# 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_58_14(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['cci'] = ta.CCI(dataframe, timeperiod=14) dataframe['adx'] = ta.ADX(dataframe, timeperiod=14) dataframe['kama'] = ta.KAMA(dataframe, timeperiod=30) dataframe['obv'] = ta.OBV(dataframe) dataframe['obv_sma'] = ta.SMA(dataframe, timeperiod=10, price='obv') dataframe['natr'] = ta.NATR(dataframe, timeperiod=14) stoch = ta.STOCH(dataframe, fastk_period=21, slowk_period=5, slowd_period=5) dataframe['slowk'] = stoch['slowk'] dataframe['slowd'] = stoch['slowd'] dataframe['apo'] = ta.APO(dataframe, fastperiod=5, slowperiod=20) dataframe['wma'] = ta.WMA(dataframe, timeperiod=20) dataframe['atr'] = ta.ATR(dataframe, timeperiod=14) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['cci'] < -100) ) & ( (dataframe['adx'] > 30) ) & ( qtpylib.crossed_above(dataframe['close'], dataframe['kama']) ) & ( qtpylib.crossed_above(dataframe['obv'], dataframe['obv_sma']) ) & ( (dataframe['natr'] > 2.0) ), 'enter_long'] = 1 return dataframe def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['slowk'] > 75) ) & ( qtpylib.crossed_below(dataframe['apo'], 0) ) & ( qtpylib.crossed_below(dataframe['close'], dataframe['wma']) ), 'exit_long'] = 1 return dataframe