70 lines
2.3 KiB
Python
70 lines
2.3 KiB
Python
"""
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BB(10, 2.5) 均值回归策略回测 — 2026/02/23 ~ 现在，本金 100U
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完全复现 bb_trade.py 的参数: BB(10,2.5) | 50x | 1%权益/单 | 递增加仓 +1%/次 max=3
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"""
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import sys
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sys.path.insert(0, str(__import__("pathlib").Path(__file__).resolve().parents[1]))
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import numpy as np
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from pathlib import Path
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from datetime import datetime, timedelta
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from strategy.bb_backtest import BBConfig, run_bb_backtest
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from strategy.data_loader import load_klines
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# 加载 2026-02-23 至今天的数据 (end_date 不包含，用明天确保含今天)
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today = datetime.now().strftime("%Y-%m-%d")
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END_DATE = (datetime.now() + timedelta(days=1)).strftime("%Y-%m-%d")
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df = load_klines('5m', '2026-02-23', END_DATE)
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print(f"数据: 2026-02-23 ~ {today}, 共 {len(df):,} 根 5 分钟 K 线")
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# 配置：完全匹配 bb_trade.py D方案
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cfg = BBConfig(
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bb_period=10,
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bb_std=2.5,
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leverage=50,
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initial_capital=100.0, # 本金 100U
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margin_pct=0.01, # 1% 权益/单
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pyramid_enabled=True,
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pyramid_step=0.01, # 递增加仓 +1%/次
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pyramid_max=3,
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max_daily_loss=50.0,
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fee_rate=0.0005,
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rebate_rate=0.0,
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rebate_pct=0.90,
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rebate_hour_utc=0,
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)
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r = run_bb_backtest(df, cfg)
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# 结果
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d = r.daily_stats
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pnl = d["pnl"].astype(float)
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eq = d["equity"].astype(float)
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final = float(eq.iloc[-1])
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dd = float((eq - eq.cummax()).min())
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ret_pct = (final - cfg.initial_capital) / cfg.initial_capital * 100
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nt = len(r.trades)
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wr = sum(1 for t in r.trades if t.net_pnl > 0) / max(nt, 1) * 100
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print("\n" + "=" * 60)
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print(" 回测结果 (BB 均值回归 | 2026/02/23 ~ 现在 | 本金 100U)")
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print("=" * 60)
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print(f" 最终权益: {final:,.2f} U")
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print(f" 收益: {final - cfg.initial_capital:+,.2f} U ({ret_pct:+.1f}%)")
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print(f" 最大回撤: {dd:+,.2f} U")
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print(f" 交易次数: {nt}")
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print(f" 胜率: {wr:.1f}%")
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print(f" 总手续费: {r.total_fee:.2f} U")
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print(f" 总返佣: {r.total_rebate:.2f} U")
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print("=" * 60)
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# 打印每日收益
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if len(d) > 1:
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print("\n每日收益:")
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for idx, row in d.iterrows():
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day_str = idx.strftime("%Y-%m-%d") if hasattr(idx, 'strftime') else str(idx)[:10]
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p = row["pnl"]
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e = row["equity"]
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print(f" {day_str}: PnL {p:+.2f} U, 权益 {e:.2f} U")
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