feat(engine): 新增 2h/6h 与 1h 策略对比回测
- comparison_2h_6h: 9 策略 × 4 币种 × 2 周期 × 4 数据量 = 288 次回测
- 包含海龟、超级趋势、MACD、布林收缩、三均线、RSI 回归、
ATR 波动率突破、EMA 多空、牛熊自适应
- 结论：6h 夏普显著优于 2h（69% 组合），ATR 策略霸榜
- 自动生成 Markdown 回测报告
- vol_break_1h_6h: ATR 波动率突破 × 1h/2h/4h/6h 近半年对比
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"""
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ATR波动率突破 — 1h/2h/4h/6h 近半年横向对比回测
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用法：
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source .venv/bin/activate && python example/vol_break_1h_6h.py
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"""
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import asyncio
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import json
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import sys
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import time
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from datetime import datetime, timedelta, 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.models import BacktestConfig
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from engine.data import DataService
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from engine.indicators.incremental import EmaInc, AtrInc, RsiInc, BbInc
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from engine.example.long_short import LongShortEngine
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# ── 全局常量 ──
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SYMBOLS = ["BTCUSDT", "ETHUSDT", "BNBUSDT", "SOLUSDT"]
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TIMEFRAMES = ["1h", "2h", "4h", "6h"]
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INITIAL = 10_000.0
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WARMUP = 150
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MAX_CONCURRENCY = 6
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NOW = datetime.now(timezone.utc)
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PERIOD_START = NOW - timedelta(days=182) # 近半年
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PERIOD_END = NOW
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# ════════════════════════════════════════════════════════
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# ATR波动率突破策略
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# ════════════════════════════════════════════════════════
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class VolBreakConfig(StrategyConfig):
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atr_period: int = 14
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squeeze_period: int = 20
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squeeze_ratio: float = 0.7
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atr_stop: float = 2.0
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class VolBreakStrategy(BaseStrategy):
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strategy_type = "波动率突破"
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strategy_desc = "ATR(14)收缩至极低后扩张突破 + EMA(10/30)方向确认"
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def __init__(self, c: VolBreakConfig):
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super().__init__(c)
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self.cfg = c
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self._atr = AtrInc(c.atr_period)
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self._ema_fast = EmaInc(10)
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self._ema_slow = EmaInc(30)
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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._side: str = ""
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self._entry_price: float = 0.0
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self._was_squeezed = 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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self._atr.update(k.high, k.low, 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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n = len(self._closes)
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if n < self.cfg.atr_period + self.cfg.squeeze_period:
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return None
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atr_now = self._atr[-1]
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atr_prev = self._atr[-2] if n >= 2 else 0
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ca = atr_now
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if ca == 0:
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return None
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atr_window = [self._atr[i] for i in range(max(0, n - self.cfg.squeeze_period), n) if self._atr[i] > 0]
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if not atr_window:
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return None
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min_atr = min(atr_window)
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is_squeezed = atr_now < min_atr * (1 + (1 - self.cfg.squeeze_ratio))
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atr_expanding = atr_now > atr_prev * 1.05 if atr_prev > 0 else False
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cf, cs = self._ema_fast[-1], self._ema_slow[-1]
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trend_up = cf > cs
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if self._side == "long":
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self._was_squeezed = False
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stop = self._entry_price - self.cfg.atr_stop * ca
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if k.close < stop or (cf < cs and not is_squeezed):
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self._side = ""
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return Signal(symbol=self.cfg.symbol, side="SELL", reason="ATR退出", timestamp=k.open_time)
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elif self._side == "short":
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self._was_squeezed = False
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stop = self._entry_price + self.cfg.atr_stop * ca
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if k.close > stop or (cf > cs and not is_squeezed):
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self._side = ""
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return Signal(symbol=self.cfg.symbol, side="BUY", reason="ATR退出", timestamp=k.open_time)
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else:
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if is_squeezed:
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self._was_squeezed = True
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elif self._was_squeezed and atr_expanding:
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self._was_squeezed = False
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if trend_up:
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self._side = "long"; self._entry_price = k.close
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return Signal(symbol=self.cfg.symbol, side="BUY", reason="ATR扩张突破做多", timestamp=k.open_time)
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else:
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self._side = "short"; self._entry_price = k.close
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return Signal(symbol=self.cfg.symbol, side="SELL", reason="ATR扩张突破做空", timestamp=k.open_time)
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return None
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async def run_one(symbol, interval, start, end):
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sc = VolBreakConfig(symbol=symbol)
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bt = BacktestConfig(
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symbol=symbol, interval=interval,
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start_time=start, end_time=end,
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initial_capital=INITIAL, warmup_bars=WARMUP,
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)
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engine = LongShortEngine(bt, db_config=config.db)
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t0 = time.time()
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try:
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r = await engine.run(VolBreakStrategy, sc)
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elapsed = time.time() - t0
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return r, elapsed, None
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except Exception as ex:
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elapsed = time.time() - t0
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return None, elapsed, str(ex)
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async def main():
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ds = DataService(config.db)
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await ds.connect()
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print("正在获取数据范围...")
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date_ranges = {}
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for symbol in SYMBOLS:
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for tf in TIMEFRAMES:
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try:
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s, e = await ds.fetch_symbol_date_range(symbol, tf)
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bar_ms = {"1h": 3_600_000, "2h": 7_200_000, "4h": 14_400_000, "6h": 21_600_000}
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estimated_bars = int((e - s).total_seconds() * 1000 / bar_ms[tf])
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date_ranges[(symbol, tf)] = (s, e, estimated_bars)
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print(f" {symbol} {tf:<4}: {s.date()} ~ {e.date()} (约{estimated_bars:,}根)")
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except Exception as ex:
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print(f" {symbol} {tf:<4}: 获取失败 — {ex}")
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await ds.close()
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sem = asyncio.Semaphore(MAX_CONCURRENCY)
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tasks_info = []
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for symbol in SYMBOLS:
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for tf in TIMEFRAMES:
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key = (symbol, tf)
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if key not in date_ranges:
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continue
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fs, fe, est_bars = date_ranges[key]
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actual_start = max(PERIOD_START, fs)
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actual_end = min(PERIOD_END, fe)
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if actual_start >= actual_end:
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continue
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tasks_info.append({"symbol": symbol, "tf": tf, "start": actual_start, "end": actual_end})
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total = len(tasks_info)
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print(f"\n共 {total} 组回测任务 (ATR波动率突破 × 4币种 × 4时间 × 近半年)")
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results = []
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completed = 0
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errors = 0
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async def run_one_safe(info):
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nonlocal completed, errors
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async with sem:
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r, elapsed, err = await run_one(info["symbol"], info["tf"], info["start"], info["end"])
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completed += 1
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if err:
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errors += 1
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status = f"✗ {err[:40]}"
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elif r is None:
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errors += 1
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status = "✗ 无结果"
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else:
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m = r.metrics
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status = f"✓ {m.annual_return_pct:+.1f}%/yr"
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print(f" [{completed}/{total}] {info['symbol']} {info['tf']} ({elapsed:.1f}s) {status}", flush=True)
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row = {
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"币种": info["symbol"],
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"时间级别": info["tf"],
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"日期范围": f"{info['start'].date()}~{info['end'].date()}",
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}
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if r is not None:
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m = r.metrics
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row.update({
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"初始资金": INITIAL,
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"最终权益": round(m.final_equity, 2),
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"总收益%": round(m.total_return_pct, 2),
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"年化收益%": round(m.annual_return_pct, 2),
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"夏普比率": round(m.sharpe_ratio, 2),
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"最大回撤%": round(m.max_drawdown_pct, 2),
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"胜率%": round(m.win_rate * 100, 2),
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"盈亏比": round(m.profit_factor, 2),
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"交易次数": m.total_trades,
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"平均盈亏": round(m.avg_trade_pnl, 2),
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"最佳盈亏": round(m.best_trade_pnl, 2),
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"最差盈亏": round(m.worst_trade_pnl, 2),
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"耗时s": round(elapsed, 1),
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})
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else:
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row.update({
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"初始资金": INITIAL, "最终权益": 0, "总收益%": 0, "年化收益%": 0,
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"夏普比率": 0, "最大回撤%": 0, "胜率%": 0, "盈亏比": 0,
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"交易次数": 0, "平均盈亏": 0, "最佳盈亏": 0, "最差盈亏": 0,
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"耗时s": round(elapsed, 1), "错误": err or "未知错误",
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})
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results.append(row)
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return row
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t_total = time.time()
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await asyncio.gather(*[run_one_safe(info) for info in tasks_info])
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total_elapsed = time.time() - t_total
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print(f"\n全部完成！成功 {total - errors}/{total}，错误 {errors}，总耗时 {total_elapsed:.0f}s")
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# ── 打印 ──
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print()
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print("═" * 145)
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print(" ATR波动率突破 — 1h / 2h / 4h / 6h 近半年横向对比")
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print(" 策略: ATR(14)/squeeze=20x0.7/EMA(10,30) | 本金 $10,000 | 多空双向")
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print("═" * 145)
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print()
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# 按时间级别排序
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results.sort(key=lambda x: TIMEFRAMES.index(x["时间级别"]))
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print(f" {'币种':<10} {'时间':<5} {'总收益%':>8} {'年化%':>8} {'夏普':>7} {'回撤%':>7} {'胜率%':>7} {'盈亏比':>7} {'交易':>6} {'最佳盈亏':>10} {'最差盈亏':>10} {'日期范围':<24}")
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print(" " + "─" * 140)
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for r in results:
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print(f" {r['币种']:<10} {r['时间级别']:<5} {r['总收益%']:>7.1f}% {r['年化收益%']:>7.1f}% {r['夏普比率']:>7.2f} {r['最大回撤%']:>7.1f}% {r['胜率%']:>6.1f}% {r['盈亏比']:>7.2f} {r['交易次数']:>6} {r['最佳盈亏']:>+9.0f} {r['最差盈亏']:>+9.0f} {r['日期范围']:<24}")
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print()
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# ── 各时间级别汇总 ──
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print("═" * 145)
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print(" ■ 各时间级别排名（按年化收益）")
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print("═" * 145)
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for tf in TIMEFRAMES:
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subset = [r for r in results if r["时间级别"] == tf]
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if not subset:
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continue
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subset.sort(key=lambda x: x.get("年化收益%", -9999), reverse=True)
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print(f"\n ▲ {tf} 近半年")
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print(f" {'排名':<5} {'币种':<10} {'总收益%':>8} {'年化%':>8} {'夏普':>7} {'回撤%':>7} {'胜率%':>7} {'盈亏比':>7} {'交易':>6}")
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print(" " + "─" * 100)
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for i, r in enumerate(subset):
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marker = ["🥇", "🥈", "🥉", " 4"][i]
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print(f" {marker:<5} {r['币种']:<10} {r['总收益%']:>7.1f}% {r['年化收益%']:>7.1f}% {r['夏普比率']:>7.2f} {r['最大回撤%']:>7.1f}% {r['胜率%']:>6.1f}% {r['盈亏比']:>7.2f} {r['交易次数']:>6}")
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print()
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print("═" * 145)
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# ── 保存 JSON ──
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output_file = _project_root / "engine" / "example" / "vol_break_1h_6h.json"
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with open(output_file, "w", encoding="utf-8") as f:
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json.dump({
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"config": {
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"strategy": "ATR波动率突破",
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"symbols": SYMBOLS,
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"timeframes": TIMEFRAMES,
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"period": "近半年",
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"initial_capital": INITIAL,
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"warmup_bars": WARMUP,
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"elapsed_seconds": total_elapsed,
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"run_time": datetime.now(timezone.utc).isoformat(),
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},
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"results": results,
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}, f, ensure_ascii=False, indent=2, default=str)
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print(f" 结果已保存至: {output_file}")
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if __name__ == "__main__":
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asyncio.run(main())
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