feat: 多周期牛熊判定模块 — 方案一矩阵展示 + 四法投票 + 多TF策略
- engine/indicators/regime.py: RegimeDetector(四法投票) + MultiTimeframeRegime(多周期并行) 四法: EMA200斜率 / 价格vsEMA200 / ATH回撤 / 窄幅盘整(<3%振幅) 全部 O(1)/bar 增量计算,适用于回测和实时 - engine/example/regime_display.py: 多周期牛熊矩阵展示脚本 独立加载各周期数据 → 运行判定 → 日线对齐矩阵 + 详细拆解 + 统计 输出 engine/backtest/REGIME_MATRIX_BTCUSDT.md - engine/example/regime_mtf_strategy.py: 多周期共识策略 + 四策略对比回测 MTF Consensus: 1w定方向 + 1d确认 + 4h EMA入场 vs Old Regime(单TF基线) vs Long/Short(无过滤) - engine/indicators/__init__.py: 导出 RegimeDetector, MultiTimeframeRegime
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"""
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多周期牛熊共识策略 — 四周期协同判定
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核心思路：
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1w 定宏观方向（只做多 / 只做空）→ 1d 确认中周期 → 4h EMA 金叉/死叉入场
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配合 ATR 动态止损 + 多周期投票确认出场
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对比基准：单周期 RegimeEmaStrategy（regime_all.py）、无过滤 LongShortEmaStrategy
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用法：
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source .venv/bin/activate && python example/regime_mtf_strategy.py
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"""
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import asyncio
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import sys
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from datetime import datetime, timezone
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from pathlib import Path
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from typing import Optional
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_project_root = Path(__file__).resolve().parent.parent.parent
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if str(_project_root) not in sys.path:
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sys.path.insert(0, str(_project_root))
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from engine.common.base import BaseStrategy, Signal, StrategyConfig
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from engine.common.models import Kline
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from engine.common.config import config
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from engine.backtest import BacktestConfig
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from engine.indicators.incremental import EmaInc, AtrInc
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from engine.indicators.regime import MultiTimeframeRegime
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from engine.example.long_short import LongShortEngine
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from engine.example.regime_all import RegimeEmaConfig as OldRegimeCfg
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from engine.example.regime_all import RegimeEmaStrategy as OldRegimeS
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from engine.example.long_short import LongShortEmaConfig as LSCfg
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from engine.example.long_short import LongShortEmaStrategy as LSS
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# ════════════════════════════════════════════════════════
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# 多周期牛熊共识策略
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# ════════════════════════════════════════════════════════
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class MTFConfig(StrategyConfig):
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fast: int = 10
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slow: int = 50
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atr_stop: float = 2.5
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class MTFRegimeStrategy(BaseStrategy):
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"""四周期协同牛熊策略
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判定层（MultiTimeframeRegime，即时法）：
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每个 4h bar 的 close 同时更新 1h / 4h / 1d / 1w 四个检测器，
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1w 定方向宏调，1d 确认中周期，1h 预警微观背离。
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入场：
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做多 — 1w bull + 1d not bear + 4h EMA 金叉
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做空 — 1w bear + 1d not bull + 4h EMA 死叉
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出场：
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EMA 交叉反转、ATR 跟踪止损、高周期方向逆转
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"""
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strategy_type = "mtf_regime"
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def __init__(self, c: MTFConfig):
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super().__init__(c)
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self.cfg = c
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self._mtf = MultiTimeframeRegime(["1h", "4h", "1d", "1w"])
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self._ema_fast = EmaInc(c.fast)
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self._ema_slow = EmaInc(c.slow)
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self._atr = AtrInc(14)
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self._side: str = ""
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self._hp: float = 0.0
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self._lp: float = float("inf")
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async def on_kline(self, k: Kline) -> Optional[Signal]:
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self._mtf.update(k.close)
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self._ema_fast.update(k.close)
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self._ema_slow.update(k.close)
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self._atr.update(k.high, k.low, k.close)
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n = len(self._mtf._prices)
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if n < 220:
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return None
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regimes = self._mtf.detect_all()
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r1h = regimes.get("1h", "unknown")
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r4h = regimes.get("4h", "unknown")
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r1d = regimes.get("1d", "unknown")
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r1w = regimes.get("1w", "unknown")
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cf, cs = self._ema_fast[-1], self._ema_slow[-1]
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ca = self._atr[-1]
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pf, ps = self._ema_fast[-2], self._ema_slow[-2]
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if cf == 0 or cs == 0 or ca == 0:
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return None
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golden = pf <= ps and cf > cs
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death = pf >= ps and cf < cs
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# ── 多头持仓 ──
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if self._side == "long":
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self._hp = max(self._hp, k.high)
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stop = self._hp - self.cfg.atr_stop * ca
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exit_reason = None
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if death:
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exit_reason = "死叉"
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elif k.close < stop:
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exit_reason = "ATR止损"
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elif r1w == "bear":
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exit_reason = "1w转熊→平多"
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elif r1d == "bear" and r4h == "bear":
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exit_reason = "1d+4h双双转熊→平多"
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if exit_reason:
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self._side = ""
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return Signal(symbol=self.cfg.symbol, side="SELL",
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reason=exit_reason, timestamp=k.open_time)
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# ── 空头持仓 ──
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elif self._side == "short":
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self._lp = min(self._lp, k.low)
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stop = self._lp + self.cfg.atr_stop * ca
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exit_reason = None
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if golden:
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exit_reason = "金叉"
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elif k.close > stop:
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exit_reason = "ATR止损"
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elif r1w == "bull":
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exit_reason = "1w转牛→平空"
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elif r1d == "bull" and r4h == "bull":
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exit_reason = "1d+4h双双转牛→平空"
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if exit_reason:
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self._side = ""
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return Signal(symbol=self.cfg.symbol, side="BUY",
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reason=exit_reason, timestamp=k.open_time)
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# ── 空仓等信号 ──
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else:
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# 做多条件：1w牛 + 1d不熊 + 4h金叉
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long_ok = r1w == "bull" and r1d != "bear" and golden
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# 做空条件：1w熊 + 1d不牛 + 4h死叉
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short_ok = r1w == "bear" and r1d != "bull" and death
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if long_ok:
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self._side = "long"
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self._hp = k.close
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return Signal(symbol=self.cfg.symbol, side="BUY",
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reason=f"多周期做多({r1w}/{r1d}/{r4h})",
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timestamp=k.open_time)
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if short_ok:
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self._side = "short"
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self._lp = k.close
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return Signal(symbol=self.cfg.symbol, side="SELL",
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reason=f"多周期做空({r1w}/{r1d}/{r4h})",
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timestamp=k.open_time)
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return None
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# ════════════════════════════════════════════════════════
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# 对照策略 2：1w 绝对过滤（更强约束）
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# ════════════════════════════════════════════════════════
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class MTFStrictConfig(StrategyConfig):
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fast: int = 10
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slow: int = 50
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atr_stop: float = 2.5
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class MTFStrictStrategy(BaseStrategy):
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"""严格多周期策略 — 必须 1w + 1d 方向一致才入场
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入场：
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做多 — 1w bull + 1d bull + 4h 金叉
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做空 — 1w bear + 1d bear + 4h 死叉
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出场：
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4h 死叉/金叉 或 ATR 止损 或 1w 方向逆转
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"""
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strategy_type = "mtf_strict"
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def __init__(self, c: MTFStrictConfig):
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super().__init__(c)
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self.cfg = c
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self._mtf = MultiTimeframeRegime(["1h", "4h", "1d", "1w"])
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self._ema_fast = EmaInc(c.fast)
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self._ema_slow = EmaInc(c.slow)
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self._atr = AtrInc(14)
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self._side: str = ""
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self._hp: float = 0.0
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self._lp: float = float("inf")
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async def on_kline(self, k: Kline) -> Optional[Signal]:
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self._mtf.update(k.close)
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self._ema_fast.update(k.close)
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self._ema_slow.update(k.close)
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self._atr.update(k.high, k.low, k.close)
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n = len(self._mtf._prices)
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if n < 220:
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return None
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regimes = self._mtf.detect_all()
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r4h = regimes.get("4h", "unknown")
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r1d = regimes.get("1d", "unknown")
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r1w = regimes.get("1w", "unknown")
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cf, cs = self._ema_fast[-1], self._ema_slow[-1]
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ca = self._atr[-1]
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pf, ps = self._ema_fast[-2], self._ema_slow[-2]
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if cf == 0 or cs == 0 or ca == 0:
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return None
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golden = pf <= ps and cf > cs
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death = pf >= ps and cf < cs
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# 多头持仓
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if self._side == "long":
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self._hp = max(self._hp, k.high)
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stop = self._hp - self.cfg.atr_stop * ca
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if death or k.close < stop or r1w == "bear":
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self._side = ""
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reason = "死叉" if death else ("ATR止损" if k.close < stop else "1w转熊")
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return Signal(symbol=self.cfg.symbol, side="SELL",
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reason=reason, timestamp=k.open_time)
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# 空头持仓
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elif self._side == "short":
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self._lp = min(self._lp, k.low)
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stop = self._lp + self.cfg.atr_stop * ca
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if golden or k.close > stop or r1w == "bull":
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self._side = ""
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reason = "金叉" if golden else ("ATR止损" if k.close > stop else "1w转牛")
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return Signal(symbol=self.cfg.symbol, side="BUY",
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reason=reason, timestamp=k.open_time)
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# 空仓
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else:
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if r1w == "bull" and r1d == "bull" and golden:
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self._side = "long"
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self._hp = k.close
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return Signal(symbol=self.cfg.symbol, side="BUY",
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reason=f"严格做多({r1w}+{r1d}+{r4h})",
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timestamp=k.open_time)
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if r1w == "bear" and r1d == "bear" and death:
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self._side = "short"
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self._lp = k.close
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return Signal(symbol=self.cfg.symbol, side="SELL",
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reason=f"严格做空({r1w}+{r1d}+{r4h})",
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timestamp=k.open_time)
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return None
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# ════════════════════════════════════════════════════════
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# 回测入口
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# ════════════════════════════════════════════════════════
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SYMBOLS = ["BTCUSDT", "ETHUSDT", "BNBUSDT", "SOLUSDT"]
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PARAMS = {
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"BTCUSDT": (10, 50),
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"ETHUSDT": (10, 75),
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"BNBUSDT": (20, 50),
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"SOLUSDT": (30, 50),
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}
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DATE_START = datetime(2024, 1, 1)
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DATE_END = datetime(2026, 1, 1)
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async def run_one(engine, strategy_cls, config_cls, symbol, desc, params=None):
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fast, slow = PARAMS[symbol] if params is None else params
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sc = config_cls(symbol=symbol, fast=fast, slow=slow)
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bt = BacktestConfig(
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symbol=symbol, interval="4h",
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start_time=DATE_START, end_time=DATE_END,
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initial_capital=10_000.0, warmup_bars=250,
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)
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eng = engine(bt, db_config=config.db)
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r = await eng.run(strategy_cls, sc)
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return r
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async def main():
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print()
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print("═" * 120)
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print(" 多周期牛熊共识策略 — MTF Regime × 4h EMA | 2024-2026")
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print("═" * 120)
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print()
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print(" 对比策略:")
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print(" • MTF Consensus — 1w定方向 + 1d确认 + 4h金叉/死叉入场（新）")
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print(" • MTF Strict — 1w+1d必须同向才入场（新）")
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print(" • Old Regime — 单周期(4h)三法投票（regime_all.py 基线）")
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print(" • Long/Short — 无牛熊过滤，始终多空（long_short.py 基线）")
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print()
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for symbol in SYMBOLS:
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print(f" ── {symbol} ──")
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print(f" {'策略':<18} {'总收益%':>7} {'年化%':>7} {'夏普':>6} {'回撤%':>7} {'交易':>5} {'胜率%':>6} {'盈亏比':>6} {'多头P&L':>9} {'空头P&L':>9}")
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print(" " + "─" * 110)
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results = {}
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# 1. MTF Consensus (new)
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try:
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r1 = await run_one(LongShortEngine, MTFRegimeStrategy, MTFConfig, symbol, "MTF Consensus")
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m = r1.metrics
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long1 = [t for t in r1.trades if t.pnl is not None and t.side == "SELL"]
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short1 = [t for t in r1.trades if t.pnl is not None and t.side == "BUY"]
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lp1 = sum(t.pnl for t in long1) if long1 else 0
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sp1 = sum(t.pnl for t in short1) if short1 else 0
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results["mtf"] = m
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print(f" {'MTF Consensus':<18} {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} {m.win_rate*100:>5.1f}% {m.profit_factor:>6.2f} {lp1:>+9.0f} {sp1:>+9.0f}")
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except Exception as e:
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print(f" {'MTF Consensus':<18} 错误: {e}")
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# 2. MTF Strict (new)
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try:
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r2 = await run_one(LongShortEngine, MTFStrictStrategy, MTFStrictConfig, symbol, "MTF Strict")
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m = r2.metrics
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long2 = [t for t in r2.trades if t.pnl is not None and t.side == "SELL"]
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short2 = [t for t in r2.trades if t.pnl is not None and t.side == "BUY"]
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lp2 = sum(t.pnl for t in long2) if long2 else 0
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sp2 = sum(t.pnl for t in short2) if short2 else 0
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results["strict"] = m
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print(f" {'MTF Strict':<18} {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} {m.win_rate*100:>5.1f}% {m.profit_factor:>6.2f} {lp2:>+9.0f} {sp2:>+9.0f}")
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except Exception as e:
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print(f" {'MTF Strict':<18} 错误: {e}")
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# 3. Old Regime (baseline)
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try:
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r3 = await run_one(LongShortEngine, OldRegimeS, OldRegimeCfg, symbol, "Old Regime")
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m = r3.metrics
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long3 = [t for t in r3.trades if t.pnl is not None and t.side == "SELL"]
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short3 = [t for t in r3.trades if t.pnl is not None and t.side == "BUY"]
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lp3 = sum(t.pnl for t in long3) if long3 else 0
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sp3 = sum(t.pnl for t in short3) if short3 else 0
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results["old"] = m
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print(f" {'Old Regime':<18} {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} {m.win_rate*100:>5.1f}% {m.profit_factor:>6.2f} {lp3:>+9.0f} {sp3:>+9.0f}")
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except Exception as e:
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print(f" {'Old Regime':<18} 错误: {e}")
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# 4. Long/Short (baseline, no filter)
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try:
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r4 = await run_one(LongShortEngine, LSS, LSCfg, symbol, "Long/Short")
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m = r4.metrics
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long4 = [t for t in r4.trades if t.pnl is not None and t.side == "SELL"]
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short4 = [t for t in r4.trades if t.pnl is not None and t.side == "BUY"]
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lp4 = sum(t.pnl for t in long4) if long4 else 0
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sp4 = sum(t.pnl for t in short4) if short4 else 0
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results["ls"] = m
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print(f" {'Long/Short':<18} {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} {m.win_rate*100:>5.1f}% {m.profit_factor:>6.2f} {lp4:>+9.0f} {sp4:>+9.0f}")
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except Exception as e:
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print(f" {'Long/Short':<18} 错误: {e}")
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# 简要对比
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if len(results) >= 2:
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best_sharpe = max(results.items(), key=lambda x: x[1].sharpe_ratio)
|
||||
worst_dd = min(results.items(), key=lambda x: x[1].max_drawdown_pct)
|
||||
print(f" └ 最佳夏普: {best_sharpe[0]} ({best_sharpe[1].sharpe_ratio:.2f}) | "
|
||||
f"最小回撤: {worst_dd[0]} ({worst_dd[1].max_drawdown_pct:.1f}%)")
|
||||
|
||||
print()
|
||||
|
||||
print("═" * 120)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
Reference in New Issue
Block a user