# source: https://raw.githubusercontent.com/bayazknn/trade-automation/bc5e1477f3652c7224438e09d946fd672257139c/strategies/ACO_18_13.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_18_13__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['ultosc'] = ta.ULTOSC(dataframe, timeperiod1=7, timeperiod2=14, timeperiod3=28)
        dataframe['sar'] = ta.SAR(dataframe, acceleration=0.03, maximum=0.3)
        dataframe['ad'] = ta.AD(dataframe)
        dataframe['ad_sma'] = ta.SMA(dataframe, timeperiod=10, price='ad')
        dataframe['atr'] = ta.ATR(dataframe, timeperiod=7)
        dataframe['willr'] = ta.WILLR(dataframe, timeperiod=7)
        dataframe['t3'] = ta.T3(dataframe, timeperiod=10, vfactor=0.9)
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            (dataframe['mfi'] < 25)
        ) & (
            (dataframe['ultosc'] < 30)
        ) & (
            qtpylib.crossed_above(dataframe['close'], dataframe['sar'])
        ) & (
            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[
        (
            (dataframe['willr'] > -25)
        ) & (
            qtpylib.crossed_below(dataframe['close'], dataframe['t3'])
        ),
        'exit_long'] = 1
        return dataframe