68 lines
2.3 KiB
Python
68 lines
2.3 KiB
Python
"""
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bb_trade.py 策略回测 — 2026年2月，输出详细交易明细
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200U 本金 | 1% 仓位/单 | 万五手续费 | 90% 返佣次日8点到账
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按北京时间加载数据 (与交易所/网页显示一致)
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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 pandas as pd
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from pathlib import Path
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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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out_dir = Path(__file__).resolve().parent / "results"
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out_dir.mkdir(parents=True, exist_ok=True)
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# 按北京时间加载 2026-02-01 00:00 ~ 2026-03-01 00:00
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df = load_klines('5m', '2026-02-01', '2026-03-01', tz='Asia/Shanghai')
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cfg = BBConfig(
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bb_period=10, bb_std=2.5, leverage=50, initial_capital=200.0,
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margin_pct=0.01, max_daily_loss=50.0, fee_rate=0.0005,
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rebate_pct=0.90, rebate_hour_utc=0, pyramid_enabled=False, # 不加仓
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pyramid_step=0.01, pyramid_max=3, slippage_pct=0.0, liq_enabled=True,
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cross_margin=True, # 全仓：仅权益<=0 时爆仓
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fill_at_close=True, # 真实成交：检测到信号后在 K 线收盘价成交
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)
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r = run_bb_backtest(df, cfg)
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# 数据库/回测使用 UTC，转为北京时间输出
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def to_beijing(ts):
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if hasattr(ts, 'tz_localize'):
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return ts.tz_localize('UTC').tz_convert('Asia/Shanghai').strftime('%Y-%m-%d %H:%M:%S')
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return str(ts)[:19]
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# 构建交易明细 DataFrame
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rows = []
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for i, t in enumerate(r.trades, 1):
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rows.append({
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"序号": i,
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"方向": "做多" if t.side == "long" else "做空",
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"开仓时间": to_beijing(t.entry_time),
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"平仓时间": to_beijing(t.exit_time),
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"开仓价": round(t.entry_price, 2),
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"平仓价": round(t.exit_price, 2),
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"保证金": round(t.margin, 2),
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"杠杆": t.leverage,
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"数量": round(t.qty, 4),
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"毛盈亏": round(t.gross_pnl, 2),
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"手续费": round(t.fee, 2),
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"净盈亏": round(t.net_pnl, 2),
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})
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trade_df = pd.DataFrame(rows)
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# 保存 CSV
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csv_path = out_dir / "bb_202602_trade_detail.csv"
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trade_df.to_csv(csv_path, index=False, encoding="utf-8-sig")
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print(f"交易明细已保存: {csv_path}")
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# 打印到控制台
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print("\n" + "=" * 150)
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print(f" 交易明细 (共 {len(r.trades)} 笔)")
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print("=" * 150)
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print(trade_df.to_string(index=False))
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