merged with develop

docs/includes/pairlists.md

@@ -165,6 +165,7 @@ Example to remove the first 10 pairs from the pairlist:
 
 ```json
 "pairlists": [
+    // ...
     {
         "method": "OffsetFilter",
         "offset": 10
@@ -190,6 +191,19 @@ Sorts pairs by past trade performance, as follows:
 
 Trade count is used as a tie breaker.
 
+You can use the `minutes` parameter to only consider performance of the past X minutes (rolling window).
+Not defining this parameter (or setting it to 0) will use all-time performance.
+
+```json
+"pairlists": [
+    // ...
+    {
+        "method": "PerformanceFilter",
+        "minutes": 1440  // rolling 24h
+    }
+],
+```
+
 !!! Note
     `PerformanceFilter` does not support backtesting mode.
 

docs/strategy-advanced.md

@@ -288,6 +288,12 @@ Stoploss values returned from `custom_stoploss()` always specify a percentage re
 
 The helper function [`stoploss_from_open()`](strategy-customization.md#stoploss_from_open) can be used to convert from an open price relative stop, to a current price relative stop which can be returned from `custom_stoploss()`.
 
+### Calculating stoploss percentage from absolute price
+
+Stoploss values returned from `custom_stoploss()` always specify a percentage relative to `current_rate`. In order to set a stoploss at specified absolute price level, we need to use `stop_rate` to calculate what percentage relative to the `current_rate` will give you the same result as if the percentage was specified from the open price.
+
+The helper function [`stoploss_from_absolute()`](strategy-customization.md#stoploss_from_absolute) can be used to convert from an absolute price, to a current price relative stop which can be returned from `custom_stoploss()`.
+
 #### Stepped stoploss
 
 Instead of continuously trailing behind the current price, this example sets fixed stoploss price levels based on the current profit.

docs/strategy-customization.md

@@ -639,6 +639,167 @@ Stoploss values returned from `custom_stoploss` must specify a percentage relati
 
     Full examples can be found in the [Custom stoploss](strategy-advanced.md#custom-stoploss) section of the Documentation.
 
+!!! Note
+    Providing invalid input to `stoploss_from_open()` may produce "CustomStoploss function did not return valid stoploss" warnings.
+    This may happen if `current_profit` parameter is below specified `open_relative_stop`. Such situations may arise when closing trade
+    is blocked by `confirm_trade_exit()` method. Warnings can be solved by never blocking stop loss sells by checking `sell_reason` in
+    `confirm_trade_exit()`, or by using `return stoploss_from_open(...) or 1` idiom, which will request to not change stop loss when
+    `current_profit < open_relative_stop`.
+
+### *stoploss_from_absolute()*
+
+In some situations it may be confusing to deal with stops relative to current rate. Instead, you may define a stoploss level using an absolute price.
+
+??? Example "Returning a stoploss using absolute price from the custom stoploss function"
+
+    If we want to trail a stop price at 2xATR below current proce we can call `stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate)`.
+
+    ``` python
+
+    from datetime import datetime
+    from freqtrade.persistence import Trade
+    from freqtrade.strategy import IStrategy, stoploss_from_open
+
+    class AwesomeStrategy(IStrategy):
+
+        use_custom_stoploss = True
+
+        def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe['atr'] = ta.ATR(dataframe, timeperiod=14)
+            return dataframe
+
+        def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+                            current_rate: float, current_profit: float, **kwargs) -> float:
+            dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+            candle = dataframe.iloc[-1].squeeze()
+            return stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate)
+
+    ```
+
+### *@informative()*
+
+``` python
+def informative(timeframe: str, asset: str = '',
+                fmt: Optional[Union[str, Callable[[KwArg(str)], str]]] = None,
+                ffill: bool = True) -> Callable[[PopulateIndicators], PopulateIndicators]:
+    """
+    A decorator for populate_indicators_Nn(self, dataframe, metadata), allowing these functions to
+    define informative indicators.
+
+    Example usage:
+
+        @informative('1h')
+        def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+            return dataframe
+
+    :param timeframe: Informative timeframe. Must always be equal or higher than strategy timeframe.
+    :param asset: Informative asset, for example BTC, BTC/USDT, ETH/BTC. Do not specify to use
+    current pair.
+    :param fmt: Column format (str) or column formatter (callable(name, asset, timeframe)). When not
+    specified, defaults to:
+    * {base}_{quote}_{column}_{timeframe} if asset is specified. 
+    * {column}_{timeframe} if asset is not specified.
+    Format string supports these format variables:
+    * {asset} - full name of the asset, for example 'BTC/USDT'.
+    * {base} - base currency in lower case, for example 'eth'.
+    * {BASE} - same as {base}, except in upper case.
+    * {quote} - quote currency in lower case, for example 'usdt'.
+    * {QUOTE} - same as {quote}, except in upper case.
+    * {column} - name of dataframe column.
+    * {timeframe} - timeframe of informative dataframe.
+    :param ffill: ffill dataframe after merging informative pair.
+    """
+```
+
+In most common case it is possible to easily define informative pairs by using a decorator. All decorated `populate_indicators_*` methods run in isolation,
+not having access to data from other informative pairs, in the end all informative dataframes are merged and passed to main `populate_indicators()` method.
+When hyperopting, use of hyperoptable parameter `.value` attribute is not supported. Please use `.range` attribute. See [optimizing an indicator parameter](hyperopt.md#optimizing-an-indicator-parameter)
+for more information.
+
+??? Example "Fast and easy way to define informative pairs"
+
+    Most of the time we do not need power and flexibility offered by `merge_informative_pair()`, therefore we can use a decorator to quickly define informative pairs.
+
+    ``` python
+
+    from datetime import datetime
+    from freqtrade.persistence import Trade
+    from freqtrade.strategy import IStrategy, informative
+
+    class AwesomeStrategy(IStrategy):
+        
+        # This method is not required. 
+        # def informative_pairs(self): ...
+
+        # Define informative upper timeframe for each pair. Decorators can be stacked on same 
+        # method. Available in populate_indicators as 'rsi_30m' and 'rsi_1h'.
+        @informative('30m')
+        @informative('1h')
+        def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+            return dataframe
+
+        # Define BTC/STAKE informative pair. Available in populate_indicators and other methods as
+        # 'btc_rsi_1h'. Current stake currency should be specified as {stake} format variable 
+        # instead of hardcoding actual stake currency. Available in populate_indicators and other 
+        # methods as 'btc_usdt_rsi_1h' (when stake currency is USDT).
+        @informative('1h', 'BTC/{stake}')
+        def populate_indicators_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+            return dataframe
+
+        # Define BTC/ETH informative pair. You must specify quote currency if it is different from
+        # stake currency. Available in populate_indicators and other methods as 'eth_btc_rsi_1h'.
+        @informative('1h', 'ETH/BTC')
+        def populate_indicators_eth_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+            return dataframe
+    
+        # Define BTC/STAKE informative pair. A custom formatter may be specified for formatting
+        # column names. A callable `fmt(**kwargs) -> str` may be specified, to implement custom
+        # formatting. Available in populate_indicators and other methods as 'rsi_upper'.
+        @informative('1h', 'BTC/{stake}', '{column}')
+        def populate_indicators_btc_1h_2(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe['rsi_upper'] = ta.RSI(dataframe, timeperiod=14)
+            return dataframe
+    
+        def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            # Strategy timeframe indicators for current pair.
+            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+            # Informative pairs are available in this method.
+            dataframe['rsi_less'] = dataframe['rsi'] < dataframe['rsi_1h']
+            return dataframe
+
+    ```
+
+!!! Note
+    Do not use `@informative` decorator if you need to use data of one informative pair when generating another informative pair. Instead, define informative pairs
+    manually as described [in the DataProvider section](#complete-data-provider-sample).
+
+!!! Note
+    Use string formatting when accessing informative dataframes of other pairs. This will allow easily changing stake currency in config without having to adjust strategy code.
+
+    ``` python
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        stake = self.config['stake_currency']
+        dataframe.loc[
+            (
+                (dataframe[f'btc_{stake}_rsi_1h'] < 35)
+                &
+                (dataframe['volume'] > 0)
+            ),
+            ['buy', 'buy_tag']] = (1, 'buy_signal_rsi')
+    
+        return dataframe
+    ```
+
+    Alternatively column renaming may be used to remove stake currency from column names: `@informative('1h', 'BTC/{stake}', fmt='{base}_{column}_{timeframe}')`.
+
+!!! Warning "Duplicate method names"
+    Methods tagged with `@informative()` decorator must always have unique names! Re-using same name (for example when copy-pasting already defined informative method)
+    will overwrite previously defined method and not produce any errors due to limitations of Python programming language. In such cases you will find that indicators
+    created in earlier-defined methods are not available in the dataframe. Carefully review method names and make sure they are unique!
 
 ## Additional data (Wallets)
 

freqtrade/commands/hyperopt_commands.py

@@ -53,7 +53,7 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None:
 
     if epochs and export_csv:
         HyperoptTools.export_csv_file(
-            config, epochs, total_epochs, not config.get('hyperopt_list_best', False), export_csv
+            config, epochs, export_csv
         )
 
 

freqtrade/edge/edge_positioning.py

@@ -119,7 +119,7 @@ class Edge:
             )
             # Download informative pairs too
             res = defaultdict(list)
-            for p, t in self.strategy.informative_pairs():
+            for p, t in self.strategy.gather_informative_pairs():
                 res[t].append(p)
             for timeframe, inf_pairs in res.items():
                 timerange_startup = deepcopy(self._timerange)

freqtrade/freqtradebot.py

@@ -85,10 +85,10 @@ class FreqtradeBot(LoggingMixin):
 
         self.dataprovider = DataProvider(self.config, self.exchange, self.pairlists)
 
-        # Attach Dataprovider to Strategy baseclass
+        # Attach Dataprovider to strategy instance
-        IStrategy.dp = self.dataprovider
+        self.strategy.dp = self.dataprovider
-        # Attach Wallets to Strategy baseclass
+        # Attach Wallets to strategy instance
-        IStrategy.wallets = self.wallets
+        self.strategy.wallets = self.wallets
 
         # Initializing Edge only if enabled
         self.edge = Edge(self.config, self.exchange, self.strategy) if \
@@ -162,7 +162,7 @@ class FreqtradeBot(LoggingMixin):
 
         # Refreshing candles
         self.dataprovider.refresh(self.pairlists.create_pair_list(self.active_pair_whitelist),
-                                  self.strategy.informative_pairs())
+                                  self.strategy.gather_informative_pairs())
 
         strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)()
 

freqtrade/optimize/backtesting.py

@@ -154,7 +154,7 @@ class Backtesting:
         self.strategy: IStrategy = strategy
         strategy.dp = self.dataprovider
         # Attach Wallets to Strategy baseclass
-        IStrategy.wallets = self.wallets
+        strategy.wallets = self.wallets
         # 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

freqtrade/optimize/edge_cli.py

@@ -8,6 +8,7 @@ from typing import Any, Dict
 
 from freqtrade import constants
 from freqtrade.configuration import TimeRange, validate_config_consistency
+from freqtrade.data.dataprovider import DataProvider
 from freqtrade.edge import Edge
 from freqtrade.optimize.optimize_reports import generate_edge_table
 from freqtrade.resolvers import ExchangeResolver, StrategyResolver
@@ -33,6 +34,7 @@ class EdgeCli:
         self.config['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
         self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
         self.strategy = StrategyResolver.load_strategy(self.config)
+        self.strategy.dp = DataProvider(config, None)
 
         validate_config_consistency(self.config)
 

freqtrade/optimize/hyperopt_tools.py

@@ -7,6 +7,7 @@ from pathlib import Path
 from typing import Any, Dict, Iterator, List, Optional, Tuple
 
 import numpy as np
+import pandas as pd
 import rapidjson
 import tabulate
 from colorama import Fore, Style
@@ -298,8 +299,8 @@ class HyperoptTools():
                 f"Objective: {results['loss']:.5f}")
 
     @staticmethod
-    def prepare_trials_columns(trials, legacy_mode: bool, has_drawdown: bool) -> str:
+    def prepare_trials_columns(trials: pd.DataFrame, legacy_mode: bool,
-
+                               has_drawdown: bool) -> pd.DataFrame:
         trials['Best'] = ''
 
         if 'results_metrics.winsdrawslosses' not in trials.columns:
@@ -435,8 +436,7 @@ class HyperoptTools():
         return table
 
     @staticmethod
-    def export_csv_file(config: dict, results: list, total_epochs: int, highlight_best: bool,
+    def export_csv_file(config: dict, results: list, csv_file: str) -> None:
-                        csv_file: str) -> None:
         """
         Log result to csv-file
         """

freqtrade/persistence/models.py

@@ -2,7 +2,7 @@
 This module contains the class to persist trades into SQLite
 """
 import logging
-from datetime import datetime, timezone
+from datetime import datetime, timedelta, timezone
 from decimal import Decimal
 from typing import Any, Dict, List, Optional
 
@@ -1026,17 +1026,21 @@ class Trade(_DECL_BASE, LocalTrade):
         return total_open_stake_amount or 0
 
     @staticmethod
-    def get_overall_performance() -> List[Dict[str, Any]]:
+    def get_overall_performance(minutes=None) -> List[Dict[str, Any]]:
         """
         Returns List of dicts containing all Trades, including profit and trade count
         NOTE: Not supported in Backtesting.
         """
+        filters = [Trade.is_open.is_(False)]
+        if minutes:
+            start_date = datetime.now(timezone.utc) - timedelta(minutes=minutes)
+            filters.append(Trade.close_date >= start_date)
         pair_rates = Trade.query.with_entities(
             Trade.pair,
             func.sum(Trade.close_profit).label('profit_sum'),
             func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
             func.count(Trade.pair).label('count')
-        ).filter(Trade.is_open.is_(False))\
+        ).filter(*filters)\
             .group_by(Trade.pair) \
             .order_by(desc('profit_sum_abs')) \
             .all()

freqtrade/plugins/pairlist/PerformanceFilter.py

@@ -2,7 +2,7 @@
 Performance pair list filter
 """
 import logging
-from typing import Dict, List
+from typing import Any, Dict, List
 
 import pandas as pd
 
@@ -15,6 +15,13 @@ logger = logging.getLogger(__name__)
 
 class PerformanceFilter(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._minutes = pairlistconfig.get('minutes', 0)
+
     @property
     def needstickers(self) -> bool:
         """
@@ -40,7 +47,7 @@ class PerformanceFilter(IPairList):
         """
         # Get the trading performance for pairs from database
         try:
-            performance = pd.DataFrame(Trade.get_overall_performance())
+            performance = pd.DataFrame(Trade.get_overall_performance(self._minutes))
         except AttributeError:
             # Performancefilter does not work in backtesting.
             self.log_once("PerformanceFilter is not available in this mode.", logger.warning)

freqtrade/rpc/api_server/api_schemas.py

@@ -46,6 +46,12 @@ class Balances(BaseModel):
     value: float
     stake: str
     note: str
+    starting_capital: float
+    starting_capital_ratio: float
+    starting_capital_pct: float
+    starting_capital_fiat: float
+    starting_capital_fiat_ratio: float
+    starting_capital_fiat_pct: float
 
 
 class Count(BaseModel):

freqtrade/rpc/rpc.py

@@ -459,6 +459,9 @@ class RPC:
             raise RPCException('Error getting current tickers.')
 
         self._freqtrade.wallets.update(require_update=False)
+        starting_capital = self._freqtrade.wallets.get_starting_balance()
+        starting_cap_fiat = self._fiat_converter.convert_amount(
+            starting_capital, stake_currency, fiat_display_currency) if self._fiat_converter else 0
 
         for coin, balance in self._freqtrade.wallets.get_all_balances().items():
             if not balance.total:
@@ -494,15 +497,25 @@ class RPC:
             else:
                 raise RPCException('All balances are zero.')
 
-        symbol = fiat_display_currency
+        value = self._fiat_converter.convert_amount(
-        value = self._fiat_converter.convert_amount(total, stake_currency,
+            total, stake_currency, fiat_display_currency) if self._fiat_converter else 0
-                                                    symbol) if self._fiat_converter else 0
+
+        starting_capital_ratio = 0.0
+        starting_capital_ratio = (total / starting_capital) - 1 if starting_capital else 0.0
+        starting_cap_fiat_ratio = (value / starting_cap_fiat) - 1 if starting_cap_fiat else 0.0
+
         return {
             'currencies': output,
             'total': total,
-            'symbol': symbol,
+            'symbol': fiat_display_currency,
             'value': value,
             'stake': stake_currency,
+            'starting_capital': starting_capital,
+            'starting_capital_ratio': starting_capital_ratio,
+            'starting_capital_pct': round(starting_capital_ratio * 100, 2),
+            'starting_capital_fiat': starting_cap_fiat,
+            'starting_capital_fiat_ratio': starting_cap_fiat_ratio,
+            'starting_capital_fiat_pct': round(starting_cap_fiat_ratio * 100, 2),
             'note': 'Simulated balances' if self._freqtrade.config['dry_run'] else ''
         }
 

freqtrade/rpc/telegram.py

@@ -603,12 +603,15 @@ class Telegram(RPCHandler):
 
             output = ''
             if self._config['dry_run']:
-                output += (
+                output += "*Warning:* Simulated balances in Dry Mode.\n"
-                    f"*Warning:* Simulated balances in Dry Mode.\n"
+
-                    "This mode is still experimental!\n"
+            output += ("Starting capital: "
-                    "Starting capital: "
+                       f"`{result['starting_capital']}` {self._config['stake_currency']}"
-                    f"`{self._config['dry_run_wallet']}` {self._config['stake_currency']}.\n"
                        )
+            output += (f" `{result['starting_capital_fiat']}` "
+                       f"{self._config['fiat_display_currency']}.\n"
+                       ) if result['starting_capital_fiat'] > 0 else '.\n'
+
             total_dust_balance = 0
             total_dust_currencies = 0
             for curr in result['currencies']:
@@ -641,9 +644,12 @@ class Telegram(RPCHandler):
                     f"{round_coin_value(total_dust_balance, result['stake'], False)}`\n")
 
             output += ("\n*Estimated Value*:\n"
-                       f"\t`{result['stake']}: {result['total']: .8f}`\n"
+                       f"\t`{result['stake']}: "
+                       f"{round_coin_value(result['total'], result['stake'], False)}`"
+                       f" `({result['starting_capital_pct']}%)`\n"
                        f"\t`{result['symbol']}: "
-                       f"{round_coin_value(result['value'], result['symbol'], False)}`\n")
+                       f"{round_coin_value(result['value'], result['symbol'], False)}`"
+                       f" `({result['starting_capital_fiat_pct']}%)`\n")
             self._send_msg(output, reload_able=True, callback_path="update_balance",
                            query=update.callback_query)
         except RPCException as e:

freqtrade/strategy/__init__.py

@@ -3,5 +3,7 @@ from freqtrade.exchange import (timeframe_to_minutes, timeframe_to_msecs, timefr
                                 timeframe_to_prev_date, timeframe_to_seconds)
 from freqtrade.strategy.hyper import (BooleanParameter, CategoricalParameter, DecimalParameter,
                                       IntParameter, RealParameter)
+from freqtrade.strategy.informative_decorator import informative
 from freqtrade.strategy.interface import IStrategy
-from freqtrade.strategy.strategy_helper import merge_informative_pair, stoploss_from_open
+from freqtrade.strategy.strategy_helper import (merge_informative_pair, stoploss_from_absolute,
+                                                stoploss_from_open)

freqtrade/strategy/informative_decorator.py

@@ -0,0 +1,128 @@
+from typing import Any, Callable, NamedTuple, Optional, Union
+
+from pandas import DataFrame
+
+from freqtrade.exceptions import OperationalException
+from freqtrade.strategy.strategy_helper import merge_informative_pair
+
+
+PopulateIndicators = Callable[[Any, DataFrame, dict], DataFrame]
+
+
+class InformativeData(NamedTuple):
+    asset: Optional[str]
+    timeframe: str
+    fmt: Union[str, Callable[[Any], str], None]
+    ffill: bool
+
+
+def informative(timeframe: str, asset: str = '',
+                fmt: Optional[Union[str, Callable[[Any], str]]] = None,
+                ffill: bool = True) -> Callable[[PopulateIndicators], PopulateIndicators]:
+    """
+    A decorator for populate_indicators_Nn(self, dataframe, metadata), allowing these functions to
+    define informative indicators.
+
+    Example usage:
+
+        @informative('1h')
+        def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+            return dataframe
+
+    :param timeframe: Informative timeframe. Must always be equal or higher than strategy timeframe.
+    :param asset: Informative asset, for example BTC, BTC/USDT, ETH/BTC. Do not specify to use
+    current pair.
+    :param fmt: Column format (str) or column formatter (callable(name, asset, timeframe)). When not
+    specified, defaults to:
+    * {base}_{quote}_{column}_{timeframe} if asset is specified.
+    * {column}_{timeframe} if asset is not specified.
+    Format string supports these format variables:
+    * {asset} - full name of the asset, for example 'BTC/USDT'.
+    * {base} - base currency in lower case, for example 'eth'.
+    * {BASE} - same as {base}, except in upper case.
+    * {quote} - quote currency in lower case, for example 'usdt'.
+    * {QUOTE} - same as {quote}, except in upper case.
+    * {column} - name of dataframe column.
+    * {timeframe} - timeframe of informative dataframe.
+    :param ffill: ffill dataframe after merging informative pair.
+    """
+    _asset = asset
+    _timeframe = timeframe
+    _fmt = fmt
+    _ffill = ffill
+
+    def decorator(fn: PopulateIndicators):
+        informative_pairs = getattr(fn, '_ft_informative', [])
+        informative_pairs.append(InformativeData(_asset, _timeframe, _fmt, _ffill))
+        setattr(fn, '_ft_informative', informative_pairs)
+        return fn
+    return decorator
+
+
+def _format_pair_name(config, pair: str) -> str:
+    return pair.format(stake_currency=config['stake_currency'],
+                       stake=config['stake_currency']).upper()
+
+
+def _create_and_merge_informative_pair(strategy, dataframe: DataFrame, metadata: dict,
+                                       inf_data: InformativeData,
+                                       populate_indicators: PopulateIndicators):
+    asset = inf_data.asset or ''
+    timeframe = inf_data.timeframe
+    fmt = inf_data.fmt
+    config = strategy.config
+
+    if asset:
+        # Insert stake currency if needed.
+        asset = _format_pair_name(config, asset)
+    else:
+        # Not specifying an asset will define informative dataframe for current pair.
+        asset = metadata['pair']
+
+    if '/' in asset:
+        base, quote = asset.split('/')
+    else:
+        # When futures are supported this may need reevaluation.
+        # base, quote = asset, ''
+        raise OperationalException('Not implemented.')
+
+    # Default format. This optimizes for the common case: informative pairs using same stake
+    # currency. When quote currency matches stake currency, column name will omit base currency.
+    # This allows easily reconfiguring strategy to use different base currency. In a rare case
+    # where it is desired to keep quote currency in column name at all times user should specify
+    # fmt='{base}_{quote}_{column}_{timeframe}' format or similar.
+    if not fmt:
+        fmt = '{column}_{timeframe}'                # Informatives of current pair
+        if inf_data.asset:
+            fmt = '{base}_{quote}_' + fmt           # Informatives of other pairs
+
+    inf_metadata = {'pair': asset, 'timeframe': timeframe}
+    inf_dataframe = strategy.dp.get_pair_dataframe(asset, timeframe)
+    inf_dataframe = populate_indicators(strategy, inf_dataframe, inf_metadata)
+
+    formatter: Any = None
+    if callable(fmt):
+        formatter = fmt             # A custom user-specified formatter function.
+    else:
+        formatter = fmt.format      # A default string formatter.
+
+    fmt_args = {
+        'BASE': base.upper(),
+        'QUOTE': quote.upper(),
+        'base': base.lower(),
+        'quote': quote.lower(),
+        'asset': asset,
+        'timeframe': timeframe,
+    }
+    inf_dataframe.rename(columns=lambda column: formatter(column=column, **fmt_args),
+                         inplace=True)
+
+    date_column = formatter(column='date', **fmt_args)
+    if date_column in dataframe.columns:
+        raise OperationalException(f'Duplicate column name {date_column} exists in '
+                                   f'dataframe! Ensure column names are unique!')
+    dataframe = merge_informative_pair(dataframe, inf_dataframe, strategy.timeframe, timeframe,
+                                       ffill=inf_data.ffill, append_timeframe=False,
+                                       date_column=date_column)
+    return dataframe

freqtrade/strategy/interface.py

@@ -19,6 +19,9 @@ from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
 from freqtrade.exchange.exchange import timeframe_to_next_date
 from freqtrade.persistence import PairLocks, Trade
 from freqtrade.strategy.hyper import HyperStrategyMixin
+from freqtrade.strategy.informative_decorator import (InformativeData, PopulateIndicators,
+                                                      _create_and_merge_informative_pair,
+                                                      _format_pair_name)
 from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
 from freqtrade.wallets import Wallets
 
@@ -118,7 +121,7 @@ class IStrategy(ABC, HyperStrategyMixin):
     # Class level variables (intentional) containing
     # the dataprovider (dp) (access to other candles, historic data, ...)
     # and wallets - access to the current balance.
-    dp: Optional[DataProvider] = None
+    dp: Optional[DataProvider]
     wallets: Optional[Wallets] = None
     # Filled from configuration
     stake_currency: str
@@ -134,6 +137,24 @@ class IStrategy(ABC, HyperStrategyMixin):
         self._last_candle_seen_per_pair: Dict[str, datetime] = {}
         super().__init__(config)
 
+        # Gather informative pairs from @informative-decorated methods.
+        self._ft_informative: List[Tuple[InformativeData, PopulateIndicators]] = []
+        for attr_name in dir(self.__class__):
+            cls_method = getattr(self.__class__, attr_name)
+            if not callable(cls_method):
+                continue
+            informative_data_list = getattr(cls_method, '_ft_informative', None)
+            if not isinstance(informative_data_list, list):
+                # Type check is required because mocker would return a mock object that evaluates to
+                # True, confusing this code.
+                continue
+            strategy_timeframe_minutes = timeframe_to_minutes(self.timeframe)
+            for informative_data in informative_data_list:
+                if timeframe_to_minutes(informative_data.timeframe) < strategy_timeframe_minutes:
+                    raise OperationalException('Informative timeframe must be equal or higher than '
+                                               'strategy timeframe!')
+                self._ft_informative.append((informative_data, cls_method))
+
     @abstractmethod
     def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         """
@@ -377,6 +398,23 @@ class IStrategy(ABC, HyperStrategyMixin):
 # END - Intended to be overridden by strategy
 ###
 
+    def gather_informative_pairs(self) -> ListPairsWithTimeframes:
+        """
+        Internal method which gathers all informative pairs (user or automatically defined).
+        """
+        informative_pairs = self.informative_pairs()
+        for inf_data, _ in self._ft_informative:
+            if inf_data.asset:
+                pair_tf = (_format_pair_name(self.config, inf_data.asset), inf_data.timeframe)
+                informative_pairs.append(pair_tf)
+            else:
+                if not self.dp:
+                    raise OperationalException('@informative decorator with unspecified asset '
+                                               'requires DataProvider instance.')
+                for pair in self.dp.current_whitelist():
+                    informative_pairs.append((pair, inf_data.timeframe))
+        return list(set(informative_pairs))
+
     def get_strategy_name(self) -> str:
         """
         Returns strategy class name
@@ -802,6 +840,12 @@ class IStrategy(ABC, HyperStrategyMixin):
         :return: a Dataframe with all mandatory indicators for the strategies
         """
         logger.debug(f"Populating indicators for pair {metadata.get('pair')}.")
+
+        # call populate_indicators_Nm() which were tagged with @informative decorator.
+        for inf_data, populate_fn in self._ft_informative:
+            dataframe = _create_and_merge_informative_pair(
+                self, dataframe, metadata, inf_data, populate_fn)
+
         if self._populate_fun_len == 2:
             warnings.warn("deprecated - check out the Sample strategy to see "
                           "the current function headers!", DeprecationWarning)

freqtrade/strategy/strategy_helper.py

@@ -4,7 +4,9 @@ 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:
+                           timeframe: str, timeframe_inf: str, ffill: bool = True,
+                           append_timeframe: bool = True,
+                           date_column: str = 'date') -> pd.DataFrame:
     """
     Correctly merge informative samples to the original dataframe, avoiding lookahead bias.
 
@@ -24,6 +26,8 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.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
+    :param append_timeframe: Rename columns by appending timeframe.
+    :param date_column: A custom date column name.
     :return: Merged dataframe
     :raise: ValueError if the secondary timeframe is shorter than the dataframe timeframe
     """
@@ -32,25 +36,29 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
     minutes = timeframe_to_minutes(timeframe)
     if minutes == minutes_inf:
         # No need to forwardshift if the timeframes are identical
-        informative['date_merge'] = informative["date"]
+        informative['date_merge'] = informative[date_column]
     elif minutes < minutes_inf:
         # Subtract "small" timeframe so merging is not delayed by 1 small candle
         # Detailed explanation in https://github.com/freqtrade/freqtrade/issues/4073
         informative['date_merge'] = (
-            informative["date"] + pd.to_timedelta(minutes_inf, 'm') - pd.to_timedelta(minutes, 'm')
+            informative[date_column] + pd.to_timedelta(minutes_inf, 'm') -
+            pd.to_timedelta(minutes, 'm')
         )
     else:
         raise ValueError("Tried to merge a faster timeframe to a slower timeframe."
                          "This would create new rows, and can throw off your regular indicators.")
 
     # Rename columns to be unique
+    date_merge = 'date_merge'
+    if append_timeframe:
+        date_merge = f'date_merge_{timeframe_inf}'
         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')
+                         right_on=date_merge, how='left')
-    dataframe = dataframe.drop(f'date_merge_{timeframe_inf}', axis=1)
+    dataframe = dataframe.drop(date_merge, axis=1)
 
     if ffill:
         dataframe = dataframe.ffill()
@@ -83,3 +91,28 @@ def stoploss_from_open(open_relative_stop: float, current_profit: float) -> floa
 
     # negative stoploss values indicate the requested stop price is higher than the current price
     return max(stoploss, 0.0)
+
+
+def stoploss_from_absolute(stop_rate: float, current_rate: float) -> float:
+    """
+    Given current price and desired stop price, return a stop loss value that is relative to current
+    price.
+
+    The requested stop can be positive for a stop above the open price, or negative for
+    a stop below the open price. The return value is always >= 0.
+
+    Returns 0 if the resulting stop price would be above the current price.
+
+    :param stop_rate: Stop loss price.
+    :param current_rate: Current asset price.
+    :return: Positive stop loss value relative to current price
+    """
+
+    # formula is undefined for current_rate 0, return maximum value
+    if current_rate == 0:
+        return 1
+
+    stoploss = 1 - (stop_rate / current_rate)
+
+    # negative stoploss values indicate the requested stop price is higher than the current price
+    return max(stoploss, 0.0)

setup.sh

@@ -62,7 +62,7 @@ function updateenv() {
     then
         REQUIREMENTS_PLOT="-r requirements-plot.txt"
     fi
-    if [ "${SYS_ARCH}" == "armv7l" ]; then
+    if [ "${SYS_ARCH}" == "armv7l" ] || [ "${SYS_ARCH}" == "armv6l" ]; then
         echo "Detected Raspberry, installing cython, skipping hyperopt installation."
         ${PYTHON} -m pip install --upgrade cython
     else

tests/plugins/test_pairlist.py

@@ -12,7 +12,8 @@ from freqtrade.persistence import Trade
 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
 from freqtrade.plugins.pairlistmanager import PairListManager
 from freqtrade.resolvers import PairListResolver
-from tests.conftest import get_patched_exchange, get_patched_freqtradebot, log_has, log_has_re
+from tests.conftest import (create_mock_trades, get_patched_exchange, get_patched_freqtradebot,
+                            log_has, log_has_re)
 
 
 @pytest.fixture(scope="function")
@@ -663,6 +664,31 @@ def test_PerformanceFilter_error(mocker, whitelist_conf, caplog) -> None:
     assert log_has("PerformanceFilter is not available in this mode.", caplog)
 
 
+@pytest.mark.usefixtures("init_persistence")
+def test_PerformanceFilter_lookback(mocker, whitelist_conf, fee) -> None:
+    whitelist_conf['exchange']['pair_whitelist'].append('XRP/BTC')
+    whitelist_conf['pairlists'] = [
+        {"method": "StaticPairList"},
+        {"method": "PerformanceFilter", "minutes": 60}
+    ]
+    mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
+    exchange = get_patched_exchange(mocker, whitelist_conf)
+    pm = PairListManager(exchange, whitelist_conf)
+    pm.refresh_pairlist()
+
+    assert pm.whitelist == ['ETH/BTC', 'TKN/BTC', 'XRP/BTC']
+
+    with time_machine.travel("2021-09-01 05:00:00 +00:00") as t:
+        create_mock_trades(fee)
+        pm.refresh_pairlist()
+        assert pm.whitelist == ['XRP/BTC', 'ETH/BTC', 'TKN/BTC']
+
+        # Move to "outside" of lookback window, so original sorting is restored.
+        t.move_to("2021-09-01 07:00:00 +00:00")
+        pm.refresh_pairlist()
+        assert pm.whitelist == ['ETH/BTC', 'TKN/BTC', 'XRP/BTC']
+
+
 def test_gen_pair_whitelist_not_supported(mocker, default_conf, tickers) -> None:
     default_conf['pairlists'] = [{'method': 'VolumePairList', 'number_assets': 10}]
 

tests/rpc/test_rpc_apiserver.py

@@ -422,20 +422,22 @@ def test_api_stopbuy(botclient):
     assert ftbot.config['max_open_trades'] == 0
 
 
-def test_api_balance(botclient, mocker, rpc_balance):
+def test_api_balance(botclient, mocker, rpc_balance, tickers):
     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_tickers', tickers)
     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()
+    response = rc.json()
-    assert len(rc.json()["currencies"]) == 5
+    assert "currencies" in response
-    assert rc.json()['currencies'][0] == {
+    assert len(response["currencies"]) == 5
+    assert response['currencies'][0] == {
         'currency': 'BTC',
         'free': 12.0,
         'balance': 12.0,
@@ -443,6 +445,10 @@ def test_api_balance(botclient, mocker, rpc_balance):
         'est_stake': 12.0,
         'stake': 'BTC',
     }
+    assert 'starting_capital' in response
+    assert 'starting_capital_fiat' in response
+    assert 'starting_capital_pct' in response
+    assert 'starting_capital_ratio' in response
 
 
 def test_api_count(botclient, mocker, ticker, fee, markets):
@@ -1218,6 +1224,7 @@ def test_api_strategies(botclient):
     assert_response(rc)
     assert rc.json() == {'strategies': [
         'HyperoptableStrategy',
+        'InformativeDecoratorTest',
         'StrategyTestV2',
         'TestStrategyLegacyV1'
     ]}

tests/rpc/test_rpc_telegram.py

@@ -576,6 +576,8 @@ def test_balance_handle_too_large_response(default_conf, update, mocker) -> None
         'total': 100.0,
         'symbol': 100.0,
         'value': 1000.0,
+        'starting_capital': 1000,
+        'starting_capital_fiat': 1000,
     })
 
     telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)

tests/strategy/strats/informative_decorator_strategy.py

@@ -0,0 +1,75 @@
+# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
+
+from pandas import DataFrame
+
+from freqtrade.strategy import informative, merge_informative_pair
+from freqtrade.strategy.interface import IStrategy
+
+
+class InformativeDecoratorTest(IStrategy):
+    """
+    Strategy used by tests 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
+    stoploss = -0.10
+    timeframe = '5m'
+    startup_candle_count: int = 20
+
+    def informative_pairs(self):
+        return [('BTC/USDT', '5m')]
+
+    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe['buy'] = 0
+        return dataframe
+
+    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe['sell'] = 0
+        return dataframe
+
+    # Decorator stacking test.
+    @informative('30m')
+    @informative('1h')
+    def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe['rsi'] = 14
+        return dataframe
+
+    # Simple informative test.
+    @informative('1h', 'BTC/{stake}')
+    def populate_indicators_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe['rsi'] = 14
+        return dataframe
+
+    # Quote currency different from stake currency test.
+    @informative('1h', 'ETH/BTC')
+    def populate_indicators_eth_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe['rsi'] = 14
+        return dataframe
+
+    # Formatting test.
+    @informative('30m', 'BTC/{stake}', '{column}_{BASE}_{QUOTE}_{base}_{quote}_{asset}_{timeframe}')
+    def populate_indicators_btc_1h_2(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe['rsi'] = 14
+        return dataframe
+
+    # Custom formatter test
+    @informative('30m', 'ETH/{stake}', fmt=lambda column, **kwargs: column + '_from_callable')
+    def populate_indicators_eth_30m(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        dataframe['rsi'] = 14
+        return dataframe
+
+    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+        # Strategy timeframe indicators for current pair.
+        dataframe['rsi'] = 14
+        # Informative pairs are available in this method.
+        dataframe['rsi_less'] = dataframe['rsi'] < dataframe['rsi_1h']
+
+        # Mixing manual informative pairs with decorators.
+        informative = self.dp.get_pair_dataframe('BTC/USDT', '5m')
+        informative['rsi'] = 14
+        dataframe = merge_informative_pair(dataframe, informative, self.timeframe, '5m', ffill=True)
+
+        return dataframe

tests/strategy/test_interface.py

@@ -611,7 +611,7 @@ def test_is_informative_pairs_callback(default_conf):
     strategy = StrategyResolver.load_strategy(default_conf)
     # Should return empty
     # Uses fallback to base implementation
-    assert [] == strategy.informative_pairs()
+    assert [] == strategy.gather_informative_pairs()
 
 
 @pytest.mark.parametrize('error', [

tests/strategy/test_strategy_helpers.py

@@ -4,7 +4,9 @@ import numpy as np
 import pandas as pd
 import pytest
 
-from freqtrade.strategy import merge_informative_pair, stoploss_from_open, timeframe_to_minutes
+from freqtrade.data.dataprovider import DataProvider
+from freqtrade.strategy import (merge_informative_pair, stoploss_from_absolute, stoploss_from_open,
+                                timeframe_to_minutes)
 
 
 def generate_test_data(timeframe: str, size: int):
@@ -132,3 +134,65 @@ def test_stoploss_from_open():
                         assert stoploss == 0
                     else:
                         assert isclose(stop_price, expected_stop_price, rel_tol=0.00001)
+
+
+def test_stoploss_from_absolute():
+    assert stoploss_from_absolute(90, 100) == 1 - (90 / 100)
+    assert stoploss_from_absolute(100, 100) == 0
+    assert stoploss_from_absolute(110, 100) == 0
+    assert stoploss_from_absolute(100, 0) == 1
+    assert stoploss_from_absolute(0, 100) == 1
+
+
+def test_informative_decorator(mocker, default_conf):
+    test_data_5m = generate_test_data('5m', 40)
+    test_data_30m = generate_test_data('30m', 40)
+    test_data_1h = generate_test_data('1h', 40)
+    data = {
+        ('XRP/USDT', '5m'): test_data_5m,
+        ('XRP/USDT', '30m'): test_data_30m,
+        ('XRP/USDT', '1h'): test_data_1h,
+        ('LTC/USDT', '5m'): test_data_5m,
+        ('LTC/USDT', '30m'): test_data_30m,
+        ('LTC/USDT', '1h'): test_data_1h,
+        ('BTC/USDT', '30m'): test_data_30m,
+        ('BTC/USDT', '5m'): test_data_5m,
+        ('BTC/USDT', '1h'): test_data_1h,
+        ('ETH/USDT', '1h'): test_data_1h,
+        ('ETH/USDT', '30m'): test_data_30m,
+        ('ETH/BTC', '1h'): test_data_1h,
+    }
+    from .strats.informative_decorator_strategy import InformativeDecoratorTest
+    default_conf['stake_currency'] = 'USDT'
+    strategy = InformativeDecoratorTest(config=default_conf)
+    strategy.dp = DataProvider({}, None, None)
+    mocker.patch.object(strategy.dp, 'current_whitelist', return_value=[
+        'XRP/USDT', 'LTC/USDT', 'BTC/USDT'
+    ])
+
+    assert len(strategy._ft_informative) == 6   # Equal to number of decorators used
+    informative_pairs = [('XRP/USDT', '1h'), ('LTC/USDT', '1h'), ('XRP/USDT', '30m'),
+                         ('LTC/USDT', '30m'), ('BTC/USDT', '1h'), ('BTC/USDT', '30m'),
+                         ('BTC/USDT', '5m'), ('ETH/BTC', '1h'), ('ETH/USDT', '30m')]
+    for inf_pair in informative_pairs:
+        assert inf_pair in strategy.gather_informative_pairs()
+
+    def test_historic_ohlcv(pair, timeframe):
+        return data[(pair, timeframe or strategy.timeframe)].copy()
+    mocker.patch('freqtrade.data.dataprovider.DataProvider.historic_ohlcv',
+                 side_effect=test_historic_ohlcv)
+
+    analyzed = strategy.advise_all_indicators(
+        {p: data[(p, strategy.timeframe)] for p in ('XRP/USDT', 'LTC/USDT')})
+    expected_columns = [
+        'rsi_1h', 'rsi_30m',                    # Stacked informative decorators
+        'btc_usdt_rsi_1h',                      # BTC 1h informative
+        'rsi_BTC_USDT_btc_usdt_BTC/USDT_30m',   # Column formatting
+        'rsi_from_callable',                    # Custom column formatter
+        'eth_btc_rsi_1h',                       # Quote currency not matching stake currency
+        'rsi', 'rsi_less',                      # Non-informative columns
+        'rsi_5m',                               # Manual informative dataframe
+    ]
+    for _, dataframe in analyzed.items():
+        for col in expected_columns:
+            assert col in dataframe.columns

tests/strategy/test_strategy_loading.py

@@ -35,7 +35,7 @@ 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) == 3
+    assert len(strategies) == 4
     assert isinstance(strategies[0], dict)
 
 
@@ -43,10 +43,10 @@ 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) == 4
+    assert len(strategies) == 5
     # 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]) == 3
+    assert len([x for x in strategies if x['class'] is not None]) == 4
     assert len([x for x in strategies if x['class'] is None]) == 1
 
 

tests/test_freqtradebot.py

@@ -78,43 +78,15 @@ def test_bot_cleanup(mocker, default_conf, caplog) -> None:
     assert coo_mock.call_count == 1
 
 
-def test_order_dict_dry_run(default_conf, mocker, caplog) -> None:
+@pytest.mark.parametrize('runmode', [
+    RunMode.DRY_RUN,
+    RunMode.LIVE
+])
+def test_order_dict(default_conf, mocker, runmode, caplog) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     conf = default_conf.copy()
-    conf['runmode'] = RunMode.DRY_RUN
+    conf['runmode'] = runmode
-    conf['order_types'] = {
-        'buy': 'market',
-        'sell': 'limit',
-        'stoploss': 'limit',
-        'stoploss_on_exchange': True,
-    }
-    conf['bid_strategy']['price_side'] = 'ask'
-
-    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)
-
-    conf = default_conf.copy()
-    conf['runmode'] = RunMode.LIVE
     conf['order_types'] = {
         'buy': 'market',
         'sell': 'limit',
@@ -124,13 +96,14 @@ def test_order_dict_live(default_conf, mocker, caplog) -> None:
     conf['bid_strategy']['price_side'] = 'ask'
 
     freqtrade = FreqtradeBot(conf)
+    if runmode == RunMode.LIVE:
         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['runmode'] = runmode
     conf['order_types'] = {
         'buy': 'market',
         'sell': 'limit',
@@ -219,8 +192,14 @@ def test_edge_overrides_stake_amount(mocker, edge_conf) -> None:
         'LTC/BTC', freqtrade.edge) == (999.9 * 0.5 * 0.01) / 0.21
 
 
-def test_edge_overrides_stoploss(limit_buy_order, fee, caplog, mocker, edge_conf) -> None:
+@pytest.mark.parametrize('buy_price_mult,ignore_strat_sl', [
-
+    # Override stoploss
+    (0.79, False),
+    # Override strategy stoploss
+    (0.85, True)
+])
+def test_edge_overrides_stoploss(limit_buy_order, fee, caplog, mocker,
+                                 buy_price_mult, ignore_strat_sl, edge_conf) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     patch_edge(mocker)
@@ -234,9 +213,9 @@ def test_edge_overrides_stoploss(limit_buy_order, fee, caplog, mocker, edge_conf
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': buy_price * 0.79,
+            'bid': buy_price * buy_price_mult,
-            'ask': buy_price * 0.79,
+            'ask': buy_price * buy_price_mult,
-            'last': buy_price * 0.79
+            'last': buy_price * buy_price_mult,
         }),
         get_fee=fee,
     )
@@ -253,48 +232,12 @@ def test_edge_overrides_stoploss(limit_buy_order, fee, caplog, mocker, edge_conf
     #############################################
 
     # stoploss shoud be hit
-    assert freqtrade.handle_trade(trade) is True
+    assert freqtrade.handle_trade(trade) is not ignore_strat_sl
+    if not ignore_strat_sl:
         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)
@@ -376,8 +319,16 @@ def test_create_trade_no_stake_amount(default_conf, ticker, limit_buy_order,
         freqtrade.create_trade('ETH/BTC')
 
 
-def test_create_trade_minimal_amount(default_conf, ticker, limit_buy_order_open,
+@pytest.mark.parametrize('stake_amount,create,amount_enough,max_open_trades', [
-                                     fee, mocker) -> None:
+    (0.0005, True, True, 99),
+    (0.000000005, True, False, 99),
+    (0, False, True, 99),
+    (UNLIMITED_STAKE_AMOUNT, False, True, 0),
+])
+def test_create_trade_minimal_amount(
+    default_conf, ticker, limit_buy_order_open, fee, mocker,
+    stake_amount, create, amount_enough, max_open_trades, caplog
+) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     buy_mock = MagicMock(return_value=limit_buy_order_open)
@@ -387,78 +338,33 @@ def test_create_trade_minimal_amount(default_conf, ticker, limit_buy_order_open,
         create_order=buy_mock,
         get_fee=fee,
     )
-    default_conf['stake_amount'] = 0.0005
+    default_conf['max_open_trades'] = max_open_trades
     freqtrade = FreqtradeBot(default_conf)
+    freqtrade.config['stake_amount'] = stake_amount
     patch_get_signal(freqtrade)
 
-    freqtrade.create_trade('ETH/BTC')
+    if create:
+        assert freqtrade.create_trade('ETH/BTC')
+        if amount_enough:
             rate, amount = buy_mock.call_args[1]['rate'], buy_mock.call_args[1]['amount']
             assert rate * amount <= default_conf['stake_amount']
-
+        else:
-
+            assert log_has_re(
-def test_create_trade_too_small_stake_amount(default_conf, ticker, limit_buy_order_open,
+                r"Stake amount for pair .* is too small.*",
-                                             fee, mocker, caplog) -> None:
+                caplog
-    patch_RPCManager(mocker)
-    patch_exchange(mocker)
-    buy_mock = MagicMock(return_value=limit_buy_order_open)
-    mocker.patch.multiple(
-        'freqtrade.exchange.Exchange',
-        fetch_ticker=ticker,
-        create_order=buy_mock,
-        get_fee=fee,
             )
-
+    else:
-    freqtrade = FreqtradeBot(default_conf)
-    freqtrade.config['stake_amount'] = 0.000000005
-
-    patch_get_signal(freqtrade)
-
-    assert freqtrade.create_trade('ETH/BTC')
-    assert log_has_re(r"Stake amount for pair .* is too small.*", caplog)
-
-
-def test_create_trade_zero_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,
-        create_order=buy_mock,
-        get_fee=fee,
-    )
-
-    freqtrade = FreqtradeBot(default_conf)
-    freqtrade.config['stake_amount'] = 0
-
-    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,
-        create_order=MagicMock(return_value=limit_buy_order_open),
-        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')
+        if not max_open_trades:
             assert freqtrade.wallets.get_trade_stake_amount('ETH/BTC', freqtrade.edge) == 0
 
 
+@pytest.mark.parametrize('whitelist,positions', [
+    (["ETH/BTC"], 1),  # No pairs left
+    ([], 0),  # No pairs in whitelist
+])
 def test_enter_positions_no_pairs_left(default_conf, ticker, limit_buy_order_open, fee,
-                                       mocker, caplog) -> None:
+                                       whitelist, positions, mocker, caplog) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
@@ -467,34 +373,18 @@ def test_enter_positions_no_pairs_left(default_conf, ticker, limit_buy_order_ope
         create_order=MagicMock(return_value=limit_buy_order_open),
         get_fee=fee,
     )
-
+    default_conf['exchange']['pair_whitelist'] = whitelist
-    default_conf['exchange']['pair_whitelist'] = ["ETH/BTC"]
     freqtrade = FreqtradeBot(default_conf)
     patch_get_signal(freqtrade)
 
     n = freqtrade.enter_positions()
-    assert n == 1
+    assert n == positions
+    if positions:
         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)
-
+    else:
-
-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,
-        create_order=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)
 
@@ -1668,30 +1558,27 @@ def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog,
     )
 
 
-def test_enter_positions(mocker, default_conf, caplog) -> None:
+@pytest.mark.parametrize('return_value,side_effect,log_message', [
+    (False, None, 'Found no buy signals for whitelisted currencies. Trying again...'),
+    (None, DependencyException, 'Unable to create trade for ETH/BTC: ')
+])
+def test_enter_positions(mocker, default_conf, return_value, side_effect,
+                         log_message, 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 enter 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)
+        MagicMock(
+            return_value=return_value,
+            side_effect=side_effect
+        )
     )
     n = freqtrade.enter_positions()
     assert n == 0
+    assert log_has(log_message, caplog)
+    # create_trade should be called once for every pair in the whitelist.
     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:
@@ -1785,8 +1672,13 @@ def test_update_trade_state(mocker, default_conf, limit_buy_order, caplog) -> No
     assert log_has_re('Found open order for.*', caplog)
 
 
+@pytest.mark.parametrize('initial_amount,has_rounding_fee', [
+    (90.99181073 + 1e-14, True),
+    (8.0, False)
+])
 def test_update_trade_state_withorderdict(default_conf, trades_for_order, limit_buy_order, fee,
-                                          mocker):
+                                          mocker, initial_amount, has_rounding_fee, caplog):
+    trades_for_order[0]['amount'] = initial_amount
     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))
@@ -1807,31 +1699,7 @@ def test_update_trade_state_withorderdict(default_conf, trades_for_order, limit_
     freqtrade.update_trade_state(trade, '123456', limit_buy_order)
     assert trade.amount != amount
     assert trade.amount == limit_buy_order['amount']
-
+    if has_rounding_fee:
-
-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)
-    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)
 
 
@@ -3144,16 +3012,28 @@ def test_execute_trade_exit_insufficient_funds_error(default_conf, ticker, fee,
     assert mock_insuf.call_count == 1
 
 
-def test_sell_profit_only_enable_profit(default_conf, limit_buy_order, limit_buy_order_open,
+@pytest.mark.parametrize('profit_only,bid,ask,handle_first,handle_second,sell_type', [
-                                        fee, mocker) -> None:
+    # Enable profit
+    (True, 0.00001172, 0.00001173, False, True, SellType.SELL_SIGNAL.value),
+    # Disable profit
+    (False, 0.00002172, 0.00002173, True,  False, SellType.SELL_SIGNAL.value),
+    # Enable loss
+    # * Shouldn't this be SellType.STOP_LOSS.value
+    (True, 0.00000172, 0.00000173, False, False, None),
+    # Disable loss
+    (False, 0.00000172, 0.00000173, True, False, SellType.SELL_SIGNAL.value),
+])
+def test_sell_profit_only(
+        default_conf, limit_buy_order, limit_buy_order_open,
+        fee, mocker, profit_only, bid, ask, handle_first, handle_second, sell_type) -> None:
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
         fetch_ticker=MagicMock(return_value={
-            'bid': 0.00001172,
+            'bid': bid,
-            'ask': 0.00001173,
+            'ask': ask,
-            'last': 0.00001172
+            'last': bid
         }),
         create_order=MagicMock(side_effect=[
             limit_buy_order_open,
@@ -3163,128 +3043,29 @@ def test_sell_profit_only_enable_profit(default_conf, limit_buy_order, limit_buy
     )
     default_conf.update({
         'use_sell_signal': True,
-        'sell_profit_only': True,
+        'sell_profit_only': profit_only,
         'sell_profit_offset': 0.1,
     })
     freqtrade = FreqtradeBot(default_conf)
     patch_get_signal(freqtrade)
+    if sell_type == SellType.SELL_SIGNAL.value:
         freqtrade.strategy.min_roi_reached = MagicMock(return_value=False)
-
+    else:
-    freqtrade.enter_positions()
-
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    freqtrade.wallets.update()
-    patch_get_signal(freqtrade, value=(False, True, None))
-    assert freqtrade.handle_trade(trade) is False
-
-    freqtrade.strategy.sell_profit_offset = 0.0
-    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
-        }),
-        create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
-            {'id': 1234553382},
-        ]),
-        get_fee=fee,
-    )
-    default_conf.update({
-        '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, None))
-    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
-        }),
-        create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
-            {'id': 1234553382},
-        ]),
-        get_fee=fee,
-    )
-    default_conf.update({
-        '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_type=SellType.NONE))
     freqtrade.enter_positions()
 
-    trade = Trade.query.first()
-    trade.update(limit_buy_order)
-    patch_get_signal(freqtrade, value=(False, True, None))
-    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
-        }),
-        create_order=MagicMock(side_effect=[
-            limit_buy_order_open,
-            {'id': 1234553382},
-        ]),
-        get_fee=fee,
-    )
-    default_conf.update({
-        '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, None))
+    assert freqtrade.handle_trade(trade) is handle_first
+
+    if handle_second:
+        freqtrade.strategy.sell_profit_offset = 0.0
         assert freqtrade.handle_trade(trade) is True
-    assert trade.sell_reason == SellType.SELL_SIGNAL.value
+
+    assert trade.sell_reason == sell_type
 
 
 def test_sell_not_enough_balance(default_conf, limit_buy_order, limit_buy_order_open,
@@ -3322,11 +3103,15 @@ def test_sell_not_enough_balance(default_conf, limit_buy_order, limit_buy_order_
     assert trade.amount != amnt
 
 
-def test__safe_exit_amount(default_conf, fee, caplog, mocker):
+@pytest.mark.parametrize('amount_wallet,has_err', [
+    (95.29, False),
+    (91.29, True)
+])
+def test__safe_exit_amount(default_conf, fee, caplog, mocker, amount_wallet, has_err):
     patch_RPCManager(mocker)
     patch_exchange(mocker)
     amount = 95.33
-    amount_wallet = 95.29
+    amount_wallet = amount_wallet
     mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(return_value=amount_wallet))
     wallet_update = mocker.patch('freqtrade.wallets.Wallets.update')
     trade = Trade(
@@ -3340,7 +3125,10 @@ def test__safe_exit_amount(default_conf, fee, caplog, mocker):
     )
     freqtrade = FreqtradeBot(default_conf)
     patch_get_signal(freqtrade)
-
+    if has_err:
+        with pytest.raises(DependencyException, match=r"Not enough amount to sell."):
+            assert freqtrade._safe_exit_amount(trade.pair, trade.amount)
+    else:
         wallet_update.reset_mock()
         assert freqtrade._safe_exit_amount(trade.pair, trade.amount) == amount_wallet
         assert log_has_re(r'.*Falling back to wallet-amount.', caplog)
@@ -3352,27 +3140,6 @@ def test__safe_exit_amount(default_conf, fee, caplog, mocker):
         assert wallet_update.call_count == 1
 
 
-def test__safe_exit_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 exit."):
-        assert freqtrade._safe_exit_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)
@@ -4158,50 +3925,37 @@ def test_order_book_depth_of_market_high_delta(default_conf, ticker, limit_buy_o
     assert trade is None
 
 
-def test_order_book_bid_strategy1(mocker, default_conf, order_book_l2) -> None:
+@pytest.mark.parametrize('exception_thrown,ask,last,order_book_top,order_book', [
+    (False, 0.045, 0.046, 2, None),
+    (True,  0.042, 0.046, 1, {'bids': [[]], 'asks': [[]]})
+])
+def test_order_book_bid_strategy1(mocker, default_conf, order_book_l2, exception_thrown,
+                                  ask, last, order_book_top, order_book, caplog) -> None:
     """
-    test if function get_rate will return the order book price
+    test if function get_rate will return the order book price instead of the ask rate
-    instead of the ask rate
     """
     patch_exchange(mocker)
-    ticker_mock = MagicMock(return_value={'ask': 0.045, 'last': 0.046})
+    ticker_mock = MagicMock(return_value={'ask': ask, 'last': last})
     mocker.patch.multiple(
         'freqtrade.exchange.Exchange',
-        fetch_l2_order_book=order_book_l2,
+        fetch_l2_order_book=MagicMock(return_value=order_book) if order_book else 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']['order_book_top'] = order_book_top
     default_conf['bid_strategy']['ask_last_balance'] = 0
     default_conf['telegram']['enabled'] = False
 
     freqtrade = FreqtradeBot(default_conf)
-    assert freqtrade.exchange.get_rate('ETH/BTC', refresh=True, side="buy") == 0.043935
+    if exception_thrown:
-    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.exchange.get_rate('ETH/BTC', refresh=True, side="buy")
-    assert log_has_re(r'Buy Price at location 1 from orderbook could not be determined.', caplog)
+        assert log_has_re(
+            r'Buy Price at location 1 from orderbook could not be determined.', caplog)
+    else:
+        assert freqtrade.exchange.get_rate('ETH/BTC', refresh=True, side="buy") == 0.043935
+        assert ticker_mock.call_count == 0
 
 
 def test_check_depth_of_market_buy(default_conf, mocker, order_book_l2) -> None: