feat(engine): 添加策略示例集（18 个 Demo）
- backtest_demo.py: 回测基础演示 - strategy_simple.py / three_ema.py / long_short.py: 基础策略（双均线/三均线/多空） - strategy_optimize*.py (3 版本): 参数优化示例（网格搜索/贝叶斯/遗传算法） - multi_tf_*.py (4 版本): 多时间框架策略（EMA200/多周期共振/混合信号） - regime_*.py (4 版本): 市场状态检测（趋势/震荡/波动率区间/全状态） - cross_section.py: 截面多品种策略 - factor_demo.py: 多因子模型演示 - strategy_battle.py / strategy_more.py: 策略对比与组合 - full_cycle.py: 全流程演示（数据→回测→分析） - data.py: 数据读取示例
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"""
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同周期三EMA策略 — 4h EMA50>200 定方向 + EMA20金叉EMA50入场
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所有信号在同一周期(4h)上，不跨级。
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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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_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 BacktestEngine, BacktestConfig
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from engine.indicators import ema, atr
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class ThreeEMAConfig(StrategyConfig):
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ema_entry: int = 20 # 入场均线（金叉慢线时入场）
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ema_trend: int = 50 # 趋势均线（在200上方=多头）
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ema_filter: int = 200 # 长期过滤（50必须在其上）
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atr_stop: float = 2.5
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class ThreeEMAStrategy(BaseStrategy):
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"""三EMA同周期策略
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EMA200 长期方向 → EMA50>200 才做多
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EMA20 金叉 EMA50 → 入场
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EMA20 死叉 EMA50 或 EMA50<200 → 出场
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ATR 动态止损
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"""
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strategy_type = "three_ema"
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def __init__(self, c: ThreeEMAConfig):
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super().__init__(c)
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self.cfg = c
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self._closes: list[float] = []
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self._highs: list[float] = []
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self._lows: list[float] = []
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self._highest: float = 0.0
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self._in_position = False
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async def on_kline(self, k: Kline) -> Optional[Signal]:
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self._closes.append(k.close)
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self._highs.append(k.high)
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self._lows.append(k.low)
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n = len(self._closes)
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if n < self.cfg.ema_filter + 10:
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return None
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# 三条EMA
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e20 = ema(self._closes, self.cfg.ema_entry)
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e50 = ema(self._closes, self.cfg.ema_trend)
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e200 = ema(self._closes, self.cfg.ema_filter)
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atr_vals = atr(self._highs, self._lows, self._closes, 14)
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# 当前值和前值
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c20, p20 = e20[-1], e20[-2]
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c50, p50 = e50[-1], e50[-2]
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c200 = e200[-1]
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cur_atr = atr_vals[-1]
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if c20 == 0 or c50 == 0 or c200 == 0 or cur_atr == 0:
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return None
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is_bull = c50 > c200 # EMA50在200上方=多头市场
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golden = p20 <= p50 and c20 > p50 # 金叉
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death = p20 >= p50 and c20 < p50 # 死叉
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# ── 出场 ──
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if self._in_position:
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self._highest = max(self._highest, k.high)
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stop = self._highest - self.cfg.atr_stop * cur_atr
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if not is_bull:
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self._in_position = False
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return Signal(symbol=self.cfg.symbol, side="SELL", reason="EMA50<200转空", timestamp=k.open_time)
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if k.close < stop:
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self._in_position = False
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return Signal(symbol=self.cfg.symbol, side="SELL", reason="ATR止损", timestamp=k.open_time)
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if death:
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self._in_position = False
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return Signal(symbol=self.cfg.symbol, side="SELL", reason="EMA20死叉50", timestamp=k.open_time)
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# ── 入场 ──
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if not self._in_position and is_bull and golden:
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self._in_position = True
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self._highest = k.close
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return Signal(symbol=self.cfg.symbol, side="BUY",
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reason=f"EMA20金叉50 多头确认", timestamp=k.open_time)
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return None
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# ═══════════════════════════════════════════════
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SYMBOLS = ["BTCUSDT", "ETHUSDT", "BNBUSDT", "SOLUSDT"]
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DATE_START = datetime(2024, 1, 1)
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DATE_END = datetime(2026, 1, 1)
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# 之前最优对比
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BEST = {
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"BTCUSDT": ("EMA v3(10,50)", 39.9, 1.03, -11.5, 20),
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"ETHUSDT": ("EMA v3(10,75)", 53.6, 1.04, -15.3, 18),
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"BNBUSDT": ("EMA v1(20,50)", 52.0, 0.71, -39.8, 41),
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"SOLUSDT": ("EMA v3(30,50)", 73.6, 1.18, -25.7, 13),
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}
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async def main():
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print()
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print("═" * 105)
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print(" 三EMA同周期 — 4h EMA200定势 / EMA20×50交易 | 2024-2026")
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print("═" * 105)
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print(f" {'币种':<10} {'收益%':>7} {'夏普':>6} {'回撤%':>7} {'交易':>5} {'胜率%':>6} {'盈亏比':>6} {'vs最优':>8}")
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print("─" * 105)
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results = {}
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for symbol in SYMBOLS:
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sc = ThreeEMAConfig(symbol=symbol)
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bt = BacktestConfig(symbol=symbol, interval="4h",
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start_time=DATE_START, end_time=DATE_END, initial_capital=10_000.0)
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engine = BacktestEngine(bt, db_config=config.db)
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r = await engine.run(ThreeEMAStrategy, sc)
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m = r.metrics
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results[symbol] = m
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_, best_ret, best_sh, _, _ = BEST[symbol]
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delta = m.total_return_pct - best_ret
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tag = " ← 新最佳!" if m.sharpe_ratio > best_sh else ""
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print(f" {symbol:<10} {m.total_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} {delta:>+7.1f}%{tag}")
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sells = [t for t in r.trades if t.side == "SELL" and t.pnl is not None]
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for t in sells[-2:]:
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dt = datetime.fromtimestamp(t.timestamp / 1000, tz=timezone.utc).strftime("%m-%d %H:%M")
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print(f" {'':<10} └ {dt} {t.pnl:>+8.2f} {t.reason}")
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print("─" * 105)
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print(f"\n {'币种':<10} {'之前最优':<20} {'收益%':>7} {'夏普':>6} → {'三EMA收益%':>9} {'三EMA夏普':>8}")
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for symbol in SYMBOLS:
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name, ret, sh, _, _ = BEST[symbol]
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m = results[symbol]
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print(f" {symbol:<10} {name:<20} {ret:>6.1f}% {sh:>6.2f} → {m.total_return_pct:>8.1f}% {m.sharpe_ratio:>7.2f}")
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print("\n═" * 105)
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if __name__ == "__main__":
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asyncio.run(main())
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