# --- Do not remove these libs --- from freqtrade.strategy.interface import IStrategy from pandas import DataFrame import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib # -------------------------------- class BbandRsi(IStrategy): """ author@: Gert Wohlgemuth converted from: https://github.com/sthewissen/Mynt/blob/master/src/Mynt.Core/Strategies/BbandRsi.cs """ # Minimal ROI designed for the strategy. # adjust based on market conditions. We would recommend to keep it low for quick turn arounds # This attribute will be overridden if the config file contains "minimal_roi" # minimal_roi = { # "0": 0.1 # } # # Optimal stoploss designed for the strategy # stoploss = -0.25 # ROI table: # ROI table: minimal_roi = { "0": 0.17139, "10": 0.07792, "66": 0.03513, "130": 0 } # Stoploss: stoploss = -0.24504 # Trailing stop: trailing_stop = True trailing_stop_positive = 0.258 trailing_stop_positive_offset = 0.35585 trailing_only_offset_is_reached = True # Optimal timeframe for the strategy timeframe = '15m' #1h def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14) # Bollinger bands bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2) dataframe['bb_lowerband'] = bollinger['lower'] dataframe['bb_middleband'] = bollinger['mid'] dataframe['bb_upperband'] = bollinger['upper'] return dataframe def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['rsi'] < 30) & (dataframe['close'] < dataframe['bb_lowerband']) ), 'buy'] = 1 return dataframe def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['rsi'] > 70) ), 'sell'] = 1 return dataframe