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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4h EMA50>EMA200 定大势 / 30m 找买点
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策略：
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4h EMA50 > EMA200 → 中长期多头趋势确认，允许做多
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30m 入场 → 4h多头区间中，30m价格上穿EMA20 + 收阳 → 买入
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30m 出场 → 下穿EMA20 或 4h趋势打破(EMA50<EMA200) 或 ATR止损
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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 BacktestEngine, BacktestConfig
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from engine.data import DataService
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from engine.indicators import ema, atr
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class EMA200FilterConfig(StrategyConfig):
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ema30_fast: int = 10 # 30m 快线
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ema30_slow: int = 50 # 30m 慢线
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atr_stop: float = 3.0
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data_start: Optional[datetime] = None
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data_end: Optional[datetime] = None
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class EMA200FilterStrategy(BaseStrategy):
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"""4h EMA50>200 多头趋势 + 30m 双EMA金叉
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30m 用双EMA交叉替代价格穿越，大幅减少假信号。
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"""
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strategy_type = "ema200_filter"
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def __init__(self, c: EMA200FilterConfig):
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super().__init__(c)
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self.cfg = c
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self._klines_4h: list[Kline] = []
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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_start(self):
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from engine.common.config import config as app_config
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ds = DataService(app_config.db)
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await ds.connect()
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try:
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self._klines_4h = await ds.fetch_klines(
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symbol=self.cfg.symbol, interval="4h",
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start_time=datetime(2023, 1, 1),
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end_time=self.cfg.data_end,
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limit=1_000_000,
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)
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finally:
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await ds.close()
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await super().on_start()
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def _is_4h_bull(self, ts: float) -> bool:
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if len(self._klines_4h) < 201:
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return False
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if not hasattr(self, '_ema50_4h'):
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closes = [k.close for k in self._klines_4h]
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self._ema50_4h = ema(closes, 50)
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self._ema200_4h = ema(closes, 200)
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for i in range(len(self._klines_4h) - 1, -1, -1):
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if self._klines_4h[i].close_time <= ts:
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e50 = self._ema50_4h[i]
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e200 = self._ema200_4h[i]
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return e50 > 0 and e200 > 0 and e50 > e200
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return 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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need = self.cfg.ema30_slow + 10
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if n < need:
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return None
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# 30m 双EMA（金叉/死叉）
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fast = ema(self._closes, self.cfg.ema30_fast)
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slow = ema(self._closes, self.cfg.ema30_slow)
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atr_vals = atr(self._highs, self._lows, self._closes, 14)
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cur_f, cur_s = fast[-1], slow[-1]
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prev_f, prev_s = fast[-2], slow[-2]
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cur_atr = atr_vals[-1]
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if cur_f == 0 or cur_s == 0 or cur_atr == 0:
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return None
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is_bull = self._is_4h_bull(k.open_time)
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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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death = prev_f >= prev_s and cur_f < cur_s
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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="4h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",
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reason=f"30m EMA死叉", timestamp=k.open_time)
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# ── 入场 ──
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if not self._in_position and is_bull:
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golden = prev_f <= prev_s and cur_f > cur_s
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if golden and k.close > k.open:
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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"4h多头+30m金叉", 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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async def main():
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print()
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print("═" * 105)
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print(" 4h EMA50>EMA200 定大势 / 30m 双EMA金叉 | 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} {'持有%':>6}")
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print("─" * 105)
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for symbol in SYMBOLS:
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sc = EMA200FilterConfig(symbol=symbol, data_start=DATE_START, data_end=DATE_END)
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bt = BacktestConfig(symbol=symbol, interval="30m",
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start_time=DATE_START, end_time=DATE_END, initial_capital=10_000.0,
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warmup_bars=50)
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engine = BacktestEngine(bt, db_config=config.db)
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r = await engine.run(EMA200FilterStrategy, sc)
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m = r.metrics
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# 持仓时间占比
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if r.equity_curve:
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bars_with_position = sum(1 for e in r.equity_curve if e.get("position", 0) > 0)
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position_pct = bars_with_position / len(r.equity_curve) * 100
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else:
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position_pct = 0
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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} {position_pct:>5.0f}%")
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# 最近平仓
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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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if sells:
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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} USDT {t.reason}")
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print("─" * 105)
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# 对比之前最优
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print("\n ■ 对比：之前最优策略")
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BEST = {
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"BTCUSDT": ("EMA v3(10,50) 4h", 39.9, 1.03, -11.5, 20),
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"ETHUSDT": ("EMA v3(10,75) 4h", 53.6, 1.04, -15.3, 18),
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"BNBUSDT": ("EMA v1(20,50) 4h", 52.0, 0.71, -39.8, 41),
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"SOLUSDT": ("EMA v3(30,50) 4h", 73.6, 1.18, -25.7, 13),
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}
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print(f" {'币种':<10} {'策略':<22} {'收益%':>7} {'夏普':>6} {'回撤%':>7} {'交易':>5}")
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for symbol in SYMBOLS:
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name, ret, sh, dd, tr = BEST[symbol]
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print(f" {symbol:<10} {name:<22} {ret:>6.1f}% {sh:>6.2f} {dd:>6.1f}% {tr:>5}")
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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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