade) is False
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+    assert trade.stop_loss == 0.000009384
+
+    cancel_order_mock = MagicMock()
+    stoploss_order_mock = MagicMock()
+    mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order', cancel_order_mock)
+    mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss_order_mock)
+
+    # price goes down 5%
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', MagicMock(return_value={
+        'bid': 0.00001172 * 0.95,
+        'ask': 0.00001173 * 0.95,
+        'last': 0.00001172 * 0.95
+    }))
+
+    assert freqtrade.handle_trade(trade) is False
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+
+    # stoploss should remain the same
+    assert trade.stop_loss == 0.000009384
+
+    # stoploss on exchange should not be canceled
+    cancel_order_mock.assert_not_called()
+
+    # price jumped 2x
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', MagicMock(return_value={
+        'bid': 0.00002344,
+        'ask': 0.00002346,
+        'last': 0.00002344
+    }))
+
+    assert freqtrade.handle_trade(trade) is False
+    assert freqtrade.handle_stoploss_on_exchange(trade) is False
+
+    # stoploss should be set to 1% as trailing is on
+    assert trade.stop_loss == 0.00002346 * 0.99
+    cancel_order_mock.assert_called_once_with(100, 'NEO/BTC')
+    stoploss_order_mock.assert_called_once_with(amount=2132892.49146757,
+                                                pair='NEO/BTC',
+                                                order_types=freqtrade.strategy.order_types,
+                                                stop_price=0.00002346 * 0.99)
+
+
+def test_enter_positions(mocker, default_conf, caplog) -> None:
+    caplog.set_level(logging.DEBUG)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    mock_ct = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.create_trade',
+                           MagicMock(return_value=False))
+    n = freqtrade.enter_positions()
+    assert n == 0
+    assert log_has('Found no buy signals for whitelisted currencies. Trying again...', caplog)
+    # create_trade should be called once for every pair in the whitelist.
+    assert mock_ct.call_count == len(default_conf['exchange']['pair_whitelist'])
+
+
+def test_enter_positions_exception(mocker, default_conf, caplog) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    mock_ct = mocker.patch(
+        'freqtrade.freqtradebot.FreqtradeBot.create_trade',
+        MagicMock(side_effect=DependencyException)
+    )
+    n = freqtrade.enter_positions()
+    assert n == 0
+    assert mock_ct.call_count == len(default_conf['exchange']['pair_whitelist'])
+    assert log_has('Unable to create trade for ETH/BTC: ', caplog)
+
+
+def test_exit_positions(mocker, default_conf, limit_buy_order, caplog) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_trade', MagicMock(return_value=True))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=limit_buy_order)
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
+                 return_value=limit_buy_order['amount'])
+
+    trade = MagicMock()
+    trade.open_order_id = '123'
+    trade.open_fee = 0.001
+    trades = [trade]
+    n = freqtrade.exit_positions(trades)
+    assert n == 0
+    # Test amount not modified by fee-logic
+    assert not log_has(
+        'Applying fee to amount for Trade {} from 90.99181073 to 90.81'.format(trade), caplog
+    )
+
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', return_value=90.81)
+    # test amount modified by fee-logic
+    n = freqtrade.exit_positions(trades)
+    assert n == 0
+
+
+def test_exit_positions_exception(mocker, default_conf, limit_buy_order, caplog) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=limit_buy_order)
+
+    trade = MagicMock()
+    trade.open_order_id = None
+    trade.open_fee = 0.001
+    trade.pair = 'ETH/BTC'
+    trades = [trade]
+
+    # Test raise of DependencyException exception
+    mocker.patch(
+        'freqtrade.freqtradebot.FreqtradeBot.handle_trade',
+        side_effect=DependencyException()
+    )
+    n = freqtrade.exit_positions(trades)
+    assert n == 0
+    assert log_has('Unable to sell trade ETH/BTC: ', caplog)
+
+
+def test_update_trade_state(mocker, default_conf, limit_buy_order, caplog) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_trade', MagicMock(return_value=True))
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=limit_buy_order)
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
+                 return_value=limit_buy_order['amount'])
+
+    trade = Trade(
+        open_order_id=123,
+        fee_open=0.001,
+        fee_close=0.001,
+        open_rate=0.01,
+        open_date=arrow.utcnow().datetime,
+        amount=11,
+    )
+    assert not freqtrade.update_trade_state(trade, None)
+    assert log_has_re(r'Orderid for trade .* is empty.', caplog)
+    # Add datetime explicitly since sqlalchemy defaults apply only once written to database
+    freqtrade.update_trade_state(trade, '123')
+    # Test amount not modified by fee-logic
+    assert not log_has_re(r'Applying fee to .*', caplog)
+    assert trade.open_order_id is None
+    assert trade.amount == limit_buy_order['amount']
+
+    trade.open_order_id = '123'
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', return_value=90.81)
+    assert trade.amount != 90.81
+    # test amount modified by fee-logic
+    freqtrade.update_trade_state(trade, '123')
+    assert trade.amount == 90.81
+    assert trade.open_order_id is None
+
+    trade.is_open = True
+    trade.open_order_id = None
+    # Assert we call handle_trade() if trade is feasible for execution
+    freqtrade.update_trade_state(trade, '123')
+
+    assert log_has_re('Found open order for.*', caplog)
+
+
+def test_update_trade_state_withorderdict(default_conf, trades_for_order, limit_buy_order, fee,
+                                          mocker):
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
+    # fetch_order should not be called!!
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', MagicMock(side_effect=ValueError))
+    patch_exchange(mocker)
+    Trade.session = MagicMock()
+    amount = sum(x['amount'] for x in trades_for_order)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        open_rate=0.245441,
+        open_date=arrow.utcnow().datetime,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_order_id="123456",
+        is_open=True,
+    )
+    freqtrade.update_trade_state(trade, '123456', limit_buy_order)
+    assert trade.amount != amount
+    assert trade.amount == limit_buy_order['amount']
+
+
+def test_update_trade_state_withorderdict_rounding_fee(default_conf, trades_for_order, fee,
+                                                       limit_buy_order, mocker, caplog):
+    trades_for_order[0]['amount'] = limit_buy_order['amount'] + 1e-14
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
+    # fetch_order should not be called!!
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', MagicMock(side_effect=ValueError))
+    patch_exchange(mocker)
+    Trade.session = MagicMock()
+    amount = sum(x['amount'] for x in trades_for_order)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        open_rate=0.245441,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_order_id='123456',
+        is_open=True,
+        open_date=arrow.utcnow().datetime,
+    )
+    freqtrade.update_trade_state(trade, '123456', limit_buy_order)
+    assert trade.amount != amount
+    assert trade.amount == limit_buy_order['amount']
+    assert log_has_re(r'Applying fee on amount for .*', caplog)
+
+
+def test_update_trade_state_exception(mocker, default_conf,
+                                      limit_buy_order, caplog) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=limit_buy_order)
+
+    trade = MagicMock()
+    trade.open_order_id = '123'
+    trade.open_fee = 0.001
+
+    # Test raise of OperationalException exception
+    mocker.patch(
+        'freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
+        side_effect=DependencyException()
+    )
+    freqtrade.update_trade_state(trade, trade.open_order_id)
+    assert log_has('Could not update trade amount: ', caplog)
+
+
+def test_update_trade_state_orderexception(mocker, default_conf, caplog) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order',
+                 MagicMock(side_effect=InvalidOrderException))
+
+    trade = MagicMock()
+    trade.open_order_id = '123'
+    trade.open_fee = 0.001
+
+    # Test raise of OperationalException exception
+    grm_mock = mocker.patch("freqtrade.freqtradebot.FreqtradeBot.get_real_amount", MagicMock())
+    freqtrade.update_trade_state(trade, trade.open_order_id)
+    assert grm_mock.call_count == 0
+    assert log_has(f'Unable to fetch order {trade.open_order_id}: ', caplog)
+
+
+def test_update_trade_state_sell(default_conf, trades_for_order, limit_sell_order_open,
+                                 limit_sell_order, mocker):
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
+    # fetch_order should not be called!!
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', MagicMock(side_effect=ValueError))
+    wallet_mock = MagicMock()
+    mocker.patch('freqtrade.wallets.Wallets.update', wallet_mock)
+
+    patch_exchange(mocker)
+    Trade.session = MagicMock()
+    amount = limit_sell_order["amount"]
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    wallet_mock.reset_mock()
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        open_rate=0.245441,
+        fee_open=0.0025,
+        fee_close=0.0025,
+        open_date=arrow.utcnow().datetime,
+        open_order_id="123456",
+        is_open=True,
+    )
+    order = Order.parse_from_ccxt_object(limit_sell_order_open, 'LTC/ETH', 'sell')
+    trade.orders.append(order)
+    assert order.status == 'open'
+    freqtrade.update_trade_state(trade, trade.open_order_id, limit_sell_order)
+    assert trade.amount == limit_sell_order['amount']
+    # Wallet needs to be updated after closing a limit-sell order to reenable buying
+    assert wallet_mock.call_count == 1
+    assert not trade.is_open
+    # Order is updated by update_trade_state
+    assert order.status == 'closed'
+
+
+def test_handle_trade(default_conf, limit_buy_order, limit_sell_order_open, limit_sell_order,
+                      fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00001172,
+            'ask': 0.00001173,
+            'last': 0.00001172
+        }),
+        buy=MagicMock(return_value=limit_buy_order),
+        sell=MagicMock(return_value=limit_sell_order_open),
+        get_fee=fee,
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    assert trade
+
+    time.sleep(0.01)  # Race condition fix
+    trade.update(limit_buy_order)
+    assert trade.is_open is True
+    freqtrade.wallets.update()
+
+    patch_get_signal(freqtrade, value=(False, True))
+    assert freqtrade.handle_trade(trade) is True
+    assert trade.open_order_id == limit_sell_order['id']
+
+    # Simulate fulfilled LIMIT_SELL order for trade
+    trade.update(limit_sell_order)
+
+    assert trade.close_rate == 0.00001173
+    assert trade.close_profit == 0.06201058
+    assert trade.calc_profit() == 0.00006217
+    assert trade.close_date is not None
+
+
+def test_handle_overlapping_signals(default_conf, ticker, limit_buy_order_open,
+                                    fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade, value=(True, True))
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
+
+    freqtrade.enter_positions()
+
+    # Buy and Sell triggering, so doing nothing ...
+    trades = Trade.query.all()
+    nb_trades = len(trades)
+    assert nb_trades == 0
+
+    # Buy is triggering, so buying ...
+    patch_get_signal(freqtrade, value=(True, False))
+    freqtrade.enter_positions()
+    trades = Trade.query.all()
+    nb_trades = len(trades)
+    assert nb_trades == 1
+    assert trades[0].is_open is True
+
+    # Buy and Sell are not triggering, so doing nothing ...
+    patch_get_signal(freqtrade, value=(False, False))
+    assert freqtrade.handle_trade(trades[0]) is False
+    trades = Trade.query.all()
+    nb_trades = len(trades)
+    assert nb_trades == 1
+    assert trades[0].is_open is True
+
+    # Buy and Sell are triggering, so doing nothing ...
+    patch_get_signal(freqtrade, value=(True, True))
+    assert freqtrade.handle_trade(trades[0]) is False
+    trades = Trade.query.all()
+    nb_trades = len(trades)
+    assert nb_trades == 1
+    assert trades[0].is_open is True
+
+    # Sell is triggering, guess what : we are Selling!
+    patch_get_signal(freqtrade, value=(False, True))
+    trades = Trade.query.all()
+    assert freqtrade.handle_trade(trades[0]) is True
+
+
+def test_handle_trade_roi(default_conf, ticker, limit_buy_order_open,
+                          fee, mocker, caplog) -> None:
+    caplog.set_level(logging.DEBUG)
+
+    patch_RPCManager(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    patch_get_signal(freqtrade, value=(True, False))
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=True)
+
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    trade.is_open = True
+
+    # FIX: sniffing logs, suggest handle_trade should not execute_sell
+    #      instead that responsibility should be moved out of handle_trade(),
+    #      we might just want to check if we are in a sell condition without
+    #      executing
+    # if ROI is reached we must sell
+    patch_get_signal(freqtrade, value=(False, True))
+    assert freqtrade.handle_trade(trade)
+    assert log_has("ETH/BTC - Required profit reached. sell_flag=True, sell_type=SellType.ROI",
+                   caplog)
+
+
+def test_handle_trade_use_sell_signal(
+        default_conf, ticker, limit_buy_order_open, fee, mocker, caplog) -> None:
+    # use_sell_signal is True buy default
+    caplog.set_level(logging.DEBUG)
+    patch_RPCManager(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    trade.is_open = True
+
+    patch_get_signal(freqtrade, value=(False, False))
+    assert not freqtrade.handle_trade(trade)
+
+    patch_get_signal(freqtrade, value=(False, True))
+    assert freqtrade.handle_trade(trade)
+    assert log_has("ETH/BTC - Sell signal received. sell_flag=True, sell_type=SellType.SELL_SIGNAL",
+                   caplog)
+
+
+def test_close_trade(default_conf, ticker, limit_buy_order, limit_buy_order_open, limit_sell_order,
+                     fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    # Create trade and sell it
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    assert trade
+
+    trade.update(limit_buy_order)
+    trade.update(limit_sell_order)
+    assert trade.is_open is False
+
+    with pytest.raises(DependencyException, match=r'.*closed trade.*'):
+        freqtrade.handle_trade(trade)
+
+
+def test_bot_loop_start_called_once(mocker, default_conf, caplog):
+    ftbot = get_patched_freqtradebot(mocker, default_conf)
+    patch_get_signal(ftbot)
+    ftbot.strategy.bot_loop_start = MagicMock(side_effect=ValueError)
+    ftbot.strategy.analyze = MagicMock()
+
+    ftbot.process()
+    assert log_has_re(r'Strategy caused the following exception.*', caplog)
+    assert ftbot.strategy.bot_loop_start.call_count == 1
+    assert ftbot.strategy.analyze.call_count == 1
+
+
+def test_check_handle_timedout_buy_usercustom(default_conf, ticker, limit_buy_order_old, open_trade,
+                                              fee, mocker) -> None:
+    default_conf["unfilledtimeout"] = {"buy": 1400, "sell": 30}
+
+    rpc_mock = patch_RPCManager(mocker)
+    cancel_order_mock = MagicMock(return_value=limit_buy_order_old)
+    cancel_buy_order = deepcopy(limit_buy_order_old)
+    cancel_buy_order['status'] = 'canceled'
+    cancel_order_wr_mock = MagicMock(return_value=cancel_buy_order)
+
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        fetch_order=MagicMock(return_value=limit_buy_order_old),
+        cancel_order_with_result=cancel_order_wr_mock,
+        cancel_order=cancel_order_mock,
+        get_fee=fee
+    )
+    freqtrade = FreqtradeBot(default_conf)
+
+    Trade.session.add(open_trade)
+
+    # Ensure default is to return empty (so not mocked yet)
+    freqtrade.check_handle_timedout()
+    assert cancel_order_mock.call_count == 0
+
+    # Return false - trade remains open
+    freqtrade.strategy.check_buy_timeout = MagicMock(return_value=False)
+    freqtrade.check_handle_timedout()
+    assert cancel_order_mock.call_count == 0
+    trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
+    nb_trades = len(trades)
+    assert nb_trades == 1
+    assert freqtrade.strategy.check_buy_timeout.call_count == 1
+
+    # Raise Keyerror ... (no impact on trade)
+    freqtrade.strategy.check_buy_timeout = MagicMock(side_effect=KeyError)
+    freqtrade.check_handle_timedout()
+    assert cancel_order_mock.call_count == 0
+    trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
+    nb_trades = len(trades)
+    assert nb_trades == 1
+    assert freqtrade.strategy.check_buy_timeout.call_count == 1
+
+    freqtrade.strategy.check_buy_timeout = MagicMock(return_value=True)
+    # Trade should be closed since the function returns true
+    freqtrade.check_handle_timedout()
+    assert cancel_order_wr_mock.call_count == 1
+    assert rpc_mock.call_count == 1
+    trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
+    nb_trades = len(trades)
+    assert nb_trades == 0
+    assert freqtrade.strategy.check_buy_timeout.call_count == 1
+
+
+def test_check_handle_timedout_buy(default_conf, ticker, limit_buy_order_old, open_trade,
+                                   fee, mocker) -> None:
+    rpc_mock = patch_RPCManager(mocker)
+    limit_buy_cancel = deepcopy(limit_buy_order_old)
+    limit_buy_cancel['status'] = 'canceled'
+    cancel_order_mock = MagicMock(return_value=limit_buy_cancel)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        fetch_order=MagicMock(return_value=limit_buy_order_old),
+        cancel_order_with_result=cancel_order_mock,
+        get_fee=fee
+    )
+    freqtrade = FreqtradeBot(default_conf)
+
+    Trade.session.add(open_trade)
+
+    freqtrade.strategy.check_buy_timeout = MagicMock(return_value=False)
+    # check it does cancel buy orders over the time limit
+    freqtrade.check_handle_timedout()
+    assert cancel_order_mock.call_count == 1
+    assert rpc_mock.call_count == 1
+    trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
+    nb_trades = len(trades)
+    assert nb_trades == 0
+    # Custom user buy-timeout is never called
+    assert freqtrade.strategy.check_buy_timeout.call_count == 0
+
+
+def test_check_handle_cancelled_buy(default_conf, ticker, limit_buy_order_old, open_trade,
+                                    fee, mocker, caplog) -> None:
+    """ Handle Buy order cancelled on exchange"""
+    rpc_mock = patch_RPCManager(mocker)
+    cancel_order_mock = MagicMock()
+    patch_exchange(mocker)
+    limit_buy_order_old.update({"status": "canceled", 'filled': 0.0})
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        fetch_order=MagicMock(return_value=limit_buy_order_old),
+        cancel_order=cancel_order_mock,
+        get_fee=fee
+    )
+    freqtrade = FreqtradeBot(default_conf)
+
+    Trade.session.add(open_trade)
+
+    # check it does cancel buy orders over the time limit
+    freqtrade.check_handle_timedout()
+    assert cancel_order_mock.call_count == 0
+    assert rpc_mock.call_count == 1
+    trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
+    nb_trades = len(trades)
+    assert nb_trades == 0
+    assert log_has_re("Buy order cancelled on exchange for Trade.*", caplog)
+
+
+def test_check_handle_timedout_buy_exception(default_conf, ticker, limit_buy_order_old, open_trade,
+                                             fee, mocker) -> None:
+    rpc_mock = patch_RPCManager(mocker)
+    cancel_order_mock = MagicMock()
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        validate_pairs=MagicMock(),
+        fetch_ticker=ticker,
+        fetch_order=MagicMock(side_effect=ExchangeError),
+        cancel_order=cancel_order_mock,
+        get_fee=fee
+    )
+    freqtrade = FreqtradeBot(default_conf)
+
+    Trade.session.add(open_trade)
+
+    # check it does cancel buy orders over the time limit
+    freqtrade.check_handle_timedout()
+    assert cancel_order_mock.call_count == 0
+    assert rpc_mock.call_count == 0
+    trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
+    nb_trades = len(trades)
+    assert nb_trades == 1
+
+
+def test_check_handle_timedout_sell_usercustom(default_conf, ticker, limit_sell_order_old, mocker,
+                                               open_trade) -> None:
+    default_conf["unfilledtimeout"] = {"buy": 1440, "sell": 1440}
+    rpc_mock = patch_RPCManager(mocker)
+    cancel_order_mock = MagicMock()
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        fetch_order=MagicMock(return_value=limit_sell_order_old),
+        cancel_order=cancel_order_mock
+    )
+    freqtrade = FreqtradeBot(default_conf)
+
+    open_trade.open_date = arrow.utcnow().shift(hours=-5).datetime
+    open_trade.close_date = arrow.utcnow().shift(minutes=-601).datetime
+    open_trade.is_open = False
+
+    Trade.session.add(open_trade)
+    # Ensure default is false
+    freqtrade.check_handle_timedout()
+    assert cancel_order_mock.call_count == 0
+
+    freqtrade.strategy.check_sell_timeout = MagicMock(return_value=False)
+    # Return false - No impact
+    freqtrade.check_handle_timedout()
+    assert cancel_order_mock.call_count == 0
+    assert rpc_mock.call_count == 0
+    assert open_trade.is_open is False
+    assert freqtrade.strategy.check_sell_timeout.call_count == 1
+
+    freqtrade.strategy.check_sell_timeout = MagicMock(side_effect=KeyError)
+    # Return Error - No impact
+    freqtrade.check_handle_timedout()
+    assert cancel_order_mock.call_count == 0
+    assert rpc_mock.call_count == 0
+    assert open_trade.is_open is False
+    assert freqtrade.strategy.check_sell_timeout.call_count == 1
+
+    # Return True - sells!
+    freqtrade.strategy.check_sell_timeout = MagicMock(return_value=True)
+    freqtrade.check_handle_timedout()
+    assert cancel_order_mock.call_count == 1
+    assert rpc_mock.call_count == 1
+    assert open_trade.is_open is True
+    assert freqtrade.strategy.check_sell_timeout.call_count == 1
+
+
+def test_check_handle_timedout_sell(default_conf, ticker, limit_sell_order_old, mocker,
+                                    open_trade) -> None:
+    rpc_mock = patch_RPCManager(mocker)
+    cancel_order_mock = MagicMock()
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        fetch_order=MagicMock(return_value=limit_sell_order_old),
+        cancel_order=cancel_order_mock
+    )
+    freqtrade = FreqtradeBot(default_conf)
+
+    open_trade.open_date = arrow.utcnow().shift(hours=-5).datetime
+    open_trade.close_date = arrow.utcnow().shift(minutes=-601).datetime
+    open_trade.is_open = False
+
+    Trade.session.add(open_trade)
+
+    freqtrade.strategy.check_sell_timeout = MagicMock(return_value=False)
+    # check it does cancel sell orders over the time limit
+    freqtrade.check_handle_timedout()
+    assert cancel_order_mock.call_count == 1
+    assert rpc_mock.call_count == 1
+    assert open_trade.is_open is True
+    # Custom user sell-timeout is never called
+    assert freqtrade.strategy.check_sell_timeout.call_count == 0
+
+
+def test_check_handle_cancelled_sell(default_conf, ticker, limit_sell_order_old, open_trade,
+                                     mocker, caplog) -> None:
+    """ Handle sell order cancelled on exchange"""
+    rpc_mock = patch_RPCManager(mocker)
+    cancel_order_mock = MagicMock()
+    limit_sell_order_old.update({"status": "canceled", 'filled': 0.0})
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        fetch_order=MagicMock(return_value=limit_sell_order_old),
+        cancel_order_with_result=cancel_order_mock
+    )
+    freqtrade = FreqtradeBot(default_conf)
+
+    open_trade.open_date = arrow.utcnow().shift(hours=-5).datetime
+    open_trade.close_date = arrow.utcnow().shift(minutes=-601).datetime
+    open_trade.is_open = False
+
+    Trade.session.add(open_trade)
+
+    # check it does cancel sell orders over the time limit
+    freqtrade.check_handle_timedout()
+    assert cancel_order_mock.call_count == 0
+    assert rpc_mock.call_count == 1
+    assert open_trade.is_open is True
+    assert log_has_re("Sell order cancelled on exchange for Trade.*", caplog)
+
+
+def test_check_handle_timedout_partial(default_conf, ticker, limit_buy_order_old_partial,
+                                       open_trade, mocker) -> None:
+    rpc_mock = patch_RPCManager(mocker)
+    limit_buy_canceled = deepcopy(limit_buy_order_old_partial)
+    limit_buy_canceled['status'] = 'canceled'
+
+    cancel_order_mock = MagicMock(return_value=limit_buy_canceled)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        fetch_order=MagicMock(return_value=limit_buy_order_old_partial),
+        cancel_order_with_result=cancel_order_mock
+    )
+    freqtrade = FreqtradeBot(default_conf)
+
+    Trade.session.add(open_trade)
+
+    # check it does cancel buy orders over the time limit
+    # note this is for a partially-complete buy order
+    freqtrade.check_handle_timedout()
+    assert cancel_order_mock.call_count == 1
+    assert rpc_mock.call_count == 1
+    trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
+    assert len(trades) == 1
+    assert trades[0].amount == 23.0
+    assert trades[0].stake_amount == open_trade.open_rate * trades[0].amount
+
+
+def test_check_handle_timedout_partial_fee(default_conf, ticker, open_trade, caplog, fee,
+                                           limit_buy_order_old_partial, trades_for_order,
+                                           limit_buy_order_old_partial_canceled, mocker) -> None:
+    rpc_mock = patch_RPCManager(mocker)
+    cancel_order_mock = MagicMock(return_value=limit_buy_order_old_partial_canceled)
+    mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(return_value=0))
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        fetch_order=MagicMock(return_value=limit_buy_order_old_partial),
+        cancel_order_with_result=cancel_order_mock,
+        get_trades_for_order=MagicMock(return_value=trades_for_order),
+    )
+    freqtrade = FreqtradeBot(default_conf)
+
+    assert open_trade.amount == limit_buy_order_old_partial['amount']
+
+    open_trade.fee_open = fee()
+    open_trade.fee_close = fee()
+    Trade.session.add(open_trade)
+    # cancelling a half-filled order should update the amount to the bought amount
+    # and apply fees if necessary.
+    freqtrade.check_handle_timedout()
+
+    assert log_has_re(r"Applying fee on amount for Trade.*", caplog)
+
+    assert cancel_order_mock.call_count == 1
+    assert rpc_mock.call_count == 1
+    trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
+    assert len(trades) == 1
+    # Verify that trade has been updated
+    assert trades[0].amount == (limit_buy_order_old_partial['amount'] -
+                                limit_buy_order_old_partial['remaining']) - 0.023
+    assert trades[0].open_order_id is None
+    assert trades[0].fee_updated('buy')
+    assert pytest.approx(trades[0].fee_open) == 0.001
+
+
+def test_check_handle_timedout_partial_except(default_conf, ticker, open_trade, caplog, fee,
+                                              limit_buy_order_old_partial, trades_for_order,
+                                              limit_buy_order_old_partial_canceled, mocker) -> None:
+    rpc_mock = patch_RPCManager(mocker)
+    cancel_order_mock = MagicMock(return_value=limit_buy_order_old_partial_canceled)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        fetch_order=MagicMock(return_value=limit_buy_order_old_partial),
+        cancel_order_with_result=cancel_order_mock,
+        get_trades_for_order=MagicMock(return_value=trades_for_order),
+    )
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
+                 MagicMock(side_effect=DependencyException))
+    freqtrade = FreqtradeBot(default_conf)
+
+    assert open_trade.amount == limit_buy_order_old_partial['amount']
+
+    open_trade.fee_open = fee()
+    open_trade.fee_close = fee()
+    Trade.session.add(open_trade)
+    # cancelling a half-filled order should update the amount to the bought amount
+    # and apply fees if necessary.
+    freqtrade.check_handle_timedout()
+
+    assert log_has_re(r"Could not update trade amount: .*", caplog)
+
+    assert cancel_order_mock.call_count == 1
+    assert rpc_mock.call_count == 1
+    trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
+    assert len(trades) == 1
+    # Verify that trade has been updated
+
+    assert trades[0].amount == (limit_buy_order_old_partial['amount'] -
+                                limit_buy_order_old_partial['remaining'])
+    assert trades[0].open_order_id is None
+    assert trades[0].fee_open == fee()
+
+
+def test_check_handle_timedout_exception(default_conf, ticker, open_trade, mocker, caplog) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    cancel_order_mock = MagicMock()
+
+    mocker.patch.multiple(
+        'freqtrade.freqtradebot.FreqtradeBot',
+        handle_cancel_buy=MagicMock(),
+        handle_cancel_sell=MagicMock(),
+    )
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        fetch_order=MagicMock(side_effect=ExchangeError('Oh snap')),
+        cancel_order=cancel_order_mock
+    )
+    freqtrade = FreqtradeBot(default_conf)
+
+    Trade.session.add(open_trade)
+
+    freqtrade.check_handle_timedout()
+    assert log_has_re(r"Cannot query order for Trade\(id=1, pair=ETH/BTC, amount=90.99181073, "
+                      r"open_rate=0.00001099, open_since="
+                      f"{open_trade.open_date.strftime('%Y-%m-%d %H:%M:%S')}"
+                      r"\) due to Traceback \(most recent call last\):\n*",
+                      caplog)
+
+
+def test_handle_cancel_buy(mocker, caplog, default_conf, limit_buy_order) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    cancel_buy_order = deepcopy(limit_buy_order)
+    cancel_buy_order['status'] = 'canceled'
+    del cancel_buy_order['filled']
+
+    cancel_order_mock = MagicMock(return_value=cancel_buy_order)
+    mocker.patch('freqtrade.exchange.Exchange.cancel_order_with_result', cancel_order_mock)
+
+    freqtrade = FreqtradeBot(default_conf)
+    freqtrade._notify_buy_cancel = MagicMock()
+
+    Trade.session = MagicMock()
+    trade = MagicMock()
+    trade.pair = 'LTC/ETH'
+    limit_buy_order['filled'] = 0.0
+    limit_buy_order['status'] = 'open'
+    reason = CANCEL_REASON['TIMEOUT']
+    assert freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
+    assert cancel_order_mock.call_count == 1
+
+    cancel_order_mock.reset_mock()
+    limit_buy_order['filled'] = 2
+    assert not freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
+    assert cancel_order_mock.call_count == 1
+
+    # Order remained open for some reason (cancel failed)
+    cancel_buy_order['status'] = 'open'
+    cancel_order_mock = MagicMock(return_value=cancel_buy_order)
+    mocker.patch('freqtrade.exchange.Exchange.cancel_order_with_result', cancel_order_mock)
+    assert not freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
+    assert log_has_re(r"Order .* for .* not cancelled.", caplog)
+
+
+@pytest.mark.parametrize("limit_buy_order_canceled_empty", ['binance', 'ftx', 'kraken', 'bittrex'],
+                         indirect=['limit_buy_order_canceled_empty'])
+def test_handle_cancel_buy_exchanges(mocker, caplog, default_conf,
+                                     limit_buy_order_canceled_empty) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    cancel_order_mock = mocker.patch(
+        'freqtrade.exchange.Exchange.cancel_order_with_result',
+        return_value=limit_buy_order_canceled_empty)
+    nofiy_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot._notify_buy_cancel')
+    freqtrade = FreqtradeBot(default_conf)
+
+    Trade.session = MagicMock()
+    reason = CANCEL_REASON['TIMEOUT']
+    trade = MagicMock()
+    trade.pair = 'LTC/ETH'
+    assert freqtrade.handle_cancel_buy(trade, limit_buy_order_canceled_empty, reason)
+    assert cancel_order_mock.call_count == 0
+    assert log_has_re(r'Buy order fully cancelled. Removing .* from database\.', caplog)
+    assert nofiy_mock.call_count == 1
+
+
+@pytest.mark.parametrize('cancelorder', [
+    {},
+    {'remaining': None},
+    'String Return value',
+    123
+])
+def test_handle_cancel_buy_corder_empty(mocker, default_conf, limit_buy_order,
+                                        cancelorder) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    cancel_order_mock = MagicMock(return_value=cancelorder)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        cancel_order=cancel_order_mock
+    )
+
+    freqtrade = FreqtradeBot(default_conf)
+    freqtrade._notify_buy_cancel = MagicMock()
+
+    Trade.session = MagicMock()
+    trade = MagicMock()
+    trade.pair = 'LTC/ETH'
+    limit_buy_order['filled'] = 0.0
+    limit_buy_order['status'] = 'open'
+    reason = CANCEL_REASON['TIMEOUT']
+    assert freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
+    assert cancel_order_mock.call_count == 1
+
+    cancel_order_mock.reset_mock()
+    limit_buy_order['filled'] = 1.0
+    assert not freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
+    assert cancel_order_mock.call_count == 1
+
+
+def test_handle_cancel_sell_limit(mocker, default_conf, fee) -> None:
+    send_msg_mock = patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    cancel_order_mock = MagicMock()
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        cancel_order=cancel_order_mock,
+    )
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_sell_rate', return_value=0.245441)
+
+    freqtrade = FreqtradeBot(default_conf)
+
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=2,
+        exchange='binance',
+        open_rate=0.245441,
+        open_order_id="123456",
+        open_date=arrow.utcnow().datetime,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+    )
+    order = {'remaining': 1,
+             'amount': 1,
+             'status': "open"}
+    reason = CANCEL_REASON['TIMEOUT']
+    assert freqtrade.handle_cancel_sell(trade, order, reason)
+    assert cancel_order_mock.call_count == 1
+    assert send_msg_mock.call_count == 1
+
+    send_msg_mock.reset_mock()
+
+    order['amount'] = 2
+    assert freqtrade.handle_cancel_sell(trade, order, reason
+                                        ) == CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
+    # Assert cancel_order was not called (callcount remains unchanged)
+    assert cancel_order_mock.call_count == 1
+    assert send_msg_mock.call_count == 1
+    assert freqtrade.handle_cancel_sell(trade, order, reason
+                                        ) == CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
+    # Message should not be iterated again
+    assert trade.sell_order_status == CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
+    assert send_msg_mock.call_count == 1
+
+
+def test_handle_cancel_sell_cancel_exception(mocker, default_conf) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch(
+        'freqtrade.exchange.Exchange.cancel_order', side_effect=InvalidOrderException())
+
+    freqtrade = FreqtradeBot(default_conf)
+
+    trade = MagicMock()
+    reason = CANCEL_REASON['TIMEOUT']
+    order = {'remaining': 1,
+             'amount': 1,
+             'status': "open"}
+    assert freqtrade.handle_cancel_sell(trade, order, reason) == 'error cancelling order'
+
+
+def test_execute_sell_up(default_conf, ticker, fee, ticker_sell_up, mocker) -> None:
+    rpc_mock = patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+    patch_whitelist(mocker, default_conf)
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.confirm_trade_exit = MagicMock(return_value=False)
+
+    # Create some test data
+    freqtrade.enter_positions()
+    rpc_mock.reset_mock()
+
+    trade = Trade.query.first()
+    assert trade
+    assert freqtrade.strategy.confirm_trade_exit.call_count == 0
+
+    # Increase the price and sell it
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker_sell_up
+    )
+    # Prevented sell ...
+    freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'], sell_reason=SellType.ROI)
+    assert rpc_mock.call_count == 0
+    assert freqtrade.strategy.confirm_trade_exit.call_count == 1
+
+    # Repatch with true
+    freqtrade.strategy.confirm_trade_exit = MagicMock(return_value=True)
+
+    freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'], sell_reason=SellType.ROI)
+    assert freqtrade.strategy.confirm_trade_exit.call_count == 1
+
+    assert rpc_mock.call_count == 1
+    last_msg = rpc_mock.call_args_list[-1][0][0]
+    assert {
+        'trade_id': 1,
+        'type': RPCMessageType.SELL_NOTIFICATION,
+        'exchange': 'Bittrex',
+        'pair': 'ETH/BTC',
+        'gain': 'profit',
+        'limit': 1.172e-05,
+        'amount': 91.07468123,
+        'order_type': 'limit',
+        'open_rate': 1.098e-05,
+        'current_rate': 1.173e-05,
+        'profit_amount': 6.223e-05,
+        'profit_ratio': 0.0620716,
+        'stake_currency': 'BTC',
+        'fiat_currency': 'USD',
+        'sell_reason': SellType.ROI.value,
+        'open_date': ANY,
+        'close_date': ANY,
+    } == last_msg
+
+
+def test_execute_sell_down(default_conf, ticker, fee, ticker_sell_down, mocker) -> None:
+    rpc_mock = patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+    patch_whitelist(mocker, default_conf)
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    # Create some test data
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    assert trade
+
+    # Decrease the price and sell it
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker_sell_down
+    )
+
+    freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
+                           sell_reason=SellType.STOP_LOSS)
+
+    assert rpc_mock.call_count == 2
+    last_msg = rpc_mock.call_args_list[-1][0][0]
+    assert {
+        'type': RPCMessageType.SELL_NOTIFICATION,
+        'trade_id': 1,
+        'exchange': 'Bittrex',
+        'pair': 'ETH/BTC',
+        'gain': 'loss',
+        'limit': 1.044e-05,
+        'amount': 91.07468123,
+        'order_type': 'limit',
+        'open_rate': 1.098e-05,
+        'current_rate': 1.043e-05,
+        'profit_amount': -5.406e-05,
+        'profit_ratio': -0.05392257,
+        'stake_currency': 'BTC',
+        'fiat_currency': 'USD',
+        'sell_reason': SellType.STOP_LOSS.value,
+        'open_date': ANY,
+        'close_date': ANY,
+    } == last_msg
+
+
+def test_execute_sell_down_stoploss_on_exchange_dry_run(default_conf, ticker, fee,
+                                                        ticker_sell_down, mocker) -> None:
+    rpc_mock = patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+    patch_whitelist(mocker, default_conf)
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    # Create some test data
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    assert trade
+
+    # Decrease the price and sell it
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker_sell_down
+    )
+
+    default_conf['dry_run'] = True
+    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
+    # Setting trade stoploss to 0.01
+
+    trade.stop_loss = 0.00001099 * 0.99
+    freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
+                           sell_reason=SellType.STOP_LOSS)
+
+    assert rpc_mock.call_count == 2
+    last_msg = rpc_mock.call_args_list[-1][0][0]
+
+    assert {
+        'type': RPCMessageType.SELL_NOTIFICATION,
+        'trade_id': 1,
+        'exchange': 'Bittrex',
+        'pair': 'ETH/BTC',
+        'gain': 'loss',
+        'limit': 1.08801e-05,
+        'amount': 91.07468123,
+        'order_type': 'limit',
+        'open_rate': 1.098e-05,
+        'current_rate': 1.043e-05,
+        'profit_amount': -1.408e-05,
+        'profit_ratio': -0.01404051,
+        'stake_currency': 'BTC',
+        'fiat_currency': 'USD',
+        'sell_reason': SellType.STOP_LOSS.value,
+        'open_date': ANY,
+        'close_date': ANY,
+
+    } == last_msg
+
+
+def test_execute_sell_sloe_cancel_exception(mocker, default_conf, ticker, fee, caplog) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    mocker.patch('freqtrade.exchange.Exchange.cancel_stoploss_order',
+                 side_effect=InvalidOrderException())
+    mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(return_value=300))
+    sellmock = MagicMock()
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+        sell=sellmock
+    )
+
+    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
+    patch_get_signal(freqtrade)
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    Trade.session = MagicMock()
+    PairLock.session = MagicMock()
+
+    freqtrade.config['dry_run'] = False
+    trade.stoploss_order_id = "abcd"
+
+    freqtrade.execute_sell(trade=trade, limit=1234,
+                           sell_reason=SellType.STOP_LOSS)
+    assert sellmock.call_count == 1
+    assert log_has('Could not cancel stoploss order abcd', caplog)
+
+
+def test_execute_sell_with_stoploss_on_exchange(default_conf, ticker, fee, ticker_sell_up,
+                                                mocker) -> None:
+
+    default_conf['exchange']['name'] = 'binance'
+    rpc_mock = patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    stoploss = MagicMock(return_value={
+        'id': 123,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+
+    cancel_order = MagicMock(return_value=True)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+        amount_to_precision=lambda s, x, y: y,
+        price_to_precision=lambda s, x, y: y,
+        stoploss=stoploss,
+        cancel_stoploss_order=cancel_order,
+    )
+
+    freqtrade = FreqtradeBot(default_conf)
+    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
+    patch_get_signal(freqtrade)
+
+    # Create some test data
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    assert trade
+    trades = [trade]
+
+    freqtrade.check_handle_timedout()
+    freqtrade.exit_positions(trades)
+
+    # Increase the price and sell it
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker_sell_up
+    )
+
+    freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
+                           sell_reason=SellType.SELL_SIGNAL)
+
+    trade = Trade.query.first()
+    assert trade
+    assert cancel_order.call_count == 1
+    assert rpc_mock.call_count == 2
+
+
+def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf, ticker, fee,
+                                                         mocker) -> None:
+    default_conf['exchange']['name'] = 'binance'
+    rpc_mock = patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+        amount_to_precision=lambda s, x, y: y,
+        price_to_precision=lambda s, x, y: y,
+    )
+
+    stoploss = MagicMock(return_value={
+        'id': 123,
+        'info': {
+            'foo': 'bar'
+        }
+    })
+
+    mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss)
+
+    freqtrade = FreqtradeBot(default_conf)
+    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
+    patch_get_signal(freqtrade)
+
+    # Create some test data
+    freqtrade.enter_positions()
+    freqtrade.check_handle_timedout()
+    trade = Trade.query.first()
+    trades = [trade]
+    assert trade.stoploss_order_id is None
+
+    freqtrade.exit_positions(trades)
+    assert trade
+    assert trade.stoploss_order_id == '123'
+    assert trade.open_order_id is None
+
+    # Assuming stoploss on exchnage is hit
+    # stoploss_order_id should become None
+    # and trade should be sold at the price of stoploss
+    stoploss_executed = MagicMock(return_value={
+        "id": "123",
+        "timestamp": 1542707426845,
+        "datetime": "2018-11-20T09:50:26.845Z",
+        "lastTradeTimestamp": None,
+        "symbol": "BTC/USDT",
+        "type": "stop_loss_limit",
+        "side": "sell",
+        "price": 1.08801,
+        "amount": 90.99181074,
+        "cost": 99.0000000032274,
+        "average": 1.08801,
+        "filled": 90.99181074,
+        "remaining": 0.0,
+        "status": "closed",
+        "fee": None,
+        "trades": None
+    })
+    mocker.patch('freqtrade.exchange.Exchange.fetch_stoploss_order', stoploss_executed)
+
+    freqtrade.exit_positions(trades)
+    assert trade.stoploss_order_id is None
+    assert trade.is_open is False
+    assert trade.sell_reason == SellType.STOPLOSS_ON_EXCHANGE.value
+    assert rpc_mock.call_count == 2
+
+
+def test_execute_sell_market_order(default_conf, ticker, fee,
+                                   ticker_sell_up, mocker) -> None:
+    rpc_mock = patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+    patch_whitelist(mocker, default_conf)
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    # Create some test data
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    assert trade
+
+    # Increase the price and sell it
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker_sell_up
+    )
+    freqtrade.config['order_types']['sell'] = 'market'
+
+    freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'], sell_reason=SellType.ROI)
+
+    assert not trade.is_open
+    assert trade.close_profit == 0.0620716
+
+    assert rpc_mock.call_count == 2
+    last_msg = rpc_mock.call_args_list[-1][0][0]
+    assert {
+        'type': RPCMessageType.SELL_NOTIFICATION,
+        'trade_id': 1,
+        'exchange': 'Bittrex',
+        'pair': 'ETH/BTC',
+        'gain': 'profit',
+        'limit': 1.172e-05,
+        'amount': 91.07468123,
+        'order_type': 'market',
+        'open_rate': 1.098e-05,
+        'current_rate': 1.173e-05,
+        'profit_amount': 6.223e-05,
+        'profit_ratio': 0.0620716,
+        'stake_currency': 'BTC',
+        'fiat_currency': 'USD',
+        'sell_reason': SellType.ROI.value,
+        'open_date': ANY,
+        'close_date': ANY,
+
+    } == last_msg
+
+
+def test_execute_sell_insufficient_funds_error(default_conf, ticker, fee,
+                                               ticker_sell_up, mocker) -> None:
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    mock_insuf = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_insufficient_funds')
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+        sell=MagicMock(side_effect=InsufficientFundsError())
+    )
+    patch_get_signal(freqtrade)
+
+    # Create some test data
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    assert trade
+
+    # Increase the price and sell it
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker_sell_up
+    )
+
+    assert not freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
+                                      sell_reason=SellType.ROI)
+    assert mock_insuf.call_count == 1
+
+
+def test_sell_profit_only_enable_profit(default_conf, limit_buy_order, limit_buy_order_open,
+                                        fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00002172,
+            'ask': 0.00002173,
+            'last': 0.00002172
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    default_conf['ask_strategy'] = {
+        'use_sell_signal': True,
+        'sell_profit_only': True,
+    }
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
+
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    trade.update(limit_buy_order)
+    freqtrade.wallets.update()
+    patch_get_signal(freqtrade, value=(False, True))
+    assert freqtrade.handle_trade(trade) is True
+    assert trade.sell_reason == SellType.SELL_SIGNAL.value
+
+
+def test_sell_profit_only_disable_profit(default_conf, limit_buy_order, limit_buy_order_open,
+                                         fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00002172,
+            'ask': 0.00002173,
+            'last': 0.00002172
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    default_conf['ask_strategy'] = {
+        'use_sell_signal': True,
+        'sell_profit_only': False,
+    }
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    trade.update(limit_buy_order)
+    freqtrade.wallets.update()
+    patch_get_signal(freqtrade, value=(False, True))
+    assert freqtrade.handle_trade(trade) is True
+    assert trade.sell_reason == SellType.SELL_SIGNAL.value
+
+
+def test_sell_profit_only_enable_loss(default_conf, limit_buy_order, limit_buy_order_open,
+                                      fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00000172,
+            'ask': 0.00000173,
+            'last': 0.00000172
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    default_conf['ask_strategy'] = {
+        'use_sell_signal': True,
+        'sell_profit_only': True,
+    }
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.stop_loss_reached = MagicMock(return_value=SellCheckTuple(
+        sell_flag=False, sell_type=SellType.NONE))
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    trade.update(limit_buy_order)
+    patch_get_signal(freqtrade, value=(False, True))
+    assert freqtrade.handle_trade(trade) is False
+
+
+def test_sell_profit_only_disable_loss(default_conf, limit_buy_order, limit_buy_order_open,
+                                       fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.0000172,
+            'ask': 0.0000173,
+            'last': 0.0000172
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    default_conf['ask_strategy'] = {
+        'use_sell_signal': True,
+        'sell_profit_only': False,
+    }
+
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
+
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    trade.update(limit_buy_order)
+    freqtrade.wallets.update()
+    patch_get_signal(freqtrade, value=(False, True))
+    assert freqtrade.handle_trade(trade) is True
+    assert trade.sell_reason == SellType.SELL_SIGNAL.value
+
+
+def test_sell_not_enough_balance(default_conf, limit_buy_order, limit_buy_order_open,
+                                 fee, mocker, caplog) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00002172,
+            'ask': 0.00002173,
+            'last': 0.00002172
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
+
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    amnt = trade.amount
+    trade.update(limit_buy_order)
+    patch_get_signal(freqtrade, value=(False, True))
+    mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(return_value=trade.amount * 0.985))
+
+    assert freqtrade.handle_trade(trade) is True
+    assert log_has_re(r'.*Falling back to wallet-amount.', caplog)
+    assert trade.amount != amnt
+
+
+def test__safe_sell_amount(default_conf, fee, caplog, mocker):
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    amount = 95.33
+    amount_wallet = 95.29
+    mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(return_value=amount_wallet))
+    wallet_update = mocker.patch('freqtrade.wallets.Wallets.update')
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        open_rate=0.245441,
+        open_order_id="123456",
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    wallet_update.reset_mock()
+    assert freqtrade._safe_sell_amount(trade.pair, trade.amount) == amount_wallet
+    assert log_has_re(r'.*Falling back to wallet-amount.', caplog)
+    assert wallet_update.call_count == 1
+    caplog.clear()
+    wallet_update.reset_mock()
+    assert freqtrade._safe_sell_amount(trade.pair, amount_wallet) == amount_wallet
+    assert not log_has_re(r'.*Falling back to wallet-amount.', caplog)
+    assert wallet_update.call_count == 1
+
+
+def test__safe_sell_amount_error(default_conf, fee, caplog, mocker):
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    amount = 95.33
+    amount_wallet = 91.29
+    mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(return_value=amount_wallet))
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        open_rate=0.245441,
+        open_order_id="123456",
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    with pytest.raises(DependencyException, match=r"Not enough amount to sell."):
+        assert freqtrade._safe_sell_amount(trade.pair, trade.amount)
+
+
+def test_locked_pairs(default_conf, ticker, fee, ticker_sell_down, mocker, caplog) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    # Create some test data
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    assert trade
+
+    # Decrease the price and sell it
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker_sell_down
+    )
+
+    freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
+                           sell_reason=SellType.STOP_LOSS)
+    trade.close(ticker_sell_down()['bid'])
+    assert freqtrade.strategy.is_pair_locked(trade.pair)
+
+    # reinit - should buy other pair.
+    caplog.clear()
+    freqtrade.enter_positions()
+
+    assert log_has(f"Pair {trade.pair} is currently locked.", caplog)
+
+
+def test_ignore_roi_if_buy_signal(default_conf, limit_buy_order, limit_buy_order_open,
+                                  fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.0000172,
+            'ask': 0.0000173,
+            'last': 0.0000172
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    default_conf['ask_strategy'] = {
+        'ignore_roi_if_buy_signal': True
+    }
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=True)
+
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    trade.update(limit_buy_order)
+    freqtrade.wallets.update()
+    patch_get_signal(freqtrade, value=(True, True))
+    assert freqtrade.handle_trade(trade) is False
+
+    # Test if buy-signal is absent (should sell due to roi = true)
+    patch_get_signal(freqtrade, value=(False, True))
+    assert freqtrade.handle_trade(trade) is True
+    assert trade.sell_reason == SellType.ROI.value
+
+
+def test_trailing_stop_loss(default_conf, limit_buy_order_open, limit_buy_order,
+                            fee, caplog, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00001099,
+            'ask': 0.00001099,
+            'last': 0.00001099
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    default_conf['trailing_stop'] = True
+    patch_whitelist(mocker, default_conf)
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
+
+    freqtrade.enter_positions()
+    trade = Trade.query.first()
+    assert freqtrade.handle_trade(trade) is False
+
+    # Raise ticker above buy price
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
+                 MagicMock(return_value={
+                     'bid': 0.00001099 * 1.5,
+                     'ask': 0.00001099 * 1.5,
+                     'last': 0.00001099 * 1.5
+                 }))
+
+    # Stoploss should be adjusted
+    assert freqtrade.handle_trade(trade) is False
+
+    # Price fell
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
+                 MagicMock(return_value={
+                     'bid': 0.00001099 * 1.1,
+                     'ask': 0.00001099 * 1.1,
+                     'last': 0.00001099 * 1.1
+                 }))
+
+    caplog.set_level(logging.DEBUG)
+    # Sell as trailing-stop is reached
+    assert freqtrade.handle_trade(trade) is True
+    assert log_has("ETH/BTC - HIT STOP: current price at 0.000012, stoploss is 0.000015, "
+                   "initial stoploss was at 0.000010, trade opened at 0.000011", caplog)
+    assert trade.sell_reason == SellType.TRAILING_STOP_LOSS.value
+
+
+def test_trailing_stop_loss_positive(default_conf, limit_buy_order, limit_buy_order_open, fee,
+                                     caplog, mocker) -> None:
+    buy_price = limit_buy_order['price']
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': buy_price - 0.000001,
+            'ask': buy_price - 0.000001,
+            'last': buy_price - 0.000001
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    default_conf['trailing_stop'] = True
+    default_conf['trailing_stop_positive'] = 0.01
+    patch_whitelist(mocker, default_conf)
+
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    trade.update(limit_buy_order)
+    caplog.set_level(logging.DEBUG)
+    # stop-loss not reached
+    assert freqtrade.handle_trade(trade) is False
+
+    # Raise ticker above buy price
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
+                 MagicMock(return_value={
+                     'bid': buy_price + 0.000003,
+                     'ask': buy_price + 0.000003,
+                     'last': buy_price + 0.000003
+                 }))
+    # stop-loss not reached, adjusted stoploss
+    assert freqtrade.handle_trade(trade) is False
+    assert log_has("ETH/BTC - Using positive stoploss: 0.01 offset: 0 profit: 0.2666%", caplog)
+    assert log_has("ETH/BTC - Adjusting stoploss...", caplog)
+    assert trade.stop_loss == 0.0000138501
+
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
+                 MagicMock(return_value={
+                     'bid': buy_price + 0.000002,
+                     'ask': buy_price + 0.000002,
+                     'last': buy_price + 0.000002
+                 }))
+    # Lower price again (but still positive)
+    assert freqtrade.handle_trade(trade) is True
+    assert log_has(
+        f"ETH/BTC - HIT STOP: current price at {buy_price + 0.000002:.6f}, "
+        f"stoploss is {trade.stop_loss:.6f}, "
+        f"initial stoploss was at 0.000010, trade opened at 0.000011", caplog)
+
+
+def test_trailing_stop_loss_offset(default_conf, limit_buy_order, limit_buy_order_open, fee,
+                                   caplog, mocker) -> None:
+    buy_price = limit_buy_order['price']
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': buy_price - 0.000001,
+            'ask': buy_price - 0.000001,
+            'last': buy_price - 0.000001
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    patch_whitelist(mocker, default_conf)
+    default_conf['trailing_stop'] = True
+    default_conf['trailing_stop_positive'] = 0.01
+    default_conf['trailing_stop_positive_offset'] = 0.011
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    trade.update(limit_buy_order)
+    caplog.set_level(logging.DEBUG)
+    # stop-loss not reached
+    assert freqtrade.handle_trade(trade) is False
+
+    # Raise ticker above buy price
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
+                 MagicMock(return_value={
+                     'bid': buy_price + 0.000003,
+                     'ask': buy_price + 0.000003,
+                     'last': buy_price + 0.000003
+                 }))
+    # stop-loss not reached, adjusted stoploss
+    assert freqtrade.handle_trade(trade) is False
+    assert log_has("ETH/BTC - Using positive stoploss: 0.01 offset: 0.011 profit: 0.2666%", caplog)
+    assert log_has("ETH/BTC - Adjusting stoploss...", caplog)
+    assert trade.stop_loss == 0.0000138501
+
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
+                 MagicMock(return_value={
+                     'bid': buy_price + 0.000002,
+                     'ask': buy_price + 0.000002,
+                     'last': buy_price + 0.000002
+                 }))
+    # Lower price again (but still positive)
+    assert freqtrade.handle_trade(trade) is True
+    assert log_has(
+        f"ETH/BTC - HIT STOP: current price at {buy_price + 0.000002:.6f}, "
+        f"stoploss is {trade.stop_loss:.6f}, "
+        f"initial stoploss was at 0.000010, trade opened at 0.000011", caplog)
+    assert trade.sell_reason == SellType.TRAILING_STOP_LOSS.value
+
+
+def test_tsl_only_offset_reached(default_conf, limit_buy_order, limit_buy_order_open, fee,
+                                 caplog, mocker) -> None:
+    buy_price = limit_buy_order['price']
+    # buy_price: 0.00001099
+
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': buy_price,
+            'ask': buy_price,
+            'last': buy_price
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    patch_whitelist(mocker, default_conf)
+    default_conf['trailing_stop'] = True
+    default_conf['trailing_stop_positive'] = 0.05
+    default_conf['trailing_stop_positive_offset'] = 0.055
+    default_conf['trailing_only_offset_is_reached'] = True
+
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    trade.update(limit_buy_order)
+    caplog.set_level(logging.DEBUG)
+    # stop-loss not reached
+    assert freqtrade.handle_trade(trade) is False
+    assert trade.stop_loss == 0.0000098910
+
+    # Raise ticker above buy price
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
+                 MagicMock(return_value={
+                     'bid': buy_price + 0.0000004,
+                     'ask': buy_price + 0.0000004,
+                     'last': buy_price + 0.0000004
+                 }))
+
+    # stop-loss should not be adjusted as offset is not reached yet
+    assert freqtrade.handle_trade(trade) is False
+
+    assert not log_has("ETH/BTC - Adjusting stoploss...", caplog)
+    assert trade.stop_loss == 0.0000098910
+
+    # price rises above the offset (rises 12% when the offset is 5.5%)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
+                 MagicMock(return_value={
+                     'bid': buy_price + 0.0000014,
+                     'ask': buy_price + 0.0000014,
+                     'last': buy_price + 0.0000014
+                 }))
+
+    assert freqtrade.handle_trade(trade) is False
+    assert log_has("ETH/BTC - Using positive stoploss: 0.05 offset: 0.055 profit: 0.1218%", caplog)
+    assert log_has("ETH/BTC - Adjusting stoploss...", caplog)
+    assert trade.stop_loss == 0.0000117705
+
+
+def test_disable_ignore_roi_if_buy_signal(default_conf, limit_buy_order, limit_buy_order_open,
+                                          fee, mocker) -> None:
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00000172,
+            'ask': 0.00000173,
+            'last': 0.00000172
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+    default_conf['ask_strategy'] = {
+        'ignore_roi_if_buy_signal': False
+    }
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.strategy.min_roi_reached = MagicMock(return_value=True)
+
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    trade.update(limit_buy_order)
+    # Sell due to min_roi_reached
+    patch_get_signal(freqtrade, value=(True, True))
+    assert freqtrade.handle_trade(trade) is True
+
+    # Test if buy-signal is absent
+    patch_get_signal(freqtrade, value=(False, True))
+    assert freqtrade.handle_trade(trade) is True
+    assert trade.sell_reason == SellType.STOP_LOSS.value
+
+
+def test_get_real_amount_quote(default_conf, trades_for_order, buy_order_fee, fee, caplog, mocker):
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
+    amount = sum(x['amount'] for x in trades_for_order)
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        open_rate=0.245441,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    # Amount is reduced by "fee"
+    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount - (amount * 0.001)
+    assert log_has('Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
+                   'open_rate=0.24544100, open_since=closed) (from 8.0 to 7.992).',
+                   caplog)
+
+
+def test_get_real_amount_quote_dust(default_conf, trades_for_order, buy_order_fee, fee,
+                                    caplog, mocker):
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
+    walletmock = mocker.patch('freqtrade.wallets.Wallets.update')
+    mocker.patch('freqtrade.wallets.Wallets.get_free', return_value=8.1122)
+    amount = sum(x['amount'] for x in trades_for_order)
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        open_rate=0.245441,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    walletmock.reset_mock()
+    # Amount is kept as is
+    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
+    assert walletmock.call_count == 1
+    assert log_has_re(r'Fee amount for Trade.* was in base currency '
+                      '- Eating Fee 0.008 into dust', caplog)
+
+
+def test_get_real_amount_no_trade(default_conf, buy_order_fee, caplog, mocker, fee):
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
+
+    amount = buy_order_fee['amount']
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        open_rate=0.245441,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    # Amount is reduced by "fee"
+    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
+    assert log_has('Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
+                   'open_rate=0.24544100, open_since=closed) failed: myTrade-Dict empty found',
+                   caplog)
+
+
+def test_get_real_amount_stake(default_conf, trades_for_order, buy_order_fee, fee, mocker):
+    trades_for_order[0]['fee']['currency'] = 'ETH'
+
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
+    amount = sum(x['amount'] for x in trades_for_order)
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.245441,
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    # Amount does not change
+    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
+
+
+def test_get_real_amount_no_currency_in_fee(default_conf, trades_for_order, buy_order_fee,
+                                            fee, mocker):
+
+    limit_buy_order = deepcopy(buy_order_fee)
+    limit_buy_order['fee'] = {'cost': 0.004, 'currency': None}
+    trades_for_order[0]['fee']['currency'] = None
+
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
+    amount = sum(x['amount'] for x in trades_for_order)
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.245441,
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    # Amount does not change
+    assert freqtrade.get_real_amount(trade, limit_buy_order) == amount
+
+
+def test_get_real_amount_BNB(default_conf, trades_for_order, buy_order_fee, fee, mocker):
+    trades_for_order[0]['fee']['currency'] = 'BNB'
+    trades_for_order[0]['fee']['cost'] = 0.00094518
+
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
+    amount = sum(x['amount'] for x in trades_for_order)
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.245441,
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    # Amount does not change
+    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
+
+
+def test_get_real_amount_multi(default_conf, trades_for_order2, buy_order_fee, caplog, fee, mocker):
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order2)
+    amount = float(sum(x['amount'] for x in trades_for_order2))
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.245441,
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    # Amount is reduced by "fee"
+    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount - (amount * 0.001)
+    assert log_has('Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
+                   'open_rate=0.24544100, open_since=closed) (from 8.0 to 7.992).',
+                   caplog)
+
+
+def test_get_real_amount_fromorder(default_conf, trades_for_order, buy_order_fee, fee,
+                                   caplog, mocker):
+    limit_buy_order = deepcopy(buy_order_fee)
+    limit_buy_order['fee'] = {'cost': 0.004, 'currency': 'LTC'}
+
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order',
+                 return_value=[trades_for_order])
+    amount = float(sum(x['amount'] for x in trades_for_order))
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.245441,
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    # Amount is reduced by "fee"
+    assert freqtrade.get_real_amount(trade, limit_buy_order) == amount - 0.004
+    assert log_has('Applying fee on amount for Trade(id=None, pair=LTC/ETH, amount=8.00000000, '
+                   'open_rate=0.24544100, open_since=closed) (from 8.0 to 7.996).',
+                   caplog)
+
+
+def test_get_real_amount_invalid_order(default_conf, trades_for_order, buy_order_fee, fee, mocker):
+    limit_buy_order = deepcopy(buy_order_fee)
+    limit_buy_order['fee'] = {'cost': 0.004}
+
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=[])
+    amount = float(sum(x['amount'] for x in trades_for_order))
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.245441,
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    # Amount does not change
+    assert freqtrade.get_real_amount(trade, limit_buy_order) == amount
+
+
+def test_get_real_amount_wrong_amount(default_conf, trades_for_order, buy_order_fee, fee, mocker):
+    limit_buy_order = deepcopy(buy_order_fee)
+    limit_buy_order['amount'] = limit_buy_order['amount'] - 0.001
+
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
+    amount = float(sum(x['amount'] for x in trades_for_order))
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        open_rate=0.245441,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    # Amount does not change
+    with pytest.raises(DependencyException, match=r"Half bought\? Amounts don't match"):
+        freqtrade.get_real_amount(trade, limit_buy_order)
+
+
+def test_get_real_amount_wrong_amount_rounding(default_conf, trades_for_order, buy_order_fee, fee,
+                                               mocker):
+    # Floats should not be compared directly.
+    limit_buy_order = deepcopy(buy_order_fee)
+    trades_for_order[0]['amount'] = trades_for_order[0]['amount'] + 1e-15
+
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
+    amount = float(sum(x['amount'] for x in trades_for_order))
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_rate=0.245441,
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    # Amount changes by fee amount.
+    assert isclose(freqtrade.get_real_amount(trade, limit_buy_order), amount - (amount * 0.001),
+                   abs_tol=MATH_CLOSE_PREC,)
+
+
+def test_get_real_amount_invalid(default_conf, trades_for_order, buy_order_fee, fee, mocker):
+    # Remove "Currency" from fee dict
+    trades_for_order[0]['fee'] = {'cost': 0.008}
+
+    mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
+    amount = sum(x['amount'] for x in trades_for_order)
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        open_rate=0.245441,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    # Amount does not change
+    assert freqtrade.get_real_amount(trade, buy_order_fee) == amount
+
+
+def test_get_real_amount_open_trade(default_conf, fee, mocker):
+    amount = 12345
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        open_rate=0.245441,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_order_id="123456"
+    )
+    order = {
+        'id': 'mocked_order',
+        'amount': amount,
+        'status': 'open',
+        'side': 'buy',
+    }
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    assert freqtrade.get_real_amount(trade, order) == amount
+
+
+@pytest.mark.parametrize('amount,fee_abs,wallet,amount_exp', [
+    (8.0, 0.0, 10, 8),
+    (8.0, 0.0, 0, 8),
+    (8.0, 0.1, 0, 7.9),
+    (8.0, 0.1, 10, 8),
+    (8.0, 0.1, 8.0, 8.0),
+    (8.0, 0.1, 7.9, 7.9),
+])
+def test_apply_fee_conditional(default_conf, fee, caplog, mocker,
+                               amount, fee_abs, wallet, amount_exp):
+    walletmock = mocker.patch('freqtrade.wallets.Wallets.update')
+    mocker.patch('freqtrade.wallets.Wallets.get_free', return_value=wallet)
+    trade = Trade(
+        pair='LTC/ETH',
+        amount=amount,
+        exchange='binance',
+        open_rate=0.245441,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_order_id="123456"
+    )
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    walletmock.reset_mock()
+    # Amount is kept as is
+    assert freqtrade.apply_fee_conditional(trade, 'LTC', amount, fee_abs) == amount_exp
+    assert walletmock.call_count == 1
+
+
+def test_order_book_depth_of_market(default_conf, ticker, limit_buy_order_open, limit_buy_order,
+                                    fee, mocker, order_book_l2):
+    default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
+    default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 0.1
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book', order_book_l2)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+
+    # Save state of current whitelist
+    whitelist = deepcopy(default_conf['exchange']['pair_whitelist'])
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    assert trade is not None
+    assert trade.stake_amount == 0.001
+    assert trade.is_open
+    assert trade.open_date is not None
+    assert trade.exchange == 'bittrex'
+
+    assert len(Trade.query.all()) == 1
+
+    # Simulate fulfilled LIMIT_BUY order for trade
+    trade.update(limit_buy_order)
+
+    assert trade.open_rate == 0.00001099
+    assert whitelist == default_conf['exchange']['pair_whitelist']
+
+
+def test_order_book_depth_of_market_high_delta(default_conf, ticker, limit_buy_order,
+                                               fee, mocker, order_book_l2):
+    default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
+    # delta is 100 which is impossible to reach. hence check_depth_of_market will return false
+    default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 100
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book', order_book_l2)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value={'id': limit_buy_order['id']}),
+        get_fee=fee,
+    )
+    # Save state of current whitelist
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    assert trade is None
+
+
+def test_order_book_bid_strategy1(mocker, default_conf, order_book_l2) -> None:
+    """
+    test if function get_buy_rate will return the order book price
+    instead of the ask rate
+    """
+    patch_exchange(mocker)
+    ticker_mock = MagicMock(return_value={'ask': 0.045, 'last': 0.046})
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_l2_order_book=order_book_l2,
+        fetch_ticker=ticker_mock,
+
+    )
+    default_conf['exchange']['name'] = 'binance'
+    default_conf['bid_strategy']['use_order_book'] = True
+    default_conf['bid_strategy']['order_book_top'] = 2
+    default_conf['bid_strategy']['ask_last_balance'] = 0
+    default_conf['telegram']['enabled'] = False
+
+    freqtrade = FreqtradeBot(default_conf)
+    assert freqtrade.get_buy_rate('ETH/BTC', True) == 0.043935
+    assert ticker_mock.call_count == 0
+
+
+def test_order_book_bid_strategy_exception(mocker, default_conf, caplog) -> None:
+    patch_exchange(mocker)
+    ticker_mock = MagicMock(return_value={'ask': 0.042, 'last': 0.046})
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_l2_order_book=MagicMock(return_value={'bids': [[]], 'asks': [[]]}),
+        fetch_ticker=ticker_mock,
+
+    )
+    default_conf['exchange']['name'] = 'binance'
+    default_conf['bid_strategy']['use_order_book'] = True
+    default_conf['bid_strategy']['order_book_top'] = 1
+    default_conf['bid_strategy']['ask_last_balance'] = 0
+    default_conf['telegram']['enabled'] = False
+
+    freqtrade = FreqtradeBot(default_conf)
+    # orderbook shall be used even if tickers would be lower.
+    with pytest.raises(PricingError):
+        freqtrade.get_buy_rate('ETH/BTC', refresh=True)
+    assert log_has_re(r'Buy Price from orderbook could not be determined.', caplog)
+
+
+def test_check_depth_of_market_buy(default_conf, mocker, order_book_l2) -> None:
+    """
+    test check depth of market
+    """
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_l2_order_book=order_book_l2
+    )
+    default_conf['telegram']['enabled'] = False
+    default_conf['exchange']['name'] = 'binance'
+    default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
+    # delta is 100 which is impossible to reach. hence function will return false
+    default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 100
+    freqtrade = FreqtradeBot(default_conf)
+
+    conf = default_conf['bid_strategy']['check_depth_of_market']
+    assert freqtrade._check_depth_of_market_buy('ETH/BTC', conf) is False
+
+
+def test_order_book_ask_strategy(default_conf, limit_buy_order_open, limit_buy_order, fee,
+                                 limit_sell_order_open, mocker, order_book_l2, caplog) -> None:
+    """
+    test order book ask strategy
+    """
+    mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book', order_book_l2)
+    default_conf['exchange']['name'] = 'binance'
+    default_conf['ask_strategy']['use_order_book'] = True
+    default_conf['ask_strategy']['order_book_min'] = 1
+    default_conf['ask_strategy']['order_book_max'] = 2
+    default_conf['telegram']['enabled'] = False
+    patch_RPCManager(mocker)
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=MagicMock(return_value={
+            'bid': 0.00001172,
+            'ask': 0.00001173,
+            'last': 0.00001172
+        }),
+        buy=MagicMock(return_value=limit_buy_order_open),
+        sell=MagicMock(return_value=limit_sell_order_open),
+        get_fee=fee,
+    )
+    freqtrade = FreqtradeBot(default_conf)
+    patch_get_signal(freqtrade)
+
+    freqtrade.enter_positions()
+
+    trade = Trade.query.first()
+    assert trade
+
+    time.sleep(0.01)  # Race condition fix
+    trade.update(limit_buy_order)
+    freqtrade.wallets.update()
+    assert trade.is_open is True
+
+    patch_get_signal(freqtrade, value=(False, True))
+    assert freqtrade.handle_trade(trade) is True
+    assert trade.close_rate_requested == order_book_l2.return_value['asks'][0][0]
+
+    mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book',
+                 return_value={'bids': [[]], 'asks': [[]]})
+    with pytest.raises(PricingError):
+        freqtrade.handle_trade(trade)
+    assert log_has('Sell Price at location 1 from orderbook could not be determined.', caplog)
+
+
+@pytest.mark.parametrize('side,ask,bid,expected', [
+    ('bid', 10.0, 11.0, 11.0),
+    ('bid', 10.0, 11.2, 11.2),
+    ('bid', 10.0, 11.0, 11.0),
+    ('bid', 9.8, 11.0, 11.0),
+    ('bid', 0.0001, 0.002, 0.002),
+    ('ask', 10.0, 11.0, 10.0),
+    ('ask', 10.11, 11.2, 10.11),
+    ('ask', 0.001, 0.002, 0.001),
+    ('ask', 0.006, 1.0, 0.006),
+])
+def test_get_sell_rate(default_conf, mocker, caplog, side, bid, ask, expected) -> None:
+    caplog.set_level(logging.DEBUG)
+
+    default_conf['ask_strategy']['price_side'] = side
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', return_value={'ask': ask, 'bid': bid})
+    pair = "ETH/BTC"
+
+    # Test regular mode
+    ft = get_patched_freqtradebot(mocker, default_conf)
+    rate = ft.get_sell_rate(pair, True)
+    assert not log_has("Using cached sell rate for ETH/BTC.", caplog)
+    assert isinstance(rate, float)
+    assert rate == expected
+    # Use caching
+    rate = ft.get_sell_rate(pair, False)
+    assert rate == expected
+    assert log_has("Using cached sell rate for ETH/BTC.", caplog)
+
+
+@pytest.mark.parametrize('side,expected', [
+    ('bid', 0.043936),  # Value from order_book_l2 fiture - bids side
+    ('ask', 0.043949),  # Value from order_book_l2 fiture - asks side
+])
+def test_get_sell_rate_orderbook(default_conf, mocker, caplog, side, expected, order_book_l2):
+    caplog.set_level(logging.DEBUG)
+    # Test orderbook mode
+    default_conf['ask_strategy']['price_side'] = side
+    default_conf['ask_strategy']['use_order_book'] = True
+    default_conf['ask_strategy']['order_book_min'] = 1
+    default_conf['ask_strategy']['order_book_max'] = 2
+    pair = "ETH/BTC"
+    mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book', order_book_l2)
+    ft = get_patched_freqtradebot(mocker, default_conf)
+    rate = ft.get_sell_rate(pair, True)
+    assert not log_has("Using cached sell rate for ETH/BTC.", caplog)
+    assert isinstance(rate, float)
+    assert rate == expected
+    rate = ft.get_sell_rate(pair, False)
+    assert rate == expected
+    assert log_has("Using cached sell rate for ETH/BTC.", caplog)
+
+
+def test_get_sell_rate_orderbook_exception(default_conf, mocker, caplog):
+    # Test orderbook mode
+    default_conf['ask_strategy']['price_side'] = 'ask'
+    default_conf['ask_strategy']['use_order_book'] = True
+    default_conf['ask_strategy']['order_book_min'] = 1
+    default_conf['ask_strategy']['order_book_max'] = 2
+    pair = "ETH/BTC"
+    # Test What happens if the exchange returns an empty orderbook.
+    mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book',
+                 return_value={'bids': [[]], 'asks': [[]]})
+    ft = get_patched_freqtradebot(mocker, default_conf)
+    with pytest.raises(PricingError):
+        ft.get_sell_rate(pair, True)
+    assert log_has("Sell Price at location from orderbook could not be determined.", caplog)
+
+
+def test_get_sell_rate_exception(default_conf, mocker, caplog):
+    # Ticker on one side can be empty in certain circumstances.
+    default_conf['ask_strategy']['price_side'] = 'ask'
+    pair = "ETH/BTC"
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
+                 return_value={'ask': None, 'bid': 0.12})
+    ft = get_patched_freqtradebot(mocker, default_conf)
+    with pytest.raises(PricingError, match=r"Sell-Rate for ETH/BTC was empty."):
+        ft.get_sell_rate(pair, True)
+
+    ft.config['ask_strategy']['price_side'] = 'bid'
+    assert ft.get_sell_rate(pair, True) == 0.12
+    # Reverse sides
+    mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
+                 return_value={'ask': 0.13, 'bid': None})
+    with pytest.raises(PricingError, match=r"Sell-Rate for ETH/BTC was empty."):
+        ft.get_sell_rate(pair, True)
+
+    ft.config['ask_strategy']['price_side'] = 'ask'
+    assert ft.get_sell_rate(pair, True) == 0.13
+
+
+def test_startup_state(default_conf, mocker):
+    default_conf['pairlist'] = {'method': 'VolumePairList',
+                                'config': {'number_assets': 20}
+                                }
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
+    worker = get_patched_worker(mocker, default_conf)
+    assert worker.freqtrade.state is State.RUNNING
+
+
+def test_startup_trade_reinit(default_conf, edge_conf, mocker):
+
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
+    reinit_mock = MagicMock()
+    mocker.patch('freqtrade.persistence.Trade.stoploss_reinitialization', reinit_mock)
+
+    ftbot = get_patched_freqtradebot(mocker, default_conf)
+    ftbot.startup()
+    assert reinit_mock.call_count == 1
+
+    reinit_mock.reset_mock()
+
+    ftbot = get_patched_freqtradebot(mocker, edge_conf)
+    ftbot.startup()
+    assert reinit_mock.call_count == 0
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_sync_wallet_dry_run(mocker, default_conf, ticker, fee, limit_buy_order_open, caplog):
+    default_conf['dry_run'] = True
+    # Initialize to 2 times stake amount
+    default_conf['dry_run_wallet'] = 0.002
+    default_conf['max_open_trades'] = 2
+    default_conf['tradable_balance_ratio'] = 1.0
+    patch_exchange(mocker)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        buy=MagicMock(return_value=limit_buy_order_open),
+        get_fee=fee,
+    )
+
+    bot = get_patched_freqtradebot(mocker, default_conf)
+    patch_get_signal(bot)
+    assert bot.wallets.get_free('BTC') == 0.002
+
+    n = bot.enter_positions()
+    assert n == 2
+    trades = Trade.query.all()
+    assert len(trades) == 2
+
+    bot.config['max_open_trades'] = 3
+    n = bot.enter_positions()
+    assert n == 0
+    assert log_has_re(r"Unable to create trade for XRP/BTC: "
+                      r"Available balance \(0.0 BTC\) is lower than stake amount \(0.001 BTC\)",
+                      caplog)
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_cancel_all_open_orders(mocker, default_conf, fee, limit_buy_order, limit_sell_order):
+    default_conf['cancel_open_orders_on_exit'] = True
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order',
+                 side_effect=[
+                     ExchangeError(), limit_sell_order, limit_buy_order, limit_sell_order])
+    buy_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_cancel_buy')
+    sell_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_cancel_sell')
+
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    create_mock_trades(fee)
+    trades = Trade.query.all()
+    assert len(trades) == MOCK_TRADE_COUNT
+    freqtrade.cancel_all_open_orders()
+    assert buy_mock.call_count == 1
+    assert sell_mock.call_count == 2
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_check_for_open_trades(mocker, default_conf, fee):
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    freqtrade.check_for_open_trades()
+    assert freqtrade.rpc.send_msg.call_count == 0
+
+    create_mock_trades(fee)
+    trade = Trade.query.first()
+    trade.is_open = True
+
+    freqtrade.check_for_open_trades()
+    assert freqtrade.rpc.send_msg.call_count == 1
+    assert 'Handle these trades manually' in freqtrade.rpc.send_msg.call_args[0][0]['status']
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_update_open_orders(mocker, default_conf, fee, caplog):
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    create_mock_trades(fee)
+
+    freqtrade.update_open_orders()
+    assert log_has_re(r"Error updating Order .*", caplog)
+    caplog.clear()
+
+    assert len(Order.get_open_orders()) == 3
+    matching_buy_order = mock_order_4()
+    matching_buy_order.update({
+        'status': 'closed',
+    })
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order', return_value=matching_buy_order)
+    freqtrade.update_open_orders()
+    # Only stoploss and sell orders are kept open
+    assert len(Order.get_open_orders()) == 2
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_update_closed_trades_without_assigned_fees(mocker, default_conf, fee):
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+
+    def patch_with_fee(order):
+        order.update({'fee': {'cost': 0.1, 'rate': 0.2,
+                      'currency': order['symbol'].split('/')[0]}})
+        return order
+
+    mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
+                 side_effect=[
+                     patch_with_fee(mock_order_2_sell()),
+                     patch_with_fee(mock_order_3_sell()),
+                     patch_with_fee(mock_order_1()),
+                     patch_with_fee(mock_order_2()),
+                     patch_with_fee(mock_order_3()),
+                     patch_with_fee(mock_order_4()),
+                 ]
+                 )
+
+    create_mock_trades(fee)
+    trades = Trade.get_trades().all()
+    assert len(trades) == MOCK_TRADE_COUNT
+    for trade in trades:
+        assert trade.fee_open_cost is None
+        assert trade.fee_open_currency is None
+        assert trade.fee_close_cost is None
+        assert trade.fee_close_currency is None
+
+    freqtrade.update_closed_trades_without_assigned_fees()
+
+    trades = Trade.get_trades().all()
+    assert len(trades) == MOCK_TRADE_COUNT
+
+    for trade in trades:
+        if trade.is_open:
+            # Exclude Trade 4 - as the order is still open.
+            if trade.select_order('buy', False):
+                assert trade.fee_open_cost is not None
+                assert trade.fee_open_currency is not None
+            else:
+                assert trade.fee_open_cost is None
+                assert trade.fee_open_currency is None
+
+        else:
+            assert trade.fee_close_cost is not None
+            assert trade.fee_close_currency is not None
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_reupdate_buy_order_fees(mocker, default_conf, fee, caplog):
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    mock_uts = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.update_trade_state')
+
+    create_mock_trades(fee)
+    trades = Trade.get_trades().all()
+
+    freqtrade.reupdate_buy_order_fees(trades[0])
+    assert log_has_re(r"Trying to reupdate buy fees for .*", caplog)
+    assert mock_uts.call_count == 1
+    assert mock_uts.call_args_list[0][0][0] == trades[0]
+    assert mock_uts.call_args_list[0][0][1] == mock_order_1()['id']
+    assert log_has_re(r"Updating buy-fee on trade .* for order .*\.", caplog)
+    mock_uts.reset_mock()
+    caplog.clear()
+
+    # Test with trade without orders
+    trade = Trade(
+        pair='XRP/ETH',
+        stake_amount=0.001,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_date=arrow.utcnow().datetime,
+        is_open=True,
+        amount=20,
+        open_rate=0.01,
+        exchange='bittrex',
+    )
+    Trade.session.add(trade)
+
+    freqtrade.reupdate_buy_order_fees(trade)
+    assert log_has_re(r"Trying to reupdate buy fees for .*", caplog)
+    assert mock_uts.call_count == 0
+    assert not log_has_re(r"Updating buy-fee on trade .* for order .*\.", caplog)
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_handle_insufficient_funds(mocker, default_conf, fee):
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    mock_rlo = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.refind_lost_order')
+    mock_bof = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.reupdate_buy_order_fees')
+    create_mock_trades(fee)
+    trades = Trade.get_trades().all()
+
+    # Trade 0 has only a open buy order, no closed order
+    freqtrade.handle_insufficient_funds(trades[0])
+    assert mock_rlo.call_count == 0
+    assert mock_bof.call_count == 1
+
+    mock_rlo.reset_mock()
+    mock_bof.reset_mock()
+
+    # Trade 1 has closed buy and sell orders
+    freqtrade.handle_insufficient_funds(trades[1])
+    assert mock_rlo.call_count == 1
+    assert mock_bof.call_count == 0
+
+    mock_rlo.reset_mock()
+    mock_bof.reset_mock()
+
+    # Trade 2 has closed buy and sell orders
+    freqtrade.handle_insufficient_funds(trades[2])
+    assert mock_rlo.call_count == 1
+    assert mock_bof.call_count == 0
+
+    mock_rlo.reset_mock()
+    mock_bof.reset_mock()
+
+    # Trade 3 has an opne buy order
+    freqtrade.handle_insufficient_funds(trades[3])
+    assert mock_rlo.call_count == 0
+    assert mock_bof.call_count == 1
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_refind_lost_order(mocker, default_conf, fee, caplog):
+    caplog.set_level(logging.DEBUG)
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    mock_uts = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.update_trade_state')
+
+    mock_fo = mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
+                           return_value={'status': 'open'})
+
+    def reset_open_orders(trade):
+        trade.open_order_id = None
+        trade.stoploss_order_id = None
+
+    create_mock_trades(fee)
+    trades = Trade.get_trades().all()
+
+    caplog.clear()
+
+    # No open order
+    trade = trades[0]
+    reset_open_orders(trade)
+    assert trade.open_order_id is None
+    assert trade.stoploss_order_id is None
+
+    freqtrade.refind_lost_order(trade)
+    order = mock_order_1()
+    assert log_has_re(r"Order Order(.*order_id=" + order['id'] + ".*) is no longer open.", caplog)
+    assert mock_fo.call_count == 0
+    assert mock_uts.call_count == 0
+    # No change to orderid - as update_trade_state is mocked
+    assert trade.open_order_id is None
+    assert trade.stoploss_order_id is None
+
+    caplog.clear()
+    mock_fo.reset_mock()
+
+    # Open buy order
+    trade = trades[3]
+    reset_open_orders(trade)
+    assert trade.open_order_id is None
+    assert trade.stoploss_order_id is None
+
+    freqtrade.refind_lost_order(trade)
+    order = mock_order_4()
+    assert log_has_re(r"Trying to refind Order\(.*", caplog)
+    assert mock_fo.call_count == 0
+    assert mock_uts.call_count == 0
+    # No change to orderid - as update_trade_state is mocked
+    assert trade.open_order_id is None
+    assert trade.stoploss_order_id is None
+
+    caplog.clear()
+    mock_fo.reset_mock()
+
+    # Open stoploss order
+    trade = trades[4]
+    reset_open_orders(trade)
+    assert trade.open_order_id is None
+    assert trade.stoploss_order_id is None
+
+    freqtrade.refind_lost_order(trade)
+    order = mock_order_5_stoploss()
+    assert log_has_re(r"Trying to refind Order\(.*", caplog)
+    assert mock_fo.call_count == 1
+    assert mock_uts.call_count == 1
+    # stoploss_order_id is "refound" and added to the trade
+    assert trade.open_order_id is None
+    assert trade.stoploss_order_id is not None
+
+    caplog.clear()
+    mock_fo.reset_mock()
+    mock_uts.reset_mock()
+
+    # Open sell order
+    trade = trades[5]
+    reset_open_orders(trade)
+    assert trade.open_order_id is None
+    assert trade.stoploss_order_id is None
+
+    freqtrade.refind_lost_order(trade)
+    order = mock_order_6_sell()
+    assert log_has_re(r"Trying to refind Order\(.*", caplog)
+    assert mock_fo.call_count == 1
+    assert mock_uts.call_count == 1
+    # sell-orderid is "refound" and added to the trade
+    assert trade.open_order_id == order['id']
+    assert trade.stoploss_order_id is None
+
+    caplog.clear()
+
+    # Test error case
+    mock_fo = mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
+                           side_effect=ExchangeError())
+    order = mock_order_5_stoploss()
+
+    freqtrade.refind_lost_order(trades[4])
+    assert log_has(f"Error updating {order['id']}.", caplog)
diff --git a/tests/test_indicators.py b/tests/test_indicators.py
new file mode 100644
index 000000000..8d02330a1
--- /dev/null
+++ b/tests/test_indicators.py
@@ -0,0 +1,19 @@
+import numpy as np
+import pandas as pd
+
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+
+
+def test_crossed_numpy_types():
+    """
+    This test is only present since this method currently diverges from the qtpylib implementation.
+    And we must ensure to not break this again once we update from the original source.
+    """
+    series = pd.Series([56, 97, 19, 76, 65, 25, 87, 91, 79, 79])
+    expected_result = pd.Series([False, True, False, True, False, False, True, False, False, False])
+
+    assert qtpylib.crossed_above(series, 60).equals(expected_result)
+    assert qtpylib.crossed_above(series, 60.0).equals(expected_result)
+    assert qtpylib.crossed_above(series, np.int32(60)).equals(expected_result)
+    assert qtpylib.crossed_above(series, np.int64(60)).equals(expected_result)
+    assert qtpylib.crossed_above(series, np.float64(60.0)).equals(expected_result)
diff --git a/tests/test_integration.py b/tests/test_integration.py
new file mode 100644
index 000000000..9695977ac
--- /dev/null
+++ b/tests/test_integration.py
@@ -0,0 +1,209 @@
+from unittest.mock import MagicMock
+
+import pytest
+
+from freqtrade.persistence import Trade
+from freqtrade.rpc.rpc import RPC
+from freqtrade.strategy.interface import SellCheckTuple, SellType
+from tests.conftest import get_patched_freqtradebot, patch_get_signal
+
+
+def test_may_execute_sell_stoploss_on_exchange_multi(default_conf, ticker, fee,
+                                                     limit_buy_order, mocker) -> None:
+    """
+    Tests workflow of selling stoploss_on_exchange.
+    Sells
+    * first trade as stoploss
+    * 2nd trade is kept
+    * 3rd trade is sold via sell-signal
+    """
+    default_conf['max_open_trades'] = 3
+    default_conf['exchange']['name'] = 'binance'
+
+    stoploss = {
+        'id': 123,
+        'info': {}
+    }
+    stoploss_order_open = {
+        "id": "123",
+        "timestamp": 1542707426845,
+        "datetime": "2018-11-20T09:50:26.845Z",
+        "lastTradeTimestamp": None,
+        "symbol": "BTC/USDT",
+        "type": "stop_loss_limit",
+        "side": "sell",
+        "price": 1.08801,
+        "amount": 90.99181074,
+        "cost": 0.0,
+        "average": 0.0,
+        "filled": 0.0,
+        "remaining": 0.0,
+        "status": "open",
+        "fee": None,
+        "trades": None
+    }
+    stoploss_order_closed = stoploss_order_open.copy()
+    stoploss_order_closed['status'] = 'closed'
+    stoploss_order_closed['filled'] = stoploss_order_closed['amount']
+
+    # Sell first trade based on stoploss, keep 2nd and 3rd trade open
+    stoploss_order_mock = MagicMock(
+        side_effect=[stoploss_order_closed, stoploss_order_open, stoploss_order_open])
+    # Sell 3rd trade (not called for the first trade)
+    should_sell_mock = MagicMock(side_effect=[
+        SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
+        SellCheckTuple(sell_flag=True, sell_type=SellType.SELL_SIGNAL)]
+    )
+    cancel_order_mock = MagicMock()
+    mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss)
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+        amount_to_precision=lambda s, x, y: y,
+        price_to_precision=lambda s, x, y: y,
+        fetch_stoploss_order=stoploss_order_mock,
+        cancel_stoploss_order=cancel_order_mock,
+    )
+
+    mocker.patch.multiple(
+        'freqtrade.freqtradebot.FreqtradeBot',
+        create_stoploss_order=MagicMock(return_value=True),
+        _notify_sell=MagicMock(),
+    )
+    mocker.patch("freqtrade.strategy.interface.IStrategy.should_sell", should_sell_mock)
+    wallets_mock = mocker.patch("freqtrade.wallets.Wallets.update", MagicMock())
+    mocker.patch("freqtrade.wallets.Wallets.get_free", MagicMock(return_value=1000))
+
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
+    # Switch ordertype to market to close trade immediately
+    freqtrade.strategy.order_types['sell'] = 'market'
+    freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=True)
+    freqtrade.strategy.confirm_trade_exit = MagicMock(return_value=True)
+    patch_get_signal(freqtrade)
+
+    # Create some test data
+    freqtrade.enter_positions()
+    assert freqtrade.strategy.confirm_trade_entry.call_count == 3
+    freqtrade.strategy.confirm_trade_entry.reset_mock()
+    assert freqtrade.strategy.confirm_trade_exit.call_count == 0
+    wallets_mock.reset_mock()
+    Trade.session = MagicMock()
+
+    trades = Trade.query.all()
+    # Make sure stoploss-order is open and trade is bought (since we mock update_trade_state)
+    for trade in trades:
+        trade.stoploss_order_id = 3
+        trade.open_order_id = None
+
+    n = freqtrade.exit_positions(trades)
+    assert n == 2
+    assert should_sell_mock.call_count == 2
+    assert freqtrade.strategy.confirm_trade_entry.call_count == 0
+    assert freqtrade.strategy.confirm_trade_exit.call_count == 1
+    freqtrade.strategy.confirm_trade_exit.reset_mock()
+
+    # Only order for 3rd trade needs to be cancelled
+    assert cancel_order_mock.call_count == 1
+    # Wallets must be updated between stoploss cancellation and selling, and will be updated again
+    # during update_trade_state
+    assert wallets_mock.call_count == 4
+
+    trade = trades[0]
+    assert trade.sell_reason == SellType.STOPLOSS_ON_EXCHANGE.value
+    assert not trade.is_open
+
+    trade = trades[1]
+    assert not trade.sell_reason
+    assert trade.is_open
+
+    trade = trades[2]
+    assert trade.sell_reason == SellType.SELL_SIGNAL.value
+    assert not trade.is_open
+
+
+@pytest.mark.parametrize("balance_ratio,result1", [
+                        (1, 200),
+                        (0.99, 198),
+])
+def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, mocker, balance_ratio,
+                                 result1) -> None:
+    """
+    Tests workflow unlimited stake-amount
+    Buy 4 trades, forcebuy a 5th trade
+    Sell one trade, calculated stake amount should now be lower than before since
+    one trade was sold at a loss.
+    """
+    default_conf['max_open_trades'] = 5
+    default_conf['forcebuy_enable'] = True
+    default_conf['stake_amount'] = 'unlimited'
+    default_conf['tradable_balance_ratio'] = balance_ratio
+    default_conf['dry_run_wallet'] = 1000
+    default_conf['exchange']['name'] = 'binance'
+    default_conf['telegram']['enabled'] = True
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
+    mocker.patch.multiple(
+        'freqtrade.exchange.Exchange',
+        fetch_ticker=ticker,
+        get_fee=fee,
+        amount_to_precision=lambda s, x, y: y,
+        price_to_precision=lambda s, x, y: y,
+    )
+
+    mocker.patch.multiple(
+        'freqtrade.freqtradebot.FreqtradeBot',
+        create_stoploss_order=MagicMock(return_value=True),
+        _notify_sell=MagicMock(),
+    )
+    should_sell_mock = MagicMock(side_effect=[
+        SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
+        SellCheckTuple(sell_flag=True, sell_type=SellType.SELL_SIGNAL),
+        SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
+        SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
+        SellCheckTuple(sell_flag=None, sell_type=SellType.NONE)]
+    )
+    mocker.patch("freqtrade.strategy.interface.IStrategy.should_sell", should_sell_mock)
+
+    freqtrade = get_patched_freqtradebot(mocker, default_conf)
+    rpc = RPC(freqtrade)
+    freqtrade.strategy.order_types['stoploss_on_exchange'] = True
+    # Switch ordertype to market to close trade immediately
+    freqtrade.strategy.order_types['sell'] = 'market'
+    patch_get_signal(freqtrade)
+
+    # Create 4 trades
+    n = freqtrade.enter_positions()
+    assert n == 4
+
+    trades = Trade.query.all()
+    assert len(trades) == 4
+    assert freqtrade.get_trade_stake_amount('XRP/BTC') == result1
+
+    rpc._rpc_forcebuy('TKN/BTC', None)
+
+    trades = Trade.query.all()
+    assert len(trades) == 5
+
+    for trade in trades:
+        assert trade.stake_amount == result1
+        # Reset trade open order id's
+        trade.open_order_id = None
+    trades = Trade.get_open_trades()
+    assert len(trades) == 5
+    bals = freqtrade.wallets.get_all_balances()
+
+    n = freqtrade.exit_positions(trades)
+    assert n == 1
+    trades = Trade.get_open_trades()
+    # One trade sold
+    assert len(trades) == 4
+    # stake-amount should now be reduced, since one trade was sold at a loss.
+    assert freqtrade.get_trade_stake_amount('XRP/BTC') < result1
+    # Validate that balance of sold trade is not in dry-run balances anymore.
+    bals2 = freqtrade.wallets.get_all_balances()
+    assert bals != bals2
+    assert len(bals) == 6
+    assert len(bals2) == 5
+    assert 'LTC' in bals
+    assert 'LTC' not in bals2
diff --git a/freqtrade/tests/test_main.py b/tests/test_main.py
similarity index 55%
rename from freqtrade/tests/test_main.py
rename to tests/test_main.py
index bcaad4d7d..f55aea336 100644
--- a/freqtrade/tests/test_main.py
+++ b/tests/test_main.py
@@ -1,18 +1,25 @@
 # pragma pylint: disable=missing-docstring
 
 from copy import deepcopy
-from unittest.mock import MagicMock
+from pathlib import Path
+from unittest.mock import MagicMock, PropertyMock
 
 import pytest
 
-from freqtrade import OperationalException
-from freqtrade.configuration import Arguments
+from freqtrade.commands import Arguments
+from freqtrade.exceptions import FreqtradeException, OperationalException
 from freqtrade.freqtradebot import FreqtradeBot
 from freqtrade.main import main
 from freqtrade.state import State
-from freqtrade.tests.conftest import (log_has, patch_exchange,
-                                      patched_configuration_load_config_file)
 from freqtrade.worker import Worker
+from tests.conftest import (log_has, log_has_re, patch_exchange,
+                            patched_configuration_load_config_file)
+
+
+def test_parse_args_None(caplog) -> None:
+    with pytest.raises(SystemExit):
+        main([])
+    assert log_has_re(r"Usage of Freqtrade requires a subcommand.*", caplog)
 
 
 def test_parse_args_backtesting(mocker) -> None:
@@ -20,31 +27,36 @@ def test_parse_args_backtesting(mocker) -> None:
     Test that main() can start backtesting and also ensure we can pass some specific arguments
     further argument parsing is done in test_arguments.py
     """
-    backtesting_mock = mocker.patch('freqtrade.optimize.start_backtesting', MagicMock())
+    mocker.patch.object(Path, "is_file", MagicMock(side_effect=[False, True]))
+    backtesting_mock = mocker.patch('freqtrade.commands.start_backtesting')
+    backtesting_mock.__name__ = PropertyMock("start_backtesting")
     # it's sys.exit(0) at the end of backtesting
     with pytest.raises(SystemExit):
         main(['backtesting'])
     assert backtesting_mock.call_count == 1
     call_args = backtesting_mock.call_args[0][0]
-    assert call_args.config == ['config.json']
-    assert call_args.live is False
-    assert call_args.verbosity == 0
-    assert call_args.subparser == 'backtesting'
-    assert call_args.func is not None
-    assert call_args.ticker_interval is None
+    assert call_args['config'] == ['config.json']
+    assert call_args['verbosity'] == 0
+    assert call_args['command'] == 'backtesting'
+    assert call_args['func'] is not None
+    assert callable(call_args['func'])
+    assert call_args['timeframe'] is None
 
 
 def test_main_start_hyperopt(mocker) -> None:
-    hyperopt_mock = mocker.patch('freqtrade.optimize.start_hyperopt', MagicMock())
+    mocker.patch.object(Path, 'is_file', MagicMock(side_effect=[False, True]))
+    hyperopt_mock = mocker.patch('freqtrade.commands.start_hyperopt', MagicMock())
+    hyperopt_mock.__name__ = PropertyMock('start_hyperopt')
     # it's sys.exit(0) at the end of hyperopt
     with pytest.raises(SystemExit):
         main(['hyperopt'])
     assert hyperopt_mock.call_count == 1
     call_args = hyperopt_mock.call_args[0][0]
-    assert call_args.config == ['config.json']
-    assert call_args.verbosity == 0
-    assert call_args.subparser == 'hyperopt'
-    assert call_args.func is not None
+    assert call_args['config'] == ['config.json']
+    assert call_args['verbosity'] == 0
+    assert call_args['command'] == 'hyperopt'
+    assert call_args['func'] is not None
+    assert callable(call_args['func'])
 
 
 def test_main_fatal_exception(mocker, default_conf, caplog) -> None:
@@ -53,15 +65,15 @@ def test_main_fatal_exception(mocker, default_conf, caplog) -> None:
     mocker.patch('freqtrade.worker.Worker._worker', MagicMock(side_effect=Exception))
     patched_configuration_load_config_file(mocker, default_conf)
     mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
-    mocker.patch('freqtrade.freqtradebot.persistence.init', MagicMock())
+    mocker.patch('freqtrade.freqtradebot.init_db', MagicMock())
 
-    args = ['-c', 'config.json.example']
+    args = ['trade', '-c', 'config.json.example']
 
     # Test Main + the KeyboardInterrupt exception
     with pytest.raises(SystemExit):
         main(args)
-    assert log_has('Using config: config.json.example ...', caplog.record_tuples)
-    assert log_has('Fatal exception!', caplog.record_tuples)
+    assert log_has('Using config: config.json.example ...', caplog)
+    assert log_has('Fatal exception!', caplog)
 
 
 def test_main_keyboard_interrupt(mocker, default_conf, caplog) -> None:
@@ -70,15 +82,16 @@ def test_main_keyboard_interrupt(mocker, default_conf, caplog) -> None:
     mocker.patch('freqtrade.worker.Worker._worker', MagicMock(side_effect=KeyboardInterrupt))
     patched_configuration_load_config_file(mocker, default_conf)
     mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
-    mocker.patch('freqtrade.freqtradebot.persistence.init', MagicMock())
+    mocker.patch('freqtrade.wallets.Wallets.update', MagicMock())
+    mocker.patch('freqtrade.freqtradebot.init_db', MagicMock())
 
-    args = ['-c', 'config.json.example']
+    args = ['trade', '-c', 'config.json.example']
 
     # Test Main + the KeyboardInterrupt exception
     with pytest.raises(SystemExit):
         main(args)
-    assert log_has('Using config: config.json.example ...', caplog.record_tuples)
-    assert log_has('SIGINT received, aborting ...', caplog.record_tuples)
+    assert log_has('Using config: config.json.example ...', caplog)
+    assert log_has('SIGINT received, aborting ...', caplog)
 
 
 def test_main_operational_exception(mocker, default_conf, caplog) -> None:
@@ -86,42 +99,70 @@ def test_main_operational_exception(mocker, default_conf, caplog) -> None:
     mocker.patch('freqtrade.freqtradebot.FreqtradeBot.cleanup', MagicMock())
     mocker.patch(
         'freqtrade.worker.Worker._worker',
-        MagicMock(side_effect=OperationalException('Oh snap!'))
+        MagicMock(side_effect=FreqtradeException('Oh snap!'))
     )
     patched_configuration_load_config_file(mocker, default_conf)
+    mocker.patch('freqtrade.wallets.Wallets.update', MagicMock())
     mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
-    mocker.patch('freqtrade.freqtradebot.persistence.init', MagicMock())
+    mocker.patch('freqtrade.freqtradebot.init_db', MagicMock())
 
-    args = ['-c', 'config.json.example']
+    args = ['trade', '-c', 'config.json.example']
 
     # Test Main + the KeyboardInterrupt exception
     with pytest.raises(SystemExit):
         main(args)
-    assert log_has('Using config: config.json.example ...', caplog.record_tuples)
-    assert log_has('Oh snap!', caplog.record_tuples)
+    assert log_has('Using config: config.json.example ...', caplog)
+    assert log_has('Oh snap!', caplog)
 
 
-def test_main_reload_conf(mocker, default_conf, caplog) -> None:
+def test_main_operational_exception1(mocker, default_conf, caplog) -> None:
+    patch_exchange(mocker)
+    mocker.patch(
+        'freqtrade.commands.list_commands.available_exchanges',
+        MagicMock(side_effect=ValueError('Oh snap!'))
+    )
+    patched_configuration_load_config_file(mocker, default_conf)
+
+    args = ['list-exchanges']
+
+    # Test Main + the KeyboardInterrupt exception
+    with pytest.raises(SystemExit):
+        main(args)
+
+    assert log_has('Fatal exception!', caplog)
+    assert not log_has_re(r'SIGINT.*', caplog)
+    mocker.patch(
+        'freqtrade.commands.list_commands.available_exchanges',
+        MagicMock(side_effect=KeyboardInterrupt)
+    )
+    with pytest.raises(SystemExit):
+        main(args)
+
+    assert log_has_re(r'SIGINT.*', caplog)
+
+
+def test_main_reload_config(mocker, default_conf, caplog) -> None:
     patch_exchange(mocker)
     mocker.patch('freqtrade.freqtradebot.FreqtradeBot.cleanup', MagicMock())
     # Simulate Running, reload, running workflow
     worker_mock = MagicMock(side_effect=[State.RUNNING,
-                                         State.RELOAD_CONF,
+                                         State.RELOAD_CONFIG,
                                          State.RUNNING,
                                          OperationalException("Oh snap!")])
     mocker.patch('freqtrade.worker.Worker._worker', worker_mock)
     patched_configuration_load_config_file(mocker, default_conf)
-    reconfigure_mock = mocker.patch('freqtrade.main.Worker._reconfigure', MagicMock())
+    mocker.patch('freqtrade.wallets.Wallets.update', MagicMock())
+    reconfigure_mock = mocker.patch('freqtrade.worker.Worker._reconfigure', MagicMock())
 
     mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
-    mocker.patch('freqtrade.freqtradebot.persistence.init', MagicMock())
+    mocker.patch('freqtrade.freqtradebot.init_db', MagicMock())
 
-    args = Arguments(['-c', 'config.json.example'], '').get_parsed_arg()
+    args = Arguments(['trade', '-c', 'config.json.example']).get_parsed_arg()
     worker = Worker(args=args, config=default_conf)
     with pytest.raises(SystemExit):
-        main(['-c', 'config.json.example'])
+        main(['trade', '-c', 'config.json.example'])
 
-    assert log_has('Using config: config.json.example ...', caplog.record_tuples)
+    assert log_has('Using config: config.json.example ...', caplog)
     assert worker_mock.call_count == 4
     assert reconfigure_mock.call_count == 1
     assert isinstance(worker.freqtrade, FreqtradeBot)
@@ -134,11 +175,12 @@ def test_reconfigure(mocker, default_conf) -> None:
         'freqtrade.worker.Worker._worker',
         MagicMock(side_effect=OperationalException('Oh snap!'))
     )
+    mocker.patch('freqtrade.wallets.Wallets.update', MagicMock())
     patched_configuration_load_config_file(mocker, default_conf)
     mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
-    mocker.patch('freqtrade.freqtradebot.persistence.init', MagicMock())
+    mocker.patch('freqtrade.freqtradebot.init_db', MagicMock())
 
-    args = Arguments(['-c', 'config.json.example'], '').get_parsed_arg()
+    args = Arguments(['trade', '-c', 'config.json.example']).get_parsed_arg()
     worker = Worker(args=args, config=default_conf)
     freqtrade = worker.freqtrade
 
diff --git a/tests/test_misc.py b/tests/test_misc.py
new file mode 100644
index 000000000..6dcd9fbe5
--- /dev/null
+++ b/tests/test_misc.py
@@ -0,0 +1,177 @@
+# pragma pylint: disable=missing-docstring,C0103
+
+import datetime
+from pathlib import Path
+from unittest.mock import MagicMock
+
+import pytest
+
+from freqtrade.data.converter import ohlcv_to_dataframe
+from freqtrade.misc import (datesarray_to_datetimearray, file_dump_json, file_load_json,
+                            format_ms_time, pair_to_filename, plural, render_template,
+                            render_template_with_fallback, safe_value_fallback,
+                            safe_value_fallback2, shorten_date)
+
+
+def test_shorten_date() -> None:
+    str_data = '1 day, 2 hours, 3 minutes, 4 seconds ago'
+    str_shorten_data = '1 d, 2 h, 3 min, 4 sec ago'
+    assert shorten_date(str_data) == str_shorten_data
+
+
+def test_datesarray_to_datetimearray(ohlcv_history_list):
+    dataframes = ohlcv_to_dataframe(ohlcv_history_list, "5m", pair="UNITTEST/BTC",
+                                    fill_missing=True)
+    dates = datesarray_to_datetimearray(dataframes['date'])
+
+    assert isinstance(dates[0], datetime.datetime)
+    assert dates[0].year == 2017
+    assert dates[0].month == 11
+    assert dates[0].day == 26
+    assert dates[0].hour == 8
+    assert dates[0].minute == 50
+
+    date_len = len(dates)
+    assert date_len == 2
+
+
+def test_file_dump_json(mocker) -> None:
+    file_open = mocker.patch('freqtrade.misc.open', MagicMock())
+    json_dump = mocker.patch('rapidjson.dump', MagicMock())
+    file_dump_json(Path('somefile'), [1, 2, 3])
+    assert file_open.call_count == 1
+    assert json_dump.call_count == 1
+    file_open = mocker.patch('freqtrade.misc.gzip.open', MagicMock())
+    json_dump = mocker.patch('rapidjson.dump', MagicMock())
+    file_dump_json(Path('somefile'), [1, 2, 3], True)
+    assert file_open.call_count == 1
+    assert json_dump.call_count == 1
+
+
+def test_file_load_json(mocker, testdatadir) -> None:
+
+    # 7m .json does not exist
+    ret = file_load_json(testdatadir / 'UNITTEST_BTC-7m.json')
+    assert not ret
+    # 1m json exists (but no .gz exists)
+    ret = file_load_json(testdatadir / 'UNITTEST_BTC-1m.json')
+    assert ret
+    # 8 .json is empty and will fail if it's loaded. .json.gz is a copy of 1.json
+    ret = file_load_json(testdatadir / 'UNITTEST_BTC-8m.json')
+    assert ret
+
+
+@pytest.mark.parametrize("pair,expected_result", [
+    ("ETH/BTC", 'ETH_BTC'),
+    ("Fabric Token/ETH", 'Fabric_Token_ETH'),
+    ("ETHH20", 'ETHH20'),
+    (".XBTBON2H", '_XBTBON2H'),
+    ("ETHUSD.d", 'ETHUSD_d'),
+    ("ADA-0327", 'ADA_0327'),
+    ("BTC-USD-200110", 'BTC_USD_200110'),
+    ("F-AKRO/USDT", 'F_AKRO_USDT'),
+    ("LC+/ETH", 'LC__ETH'),
+    ("CMT@18/ETH", 'CMT_18_ETH'),
+    ("LBTC:1022/SAI", 'LBTC_1022_SAI'),
+    ("$PAC/BTC", '_PAC_BTC'),
+    ("ACC_OLD/BTC", 'ACC_OLD_BTC'),
+])
+def test_pair_to_filename(pair, expected_result):
+    pair_s = pair_to_filename(pair)
+    assert pair_s == expected_result
+
+
+def test_format_ms_time() -> None:
+    # Date 2018-04-10 18:02:01
+    date_in_epoch_ms = 1523383321000
+    date = format_ms_time(date_in_epoch_ms)
+    assert type(date) is str
+    res = datetime.datetime(2018, 4, 10, 18, 2, 1, tzinfo=datetime.timezone.utc)
+    assert date == res.astimezone(None).strftime('%Y-%m-%dT%H:%M:%S')
+    res = datetime.datetime(2017, 12, 13, 8, 2, 1, tzinfo=datetime.timezone.utc)
+    # Date 2017-12-13 08:02:01
+    date_in_epoch_ms = 1513152121000
+    assert format_ms_time(date_in_epoch_ms) == res.astimezone(None).strftime('%Y-%m-%dT%H:%M:%S')
+
+
+def test_safe_value_fallback():
+    dict1 = {'keya': None, 'keyb': 2, 'keyc': 5, 'keyd': None}
+    assert safe_value_fallback(dict1, 'keya', 'keyb') == 2
+    assert safe_value_fallback(dict1, 'keyb', 'keya') == 2
+
+    assert safe_value_fallback(dict1, 'keyb', 'keyc') == 2
+    assert safe_value_fallback(dict1, 'keya', 'keyc') == 5
+
+    assert safe_value_fallback(dict1, 'keyc', 'keyb') == 5
+
+    assert safe_value_fallback(dict1, 'keya', 'keyd') is None
+
+    assert safe_value_fallback(dict1, 'keyNo', 'keyNo') is None
+    assert safe_value_fallback(dict1, 'keyNo', 'keyNo', 55) == 55
+
+
+def test_safe_value_fallback2():
+    dict1 = {'keya': None, 'keyb': 2, 'keyc': 5, 'keyd': None}
+    dict2 = {'keya': 20, 'keyb': None, 'keyc': 6, 'keyd': None}
+    assert safe_value_fallback2(dict1, dict2, 'keya', 'keya') == 20
+    assert safe_value_fallback2(dict2, dict1, 'keya', 'keya') == 20
+
+    assert safe_value_fallback2(dict1, dict2, 'keyb', 'keyb') == 2
+    assert safe_value_fallback2(dict2, dict1, 'keyb', 'keyb') == 2
+
+    assert safe_value_fallback2(dict1, dict2, 'keyc', 'keyc') == 5
+    assert safe_value_fallback2(dict2, dict1, 'keyc', 'keyc') == 6
+
+    assert safe_value_fallback2(dict1, dict2, 'keyd', 'keyd') is None
+    assert safe_value_fallback2(dict2, dict1, 'keyd', 'keyd') is None
+    assert safe_value_fallback2(dict2, dict1, 'keyd', 'keyd', 1234) == 1234
+
+    assert safe_value_fallback2(dict1, dict2, 'keyNo', 'keyNo') is None
+    assert safe_value_fallback2(dict2, dict1, 'keyNo', 'keyNo') is None
+    assert safe_value_fallback2(dict2, dict1, 'keyNo', 'keyNo', 1234) == 1234
+
+
+def test_plural() -> None:
+    assert plural(0, "page") == "pages"
+    assert plural(0.0, "page") == "pages"
+    assert plural(1, "page") == "page"
+    assert plural(1.0, "page") == "page"
+    assert plural(2, "page") == "pages"
+    assert plural(2.0, "page") == "pages"
+    assert plural(-1, "page") == "page"
+    assert plural(-1.0, "page") == "page"
+    assert plural(-2, "page") == "pages"
+    assert plural(-2.0, "page") == "pages"
+    assert plural(0.5, "page") == "pages"
+    assert plural(1.5, "page") == "pages"
+    assert plural(-0.5, "page") == "pages"
+    assert plural(-1.5, "page") == "pages"
+
+    assert plural(0, "ox", "oxen") == "oxen"
+    assert plural(0.0, "ox", "oxen") == "oxen"
+    assert plural(1, "ox", "oxen") == "ox"
+    assert plural(1.0, "ox", "oxen") == "ox"
+    assert plural(2, "ox", "oxen") == "oxen"
+    assert plural(2.0, "ox", "oxen") == "oxen"
+    assert plural(-1, "ox", "oxen") == "ox"
+    assert plural(-1.0, "ox", "oxen") == "ox"
+    assert plural(-2, "ox", "oxen") == "oxen"
+    assert plural(-2.0, "ox", "oxen") == "oxen"
+    assert plural(0.5, "ox", "oxen") == "oxen"
+    assert plural(1.5, "ox", "oxen") == "oxen"
+    assert plural(-0.5, "ox", "oxen") == "oxen"
+    assert plural(-1.5, "ox", "oxen") == "oxen"
+
+
+def test_render_template_fallback(mocker):
+    from jinja2.exceptions import TemplateNotFound
+    with pytest.raises(TemplateNotFound):
+        val = render_template(
+            templatefile='subtemplates/indicators_does-not-exist.j2',)
+
+    val = render_template_with_fallback(
+        templatefile='subtemplates/indicators_does-not-exist.j2',
+        templatefallbackfile='subtemplates/indicators_minimal.j2',
+    )
+    assert isinstance(val, str)
+    assert 'if self.dp' in val
diff --git a/freqtrade/tests/test_persistence.py b/tests/test_persistence.py
similarity index 60%
rename from freqtrade/tests/test_persistence.py
rename to tests/test_persistence.py
index 32425ef7b..41b99b34f 100644
--- a/freqtrade/tests/test_persistence.py
+++ b/tests/test_persistence.py
@@ -6,68 +6,25 @@ import arrow
 import pytest
 from sqlalchemy import create_engine
 
-from freqtrade import OperationalException, constants
-from freqtrade.persistence import Trade, clean_dry_run_db, init
-from freqtrade.tests.conftest import log_has
-
-
-def create_mock_trades(fee):
-    """
-    Create some fake trades ...
-    """
-    # Simulate dry_run entries
-    trade = Trade(
-        pair='ETH/BTC',
-        stake_amount=0.001,
-        amount=123.0,
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-        open_rate=0.123,
-        exchange='bittrex',
-        open_order_id='dry_run_buy_12345'
-    )
-    Trade.session.add(trade)
-
-    trade = Trade(
-        pair='ETC/BTC',
-        stake_amount=0.001,
-        amount=123.0,
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-        open_rate=0.123,
-        exchange='bittrex',
-        is_open=False,
-        open_order_id='dry_run_sell_12345'
-    )
-    Trade.session.add(trade)
-
-    # Simulate prod entry
-    trade = Trade(
-        pair='ETC/BTC',
-        stake_amount=0.001,
-        amount=123.0,
-        fee_open=fee.return_value,
-        fee_close=fee.return_value,
-        open_rate=0.123,
-        exchange='bittrex',
-        open_order_id='prod_buy_12345'
-    )
-    Trade.session.add(trade)
+from freqtrade import constants
+from freqtrade.exceptions import DependencyException, OperationalException
+from freqtrade.persistence import Order, Trade, clean_dry_run_db, init_db
+from tests.conftest import create_mock_trades, log_has, log_has_re
 
 
 def test_init_create_session(default_conf):
     # Check if init create a session
-    init(default_conf['db_url'], default_conf['dry_run'])
+    init_db(default_conf['db_url'], default_conf['dry_run'])
     assert hasattr(Trade, 'session')
-    assert 'Session' in type(Trade.session).__name__
+    assert 'scoped_session' in type(Trade.session).__name__
 
 
 def test_init_custom_db_url(default_conf, mocker):
     # Update path to a value other than default, but still in-memory
     default_conf.update({'db_url': 'sqlite:///tmp/freqtrade2_test.sqlite'})
-    create_engine_mock = mocker.patch('freqtrade.persistence.create_engine', MagicMock())
+    create_engine_mock = mocker.patch('freqtrade.persistence.models.create_engine', MagicMock())
 
-    init(default_conf['db_url'], default_conf['dry_run'])
+    init_db(default_conf['db_url'], default_conf['dry_run'])
     assert create_engine_mock.call_count == 1
     assert create_engine_mock.mock_calls[0][1][0] == 'sqlite:///tmp/freqtrade2_test.sqlite'
 
@@ -76,16 +33,16 @@ def test_init_invalid_db_url(default_conf):
     # Update path to a value other than default, but still in-memory
     default_conf.update({'db_url': 'unknown:///some.url'})
     with pytest.raises(OperationalException, match=r'.*no valid database URL*'):
-        init(default_conf['db_url'], default_conf['dry_run'])
+        init_db(default_conf['db_url'], default_conf['dry_run'])
 
 
 def test_init_prod_db(default_conf, mocker):
     default_conf.update({'dry_run': False})
     default_conf.update({'db_url': constants.DEFAULT_DB_PROD_URL})
 
-    create_engine_mock = mocker.patch('freqtrade.persistence.create_engine', MagicMock())
+    create_engine_mock = mocker.patch('freqtrade.persistence.models.create_engine', MagicMock())
 
-    init(default_conf['db_url'], default_conf['dry_run'])
+    init_db(default_conf['db_url'], default_conf['dry_run'])
     assert create_engine_mock.call_count == 1
     assert create_engine_mock.mock_calls[0][1][0] == 'sqlite:///tradesv3.sqlite'
 
@@ -94,11 +51,11 @@ def test_init_dryrun_db(default_conf, mocker):
     default_conf.update({'dry_run': True})
     default_conf.update({'db_url': constants.DEFAULT_DB_DRYRUN_URL})
 
-    create_engine_mock = mocker.patch('freqtrade.persistence.create_engine', MagicMock())
+    create_engine_mock = mocker.patch('freqtrade.persistence.models.create_engine', MagicMock())
 
-    init(default_conf['db_url'], default_conf['dry_run'])
+    init_db(default_conf['db_url'], default_conf['dry_run'])
     assert create_engine_mock.call_count == 1
-    assert create_engine_mock.mock_calls[0][1][0] == 'sqlite://'
+    assert create_engine_mock.mock_calls[0][1][0] == 'sqlite:///tradesv3.dryrun.sqlite'
 
 
 @pytest.mark.usefixtures("init_persistence")
@@ -134,12 +91,15 @@ def test_update_with_bittrex(limit_buy_order, limit_sell_order, fee, caplog):
         id=2,
         pair='ETH/BTC',
         stake_amount=0.001,
+        open_rate=0.01,
+        amount=5,
+        is_open=True,
+        open_date=arrow.utcnow().datetime,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         exchange='bittrex',
     )
     assert trade.open_order_id is None
-    assert trade.open_rate is None
     assert trade.close_profit is None
     assert trade.close_date is None
 
@@ -149,9 +109,9 @@ def test_update_with_bittrex(limit_buy_order, limit_sell_order, fee, caplog):
     assert trade.open_rate == 0.00001099
     assert trade.close_profit is None
     assert trade.close_date is None
-    assert log_has("LIMIT_BUY has been fulfilled for Trade(id=2, "
-                   "pair=ETH/BTC, amount=90.99181073, open_rate=0.00001099, open_since=closed).",
-                   caplog.record_tuples)
+    assert log_has_re(r"LIMIT_BUY has been fulfilled for Trade\(id=2, "
+                      r"pair=ETH/BTC, amount=90.99181073, open_rate=0.00001099, open_since=.*\).",
+                      caplog)
 
     caplog.clear()
     trade.open_order_id = 'something'
@@ -160,9 +120,9 @@ def test_update_with_bittrex(limit_buy_order, limit_sell_order, fee, caplog):
     assert trade.close_rate == 0.00001173
     assert trade.close_profit == 0.06201058
     assert trade.close_date is not None
-    assert log_has("LIMIT_SELL has been fulfilled for Trade(id=2, "
-                   "pair=ETH/BTC, amount=90.99181073, open_rate=0.00001099, open_since=closed).",
-                   caplog.record_tuples)
+    assert log_has_re(r"LIMIT_SELL has been fulfilled for Trade\(id=2, "
+                      r"pair=ETH/BTC, amount=90.99181073, open_rate=0.00001099, open_since=.*\).",
+                      caplog)
 
 
 @pytest.mark.usefixtures("init_persistence")
@@ -171,8 +131,12 @@ def test_update_market_order(market_buy_order, market_sell_order, fee, caplog):
         id=1,
         pair='ETH/BTC',
         stake_amount=0.001,
+        amount=5,
+        open_rate=0.01,
+        is_open=True,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
+        open_date=arrow.utcnow().datetime,
         exchange='bittrex',
     )
 
@@ -182,20 +146,21 @@ def test_update_market_order(market_buy_order, market_sell_order, fee, caplog):
     assert trade.open_rate == 0.00004099
     assert trade.close_profit is None
     assert trade.close_date is None
-    assert log_has("MARKET_BUY has been fulfilled for Trade(id=1, "
-                   "pair=ETH/BTC, amount=91.99181073, open_rate=0.00004099, open_since=closed).",
-                   caplog.record_tuples)
+    assert log_has_re(r"MARKET_BUY has been fulfilled for Trade\(id=1, "
+                      r"pair=ETH/BTC, amount=91.99181073, open_rate=0.00004099, open_since=.*\).",
+                      caplog)
 
     caplog.clear()
+    trade.is_open = True
     trade.open_order_id = 'something'
     trade.update(market_sell_order)
     assert trade.open_order_id is None
     assert trade.close_rate == 0.00004173
     assert trade.close_profit == 0.01297561
     assert trade.close_date is not None
-    assert log_has("MARKET_SELL has been fulfilled for Trade(id=1, "
-                   "pair=ETH/BTC, amount=91.99181073, open_rate=0.00004099, open_since=closed).",
-                   caplog.record_tuples)
+    assert log_has_re(r"MARKET_SELL has been fulfilled for Trade\(id=1, "
+                      r"pair=ETH/BTC, amount=91.99181073, open_rate=0.00004099, open_since=.*\).",
+                      caplog)
 
 
 @pytest.mark.usefixtures("init_persistence")
@@ -203,6 +168,8 @@ def test_calc_open_close_trade_price(limit_buy_order, limit_sell_order, fee):
     trade = Trade(
         pair='ETH/BTC',
         stake_amount=0.001,
+        open_rate=0.01,
+        amount=5,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         exchange='bittrex',
@@ -210,7 +177,7 @@ def test_calc_open_close_trade_price(limit_buy_order, limit_sell_order, fee):
 
     trade.open_order_id = 'something'
     trade.update(limit_buy_order)
-    assert trade.calc_open_trade_price() == 0.0010024999999225068
+    assert trade._calc_open_trade_price() == 0.0010024999999225068
 
     trade.update(limit_sell_order)
     assert trade.calc_close_trade_price() == 0.0010646656050132426
@@ -219,7 +186,37 @@ def test_calc_open_close_trade_price(limit_buy_order, limit_sell_order, fee):
     assert trade.calc_profit() == 0.00006217
 
     # Profit in percent
-    assert trade.calc_profit_percent() == 0.06201058
+    assert trade.calc_profit_ratio() == 0.06201058
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_trade_close(limit_buy_order, limit_sell_order, fee):
+    trade = Trade(
+        pair='ETH/BTC',
+        stake_amount=0.001,
+        open_rate=0.01,
+        amount=5,
+        is_open=True,
+        fee_open=fee.return_value,
+        fee_close=fee.return_value,
+        open_date=arrow.Arrow(2020, 2, 1, 15, 5, 1).datetime,
+        exchange='bittrex',
+    )
+    assert trade.close_profit is None
+    assert trade.close_date is None
+    assert trade.is_open is True
+    trade.close(0.02)
+    assert trade.is_open is False
+    assert trade.close_profit == 0.99002494
+    assert trade.close_date is not None
+
+    new_date = arrow.Arrow(2020, 2, 2, 15, 6, 1).datetime,
+    assert trade.close_date != new_date
+    # Close should NOT update close_date if the trade has been closed already
+    assert trade.is_open is False
+    trade.close_date = new_date
+    trade.close(0.02)
+    assert trade.close_date == new_date
 
 
 @pytest.mark.usefixtures("init_persistence")
@@ -227,6 +224,8 @@ def test_calc_close_trade_price_exception(limit_buy_order, fee):
     trade = Trade(
         pair='ETH/BTC',
         stake_amount=0.001,
+        open_rate=0.1,
+        amount=5,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         exchange='bittrex',
@@ -242,13 +241,14 @@ def test_update_open_order(limit_buy_order):
     trade = Trade(
         pair='ETH/BTC',
         stake_amount=1.00,
+        open_rate=0.01,
+        amount=5,
         fee_open=0.1,
         fee_close=0.1,
         exchange='bittrex',
     )
 
     assert trade.open_order_id is None
-    assert trade.open_rate is None
     assert trade.close_profit is None
     assert trade.close_date is None
 
@@ -256,7 +256,6 @@ def test_update_open_order(limit_buy_order):
     trade.update(limit_buy_order)
 
     assert trade.open_order_id is None
-    assert trade.open_rate is None
     assert trade.close_profit is None
     assert trade.close_date is None
 
@@ -266,6 +265,8 @@ def test_update_invalid_order(limit_buy_order):
     trade = Trade(
         pair='ETH/BTC',
         stake_amount=1.00,
+        amount=5,
+        open_rate=0.001,
         fee_open=0.1,
         fee_close=0.1,
         exchange='bittrex',
@@ -280,6 +281,8 @@ def test_calc_open_trade_price(limit_buy_order, fee):
     trade = Trade(
         pair='ETH/BTC',
         stake_amount=0.001,
+        amount=5,
+        open_rate=0.00001099,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         exchange='bittrex',
@@ -288,10 +291,10 @@ def test_calc_open_trade_price(limit_buy_order, fee):
     trade.update(limit_buy_order)  # Buy @ 0.00001099
 
     # Get the open rate price with the standard fee rate
-    assert trade.calc_open_trade_price() == 0.0010024999999225068
-
+    assert trade._calc_open_trade_price() == 0.0010024999999225068
+    trade.fee_open = 0.003
     # Get the open rate price with a custom fee rate
-    assert trade.calc_open_trade_price(fee=0.003) == 0.001002999999922468
+    assert trade._calc_open_trade_price() == 0.001002999999922468
 
 
 @pytest.mark.usefixtures("init_persistence")
@@ -299,6 +302,8 @@ def test_calc_close_trade_price(limit_buy_order, limit_sell_order, fee):
     trade = Trade(
         pair='ETH/BTC',
         stake_amount=0.001,
+        amount=5,
+        open_rate=0.00001099,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         exchange='bittrex',
@@ -322,11 +327,13 @@ def test_calc_profit(limit_buy_order, limit_sell_order, fee):
     trade = Trade(
         pair='ETH/BTC',
         stake_amount=0.001,
+        amount=5,
+        open_rate=0.00001099,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         exchange='bittrex',
     )
-    trade.open_order_id = 'profit_percent'
+    trade.open_order_id = 'something'
     trade.update(limit_buy_order)  # Buy @ 0.00001099
 
     # Custom closing rate and regular fee rate
@@ -350,29 +357,31 @@ def test_calc_profit(limit_buy_order, limit_sell_order, fee):
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_calc_profit_percent(limit_buy_order, limit_sell_order, fee):
+def test_calc_profit_ratio(limit_buy_order, limit_sell_order, fee):
     trade = Trade(
         pair='ETH/BTC',
         stake_amount=0.001,
+        amount=5,
+        open_rate=0.00001099,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         exchange='bittrex',
     )
-    trade.open_order_id = 'profit_percent'
+    trade.open_order_id = 'something'
     trade.update(limit_buy_order)  # Buy @ 0.00001099
 
     # Get percent of profit with a custom rate (Higher than open rate)
-    assert trade.calc_profit_percent(rate=0.00001234) == 0.11723875
+    assert trade.calc_profit_ratio(rate=0.00001234) == 0.11723875
 
     # Get percent of profit with a custom rate (Lower than open rate)
-    assert trade.calc_profit_percent(rate=0.00000123) == -0.88863828
+    assert trade.calc_profit_ratio(rate=0.00000123) == -0.88863828
 
     # Test when we apply a Sell order. Sell higher than open rate @ 0.00001173
     trade.update(limit_sell_order)
-    assert trade.calc_profit_percent() == 0.06201058
+    assert trade.calc_profit_ratio() == 0.06201058
 
     # Test with a custom fee rate on the close trade
-    assert trade.calc_profit_percent(fee=0.003) == 0.06147824
+    assert trade.calc_profit_ratio(fee=0.003) == 0.06147824
 
 
 @pytest.mark.usefixtures("init_persistence")
@@ -447,23 +456,33 @@ def test_migrate_old(mocker, default_conf, fee):
                                 PRIMARY KEY (id),
                                 CHECK (is_open IN (0, 1))
                                 );"""
-    insert_table_old = """INSERT INTO trades (exchange, pair, is_open, fee,
+    insert_table_old = """INSERT INTO trades (exchange, pair, is_open, open_order_id, fee,
                           open_rate, stake_amount, amount, open_date)
-                          VALUES ('BITTREX', 'BTC_ETC', 1, {fee},
+                          VALUES ('BITTREX', 'BTC_ETC', 1, '123123', {fee},
                           0.00258580, {stake}, {amount},
                           '2017-11-28 12:44:24.000000')
                           """.format(fee=fee.return_value,
                                      stake=default_conf.get("stake_amount"),
                                      amount=amount
                                      )
+    insert_table_old2 = """INSERT INTO trades (exchange, pair, is_open, fee,
+                          open_rate, close_rate, stake_amount, amount, open_date)
+                          VALUES ('BITTREX', 'BTC_ETC', 0, {fee},
+                          0.00258580, 0.00268580, {stake}, {amount},
+                          '2017-11-28 12:44:24.000000')
+                          """.format(fee=fee.return_value,
+                                     stake=default_conf.get("stake_amount"),
+                                     amount=amount
+                                     )
     engine = create_engine('sqlite://')
-    mocker.patch('freqtrade.persistence.create_engine', lambda *args, **kwargs: engine)
+    mocker.patch('freqtrade.persistence.models.create_engine', lambda *args, **kwargs: engine)
 
     # Create table using the old format
     engine.execute(create_table_old)
     engine.execute(insert_table_old)
+    engine.execute(insert_table_old2)
     # Run init to test migration
-    init(default_conf['db_url'], default_conf['dry_run'])
+    init_db(default_conf['db_url'], default_conf['dry_run'])
 
     assert len(Trade.query.filter(Trade.id == 1).all()) == 1
     trade = Trade.query.filter(Trade.id == 1).first()
@@ -473,12 +492,35 @@ def test_migrate_old(mocker, default_conf, fee):
     assert trade.close_rate_requested is None
     assert trade.is_open == 1
     assert trade.amount == amount
+    assert trade.amount_requested == amount
     assert trade.stake_amount == default_conf.get("stake_amount")
     assert trade.pair == "ETC/BTC"
     assert trade.exchange == "bittrex"
     assert trade.max_rate == 0.0
     assert trade.stop_loss == 0.0
     assert trade.initial_stop_loss == 0.0
+    assert trade.open_trade_price == trade._calc_open_trade_price()
+    assert trade.close_profit_abs is None
+    assert trade.fee_open_cost is None
+    assert trade.fee_open_currency is None
+    assert trade.fee_close_cost is None
+    assert trade.fee_close_currency is None
+    assert trade.timeframe is None
+
+    trade = Trade.query.filter(Trade.id == 2).first()
+    assert trade.close_rate is not None
+    assert trade.is_open == 0
+    assert trade.open_rate_requested is None
+    assert trade.close_rate_requested is None
+    assert trade.close_rate is not None
+    assert pytest.approx(trade.close_profit_abs) == trade.calc_profit()
+    assert trade.sell_order_status is None
+
+    # Should've created one order
+    assert len(Order.query.all()) == 1
+    order = Order.query.first()
+    assert order.order_id == '123123'
+    assert order.ft_order_side == 'buy'
 
 
 def test_migrate_new(mocker, default_conf, fee, caplog):
@@ -508,22 +550,25 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
                                 sell_reason VARCHAR,
                                 strategy VARCHAR,
                                 ticker_interval INTEGER,
+                                stoploss_order_id VARCHAR,
                                 PRIMARY KEY (id),
                                 CHECK (is_open IN (0, 1))
                                 );"""
     insert_table_old = """INSERT INTO trades (exchange, pair, is_open, fee,
                           open_rate, stake_amount, amount, open_date,
-                          stop_loss, initial_stop_loss, max_rate)
+                          stop_loss, initial_stop_loss, max_rate, ticker_interval,
+                          open_order_id, stoploss_order_id)
                           VALUES ('binance', 'ETC/BTC', 1, {fee},
                           0.00258580, {stake}, {amount},
                           '2019-11-28 12:44:24.000000',
-                          0.0, 0.0, 0.0)
+                          0.0, 0.0, 0.0, '5m',
+                          'buy_order', 'stop_order_id222')
                           """.format(fee=fee.return_value,
                                      stake=default_conf.get("stake_amount"),
                                      amount=amount
                                      )
     engine = create_engine('sqlite://')
-    mocker.patch('freqtrade.persistence.create_engine', lambda *args, **kwargs: engine)
+    mocker.patch('freqtrade.persistence.models.create_engine', lambda *args, **kwargs: engine)
 
     # Create table using the old format
     engine.execute(create_table_old)
@@ -536,7 +581,7 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
 
     engine.execute("create table trades_bak1 as select * from trades")
     # Run init to test migration
-    init(default_conf['db_url'], default_conf['dry_run'])
+    init_db(default_conf['db_url'], default_conf['dry_run'])
 
     assert len(Trade.query.filter(Trade.id == 1).all()) == 1
     trade = Trade.query.filter(Trade.id == 1).first()
@@ -546,6 +591,7 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
     assert trade.close_rate_requested is None
     assert trade.is_open == 1
     assert trade.amount == amount
+    assert trade.amount_requested == amount
     assert trade.stake_amount == default_conf.get("stake_amount")
     assert trade.pair == "ETC/BTC"
     assert trade.exchange == "binance"
@@ -555,13 +601,23 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
     assert trade.initial_stop_loss == 0.0
     assert trade.sell_reason is None
     assert trade.strategy is None
-    assert trade.ticker_interval is None
-    assert trade.stoploss_order_id is None
+    assert trade.timeframe == '5m'
+    assert trade.stoploss_order_id == 'stop_order_id222'
     assert trade.stoploss_last_update is None
-    assert log_has("trying trades_bak1", caplog.record_tuples)
-    assert log_has("trying trades_bak2", caplog.record_tuples)
-    assert log_has("Running database migration - backup available as trades_bak2",
-                   caplog.record_tuples)
+    assert log_has("trying trades_bak1", caplog)
+    assert log_has("trying trades_bak2", caplog)
+    assert log_has("Running database migration for trades - backup: trades_bak2", caplog)
+    assert trade.open_trade_price == trade._calc_open_trade_price()
+    assert trade.close_profit_abs is None
+
+    assert log_has("Moving open orders to Orders table.", caplog)
+    orders = Order.query.all()
+    assert len(orders) == 2
+    assert orders[0].order_id == 'buy_order'
+    assert orders[0].ft_order_side == 'buy'
+
+    assert orders[1].order_id == 'stop_order_id222'
+    assert orders[1].ft_order_side == 'stoploss'
 
 
 def test_migrate_mid_state(mocker, default_conf, fee, caplog):
@@ -598,14 +654,14 @@ def test_migrate_mid_state(mocker, default_conf, fee, caplog):
                                      amount=amount
                                      )
     engine = create_engine('sqlite://')
-    mocker.patch('freqtrade.persistence.create_engine', lambda *args, **kwargs: engine)
+    mocker.patch('freqtrade.persistence.models.create_engine', lambda *args, **kwargs: engine)
 
     # Create table using the old format
     engine.execute(create_table_old)
     engine.execute(insert_table_old)
 
     # Run init to test migration
-    init(default_conf['db_url'], default_conf['dry_run'])
+    init_db(default_conf['db_url'], default_conf['dry_run'])
 
     assert len(Trade.query.filter(Trade.id == 1).all()) == 1
     trade = Trade.query.filter(Trade.id == 1).first()
@@ -621,15 +677,16 @@ def test_migrate_mid_state(mocker, default_conf, fee, caplog):
     assert trade.max_rate == 0.0
     assert trade.stop_loss == 0.0
     assert trade.initial_stop_loss == 0.0
-    assert log_has("trying trades_bak0", caplog.record_tuples)
-    assert log_has("Running database migration - backup available as trades_bak0",
-                   caplog.record_tuples)
+    assert trade.open_trade_price == trade._calc_open_trade_price()
+    assert log_has("trying trades_bak0", caplog)
+    assert log_has("Running database migration for trades - backup: trades_bak0", caplog)
 
 
 def test_adjust_stop_loss(fee):
     trade = Trade(
         pair='ETH/BTC',
         stake_amount=0.001,
+        amount=5,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         exchange='bittrex',
@@ -681,6 +738,7 @@ def test_adjust_min_max_rates(fee):
     trade = Trade(
         pair='ETH/BTC',
         stake_amount=0.001,
+        amount=5,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         exchange='bittrex',
@@ -708,10 +766,10 @@ def test_adjust_min_max_rates(fee):
 
 
 @pytest.mark.usefixtures("init_persistence")
-def test_get_open(default_conf, fee):
+def test_get_open(fee):
 
     create_mock_trades(fee)
-    assert len(Trade.get_open_trades()) == 2
+    assert len(Trade.get_open_trades()) == 4
 
 
 @pytest.mark.usefixtures("init_persistence")
@@ -722,6 +780,7 @@ def test_to_json(default_conf, fee):
         pair='ETH/BTC',
         stake_amount=0.001,
         amount=123.0,
+        amount_requested=123.0,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         open_date=arrow.utcnow().shift(hours=-2).datetime,
@@ -731,28 +790,61 @@ def test_to_json(default_conf, fee):
     )
     result = trade.to_json()
     assert isinstance(result, dict)
-    print(result)
 
     assert result == {'trade_id': None,
                       'pair': 'ETH/BTC',
+                      'is_open': None,
                       'open_date_hum': '2 hours ago',
                       'open_date': trade.open_date.strftime("%Y-%m-%d %H:%M:%S"),
+                      'open_timestamp': int(trade.open_date.timestamp() * 1000),
+                      'open_order_id': 'dry_run_buy_12345',
                       'close_date_hum': None,
                       'close_date': None,
+                      'close_timestamp': None,
                       'open_rate': 0.123,
+                      'open_rate_requested': None,
+                      'open_trade_price': 15.1668225,
+                      'fee_close': 0.0025,
+                      'fee_close_cost': None,
+                      'fee_close_currency': None,
+                      'fee_open': 0.0025,
+                      'fee_open_cost': None,
+                      'fee_open_currency': None,
                       'close_rate': None,
+                      'close_rate_requested': None,
                       'amount': 123.0,
+                      'amount_requested': 123.0,
                       'stake_amount': 0.001,
-                      'stop_loss': None,
+                      'close_profit': None,
+                      'close_profit_pct': None,
+                      'close_profit_abs': None,
+                      'profit_ratio': None,
+                      'profit_pct': None,
+                      'profit_abs': None,
+                      'sell_reason': None,
+                      'sell_order_status': None,
+                      'stop_loss_abs': None,
+                      'stop_loss_ratio': None,
                       'stop_loss_pct': None,
-                      'initial_stop_loss': None,
-                      'initial_stop_loss_pct': None}
+                      'stoploss_order_id': None,
+                      'stoploss_last_update': None,
+                      'stoploss_last_update_timestamp': None,
+                      'initial_stop_loss_abs': None,
+                      'initial_stop_loss_pct': None,
+                      'initial_stop_loss_ratio': None,
+                      'min_rate': None,
+                      'max_rate': None,
+                      'strategy': None,
+                      'timeframe': None,
+                      'exchange': 'bittrex',
+                      }
 
     # Simulate dry_run entries
     trade = Trade(
         pair='XRP/BTC',
         stake_amount=0.001,
         amount=100.0,
+        amount_requested=101.0,
         fee_open=fee.return_value,
         fee_close=fee.return_value,
         open_date=arrow.utcnow().shift(hours=-2).datetime,
@@ -768,20 +860,53 @@ def test_to_json(default_conf, fee):
                       'pair': 'XRP/BTC',
                       'open_date_hum': '2 hours ago',
                       'open_date': trade.open_date.strftime("%Y-%m-%d %H:%M:%S"),
+                      'open_timestamp': int(trade.open_date.timestamp() * 1000),
                       'close_date_hum': 'an hour ago',
                       'close_date': trade.close_date.strftime("%Y-%m-%d %H:%M:%S"),
+                      'close_timestamp': int(trade.close_date.timestamp() * 1000),
                       'open_rate': 0.123,
                       'close_rate': 0.125,
                       'amount': 100.0,
+                      'amount_requested': 101.0,
                       'stake_amount': 0.001,
-                      'stop_loss': None,
+                      'stop_loss_abs': None,
                       'stop_loss_pct': None,
-                      'initial_stop_loss': None,
-                      'initial_stop_loss_pct': None}
+                      'stop_loss_ratio': None,
+                      'stoploss_order_id': None,
+                      'stoploss_last_update': None,
+                      'stoploss_last_update_timestamp': None,
+                      'initial_stop_loss_abs': None,
+                      'initial_stop_loss_pct': None,
+                      'initial_stop_loss_ratio': None,
+                      'close_profit': None,
+                      'close_profit_pct': None,
+                      'close_profit_abs': None,
+                      'profit_ratio': None,
+                      'profit_pct': None,
+                      'profit_abs': None,
+                      'close_rate_requested': None,
+                      'fee_close': 0.0025,
+                      'fee_close_cost': None,
+                      'fee_close_currency': None,
+                      'fee_open': 0.0025,
+                      'fee_open_cost': None,
+                      'fee_open_currency': None,
+                      'is_open': None,
+                      'max_rate': None,
+                      'min_rate': None,
+                      'open_order_id': None,
+                      'open_rate_requested': None,
+                      'open_trade_price': 12.33075,
+                      'sell_reason': None,
+                      'sell_order_status': None,
+                      'strategy': None,
+                      'timeframe': None,
+                      'exchange': 'bittrex',
+                      }
 
 
 def test_stoploss_reinitialization(default_conf, fee):
-    init(default_conf['db_url'])
+    init_db(default_conf['db_url'])
     trade = Trade(
         pair='ETH/BTC',
         stake_amount=0.001,
@@ -838,3 +963,200 @@ def test_stoploss_reinitialization(default_conf, fee):
     assert trade_adj.stop_loss_pct == -0.04
     assert trade_adj.initial_stop_loss == 0.96
     assert trade_adj.initial_stop_loss_pct == -0.04
+
+
+def test_update_fee(fee):
+    trade = Trade(
+        pair='ETH/BTC',
+        stake_amount=0.001,
+        fee_open=fee.return_value,
+        open_date=arrow.utcnow().shift(hours=-2).datetime,
+        amount=10,
+        fee_close=fee.return_value,
+        exchange='bittrex',
+        open_rate=1,
+        max_rate=1,
+    )
+    fee_cost = 0.15
+    fee_currency = 'BTC'
+    fee_rate = 0.0075
+    assert trade.fee_open_currency is None
+    assert not trade.fee_updated('buy')
+    assert not trade.fee_updated('sell')
+
+    trade.update_fee(fee_cost, fee_currency, fee_rate, 'buy')
+    assert trade.fee_updated('buy')
+    assert not trade.fee_updated('sell')
+    assert trade.fee_open_currency == fee_currency
+    assert trade.fee_open_cost == fee_cost
+    assert trade.fee_open == fee_rate
+    # Setting buy rate should "guess" close rate
+    assert trade.fee_close == fee_rate
+    assert trade.fee_close_currency is None
+    assert trade.fee_close_cost is None
+
+    fee_rate = 0.0076
+    trade.update_fee(fee_cost, fee_currency, fee_rate, 'sell')
+    assert trade.fee_updated('buy')
+    assert trade.fee_updated('sell')
+    assert trade.fee_close == 0.0076
+    assert trade.fee_close_cost == fee_cost
+    assert trade.fee_close == fee_rate
+
+
+def test_fee_updated(fee):
+    trade = Trade(
+        pair='ETH/BTC',
+        stake_amount=0.001,
+        fee_open=fee.return_value,
+        open_date=arrow.utcnow().shift(hours=-2).datetime,
+        amount=10,
+        fee_close=fee.return_value,
+        exchange='bittrex',
+        open_rate=1,
+        max_rate=1,
+    )
+
+    assert trade.fee_open_currency is None
+    assert not trade.fee_updated('buy')
+    assert not trade.fee_updated('sell')
+    assert not trade.fee_updated('asdf')
+
+    trade.update_fee(0.15, 'BTC', 0.0075, 'buy')
+    assert trade.fee_updated('buy')
+    assert not trade.fee_updated('sell')
+    assert trade.fee_open_currency is not None
+    assert trade.fee_close_currency is None
+
+    trade.update_fee(0.15, 'ABC', 0.0075, 'sell')
+    assert trade.fee_updated('buy')
+    assert trade.fee_updated('sell')
+    assert not trade.fee_updated('asfd')
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_total_open_trades_stakes(fee):
+
+    res = Trade.total_open_trades_stakes()
+    assert res == 0
+    create_mock_trades(fee)
+    res = Trade.total_open_trades_stakes()
+    assert res == 0.004
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_get_overall_performance(fee):
+
+    create_mock_trades(fee)
+    res = Trade.get_overall_performance()
+
+    assert len(res) == 2
+    assert 'pair' in res[0]
+    assert 'profit' in res[0]
+    assert 'count' in res[0]
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_get_best_pair(fee):
+
+    res = Trade.get_best_pair()
+    assert res is None
+
+    create_mock_trades(fee)
+    res = Trade.get_best_pair()
+    assert len(res) == 2
+    assert res[0] == 'XRP/BTC'
+    assert res[1] == 0.01
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_update_order_from_ccxt():
+    # Most basic order return (only has orderid)
+    o = Order.parse_from_ccxt_object({'id': '1234'}, 'ETH/BTC', 'buy')
+    assert isinstance(o, Order)
+    assert o.ft_pair == 'ETH/BTC'
+    assert o.ft_order_side == 'buy'
+    assert o.order_id == '1234'
+    assert o.ft_is_open
+    ccxt_order = {
+        'id': '1234',
+        'side': 'buy',
+        'symbol': 'ETH/BTC',
+        'type': 'limit',
+        'price': 1234.5,
+        'amount':  20.0,
+        'filled': 9,
+        'remaining': 11,
+        'status': 'open',
+        'timestamp': 1599394315123
+    }
+    o = Order.parse_from_ccxt_object(ccxt_order, 'ETH/BTC', 'buy')
+    assert isinstance(o, Order)
+    assert o.ft_pair == 'ETH/BTC'
+    assert o.ft_order_side == 'buy'
+    assert o.order_id == '1234'
+    assert o.order_type == 'limit'
+    assert o.price == 1234.5
+    assert o.filled == 9
+    assert o.remaining == 11
+    assert o.order_date is not None
+    assert o.ft_is_open
+    assert o.order_filled_date is None
+
+    # Order has been closed
+    ccxt_order.update({'filled': 20.0, 'remaining': 0.0, 'status': 'closed'})
+    o.update_from_ccxt_object(ccxt_order)
+
+    assert o.filled == 20.0
+    assert o.remaining == 0.0
+    assert not o.ft_is_open
+    assert o.order_filled_date is not None
+
+    ccxt_order.update({'id': 'somethingelse'})
+    with pytest.raises(DependencyException, match=r"Order-id's don't match"):
+        o.update_from_ccxt_object(ccxt_order)
+
+
+@pytest.mark.usefixtures("init_persistence")
+def test_select_order(fee):
+    create_mock_trades(fee)
+
+    trades = Trade.get_trades().all()
+
+    # Open buy order, no sell order
+    order = trades[0].select_order('buy', True)
+    assert order is None
+    order = trades[0].select_order('buy', False)
+    assert order is not None
+    order = trades[0].select_order('sell', None)
+    assert order is None
+
+    # closed buy order, and open sell order
+    order = trades[1].select_order('buy', True)
+    assert order is None
+    order = trades[1].select_order('buy', False)
+    assert order is not None
+    order = trades[1].select_order('buy', None)
+    assert order is not None
+    order = trades[1].select_order('sell', True)
+    assert order is None
+    order = trades[1].select_order('sell', False)
+    assert order is not None
+
+    # Has open buy order
+    order = trades[3].select_order('buy', True)
+    assert order is not None
+    order = trades[3].select_order('buy', False)
+    assert order is None
+
+    # Open sell order
+    order = trades[4].select_order('buy', True)
+    assert order is None
+    order = trades[4].select_order('buy', False)
+    assert order is not None
+
+    order = trades[4].select_order('sell', True)
+    assert order is not None
+    assert order.ft_order_side == 'stoploss'
+    order = trades[4].select_order('sell', False)
+    assert order is None
diff --git a/tests/test_plotting.py b/tests/test_plotting.py
new file mode 100644
index 000000000..d3f97013d
--- /dev/null
+++ b/tests/test_plotting.py
@@ -0,0 +1,444 @@
+
+from copy import deepcopy
+from pathlib import Path
+from unittest.mock import MagicMock
+
+import pandas as pd
+import plotly.graph_objects as go
+import pytest
+from plotly.subplots import make_subplots
+
+from freqtrade.commands import start_plot_dataframe, start_plot_profit
+from freqtrade.configuration import TimeRange
+from freqtrade.data import history
+from freqtrade.data.btanalysis import create_cum_profit, load_backtest_data
+from freqtrade.exceptions import OperationalException
+from freqtrade.plot.plotting import (add_indicators, add_profit, create_plotconfig,
+                                     generate_candlestick_graph, generate_plot_filename,
+                                     generate_profit_graph, init_plotscript, load_and_plot_trades,
+                                     plot_profit, plot_trades, store_plot_file)
+from freqtrade.resolvers import StrategyResolver
+from tests.conftest import get_args, log_has, log_has_re, patch_exchange
+
+
+def fig_generating_mock(fig, *args, **kwargs):
+    """ Return Fig - used to mock add_indicators and plot_trades"""
+    return fig
+
+
+def find_trace_in_fig_data(data, search_string: str):
+    matches = (d for d in data if d.name == search_string)
+    return next(matches)
+
+
+def generate_empty_figure():
+    return make_subplots(
+        rows=3,
+        cols=1,
+        shared_xaxes=True,
+        row_width=[1, 1, 4],
+        vertical_spacing=0.0001,
+    )
+
+
+def test_init_plotscript(default_conf, mocker, testdatadir):
+    default_conf['timerange'] = "20180110-20180112"
+    default_conf['trade_source'] = "file"
+    default_conf['timeframe'] = "5m"
+    default_conf["datadir"] = testdatadir
+    default_conf['exportfilename'] = testdatadir / "backtest-result_test.json"
+    ret = init_plotscript(default_conf)
+    assert "ohlcv" in ret
+    assert "trades" in ret
+    assert "pairs" in ret
+    assert 'timerange' in ret
+
+    default_conf['pairs'] = ["TRX/BTC", "ADA/BTC"]
+    ret = init_plotscript(default_conf, 20)
+    assert "ohlcv" in ret
+    assert "TRX/BTC" in ret["ohlcv"]
+    assert "ADA/BTC" in ret["ohlcv"]
+
+
+def test_add_indicators(default_conf, testdatadir, caplog):
+    pair = "UNITTEST/BTC"
+    timerange = TimeRange(None, 'line', 0, -1000)
+
+    data = history.load_pair_history(pair=pair, timeframe='1m',
+                                     datadir=testdatadir, timerange=timerange)
+    indicators1 = {"ema10": {}}
+    indicators2 = {"macd": {"color": "red"}}
+
+    default_conf.update({'strategy': 'DefaultStrategy'})
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    # Generate buy/sell signals and indicators
+    data = strategy.analyze_ticker(data, {'pair': pair})
+    fig = generate_empty_figure()
+
+    # Row 1
+    fig1 = add_indicators(fig=deepcopy(fig), row=1, indicators=indicators1, data=data)
+    figure = fig1.layout.figure
+    ema10 = find_trace_in_fig_data(figure.data, "ema10")
+    assert isinstance(ema10, go.Scatter)
+    assert ema10.yaxis == "y"
+
+    fig2 = add_indicators(fig=deepcopy(fig), row=3, indicators=indicators2, data=data)
+    figure = fig2.layout.figure
+    macd = find_trace_in_fig_data(figure.data, "macd")
+    assert isinstance(macd, go.Scatter)
+    assert macd.yaxis == "y3"
+    assert macd.line.color == "red"
+
+    # No indicator found
+    fig3 = add_indicators(fig=deepcopy(fig), row=3, indicators={'no_indicator': {}}, data=data)
+    assert fig == fig3
+    assert log_has_re(r'Indicator "no_indicator" ignored\..*', caplog)
+
+
+def test_plot_trades(testdatadir, caplog):
+    fig1 = generate_empty_figure()
+    # nothing happens when no trades are available
+    fig = plot_trades(fig1, None)
+    assert fig == fig1
+    assert log_has("No trades found.", caplog)
+    pair = "ADA/BTC"
+    filename = testdatadir / "backtest-result_test.json"
+    trades = load_backtest_data(filename)
+    trades = trades.loc[trades['pair'] == pair]
+
+    fig = plot_trades(fig, trades)
+    figure = fig1.layout.figure
+
+    # Check buys - color, should be in first graph, ...
+    trade_buy = find_trace_in_fig_data(figure.data, 'Trade buy')
+    assert isinstance(trade_buy, go.Scatter)
+    assert trade_buy.yaxis == 'y'
+    assert len(trades) == len(trade_buy.x)
+    assert trade_buy.marker.color == 'cyan'
+    assert trade_buy.marker.symbol == 'circle-open'
+    assert trade_buy.text[0] == '4.0%, roi, 15 min'
+
+    trade_sell = find_trace_in_fig_data(figure.data, 'Sell - Profit')
+    assert isinstance(trade_sell, go.Scatter)
+    assert trade_sell.yaxis == 'y'
+    assert len(trades.loc[trades['profit_percent'] > 0]) == len(trade_sell.x)
+    assert trade_sell.marker.color == 'green'
+    assert trade_sell.marker.symbol == 'square-open'
+    assert trade_sell.text[0] == '4.0%, roi, 15 min'
+
+    trade_sell_loss = find_trace_in_fig_data(figure.data, 'Sell - Loss')
+    assert isinstance(trade_sell_loss, go.Scatter)
+    assert trade_sell_loss.yaxis == 'y'
+    assert len(trades.loc[trades['profit_percent'] <= 0]) == len(trade_sell_loss.x)
+    assert trade_sell_loss.marker.color == 'red'
+    assert trade_sell_loss.marker.symbol == 'square-open'
+    assert trade_sell_loss.text[5] == '-10.4%, stop_loss, 720 min'
+
+
+def test_generate_candlestick_graph_no_signals_no_trades(default_conf, mocker, testdatadir, caplog):
+    row_mock = mocker.patch('freqtrade.plot.plotting.add_indicators',
+                            MagicMock(side_effect=fig_generating_mock))
+    trades_mock = mocker.patch('freqtrade.plot.plotting.plot_trades',
+                               MagicMock(side_effect=fig_generating_mock))
+
+    pair = "UNITTEST/BTC"
+    timerange = TimeRange(None, 'line', 0, -1000)
+    data = history.load_pair_history(pair=pair, timeframe='1m',
+                                     datadir=testdatadir, timerange=timerange)
+    data['buy'] = 0
+    data['sell'] = 0
+
+    indicators1 = []
+    indicators2 = []
+    fig = generate_candlestick_graph(pair=pair, data=data, trades=None,
+                                     indicators1=indicators1, indicators2=indicators2)
+    assert isinstance(fig, go.Figure)
+    assert fig.layout.title.text == pair
+    figure = fig.layout.figure
+
+    assert len(figure.data) == 2
+    # Candlesticks are plotted first
+    candles = find_trace_in_fig_data(figure.data, "Price")
+    assert isinstance(candles, go.Candlestick)
+
+    volume = find_trace_in_fig_data(figure.data, "Volume")
+    assert isinstance(volume, go.Bar)
+
+    assert row_mock.call_count == 2
+    assert trades_mock.call_count == 1
+
+    assert log_has("No buy-signals found.", caplog)
+    assert log_has("No sell-signals found.", caplog)
+
+
+def test_generate_candlestick_graph_no_trades(default_conf, mocker, testdatadir):
+    row_mock = mocker.patch('freqtrade.plot.plotting.add_indicators',
+                            MagicMock(side_effect=fig_generating_mock))
+    trades_mock = mocker.patch('freqtrade.plot.plotting.plot_trades',
+                               MagicMock(side_effect=fig_generating_mock))
+    pair = 'UNITTEST/BTC'
+    timerange = TimeRange(None, 'line', 0, -1000)
+    data = history.load_pair_history(pair=pair, timeframe='1m',
+                                     datadir=testdatadir, timerange=timerange)
+
+    default_conf.update({'strategy': 'DefaultStrategy'})
+    strategy = StrategyResolver.load_strategy(default_conf)
+
+    # Generate buy/sell signals and indicators
+    data = strategy.analyze_ticker(data, {'pair': pair})
+
+    indicators1 = []
+    indicators2 = []
+    fig = generate_candlestick_graph(pair=pair, data=data, trades=None,
+                                     indicators1=indicators1, indicators2=indicators2)
+    assert isinstance(fig, go.Figure)
+    assert fig.layout.title.text == pair
+    figure = fig.layout.figure
+
+    assert len(figure.data) == 6
+    # Candlesticks are plotted first
+    candles = find_trace_in_fig_data(figure.data, "Price")
+    assert isinstance(candles, go.Candlestick)
+
+    volume = find_trace_in_fig_data(figure.data, "Volume")
+    assert isinstance(volume, go.Bar)
+
+    buy = find_trace_in_fig_data(figure.data, "buy")
+    assert isinstance(buy, go.Scatter)
+    # All buy-signals should be plotted
+    assert int(data.buy.sum()) == len(buy.x)
+
+    sell = find_trace_in_fig_data(figure.data, "sell")
+    assert isinstance(sell, go.Scatter)
+    # All buy-signals should be plotted
+    assert int(data.sell.sum()) == len(sell.x)
+
+    assert find_trace_in_fig_data(figure.data, "Bollinger Band")
+
+    assert row_mock.call_count == 2
+    assert trades_mock.call_count == 1
+
+
+def test_generate_Plot_filename():
+    fn = generate_plot_filename("UNITTEST/BTC", "5m")
+    assert fn == "freqtrade-plot-UNITTEST_BTC-5m.html"
+
+
+def test_generate_plot_file(mocker, caplog):
+    fig = generate_empty_figure()
+    plot_mock = mocker.patch("freqtrade.plot.plotting.plot", MagicMock())
+    store_plot_file(fig, filename="freqtrade-plot-UNITTEST_BTC-5m.html",
+                    directory=Path("user_data/plot"))
+
+    expected_fn = str(Path("user_data/plot/freqtrade-plot-UNITTEST_BTC-5m.html"))
+    assert plot_mock.call_count == 1
+    assert plot_mock.call_args[0][0] == fig
+    assert (plot_mock.call_args_list[0][1]['filename']
+            == expected_fn)
+    assert log_has(f"Stored plot as {expected_fn}",
+                   caplog)
+
+
+def test_add_profit(testdatadir):
+    filename = testdatadir / "backtest-result_test.json"
+    bt_data = load_backtest_data(filename)
+    timerange = TimeRange.parse_timerange("20180110-20180112")
+
+    df = history.load_pair_history(pair="TRX/BTC", timeframe='5m',
+                                   datadir=testdatadir, timerange=timerange)
+    fig = generate_empty_figure()
+
+    cum_profits = create_cum_profit(df.set_index('date'),
+                                    bt_data[bt_data["pair"] == 'TRX/BTC'],
+                                    "cum_profits", timeframe="5m")
+
+    fig1 = add_profit(fig, row=2, data=cum_profits, column='cum_profits', name='Profits')
+    figure = fig1.layout.figure
+    profits = find_trace_in_fig_data(figure.data, "Profits")
+    assert isinstance(profits, go.Scatter)
+    assert profits.yaxis == "y2"
+
+
+def test_generate_profit_graph(testdatadir):
+    filename = testdatadir / "backtest-result_test.json"
+    trades = load_backtest_data(filename)
+    timerange = TimeRange.parse_timerange("20180110-20180112")
+    pairs = ["TRX/BTC", "XLM/BTC"]
+    trades = trades[trades['close_date'] < pd.Timestamp('2018-01-12', tz='UTC')]
+
+    data = history.load_data(datadir=testdatadir,
+                             pairs=pairs,
+                             timeframe='5m',
+                             timerange=timerange)
+
+    trades = trades[trades['pair'].isin(pairs)]
+
+    fig = generate_profit_graph(pairs, data, trades, timeframe="5m")
+    assert isinstance(fig, go.Figure)
+
+    assert fig.layout.title.text == "Freqtrade Profit plot"
+    assert fig.layout.yaxis.title.text == "Price"
+    assert fig.layout.yaxis2.title.text == "Profit"
+    assert fig.layout.yaxis3.title.text == "Profit"
+
+    figure = fig.layout.figure
+    assert len(figure.data) == 5
+
+    avgclose = find_trace_in_fig_data(figure.data, "Avg close price")
+    assert isinstance(avgclose, go.Scatter)
+
+    profit = find_trace_in_fig_data(figure.data, "Profit")
+    assert isinstance(profit, go.Scatter)
+    profit = find_trace_in_fig_data(figure.data, "Max drawdown 10.45%")
+    assert isinstance(profit, go.Scatter)
+
+    for pair in pairs:
+        profit_pair = find_trace_in_fig_data(figure.data, f"Profit {pair}")
+        assert isinstance(profit_pair, go.Scatter)
+
+
+def test_start_plot_dataframe(mocker):
+    aup = mocker.patch("freqtrade.plot.plotting.load_and_plot_trades", MagicMock())
+    args = [
+        "plot-dataframe",
+        "--config", "config.json.example",
+        "--pairs", "ETH/BTC"
+    ]
+    start_plot_dataframe(get_args(args))
+
+    assert aup.call_count == 1
+    called_config = aup.call_args_list[0][0][0]
+    assert "pairs" in called_config
+    assert called_config['pairs'] == ["ETH/BTC"]
+
+
+def test_load_and_plot_trades(default_conf, mocker, caplog, testdatadir):
+    patch_exchange(mocker)
+
+    default_conf['trade_source'] = 'file'
+    default_conf["datadir"] = testdatadir
+    default_conf['exportfilename'] = testdatadir / "backtest-result_test.json"
+    default_conf['indicators1'] = ["sma5", "ema10"]
+    default_conf['indicators2'] = ["macd"]
+    default_conf['pairs'] = ["ETH/BTC", "LTC/BTC"]
+
+    candle_mock = MagicMock()
+    store_mock = MagicMock()
+    mocker.patch.multiple(
+        "freqtrade.plot.plotting",
+        generate_candlestick_graph=candle_mock,
+        store_plot_file=store_mock
+    )
+    load_and_plot_trades(default_conf)
+
+    # Both mocks should be called once per pair
+    assert candle_mock.call_count == 2
+    assert store_mock.call_count == 2
+
+    assert candle_mock.call_args_list[0][1]['indicators1'] == ['sma5', 'ema10']
+    assert candle_mock.call_args_list[0][1]['indicators2'] == ['macd']
+
+    assert log_has("End of plotting process. 2 plots generated", caplog)
+
+
+def test_start_plot_profit(mocker):
+    aup = mocker.patch("freqtrade.plot.plotting.plot_profit", MagicMock())
+    args = [
+        "plot-profit",
+        "--config", "config.json.example",
+        "--pairs", "ETH/BTC"
+    ]
+    start_plot_profit(get_args(args))
+
+    assert aup.call_count == 1
+    called_config = aup.call_args_list[0][0][0]
+    assert "pairs" in called_config
+    assert called_config['pairs'] == ["ETH/BTC"]
+
+
+def test_start_plot_profit_error(mocker):
+
+    args = [
+        'plot-profit',
+        '--pairs', 'ETH/BTC'
+    ]
+    argsp = get_args(args)
+    # Make sure we use no config. Details: #2241
+    # not resetting config causes random failures if config.json exists
+    argsp['config'] = []
+    with pytest.raises(OperationalException):
+        start_plot_profit(argsp)
+
+
+def test_plot_profit(default_conf, mocker, testdatadir, caplog):
+    default_conf['trade_source'] = 'file'
+    default_conf['datadir'] = testdatadir
+    default_conf['exportfilename'] = testdatadir / 'backtest-result_test_nofile.json'
+    default_conf['pairs'] = ['ETH/BTC', 'LTC/BTC']
+
+    profit_mock = MagicMock()
+    store_mock = MagicMock()
+    mocker.patch.multiple(
+        "freqtrade.plot.plotting",
+        generate_profit_graph=profit_mock,
+        store_plot_file=store_mock
+    )
+    with pytest.raises(OperationalException,
+                       match=r"No trades found, cannot generate Profit-plot.*"):
+        plot_profit(default_conf)
+
+    default_conf['exportfilename'] = testdatadir / "backtest-result_test.json"
+
+    plot_profit(default_conf)
+
+    # Plot-profit generates one combined plot
+    assert profit_mock.call_count == 1
+    assert store_mock.call_count == 1
+
+    assert profit_mock.call_args_list[0][0][0] == default_conf['pairs']
+    assert store_mock.call_args_list[0][1]['auto_open'] is True
+
+
+@pytest.mark.parametrize("ind1,ind2,plot_conf,exp", [
+    # No indicators, use plot_conf
+    ([], [], {},
+     {'main_plot': {'sma': {}, 'ema3': {}, 'ema5': {}},
+      'subplots': {'Other': {'macd': {}, 'macdsignal': {}}}}),
+    # use indicators
+    (['sma', 'ema3'], ['macd'], {},
+     {'main_plot': {'sma': {}, 'ema3': {}}, 'subplots': {'Other': {'macd': {}}}}),
+    # only main_plot - adds empty subplots
+    ([], [], {'main_plot': {'sma': {}}},
+     {'main_plot': {'sma': {}}, 'subplots': {}}),
+    # Main and subplots
+    ([], [], {'main_plot': {'sma': {}}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}},
+     {'main_plot': {'sma': {}}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}}),
+    # no main_plot, adds empty main_plot
+    ([], [], {'subplots': {'RSI': {'rsi': {'color': 'red'}}}},
+     {'main_plot': {}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}}),
+    # indicator 1 / 2 should have prevelance
+    (['sma', 'ema3'], ['macd'],
+     {'main_plot': {'sma': {}}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}},
+     {'main_plot': {'sma': {}, 'ema3': {}}, 'subplots': {'Other': {'macd': {}}}}
+     ),
+    # indicator 1 - overrides plot_config main_plot
+    (['sma', 'ema3'], [],
+     {'main_plot': {'sma': {}}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}},
+     {'main_plot': {'sma': {}, 'ema3': {}}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}}
+     ),
+    # indicator 2 - overrides plot_config subplots
+    ([], ['macd', 'macd_signal'],
+     {'main_plot': {'sma': {}}, 'subplots': {'RSI': {'rsi': {'color': 'red'}}}},
+     {'main_plot': {'sma': {}}, 'subplots': {'Other': {'macd': {}, 'macd_signal': {}}}}
+     ),
+])
+def test_create_plotconfig(ind1, ind2, plot_conf, exp):
+
+    res = create_plotconfig(ind1, ind2, plot_conf)
+    assert 'main_plot' in res
+    assert 'subplots' in res
+    assert isinstance(res['main_plot'], dict)
+    assert isinstance(res['subplots'], dict)
+
+    assert res == exp
diff --git a/freqtrade/tests/test_talib.py b/tests/test_talib.py
similarity index 99%
rename from freqtrade/tests/test_talib.py
rename to tests/test_talib.py
index 2c7f73eb1..f526fdd4d 100644
--- a/freqtrade/tests/test_talib.py
+++ b/tests/test_talib.py
@@ -1,7 +1,5 @@
-
-
-import talib.abstract as ta
 import pandas as pd
+import talib.abstract as ta
 
 
 def test_talib_bollingerbands_near_zero_values():
diff --git a/tests/test_timerange.py b/tests/test_timerange.py
new file mode 100644
index 000000000..5c35535f0
--- /dev/null
+++ b/tests/test_timerange.py
@@ -0,0 +1,65 @@
+# pragma pylint: disable=missing-docstring, C0103
+import arrow
+import pytest
+
+from freqtrade.configuration import TimeRange
+
+
+def test_parse_timerange_incorrect():
+
+    assert TimeRange('date', None, 1274486400, 0) == TimeRange.parse_timerange('20100522-')
+    assert TimeRange(None, 'date', 0, 1274486400) == TimeRange.parse_timerange('-20100522')
+    timerange = TimeRange.parse_timerange('20100522-20150730')
+    assert timerange == TimeRange('date', 'date', 1274486400, 1438214400)
+
+    # Added test for unix timestamp - BTC genesis date
+    assert TimeRange('date', None, 1231006505, 0) == TimeRange.parse_timerange('1231006505-')
+    assert TimeRange(None, 'date', 0, 1233360000) == TimeRange.parse_timerange('-1233360000')
+    timerange = TimeRange.parse_timerange('1231006505-1233360000')
+    assert TimeRange('date', 'date', 1231006505, 1233360000) == timerange
+
+    timerange = TimeRange.parse_timerange('1231006505000-1233360000000')
+    assert TimeRange('date', 'date', 1231006505, 1233360000) == timerange
+
+    timerange = TimeRange.parse_timerange('1231006505000-')
+    assert TimeRange('date', None, 1231006505, 0) == timerange
+
+    timerange = TimeRange.parse_timerange('-1231006505000')
+    assert TimeRange(None, 'date', 0, 1231006505) == timerange
+
+    with pytest.raises(Exception, match=r'Incorrect syntax.*'):
+        TimeRange.parse_timerange('-')
+
+
+def test_subtract_start():
+    x = TimeRange('date', 'date', 1274486400, 1438214400)
+    x.subtract_start(300)
+    assert x.startts == 1274486400 - 300
+
+    # Do nothing if no startdate exists
+    x = TimeRange(None, 'date', 0, 1438214400)
+    x.subtract_start(300)
+    assert not x.startts
+
+    x = TimeRange('date', None, 1274486400, 0)
+    x.subtract_start(300)
+    assert x.startts == 1274486400 - 300
+
+
+def test_adjust_start_if_necessary():
+    min_date = arrow.Arrow(2017, 11, 14, 21, 15, 00)
+
+    x = TimeRange('date', 'date', 1510694100, 1510780500)
+    # Adjust by 20 candles - min_date == startts
+    x.adjust_start_if_necessary(300, 20, min_date)
+    assert x.startts == 1510694100 + (20 * 300)
+
+    x = TimeRange('date', 'date', 1510700100, 1510780500)
+    # Do nothing, startup is set and different min_date
+    x.adjust_start_if_necessary(300, 20, min_date)
+    assert x.startts == 1510694100 + (20 * 300)
+
+    x = TimeRange(None, 'date', 0, 1510780500)
+    # Adjust by 20 candles = 20 * 5m
+    x.adjust_start_if_necessary(300, 20, min_date)
+    assert x.startts == 1510694100 + (20 * 300)
diff --git a/freqtrade/tests/test_wallets.py b/tests/test_wallets.py
similarity index 79%
rename from freqtrade/tests/test_wallets.py
rename to tests/test_wallets.py
index 2c493cfc3..b7aead0c4 100644
--- a/freqtrade/tests/test_wallets.py
+++ b/tests/test_wallets.py
@@ -1,7 +1,8 @@
 # pragma pylint: disable=missing-docstring
-from freqtrade.tests.conftest import get_patched_freqtradebot
 from unittest.mock import MagicMock
 
+from tests.conftest import get_patched_freqtradebot
+
 
 def test_sync_wallet_at_boot(mocker, default_conf):
     default_conf['dry_run'] = False
@@ -18,12 +19,17 @@ def test_sync_wallet_at_boot(mocker, default_conf):
                 "used": 0.0,
                 "total": 0.260739
             },
+            "USDT": {
+                "free": 20,
+                "used": 20,
+                "total": 40
+            },
         })
     )
 
     freqtrade = get_patched_freqtradebot(mocker, default_conf)
 
-    assert len(freqtrade.wallets._wallets) == 2
+    assert len(freqtrade.wallets._wallets) == 3
     assert freqtrade.wallets._wallets['BNT'].free == 1.0
     assert freqtrade.wallets._wallets['BNT'].used == 2.0
     assert freqtrade.wallets._wallets['BNT'].total == 3.0
@@ -31,7 +37,8 @@ def test_sync_wallet_at_boot(mocker, default_conf):
     assert freqtrade.wallets._wallets['GAS'].used == 0.0
     assert freqtrade.wallets._wallets['GAS'].total == 0.260739
     assert freqtrade.wallets.get_free('BNT') == 1.0
-
+    assert 'USDT' in freqtrade.wallets._wallets
+    assert freqtrade.wallets._last_wallet_refresh > 0
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         get_balances=MagicMock(return_value={
@@ -50,6 +57,7 @@ def test_sync_wallet_at_boot(mocker, default_conf):
 
     freqtrade.wallets.update()
 
+    # USDT is missing from the 2nd result - so should not be in this either.
     assert len(freqtrade.wallets._wallets) == 2
     assert freqtrade.wallets._wallets['BNT'].free == 1.2
     assert freqtrade.wallets._wallets['BNT'].used == 1.9
@@ -60,6 +68,15 @@ def test_sync_wallet_at_boot(mocker, default_conf):
     assert freqtrade.wallets.get_free('GAS') == 0.270739
     assert freqtrade.wallets.get_used('GAS') == 0.1
     assert freqtrade.wallets.get_total('GAS') == 0.260439
+    update_mock = mocker.patch('freqtrade.wallets.Wallets._update_live')
+    freqtrade.wallets.update(False)
+    assert update_mock.call_count == 0
+    freqtrade.wallets.update()
+    assert update_mock.call_count == 1
+
+    assert freqtrade.wallets.get_free('NOCURRENCY') == 0
+    assert freqtrade.wallets.get_used('NOCURRENCY') == 0
+    assert freqtrade.wallets.get_total('NOCURRENCY') == 0
 
 
 def test_sync_wallet_missing_data(mocker, default_conf):
diff --git a/tests/test_worker.py b/tests/test_worker.py
new file mode 100644
index 000000000..839f7cdac
--- /dev/null
+++ b/tests/test_worker.py
@@ -0,0 +1,125 @@
+import logging
+import time
+from unittest.mock import MagicMock, PropertyMock
+
+from freqtrade.data.dataprovider import DataProvider
+from freqtrade.state import State
+from freqtrade.worker import Worker
+from tests.conftest import get_patched_worker, log_has, log_has_re
+
+
+def test_worker_state(mocker, default_conf, markets) -> None:
+    mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
+    worker = get_patched_worker(mocker, default_conf)
+    assert worker.freqtrade.state is State.RUNNING
+
+    default_conf.pop('initial_state')
+    worker = Worker(args=None, config=default_conf)
+    assert worker.freqtrade.state is State.STOPPED
+
+
+def test_worker_running(mocker, default_conf, caplog) -> None:
+    mock_throttle = MagicMock()
+    mocker.patch('freqtrade.worker.Worker._throttle', mock_throttle)
+    mocker.patch('freqtrade.persistence.Trade.stoploss_reinitialization', MagicMock())
+
+    worker = get_patched_worker(mocker, default_conf)
+
+    state = worker._worker(old_state=None)
+    assert state is State.RUNNING
+    assert log_has('Changing state to: RUNNING', caplog)
+    assert mock_throttle.call_count == 1
+    # Check strategy is loaded, and received a dataprovider object
+    assert worker.freqtrade.strategy
+    assert worker.freqtrade.strategy.dp
+    assert isinstance(worker.freqtrade.strategy.dp, DataProvider)
+
+
+def test_worker_stopped(mocker, default_conf, caplog) -> None:
+    mock_throttle = MagicMock()
+    mocker.patch('freqtrade.worker.Worker._throttle', mock_throttle)
+
+    worker = get_patched_worker(mocker, default_conf)
+    worker.freqtrade.state = State.STOPPED
+    state = worker._worker(old_state=State.RUNNING)
+    assert state is State.STOPPED
+    assert log_has('Changing state to: STOPPED', caplog)
+    assert mock_throttle.call_count == 1
+
+
+def test_throttle(mocker, default_conf, caplog) -> None:
+    def throttled_func():
+        return 42
+
+    caplog.set_level(logging.DEBUG)
+    worker = get_patched_worker(mocker, default_conf)
+
+    start = time.time()
+    result = worker._throttle(throttled_func, throttle_secs=0.1)
+    end = time.time()
+
+    assert result == 42
+    assert end - start > 0.1
+    assert log_has_re(r"Throttling with 'throttled_func\(\)': sleep for \d\.\d{2} s.*", caplog)
+
+    result = worker._throttle(throttled_func, throttle_secs=-1)
+    assert result == 42
+
+
+def test_throttle_with_assets(mocker, default_conf) -> None:
+    def throttled_func(nb_assets=-1):
+        return nb_assets
+
+    worker = get_patched_worker(mocker, default_conf)
+
+    result = worker._throttle(throttled_func, throttle_secs=0.1, nb_assets=666)
+    assert result == 666
+
+    result = worker._throttle(throttled_func, throttle_secs=0.1)
+    assert result == -1
+
+
+def test_worker_heartbeat_running(default_conf, mocker, caplog):
+    message = r"Bot heartbeat\. PID=.*state='RUNNING'"
+
+    mock_throttle = MagicMock()
+    mocker.patch('freqtrade.worker.Worker._throttle', mock_throttle)
+    worker = get_patched_worker(mocker, default_conf)
+
+    worker.freqtrade.state = State.RUNNING
+    worker._worker(old_state=State.STOPPED)
+    assert log_has_re(message, caplog)
+
+    caplog.clear()
+    # Message is not shown before interval is up
+    worker._worker(old_state=State.RUNNING)
+    assert not log_has_re(message, caplog)
+
+    caplog.clear()
+    # Set clock - 70 seconds
+    worker._heartbeat_msg -= 70
+    worker._worker(old_state=State.RUNNING)
+    assert log_has_re(message, caplog)
+
+
+def test_worker_heartbeat_stopped(default_conf, mocker, caplog):
+    message = r"Bot heartbeat\. PID=.*state='STOPPED'"
+
+    mock_throttle = MagicMock()
+    mocker.patch('freqtrade.worker.Worker._throttle', mock_throttle)
+    worker = get_patched_worker(mocker, default_conf)
+
+    worker.freqtrade.state = State.STOPPED
+    worker._worker(old_state=State.RUNNING)
+    assert log_has_re(message, caplog)
+
+    caplog.clear()
+    # Message is not shown before interval is up
+    worker._worker(old_state=State.STOPPED)
+    assert not log_has_re(message, caplog)
+
+    caplog.clear()
+    # Set clock - 70 seconds
+    worker._heartbeat_msg -= 70
+    worker._worker(old_state=State.STOPPED)
+    assert log_has_re(message, caplog)
diff --git a/tests/testdata/.last_result.json b/tests/testdata/.last_result.json
new file mode 100644
index 000000000..98448e10f
--- /dev/null
+++ b/tests/testdata/.last_result.json
@@ -0,0 +1 @@
+{"latest_backtest":"backtest-result_new.json"}
diff --git a/freqtrade/tests/testdata/ADA_BTC-5m.json b/tests/testdata/ADA_BTC-5m.json
similarity index 100%
rename from freqtrade/tests/testdata/ADA_BTC-5m.json
rename to tests/testdata/ADA_BTC-5m.json
diff --git a/freqtrade/tests/testdata/DASH_BTC-5m.json b/tests/testdata/DASH_BTC-5m.json
similarity index 100%
rename from freqtrade/tests/testdata/DASH_BTC-5m.json
rename to tests/testdata/DASH_BTC-5m.json
diff --git a/freqtrade/tests/testdata/ETC_BTC-5m.json b/tests/testdata/ETC_BTC-5m.json
similarity index 100%
rename from freqtrade/tests/testdata/ETC_BTC-5m.json
rename to tests/testdata/ETC_BTC-5m.json
diff --git a/freqtrade/tests/testdata/ETH_BTC-5m.json b/tests/testdata/ETH_BTC-5m.json
similarity index 100%
rename from freqtrade/tests/testdata/ETH_BTC-5m.json
rename to tests/testdata/ETH_BTC-5m.json
diff --git a/freqtrade/tests/testdata/LTC_BTC-5m.json b/tests/testdata/LTC_BTC-5m.json
similarity index 100%
rename from freqtrade/tests/testdata/LTC_BTC-5m.json
rename to tests/testdata/LTC_BTC-5m.json
diff --git a/freqtrade/tests/testdata/NXT_BTC-5m.json b/tests/testdata/NXT_BTC-5m.json
similarity index 100%
rename from freqtrade/tests/testdata/NXT_BTC-5m.json
rename to tests/testdata/NXT_BTC-5m.json
diff --git a/freqtrade/tests/testdata/POWR_BTC-5m.json b/tests/testdata/TRX_BTC-5m.json
similarity index 100%
rename from freqtrade/tests/testdata/POWR_BTC-5m.json
rename to tests/testdata/TRX_BTC-5m.json
diff --git a/freqtrade/tests/testdata/UNITTEST_BTC-1m.json b/tests/testdata/UNITTEST_BTC-1m.json
similarity index 100%
rename from freqtrade/tests/testdata/UNITTEST_BTC-1m.json
rename to tests/testdata/UNITTEST_BTC-1m.json
diff --git a/freqtrade/tests/testdata/UNITTEST_BTC-30m.json b/tests/testdata/UNITTEST_BTC-30m.json
similarity index 100%
rename from freqtrade/tests/testdata/UNITTEST_BTC-30m.json
rename to tests/testdata/UNITTEST_BTC-30m.json
diff --git a/tests/testdata/UNITTEST_BTC-5m.h5 b/tests/testdata/UNITTEST_BTC-5m.h5
new file mode 100644
index 000000000..52232af9e
Binary files /dev/null and b/tests/testdata/UNITTEST_BTC-5m.h5 differ
diff --git a/freqtrade/tests/testdata/UNITTEST_BTC-5m.json b/tests/testdata/UNITTEST_BTC-5m.json
similarity index 100%
rename from freqtrade/tests/testdata/UNITTEST_BTC-5m.json
rename to tests/testdata/UNITTEST_BTC-5m.json
diff --git a/user_data/backtest_data/.gitkeep b/tests/testdata/UNITTEST_BTC-8m.json
similarity index 100%
rename from user_data/backtest_data/.gitkeep
rename to tests/testdata/UNITTEST_BTC-8m.json
diff --git a/freqtrade/tests/testdata/UNITTEST_BTC-8m.json.gz b/tests/testdata/UNITTEST_BTC-8m.json.gz
similarity index 100%
rename from freqtrade/tests/testdata/UNITTEST_BTC-8m.json.gz
rename to tests/testdata/UNITTEST_BTC-8m.json.gz
diff --git a/freqtrade/tests/testdata/XLM_BTC-5m.json b/tests/testdata/XLM_BTC-5m.json
similarity index 100%
rename from freqtrade/tests/testdata/XLM_BTC-5m.json
rename to tests/testdata/XLM_BTC-5m.json
diff --git a/freqtrade/tests/testdata/XMR_BTC-5m.json b/tests/testdata/XMR_BTC-5m.json
similarity index 100%
rename from freqtrade/tests/testdata/XMR_BTC-5m.json
rename to tests/testdata/XMR_BTC-5m.json
diff --git a/tests/testdata/XRP_ETH-1m.json b/tests/testdata/XRP_ETH-1m.json
new file mode 100644
index 000000000..4ec7c15ab
--- /dev/null
+++ b/tests/testdata/XRP_ETH-1m.json
@@ -0,0 +1 @@
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diff --git a/tests/testdata/XRP_ETH-5m.json b/tests/testdata/XRP_ETH-5m.json
new file mode 100644
index 000000000..92da3c17d
--- /dev/null
+++ b/tests/testdata/XRP_ETH-5m.json
@@ -0,0 +1 @@
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diff --git a/tests/testdata/XRP_ETH-trades.h5 b/tests/testdata/XRP_ETH-trades.h5
new file mode 100644
index 000000000..c13789e2a
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diff --git a/tests/testdata/XRP_ETH-trades.json.gz b/tests/testdata/XRP_ETH-trades.json.gz
new file mode 100644
index 000000000..dad822005
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diff --git a/tests/testdata/XRP_OLD-trades.json.gz b/tests/testdata/XRP_OLD-trades.json.gz
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index 000000000..69b92cac8
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diff --git a/freqtrade/tests/testdata/ZEC_BTC-5m.json b/tests/testdata/ZEC_BTC-5m.json
similarity index 100%
rename from freqtrade/tests/testdata/ZEC_BTC-5m.json
rename to tests/testdata/ZEC_BTC-5m.json
diff --git a/tests/testdata/backtest-result_multistrat.json b/tests/testdata/backtest-result_multistrat.json
new file mode 100644
index 000000000..0e5386ef3
--- /dev/null
+++ b/tests/testdata/backtest-result_multistrat.json
@@ -0,0 +1 @@
+{"strategy": {"DefaultStrategy": {"trades": [{"pair": "TRX/BTC", "profit_percent": 0.03990025, "open_date": "2018-01-10 07:15:00+00:00", "close_date": "2018-01-10 07:20:00+00:00", "trade_duration": 5, "open_rate": 9.64e-05, "close_rate": 0.00010074887218045112, "open_at_end": false, "sell_reason": "roi", "open_fee": 0.0025, "close_fee": 0.0025, "amount": 1037.344398340249, "profit_abs": 0.00399999999999999}, {"pair": "ADA/BTC", "profit_percent": 0.03990025, "open_date": "2018-01-10 07:15:00+00:00", "close_date": "2018-01-10 07:30:00+00:00", "trade_duration": 15, "open_rate": 4.756e-05, "close_rate": 4.9705563909774425e-05, "open_at_end": false, "sell_reason": "roi", "open_fee": 0.0025, "close_fee": 0.0025, "amount": 2102.6072329688814, "profit_abs": 0.00399999999999999}, {"pair": "XLM/BTC", "profit_percent": 0.03990025, "open_date": "2018-01-10 07:25:00+00:00", "close_date": "2018-01-10 07:35:00+00:00", "trade_duration": 10, "open_rate": 3.339e-05, "close_rate": 3.489631578947368e-05, 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diff --git a/tests/testdata/backtest-result_new.json b/tests/testdata/backtest-result_new.json
new file mode 100644
index 000000000..f004e879a
--- /dev/null
+++ b/tests/testdata/backtest-result_new.json
@@ -0,0 +1 @@
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diff --git a/tests/testdata/backtest-result_test.json b/tests/testdata/backtest-result_test.json
new file mode 100644
index 000000000..dce22acaf
--- /dev/null
+++ b/tests/testdata/backtest-result_test.json
@@ -0,0 +1 @@
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0,1516423800.0,1516461300.0,2878,625,0.00270505,0.002718609147869674,false,"roi"],["XMR/BTC",-0.0,1516423800.0,1516431600.0,2878,130,0.03000002,0.030150396040100245,false,"roi"],["ADA/BTC",-0.0,1516438800.0,1516441200.0,2928,40,5.46e-05,5.4873684210526304e-05,false,"roi"],["XMR/BTC",-0.10448878,1516472700.0,1516852200.0,3041,6325,0.03082222,0.027739998000000002,false,"stop_loss"],["ETH/BTC",-0.0,1516487100.0,1516490100.0,3089,50,0.08969999,0.09014961401002504,false,"roi"],["LTC/BTC",0.0,1516503000.0,1516545000.0,3142,700,0.01632501,0.01640683962406015,false,"roi"],["DASH/BTC",-0.0,1516530000.0,1516532400.0,3232,40,0.070538,0.07089157393483708,false,"roi"],["ADA/BTC",-0.0,1516549800.0,1516560300.0,3298,175,5.301e-05,5.3275714285714276e-05,false,"roi"],["XLM/BTC",0.0,1516551600.0,1516554000.0,3304,40,3.955e-05,3.9748245614035085e-05,false,"roi"],["ETC/BTC",0.00997506,1516569300.0,1516571100.0,3363,30,0.00258505,0.002623922932330827,false,"roi"],["XLM/BTC",-0.0,1516569300.0,1516571700.0,3363,40,3.903e-05,3.922563909774435e-05,false,"roi"],["ADA/BTC",-0.0,1516581300.0,1516617300.0,3403,600,5.236e-05,5.262245614035087e-05,false,"roi"],["TRX/BTC",0.0,1516584600.0,1516587000.0,3414,40,9.028e-05,9.073253132832079e-05,false,"roi"],["ETC/BTC",-0.0,1516623900.0,1516631700.0,3545,130,0.002687,0.002700468671679198,false,"roi"],["XLM/BTC",-0.0,1516626900.0,1516629300.0,3555,40,4.168e-05,4.1888922305764405e-05,false,"roi"],["TRX/BTC",0.00997506,1516629600.0,1516631400.0,3564,30,8.821e-05,8.953646616541353e-05,false,"roi"],["ADA/BTC",-0.0,1516636500.0,1516639200.0,3587,45,5.172e-05,5.1979248120300745e-05,false,"roi"],["NXT/BTC",0.01995012,1516637100.0,1516638300.0,3589,20,3.026e-05,3.101839598997494e-05,false,"roi"],["DASH/BTC",0.0,1516650600.0,1516666200.0,3634,260,0.07064,0.07099408521303258,false,"roi"],["LTC/BTC",0.0,1516656300.0,1516658700.0,3653,40,0.01644483,0.01652726022556391,false,"roi"],["XLM/BTC",0.00997506,1516665900.0,1516667700.0,3685,30,4.331e-05,4.3961278195488714e-05,false,"roi"],["NXT/BTC",0.01995012,1516672200.0,1516673700.0,3706,25,3.2e-05,3.2802005012531326e-05,false,"roi"],["ETH/BTC",0.0,1516681500.0,1516684500.0,3737,50,0.09167706,0.09213659413533835,false,"roi"],["DASH/BTC",0.0,1516692900.0,1516698000.0,3775,85,0.0692498,0.06959691679197995,false,"roi"],["NXT/BTC",0.0,1516704600.0,1516712700.0,3814,135,3.182e-05,3.197949874686716e-05,false,"roi"],["ZEC/BTC",-0.0,1516705500.0,1516723500.0,3817,300,0.04088,0.04108491228070175,false,"roi"],["ADA/BTC",-0.0,1516719300.0,1516721700.0,3863,40,5.15e-05,5.175814536340851e-05,false,"roi"],["ETH/BTC",0.0,1516725300.0,1516752300.0,3883,450,0.09071698,0.09117170170426064,false,"roi"],["NXT/BTC",-0.0,1516728300.0,1516733100.0,3893,80,3.128e-05,3.1436791979949865e-05,false,"roi"],["TRX/BTC",-0.0,1516738500.0,1516744800.0,3927,105,9.555e-05,9.602894736842104e-05,false,"roi"],["ZEC/BTC",-0.0,1516746600.0,1516749000.0,3954,40,0.04080001,0.041004521328320796,false,"roi"],["ADA/BTC",-0.0,1516751400.0,1516764900.0,3970,225,5.163e-05,5.1888796992481196e-05,false,"roi"],["ZEC/BTC",0.0,1516753200.0,1516758600.0,3976,90,0.04040781,0.04061035541353383,false,"roi"],["ADA/BTC",-0.0,1516776300.0,1516778700.0,4053,40,5.132e-05,5.157724310776942e-05,false,"roi"],["ADA/BTC",0.03990025,1516803300.0,1516803900.0,4143,10,5.198e-05,5.432496240601503e-05,false,"roi"],["NXT/BTC",-0.0,1516805400.0,1516811700.0,4150,105,3.054e-05,3.069308270676692e-05,false,"roi"],["TRX/BTC",0.0,1516806600.0,1516810500.0,4154,65,9.263e-05,9.309431077694235e-05,false,"roi"],["ADA/BTC",-0.0,1516833600.0,1516836300.0,4244,45,5.514e-05,5.5416390977443596e-05,false,"roi"],["XLM/BTC",0.0,1516841400.0,1516843800.0,4270,40,4.921e-05,4.9456666666666664e-05,false,"roi"],["ETC/BTC",0.0,1516868100.0,1516882500.0,4359,240,0.0026,0.002613032581453634,false,"roi"],["XMR/BTC",-0.0,1516875900.0,1516896900.0,4385,350,0.02799871,0.028139054411027563,false,"roi"],["ZEC/BTC",-0.0,1516878000.0,1516880700.0,4392,45,0.04078902,0.0409934762406015,false,"roi"],["NXT/BTC",-0.0,1516885500.0,1516887900.0,4417,40,2.89e-05,2.904486215538847e-05,false,"roi"],["ZEC/BTC",-0.0,1516886400.0,1516889100.0,4420,45,0.041103,0.041309030075187964,false,"roi"],["XLM/BTC",0.00997506,1516895100.0,1516896900.0,4449,30,5.428e-05,5.5096240601503756e-05,false,"roi"],["XLM/BTC",-0.0,1516902300.0,1516922100.0,4473,330,5.414e-05,5.441137844611528e-05,false,"roi"],["ZEC/BTC",-0.0,1516914900.0,1516917300.0,4515,40,0.04140777,0.0416153277443609,false,"roi"],["ETC/BTC",0.0,1516932300.0,1516934700.0,4573,40,0.00254309,0.002555837318295739,false,"roi"],["ADA/BTC",-0.0,1516935300.0,1516979400.0,4583,735,5.607e-05,5.6351052631578935e-05,false,"roi"],["ETC/BTC",0.0,1516947000.0,1516958700.0,4622,195,0.00253806,0.0025507821052631577,false,"roi"],["ZEC/BTC",-0.0,1516951500.0,1516960500.0,4637,150,0.0415,0.04170802005012531,false,"roi"],["XLM/BTC",0.00997506,1516960500.0,1516962300.0,4667,30,5.321e-05,5.401015037593984e-05,false,"roi"],["XMR/BTC",-0.0,1516982700.0,1516985100.0,4741,40,0.02772046,0.02785940967418546,false,"roi"],["ETH/BTC",0.0,1517009700.0,1517012100.0,4831,40,0.09461341,0.09508766268170425,false,"roi"],["XLM/BTC",-0.0,1517013300.0,1517016600.0,4843,55,5.615e-05,5.643145363408521e-05,false,"roi"],["ADA/BTC",-0.07877175,1517013900.0,1517287500.0,4845,4560,5.556e-05,5.144e-05,true,"force_sell"],["DASH/BTC",-0.0,1517020200.0,1517052300.0,4866,535,0.06900001,0.06934587471177944,false,"roi"],["ETH/BTC",-0.0,1517034300.0,1517036700.0,4913,40,0.09449985,0.09497353345864659,false,"roi"],["ZEC/BTC",-0.04815133,1517046000.0,1517287200.0,4952,4020,0.0410697,0.03928809,true,"force_sell"],["XMR/BTC",-0.0,1517053500.0,1517056200.0,4977,45,0.0285,0.02864285714285714,false,"roi"],["XMR/BTC",-0.0,1517056500.0,1517066700.0,4987,170,0.02866372,0.02880739779448621,false,"roi"],["ETH/BTC",-0.0,1517068200.0,1517071800.0,5026,60,0.095381,0.09585910025062655,false,"roi"],["DASH/BTC",-0.0,1517072700.0,1517075100.0,5041,40,0.06759092,0.06792972160401002,false,"roi"],["ETC/BTC",-0.0,1517096400.0,1517101500.0,5120,85,0.00258501,0.002597967443609022,false,"roi"],["DASH/BTC",-0.0,1517106300.0,1517127000.0,5153,345,0.06698502,0.0673207845112782,false,"roi"],["DASH/BTC",-0.0,1517135100.0,1517157000.0,5249,365,0.0677177,0.06805713709273183,false,"roi"],["XLM/BTC",0.0,1517171700.0,1517175300.0,5371,60,5.215e-05,5.2411403508771925e-05,false,"roi"],["ETC/BTC",0.00997506,1517176800.0,1517178600.0,5388,30,0.00273809,0.002779264285714285,false,"roi"],["ETC/BTC",0.00997506,1517184000.0,1517185800.0,5412,30,0.00274632,0.002787618045112782,false,"roi"],["LTC/BTC",0.0,1517192100.0,1517194800.0,5439,45,0.01622478,0.016306107218045113,false,"roi"],["DASH/BTC",-0.0,1517195100.0,1517197500.0,5449,40,0.069,0.06934586466165413,false,"roi"],["TRX/BTC",-0.0,1517203200.0,1517208900.0,5476,95,8.755e-05,8.798884711779448e-05,false,"roi"],["DASH/BTC",-0.0,1517209200.0,1517253900.0,5496,745,0.06825763,0.06859977350877192,false,"roi"],["DASH/BTC",-0.0,1517255100.0,1517257500.0,5649,40,0.06713892,0.06747545593984962,false,"roi"],["TRX/BTC",-0.0199116,1517268600.0,1517287500.0,5694,315,8.934e-05,8.8e-05,true,"force_sell"]]
diff --git a/freqtrade/tests/testdata/pairs.json b/tests/testdata/pairs.json
similarity index 95%
rename from freqtrade/tests/testdata/pairs.json
rename to tests/testdata/pairs.json
index f4bab6dc5..15aae2643 100644
--- a/freqtrade/tests/testdata/pairs.json
+++ b/tests/testdata/pairs.json
@@ -9,7 +9,7 @@
     "LTC/BTC",
     "NEO/BTC",
     "NXT/BTC",
-    "POWR/BTC",
+    "TRX/BTC",
     "STORJ/BTC",
     "QTUM/BTC",
     "WAVES/BTC",
diff --git a/user_data/backtest_results/.gitkeep b/user_data/backtest_results/.gitkeep
new file mode 100644
index 000000000..e69de29bb
diff --git a/user_data/hyperopts/.gitkeep b/user_data/hyperopts/.gitkeep
new file mode 100644
index 000000000..e69de29bb
diff --git a/user_data/logs/.gitkeep b/user_data/logs/.gitkeep
new file mode 100644
index 000000000..e69de29bb
diff --git a/user_data/notebooks/.gitkeep b/user_data/notebooks/.gitkeep
new file mode 100644
index 000000000..e69de29bb
diff --git a/user_data/strategies/.gitkeep b/user_data/strategies/.gitkeep
new file mode 100644
index 000000000..e69de29bb
diff --git a/user_data/strategies/test_strategy.py b/user_data/strategies/test_strategy.py
deleted file mode 100644
index d8ff790b2..000000000
--- a/user_data/strategies/test_strategy.py
+++ /dev/null
@@ -1,302 +0,0 @@
-
-# --- Do not remove these libs ---
-from freqtrade.strategy.interface import IStrategy
-from pandas import DataFrame
-# --------------------------------
-
-# Add your lib to import here
-import talib.abstract as ta
-import freqtrade.vendor.qtpylib.indicators as qtpylib
-import numpy  # noqa
-
-
-# This class is a sample. Feel free to customize it.
-class TestStrategy(IStrategy):
-    __test__ = False  # pytest expects to find tests here because of the name
-    """
-    This is a test strategy to inspire you.
-    More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md
-
-    You can:
-        :return: a Dataframe with all mandatory indicators for the strategies
-    - Rename the class name (Do not forget to update class_name)
-    - Add any methods you want to build your strategy
-    - Add any lib you need to build your strategy
-
-    You must keep:
-    - the lib in the section "Do not remove these libs"
-    - the prototype for the methods: minimal_roi, stoploss, populate_indicators, populate_buy_trend,
-    populate_sell_trend, hyperopt_space, buy_strategy_generator
-    """
-
-    # Minimal ROI designed for the strategy.
-    # This attribute will be overridden if the config file contains "minimal_roi"
-    minimal_roi = {
-        "40": 0.0,
-        "30": 0.01,
-        "20": 0.02,
-        "0": 0.04
-    }
-
-    # Optimal stoploss designed for the strategy
-    # This attribute will be overridden if the config file contains "stoploss"
-    stoploss = -0.10
-
-    # trailing stoploss
-    trailing_stop = False
-    # trailing_stop_positive = 0.01
-    # trailing_stop_positive_offset = 0.0  # Disabled / not configured
-
-    # Optimal ticker interval for the strategy
-    ticker_interval = '5m'
-
-    # run "populate_indicators" only for new candle
-    process_only_new_candles = False
-
-    # Experimental settings (configuration will overide these if set)
-    use_sell_signal = False
-    sell_profit_only = False
-    ignore_roi_if_buy_signal = False
-
-    # Optional order type mapping
-    order_types = {
-        'buy': 'limit',
-        'sell': 'limit',
-        'stoploss': 'market',
-        'stoploss_on_exchange': False
-    }
-
-    # Optional order time in force
-    order_time_in_force = {
-        'buy': 'gtc',
-        'sell': 'gtc'
-    }
-
-    def informative_pairs(self):
-        """
-        Define additional, informative pair/interval combinations to be cached from the exchange.
-        These pair/interval combinations are non-tradeable, unless they are part
-        of the whitelist as well.
-        For more information, please consult the documentation
-        :return: List of tuples in the format (pair, interval)
-            Sample: return [("ETH/USDT", "5m"),
-                            ("BTC/USDT", "15m"),
-                            ]
-        """
-        return []
-
-    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-        """
-        Adds several different TA indicators to the given DataFrame
-
-        Performance Note: For the best performance be frugal on the number of indicators
-        you are using. Let uncomment only the indicator you are using in your strategies
-        or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
-        :param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
-        :param metadata: Additional information, like the currently traded pair
-        :return: a Dataframe with all mandatory indicators for the strategies
-        """
-
-        # Momentum Indicator
-        # ------------------------------------
-
-        # ADX
-        dataframe['adx'] = ta.ADX(dataframe)
-
-        """
-        # Awesome oscillator
-        dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
-
-        # Commodity Channel Index: values Oversold:<-100, Overbought:>100
-        dataframe['cci'] = ta.CCI(dataframe)
-
-        # MACD
-        macd = ta.MACD(dataframe)
-        dataframe['macd'] = macd['macd']
-        dataframe['macdsignal'] = macd['macdsignal']
-        dataframe['macdhist'] = macd['macdhist']
-
-        # MFI
-        dataframe['mfi'] = ta.MFI(dataframe)
-
-        # Minus Directional Indicator / Movement
-        dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
-        dataframe['minus_di'] = ta.MINUS_DI(dataframe)
-
-        # Plus Directional Indicator / Movement
-        dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
-        dataframe['plus_di'] = ta.PLUS_DI(dataframe)
-        dataframe['minus_di'] = ta.MINUS_DI(dataframe)
-
-        # ROC
-        dataframe['roc'] = ta.ROC(dataframe)
-
-        # RSI
-        dataframe['rsi'] = ta.RSI(dataframe)
-
-        # Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
-        rsi = 0.1 * (dataframe['rsi'] - 50)
-        dataframe['fisher_rsi'] = (numpy.exp(2 * rsi) - 1) / (numpy.exp(2 * rsi) + 1)
-
-        # Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
-        dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
-
-        # Stoch
-        stoch = ta.STOCH(dataframe)
-        dataframe['slowd'] = stoch['slowd']
-        dataframe['slowk'] = stoch['slowk']
-
-        # Stoch fast
-        stoch_fast = ta.STOCHF(dataframe)
-        dataframe['fastd'] = stoch_fast['fastd']
-        dataframe['fastk'] = stoch_fast['fastk']
-
-        # Stoch RSI
-        stoch_rsi = ta.STOCHRSI(dataframe)
-        dataframe['fastd_rsi'] = stoch_rsi['fastd']
-        dataframe['fastk_rsi'] = stoch_rsi['fastk']
-        """
-
-        # Overlap Studies
-        # ------------------------------------
-
-        # Bollinger bands
-        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
-        dataframe['bb_lowerband'] = bollinger['lower']
-        dataframe['bb_middleband'] = bollinger['mid']
-        dataframe['bb_upperband'] = bollinger['upper']
-
-        """
-        # EMA - Exponential Moving Average
-        dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3)
-        dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
-        dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
-        dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
-        dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
-
-        # SAR Parabol
-        dataframe['sar'] = ta.SAR(dataframe)
-
-        # SMA - Simple Moving Average
-        dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
-        """
-
-        # TEMA - Triple Exponential Moving Average
-        dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
-
-        # Cycle Indicator
-        # ------------------------------------
-        # Hilbert Transform Indicator - SineWave
-        hilbert = ta.HT_SINE(dataframe)
-        dataframe['htsine'] = hilbert['sine']
-        dataframe['htleadsine'] = hilbert['leadsine']
-
-        # Pattern Recognition - Bullish candlestick patterns
-        # ------------------------------------
-        """
-        # Hammer: values [0, 100]
-        dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
-        # Inverted Hammer: values [0, 100]
-        dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
-        # Dragonfly Doji: values [0, 100]
-        dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
-        # Piercing Line: values [0, 100]
-        dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
-        # Morningstar: values [0, 100]
-        dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
-        # Three White Soldiers: values [0, 100]
-        dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
-        """
-
-        # Pattern Recognition - Bearish candlestick patterns
-        # ------------------------------------
-        """
-        # Hanging Man: values [0, 100]
-        dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
-        # Shooting Star: values [0, 100]
-        dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
-        # Gravestone Doji: values [0, 100]
-        dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
-        # Dark Cloud Cover: values [0, 100]
-        dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
-        # Evening Doji Star: values [0, 100]
-        dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
-        # Evening Star: values [0, 100]
-        dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
-        """
-
-        # Pattern Recognition - Bullish/Bearish candlestick patterns
-        # ------------------------------------
-        """
-        # Three Line Strike: values [0, -100, 100]
-        dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
-        # Spinning Top: values [0, -100, 100]
-        dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
-        # Engulfing: values [0, -100, 100]
-        dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
-        # Harami: values [0, -100, 100]
-        dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
-        # Three Outside Up/Down: values [0, -100, 100]
-        dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
-        # Three Inside Up/Down: values [0, -100, 100]
-        dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
-        """
-
-        # Chart type
-        # ------------------------------------
-        """
-        # Heikinashi stategy
-        heikinashi = qtpylib.heikinashi(dataframe)
-        dataframe['ha_open'] = heikinashi['open']
-        dataframe['ha_close'] = heikinashi['close']
-        dataframe['ha_high'] = heikinashi['high']
-        dataframe['ha_low'] = heikinashi['low']
-        """
-
-        # Retrieve best bid and best ask
-        # ------------------------------------
-        """
-        # first check if dataprovider is available 
-        if self.dp:
-            if self.dp.runmode in ('live', 'dry_run'):
-                ob = self.dp.orderbook(metadata['pair'], 1)
-                dataframe['best_bid'] = ob['bids'][0][0]
-                dataframe['best_ask'] = ob['asks'][0][0]
-        """
-        
-        return dataframe
-
-    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-        """
-        Based on TA indicators, populates the buy signal for the given dataframe
-        :param dataframe: DataFrame populated with indicators
-        :param metadata: Additional information, like the currently traded pair
-        :return: DataFrame with buy column
-        """
-        dataframe.loc[
-            (
-                (dataframe['adx'] > 30) &
-                (dataframe['tema'] <= dataframe['bb_middleband']) &
-                (dataframe['tema'] > dataframe['tema'].shift(1)) &
-                (dataframe['volume'] > 0)  # Make sure Volume is not 0
-            ),
-            'buy'] = 1
-
-        return dataframe
-
-    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-        """
-        Based on TA indicators, populates the sell signal for the given dataframe
-        :param dataframe: DataFrame populated with indicators
-        :param metadata: Additional information, like the currently traded pair
-        :return: DataFrame with buy column
-        """
-        dataframe.loc[
-            (
-                (dataframe['adx'] > 70) &
-                (dataframe['tema'] > dataframe['bb_middleband']) &
-                (dataframe['tema'] < dataframe['tema'].shift(1)) &
-                (dataframe['volume'] > 0)  # Make sure Volume is not 0
-            ),
-            'sell'] = 1
-        return dataframe