# 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_55_16(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['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=12, slowperiod=26, signalperiod=9)
        dataframe['macd'] = macd['macd']
        dataframe['macdsignal'] = macd['macdsignal']
        dataframe['macdhist'] = macd['macdhist']
        dataframe['wma'] = ta.WMA(dataframe, timeperiod=20)
        dataframe['t3'] = ta.T3(dataframe, timeperiod=5, vfactor=0.7)
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            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'])
        ) & (
            qtpylib.crossed_below(dataframe['close'], dataframe['wma'])
        ) & (
            qtpylib.crossed_below(dataframe['close'], dataframe['t3'])
        ),
        'exit_long'] = 1
        return dataframe