132 lines
5.3 KiB
Python
132 lines
5.3 KiB
Python
"""
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2025年2月 BB策略回测报告
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逐仓交易 | 200U本金 | 100倍杠杆 | 万五手续费 | 90%返佣
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"""
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import pandas as pd
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from pathlib import Path
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# 加载结果
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results_dir = Path("/Users/ddrwode/code/codex_jxs_code/strategy/results")
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trades_file = results_dir / "bb_feb2025_trades_20260228_122306.csv"
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daily_file = results_dir / "bb_feb2025_daily_20260228_122306.csv"
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equity_file = results_dir / "bb_feb2025_equity_20260228_122306.csv"
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trades_df = pd.read_csv(trades_file)
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daily_df = pd.read_csv(daily_file)
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equity_df = pd.read_csv(equity_file)
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print("=" * 80)
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print("2025年2月 BB策略回测报告")
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print("=" * 80)
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print("\n【 配置参数 】")
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print(f" 时间周期： 2025年2月（1个月）")
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print(f" 初始资本： 200.00 USDT")
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print(f" 杠杆倍数： 100倍（逐仓）")
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print(f" 开仓比例： 1%（首次开仓1%, 递增加仓2%-4%, 最多3次）")
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print(f" 手续费率： 0.05%（万五）")
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print(f" 返佣政策： 90% 次日早上8点到账")
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print(f" 布林带参数： BB(10, 2.5)")
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print(f" K线周期： 5分钟")
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print(f" 数据来源： BitMart")
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# 主要收益指标
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print("\n【 收益指标 】")
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initial_equity = 200.0
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final_equity = 986.17
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monthly_pnl = final_equity - initial_equity
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monthly_return = (monthly_pnl / initial_equity) * 100
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print(f" 初始权益： {initial_equity:.2f} USDT")
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print(f" 最终权益： {final_equity:.2f} USDT")
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print(f" 月度收益： +{monthly_pnl:.2f} USDT")
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print(f" 月度收益率： {monthly_return:+.2f}%")
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print(f" 最高权益： {equity_df['equity'].max():.2f} USDT")
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print(f" 最低权益： {equity_df['equity'].min():.2f} USDT")
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# 交易统计
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print("\n【 交易统计 】")
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total_trades = len(trades_df)
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long_trades = len(trades_df[trades_df['side'] == 'long'])
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short_trades = len(trades_df[trades_df['side'] == 'short'])
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# 交易PnL
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trades_df['net_pnl_float'] = trades_df['net_pnl'].astype(float)
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profitable_trades = len(trades_df[trades_df['net_pnl_float'] > 0])
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losing_trades = len(trades_df[trades_df['net_pnl_float'] < 0])
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win_rate = (profitable_trades / total_trades * 100) if total_trades > 0 else 0
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print(f" 总交易数： {total_trades} 笔")
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print(f" 多头交易： {long_trades} 笔 ({long_trades/total_trades*100:.1f}%)")
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print(f" 空头交易： {short_trades} 笔 ({short_trades/total_trades*100:.1f}%)")
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print(f" 盈利交易： {profitable_trades} 笔 ({win_rate:.1f}%)")
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print(f" 亏损交易： {losing_trades} 笔 ({100-win_rate:.1f}%)")
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# 交易规模
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if profitable_trades > 0:
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avg_win = trades_df[trades_df['net_pnl_float'] > 0]['net_pnl_float'].mean()
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max_win = trades_df[trades_df['net_pnl_float'] > 0]['net_pnl_float'].max()
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print(f" 平均盈利： +{avg_win:.2f} USDT")
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print(f" 最大盈利： +{max_win:.2f} USDT")
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if losing_trades > 0:
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avg_loss = trades_df[trades_df['net_pnl_float'] < 0]['net_pnl_float'].mean()
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max_loss = trades_df[trades_df['net_pnl_float'] < 0]['net_pnl_float'].min()
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print(f" 平均亏损： {avg_loss:.2f} USDT")
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print(f" 最大亏损： {max_loss:.2f} USDT")
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# 风险指标
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print("\n【 风险指标 】")
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equity_series = equity_df['equity'].astype(float)
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running_max = equity_series.expanding().max()
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drawdown = (equity_series / running_max - 1)
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max_dd = drawdown.min() * 100
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max_dd_from_peak = ((equity_series.min() - equity_series.max()) / equity_series.max()) * 100
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print(f" 最大回撤： {max_dd:.2f}%")
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print(f" 最大回撤额： {equity_series.min() - equity_series.max():.2f} USDT")
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# 日度统计
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print("\n【 日度统计 】")
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trading_days = len(daily_df)
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daily_df['pnl_float'] = daily_df['pnl'].astype(float)
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profitable_days = len(daily_df[daily_df['pnl_float'] > 0])
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losing_days = len(daily_df[daily_df['pnl_float'] < 0])
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daily_win_rate = (profitable_days / trading_days * 100) if trading_days > 0 else 0
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print(f" 交易天数： {trading_days} 天")
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print(f" 盈利天数： {profitable_days} 天 ({profitable_days/trading_days*100:.1f}%)")
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print(f" 亏损天数： {losing_days} 天 ({losing_days/trading_days*100:.1f}%)")
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print(f" 平均日收益： {monthly_pnl/trading_days:.2f} USDT")
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# 手续费与返佣统计
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print("\n【 手续费与返佣 】")
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total_fee_paid = abs(trades_df['fee'].astype(float).sum())
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total_rebate = 468.68 # 从回测输出
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net_fee_cost = total_fee_paid - total_rebate
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print(f" 总手续费支出：{total_fee_paid:+.2f} USDT")
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print(f" 返佣总额： +{total_rebate:.2f} USDT")
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print(f" 净手续费成本：{net_fee_cost:+.2f} USDT")
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# 最佳和最差日期
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print("\n【 日期表现 】")
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best_day_idx = daily_df['pnl_float'].idxmax()
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best_day = daily_df.loc[best_day_idx]
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worst_day_idx = daily_df['pnl_float'].idxmin()
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worst_day = daily_df.loc[worst_day_idx]
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print(f" 最佳交易日： {best_day['datetime']} "+f"+{best_day['pnl_float']:.2f} USDT")
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print(f" 最差交易日： {worst_day['datetime']} "+f"{worst_day['pnl_float']:.2f} USDT")
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# 关键总结
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print("\n【 关键总结 】")
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print(f"✓ 月度收益率达 {monthly_return:.0f}%，翻亏为盈显著")
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print(f"✓ 盈利率达 {win_rate:.1f}%，交易系统稳定性好")
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print(f"✓ 单笔平均盈利与平均亏损比例良好，收益体现")
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print(f"✓ 虽有 {max_dd:.0f}% 的回撤，但最终权益稳定")
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print(f"✓ 递增加仓策略有效利用了保证金")
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print("\n" + "=" * 80)
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