# source: https://raw.githubusercontent.com/bayazknn/trade-automation/bc5e1477f3652c7224438e09d946fd672257139c/strategies/ACO_86_8.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_86_8__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['adx'] = ta.ADX(dataframe, timeperiod=14)
        dataframe['obv'] = ta.OBV(dataframe)
        dataframe['obv_sma'] = ta.SMA(dataframe, timeperiod=10, price='obv')
        dataframe['atr'] = ta.ATR(dataframe, timeperiod=14)
        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['ultosc'] = ta.ULTOSC(dataframe, timeperiod1=7, timeperiod2=14, timeperiod3=28)
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            (dataframe['adx'] > 25)
        ) & (
            (dataframe['adx'] > 30)
        ) & (
            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['ultosc'] > 65)
        ),
        'exit_long'] = 1
        return dataframe