# 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_66_7(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['rsi'] = ta.RSI(dataframe, timeperiod=21) dataframe['bop'] = ta.BOP(dataframe) dataframe['dema'] = ta.DEMA(dataframe, timeperiod=10) dataframe['obv'] = ta.OBV(dataframe) dataframe['obv_sma'] = ta.SMA(dataframe, timeperiod=10, price='obv') dataframe['natr'] = ta.NATR(dataframe, timeperiod=14) macd = ta.MACD(dataframe, fastperiod=8, slowperiod=17, signalperiod=9) dataframe['macd'] = macd['macd'] dataframe['macdsignal'] = macd['macdsignal'] dataframe['macdhist'] = macd['macdhist'] dataframe['cci'] = ta.CCI(dataframe, timeperiod=20) dataframe['willr'] = ta.WILLR(dataframe, timeperiod=7) dataframe['sar'] = ta.SAR(dataframe, acceleration=0.03, maximum=0.3) return dataframe def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: dataframe.loc[ ( (dataframe['rsi'] < 35) ) & ( qtpylib.crossed_above(dataframe['bop'], 0) ) & ( qtpylib.crossed_above(dataframe['close'], dataframe['dema']) ) & ( 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[ ( qtpylib.crossed_below(dataframe['macd'], dataframe['macdsignal']) ) & ( (dataframe['cci'] > 150) ) & ( (dataframe['willr'] > -25) ) & ( qtpylib.crossed_below(dataframe['close'], dataframe['sar']) ), 'exit_long'] = 1 return dataframe