608 lines
2.3 MiB
Plaintext
608 lines
2.3 MiB
Plaintext
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 75,
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"id": "initial_id",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-07-12T14:39:30.843472Z",
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"start_time": "2025-07-12T14:39:30.823755Z"
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},
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"collapsed": true
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The autoreload extension is already loaded. To reload it, use:\n",
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" %reload_ext autoreload\n"
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]
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}
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],
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"source": [
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"from datetime import datetime\n",
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"%load_ext autoreload\n",
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"%autoreload 2\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a559dfcf",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-07-12T14:39:35.610573Z",
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"start_time": "2025-07-12T14:39:30.855663Z"
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}
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"初始化数据管理器...\n",
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"数据加载成功: /mnt/d/PyProject/NewQuant/data/data/KQ_m@SHFE_rb/KQ_m@SHFE_rb_min60.csv\n",
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"数据范围从 2021-12-31 14:00:00 到 2025-06-20 21:00:00\n",
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"总计 5811 条记录。\n",
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"\n",
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"初始化回测引擎...\n",
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"模拟器初始化：初始资金=100000.00, 滑点率=0.0, 佣金率=0.0001\n",
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"\n",
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"--- 回测引擎初始化完成 ---\n",
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" 策略: SimpleLimitBuyStrategyShort\n",
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" 初始资金: 100000.00\n",
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" 换月模式: 启用\n",
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"\n",
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"开始运行回测...\n",
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"\n",
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"--- 回测开始 ---\n",
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"SimpleLimitBuyStrategyShort 策略初始化回调被调用。\n",
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"开始将 DataFrame 转换为 Bar 对象流...\n",
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"Bar 对象流生成完毕。\n",
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"\n",
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"--- 回测结束，检查并平仓所有剩余持仓 ---\n",
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"--- 回测结束 ---\n",
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"总计处理了 1671 根K线。\n",
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"总计发生了 90 笔交易。\n",
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"最终总净值: 101766.31\n",
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"总收益率: 1.77%\n",
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"\n",
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"回测运行完毕。\n",
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"\n",
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"--- 结果分析器初始化完成 ---\n",
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"\n",
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"--- 交易明细 ---\n",
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" 2024-06-20 09:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3619.00 | Comm: 0.36\n",
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" 2024-06-21 21:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3559.00 | Comm: 0.36 | PnL: 60.00\n",
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" 2024-07-15 10:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3577.00 | Comm: 0.36\n",
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" 2024-07-16 11:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3541.00 | Comm: 0.35 | PnL: 36.00\n",
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" 2024-07-22 11:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3474.00 | Comm: 0.35\n",
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" 2024-07-23 11:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3418.00 | Comm: 0.34 | PnL: 56.00\n",
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" 2024-07-25 21:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3334.00 | Comm: 0.33\n",
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" 2024-07-25 22:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3381.00 | Comm: 0.34 | PnL: -47.00\n",
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" 2024-07-26 11:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3385.00 | Comm: 0.34\n",
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" 2024-07-30 22:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3281.00 | Comm: 0.33 | PnL: 104.00\n",
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" 2024-08-01 13:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3345.00 | Comm: 0.33\n",
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" 2024-08-02 14:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3366.00 | Comm: 0.34 | PnL: -21.00\n",
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" 2024-08-05 10:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3363.00 | Comm: 0.34\n",
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" 2024-08-05 13:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3389.00 | Comm: 0.34 | PnL: -26.00\n",
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" 2024-08-05 21:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3355.00 | Comm: 0.34\n",
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" 2024-08-08 10:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3290.00 | Comm: 0.33 | PnL: 65.00\n",
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" 2024-08-08 11:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3291.00 | Comm: 0.33\n",
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" 2024-08-12 13:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3227.00 | Comm: 0.32 | PnL: 64.00\n",
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" 2024-08-12 14:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3230.00 | Comm: 0.32\n",
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" 2024-08-13 22:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3162.00 | Comm: 0.32 | PnL: 68.00\n",
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" 2024-08-14 09:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3165.00 | Comm: 0.32\n",
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" 2024-08-16 21:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3061.00 | Comm: 0.31 | PnL: 104.00\n",
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" 2024-08-20 11:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3154.00 | Comm: 0.32\n",
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" 2024-08-20 21:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3191.00 | Comm: 0.32 | PnL: -37.00\n",
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" 2024-08-20 22:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3188.00 | Comm: 0.32\n",
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" 2024-08-21 13:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3210.00 | Comm: 0.32 | PnL: -22.00\n",
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" 2024-08-22 21:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3178.00 | Comm: 0.32\n",
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" 2024-08-26 09:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3216.00 | Comm: 0.32 | PnL: -38.00\n",
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" 2024-08-27 09:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3253.00 | Comm: 0.33\n",
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" 2024-08-27 14:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3285.00 | Comm: 0.33 | PnL: -32.00\n",
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" 2024-08-27 22:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3256.00 | Comm: 0.33\n",
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" 2024-08-29 13:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3278.00 | Comm: 0.33 | PnL: -22.00\n",
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" 2024-08-29 14:00:00 | SELL | SHFE.rb2410 | Vol: 1 | Price: 3272.00 | Comm: 0.33\n",
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" 2024-08-30 14:00:00 | CLOSE_SHORT | SHFE.rb2410 | Vol: 1 | Price: 3256.00 | Comm: 0.33 | PnL: 16.00\n",
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" 2024-09-02 22:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3237.00 | Comm: 0.32\n",
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" 2024-09-03 13:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3181.00 | Comm: 0.32 | PnL: 56.00\n",
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" 2024-09-12 21:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3192.00 | Comm: 0.32\n",
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" 2024-09-13 10:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3213.00 | Comm: 0.32 | PnL: -21.00\n",
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" 2024-09-18 09:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3192.00 | Comm: 0.32\n",
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" 2024-09-19 22:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3221.00 | Comm: 0.32 | PnL: -29.00\n",
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" 2024-09-26 13:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3283.00 | Comm: 0.33\n",
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" 2024-09-26 21:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3309.00 | Comm: 0.33 | PnL: -26.00\n",
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" 2024-10-08 09:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3701.00 | Comm: 0.37\n",
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" 2024-10-08 11:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3542.00 | Comm: 0.35 | PnL: 159.00\n",
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" 2024-10-16 22:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3463.00 | Comm: 0.35\n",
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" 2024-10-17 13:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3356.00 | Comm: 0.34 | PnL: 107.00\n",
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" 2024-10-21 21:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3361.00 | Comm: 0.34\n",
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" 2024-10-25 21:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3383.00 | Comm: 0.34 | PnL: -22.00\n",
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" 2024-10-28 13:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3472.00 | Comm: 0.35\n",
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" 2024-10-29 13:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3415.00 | Comm: 0.34 | PnL: 57.00\n",
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" 2024-10-29 22:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3444.00 | Comm: 0.34\n",
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" 2024-11-04 13:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3400.00 | Comm: 0.34 | PnL: 44.00\n",
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" 2024-11-05 11:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3447.00 | Comm: 0.34\n",
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" 2024-11-06 11:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3389.00 | Comm: 0.34 | PnL: 58.00\n",
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" 2024-11-07 14:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3428.00 | Comm: 0.34\n",
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" 2024-11-11 13:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3341.00 | Comm: 0.33 | PnL: 87.00\n",
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" 2024-11-12 09:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3336.00 | Comm: 0.33\n",
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" 2024-11-13 14:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3362.00 | Comm: 0.34 | PnL: -26.00\n",
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" 2024-11-15 10:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3269.00 | Comm: 0.33\n",
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" 2024-11-19 14:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3290.00 | Comm: 0.33 | PnL: -21.00\n",
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" 2024-11-19 21:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3321.00 | Comm: 0.33\n",
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" 2024-11-22 13:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3275.00 | Comm: 0.33 | PnL: 46.00\n",
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" 2024-11-25 10:00:00 | SELL | SHFE.rb2501 | Vol: 1 | Price: 3317.00 | Comm: 0.33\n",
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" 2024-11-29 11:00:00 | CLOSE_SHORT | SHFE.rb2501 | Vol: 1 | Price: 3338.00 | Comm: 0.33 | PnL: -21.00\n",
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" 2024-12-06 10:00:00 | SELL | SHFE.rb2505 | Vol: 1 | Price: 3324.00 | Comm: 0.33\n",
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" 2024-12-09 21:00:00 | CLOSE_SHORT | SHFE.rb2505 | Vol: 1 | Price: 3396.00 | Comm: 0.34 | PnL: -72.00\n",
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" 2024-12-13 09:00:00 | SELL | SHFE.rb2505 | Vol: 1 | Price: 3393.00 | Comm: 0.34\n",
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" 2024-12-16 11:00:00 | CLOSE_SHORT | SHFE.rb2505 | Vol: 1 | Price: 3344.00 | Comm: 0.33 | PnL: 49.00\n",
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" 2024-12-19 11:00:00 | SELL | SHFE.rb2505 | Vol: 1 | Price: 3281.00 | Comm: 0.33\n",
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" 2024-12-24 21:00:00 | CLOSE_SHORT | SHFE.rb2505 | Vol: 1 | Price: 3309.00 | Comm: 0.33 | PnL: -28.00\n",
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" 2025-02-05 11:00:00 | SELL | SHFE.rb2505 | Vol: 1 | Price: 3323.00 | Comm: 0.33\n",
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" 2025-02-06 11:00:00 | CLOSE_SHORT | SHFE.rb2505 | Vol: 1 | Price: 3350.00 | Comm: 0.34 | PnL: -27.00\n",
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" 2025-02-10 11:00:00 | SELL | SHFE.rb2505 | Vol: 1 | Price: 3321.00 | Comm: 0.33\n",
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" 2025-02-11 22:00:00 | CLOSE_SHORT | SHFE.rb2505 | Vol: 1 | Price: 3272.00 | Comm: 0.33 | PnL: 49.00\n",
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" 2025-02-26 13:00:00 | SELL | SHFE.rb2505 | Vol: 1 | Price: 3332.00 | Comm: 0.33\n",
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" 2025-03-04 10:00:00 | CLOSE_SHORT | SHFE.rb2505 | Vol: 1 | Price: 3271.00 | Comm: 0.33 | PnL: 61.00\n",
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" 2025-03-04 11:00:00 | SELL | SHFE.rb2505 | Vol: 1 | Price: 3276.00 | Comm: 0.33\n",
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" 2025-03-10 11:00:00 | CLOSE_SHORT | SHFE.rb2505 | Vol: 1 | Price: 3228.00 | Comm: 0.32 | PnL: 48.00\n",
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" 2025-03-24 10:00:00 | SELL | SHFE.rb2505 | Vol: 1 | Price: 3190.00 | Comm: 0.32\n",
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" 2025-03-25 13:00:00 | CLOSE_SHORT | SHFE.rb2505 | Vol: 1 | Price: 3217.00 | Comm: 0.32 | PnL: -27.00\n",
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" 2025-04-10 14:00:00 | SELL | SHFE.rb2510 | Vol: 1 | Price: 3145.00 | Comm: 0.31\n",
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" 2025-04-16 11:00:00 | CLOSE_SHORT | SHFE.rb2510 | Vol: 1 | Price: 3098.00 | Comm: 0.31 | PnL: 47.00\n",
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" 2025-04-25 22:00:00 | SELL | SHFE.rb2510 | Vol: 1 | Price: 3147.00 | Comm: 0.31\n",
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" 2025-04-29 13:00:00 | CLOSE_SHORT | SHFE.rb2510 | Vol: 1 | Price: 3100.00 | Comm: 0.31 | PnL: 47.00\n",
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" 2025-05-06 10:00:00 | SELL | SHFE.rb2510 | Vol: 1 | Price: 3091.00 | Comm: 0.31\n",
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" 2025-05-07 09:00:00 | CLOSE_SHORT | SHFE.rb2510 | Vol: 1 | Price: 3118.00 | Comm: 0.31 | PnL: -27.00\n",
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" 2025-05-08 14:00:00 | SELL | SHFE.rb2510 | Vol: 1 | Price: 3060.00 | Comm: 0.31\n",
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" 2025-05-12 21:00:00 | CLOSE_SHORT | SHFE.rb2510 | Vol: 1 | Price: 3106.00 | Comm: 0.31 | PnL: -46.00\n",
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" 2025-05-14 10:00:00 | SELL | SHFE.rb2510 | Vol: 1 | Price: 3114.00 | Comm: 0.31\n",
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" 2025-05-19 13:00:00 | CLOSE_SHORT | SHFE.rb2510 | Vol: 1 | Price: 3066.00 | Comm: 0.31 | PnL: 48.00\n",
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"正在计算绩效指标...\n",
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"total_return: 0.017663100000000487, annualized_return:0.012297290879008438, 252 / total_days:0.6980609418282548\n",
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"绩效指标计算完成。\n",
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"\n",
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"--- 回测绩效报告 ---\n",
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"初始资金 : 100000.00\n",
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"最终资金 : 101766.31\n",
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"总收益率 : 1.77%\n",
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"年化收益率 : 1.23%\n",
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"最大回撤 : 0.32%\n",
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"夏普比率 : 1.13\n",
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"卡玛比率 : 3.89\n",
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"总交易次数 : 90\n",
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"总实现盈亏 : 898.00\n",
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"交易成本 : 29.69\n",
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"\n",
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"--- 交易详情 ---\n",
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"盈利交易次数 : 24\n",
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"亏损交易次数 : 21\n",
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"胜率 : 53.33%\n",
|
|||
|
|
"盈亏比 : 2.11\n",
|
|||
|
|
"平均每次盈利 : 64.00\n",
|
|||
|
|
"平均每次亏损 : -30.38\n",
|
|||
|
|
"正在绘制绩效图表...\n"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 1400x1000 with 2 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 1400x700 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"name": "stdout",
|
|||
|
|
"output_type": "stream",
|
|||
|
|
"text": [
|
|||
|
|
"图表绘制完成。\n",
|
|||
|
|
"{'初始资金': 100000.0, '最终资金': np.float64(101766.31000000006), '总收益率': np.float64(0.017663100000000487), '年化收益率': np.float64(0.012297290879008438), '最大回撤': np.float64(0.003162276839125643), '夏普比率': np.float64(1.133569794823866), '卡玛比率': np.float64(3.888745832388473), '总交易次数': 90, '交易成本': 29.69, '总实现盈亏': 898.0, '胜率': 0.5333333333333333, '盈亏比': 2.1065830721003134, '盈利交易次数': 24, '亏损交易次数': 21, '平均每次盈利': 64.0, '平均每次亏损': -30.38095238095238, 'initial_capital': 100000.0, 'final_capital': np.float64(101766.31000000006), 'total_return': np.float64(0.017663100000000487), 'annualized_return': np.float64(0.012297290879008438), 'max_drawdown': np.float64(0.003162276839125643), 'sharpe_ratio': np.float64(1.133569794823866), 'calmar_ratio': np.float64(3.888745832388473), 'total_trades': 90, 'transaction_costs': 29.69, 'total_realized_pnl': 898.0, 'win_rate': 0.5333333333333333, 'profit_loss_ratio': 2.1065830721003134, 'winning_trades_count': 24, 'losing_trades_count': 21, 'avg_profit_per_trade': 64.0, 'avg_loss_per_trade': -30.38095238095238}\n"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
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"text/plain": [
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"<Figure size 1200x700 with 1 Axes>"
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},
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"metadata": {},
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"output_type": "display_data"
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{
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"data": {
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"text/plain": [
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|||
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"<Figure size 1200x700 with 1 Axes>"
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]
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},
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"metadata": {},
|
|||
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
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"<Figure size 1200x700 with 1 Axes>"
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]
|
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},
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"metadata": {},
|
|||
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
|
|||
|
|
"<Figure size 1200x700 with 1 Axes>"
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]
|
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},
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"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
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},
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{
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"data": {
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"text/plain": [
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"<Figure size 1200x700 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
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"<Figure size 1200x700 with 1 Axes>"
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]
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},
|
|||
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"metadata": {},
|
|||
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
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"<Figure size 1200x700 with 1 Axes>"
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},
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"metadata": {},
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"text/plain": [
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"<Figure size 1200x700 with 1 Axes>"
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]
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},
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"metadata": {},
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|||
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"output_type": "display_data"
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{
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"data": {
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"text/plain": [
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},
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"metadata": {},
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{
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"data": {
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"text/plain": [
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"<Figure size 1200x700 with 1 Axes>"
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]
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},
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"metadata": {},
|
|||
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
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"metadata": {},
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{
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"data": {
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"text/plain": [
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|||
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"<Figure size 1200x700 with 1 Axes>"
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]
|
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},
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"metadata": {},
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|||
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
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"<Figure size 1200x700 with 1 Axes>"
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]
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},
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|
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"metadata": {},
|
|||
|
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"output_type": "display_data"
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},
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{
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"data": {
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"image/png": "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
|
|||
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|
"text/plain": [
|
|||
|
|
"<Figure size 1200x700 with 1 Axes>"
|
|||
|
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]
|
|||
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|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
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|
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},
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{
|
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"data": {
|
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"text/plain": [
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"<Figure size 1200x700 with 1 Axes>"
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]
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},
|
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|
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"metadata": {},
|
|||
|
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"output_type": "display_data"
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},
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{
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"data": {
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"image/png": "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|
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"text/plain": [
|
|||
|
|
"<Figure size 1200x700 with 1 Axes>"
|
|||
|
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]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
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},
|
|||
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|
{
|
|||
|
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"data": {
|
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"text/plain": [
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"<Figure size 1200x700 with 1 Axes>"
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]
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},
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|
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"metadata": {},
|
|||
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"output_type": "display_data"
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},
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{
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"data": {
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|
"text/plain": [
|
|||
|
|
"<Figure size 1200x700 with 1 Axes>"
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]
|
|||
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|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
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},
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{
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"data": {
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"text/plain": [
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"<Figure size 1200x700 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
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|||
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"<Figure size 1200x700 with 1 Axes>"
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]
|
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},
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"metadata": {},
|
|||
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
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"metadata": {},
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"text/plain": [
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"<Figure size 1200x700 with 1 Axes>"
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]
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},
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"metadata": {},
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{
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"data": {
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"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 1200x700 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAABKYAAAK1CAYAAADyjObpAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvZiW1igAAAAlwSFlzAAAPYQAAD2EBqD+naQAA+VxJREFUeJzs3Xd4VHX2x/HPnZ4OSSChVxUVEBFRUEQRCyIq7s+6iAWW1QVdu4gNxbWtFXFt2BuCHRu6YGEVBZGmYkEpUiUJkDr9/v64zECkBUhyZzLv1/PwcDP3zsyZyZ0kc+ac8zVM0zQFAAAAAAAA1DOH3QEAAAAAAAAgNZGYAgAAAAAAgC1ITAEAAAAAAMAWJKYAAAAAAABgCxJTAAAAAAAAsAWJKQAAAAAAANiCxBQAAAAAAABsQWIKAAAAAAAAtiAxBQAAAAAAAFuQmAIAoAH7+uuvtd9+++nrr7+2OxTU0HnnnafzzjuvVm/z4Ycf1n777Vert5notnfujx49Wv369avXOFauXKn99ttPb7zxRr3eLwAAycJldwAAANSml156SWlpaTr99NNr7TY3bNig119/XZ988ol+/fVXhcNhtW/fXhdccIFOOumkasdWVFToqaee0oIFC7Ro0SJt2rRJd955Z43iGTRokMrKyvTJJ5/IMIztHnP22WdrxYoV+vzzz+Vy8Wt8RxYvXqynnnpKc+bMUXFxsdLT03XAAQdo0KBBOu200+R0Ou0OsdZVVVVp4sSJ6tmzpw477DC7w5FkJcQmTJgQ/9rlcqmgoED9+vXTZZddpuzsbBujSyxff/21hg4dGv/a5XKpsLBQhxxyiC699FK1atVqt2+zX79+2mefffT444/XZqgAANQq/qIFADQor7zyiho3blyrian58+frwQcf1FFHHaVLLrlELpdL06ZN0xVXXKElS5bosssuix+7YcMGPfLII2revLn2228/zZ49u8b3M2jQIN1333365ptvdOihh26zf+XKlZo/f76GDBlCUmonpkyZoltuuUV5eXk69dRT1aZNG1VUVOirr77SDTfcoPXr1+viiy+2O8xaV1VVpQkTJmjUqFHbJKYuueQSjRgxwqbIpLFjxyo9PV1VVVWaNWuWXnjhBX3//fd65ZVX6jWOcePGyTTNer3P3XXeeeepS5cuCofD+uGHH/Tqq6/qs88+0zvvvKOCggK7wwMAoNbxVy0AIGVVVlYqPT19l8d17NhR06ZNU4sWLeKXnXvuubrgggv05JNPavjw4fHbadq0qf73v/+pSZMmWrRokf7v//6vxvEMGjRI999/v6ZOnbrdxNR7770n0zQ1aNCgGt9mqpk/f75uueUWdevWTU888YQyMzPj+y644AItWrRIv/zyi40R2sPlctmazDzhhBOUm5sryar6u+KKK/T+++9r4cKF6tq1a73F4Xa76+2+9lSPHj104oknSpL+8pe/qG3btrr99tv11ltv6e9//7vN0QEAUPuYMQUAsE1s7s3y5cs1evRo9ejRQ4cccoiuv/56VVVVVTv29ddf19ChQ9WrVy917txZJ510kl5++eVqx/Tr10+//PKLZs+erf3220/77bdffFbPG2+8Ea9gGjt2rHr16qW+ffvWKM5WrVpVS0pJkmEY6t+/v4LBoH7//ff45R6PR02aNNmTp0PNmjXToYceqmnTpikUCm2z/91331Xr1q110EEHadWqVRo7dqxOOOEEde3aVYcddpguu+wyrVy5cpf3069fP40ePXqby7c32ygYDGr8+PE67rjj1LlzZ/Xt21f33HOPgsHgTu/jtttu08EHH7zN91GSrrzySh1xxBGKRCKSpEWLFmnYsGE67LDD1LVrV/Xr10/XX3/9Lh/H9kyYMEGGYejee++tlpSK6dKlS7yabkfzt7Y3E2j06NE6+OCDtXr1av3973/XwQcfrD59+uill16SJP30008aOnSounXrpmOOOUZTp06tdps7mvEUOy939n0LBoN66KGHdPrpp+uQQw5Rt27ddO655+qrr76qFnOvXr3iz0Hs/H/44Ye3e/8nn3zydudYRaNR9enTp1oVYDQa1bPPPquBAweqS5cu6t27t26++WZt2rRphzHvSo8ePSRJK1asqHb5ggULNGzYMB1yyCE66KCDNGTIEM2dO7faMXtz7v95xtR5550Xf67+/G/r739paan+9a9/qW/fvurcubOOO+44PfHEE4pGo9Vuv7S0VKNHj9YhhxyiHj166LrrrlNZWdluPz9bO/zwwyUp/vh25+cmAADJgIopAIDtLr/8crVs2VJXXnmlfvjhB02ZMkW5ubm65ppr4se88sor2meffdSvXz+5XC598sknuvXWW2Wapv76179KksaMGaNx48YpPT093qqVn59f7b5uvfVW5ebmauTIkaqsrNyruIuKiiRJjRs33qvb2dqgQYN000036X//+5+OOeaY+OU//fSTfv75Z40cOVKSlcyZN2+eBg4cqMLCQq1atUqvvPKKhg4dqvfee09paWl7HUs0GtUll1yiuXPn6swzz1SHDh30888/67nnntOyZcv0n//8Z4fXPemkk/TSSy/p008/1YABA+KXV1VV6ZNPPtHgwYPldDpVXFysYcOGqXHjxhoxYoSys7O1cuVKffzxx7sdb1VVlb766iv16NFDzZs336PHvDORSER/+9vf1KNHD1199dWaOnWqbrvtNqWlpemBBx7QoEGDdPzxx2vSpEm67rrr1K1btz2aC/Rn5eXlmjJlik4++WSdccYZqqio0Guvvabhw4drypQp2n///ZWbm6uxY8dq7NixOu6443TcccdJ0g4Hng8YMEATJkzQ+vXrqyVS586dqz/++KPa7LSbb75Zb775pk4//XSdd955WrlypV566SX98MMPeuWVV/aoCimWZNl6xtSsWbP0t7/9TZ07d9aoUaNkGIbeeOMNnX/++Xr55ZfjlVW1ee5ffPHF21Q1vvPOO/rf//6nvLw8SdZ5NWTIEK1bt05nn322mjVrpnnz5un+++/X+vXrdcMNN0iSTNPUP/7xD82dO1dnn322OnTooI8//ljXXXfdbj8/W4sl7xo1alTt8pr83AQAIBmQmAIA2G7//ffXHXfcEf9648aNeu2116q9wXrxxRfl8/niXw8ZMkTDhg3TM888E09M9e/fXw8++KAaN26sU089dbv3lZOTo2effXavh19v3LhRU6ZMUY8ePdS0adO9uq2tnXDCCRo3bpzefffdaompd999V5LibXxHH310vN0n5phjjtFZZ52ladOm6bTTTtvrWKZOnaovv/xSL7zwQrzCRZL22Wcf3XLLLfr222/VvXv37V73kEMOUUFBgT744INqialPP/1UlZWV8cTHvHnztGnTJj311FPq0qVL/Lgrrrhit+Ndvny5QqGQ9t13392+bk0EAgGdcsop8XaqQYMGqU+fPhozZozuv//++GPq3bu3BgwYoLfeekuXXnrpXt9vTk6OZsyYIY/HE7/szDPP1IABA/TCCy/ojjvuUHp6uk444QSNHTtW++233w7P/5iTTjpJ48eP17Rp0zRkyJD45e+//77S09N19NFHS5K++eYbTZkyRffee2+1FtLDDjtMw4cP14cfflij1tJYdVUsefjyyy8rNzc33rJqmqbGjh2rww47TBMnTowP/z/77LM1cOBAPfjgg3r66acl1e65f8QRR1T7+ttvv9XXX3+tv/zlL/GKymeeeUa///673nzzTbVt2zYeV9OmTfXUU0/poosuUrNmzTR9+nTNmTNH11xzjYYPHy5JOuecc6oNNK+JiooKlZSUKBwOa/HixfrXv/4lwzB0/PHHVzuuJj83AQBIBrTyAQBsd/bZZ1f7ukePHtq4caPKy8vjl22dlCorK1NJSYl69uyp33//fbdaZc4888y9TkpFo1FdffXVKi0t1U033bRXt/VnOTk56tu3r2bMmBGv6DJNU++99546d+6sdu3aSar+fIRCIW3YsEGtW7dWdna2fvjhh1qJ5cMPP1SHDh3Uvn17lZSUxP/FWov+3AK3NcMwdOKJJ+qzzz5TRUVF/PI
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 1200x700 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"name": "stdout",
|
|||
|
|
"output_type": "stream",
|
|||
|
|
"text": [
|
|||
|
|
"\n",
|
|||
|
|
"所有指标的分析图表已生成。\n"
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"\n",
|
|||
|
|
"from turtle import down\n",
|
|||
|
|
"from src.analysis.result_analyzer import ResultAnalyzer\n",
|
|||
|
|
"# 导入所有必要的模块\n",
|
|||
|
|
"from src.data_manager import DataManager\n",
|
|||
|
|
"from src.backtest_engine import BacktestEngine\n",
|
|||
|
|
"from src.indicators.indicator_list import INDICATOR_LIST\n",
|
|||
|
|
"from src.indicators.indicators import RSI, HistoricalRange, NormalizedATR, RateOfChange, StochasticOscillator\n",
|
|||
|
|
"from src.strategies.OpenTwoFactorStrategy import SimpleLimitBuyStrategyLong, SimpleLimitBuyStrategyShort, SimpleLimitBuyStrategy\n",
|
|||
|
|
"\n",
|
|||
|
|
"\n",
|
|||
|
|
"# --- 配置参数 ---\n",
|
|||
|
|
"# 获取当前脚本所在目录，假设数据文件在项目根目录下的 data 文件夹内\n",
|
|||
|
|
"# data_file_path = '/mnt/d/PyProject/NewQuant/data/data/SHFE_rb2510/SHFE_rb2510_min60.csv'\n",
|
|||
|
|
"# data_file_path = \"/mnt/d/PyProject/NewQuant/data/data/KQ_m@CZCE_MA/KQ_m@CZCE_MA_min60.csv\"\n",
|
|||
|
|
"data_file_path = \"/mnt/d/PyProject/NewQuant/data/data/KQ_m@SHFE_rb/KQ_m@SHFE_rb_min60.csv\"\n",
|
|||
|
|
"\n",
|
|||
|
|
"initial_capital = 100000.0\n",
|
|||
|
|
"slippage_rate = 0.000 # 假设每笔交易0.1%的滑点\n",
|
|||
|
|
"commission_rate = 0.0001 # 假设每笔交易0.02%的佣金\n",
|
|||
|
|
"\n",
|
|||
|
|
"global_config = {\n",
|
|||
|
|
" 'symbol': 'KQ_m@SHFE_rb',\n",
|
|||
|
|
"}\n",
|
|||
|
|
"\n",
|
|||
|
|
"# Short 可用\n",
|
|||
|
|
"strategy_parameters = {\n",
|
|||
|
|
" # 'symbol': \"SHFE_rb2501\", # 根据您的数据文件中的品种名称调整\n",
|
|||
|
|
" 'trade_volume': 1,\n",
|
|||
|
|
" # 'range_factor': 1.8, # 示例值，需要通过网格搜索优化\n",
|
|||
|
|
" # 'profit_factor': 5.0, # 示例值\n",
|
|||
|
|
" 'range_factor': 0.2, # 示例值，需要通过网格搜索优化\n",
|
|||
|
|
" 'profit_factor': 3.8, # 示例值\n",
|
|||
|
|
" # 'range_factor_l': 1.8, # 示例值，需要通过网格搜索优化\n",
|
|||
|
|
" # 'profit_factor_l': 2.8, # 示例值\n",
|
|||
|
|
" # 'range_factor_s': 1.6, # 示例值，需要通过网格搜索优化\n",
|
|||
|
|
" # 'profit_factor_s': 2.1, # 示例值\n",
|
|||
|
|
" 'max_position': 10,\n",
|
|||
|
|
" 'enable_log': False,\n",
|
|||
|
|
" 'stop_loss_points': 20,\n",
|
|||
|
|
" 'use_indicator': True,\n",
|
|||
|
|
" # 'indicator': RSI(15, 52, 66),\n",
|
|||
|
|
" 'indicator': NormalizedATR(window=5, down_bound=0.62, up_bound=0.76),\n",
|
|||
|
|
" # 'indicator_l': HistoricalRange(21, 10, 25),\n",
|
|||
|
|
" # 'indicator_s': RSI(5, 20, 60),\n",
|
|||
|
|
"}\n",
|
|||
|
|
"start_time = datetime(2022, 1, 1)\n",
|
|||
|
|
"end_time = datetime(2024, 6, 1)\n",
|
|||
|
|
"\n",
|
|||
|
|
"start_time = datetime(2024, 6, 1)\n",
|
|||
|
|
"end_time = datetime(2025, 6, 1)\n",
|
|||
|
|
"\n",
|
|||
|
|
"\n",
|
|||
|
|
"# --- 1. 初始化数据管理器 ---\n",
|
|||
|
|
"print(\"初始化数据管理器...\")\n",
|
|||
|
|
"data_manager = DataManager(file_path=data_file_path, symbol=global_config['symbol'], start_time=start_time, end_time=end_time)\n",
|
|||
|
|
"# 确保 DataManager 能够重置以进行多次回测\n",
|
|||
|
|
"# data_manager.reset() # 首次运行不需要重置\n",
|
|||
|
|
"\n",
|
|||
|
|
"# --- 2. 初始化回测引擎并运行 ---\n",
|
|||
|
|
"print(\"\\n初始化回测引擎...\")\n",
|
|||
|
|
"engine = BacktestEngine(\n",
|
|||
|
|
" data_manager=data_manager,\n",
|
|||
|
|
" strategy_class=SimpleLimitBuyStrategyShort,\n",
|
|||
|
|
" # current_segment_symbol=strategy_parameters['symbol'],\n",
|
|||
|
|
" strategy_params=strategy_parameters,\n",
|
|||
|
|
" initial_capital=initial_capital,\n",
|
|||
|
|
" slippage_rate=slippage_rate,\n",
|
|||
|
|
" commission_rate=commission_rate,\n",
|
|||
|
|
" roll_over_mode=True,\n",
|
|||
|
|
" start_time=start_time,\n",
|
|||
|
|
" end_time=end_time,\n",
|
|||
|
|
" indicators=INDICATOR_LIST\n",
|
|||
|
|
")\n",
|
|||
|
|
"\n",
|
|||
|
|
"print(\"\\n开始运行回测...\")\n",
|
|||
|
|
"engine.run_backtest()\n",
|
|||
|
|
"print(\"\\n回测运行完毕。\")\n",
|
|||
|
|
"\n",
|
|||
|
|
"# --- 3. 获取回测结果 ---\n",
|
|||
|
|
"results = engine.get_backtest_results()\n",
|
|||
|
|
"portfolio_snapshots = results[\"portfolio_snapshots\"]\n",
|
|||
|
|
"trade_history = results[\"trade_history\"]\n",
|
|||
|
|
"initial_capital_result = results[\"initial_capital\"]\n",
|
|||
|
|
"bars = results[\"all_bars\"]\n",
|
|||
|
|
"\n",
|
|||
|
|
"# --- 4. 结果分析与可视化 ---\n",
|
|||
|
|
"if portfolio_snapshots:\n",
|
|||
|
|
" analyzer = ResultAnalyzer(portfolio_snapshots, trade_history, bars, initial_capital_result, INDICATOR_LIST)\n",
|
|||
|
|
"\n",
|
|||
|
|
" analyzer.generate_report()\n",
|
|||
|
|
" analyzer.plot_performance()\n",
|
|||
|
|
" metrics = analyzer.calculate_all_metrics()\n",
|
|||
|
|
" print(metrics)\n",
|
|||
|
|
"\n",
|
|||
|
|
" analyzer.analyze_indicators()\n",
|
|||
|
|
"else:\n",
|
|||
|
|
" print(\"\\n没有生成投资组合快照，无法进行结果分析。\")\n",
|
|||
|
|
"\n",
|
|||
|
|
"# --- 4. 结果分析与可视化 (待实现) ---\n",
|
|||
|
|
"# if portfolio_snapshots:\n",
|
|||
|
|
"# analyzer = ResultAnalyzer(portfolio_snapshots, trade_history, initial_capital_result)\n",
|
|||
|
|
"# metrics = analyzer.calculate_all_metrics()\n",
|
|||
|
|
"# print(\"\\n--- 绩效指标 ---\")\n",
|
|||
|
|
"# for key, value in metrics.items():\n",
|
|||
|
|
"# print(f\" {key}: {value:.4f}\")\n",
|
|||
|
|
"#\n",
|
|||
|
|
"# print(\"\\n--- 绘制绩效图表 ---\")\n",
|
|||
|
|
"# analyzer.plot_performance()\n",
|
|||
|
|
"# else:\n",
|
|||
|
|
"# print(\"\\n没有生成投资组合快照，无法进行结果分析。\")\n",
|
|||
|
|
"\n"
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"metadata": {
|
|||
|
|
"kernelspec": {
|
|||
|
|
"display_name": "quant",
|
|||
|
|
"language": "python",
|
|||
|
|
"name": "python3"
|
|||
|
|
},
|
|||
|
|
"language_info": {
|
|||
|
|
"codemirror_mode": {
|
|||
|
|
"name": "ipython",
|
|||
|
|
"version": 3
|
|||
|
|
},
|
|||
|
|
"file_extension": ".py",
|
|||
|
|
"mimetype": "text/x-python",
|
|||
|
|
"name": "python",
|
|||
|
|
"nbconvert_exporter": "python",
|
|||
|
|
"pygments_lexer": "ipython3",
|
|||
|
|
"version": "3.12.11"
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
"nbformat": 4,
|
|||
|
|
"nbformat_minor": 5
|
|||
|
|
}
|