# source: https://raw.githubusercontent.com/bayazknn/trade-automation/bc5e1477f3652c7224438e09d946fd672257139c/strategies/ACO_17_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_17_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['mfi'] = ta.MFI(dataframe, timeperiod=14)
        dataframe['sma_fast'] = ta.SMA(dataframe, timeperiod=20)
        dataframe['sma_slow'] = ta.SMA(dataframe, timeperiod=50)
        dataframe['kama'] = ta.KAMA(dataframe, timeperiod=10)
        dataframe['ad'] = ta.AD(dataframe)
        dataframe['ad_sma'] = ta.SMA(dataframe, timeperiod=10, price='ad')
        dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=14)
        dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=14)
        dataframe['sar'] = ta.SAR(dataframe, acceleration=0.02, maximum=0.2)
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            (dataframe['mfi'] < 20)
        ) & (
            qtpylib.crossed_above(dataframe['sma_fast'], dataframe['sma_slow'])
        ) & (
            qtpylib.crossed_above(dataframe['close'], dataframe['kama'])
        ) & (
            qtpylib.crossed_above(dataframe['ad'], dataframe['ad_sma'])
        ),
        'enter_long'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            qtpylib.crossed_below(dataframe['plus_di'], dataframe['minus_di'])
        ) & (
            qtpylib.crossed_below(dataframe['close'], dataframe['sar'])
        ),
        'exit_long'] = 1
        return dataframe
