edc50e8809
- 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
213 lines
8.5 KiB
Python
213 lines
8.5 KiB
Python
"""
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策略3 ATR波动率突破 — 全量 / 近两年 / 近一年 / 近半年 对比
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用法:
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source .venv/bin/activate && python example/vol_break_periods.py
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"""
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import asyncio
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import sys
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import time
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from datetime import datetime, timezone, timedelta
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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.config import config
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from engine.backtest import BacktestConfig
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from engine.data import DataService
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from engine.example.long_short import LongShortEngine
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from engine.example.intraday_explore import VolBreakStrategy, VolBreakConfig
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SYMBOLS = ["BTCUSDT", "ETHUSDT", "BNBUSDT", "SOLUSDT"]
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INTERVAL = "1h"
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INITIAL = 10_000.0
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TODAY = datetime.now(timezone.utc)
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# 时间段定义
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PERIODS = {
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"全量": (None, TODAY), # start 动态获取
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"近两年": (TODAY - timedelta(days=365 * 2), TODAY),
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"近一年": (TODAY - timedelta(days=365), TODAY),
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"近半年": (TODAY - timedelta(days=182), TODAY),
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}
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PARAMS = {
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"BTCUSDT": {"atr_period": 14, "squeeze_period": 20, "squeeze_ratio": 0.7, "atr_stop": 2.0},
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"ETHUSDT": {"atr_period": 14, "squeeze_period": 20, "squeeze_ratio": 0.7, "atr_stop": 2.0},
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"BNBUSDT": {"atr_period": 14, "squeeze_period": 20, "squeeze_ratio": 0.7, "atr_stop": 2.0},
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"SOLUSDT": {"atr_period": 14, "squeeze_period": 20, "squeeze_ratio": 0.7, "atr_stop": 2.0},
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}
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def fmt_ts(ts_ms: float) -> str:
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dt = datetime.fromtimestamp(ts_ms / 1000, tz=timezone.utc)
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return dt.strftime("%Y-%m-%d %H:%M")
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def pair_trades(trades: list) -> list[dict]:
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paired = []
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pending_open = None
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for t in trades:
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if t.side == "BUY":
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if pending_open and pending_open["side"] == "short":
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paired.append({
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"type": "做空",
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"entry_ts": pending_open["ts"],
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"entry_price": pending_open["price"],
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"entry_reason": pending_open["reason"],
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"exit_ts": t.timestamp,
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"exit_price": t.price,
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"exit_reason": t.reason,
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"pnl": t.pnl or 0,
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})
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pending_open = None
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elif t.pnl is None:
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pending_open = {"side": "long", "price": t.price, "reason": t.reason, "ts": t.timestamp}
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elif t.side == "SELL":
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if pending_open and pending_open["side"] == "long":
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paired.append({
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"type": "做多",
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"entry_ts": pending_open["ts"],
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"entry_price": pending_open["price"],
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"entry_reason": pending_open["reason"],
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"exit_ts": t.timestamp,
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"exit_price": t.price,
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"exit_reason": t.reason,
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"pnl": t.pnl or 0,
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})
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pending_open = None
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elif t.pnl is None:
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pending_open = {"side": "short", "price": t.price, "reason": t.reason, "ts": t.timestamp}
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return paired
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async def run_backtest(symbol, start, end):
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sc = VolBreakConfig(symbol=symbol, **PARAMS[symbol])
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bt = BacktestConfig(symbol=symbol, interval=INTERVAL, start_time=start, end_time=end, initial_capital=INITIAL)
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engine = LongShortEngine(bt, db_config=config.db)
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r = await engine.run(VolBreakStrategy, sc)
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return r
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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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full_ranges = {}
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for symbol in SYMBOLS:
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try:
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s, e = await ds.fetch_symbol_date_range(symbol, INTERVAL)
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full_ranges[symbol] = (s, e)
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print(f" {symbol}: {s.date()} ~ {e.date()}")
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except Exception as ex:
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print(f" {symbol}: 获取范围失败 {ex}")
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# 运行所有时间段
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all_results: dict[str, dict[str, object]] = {} # symbol -> period_name -> result
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for symbol in SYMBOLS:
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if symbol not in full_ranges:
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continue
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all_results[symbol] = {}
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fs, fe = full_ranges[symbol]
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for period_name, (ps, pe) in PERIODS.items():
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start = fs if period_name == "全量" else max(ps, fs)
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end = min(pe, fe)
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if start >= end:
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print(f" {symbol} {period_name}: 无有效数据范围,跳过")
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continue
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print(f" 运行 {symbol} {period_name} ({start.date()}~{end.date()})...", end=" ", flush=True)
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t0 = time.time()
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try:
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all_results[symbol][period_name] = await run_backtest(symbol, start, end)
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print(f"{time.time()-t0:.1f}s")
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except Exception as ex:
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print(f"错误: {ex}")
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await ds.close()
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# ════════════════════════════════════════════════════
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# 对比表
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# ════════════════════════════════════════════════════
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print()
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print("═" * 165)
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print(f" ATR波动率突破 1h — 全量 / 近两年 / 近一年 / 近半年 对比 ({TODAY.strftime('%Y-%m-%d')} 截止)")
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print("═" * 165)
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print()
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col_w = 36
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for symbol in SYMBOLS:
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if symbol not in all_results:
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continue
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print(f" ■ {symbol}")
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print(f" {'时段':<8} {'本金':>7} {'终值':>9} {'总收益%':>8} {'年化%':>8} {'夏普':>7} {'回撤%':>8} {'胜率%':>7} {'盈亏比':>7} {'交易':>5} {'数据范围'}")
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print(" " + "─" * 163)
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for period_name in PERIODS:
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if period_name not in all_results[symbol]:
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continue
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r = all_results[symbol][period_name]
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m = r.metrics
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data_range = f"{r.config.start_time.date()}~{r.config.end_time.date()}"
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print(f" {period_name:<8} {INITIAL:>7.0f} {m.final_equity:>9.0f} {m.total_return_pct:>7.1f}% {m.annual_return_pct:>7.1f}% {m.sharpe_ratio:>7.2f} {m.max_drawdown_pct:>7.1f}% {m.win_rate*100:>6.1f}% {m.profit_factor:>7.2f} {m.total_trades:>5} {data_range}")
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print()
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# ════════════════════════════════════════════════════
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# 详细订单
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# ════════════════════════════════════════════════════
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print("═" * 165)
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print(" 各时段详细订单")
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print("═" * 165)
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for symbol in SYMBOLS:
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if symbol not in all_results:
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continue
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for period_name in PERIODS:
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if period_name not in all_results[symbol]:
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continue
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result = all_results[symbol][period_name]
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m = result.metrics
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paired = pair_trades(result.trades)
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if len(paired) == 0:
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continue
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print(f"\n{'─' * 155}")
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print(f" {symbol} {period_name} — {len(paired)} 笔完整交易")
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print(f" 本金 {INITIAL:,.0f} → 终值 {m.final_equity:,.0f} | 总收益 {m.total_return_pct:.1f}% | 年化 {m.annual_return_pct:.1f}% | 夏普 {m.sharpe_ratio:.2f} | 回撤 {m.max_drawdown_pct:.1f}%")
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print(f" 胜率 {m.win_rate*100:.1f}% | 盈亏比 {m.profit_factor:.2f} | 最佳 {m.best_trade_pnl:+,.0f} | 最差 {m.worst_trade_pnl:+,.0f} | 平均 {m.avg_trade_pnl:+,.0f}")
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print(f" 数据范围: {result.config.start_time.date()} ~ {result.config.end_time.date()}")
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print(f"{'─' * 155}")
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print(f" {'#':>3} {'类型':<5} {'入场时间':<19} {'入场价':>10} {'出场时间':<19} {'出场价':>10} {'盈亏':>12} {'入场原因':<35} {'出场原因':<30}")
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print(f" {'─' * 153}")
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total_pnl = 0
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wins = 0
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for i, p in enumerate(paired):
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pnl = p["pnl"]
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total_pnl += pnl
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if pnl > 0:
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wins += 1
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pnl_str = f"{pnl:+,.0f}"
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print(f" {i+1:>3} {p['type']:<5} {p['entry_ts']:<19} {p['entry_price']:>10.4f} {p['exit_ts']:<19} {p['exit_price']:>10.4f} {pnl_str:>12} {p['entry_reason']:<35} {p['exit_reason']:<30}")
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print(f" {'─' * 153}")
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print(f" 合计: {len(paired)} 笔 | 盈利 {wins} 笔 ({wins/len(paired)*100 if paired else 0:.0f}%) | 总盈亏 {total_pnl:+,.0f} USDT")
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print(f"\n{'─' * 155}")
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print()
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if __name__ == "__main__":
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asyncio.run(main())
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