diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 15f64ad38..407894bd2 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -20,7 +20,7 @@ jobs:
     strategy:
       matrix:
         os: [ ubuntu-18.04, ubuntu-20.04 ]
-        python-version: ["3.7", "3.8", "3.9", "3.10"]
+        python-version: ["3.8", "3.9", "3.10"]
 
     steps:
     - uses: actions/checkout@v2
@@ -115,7 +115,7 @@ jobs:
     strategy:
       matrix:
         os: [ macos-latest ]
-        python-version: ["3.7", "3.8", "3.9", "3.10"]
+        python-version: ["3.8", "3.9", "3.10"]
 
     steps:
     - uses: actions/checkout@v2
@@ -207,7 +207,7 @@ jobs:
     strategy:
       matrix:
         os: [ windows-latest ]
-        python-version: ["3.7", "3.8", "3.9", "3.10"]
+        python-version: ["3.8", "3.9", "3.10"]
 
     steps:
     - uses: actions/checkout@v2
diff --git a/README.md b/README.md
index 3a7d42fe9..b67e16010 100644
--- a/README.md
+++ b/README.md
@@ -49,7 +49,7 @@ Please find the complete documentation on the [freqtrade website](https://www.fr
 
 ## Features
 
-- [x] **Based on Python 3.7+**: For botting on any operating system - Windows, macOS and Linux.
+- [x] **Based on Python 3.8+**: For botting on any operating system - Windows, macOS and Linux.
 - [x] **Persistence**: Persistence is achieved through sqlite.
 - [x] **Dry-run**: Run the bot without paying money.
 - [x] **Backtesting**: Run a simulation of your buy/sell strategy.
@@ -197,7 +197,7 @@ To run this bot we recommend you a cloud instance with a minimum of:
 
 ### Software requirements
 
-- [Python >= 3.7](http://docs.python-guide.org/en/latest/starting/installation/)
+- [Python >= 3.8](http://docs.python-guide.org/en/latest/starting/installation/)
 - [pip](https://pip.pypa.io/en/stable/installing/)
 - [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
 - [TA-Lib](https://mrjbq7.github.io/ta-lib/install.html)
diff --git a/build_helpers/TA_Lib-0.4.24-cp37-cp37m-win_amd64.whl b/build_helpers/TA_Lib-0.4.24-cp37-cp37m-win_amd64.whl
deleted file mode 100644
index ee8d64c6e..000000000
Binary files a/build_helpers/TA_Lib-0.4.24-cp37-cp37m-win_amd64.whl and /dev/null differ
diff --git a/build_helpers/install_windows.ps1 b/build_helpers/install_windows.ps1
index de1b1d597..4caefa340 100644
--- a/build_helpers/install_windows.ps1
+++ b/build_helpers/install_windows.ps1
@@ -5,9 +5,6 @@ python -m pip install --upgrade pip wheel
 
 $pyv = python -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')"
 
-if ($pyv -eq '3.7') {
-    pip install build_helpers\TA_Lib-0.4.24-cp37-cp37m-win_amd64.whl
-}
 if ($pyv -eq '3.8') {
     pip install build_helpers\TA_Lib-0.4.24-cp38-cp38-win_amd64.whl
 }
diff --git a/docs/advanced-hyperopt.md b/docs/advanced-hyperopt.md
index 9ac31bf16..9dbb86b2d 100644
--- a/docs/advanced-hyperopt.md
+++ b/docs/advanced-hyperopt.md
@@ -105,7 +105,7 @@ You can define your own estimator for Hyperopt by implementing `generate_estimat
 ```python
 class MyAwesomeStrategy(IStrategy):
     class HyperOpt:
-        def generate_estimator():
+        def generate_estimator(dimensions: List['Dimension'], **kwargs):
             return "RF"
 
 ```
@@ -119,13 +119,34 @@ Example for `ExtraTreesRegressor` ("ET") with additional parameters:
 ```python
 class MyAwesomeStrategy(IStrategy):
     class HyperOpt:
-        def generate_estimator():
+        def generate_estimator(dimensions: List['Dimension'], **kwargs):
             from skopt.learning import ExtraTreesRegressor
             # Corresponds to "ET" - but allows additional parameters.
             return ExtraTreesRegressor(n_estimators=100)
 
 ```
 
+The `dimensions` parameter is the list of `skopt.space.Dimension` objects corresponding to the parameters to be optimized. It can be used to create isotropic kernels for the `skopt.learning.GaussianProcessRegressor` estimator. Here's an example:
+
+```python
+class MyAwesomeStrategy(IStrategy):
+    class HyperOpt:
+        def generate_estimator(dimensions: List['Dimension'], **kwargs):
+            from skopt.utils import cook_estimator
+            from skopt.learning.gaussian_process.kernels import (Matern, ConstantKernel)
+            kernel_bounds = (0.0001, 10000)
+            kernel = (
+                ConstantKernel(1.0, kernel_bounds) * 
+                Matern(length_scale=np.ones(len(dimensions)), length_scale_bounds=[kernel_bounds for d in dimensions], nu=2.5)
+            )
+            kernel += (
+                ConstantKernel(1.0, kernel_bounds) * 
+                Matern(length_scale=np.ones(len(dimensions)), length_scale_bounds=[kernel_bounds for d in dimensions], nu=1.5)
+            )
+
+            return cook_estimator("GP", space=dimensions, kernel=kernel, n_restarts_optimizer=2)
+```
+
 !!! Note
     While custom estimators can be provided, it's up to you as User to do research on possible parameters and analyze / understand which ones should be used.
     If you're unsure about this, best use one of the Defaults (`"ET"` has proven to be the most versatile) without further parameters.
diff --git a/docs/configuration.md b/docs/configuration.md
index 8b6f34c3b..4cb09eb08 100644
--- a/docs/configuration.md
+++ b/docs/configuration.md
@@ -175,6 +175,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `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
 | `position_adjustment_enable` | Enables the strategy to use position adjustments (additional buys or sells). [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.*<br> **Datatype:** Boolean
+| `max_entry_position_adjustment` | Maximum additional order(s) for each open trade on top of the first entry Order. Set it to `-1` for unlimited additional orders. [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `-1`.*<br> **Datatype:** Positive Integer or -1
 
 ### Parameters in the strategy
 
@@ -200,6 +201,7 @@ Values set in the configuration file always overwrite values set in the strategy
 * `ignore_roi_if_buy_signal`
 * `ignore_buying_expired_candle_after`
 * `position_adjustment_enable`
+* `max_entry_position_adjustment`
 
 ### Configuring amount per trade
 
diff --git a/docs/docker_quickstart.md b/docs/docker_quickstart.md
index 95df37811..84c1d596a 100644
--- a/docs/docker_quickstart.md
+++ b/docs/docker_quickstart.md
@@ -126,6 +126,12 @@ All freqtrade arguments will be available by running `docker-compose run --rm fr
 !!! Note "`docker-compose run --rm`"
     Including `--rm` will remove the container after completion, and is highly recommended for all modes except trading mode (running with `freqtrade trade` command).
 
+??? Note "Using docker without docker-compose"
+    "`docker-compose run --rm`" will require a compose file to be provided.
+    Some freqtrade commands that don't require authentication such as `list-pairs` can be run with "`docker run --rm`" instead.  
+    For example `docker run --rm freqtradeorg/freqtrade:stable list-pairs --exchange binance --quote BTC --print-json`.  
+    This can be useful for fetching exchange information to add to your `config.json` without affecting your running containers.
+
 #### 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.
diff --git a/docs/index.md b/docs/index.md
index 292955346..1f8f15704 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -11,7 +11,7 @@
 
 ## Introduction
 
-Freqtrade is a crypto-currency algorithmic trading software developed in python (3.7+) and supported on Windows, macOS and Linux.
+Freqtrade is a crypto-currency algorithmic trading software developed in python (3.8+) 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.
@@ -67,7 +67,7 @@ To run this bot we recommend you a linux cloud instance with a minimum of:
 
 Alternatively
 
-- Python 3.7+
+- Python 3.8+
 - pip (pip3)
 - git
 - TA-Lib
diff --git a/docs/installation.md b/docs/installation.md
index c67eff60b..2a1c3db0a 100644
--- a/docs/installation.md
+++ b/docs/installation.md
@@ -42,7 +42,7 @@ These requirements apply to both [Script Installation](#script-installation) and
 
 ### Install guide
 
-* [Python >= 3.7.x](http://docs.python-guide.org/en/latest/starting/installation/)
+* [Python >= 3.8.x](http://docs.python-guide.org/en/latest/starting/installation/)
 * [pip](https://pip.pypa.io/en/stable/installing/)
 * [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
 * [virtualenv](https://virtualenv.pypa.io/en/stable/installation.html) (Recommended)
diff --git a/docs/requirements-docs.txt b/docs/requirements-docs.txt
index 15124b543..0368c90ff 100644
--- a/docs/requirements-docs.txt
+++ b/docs/requirements-docs.txt
@@ -1,4 +1,4 @@
 mkdocs==1.2.3
-mkdocs-material==8.1.7
+mkdocs-material==8.1.8
 mdx_truly_sane_lists==1.2
 pymdown-extensions==9.1
diff --git a/docs/strategy-callbacks.md b/docs/strategy-callbacks.md
index 16e412a32..b441f5180 100644
--- a/docs/strategy-callbacks.md
+++ b/docs/strategy-callbacks.md
@@ -363,8 +363,8 @@ class AwesomeStrategy(IStrategy):
 
     # ... populate_* methods
 
-    def custom_entry_price(self, pair: str, current_time: datetime,
-                           proposed_rate, **kwargs) -> float:
+    def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float, 
+                           entry_tag: Optional[str], **kwargs) -> float:
 
         dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
                                                                 timeframe=self.timeframe)
@@ -414,7 +414,7 @@ It applies a tight timeout for higher priced assets, while allowing more time to
 The function must return either `True` (cancel order) or `False` (keep order alive).
 
 ``` python
-from datetime import datetime, timedelta, timezone
+from datetime import datetime, timedelta
 from freqtrade.persistence import Trade
 
 class AwesomeStrategy(IStrategy):
@@ -427,22 +427,24 @@ class AwesomeStrategy(IStrategy):
         '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_utc < datetime.now(timezone.utc) - timedelta(minutes=5):
+    def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict, 
+                          current_time: datetime, **kwargs) -> bool:
+        if trade.open_rate > 100 and trade.open_date_utc < current_time - timedelta(minutes=5):
             return True
-        elif trade.open_rate > 10 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=3):
+        elif trade.open_rate > 10 and trade.open_date_utc < current_time - timedelta(minutes=3):
             return True
-        elif trade.open_rate < 1 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(hours=24):
+        elif trade.open_rate < 1 and trade.open_date_utc < current_time - 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_utc < datetime.now(timezone.utc) - timedelta(minutes=5):
+    def check_sell_timeout(self, pair: str, trade: Trade, order: dict,
+                           current_time: datetime, **kwargs) -> bool:
+        if trade.open_rate > 100 and trade.open_date_utc < current_time - timedelta(minutes=5):
             return True
-        elif trade.open_rate > 10 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=3):
+        elif trade.open_rate > 10 and trade.open_date_utc < current_time - timedelta(minutes=3):
             return True
-        elif trade.open_rate < 1 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(hours=24):
+        elif trade.open_rate < 1 and trade.open_date_utc < current_time - timedelta(hours=24):
            return True
         return False
 ```
@@ -501,7 +503,7 @@ class AwesomeStrategy(IStrategy):
     # ... populate_* methods
 
     def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
-                            time_in_force: str, current_time: datetime,
+                            time_in_force: str, current_time: datetime, entry_tag: Optional[str], 
                             side: str, **kwargs) -> bool:
         """
         Called right before placing a entry order.
@@ -579,11 +581,13 @@ The `position_adjustment_enable` strategy property enables the usage of `adjust_
 For performance reasons, it's disabled by default and freqtrade will show a warning message on startup if enabled.
 `adjust_trade_position()` can be used to perform additional orders, for example to manage risk with DCA (Dollar Cost Averaging).
 
+`max_entry_position_adjustment` property is used to limit the number of additional buys per trade (on top of the first buy) that the bot can execute. By default, the value is -1 which means the bot have no limit on number of adjustment buys.
+
 The strategy is expected to return a stake_amount (in stake currency) between `min_stake` and `max_stake` if and when an additional buy order should be made (position is increased).
 If there are not enough funds in the wallet (the return value is above `max_stake`) then the signal will be ignored.
 Additional orders also result in additional fees and those orders don't count towards `max_open_trades`.
 
-This callback is **not** called when there is an open order (either buy or sell) waiting for execution.
+This callback is **not** called when there is an open order (either buy or sell) waiting for execution, or when you have reached the maximum amount of extra buys that you have set on `max_entry_position_adjustment`.
 `adjust_trade_position()` is called very frequently for the duration of a trade, so you must keep your implementation as performant as possible.
 
 !!! Note "About stake size"
@@ -614,14 +618,14 @@ class DigDeeperStrategy(IStrategy):
     # ... populate_* methods
     
     # Example specific variables
-    max_dca_orders = 3
+    max_entry_position_adjustment = 3
     # This number is explained a bit further down
     max_dca_multiplier = 5.5
     
     # This is called when placing the initial order (opening trade)
     def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
                             proposed_stake: float, min_stake: float, max_stake: float,
-                            **kwargs) -> float:
+                            entry_tag: Optional[str], **kwargs) -> float:
         
         # We need to leave most of the funds for possible further DCA orders
         # This also applies to fixed stakes
@@ -656,8 +660,7 @@ class DigDeeperStrategy(IStrategy):
             return None
 
         filled_buys = trade.select_filled_orders('buy')
-        count_of_buys = len(filled_buys)
-        
+        count_of_buys = trade.nr_of_successful_buys
         # Allow up to 3 additional increasingly larger buys (4 in total)
         # Initial buy is 1x
         # If that falls to -5% profit, we buy 1.25x more, average profit should increase to roughly -2.2%
@@ -666,15 +669,14 @@ class DigDeeperStrategy(IStrategy):
         # Total stake for this trade would be 1 + 1.25 + 1.5 + 1.75 = 5.5x of the initial allowed stake.
         # That is why max_dca_multiplier is 5.5
         # Hope you have a deep wallet!
-        if 0 < count_of_buys <= self.max_dca_orders:
-            try:
-                # This returns first order stake size
-                stake_amount = filled_buys[0].cost
-                # This then calculates current safety order size
-                stake_amount = stake_amount * (1 + (count_of_buys * 0.25))
-                return stake_amount
-            except Exception as exception:
-                return None
+        try:
+            # This returns first order stake size
+            stake_amount = filled_buys[0].cost
+            # This then calculates current safety order size
+            stake_amount = stake_amount * (1 + (count_of_buys * 0.25))
+            return stake_amount
+        except Exception as exception:
+            return None
 
         return None
 
diff --git a/docs/windows_installation.md b/docs/windows_installation.md
index 0832b753c..9a068e152 100644
--- a/docs/windows_installation.md
+++ b/docs/windows_installation.md
@@ -25,7 +25,7 @@ Install ta-lib according to the [ta-lib documentation](https://github.com/mrjbq7
 
 As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial pre-compiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which need to be downloaded and installed using `pip install TA_Lib-0.4.24-cp38-cp38-win_amd64.whl` (make sure to use the version matching your python version).
 
-Freqtrade provides these dependencies for the latest 3 Python versions (3.7, 3.8, 3.9 and 3.10) and for 64bit Windows.
+Freqtrade provides these dependencies for the latest 3 Python versions (3.8, 3.9 and 3.10) and for 64bit Windows.
 Other versions must be downloaded from the above link.
 
 ``` powershell
diff --git a/environment.yml b/environment.yml
index 5f67ccb16..f2f961894 100644
--- a/environment.yml
+++ b/environment.yml
@@ -4,7 +4,7 @@ channels:
 # - defaults
 dependencies:
 # 1/4 req main
-    - python>=3.7,<3.9
+    - python>=3.8,<=3.10
     - numpy
     - pandas
     - pip
@@ -25,10 +25,14 @@ dependencies:
     - fastapi
     - uvicorn
     - pyjwt
+    - aiofiles
+    - psutil
     - colorama
     - questionary
     - prompt-toolkit
     - schedule
+    - python-dateutil
+
 
     # ============================
     # 2/4 req dev
diff --git a/freqtrade/__main__.py b/freqtrade/__main__.py
index ab4c7a110..fc45bdf61 100644
--- a/freqtrade/__main__.py
+++ b/freqtrade/__main__.py
@@ -3,7 +3,7 @@
 __main__.py for Freqtrade
 To launch Freqtrade as a module
 
-> python -m freqtrade (with Python >= 3.7)
+> python -m freqtrade (with Python >= 3.8)
 """
 
 from freqtrade import main
diff --git a/freqtrade/constants.py b/freqtrade/constants.py
index 256b2e21d..0f841e2a7 100644
--- a/freqtrade/constants.py
+++ b/freqtrade/constants.py
@@ -377,7 +377,9 @@ CONF_SCHEMA = {
             'type': 'string',
             'enum': AVAILABLE_DATAHANDLERS,
             'default': 'jsongz'
-        }
+        },
+        'position_adjustment_enable': {'type': 'boolean'},
+        'max_entry_position_adjustment': {'type': ['integer', 'number'], 'minimum': -1},
     },
     'definitions': {
         'exchange': {
diff --git a/freqtrade/exchange/exchange.py b/freqtrade/exchange/exchange.py
index e943ea81c..d37effefb 100644
--- a/freqtrade/exchange/exchange.py
+++ b/freqtrade/exchange/exchange.py
@@ -1114,7 +1114,7 @@ class Exchange:
             raise OperationalException(e) from e
 
     @retrier
-    def get_tickers(self, cached: bool = False) -> Dict:
+    def get_tickers(self, symbols: List[str] = None, cached: bool = False) -> Dict:
         """
         :param cached: Allow cached result
         :return: fetch_tickers result
@@ -1124,7 +1124,7 @@ class Exchange:
             if tickers:
                 return tickers
         try:
-            tickers = self._api.fetch_tickers()
+            tickers = self._api.fetch_tickers(symbols)
             self._fetch_tickers_cache['fetch_tickers'] = tickers
             return tickers
         except ccxt.NotSupported as e:
diff --git a/freqtrade/exchange/kraken.py b/freqtrade/exchange/kraken.py
index 7c67d870d..d96f171e1 100644
--- a/freqtrade/exchange/kraken.py
+++ b/freqtrade/exchange/kraken.py
@@ -43,6 +43,12 @@ class Kraken(Exchange):
         return (parent_check and
                 market.get('darkpool', False) is False)
 
+    def get_tickers(self, symbols: List[str] = None, cached: bool = False) -> Dict:
+        # Only fetch tickers for current stake currency
+        # Otherwise the request for kraken becomes too large.
+        symbols = list(self.get_markets(quote_currencies=[self._config['stake_currency']]))
+        return super().get_tickers(symbols=symbols, cached=cached)
+
     @retrier
     def get_balances(self) -> dict:
         if self._config['dry_run']:
diff --git a/freqtrade/freqtradebot.py b/freqtrade/freqtradebot.py
index 7b7508854..113c78a15 100644
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@@ -9,7 +9,6 @@ from math import isclose
 from threading import Lock
 from typing import Any, Dict, List, Optional, Tuple
 
-import arrow
 from schedule import Scheduler
 
 from freqtrade import __version__, constants
@@ -521,8 +520,8 @@ class FreqtradeBot(LoggingMixin):
                 try:
                     self.check_and_call_adjust_trade_position(trade)
                 except DependencyException as exception:
-                    logger.warning('Unable to adjust position of trade for %s: %s',
-                                   trade.pair, exception)
+                    logger.warning(
+                        f"Unable to adjust position of trade for {trade.pair}: {exception}")
 
     def check_and_call_adjust_trade_position(self, trade: Trade):
         """
@@ -531,6 +530,13 @@ class FreqtradeBot(LoggingMixin):
         Once that completes, the existing trade is modified to match new data.
         """
         # TODO-lev: Check what changes are necessary for DCA in relation to shorts.
+        if self.strategy.max_entry_position_adjustment > -1:
+            count_of_buys = trade.nr_of_successful_buys
+            if count_of_buys > self.strategy.max_entry_position_adjustment:
+                logger.debug(f"Max adjustment entries for {trade.pair} has been reached.")
+                return
+        else:
+            logger.debug("Max adjustment entries is set to unlimited.")
         current_rate = self.exchange.get_rate(trade.pair, refresh=True, side="buy")
         current_profit = trade.calc_profit_ratio(current_rate)
 
@@ -649,7 +655,7 @@ class FreqtradeBot(LoggingMixin):
         pos_adjust = trade is not None
 
         enter_limit_requested, stake_amount = self.get_valid_enter_price_and_stake(
-            pair, price, stake_amount, side, trade_side, trade)
+            pair, price, stake_amount, side, trade_side, enter_tag, trade)
 
         if not stake_amount:
             return False
@@ -680,8 +686,7 @@ class FreqtradeBot(LoggingMixin):
                 self.strategy.confirm_trade_entry, default_retval=True)(
                 pair=pair, order_type=order_type, amount=amount, rate=enter_limit_requested,
                 time_in_force=time_in_force, current_time=datetime.now(timezone.utc),
-                side=trade_side
-        ):
+                entry_tag=enter_tag, side=trade_side):
             logger.info(f"User requested abortion of buying {pair}")
             return False
         amount = self.exchange.amount_to_precision(pair, amount)
@@ -814,6 +819,7 @@ class FreqtradeBot(LoggingMixin):
     def get_valid_enter_price_and_stake(
             self, pair: str, price: Optional[float], stake_amount: float,
             side: str, trade_side: str,
+            entry_tag: Optional[str],
             trade: Optional[Trade]) -> Tuple[float, float]:
         if price:
             enter_limit_requested = price
@@ -823,7 +829,7 @@ class FreqtradeBot(LoggingMixin):
             custom_entry_price = strategy_safe_wrapper(self.strategy.custom_entry_price,
                                                        default_retval=proposed_enter_rate)(
                 pair=pair, current_time=datetime.now(timezone.utc),
-                proposed_rate=proposed_enter_rate)
+                proposed_rate=proposed_enter_rate, entry_tag=entry_tag)
 
             enter_limit_requested = self.get_valid_price(custom_entry_price, proposed_enter_rate)
 
@@ -844,7 +850,7 @@ class FreqtradeBot(LoggingMixin):
                 pair=pair, current_time=datetime.now(timezone.utc),
                 current_rate=enter_limit_requested, proposed_stake=stake_amount,
                 min_stake=min_stake_amount, max_stake=max_stake_amount,
-                side=trade_side
+                entry_tag=entry_tag, side=trade_side
             )
 
         stake_amount = self.wallets.validate_stake_amount(pair, stake_amount, min_stake_amount)
@@ -1145,20 +1151,6 @@ class FreqtradeBot(LoggingMixin):
             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_unit = self.config.get('unfilledtimeout', {}).get('unit', 'minutes')
-            timeout_kwargs = {timeout_unit: -timeout}
-            timeout_threshold = arrow.utcnow().shift(**timeout_kwargs).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 necessary
@@ -1178,18 +1170,12 @@ class FreqtradeBot(LoggingMixin):
             fully_cancelled = self.update_trade_state(trade, trade.open_order_id, order)
             is_entering = order['side'] == trade.enter_side
             not_closed = order['status'] == 'open' or fully_cancelled
-            side = trade.enter_side if is_entering else trade.exit_side
-            timed_out = self._check_timed_out(side, order)
-            time_method = 'check_sell_timeout' if order['side'] == 'sell' else 'check_buy_timeout'
+            time_method = 'sell' if order['side'] == 'sell' else 'buy'
             max_timeouts = self.config.get('unfilledtimeout', {}).get('exit_timeout_count', 0)
 
-            if not_closed and (fully_cancelled or timed_out or (
-                strategy_safe_wrapper(getattr(self.strategy, time_method), default_retval=False)(
-                    pair=trade.pair,
-                    trade=trade,
-                    order=order
-                )
-            )):
+            if not_closed and (fully_cancelled or self.strategy.ft_check_timed_out(
+                        time_method, trade, order, datetime.now(timezone.utc))
+                    ):
                 if is_entering:
                     self.handle_cancel_enter(trade, order, constants.CANCEL_REASON['TIMEOUT'])
                 else:
diff --git a/freqtrade/main.py b/freqtrade/main.py
index 6593fbcb6..162b4d029 100755
--- a/freqtrade/main.py
+++ b/freqtrade/main.py
@@ -9,8 +9,8 @@ from typing import Any, List
 
 
 # check min. python version
-if sys.version_info < (3, 7):  # pragma: no cover
-    sys.exit("Freqtrade requires Python version >= 3.7")
+if sys.version_info < (3, 8):  # pragma: no cover
+    sys.exit("Freqtrade requires Python version >= 3.8")
 
 from freqtrade.commands import Arguments
 from freqtrade.exceptions import FreqtradeException, OperationalException
diff --git a/freqtrade/optimize/backtesting.py b/freqtrade/optimize/backtesting.py
index 7e6aa3ce5..6fac22cdf 100644
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -434,7 +434,12 @@ class Backtesting:
 
         # Check if we need to adjust our current positions
         if self.strategy.position_adjustment_enable:
-            trade = self._get_adjust_trade_entry_for_candle(trade, sell_row)
+            check_adjust_buy = True
+            if self.strategy.max_entry_position_adjustment > -1:
+                count_of_buys = trade.nr_of_successful_buys
+                check_adjust_buy = (count_of_buys <= self.strategy.max_entry_position_adjustment)
+            if check_adjust_buy:
+                trade = self._get_adjust_trade_entry_for_candle(trade, sell_row)
 
         sell_candle_time: datetime = sell_row[DATE_IDX].to_pydatetime()
         enter = sell_row[SHORT_IDX] if trade.is_short else sell_row[LONG_IDX]
@@ -533,12 +538,14 @@ class Backtesting:
     def _enter_trade(self, pair: str, row: Tuple, direction: str,
                      stake_amount: Optional[float] = None,
                      trade: Optional[LocalTrade] = None) -> Optional[LocalTrade]:
+
         current_time = row[DATE_IDX].to_pydatetime()
+        entry_tag = row[ENTER_TAG_IDX] if len(row) >= ENTER_TAG_IDX + 1 else None
         # let's call the custom entry price, using the open price as default price
         propose_rate = strategy_safe_wrapper(self.strategy.custom_entry_price,
                                              default_retval=row[OPEN_IDX])(
             pair=pair, current_time=current_time,
-            proposed_rate=row[OPEN_IDX])  # default value is the open rate
+            proposed_rate=row[OPEN_IDX], entry_tag=entry_tag)  # default value is the open rate
 
         # Move rate to within the candle's low/high rate
         propose_rate = min(max(propose_rate, row[LOW_IDX]), row[HIGH_IDX])
@@ -557,7 +564,7 @@ class Backtesting:
                                                  default_retval=stake_amount)(
                 pair=pair, current_time=current_time, current_rate=propose_rate,
                 proposed_stake=stake_amount, min_stake=min_stake_amount, max_stake=max_stake_amount,
-                side=direction)
+                entry_tag=entry_tag, side=direction)
 
         stake_amount = self.wallets.validate_stake_amount(pair, stake_amount, min_stake_amount)
 
@@ -585,14 +592,13 @@ class Backtesting:
             if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
                     pair=pair, order_type=order_type, amount=stake_amount, rate=propose_rate,
                     time_in_force=time_in_force, current_time=current_time,
-                    side=direction):
+                    entry_tag=entry_tag, side=direction):
                 return None
 
         if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount):
             amount = round((stake_amount / propose_rate) * leverage, 8)
             if trade is None:
                 # Enter trade
-                has_buy_tag = len(row) >= ENTER_TAG_IDX + 1
                 trade = LocalTrade(
                     pair=pair,
                     open_rate=propose_rate,
@@ -602,7 +608,7 @@ class Backtesting:
                     fee_open=self.fee,
                     fee_close=self.fee,
                     is_open=True,
-                    enter_tag=row[ENTER_TAG_IDX] if has_buy_tag else None,
+                    enter_tag=entry_tag,
                     exchange=self._exchange_name,
                     is_short=(direction == 'short'),
                     trading_mode=self.trading_mode,
@@ -619,6 +625,9 @@ class Backtesting:
                 side="buy",
                 order_type="market",
                 status="closed",
+                order_date=current_time,
+                order_filled_date=current_time,
+                order_update_date=current_time,
                 price=propose_rate,
                 average=propose_rate,
                 amount=amount,
diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py
index f98014089..9664e6f07 100644
--- a/freqtrade/optimize/hyperopt.py
+++ b/freqtrade/optimize/hyperopt.py
@@ -367,7 +367,7 @@ class Hyperopt:
         }
 
     def get_optimizer(self, dimensions: List[Dimension], cpu_count) -> Optimizer:
-        estimator = self.custom_hyperopt.generate_estimator()
+        estimator = self.custom_hyperopt.generate_estimator(dimensions=dimensions)
 
         acq_optimizer = "sampling"
         if isinstance(estimator, str):
diff --git a/freqtrade/optimize/hyperopt_auto.py b/freqtrade/optimize/hyperopt_auto.py
index 63b4b14e1..5bc0af42b 100644
--- a/freqtrade/optimize/hyperopt_auto.py
+++ b/freqtrade/optimize/hyperopt_auto.py
@@ -91,5 +91,5 @@ class HyperOptAuto(IHyperOpt):
     def trailing_space(self) -> List['Dimension']:
         return self._get_func('trailing_space')()
 
-    def generate_estimator(self) -> EstimatorType:
-        return self._get_func('generate_estimator')()
+    def generate_estimator(self, dimensions: List['Dimension'], **kwargs) -> EstimatorType:
+        return self._get_func('generate_estimator')(dimensions=dimensions, **kwargs)
diff --git a/freqtrade/optimize/hyperopt_interface.py b/freqtrade/optimize/hyperopt_interface.py
index 53b4f087c..01ffd7844 100644
--- a/freqtrade/optimize/hyperopt_interface.py
+++ b/freqtrade/optimize/hyperopt_interface.py
@@ -40,7 +40,7 @@ class IHyperOpt(ABC):
         IHyperOpt.ticker_interval = str(config['timeframe'])  # DEPRECATED
         IHyperOpt.timeframe = str(config['timeframe'])
 
-    def generate_estimator(self) -> EstimatorType:
+    def generate_estimator(self, dimensions: List[Dimension], **kwargs) -> EstimatorType:
         """
         Return base_estimator.
         Can be any of "GP", "RF", "ET", "GBRT" or an instance of a class
diff --git a/freqtrade/persistence/models.py b/freqtrade/persistence/models.py
index e0421024a..d388d84b8 100644
--- a/freqtrade/persistence/models.py
+++ b/freqtrade/persistence/models.py
@@ -804,18 +804,19 @@ class LocalTrade():
 
         total_amount = 0.0
         total_stake = 0.0
-        for temp_order in self.orders:
-            if (temp_order.ft_is_open or
-                    (temp_order.ft_order_side != self.enter_side) or
-                    (temp_order.status not in NON_OPEN_EXCHANGE_STATES)):
+        for o in self.orders:
+            if (o.ft_is_open or
+                    (o.ft_order_side != self.enter_side) or
+                    (o.status not in NON_OPEN_EXCHANGE_STATES)):
                 continue
 
-            tmp_amount = temp_order.amount
-            if temp_order.filled is not None:
-                tmp_amount = temp_order.filled
-            if tmp_amount > 0.0 and temp_order.average is not None:
+            tmp_amount = o.amount
+            tmp_price = o.average or o.price
+            if o.filled is not None:
+                tmp_amount = o.filled
+            if tmp_amount > 0.0 and tmp_price is not None:
                 total_amount += tmp_amount
-                total_stake += temp_order.average * tmp_amount
+                total_stake += tmp_price * tmp_amount
 
         if total_amount > 0:
             self.open_rate = total_stake / total_amount
diff --git a/freqtrade/resolvers/strategy_resolver.py b/freqtrade/resolvers/strategy_resolver.py
index 431e57e0f..fc4b71f1a 100644
--- a/freqtrade/resolvers/strategy_resolver.py
+++ b/freqtrade/resolvers/strategy_resolver.py
@@ -97,7 +97,8 @@ class StrategyResolver(IResolver):
                       ("sell_profit_offset",              0.0),
                       ("disable_dataframe_checks",        False),
                       ("ignore_buying_expired_candle_after",  0),
-                      ("position_adjustment_enable",      False)
+                      ("position_adjustment_enable",      False),
+                      ("max_entry_position_adjustment",      -1),
                       ]
         for attribute, default in attributes:
             StrategyResolver._override_attribute_helper(strategy, config,
diff --git a/freqtrade/rpc/api_server/api_schemas.py b/freqtrade/rpc/api_server/api_schemas.py
index 83cd8ad8e..92e490646 100644
--- a/freqtrade/rpc/api_server/api_schemas.py
+++ b/freqtrade/rpc/api_server/api_schemas.py
@@ -175,6 +175,8 @@ class ShowConfig(BaseModel):
     bot_name: str
     state: str
     runmode: str
+    position_adjustment_enable: bool
+    max_entry_position_adjustment: int
 
 
 class TradeSchema(BaseModel):
diff --git a/freqtrade/rpc/fiat_convert.py b/freqtrade/rpc/fiat_convert.py
index ef9689d0a..f65fd2d54 100644
--- a/freqtrade/rpc/fiat_convert.py
+++ b/freqtrade/rpc/fiat_convert.py
@@ -77,6 +77,9 @@ class CryptoToFiatConverter:
             else:
                 return None
         found = [x for x in self._coinlistings if x['symbol'] == crypto_symbol]
+        if crypto_symbol == 'eth':
+            found = [x for x in self._coinlistings if x['id'] == 'ethereum']
+
         if len(found) == 1:
             return found[0]['id']
 
diff --git a/freqtrade/rpc/rpc.py b/freqtrade/rpc/rpc.py
index 20f7a6b38..e4fe924c0 100644
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -138,7 +138,12 @@ class RPC:
             'ask_strategy': config.get('ask_strategy', {}),
             'bid_strategy': config.get('bid_strategy', {}),
             'state': str(botstate),
-            'runmode': config['runmode'].value
+            'runmode': config['runmode'].value,
+            'position_adjustment_enable': config.get('position_adjustment_enable', False),
+            'max_entry_position_adjustment': (
+                config.get('max_entry_position_adjustment', -1)
+                if config.get('max_entry_position_adjustment') != float('inf')
+                else -1)
         }
         return val
 
@@ -252,8 +257,9 @@ class RPC:
                     profit_str
                 ]
                 if self._config.get('position_adjustment_enable', False):
-                    filled_buys = trade.select_filled_orders('buy')
-                    detail_trade.append(str(len(filled_buys)))
+                    max_buy = self._config['max_entry_position_adjustment'] + 1
+                    filled_buys = trade.nr_of_successful_buys
+                    detail_trade.append(f"{filled_buys}/{max_buy}")
                 trades_list.append(detail_trade)
             profitcol = "Profit"
             if self._fiat_converter:
diff --git a/freqtrade/rpc/telegram.py b/freqtrade/rpc/telegram.py
index 0769e0277..5e849e81a 100644
--- a/freqtrade/rpc/telegram.py
+++ b/freqtrade/rpc/telegram.py
@@ -1363,6 +1363,14 @@ class Telegram(RPCHandler):
         else:
             sl_info = f"*Stoploss:* `{val['stoploss']}`\n"
 
+        if val['position_adjustment_enable']:
+            pa_info = (
+                f"*Position adjustment:* On\n"
+                f"*Max enter position adjustment:* `{val['max_entry_position_adjustment']}`\n"
+            )
+        else:
+            pa_info = "*Position adjustment:* Off\n"
+
         self._send_msg(
             f"*Mode:* `{'Dry-run' if val['dry_run'] else 'Live'}`\n"
             f"*Exchange:* `{val['exchange']}`\n"
@@ -1372,6 +1380,7 @@ class Telegram(RPCHandler):
             f"*Ask strategy:* ```\n{json.dumps(val['ask_strategy'])}```\n"
             f"*Bid strategy:* ```\n{json.dumps(val['bid_strategy'])}```\n"
             f"{sl_info}"
+            f"{pa_info}"
             f"*Timeframe:* `{val['timeframe']}`\n"
             f"*Strategy:* `{val['strategy']}`\n"
             f"*Current state:* `{val['state']}`"
diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py
index 619dc41b1..6823255f3 100644
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@@ -108,6 +108,7 @@ class IStrategy(ABC, HyperStrategyMixin):
 
     # Position adjustment is disabled by default
     position_adjustment_enable: bool = False
+    max_entry_position_adjustment: int = -1
 
     # Number of seconds after which the candle will no longer result in a buy on expired candles
     ignore_buying_expired_candle_after: int = 0
@@ -188,7 +189,17 @@ class IStrategy(ABC, HyperStrategyMixin):
         """
         return dataframe
 
-    def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
+    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 check_buy_timeout(self, pair: str, trade: Trade, order: dict,
+                          current_time: datetime, **kwargs) -> bool:
         """
         Check buy timeout function callback.
         This method can be used to override the enter-timeout.
@@ -201,12 +212,14 @@ class IStrategy(ABC, HyperStrategyMixin):
         :param pair: Pair the trade is for
         :param trade: trade object.
         :param order: Order dictionary as returned from CCXT.
+        :param current_time: datetime object, containing the current datetime
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         :return bool: When True is returned, then the entry order is cancelled.
         """
         return False
 
-    def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
+    def check_sell_timeout(self, pair: str, trade: Trade, order: dict,
+                           current_time: datetime, **kwargs) -> bool:
         """
         Check sell timeout function callback.
         This method can be used to override the exit-timeout.
@@ -219,22 +232,14 @@ class IStrategy(ABC, HyperStrategyMixin):
         :param pair: Pair the trade is for
         :param trade: trade object.
         :param order: Order dictionary as returned from CCXT.
+        :param current_time: datetime object, containing the current datetime
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         :return bool: When True is returned, then the (long)sell/(short)buy-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, current_time: datetime,
+                            time_in_force: str, current_time: datetime, entry_tag: Optional[str],
                             side: str, **kwargs) -> bool:
         """
         Called right before placing a entry order.
@@ -251,6 +256,7 @@ class IStrategy(ABC, HyperStrategyMixin):
         :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 current_time: datetime object, containing the current datetime
+        :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
         :param side: 'long' or 'short' - indicating the direction of the proposed trade
         :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.
@@ -309,7 +315,7 @@ class IStrategy(ABC, HyperStrategyMixin):
         return self.stoploss
 
     def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
-                           **kwargs) -> float:
+                           entry_tag: Optional[str], **kwargs) -> float:
         """
         Custom entry price logic, returning the new entry price.
 
@@ -320,6 +326,7 @@ class IStrategy(ABC, HyperStrategyMixin):
         :param pair: Pair that's currently analyzed
         :param current_time: datetime object, containing the current datetime
         :param proposed_rate: Rate, calculated based on pricing settings in ask_strategy.
+        :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         :return float: New entry price value if provided
         """
@@ -371,7 +378,7 @@ class IStrategy(ABC, HyperStrategyMixin):
 
     def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
                             proposed_stake: float, min_stake: float, max_stake: float,
-                            side: str, **kwargs) -> float:
+                            entry_tag: Optional[str], side: str, **kwargs) -> float:
         """
         Customize stake size for each new trade.
 
@@ -381,6 +388,7 @@ class IStrategy(ABC, HyperStrategyMixin):
         :param proposed_stake: A stake amount proposed by the bot.
         :param min_stake: Minimal stake size allowed by exchange.
         :param max_stake: Balance available for trading.
+        :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
         :param side: 'long' or 'short' - indicating the direction of the proposed trade
         :return: A stake size, which is between min_stake and max_stake.
         """
@@ -392,6 +400,7 @@ class IStrategy(ABC, HyperStrategyMixin):
         """
         Custom trade adjustment logic, returning the stake amount that a trade should be increased.
         This means extra buy orders with additional fees.
+        Only called when `position_adjustment_enable` is set to True.
 
         For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
 
@@ -976,6 +985,29 @@ class IStrategy(ABC, HyperStrategyMixin):
         else:
             return current_profit > roi
 
+    def ft_check_timed_out(self, side: str, trade: Trade, order: Dict,
+                           current_time: datetime) -> bool:
+        """
+        FT Internal method.
+        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_unit = self.config.get('unfilledtimeout', {}).get('unit', 'minutes')
+            timeout_kwargs = {timeout_unit: -timeout}
+            timeout_threshold = current_time + timedelta(**timeout_kwargs)
+            timedout = (order['status'] == 'open' and order['side'] == side
+                        and ordertime < timeout_threshold)
+            if timedout:
+                return True
+        time_method = self.check_sell_timeout if order['side'] == 'sell' else self.check_buy_timeout
+
+        return strategy_safe_wrapper(time_method,
+                                     default_retval=False)(
+                                        pair=trade.pair, trade=trade, order=order,
+                                        current_time=current_time)
+
     def advise_all_indicators(self, data: Dict[str, DataFrame]) -> Dict[str, DataFrame]:
         """
         Populates indicators for given candle (OHLCV) data (for multiple pairs)
diff --git a/freqtrade/templates/subtemplates/strategy_methods_advanced.j2 b/freqtrade/templates/subtemplates/strategy_methods_advanced.j2
index d41bc63c3..f81514b2a 100644
--- a/freqtrade/templates/subtemplates/strategy_methods_advanced.j2
+++ b/freqtrade/templates/subtemplates/strategy_methods_advanced.j2
@@ -12,9 +12,47 @@ def bot_loop_start(self, **kwargs) -> None:
     """
     pass
 
-def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
+def custom_entry_price(self, pair: str, current_time: 'datetime', proposed_rate: float,
+                       entry_tag: 'Optional[str]', **kwargs) -> float:
+    """
+    Custom entry price logic, returning the new entry price.
+
+    For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+    When not implemented by a strategy, returns None, orderbook is used to set entry price
+
+    :param pair: Pair that's currently analyzed
+    :param current_time: datetime object, containing the current datetime
+    :param proposed_rate: Rate, calculated based on pricing settings in ask_strategy.
+    :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
+    :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+    :return float: New entry price value if provided
+    """
+    return proposed_rate
+
+def custom_exit_price(self, pair: str, trade: 'Trade',
+                      current_time: 'datetime', proposed_rate: float,
+                      current_profit: float, **kwargs) -> float:
+    """
+    Custom exit price logic, returning the new exit price.
+
+    For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+    When not implemented by a strategy, returns None, orderbook is used to set exit price
+
+    :param pair: Pair that's currently analyzed
+    :param trade: trade object.
+    :param current_time: datetime object, containing the current datetime
+    :param proposed_rate: Rate, calculated based on pricing settings in ask_strategy.
+    :param current_profit: Current profit (as ratio), calculated based on current_rate.
+    :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+    :return float: New exit price value if provided
+    """
+    return proposed_rate
+
+def custom_stake_amount(self, pair: str, current_time: 'datetime', current_rate: float,
                         proposed_stake: float, min_stake: float, max_stake: float,
-                        side: str, **kwargs) -> float:
+                        side: str, entry_tag: 'Optional[str]', **kwargs) -> float:
     """
     Customize stake size for each new trade.
 
@@ -24,6 +62,7 @@ def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: f
     :param proposed_stake: A stake amount proposed by the bot.
     :param min_stake: Minimal stake size allowed by exchange.
     :param max_stake: Balance available for trading.
+    :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
     :param side: 'long' or 'short' - indicating the direction of the proposed trade
     :return: A stake size, which is between min_stake and max_stake.
     """
@@ -78,7 +117,7 @@ def custom_sell(self, pair: str, trade: 'Trade', current_time: 'datetime', curre
     return None
 
 def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
-                        time_in_force: str, current_time: datetime,
+                        time_in_force: str, current_time: datetime, entry_tag: 'Optional[str]',
                         side: str, **kwargs) -> bool:
     """
     Called right before placing a entry order.
@@ -95,6 +134,7 @@ def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: f
     :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 current_time: datetime object, containing the current datetime
+    :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
     :param side: 'long' or 'short' - indicating the direction of the proposed trade
     :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.
@@ -169,3 +209,26 @@ def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -
     :return bool: When True is returned, then the sell-order is cancelled.
     """
     return False
+
+def adjust_trade_position(self, trade: 'Trade', current_time: 'datetime',
+                          current_rate: float, current_profit: float, min_stake: float,
+                          max_stake: float, **kwargs) -> 'Optional[float]':
+    """
+    Custom trade adjustment logic, returning the stake amount that a trade should be increased.
+    This means extra buy orders with additional fees.
+    Only called when `position_adjustment_enable` is set to True.
+
+    For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
+
+    When not implemented by a strategy, returns None
+
+    :param trade: trade object.
+    :param current_time: datetime object, containing the current datetime
+    :param current_rate: Current buy rate.
+    :param current_profit: Current profit (as ratio), calculated based on current_rate.
+    :param min_stake: Minimal stake size allowed by exchange.
+    :param max_stake: Balance available for trading.
+    :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+    :return float: Stake amount to adjust your trade
+    """
+    return None
diff --git a/requirements-dev.txt b/requirements-dev.txt
index 7773ff01a..59867ff3a 100644
--- a/requirements-dev.txt
+++ b/requirements-dev.txt
@@ -8,7 +8,7 @@ flake8==4.0.1
 flake8-tidy-imports==4.6.0
 mypy==0.931
 pytest==6.2.5
-pytest-asyncio==0.17.1
+pytest-asyncio==0.17.2
 pytest-cov==3.0.0
 pytest-mock==3.6.1
 pytest-random-order==1.0.4
@@ -21,9 +21,9 @@ nbconvert==6.4.0
 
 # mypy types
 types-cachetools==4.2.9
-types-filelock==3.2.4
+types-filelock==3.2.5
 types-requests==2.27.7
 types-tabulate==0.8.5
 
 # Extensions to datetime library
-types-python-dateutil==2.8.7
\ No newline at end of file
+types-python-dateutil==2.8.8
\ No newline at end of file
diff --git a/requirements.txt b/requirements.txt
index d8b902d97..102558e61 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,13 +1,12 @@
-numpy==1.21.5; python_version <= '3.7'
-numpy==1.22.1; python_version > '3.7'
-pandas==1.3.5
+numpy==1.22.1
+pandas==1.4.0
 pandas-ta==0.3.14b
 
-ccxt==1.68.20
+ccxt==1.70.45
 # Pin cryptography for now due to rust build errors with piwheels
 cryptography==36.0.1
 aiohttp==3.8.1
-SQLAlchemy==1.4.29
+SQLAlchemy==1.4.31
 python-telegram-bot==13.10
 arrow==1.2.1
 cachetools==4.2.2
@@ -32,7 +31,7 @@ python-rapidjson==1.5
 sdnotify==0.3.2
 
 # API Server
-fastapi==0.72.0
+fastapi==0.73.0
 uvicorn==0.17.0
 pyjwt==2.3.0
 aiofiles==0.8.0
diff --git a/setup.cfg b/setup.cfg
index c5c7f2f25..6aaec9d73 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -14,7 +14,6 @@ classifiers =
     Environment :: Console
     Intended Audience :: Science/Research
     License :: OSI Approved :: GNU General Public License v3 (GPLv3)
-    Programming Language :: Python :: 3.7
     Programming Language :: Python :: 3.8
     Programming Language :: Python :: 3.9
     Programming Language :: Python :: 3.10
diff --git a/setup.sh b/setup.sh
index c642a654d..1df9df606 100755
--- a/setup.sh
+++ b/setup.sh
@@ -25,7 +25,7 @@ function check_installed_python() {
         exit 2
     fi
 
-    for v in 9 10 8 7
+    for v in 9 10 8
     do
         PYTHON="python3.${v}"
         which $PYTHON
@@ -219,7 +219,7 @@ function install() {
         install_redhat
     else
         echo "This script does not support your OS."
-        echo "If you have Python version 3.7 - 3.10, pip, virtualenv, ta-lib you can continue."
+        echo "If you have Python version 3.8 - 3.10, pip, virtualenv, ta-lib you can continue."
         echo "Wait 10 seconds to continue the next install steps or use ctrl+c to interrupt this shell."
         sleep 10
     fi
@@ -246,7 +246,7 @@ function help() {
     echo "	-p,--plot       Install dependencies for Plotting scripts."
 }
 
-# Verify if 3.7 or 3.8 is installed
+# Verify if 3.8+ is installed
 check_installed_python
 
 case $* in
diff --git a/tests/optimize/test_backtesting.py b/tests/optimize/test_backtesting.py
index 540e963eb..30cb3932d 100644
--- a/tests/optimize/test_backtesting.py
+++ b/tests/optimize/test_backtesting.py
@@ -782,6 +782,8 @@ def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatad
     # While buy-signals are unrealistic, running backtesting
     # over and over again should not cause different results
     for [contour, numres] in tests:
+        # Debug output for random test failure
+        print(f"{contour}, {numres}")
         assert len(simple_backtest(default_conf, contour, mocker, testdatadir)['results']) == numres
 
 
diff --git a/tests/rpc/test_fiat_convert.py b/tests/rpc/test_fiat_convert.py
index 2fe5d4a56..c87cea259 100644
--- a/tests/rpc/test_fiat_convert.py
+++ b/tests/rpc/test_fiat_convert.py
@@ -148,10 +148,13 @@ def test_fiat_multiple_coins(mocker, caplog):
         {'id': 'helium', 'symbol': 'hnt', 'name': 'Helium'},
         {'id': 'hymnode', 'symbol': 'hnt', 'name': 'Hymnode'},
         {'id': 'bitcoin', 'symbol': 'btc', 'name': 'Bitcoin'},
+        {'id': 'ethereum', 'symbol': 'eth', 'name': 'Ethereum'},
+        {'id': 'ethereum-wormhole', 'symbol': 'eth', 'name': 'Ethereum Wormhole'},
     ]
 
     assert fiat_convert._get_gekko_id('btc') == 'bitcoin'
     assert fiat_convert._get_gekko_id('hnt') is None
+    assert fiat_convert._get_gekko_id('eth') == 'ethereum'
 
     assert log_has('Found multiple mappings in goingekko for hnt.', caplog)
 
diff --git a/tests/strategy/test_default_strategy.py b/tests/strategy/test_default_strategy.py
index ff2ce10a7..7eb0faab5 100644
--- a/tests/strategy/test_default_strategy.py
+++ b/tests/strategy/test_default_strategy.py
@@ -44,7 +44,7 @@ def test_strategy_test_v3(result, fee, is_short, side):
     assert strategy.confirm_trade_entry(pair='ETH/BTC', order_type='limit', amount=0.1,
                                         rate=20000, time_in_force='gtc',
                                         current_time=datetime.utcnow(),
-                                        side=side) is True
+                                        side=side, entry_tag=None) is True
     assert strategy.confirm_trade_exit(pair='ETH/BTC', trade=trade, order_type='limit', amount=0.1,
                                        rate=20000, time_in_force='gtc', sell_reason='roi',
                                        current_time=datetime.utcnow(),
diff --git a/tests/test_freqtradebot.py b/tests/test_freqtradebot.py
index f036c3538..373ffb215 100644
--- a/tests/test_freqtradebot.py
+++ b/tests/test_freqtradebot.py
@@ -5182,3 +5182,32 @@ def test_position_adjust(mocker, default_conf_usdt, fee) -> None:
     # Make sure the closed order is found as the second order.
     order = trade.select_order('buy', False)
     assert order.order_id == '652'
+
+
+def test_process_open_trade_positions_exception(mocker, default_conf_usdt, fee, caplog) -> None:
+    default_conf_usdt.update({
+        "position_adjustment_enable": True,
+    })
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+
+    mocker.patch('freqtrade.freqtradebot.FreqtradeBot.check_and_call_adjust_trade_position',
+                 side_effect=DependencyException())
+
+    create_mock_trades(fee)
+
+    freqtrade.process_open_trade_positions()
+    assert log_has_re(r"Unable to adjust position of trade for .*", caplog)
+
+
+def test_check_and_call_adjust_trade_position(mocker, default_conf_usdt, fee, caplog) -> None:
+    default_conf_usdt.update({
+        "position_adjustment_enable": True,
+        "max_entry_position_adjustment": 0,
+    })
+    freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
+
+    create_mock_trades(fee)
+    caplog.set_level(logging.DEBUG)
+
+    freqtrade.process_open_trade_positions()
+    assert log_has_re(r"Max adjustment entries for .* has been reached\.", caplog)
diff --git a/tests/test_integration.py b/tests/test_integration.py
index 13bcac351..d7da68be3 100644
--- a/tests/test_integration.py
+++ b/tests/test_integration.py
@@ -243,6 +243,8 @@ def test_dca_buying(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
     freqtrade.process()
     trade = Trade.get_trades().first()
     assert len(trade.orders) == 2
+    for o in trade.orders:
+        assert o.status == "closed"
     assert trade.stake_amount == 120
 
     # Open-rate averaged between 2.0 and 2.0 * 0.995
@@ -258,7 +260,6 @@ def test_dca_buying(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
     assert trade.orders[1].amount == 60 / ticker_usdt_modif['bid']
 
     assert trade.amount == trade.orders[0].amount + trade.orders[1].amount
-
     assert trade.nr_of_successful_buys == 2
 
     # Sell
diff --git a/tests/test_persistence.py b/tests/test_persistence.py
index 62aa2673f..e28e3b2ed 100644
--- a/tests/test_persistence.py
+++ b/tests/test_persistence.py
@@ -2464,6 +2464,33 @@ def test_recalc_trade_from_orders_ignores_bad_orders(fee):
     assert trade.fee_open_cost == 2 * o1_fee_cost
     assert trade.open_trade_value == 2 * o1_trade_val
     assert trade.nr_of_successful_buys == 2
+    # Check with 1 order
+    order_noavg = Order(
+        ft_order_side='buy',
+        ft_pair=trade.pair,
+        ft_is_open=False,
+        status="closed",
+        symbol=trade.pair,
+        order_type="market",
+        side="buy",
+        price=o1_rate,
+        average=None,
+        filled=o1_amount,
+        remaining=0,
+        cost=o1_amount,
+        order_date=trade.open_date,
+        order_filled_date=trade.open_date,
+    )
+    trade.orders.append(order_noavg)
+    trade.recalc_trade_from_orders()
+
+    # Calling recalc with single initial order should not change anything
+    assert trade.amount == 3 * o1_amount
+    assert trade.stake_amount == 3 * o1_amount
+    assert trade.open_rate == o1_rate
+    assert trade.fee_open_cost == 3 * o1_fee_cost
+    assert trade.open_trade_value == 3 * o1_trade_val
+    assert trade.nr_of_successful_buys == 3
 
 
 @pytest.mark.usefixtures("init_persistence")