from functools import reduce from pandas import DataFrame from freqtrade.strategy import IStrategy import talib.abstract as ta from freqtrade.strategy.interface import IStrategy class TrendFollowingStrategy(IStrategy): INTERFACE_VERSION = 3 INTERFACE_VERSION: int = 3 # ROI table: minimal_roi = {'0': 0.15, '30': 0.1, '60': 0.05} # minimal_roi = {"0": 1} # Stoploss: stoploss = -0.265 # Trailing stop: trailing_stop = True trailing_stop_positive = 0.05 trailing_stop_positive_offset = 0.1 trailing_only_offset_is_reached = False timeframe = '5m' def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # Calculate OBV dataframe['obv'] = ta.OBV(dataframe['close'], dataframe['volume']) # Add your trend following indicators here dataframe['trend'] = dataframe['close'].ewm(span=20, adjust=False).mean() return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # Add your trend following entry signals here dataframe.loc[(dataframe['close'] > dataframe['trend']) & (dataframe['close'].shift(1) <= dataframe['trend'].shift(1)) & (dataframe['obv'] > dataframe['obv'].shift(1)), 'enter_long'] = 1 # Add your trend following exit signals here dataframe.loc[(dataframe['close'] < dataframe['trend']) & (dataframe['close'].shift(1) >= dataframe['trend'].shift(1)) & (dataframe['obv'] < dataframe['obv'].shift(1)), 'enter_short'] = -1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: # Add your trend following exit signals for long positions here dataframe.loc[(dataframe['close'] < dataframe['trend']) & (dataframe['close'].shift(1) >= dataframe['trend'].shift(1)) & (dataframe['obv'] > dataframe['obv'].shift(1)), 'exit_long'] = 1 # Add your trend following exit signals for short positions here dataframe.loc[(dataframe['close'] > dataframe['trend']) & (dataframe['close'].shift(1) <= dataframe['trend'].shift(1)) & (dataframe['obv'] < dataframe['obv'].shift(1)), 'exit_short'] = 1 return dataframe