# Source: generated via dynamic_strategy_generator from freqtrade.strategy import IStrategy from pandas import DataFrame import talib.abstract as ta import freqtrade.vendor.qtpylib.indicators as qtpylib class ACO_76_10(IStrategy): timeframe = '1h' # Standard ROI and Stoploss minimal_roi = {"0": 0.1, "60": 0.05, "120": 0.0} stoploss = -0.05 def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe['adx'] = ta.ADX(dataframe, timeperiod=14) dataframe['obv'] = ta.OBV(dataframe) dataframe['obv_sma'] = ta.SMA(dataframe, timeperiod=10, price='obv') dataframe['adosc'] = ta.ADOSC(dataframe, fastperiod=2, slowperiod=5) dataframe['natr'] = ta.NATR(dataframe, timeperiod=14) dataframe['willr'] = ta.WILLR(dataframe, timeperiod=7) dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=14) dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=14) dataframe['apo'] = ta.APO(dataframe, fastperiod=5, slowperiod=20) dataframe['sma_fast'] = ta.SMA(dataframe, timeperiod=9) dataframe['sma_slow'] = ta.SMA(dataframe, timeperiod=21) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['adx'] > 30) ) & ( qtpylib.crossed_above(dataframe['obv'], dataframe['obv_sma']) ) & ( qtpylib.crossed_above(dataframe['adosc'], 0) ) & ( (dataframe['natr'] > 2.0) ), 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['willr'] > -25) ) & ( qtpylib.crossed_below(dataframe['plus_di'], dataframe['minus_di']) ) & ( qtpylib.crossed_below(dataframe['apo'], 0) ) & ( qtpylib.crossed_below(dataframe['sma_fast'], dataframe['sma_slow']) ), 'exit_long'] = 1 return dataframe