Btc1hDualStrategy

# BTC 1H Long/Short Futures Strategy v5
# Donchian breakout + Volume confirmation + ATR-based stop
# Works in trending markets, auto-switches direction

from pandas import DataFrame
import talib.abstract as ta
from freqtrade.strategy import IStrategy


class Btc1hDualStrategy(IStrategy):
    """
    BTC 1H 合约多空 v5 — 唐奇安通道突破

    做多: 价格突破20周期高点 + 放量 + EMA50向上
    做空: 价格跌破20周期低点 + 放量 + EMA50向下

    风控: ATR倍数止损 + 移动止损
    """

    INTERFACE_VERSION = 3
    timeframe = '1h'
    can_short = True

    stoploss = -0.02
    trailing_stop = True
    trailing_stop_positive = 0.015
    trailing_stop_positive_offset = 0.02
    trailing_only_offset_is_reached = True

    minimal_roi = {"0": 0.05, "240": 0.03, "720": 0.01, "1440": 0}

    max_open_trades = 3
    startup_candle_count = 60
    process_only_new_candles = True
    use_exit_signal = False  # ROI handles profit-taking, trailing protects gains

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # Donchian Channel
        dataframe['dc_upper'] = dataframe['high'].rolling(20).max().shift(1)
        dataframe['dc_lower'] = dataframe['low'].rolling(20).min().shift(1)
        dataframe['dc_mid'] = (dataframe['dc_upper'] + dataframe['dc_lower']) / 2

        # EMA
        dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)

        # Volume
        dataframe['volume_sma'] = ta.SMA(dataframe['volume'], timeperiod=20)
        dataframe['volume_ratio'] = dataframe['volume'] / dataframe['volume_sma']

        # ATR
        dataframe['atr'] = ta.ATR(dataframe, timeperiod=14)

        # ADX for trend strength
        dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)

        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # === 做多: 突破高点 + ADX强趋势 + 放量 ===
        dataframe.loc[
            (
                (dataframe['close'] > dataframe['dc_upper']) &
                (dataframe['adx'] > 25) &
                (dataframe['volume_ratio'] > 1.3) &
                (dataframe['volume'] > 0)
            ),
            ['enter_long', 'enter_tag']
        ] = (1, 'breakout_long')

        # === 做空: 跌破低点 + ADX强趋势 + 放量 ===
        dataframe.loc[
            (
                (dataframe['close'] < dataframe['dc_lower']) &
                (dataframe['adx'] > 25) &
                (dataframe['volume_ratio'] > 1.3) &
                (dataframe['volume'] > 0)
            ),
            ['enter_short', 'enter_tag']
        ] = (1, 'breakout_short')

        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # 回到通道中轨 = 突破失败，退出
        dataframe.loc[
            (dataframe['close'] < dataframe['dc_mid']),
            ['exit_long', 'exit_tag']
        ] = (1, 'dc_mid_exit')

        dataframe.loc[
            (dataframe['close'] > dataframe['dc_mid']),
            ['exit_short', 'exit_tag']
        ] = (1, 'dc_mid_exit')

        return dataframe