feat: 新增2h/6h时间框架支持，策略重构为增量指标计算

- 数据层: build_aggregates_sql 新增 2h/6h 聚合视图，默认起始时间调整为 2017-05 - 模型层: KlineInterval 类型扩展 2h/6h，DataService 新增对应表名和毫秒映射 - 指标层: 新增 incremental.py 增量指标模块 (EmaInc/AtrInc/RsiInc/BbInc)，O(1) per bar - 策略重构: long_short.py 和 regime_all.py 从批量 ema/atr 迁移至增量指标，避免每 bar 重复全量计算 - regime 探测器: RegimeDetector3 改为增量 EMA200，detect() 接口简化 - 回测扩展: regime_timeframe_comparison 从 4h/1d 扩展至 2h/4h/6h/1d - 新增示例: multi_strategy_report, vol_break_compare/periods, intraday_explore, top3_trades 等分析脚本
2026-06-13 19:30:25 +08:00
parent b5cdb41993
commit edc50e8809
20 changed files with 484544 additions and 34 deletions
@@ -0,0 +1,122 @@
+"""
+牛熊自适应策略 — 日内级别全币种扫描 (15m / 30m / 1h)
+
+用法：
+    source .venv/bin/activate && python example/regime_intraday.py
+"""
+
+import asyncio
+import sys
+import time
+from datetime import datetime, timezone
+from pathlib import Path
+
+_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.config import config
+from engine.backtest import BacktestConfig
+from engine.data import DataService
+from engine.example.regime_all import RegimeEmaStrategy, RegimeEmaConfig
+from engine.example.long_short import LongShortEngine
+
+SYMBOLS = ["BTCUSDT", "ETHUSDT", "BNBUSDT", "SOLUSDT"]
+INTERVALS = ["15m", "30m", "1h"]
+
+# 沿用 4h 级别优化参数（日内级别可能需单独调参）
+PARAMS = {
+    "BTCUSDT": (10, 50),
+    "ETHUSDT": (10, 75),
+    "BNBUSDT": (20, 50),
+    "SOLUSDT": (30, 50),
+}
+
+
+async def get_actual_range(ds: DataService, symbol: str, interval: str):
+    """获取币种指定周期的实际数据范围"""
+    start, end = await ds.fetch_symbol_date_range(symbol, interval)
+    return start, end
+
+
+async def main():
+    ds = DataService(config.db)
+    await ds.connect()
+
+    print()
+    print("═" * 130)
+    print("  牛熊自适应策略 — 日内级别全币种扫描 | 牛市只多/熊市只空/震荡空仓")
+    print("═" * 130)
+
+    total_start = time.time()
+    results: list[dict] = []
+
+    for interval in INTERVALS:
+        print(f"\n  ■ {interval} 级别")
+        print(f"  {'币种':<10} {'数据范围':<22} {'总收益%':>8} {'年化%':>8} {'夏普':>7} {'回撤%':>8} {'交易':>6} {'多头P&L':>11} {'空头P&L':>11} {'耗时s':>7}")
+        print("  " + "─" * 125)
+
+        for symbol in SYMBOLS:
+            fast, slow = PARAMS[symbol]
+            sc = RegimeEmaConfig(symbol=symbol, fast=fast, slow=slow)
+
+            try:
+                act_start, act_end = await get_actual_range(ds, symbol, interval)
+                range_str = f"{act_start.date()}~{act_end.date()}"
+            except Exception:
+                # 数据不存在，跳过
+                print(f"  {symbol:<10} {'无数据':<22}")
+                continue
+
+            bt = BacktestConfig(
+                symbol=symbol, interval=interval,
+                start_time=act_start, end_time=act_end,
+                initial_capital=10_000.0,
+            )
+            engine = LongShortEngine(bt, db_config=config.db)
+
+            t0 = time.time()
+            try:
+                r = await engine.run(RegimeEmaStrategy, sc)
+                elapsed = time.time() - t0
+            except Exception as ex:
+                print(f"  {symbol:<10} {range_str:<22} {'错误: ' + str(ex)[:30]}")
+                continue
+
+            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:>7.1f}% {m.annual_return_pct:>7.1f}% {m.sharpe_ratio:>7.2f} {m.max_drawdown_pct:>7.1f}% {m.total_trades:>6} {long_pnl:>+10.0f} {short_pnl:>+10.0f} {elapsed:>6.1f}s")
+
+            results.append({
+                "interval": interval, "symbol": symbol,
+                "return": m.total_return_pct, "annual": m.annual_return_pct,
+                "sharpe": m.sharpe_ratio, "dd": m.max_drawdown_pct,
+                "trades": m.total_trades, "win_rate": m.win_rate,
+                "profit_factor": m.profit_factor,
+                "long_pnl": long_pnl, "short_pnl": short_pnl,
+                "elapsed": elapsed,
+            })
+
+    await ds.close()
+
+    # ── 汇总排名 ──
+    total_elapsed = time.time() - total_start
+    print(f"\n  ■ 最佳组合 (按夏普排名)")
+    print(f"  {'排名':<5} {'级别':<6} {'币种':<10} {'总收益%':>8} {'夏普':>7} {'回撤%':>8} {'交易':>6} {'胜率%':>7} {'盈亏比':>7}")
+    print("  " + "─" * 75)
+
+    sorted_results = sorted(results, key=lambda x: x["sharpe"], reverse=True)
+    for i, r in enumerate(sorted_results):
+        medal = ["🥇", "🥈", "🥉"][i] if i < 3 else f"{i+1:>2}."
+        print(f"  {medal:<5} {r['interval']:<6} {r['symbol']:<10} {r['return']:>7.1f}% {r['sharpe']:>7.2f} {r['dd']:>7.1f}% {r['trades']:>6} {r['win_rate']*100:>6.1f}% {r['profit_factor']:>7.2f}")
+
+    print(f"\n  总耗时: {total_elapsed:.1f}s")
+    print("═" * 130)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())