# source: https://raw.githubusercontent.com/bayazknn/trade-automation/bc5e1477f3652c7224438e09d946fd672257139c/strategies/ACO_8_11.py
# 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 Github_bayazknn_trade_automation__ACO_8_11__20260107_125949(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=20)
        dataframe['mfi'] = ta.MFI(dataframe, timeperiod=14)
        dataframe['mom'] = ta.MOM(dataframe, timeperiod=10)
        dataframe['dema'] = ta.DEMA(dataframe, timeperiod=10)
        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['trix'] = ta.TRIX(dataframe, timeperiod=15)
        bbands = ta.BBANDS(dataframe, timeperiod=14, nbdevup=2.0, nbdevdn=2.0)
        dataframe['upperband'] = bbands['upperband']
        dataframe['middleband'] = bbands['middleband']
        dataframe['lowerband'] = bbands['lowerband']
        dataframe['ad'] = ta.AD(dataframe)
        dataframe['ad_sma'] = ta.SMA(dataframe, timeperiod=20, price='ad')
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            (dataframe['cci'] < -150)
        ) & (
            (dataframe['mfi'] < 25)
        ) & (
            qtpylib.crossed_above(dataframe['mom'], 0)
        ) & (
            qtpylib.crossed_above(dataframe['close'], dataframe['dema'])
        ) & (
            (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['trix'], 0)
        ) & (
            (dataframe['close'] > dataframe['upperband'] * 0.98)
        ) & (
            qtpylib.crossed_below(dataframe['ad'], dataframe['ad_sma'])
        ),
        'exit_long'] = 1
        return dataframe