trade/engine/example/regime_all.py

"""
最佳牛熊判定 — 全币种全周期回测

方法：EMA200斜率 + 价格vs EMA200 + ATH回撤，3选2投票
策略：牛市只做多 / 熊市只做空 / 震荡空仓
币种：BTC / ETH / BNB / SOL，各自最早有数据到2026

用法：
    source .venv/bin/activate && python example/regime_all.py
"""

import asyncio
import sys
from datetime import datetime, timezone
from pathlib import Path
from typing import Optional

_project_root = Path(__file__).resolve().parent.parent.parent
if str(_project_root) not in sys.path:
    sys.path.insert(0, str(_project_root))

from engine.common.base import BaseStrategy, Signal, StrategyConfig
from engine.common.models import Kline
from engine.common.config import config
from engine.backtest import BacktestConfig
from engine.indicators import ema, atr
from engine.data import DataService
from engine.example.long_short import LongShortEngine


# ════════════════════════════════════════════════════════
# 3法判定器
# ════════════════════════════════════════════════════════


class RegimeDetector3:
    def __init__(self):
        self._ath = 0.0

    def update_ath(self, price: float):
        if price > self._ath:
            self._ath = price

    def ema200_slope(self, closes: list[float], idx: int) -> str:
        if idx < 210: return "unknown"
        e200 = ema(closes, 200)
        if e200[idx - 20] == 0: return "unknown"
        slope = (e200[idx] - e200[idx - 20]) / e200[idx - 20]
        if slope > 0.002: return "bull"
        if slope < -0.002: return "bear"
        return "sideways"

    def price_vs_ema200(self, closes: list[float], idx: int) -> str:
        if idx < 210: return "unknown"
        e200 = ema(closes, 200)
        if e200[idx] == 0: return "unknown"
        return "bull" if closes[idx] > e200[idx] else "bear"

    def ath_drawdown(self, closes: list[float], idx: int) -> str:
        if self._ath == 0: return "unknown"
        dd = (closes[idx] - self._ath) / self._ath
        if dd > -0.15: return "bull"
        if dd < -0.35: return "bear"
        return "sideways"

    def detect(self, closes: list[float], idx: int) -> str:
        r1 = self.ema200_slope(closes, idx)
        r2 = self.price_vs_ema200(closes, idx)
        r3 = self.ath_drawdown(closes, idx)
        b = sum(1 for r in [r1, r2, r3] if r == "bull")
        br = sum(1 for r in [r1, r2, r3] if r == "bear")
        if b >= 2: return "bull"
        if br >= 2: return "bear"
        return "sideways"


# ════════════════════════════════════════════════════════
# 自适应策略
# ════════════════════════════════════════════════════════


class RegimeEmaConfig(StrategyConfig):
    fast: int = 10; slow: int = 50; atr_stop: float = 2.5


class RegimeEmaStrategy(BaseStrategy):
    """按市场状态自适应做多/做空"""

    strategy_type = "regime_ema"

    def __init__(self, c: RegimeEmaConfig):
        super().__init__(c)
        self.cfg = c
        self._c: list[float] = []; self._h: list[float] = []; self._l: list[float] = []
        self._detector = RegimeDetector3()
        self._side: str = ""; self._hp: float = 0.0; self._lp: float = float('inf')

    async def on_kline(self, k: Kline) -> Optional[Signal]:
        self._c.append(k.close); self._h.append(k.high); self._l.append(k.low)
        self._detector.update_ath(k.close)
        n = len(self._c)
        if n < 220: return None

        regime = self._detector.detect(self._c, n - 1)

        f = ema(self._c, self.cfg.fast); s = ema(self._c, self.cfg.slow)
        a = atr(self._h, self._l, self._c, 14)
        cf, cs, ca, pf, ps = f[-1], s[-1], a[-1], f[-2], s[-2]
        if cf == 0 or cs == 0 or ca == 0: return None
        golden = pf <= ps and cf > cs; death = pf >= ps and cf < cs

        # 多头持仓
        if self._side == "long":
            self._hp = max(self._hp, k.high); stop = self._hp - self.cfg.atr_stop * ca
            if death or k.close < stop or regime == "bear":
                self._side = ""
                reason = "死叉" if death else ("ATR止损" if k.close < stop else "转熊")
                return Signal(symbol=self.cfg.symbol, side="SELL", reason=reason, timestamp=k.open_time)

        # 空头持仓
        elif self._side == "short":
            self._lp = min(self._lp, k.low); stop = self._lp + self.cfg.atr_stop * ca
            if golden or k.close > stop or regime == "bull":
                self._side = ""
                reason = "金叉" if golden else ("ATR止损" if k.close > stop else "转牛")
                return Signal(symbol=self.cfg.symbol, side="BUY", reason=reason, timestamp=k.open_time)

        # 空仓等信号
        else:
            if regime == "bull" and golden:
                self._side = "long"; self._hp = k.close
                return Signal(symbol=self.cfg.symbol, side="BUY", reason=f"牛市金叉", timestamp=k.open_time)
            elif regime == "bear" and death:
                self._side = "short"; self._lp = k.close
                return Signal(symbol=self.cfg.symbol, side="SELL", reason=f"熊市死叉", timestamp=k.open_time)

        return None


# ════════════════════════════════════════════════════════

SYMBOLS = ["BTCUSDT", "ETHUSDT", "BNBUSDT", "SOLUSDT"]

PARAMS = {
    "BTCUSDT": (10, 50),
    "ETHUSDT": (10, 75),
    "BNBUSDT": (20, 50),
    "SOLUSDT": (30, 50),
}

DATE_START = datetime(2017, 1, 1)
DATE_END = datetime(2026, 1, 1)


async def get_actual_range(symbol: str) -> tuple[datetime, datetime]:
    """获取币种实际数据范围"""
    ds = DataService(config.db)
    await ds.connect()
    try:
        start, end = await ds.fetch_symbol_date_range(symbol, "4h")
        return start, end
    except:
        return DATE_START, DATE_END
    finally:
        await ds.close()


async def main():
    print()
    print("═" * 125)
    print("  牛熊自适应策略 — 全币种全周期 | 牛市只多/熊市只空/震荡空仓")
    print("═" * 125)

    print(f"\n  ■ 全周期汇总")
    print(f"  {'币种':<10} {'数据范围':<22} {'总收益%':>7} {'年化%':>7} {'夏普':>6} {'回撤%':>7} {'交易':>5} {'多头P&L':>10} {'空头P&L':>10}")
    print("  " + "─" * 115)

    for symbol in SYMBOLS:
        fast, slow = PARAMS[symbol]
        sc = RegimeEmaConfig(symbol=symbol, fast=fast, slow=slow)

        # 获取实际数据范围
        try:
            act_start, act_end = await get_actual_range(symbol)
            range_str = f"{act_start.date()}~{act_end.date()}"
        except:
            act_start, act_end = DATE_START, DATE_END
            range_str = "2017-2026"

        bt = BacktestConfig(symbol=symbol, interval="4h",
                            start_time=act_start, end_time=act_end, initial_capital=10_000.0)
        engine = LongShortEngine(bt, db_config=config.db)
        r = await engine.run(RegimeEmaStrategy, sc)
        m = r.metrics

        long_t = [t for t in r.trades if t.pnl is not None and t.side == "SELL"]
        short_t = [t for t in r.trades if t.pnl is not None and t.side == "BUY"]
        long_pnl = sum(t.pnl for t in long_t) if long_t else 0
        short_pnl = sum(t.pnl for t in short_t) if short_t else 0

        print(f"  {symbol:<10} {range_str:<22} {m.total_return_pct:>6.1f}% {m.annual_return_pct:>6.1f}% {m.sharpe_ratio:>6.2f} {m.max_drawdown_pct:>6.1f}% {m.total_trades:>5} {long_pnl:>+9.0f} {short_pnl:>+9.0f}")

    # ── BTC 分段 ──
    PERIODS = [
        ("2017 牛市",   datetime(2017,1,1), datetime(2018,1,1)),
        ("2018 熊市",   datetime(2018,1,1), datetime(2019,1,1)),
        ("2019 反弹",   datetime(2019,1,1), datetime(2020,1,1)),
        ("2020 牛初",   datetime(2020,1,1), datetime(2021,1,1)),
        ("2021 牛市",   datetime(2021,1,1), datetime(2022,1,1)),
        ("2022 熊市",   datetime(2022,1,1), datetime(2023,1,1)),
        ("2023 震荡",   datetime(2023,1,1), datetime(2024,1,1)),
        ("2024-25牛",   datetime(2024,1,1), datetime(2026,1,1)),
    ]
    print(f"\n  ■ BTC 分段表现")
    print(f"  {'阶段':<16} {'总收益%':>7} {'夏普':>6} {'多头P&L':>9} {'空头P&L':>9}")
    print("  " + "─" * 65)
    for name, s, e in PERIODS:
        try:
            sc = RegimeEmaConfig(symbol="BTCUSDT", fast=10, slow=50)
            bt = BacktestConfig(symbol="BTCUSDT", interval="4h", start_time=s, end_time=e, initial_capital=10_000.0)
            eng = LongShortEngine(bt, db_config=config.db)
            r = await eng.run(RegimeEmaStrategy, sc)
            lt = [t for t in r.trades if t.pnl is not None and t.side == "SELL"]
            st = [t for t in r.trades if t.pnl is not None and t.side == "BUY"]
            print(f"  {name:<16} {r.metrics.total_return_pct:>+6.1f}% {r.metrics.sharpe_ratio:>6.2f} {sum(t.pnl for t in lt) if lt else 0:>+8.0f} {sum(t.pnl for t in st) if st else 0:>+8.0f}")
        except Exception as ex:
            print(f"  {name:<16} 数据不足")

    print("\n═" * 125)


if __name__ == "__main__":
    asyncio.run(main())