freqtrade

Simple High frequency trading bot for crypto currencies designed to support multi exchanges and be controlled via Telegram.

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.

Always start by running a trading bot in Dry-run and do not engage money before you understand how it works and what profit/loss you should expect.

We strongly recommend you to have coding and Python knowledge. Do not hesitate to read the source code and understand the mechanism of this bot.

Exchange marketplaces supported

• Bittrex
• Binance
• 113 others to tests. (We cannot guarantee they will work)

Features

• Based on Python 3.6+: For botting on any operating system - Windows, macOS and Linux
• Persistence: Persistence is achieved through sqlite
• Dry-run: Run the bot without playing money.
• Backtesting: Run a simulation of your buy/sell strategy.
• Strategy Optimization by machine learning: Use machine learning to optimize your buy/sell strategy parameters with real exchange data.
• Whitelist crypto-currencies: Select which crypto-currency you want to trade.
• Blacklist crypto-currencies: Select which crypto-currency you want to avoid.
• Manageable via Telegram: Manage the bot with Telegram
• Display profit/loss in fiat: Display your profit/loss in 33 fiat.
• Daily summary of profit/loss: Provide a daily summary of your profit/loss.
• Performance status report: Provide a performance status of your current trades.

Table of Contents

• Quick start
• Documentations
  • Installation
  • Configuration
  • Strategy Optimization
  • Backtesting
  • Hyperopt
• Basic Usage
  • Bot commands
  • Telegram RPC commands
• Support
  • Help
  • Bugs
  • Feature Requests
  • Pull Requests
• Requirements
  • Min hardware required
  • Software requirements

Quick start

Freqtrade provides a Linux/macOS script to install all dependencies and help you to configure the bot.

git clone git@github.com:freqtrade/freqtrade.git
git checkout develop
cd freqtrade
./setup.sh --install

Windows installation is explained in Installation doc

Documentation

We invite you to read the bot documentation to ensure you understand how the bot is working.

• Index
• Installation
• Configuration
• Bot usage
  • How to run the bot
  • How to use Backtesting
  • How to use Hyperopt
• Strategy Optimization
• Backtesting
• Hyperopt

Basic Usage

Bot commands

usage: main.py [-h] [-v] [--version] [-c PATH] [-d PATH] [-s NAME]
               [--strategy-path PATH] [--dynamic-whitelist [INT]]
               [--dry-run-db]
               {backtesting,hyperopt} ...

Simple High Frequency Trading Bot for crypto currencies

positional arguments:
  {backtesting,hyperopt}
    backtesting         backtesting module
    hyperopt            hyperopt module

optional arguments:
  -h, --help            show this help message and exit
  -v, --verbose         be verbose
  --version             show program's version number and exit
  -c PATH, --config PATH
                        specify configuration file (default: config.json)
  -d PATH, --datadir PATH
                        path to backtest data (default:
                        freqtrade/tests/testdata
  -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 currencies)
  --dry-run-db          Force dry run to use a local DB
                        "tradesv3.dry_run.sqlite" instead of memory DB. Work
                        only if dry_run is enabled.

Telegram RPC commands

Telegram is not mandatory. However, this is a great way to control your bot. More details on our documentation

• /start: Starts the trader
• /stop: Stops the trader
• /status [table]: Lists all open trades
• /count: Displays number of 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

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.

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.

• Click here to join Slack channel.

Bugs / Issues

If you discover a bug in the bot, please search our issue tracker first. If it hasn't been reported, please create a new issue and ensure you follow the template guide so that our team can assist you as quickly as possible.

Feature Requests

Have you a great idea to improve the bot you want to share? Please, first search if this feature was not already discussed. If it hasn't been requested, please create a new request and ensure you follow the template guide so that it does not get lost in the bug reports.

Pull Requests

Feel like our bot is missing a feature? We welcome your pull requests! Please read our Contributing document to understand the requirements before sending your pull-requests.

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. 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.

Requirements

Min hardware required

To run this bot we recommend you a cloud instance with a minimum of:

• Minimal (advised) system requirements: 2GB RAM, 1GB disk space, 2vCPU

Software requirements

• Python 3.6.x
• pip
• git
• TA-Lib
• virtualenv (Recommended)
• Docker (Recommended)