diff --git a/docs/indexes/datasets_catalog.json b/docs/indexes/datasets_catalog.json
index 28154341..31d817a8 100644
--- a/docs/indexes/datasets_catalog.json
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@@ -1,7 +1,7 @@
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@@ -1316,6 +1316,86 @@
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index eaa7b6bc..735f47a8 100644
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@@ -1,7 +1,7 @@
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@@ -140,7 +140,7 @@
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@@ -180,7 +180,7 @@
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@@ -220,7 +220,7 @@
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@@ -250,7 +250,7 @@
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@@ -260,7 +260,7 @@
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@@ -270,7 +270,7 @@
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@@ -280,7 +280,7 @@
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@@ -380,7 +380,7 @@
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@@ -405,7 +405,7 @@
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@@ -431,7 +431,7 @@
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diff --git a/docs/indexes/reports.json b/docs/indexes/reports.json
index aff5bc24..6eaf565e 100644
--- a/docs/indexes/reports.json
+++ b/docs/indexes/reports.json
@@ -1,8 +1,8 @@
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@@ -28,7 +28,7 @@
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@@ -44,7 +44,7 @@
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@@ -77,7 +77,7 @@
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@@ -250,7 +250,7 @@
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@@ -280,7 +280,7 @@
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@@ -380,7 +380,7 @@
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@@ -405,7 +405,7 @@
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@@ -3251,6 +3251,126 @@
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+      "title": "回测数据汇总",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2021-01-01",
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+      "pathrefs": [],
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+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/data-integrity.md",
+      "title": "数据完整性报告",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2026-06-30",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:14:45+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/backtest_report.md",
+      "title": "回测数据汇总",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2021-01-01",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:27:44+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/data-integrity.md",
+      "title": "数据完整性报告",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2026-06-30",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:27:44+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/backtest_report.md",
+      "title": "回测数据汇总",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2021-01-01",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:29:20+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/data-integrity.md",
+      "title": "数据完整性报告",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2026-06-30",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:29:20+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/backtest_report.md",
+      "title": "回测数据汇总",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2021-01-01",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:38:34+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/data-integrity.md",
+      "title": "数据完整性报告",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2026-06-30",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:38:34+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/backtest_report.md",
+      "title": "回测数据汇总",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2021-01-01",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T18:50:06+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/data-integrity.md",
+      "title": "数据完整性报告",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2026-06-30",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T18:50:06+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/backtest_report.md",
+      "title": "回测数据汇总",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2021-01-01",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T19:37:11+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/data-integrity.md",
+      "title": "数据完整性报告",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2026-06-30",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T19:37:11+00:00"
+    },
     {
       "path": "strategies/etf_factor_rotation/reports/2026-05-07-factor-vs-dynamic-rebalance-attribution.md",
       "title": "ETF 因子轮动 vs 动态再平衡深度归因报告",
@@ -3377,7 +3497,7 @@
         "joinquant_data/JQ_场内基金数据.md",
         "repo/AGENTS.md"
       ],
-      "updated_at": "2026-06-04T17:14:06+00:00"
+      "updated_at": "2026-06-16T19:45:44+00:00"
     },
     {
       "path": "strategies/etf_factor_rotation/reports/design/2026-05-17-cash-utilization-optimization-plan.md",
@@ -3446,7 +3566,7 @@
         "joinquant_data/JQ_场内基金数据.md",
         "strategy_reports(strategy=etf_factor_rotation)/testing/测试方案设计文档.md"
       ],
-      "updated_at": "2026-05-28T07:57:25+00:00"
+      "updated_at": "2026-06-16T19:45:44+00:00"
     },
     {
       "path": "strategies/etf_factor_rotation/reports/design/ETF轮动策略方案说明书.md",
@@ -4306,7 +4426,7 @@
         "backtest_report_dir(strategy=etf_factor_rotation, run_id=20260508-0027-btb2784ac85d31dd228ec8f7e4e36ce212)/strategy-analysis.md",
         "backtest_report_dir(strategy=etf_factor_rotation, run_id=20260508-0027-btb2784ac85d31dd228ec8f7e4e36ce212)/performance-analysis.md"
       ],
-      "updated_at": "2026-05-28T07:57:26+00:00"
+      "updated_at": "2026-06-16T19:45:44+00:00"
     },
     {
       "path": "strategies/etf_factor_rotation/test_batches/20260508-hard-ma-scan/report/etf-ma-parameter-attribution.md",
@@ -4382,7 +4502,7 @@
         "backtest_report_dir(strategy=etf_factor_rotation, run_id=20260508-0027-btb2784ac85d31dd228ec8f7e4e36ce212)/strategy-analysis.md",
         "backtest_report_dir(strategy=etf_factor_rotation, run_id=20260508-0027-btb2784ac85d31dd228ec8f7e4e36ce212)/performance-analysis.md"
       ],
-      "updated_at": "2026-05-28T07:57:26+00:00"
+      "updated_at": "2026-06-16T19:45:44+00:00"
     },
     {
       "path": "strategies/etf_factor_rotation/test_batches/20260514-etf-ma-mixed-confirmation/report/param-scan-report.md",
diff --git a/docs/indexes/reports.md b/docs/indexes/reports.md
index 02213aac..df1c48dd 100644
--- a/docs/indexes/reports.md
+++ b/docs/indexes/reports.md
@@ -298,6 +298,18 @@
 | backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260526-2330-btfefcb2db54c231df54d773457629bda1/report/data-integrity.md` | 0 |
 | backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260526-2333-bt36f34fb52505979aa53d97ef4949fc60/report/backtest_report.md` | 0 |
 | backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260526-2333-bt36f34fb52505979aa53d97ef4949fc60/report/data-integrity.md` | 0 |
+| backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/backtest_report.md` | 0 |
+| backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/data-integrity.md` | 0 |
+| backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/backtest_report.md` | 0 |
+| backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/data-integrity.md` | 0 |
+| backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/backtest_report.md` | 0 |
+| backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/data-integrity.md` | 0 |
+| backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/backtest_report.md` | 0 |
+| backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/data-integrity.md` | 0 |
+| backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/backtest_report.md` | 0 |
+| backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/data-integrity.md` | 0 |
+| backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/backtest_report.md` | 0 |
+| backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/data-integrity.md` | 0 |
 | report | etf_factor_rotation | ETF 因子轮动 vs 动态再平衡深度归因报告 | `strategies/etf_factor_rotation/reports/2026-05-07-factor-vs-dynamic-rebalance-attribution.md` | 16 |
 | report | etf_factor_rotation | 深度归因分析报告 | `strategies/etf_factor_rotation/reports/2026-05-14-deep-attribution.md` | 7 |
 | report | etf_factor_rotation | 拥挤度惩罚 AB 验证 — 最终决策 | `strategies/etf_factor_rotation/reports/2026-05-15-crowd-penalty-ab-decision.md` | 8 |
diff --git a/docs/indexes/reports_catalog.json b/docs/indexes/reports_catalog.json
index 35f578e1..ddb6e6d8 100644
--- a/docs/indexes/reports_catalog.json
+++ b/docs/indexes/reports_catalog.json
@@ -1,8 +1,8 @@
 {
   "schema_version": 1,
   "catalog_type": "reports",
-  "generated_at": "2026-06-16T17:54:56+00:00",
-  "count": 381,
+  "generated_at": "2026-06-30T21:29:19+00:00",
+  "count": 393,
   "reports": [
     {
       "path": "strategies/etf_dynamic_rebalance/backtest_runs/20260504_1/report/attribution-analysis.md",
@@ -2761,6 +2761,126 @@
       "pathrefs": [],
       "updated_at": "2026-05-28T07:57:25+00:00"
     },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/backtest_report.md",
+      "title": "回测数据汇总",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2021-01-01",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:14:45+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/data-integrity.md",
+      "title": "数据完整性报告",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2026-06-30",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:14:45+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/backtest_report.md",
+      "title": "回测数据汇总",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2021-01-01",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:27:44+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/data-integrity.md",
+      "title": "数据完整性报告",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2026-06-30",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:27:44+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/backtest_report.md",
+      "title": "回测数据汇总",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2021-01-01",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:29:20+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/data-integrity.md",
+      "title": "数据完整性报告",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2026-06-30",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:29:20+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/backtest_report.md",
+      "title": "回测数据汇总",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2021-01-01",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:38:34+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/data-integrity.md",
+      "title": "数据完整性报告",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2026-06-30",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T16:38:34+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/backtest_report.md",
+      "title": "回测数据汇总",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2021-01-01",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T18:50:06+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/data-integrity.md",
+      "title": "数据完整性报告",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2026-06-30",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T18:50:06+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/backtest_report.md",
+      "title": "回测数据汇总",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2021-01-01",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T19:37:11+00:00"
+    },
+    {
+      "path": "strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/data-integrity.md",
+      "title": "数据完整性报告",
+      "category": "backtest_run",
+      "strategy": "etf_factor_rotation",
+      "date": "2026-06-30",
+      "tags": [],
+      "pathrefs": [],
+      "updated_at": "2026-06-30T19:37:11+00:00"
+    },
     {
       "path": "strategies/etf_factor_rotation/reports/2026-05-07-factor-vs-dynamic-rebalance-attribution.md",
       "title": "ETF 因子轮动 vs 动态再平衡深度归因报告",
@@ -2887,7 +3007,7 @@
         "joinquant_data/JQ_场内基金数据.md",
         "repo/AGENTS.md"
       ],
-      "updated_at": "2026-06-04T17:14:06+00:00"
+      "updated_at": "2026-06-16T19:45:44+00:00"
     },
     {
       "path": "strategies/etf_factor_rotation/reports/design/2026-05-17-cash-utilization-optimization-plan.md",
@@ -2956,7 +3076,7 @@
         "joinquant_data/JQ_场内基金数据.md",
         "strategy_reports(strategy=etf_factor_rotation)/testing/测试方案设计文档.md"
       ],
-      "updated_at": "2026-05-28T07:57:25+00:00"
+      "updated_at": "2026-06-16T19:45:44+00:00"
     },
     {
       "path": "strategies/etf_factor_rotation/reports/design/ETF轮动策略方案说明书.md",
@@ -3816,7 +3936,7 @@
         "backtest_report_dir(strategy=etf_factor_rotation, run_id=20260508-0027-btb2784ac85d31dd228ec8f7e4e36ce212)/strategy-analysis.md",
         "backtest_report_dir(strategy=etf_factor_rotation, run_id=20260508-0027-btb2784ac85d31dd228ec8f7e4e36ce212)/performance-analysis.md"
       ],
-      "updated_at": "2026-05-28T07:57:26+00:00"
+      "updated_at": "2026-06-16T19:45:44+00:00"
     },
     {
       "path": "strategies/etf_factor_rotation/test_batches/20260508-hard-ma-scan/report/etf-ma-parameter-attribution.md",
@@ -3892,7 +4012,7 @@
         "backtest_report_dir(strategy=etf_factor_rotation, run_id=20260508-0027-btb2784ac85d31dd228ec8f7e4e36ce212)/strategy-analysis.md",
         "backtest_report_dir(strategy=etf_factor_rotation, run_id=20260508-0027-btb2784ac85d31dd228ec8f7e4e36ce212)/performance-analysis.md"
       ],
-      "updated_at": "2026-05-28T07:57:26+00:00"
+      "updated_at": "2026-06-16T19:45:44+00:00"
     },
     {
       "path": "strategies/etf_factor_rotation/test_batches/20260514-etf-ma-mixed-confirmation/report/param-scan-report.md",
diff --git a/docs/indexes/reports_catalog.md b/docs/indexes/reports_catalog.md
index 90e9f48f..66b4a653 100644
--- a/docs/indexes/reports_catalog.md
+++ b/docs/indexes/reports_catalog.md
@@ -261,6 +261,18 @@
 | backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260526-2330-btfefcb2db54c231df54d773457629bda1/report/data-integrity.md` | 0 |
 | backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260526-2333-bt36f34fb52505979aa53d97ef4949fc60/report/backtest_report.md` | 0 |
 | backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260526-2333-bt36f34fb52505979aa53d97ef4949fc60/report/data-integrity.md` | 0 |
+| backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/backtest_report.md` | 0 |
+| backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/data-integrity.md` | 0 |
+| backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/backtest_report.md` | 0 |
+| backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/data-integrity.md` | 0 |
+| backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/backtest_report.md` | 0 |
+| backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/data-integrity.md` | 0 |
+| backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/backtest_report.md` | 0 |
+| backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/data-integrity.md` | 0 |
+| backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/backtest_report.md` | 0 |
+| backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/data-integrity.md` | 0 |
+| backtest_run | etf_factor_rotation | 回测数据汇总 | `strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/backtest_report.md` | 0 |
+| backtest_run | etf_factor_rotation | 数据完整性报告 | `strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/data-integrity.md` | 0 |
 | report | etf_factor_rotation | ETF 因子轮动 vs 动态再平衡深度归因报告 | `strategies/etf_factor_rotation/reports/2026-05-07-factor-vs-dynamic-rebalance-attribution.md` | 16 |
 | report | etf_factor_rotation | 深度归因分析报告 | `strategies/etf_factor_rotation/reports/2026-05-14-deep-attribution.md` | 7 |
 | report | etf_factor_rotation | 拥挤度惩罚 AB 验证 — 最终决策 | `strategies/etf_factor_rotation/reports/2026-05-15-crowd-penalty-ab-decision.md` | 8 |
diff --git a/docs/indexes/variants_catalog.json b/docs/indexes/variants_catalog.json
index f2f52c8e..1fcca1a5 100644
--- a/docs/indexes/variants_catalog.json
+++ b/docs/indexes/variants_catalog.json
@@ -1,6 +1,37 @@
 {
   "schema_version": 1,
-  "generated_at": "2026-06-16T17:54:56+00:00",
-  "count": 0,
-  "variants": []
+  "generated_at": "2026-06-30T21:29:19+00:00",
+  "count": 3,
+  "variants": [
+    {
+      "strategy": "etf_factor_rotation",
+      "variant_id": "baseline_original",
+      "variant_type": "structural",
+      "status": "candidate",
+      "merge_status": "not_merged",
+      "description": "原始正式基线代码：本次实验对照组，来源为本分支起点 origin/main 的正式策略脚本。",
+      "updated_at": "2026-06-30T20:21:17+00:00",
+      "detail": "baseline_original.json"
+    },
+    {
+      "strategy": "etf_factor_rotation",
+      "variant_id": "logic3_code_variant",
+      "variant_type": "structural",
+      "status": "candidate",
+      "merge_status": "not_merged",
+      "description": "旧实盘近似代码变体：周一标记信号，下一交易日开盘生成并执行。",
+      "updated_at": "2026-06-30T16:23:28+00:00",
+      "detail": "logic3_code_variant.json"
+    },
+    {
+      "strategy": "etf_factor_rotation",
+      "variant_id": "weekend_close_signal_next_open_variant",
+      "variant_type": "structural",
+      "status": "candidate",
+      "merge_status": "not_merged",
+      "description": "新实盘对齐代码变体：本周最后交易日收盘生成信号，次交易日开盘执行缓存计划。",
+      "updated_at": "2026-06-30T16:23:28+00:00",
+      "detail": "weekend_close_signal_next_open_variant.json"
+    }
+  ]
 }
\ No newline at end of file
diff --git a/research_datasets/catalog.json b/research_datasets/catalog.json
index e844bad2..b3454267 100644
--- a/research_datasets/catalog.json
+++ b/research_datasets/catalog.json
@@ -1312,6 +1312,86 @@
     "owner": "research-platform",
     "lifecycle": "active"
   },
+  {
+    "dataset_id": "etf_factor_rotation_backtest_runs",
+    "snapshot_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+    "fingerprint": "sha256:4eabaa7858e197ea1d9e60e733291c4c5c23b8822ba65db20f3dba4dd9992f11",
+    "row_count": 1289,
+    "date_range": [
+      "2021-01-04",
+      "2026-04-30"
+    ],
+    "source_kind": "joinquant_backtest_run",
+    "owner": "research-platform",
+    "lifecycle": "active"
+  },
+  {
+    "dataset_id": "etf_factor_rotation_backtest_runs",
+    "snapshot_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+    "fingerprint": "sha256:2a9db19d253f131c38dff3e91f28fbdd1251f19f1a9fc3c0f11ac0f1333c4b3a",
+    "row_count": 1289,
+    "date_range": [
+      "2021-01-04",
+      "2026-04-30"
+    ],
+    "source_kind": "joinquant_backtest_run",
+    "owner": "research-platform",
+    "lifecycle": "active"
+  },
+  {
+    "dataset_id": "etf_factor_rotation_backtest_runs",
+    "snapshot_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+    "fingerprint": "sha256:cd9d4301f3c996c294a5f0b66962a6c053d831ef2a0ddd1914746ad9be1105c5",
+    "row_count": 1289,
+    "date_range": [
+      "2021-01-04",
+      "2026-04-30"
+    ],
+    "source_kind": "joinquant_backtest_run",
+    "owner": "research-platform",
+    "lifecycle": "superseded",
+    "superseded_by": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+    "superseded_reason": "initial no-trade run; s04 is the active reproducible weekend-close variant evidence"
+  },
+  {
+    "dataset_id": "etf_factor_rotation_backtest_runs",
+    "snapshot_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+    "fingerprint": "sha256:6c349f1a89a62304482c4289e10433ad831b4ad6ffc42bb3326ced70e785ac96",
+    "row_count": 1289,
+    "date_range": [
+      "2021-01-04",
+      "2026-04-30"
+    ],
+    "source_kind": "joinquant_backtest_run",
+    "owner": "research-platform",
+    "lifecycle": "active"
+  },
+  {
+    "dataset_id": "etf_factor_rotation_backtest_runs",
+    "snapshot_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+    "fingerprint": "sha256:cc0f052868017cb487d7811ee5e4de461f0af77b9459546ccc69be8a3c5c82ca",
+    "row_count": 1289,
+    "date_range": [
+      "2021-01-04",
+      "2026-04-30"
+    ],
+    "source_kind": "joinquant_backtest_run",
+    "owner": "research-platform",
+    "lifecycle": "active"
+  },
+  {
+    "dataset_id": "etf_factor_rotation_backtest_runs",
+    "snapshot_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+    "fingerprint": "sha256:a3006b9f096754d0b2876f2138ccba09d0a23e63cffc91a6c3214b73361e0bbb",
+    "row_count": 1289,
+    "date_range": [
+      "2021-01-04",
+      "2026-04-30"
+    ],
+    "source_kind": "joinquant_backtest_run",
+    "owner": "research-platform",
+    "lifecycle": "active"
+  },
   {
     "dataset_id": "etf_factor_rotation_baseline_audit",
     "snapshot_id": "2026-05-17T17-36-27Z_56361cf8a32e",
diff --git a/research_datasets/catalog.md b/research_datasets/catalog.md
index 43ae6b44..13c66fd5 100644
--- a/research_datasets/catalog.md
+++ b/research_datasets/catalog.md
@@ -103,6 +103,12 @@
 | etf_factor_rotation_backtest_runs | 20260526-2327-bta35e64a2599b009eba3c6b8219d61e22 | joinquant_backtest_run | research-platform | active | 1289 | 2021-01-04 ~ 2026-04-30 |
 | etf_factor_rotation_backtest_runs | 20260526-2330-btfefcb2db54c231df54d773457629bda1 | joinquant_backtest_run | research-platform | active | 1289 | 2021-01-04 ~ 2026-04-30 |
 | etf_factor_rotation_backtest_runs | 20260526-2333-bt36f34fb52505979aa53d97ef4949fc60 | joinquant_backtest_run | research-platform | active | 1289 | 2021-01-04 ~ 2026-04-30 |
+| etf_factor_rotation_backtest_runs | 20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0 | joinquant_backtest_run | research-platform | active | 1289 | 2021-01-04 ~ 2026-04-30 |
+| etf_factor_rotation_backtest_runs | 20260701-0025-bt0d4e21c752867aa36b89ee13d7540352 | joinquant_backtest_run | research-platform | active | 1289 | 2021-01-04 ~ 2026-04-30 |
+| etf_factor_rotation_backtest_runs | 20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5 | joinquant_backtest_run | research-platform | superseded | 1289 | 2021-01-04 ~ 2026-04-30 |
+| etf_factor_rotation_backtest_runs | 20260701-0032-btdcc6252aadef8bb09592538da4dde54c | joinquant_backtest_run | research-platform | active | 1289 | 2021-01-04 ~ 2026-04-30 |
+| etf_factor_rotation_backtest_runs | 20260701-0246-bt526c312fb836d6e07826ce170809486a | joinquant_backtest_run | research-platform | active | 1289 | 2021-01-04 ~ 2026-04-30 |
+| etf_factor_rotation_backtest_runs | 20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d | joinquant_backtest_run | research-platform | active | 1289 | 2021-01-04 ~ 2026-04-30 |
 | etf_factor_rotation_baseline_audit | 2026-05-17T17-36-27Z_56361cf8a32e | joinquant_audit_log_jsonl | research-platform | active | 272 | 2021-01-01 ~ 2026-04-30 |
 | ma_crossover_backtest_runs | 20260505-1939-bt48ef4a644906d1ada69ba04637aa4bb6 | joinquant_backtest_run | research-platform | active | 56 | 2026-01-05 ~ 2026-03-31 |
 | ma_crossover_backtest_runs | 20260505-1947-bt9d35a958df27c3d1c9534f43644cdd46 | joinquant_backtest_run | research-platform | active | 56 | 2026-01-05 ~ 2026-03-31 |
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/README.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/README.md
new file mode 100644
index 00000000..25dd9160
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/README.md
@@ -0,0 +1,9 @@
+# etf_factor_rotation_backtest_runs
+
+- **snapshot**: `20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0`
+- **run_id**: `20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0`
+- **fingerprint**: `sha256:4eabaa7858e197ea1d9e60e733291c4c5c23b8822ba65db20f3dba4dd9992f11`
+- **日期范围**: `2021-01-04 ~ 2026-04-30`
+- **审计日志行数**: `1090`
+
+原始文件压缩保存在 `raw/*.gz`；常用轻量索引见 `views/`；程序读取优先使用 `data/data.parquet`。
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/data/audit_events.parquet b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/data/audit_events.parquet
new file mode 100644
index 00000000..04532692
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/data/audit_events.parquet
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:174cac57b6f902f03592c19ef48112bdb9cc6e909ff2a89b9c95dd6d3ceaa69c
+size 94149
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/data/data.parquet b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/data/data.parquet
new file mode 100644
index 00000000..730370e9
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/data/data.parquet
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b89820ab491c7834bbb1d07484f7b0118b83da7bc8b371ea4c4a50d62bb42c44
+size 16228
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/dataset.json b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/dataset.json
new file mode 100644
index 00000000..18162007
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/dataset.json
@@ -0,0 +1,171 @@
+{
+  "schema_version": 1,
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "fingerprint": "sha256:4eabaa7858e197ea1d9e60e733291c4c5c23b8822ba65db20f3dba4dd9992f11",
+  "created_at": "2026-06-30T16:14:49+00:00",
+  "owner": "research-platform",
+  "created_by": "research-platform",
+  "lifecycle": "active",
+  "source": {
+    "kind": "joinquant_backtest_run",
+    "path": "D:/My Project/Quant Trading/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0"
+  },
+  "storage": {
+    "canonical": "parquet",
+    "compression": "zstd",
+    "raw": "json.gz/jsonl.gz/md.gz"
+  },
+  "row_count": 1289,
+  "date_range": [
+    "2021-01-04",
+    "2026-04-30"
+  ],
+  "run_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "partial": false,
+  "missing_required_files": [],
+  "summary_metrics": {
+    "策略收益": "127.12%",
+    "策略年化收益": "17.25%",
+    "基准收益": "-7.75%",
+    "超额收益": "146.21%",
+    "最大回撤": "7.60%",
+    "最大回撤区间": "2021-11-22,2022-01-28",
+    "阿尔法": "0.140",
+    "贝塔": "0.139",
+    "夏普比率": "1.582",
+    "索提诺比率": "2.346",
+    "信息比率": "1.084",
+    "策略波动率": "0.084",
+    "基准波动率": "0.179",
+    "胜率": "0.740",
+    "盈亏比": "4.966",
+    "日胜率": "0.542",
+    "盈利次数": 142,
+    "亏损次数": 50
+  },
+  "source_metadata": {
+    "strategy_name": "etf_factor_rotation",
+    "strategy_file": "",
+    "strategy_dir": "",
+    "start_date_requested": "",
+    "start_date_effective": "2021-01-01",
+    "end_date_requested": "",
+    "end_date_effective": "2026-04-30",
+    "capital": 100000,
+    "backtest_id": "8d074a3098c6308f791ea33d8806d6f0",
+    "backtest_url": "",
+    "generated_at": "2026-07-01T00:14:34",
+    "extraction_method": "joinquant_research_get_backtest",
+    "primary_extraction_method": "joinquant_research_get_backtest",
+    "fallback_extraction_method": "",
+    "research_export_path": "jq_auto_exports/research_backtest_8d074a3098c6308f791ea33d8806d6f0.json",
+    "research_downloaded": true,
+    "detail_api_used": true,
+    "frequency": "1d",
+    "py_version": "Python3",
+    "internal_backtest_id": "234573daf021757752090358c356f903",
+    "audit_token": "etf_factor_rotation-s01-baseline-original-20260701001028-3e0b4107",
+    "audit_path": "jq_auto_audit/etf_factor_rotation-s01-baseline-original-20260701001028-3e0b4107.jsonl"
+  },
+  "audit_line_count": 1090,
+  "audit_date_range": [
+    "2021-01-01",
+    "2026-04-30"
+  ],
+  "audit_event_counts": {
+    "rebalance_order": 816,
+    "rebalance_signals": 272,
+    "run_end": 1,
+    "run_start": 1
+  },
+  "etf_pool": [
+    "159819.XSHE",
+    "513100.XSHG",
+    "518880.XSHG"
+  ],
+  "report_files": [
+    "backtest_report.md",
+    "data-integrity.md"
+  ],
+  "files": {
+    "raw": "raw/source.json.gz",
+    "profile_json": "views/profile.json",
+    "audit_events": "data/audit_events.parquet",
+    "daily_returns": "data/data.parquet",
+    "canonical": "data/data.parquet",
+    "sample": "views/sample.csv",
+    "api_export_source": "raw/api_export.json.gz",
+    "detail_api_export_source": "raw/detail_api_export.json.gz",
+    "summary_metrics": "raw/summary_metrics.json.gz",
+    "audit_log_source": "raw/audit_log.jsonl.gz",
+    "daily_returns_source": "raw/daily_returns.md.gz",
+    "positioninfo_source": "raw/positioninfo.md.gz",
+    "transactioninfo_source": "raw/transactioninfo.md.gz",
+    "balances_source": "raw/balances.md.gz",
+    "period_risks_source": "raw/period_risks.md.gz",
+    "logs_source": "raw/logs.md.gz"
+  },
+  "raw_file_integrity": {
+    "api_export.json": {
+      "dataset_file": "raw/api_export.json.gz",
+      "original_sha256": "f7a967d3b67c2c52e049aeeaa3dafc0920f3008f0cd495e2ad5cb33eb4ae4221",
+      "compressed_sha256": "7c8fa08bc9602a269a706e74c2d6561377418719ac90c7ec2e2572ce59f5af34",
+      "original_bytes": 3356598
+    },
+    "detail_api_export.json": {
+      "dataset_file": "raw/detail_api_export.json.gz",
+      "original_sha256": "82f066ba6c46bf633ff5487715febaee63804667bac0332d4d7da0d0805df0bf",
+      "compressed_sha256": "d96601104c203561628d12a21f6c79dc08ff11f2833fb7d3e3783ab25b6f2488",
+      "original_bytes": 4350900
+    },
+    "summary_metrics.json": {
+      "dataset_file": "raw/summary_metrics.json.gz",
+      "original_sha256": "74e9b525f50b3d66d1fdd881ac3cff7fa27b499260ba211f5392035121d16ea2",
+      "compressed_sha256": "b57ad5f2a7632af8588e874104c77b85537c143cbd613f9e7c3035081d7764a1",
+      "original_bytes": 520
+    },
+    "tabs_raw/audit_log.jsonl": {
+      "dataset_file": "raw/audit_log.jsonl.gz",
+      "original_sha256": "4b9c3166531201de33fccec8dce07ad33e80f4f70420cc15bb7aa2c9c56620ff",
+      "compressed_sha256": "424c1b1d9800c7a7c50d489ca18d8325b34a4bcd6013e8c8c978649c56fa0a3c",
+      "original_bytes": 1318032
+    },
+    "tabs_raw/daily_returns.md": {
+      "dataset_file": "raw/daily_returns.md.gz",
+      "original_sha256": "73afb8b1c7783773a152041e2d7fd3a96ff1fec6cfc3bc7a8758f63c08073970",
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+      "original_bytes": 92875
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+    "tabs_raw/positioninfo.md": {
+      "dataset_file": "raw/positioninfo.md.gz",
+      "original_sha256": "e2f334231893babfb1b91d1076f5f407d541713c23a841a9443216e1a6057e8e",
+      "compressed_sha256": "3245ae8b76e39d33c4d89e7014de3980458d6da40764819dfb754ee08bc73f74",
+      "original_bytes": 379897
+    },
+    "tabs_raw/transactioninfo.md": {
+      "dataset_file": "raw/transactioninfo.md.gz",
+      "original_sha256": "ec6ada5cd42a5306b4b1f739dce3be3df953f16ffc40a6262dc3c6579ac1809b",
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+    "tabs_raw/balances.md": {
+      "dataset_file": "raw/balances.md.gz",
+      "original_sha256": "5d4c2b9f53deda2fbdd7e5f7c1cd0f8f9e13cc5b3540fea21d12e263a7937d74",
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+      "original_bytes": 90889
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+    "tabs_raw/period_risks.md": {
+      "dataset_file": "raw/period_risks.md.gz",
+      "original_sha256": "00b68a33695b80da0837551ca441973d343584a66a44c0a43844f7412ddc7036",
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+      "original_bytes": 62839
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+    "tabs_raw/logs.md": {
+      "dataset_file": "raw/logs.md.gz",
+      "original_sha256": "d811c3e0aa782563080368e27c8bd9f2aa226afd30972ddc3c7cba7ca0fa2af3",
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diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/raw/source.json.gz b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/raw/source.json.gz
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diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/views/profile.json b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/views/profile.json
new file mode 100644
index 00000000..d48dd153
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/views/profile.json
@@ -0,0 +1,47 @@
+{
+  "row_count": 1289,
+  "date_range": [
+    "2021-01-04",
+    "2026-04-30"
+  ],
+  "audit_line_count": 1090,
+  "audit_date_range": [
+    "2021-01-01",
+    "2026-04-30"
+  ],
+  "audit_event_counts": {
+    "rebalance_order": 816,
+    "rebalance_signals": 272,
+    "run_end": 1,
+    "run_start": 1
+  },
+  "etf_pool": [
+    "159819.XSHE",
+    "513100.XSHG",
+    "518880.XSHG"
+  ],
+  "summary_metric_keys": [
+    "亏损次数",
+    "信息比率",
+    "基准收益",
+    "基准波动率",
+    "夏普比率",
+    "日胜率",
+    "最大回撤",
+    "最大回撤区间",
+    "盈亏比",
+    "盈利次数",
+    "策略年化收益",
+    "策略收益",
+    "策略波动率",
+    "索提诺比率",
+    "胜率",
+    "贝塔",
+    "超额收益",
+    "阿尔法"
+  ],
+  "report_files": [
+    "backtest_report.md",
+    "data-integrity.md"
+  ]
+}
\ No newline at end of file
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/views/profile.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/views/profile.md
new file mode 100644
index 00000000..42d4926b
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/views/profile.md
@@ -0,0 +1,23 @@
+# 回测 run 概览
+
+- **行数**: `1289`
+- **日期范围**: `2021-01-04 ~ 2026-04-30`
+- **审计日志行数**: `1090`
+- **审计日期范围**: `2021-01-01 ~ 2026-04-30`
+- **ETF 池**: `159819.XSHE, 513100.XSHG, 518880.XSHG`
+
+## 审计事件分布
+
+| 事件类型 | 数量 |
+| --- | ---: |
+| rebalance_order | 816 |
+| rebalance_signals | 272 |
+| run_end | 1 |
+| run_start | 1 |
+
+## 报告文件
+
+| 报告文件 |
+| --- |
+| backtest_report.md |
+| data-integrity.md |
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/views/sample.csv b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/views/sample.csv
new file mode 100644
index 00000000..1953f096
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/views/sample.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:27d7f60b2727a95d8820ee644e007d7aa6693ba8e6c62c7839a7abbc27ffd047
+size 710
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/views/schema.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/views/schema.md
new file mode 100644
index 00000000..14dc0788
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/views/schema.md
@@ -0,0 +1,10 @@
+# 回测 run 快照字段
+
+| 视图 | 说明 |
+| --- | --- |
+| `raw/source.json.gz` | 原始 run 文件清单与哈希 |
+| `raw/*.gz` | 压缩保存的原始回测文件 |
+| `data/data.parquet` | 累计收益序列主存储 |
+| `data/audit_events.parquet` | 审计事件主存储 |
+| `views/sample.csv` | 收益序列小样本 |
+| `views/profile.json` | 行数、日期范围、审计日志和报告文件摘要 |
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/README.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/README.md
new file mode 100644
index 00000000..96681622
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/README.md
@@ -0,0 +1,9 @@
+# etf_factor_rotation_backtest_runs
+
+- **snapshot**: `20260701-0025-bt0d4e21c752867aa36b89ee13d7540352`
+- **run_id**: `20260701-0025-bt0d4e21c752867aa36b89ee13d7540352`
+- **fingerprint**: `sha256:2a9db19d253f131c38dff3e91f28fbdd1251f19f1a9fc3c0f11ac0f1333c4b3a`
+- **日期范围**: `2021-01-04 ~ 2026-04-30`
+- **审计日志行数**: `1903`
+
+原始文件压缩保存在 `raw/*.gz`；常用轻量索引见 `views/`；程序读取优先使用 `data/data.parquet`。
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/data/audit_events.parquet b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/data/audit_events.parquet
new file mode 100644
index 00000000..099bbf5e
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+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/data/audit_events.parquet
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:25b140ab7ebf7943fb941f399044ee79f70f65f277ffaabe37f5ccfea4e104b6
+size 104150
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/data/data.parquet b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/data/data.parquet
new file mode 100644
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2d352237471a3c3d1dcd4e56512dfc8b086e5a38350658253567e2e696e4108e
+size 16266
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/dataset.json b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/dataset.json
new file mode 100644
index 00000000..1c5d83c6
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/dataset.json
@@ -0,0 +1,174 @@
+{
+  "schema_version": 1,
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "fingerprint": "sha256:2a9db19d253f131c38dff3e91f28fbdd1251f19f1a9fc3c0f11ac0f1333c4b3a",
+  "created_at": "2026-06-30T16:27:44+00:00",
+  "owner": "research-platform",
+  "created_by": "research-platform",
+  "lifecycle": "active",
+  "source": {
+    "kind": "joinquant_backtest_run",
+    "path": "D:/My Project/Quant Trading/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352"
+  },
+  "storage": {
+    "canonical": "parquet",
+    "compression": "zstd",
+    "raw": "json.gz/jsonl.gz/md.gz"
+  },
+  "row_count": 1289,
+  "date_range": [
+    "2021-01-04",
+    "2026-04-30"
+  ],
+  "run_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "partial": false,
+  "missing_required_files": [],
+  "summary_metrics": {
+    "策略收益": "120.85%",
+    "策略年化收益": "16.61%",
+    "基准收益": "-7.75%",
+    "超额收益": "139.41%",
+    "最大回撤": "11.66%",
+    "最大回撤区间": "2021-09-06,2022-10-21",
+    "阿尔法": "0.134",
+    "贝塔": "0.134",
+    "夏普比率": "1.543",
+    "索提诺比率": "2.276",
+    "信息比率": "1.047",
+    "策略波动率": "0.082",
+    "基准波动率": "0.179",
+    "胜率": "0.706",
+    "盈亏比": "4.224",
+    "日胜率": "0.545",
+    "盈利次数": 132,
+    "亏损次数": 55
+  },
+  "source_metadata": {
+    "strategy_name": "etf_factor_rotation",
+    "strategy_file": "",
+    "strategy_dir": "",
+    "start_date_requested": "",
+    "start_date_effective": "2021-01-01",
+    "end_date_requested": "",
+    "end_date_effective": "2026-04-30",
+    "capital": 100000,
+    "backtest_id": "0d4e21c752867aa36b89ee13d7540352",
+    "backtest_url": "",
+    "generated_at": "2026-07-01T00:27:32",
+    "extraction_method": "joinquant_research_get_backtest",
+    "primary_extraction_method": "joinquant_research_get_backtest",
+    "fallback_extraction_method": "",
+    "research_export_path": "jq_auto_exports/research_backtest_0d4e21c752867aa36b89ee13d7540352.json",
+    "research_downloaded": true,
+    "detail_api_used": true,
+    "frequency": "1d",
+    "py_version": "Python3",
+    "internal_backtest_id": "d79fe48b94af96dafe698c1361f19fa9",
+    "audit_token": "etf_factor_rotation-s02-logic3-code-variant-20260701002504-55d17183",
+    "audit_path": "jq_auto_audit/etf_factor_rotation-s02-logic3-code-variant-20260701002504-55d17183.jsonl"
+  },
+  "audit_line_count": 1903,
+  "audit_date_range": [
+    "2021-01-01",
+    "2026-04-30"
+  ],
+  "audit_event_counts": {
+    "live_like_rebalance_execute": 272,
+    "live_like_signal_marked": 272,
+    "live_like_wait": 269,
+    "rebalance_order": 816,
+    "rebalance_signals": 272,
+    "run_end": 1,
+    "run_start": 1
+  },
+  "etf_pool": [
+    "159819.XSHE",
+    "513100.XSHG",
+    "518880.XSHG"
+  ],
+  "report_files": [
+    "backtest_report.md",
+    "data-integrity.md"
+  ],
+  "files": {
+    "raw": "raw/source.json.gz",
+    "profile_json": "views/profile.json",
+    "audit_events": "data/audit_events.parquet",
+    "daily_returns": "data/data.parquet",
+    "canonical": "data/data.parquet",
+    "sample": "views/sample.csv",
+    "api_export_source": "raw/api_export.json.gz",
+    "detail_api_export_source": "raw/detail_api_export.json.gz",
+    "summary_metrics": "raw/summary_metrics.json.gz",
+    "audit_log_source": "raw/audit_log.jsonl.gz",
+    "daily_returns_source": "raw/daily_returns.md.gz",
+    "positioninfo_source": "raw/positioninfo.md.gz",
+    "transactioninfo_source": "raw/transactioninfo.md.gz",
+    "balances_source": "raw/balances.md.gz",
+    "period_risks_source": "raw/period_risks.md.gz",
+    "logs_source": "raw/logs.md.gz"
+  },
+  "raw_file_integrity": {
+    "api_export.json": {
+      "dataset_file": "raw/api_export.json.gz",
+      "original_sha256": "9bbff9ea33c7a3eefad1611590f0a759af491ef9a17819a873b228c6a74b48c3",
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+      "original_bytes": 3657616
+    },
+    "detail_api_export.json": {
+      "dataset_file": "raw/detail_api_export.json.gz",
+      "original_sha256": "e312b3f0bcd00a020c98131ff2a1178cc34ce07ca929b366d49f4098931a70da",
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+      "original_bytes": 4383483
+    },
+    "summary_metrics.json": {
+      "dataset_file": "raw/summary_metrics.json.gz",
+      "original_sha256": "98d1bf471f920ed60c2e5b707c6ee82a302cda99ba5019d128585bfc2b298125",
+      "compressed_sha256": "77876f051fe717cab7f6fd148ef2ae02be048c0ed4206decdea1bc8e12a2c2c0",
+      "original_bytes": 521
+    },
+    "tabs_raw/audit_log.jsonl": {
+      "dataset_file": "raw/audit_log.jsonl.gz",
+      "original_sha256": "03b8321df76348480a1607a310b405d2a36e7893369f0c78106c82b85aeddca7",
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+      "original_bytes": 1573538
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+    "tabs_raw/daily_returns.md": {
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+      "original_bytes": 92608
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+      "original_bytes": 379635
+    },
+    "tabs_raw/transactioninfo.md": {
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+      "original_sha256": "e782081b37742ef6b6be217827ed0afb4429871c018b0baf58a77329cb30704d",
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+      "original_bytes": 31319
+    },
+    "tabs_raw/balances.md": {
+      "dataset_file": "raw/balances.md.gz",
+      "original_sha256": "bb42c190a0c193426c36e3cae105bd27ce891614abf7f9e10f94dcb9a0aa6274",
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+      "original_bytes": 90295
+    },
+    "tabs_raw/period_risks.md": {
+      "dataset_file": "raw/period_risks.md.gz",
+      "original_sha256": "12b8099715fc56c767744c28dd4a581e2245ba7f789cd44365fcfcaf3b55c7d1",
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+      "original_bytes": 62815
+    },
+    "tabs_raw/logs.md": {
+      "dataset_file": "raw/logs.md.gz",
+      "original_sha256": "d811c3e0aa782563080368e27c8bd9f2aa226afd30972ddc3c7cba7ca0fa2af3",
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+      "original_bytes": 290
+    }
+  }
+}
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diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/views/profile.json b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/views/profile.json
new file mode 100644
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@@ -0,0 +1,50 @@
+{
+  "row_count": 1289,
+  "date_range": [
+    "2021-01-04",
+    "2026-04-30"
+  ],
+  "audit_line_count": 1903,
+  "audit_date_range": [
+    "2021-01-01",
+    "2026-04-30"
+  ],
+  "audit_event_counts": {
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+    "live_like_signal_marked": 272,
+    "live_like_wait": 269,
+    "rebalance_order": 816,
+    "rebalance_signals": 272,
+    "run_end": 1,
+    "run_start": 1
+  },
+  "etf_pool": [
+    "159819.XSHE",
+    "513100.XSHG",
+    "518880.XSHG"
+  ],
+  "summary_metric_keys": [
+    "亏损次数",
+    "信息比率",
+    "基准收益",
+    "基准波动率",
+    "夏普比率",
+    "日胜率",
+    "最大回撤",
+    "最大回撤区间",
+    "盈亏比",
+    "盈利次数",
+    "策略年化收益",
+    "策略收益",
+    "策略波动率",
+    "索提诺比率",
+    "胜率",
+    "贝塔",
+    "超额收益",
+    "阿尔法"
+  ],
+  "report_files": [
+    "backtest_report.md",
+    "data-integrity.md"
+  ]
+}
\ No newline at end of file
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/views/profile.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/views/profile.md
new file mode 100644
index 00000000..f6666756
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/views/profile.md
@@ -0,0 +1,26 @@
+# 回测 run 概览
+
+- **行数**: `1289`
+- **日期范围**: `2021-01-04 ~ 2026-04-30`
+- **审计日志行数**: `1903`
+- **审计日期范围**: `2021-01-01 ~ 2026-04-30`
+- **ETF 池**: `159819.XSHE, 513100.XSHG, 518880.XSHG`
+
+## 审计事件分布
+
+| 事件类型 | 数量 |
+| --- | ---: |
+| live_like_rebalance_execute | 272 |
+| live_like_signal_marked | 272 |
+| live_like_wait | 269 |
+| rebalance_order | 816 |
+| rebalance_signals | 272 |
+| run_end | 1 |
+| run_start | 1 |
+
+## 报告文件
+
+| 报告文件 |
+| --- |
+| backtest_report.md |
+| data-integrity.md |
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/views/sample.csv b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/views/sample.csv
new file mode 100644
index 00000000..f7ace3a2
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/views/sample.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:083c44fe6c9cb739e99abf1ff2f04ab1b69a737ff55e654bba5cbb08e524fa64
+size 670
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/views/schema.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/views/schema.md
new file mode 100644
index 00000000..14dc0788
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/views/schema.md
@@ -0,0 +1,10 @@
+# 回测 run 快照字段
+
+| 视图 | 说明 |
+| --- | --- |
+| `raw/source.json.gz` | 原始 run 文件清单与哈希 |
+| `raw/*.gz` | 压缩保存的原始回测文件 |
+| `data/data.parquet` | 累计收益序列主存储 |
+| `data/audit_events.parquet` | 审计事件主存储 |
+| `views/sample.csv` | 收益序列小样本 |
+| `views/profile.json` | 行数、日期范围、审计日志和报告文件摘要 |
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/README.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/README.md
new file mode 100644
index 00000000..1d608f5f
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/README.md
@@ -0,0 +1,9 @@
+# etf_factor_rotation_backtest_runs
+
+- **snapshot**: `20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5`
+- **run_id**: `20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5`
+- **fingerprint**: `sha256:cd9d4301f3c996c294a5f0b66962a6c053d831ef2a0ddd1914746ad9be1105c5`
+- **日期范围**: `2021-01-04 ~ 2026-04-30`
+- **审计日志行数**: `1291`
+
+原始文件压缩保存在 `raw/*.gz`；常用轻量索引见 `views/`；程序读取优先使用 `data/data.parquet`。
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/data/audit_events.parquet b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/data/audit_events.parquet
new file mode 100644
index 00000000..9796e3ca
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/data/audit_events.parquet
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:651b3b49e8612c27643100e50d23a424488460a40cb925c58737dea4152298ee
+size 26958
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/data/data.parquet b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/data/data.parquet
new file mode 100644
index 00000000..72ed321f
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/data/data.parquet
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bc583e5e32c3c00c52d82954ef0da86ebb868da770d1ab3b4ee7732d72b4e940
+size 5409
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/dataset.json b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/dataset.json
new file mode 100644
index 00000000..62aa82de
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/dataset.json
@@ -0,0 +1,172 @@
+{
+  "schema_version": 1,
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "fingerprint": "sha256:cd9d4301f3c996c294a5f0b66962a6c053d831ef2a0ddd1914746ad9be1105c5",
+  "created_at": "2026-06-30T16:29:20+00:00",
+  "owner": "research-platform",
+  "created_by": "research-platform",
+  "lifecycle": "superseded",
+  "source": {
+    "kind": "joinquant_backtest_run",
+    "path": "D:/My Project/Quant Trading/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5"
+  },
+  "storage": {
+    "canonical": "parquet",
+    "compression": "zstd",
+    "raw": "json.gz/jsonl.gz/md.gz"
+  },
+  "row_count": 1289,
+  "date_range": [
+    "2021-01-04",
+    "2026-04-30"
+  ],
+  "run_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "partial": false,
+  "missing_required_files": [],
+  "summary_metrics": {
+    "策略收益": "0.00%",
+    "策略年化收益": "0.00%",
+    "基准收益": "-7.75%",
+    "超额收益": "8.40%",
+    "最大回撤": "0.00%",
+    "最大回撤区间": "2021-01-04,2021-01-04",
+    "阿尔法": "-0.040",
+    "贝塔": "0.000",
+    "夏普比率": "0.000",
+    "索提诺比率": "0.000",
+    "信息比率": "0.087",
+    "策略波动率": "0.000",
+    "基准波动率": "0.179",
+    "胜率": "0.000",
+    "盈亏比": "0.000",
+    "日胜率": "0.505",
+    "盈利次数": 0,
+    "亏损次数": 0
+  },
+  "source_metadata": {
+    "strategy_name": "etf_factor_rotation",
+    "strategy_file": "",
+    "strategy_dir": "",
+    "start_date_requested": "",
+    "start_date_effective": "2021-01-01",
+    "end_date_requested": "",
+    "end_date_effective": "2026-04-30",
+    "capital": 100000,
+    "backtest_id": "cb35093c739b769b0c7cebb1bbe141b5",
+    "backtest_url": "",
+    "generated_at": "2026-07-01T00:29:10",
+    "extraction_method": "joinquant_research_get_backtest",
+    "primary_extraction_method": "joinquant_research_get_backtest",
+    "fallback_extraction_method": "",
+    "research_export_path": "jq_auto_exports/research_backtest_cb35093c739b769b0c7cebb1bbe141b5.json",
+    "research_downloaded": true,
+    "detail_api_used": true,
+    "frequency": "1d",
+    "py_version": "Python3",
+    "internal_backtest_id": "34a1ef4f300c8c4763d455b4dd5fdc1f",
+    "audit_token": "etf_factor_rotation-s03-weekend-close-signal-next-open-variant-20260701002745-dae632f4",
+    "audit_path": "jq_auto_audit/etf_factor_rotation-s03-weekend-close-signal-next-open-variant-20260701002745-dae632f4.jsonl"
+  },
+  "audit_line_count": 1291,
+  "audit_date_range": [
+    "2021-01-01",
+    "2026-04-30"
+  ],
+  "audit_event_counts": {
+    "run_end": 1,
+    "run_start": 1,
+    "weekend_close_signal_skip": 1289
+  },
+  "etf_pool": [
+    "159819.XSHE",
+    "513100.XSHG",
+    "518880.XSHG"
+  ],
+  "report_files": [
+    "backtest_report.md",
+    "data-integrity.md"
+  ],
+  "files": {
+    "raw": "raw/source.json.gz",
+    "profile_json": "views/profile.json",
+    "audit_events": "data/audit_events.parquet",
+    "daily_returns": "data/data.parquet",
+    "canonical": "data/data.parquet",
+    "sample": "views/sample.csv",
+    "api_export_source": "raw/api_export.json.gz",
+    "detail_api_export_source": "raw/detail_api_export.json.gz",
+    "summary_metrics": "raw/summary_metrics.json.gz",
+    "audit_log_source": "raw/audit_log.jsonl.gz",
+    "daily_returns_source": "raw/daily_returns.md.gz",
+    "positioninfo_source": "raw/positioninfo.md.gz",
+    "transactioninfo_source": "raw/transactioninfo.md.gz",
+    "balances_source": "raw/balances.md.gz",
+    "period_risks_source": "raw/period_risks.md.gz",
+    "logs_source": "raw/logs.md.gz"
+  },
+  "raw_file_integrity": {
+    "api_export.json": {
+      "dataset_file": "raw/api_export.json.gz",
+      "original_sha256": "c229ecd0a002776c46a8ac61b45afe338320d96f56256f86fba24ae5d1913675",
+      "compressed_sha256": "4a0508b9259be6e1c383b046076360cf9d4bb33584736686522a9fdfd22b3117",
+      "original_bytes": 1195328
+    },
+    "detail_api_export.json": {
+      "dataset_file": "raw/detail_api_export.json.gz",
+      "original_sha256": "cf5dbcd96ca03765831910e39f65b0dd4677bbdc53d0cd81183fab54e1c1c077",
+      "compressed_sha256": "f30a669cd2bf68d772ffe54597f4bd96cd469b580511c438af482e39ce850dc0",
+      "original_bytes": 1929553
+    },
+    "summary_metrics.json": {
+      "dataset_file": "raw/summary_metrics.json.gz",
+      "original_sha256": "1441610d84c772df69020a9b419b6a0d93d17925a536a0da73302043f938622c",
+      "compressed_sha256": "d93b7bc879c5078a26700fa2537df9dccb923afaa938a58b2b2fb65c8c3effc5",
+      "original_bytes": 513
+    },
+    "tabs_raw/audit_log.jsonl": {
+      "dataset_file": "raw/audit_log.jsonl.gz",
+      "original_sha256": "c2bc4e50e30b7d10d5e4442072d4c941a72ad973444e5f280f79185fdba4bdb7",
+      "compressed_sha256": "8666e944cd6e4c73d8110c1285e631d5e7f19923bf06479d59ce80097cc82695",
+      "original_bytes": 457444
+    },
+    "tabs_raw/daily_returns.md": {
+      "dataset_file": "raw/daily_returns.md.gz",
+      "original_sha256": "280364f893898ccb15f694c6d4100181227cc07f7286799990f3490b5a1bce6c",
+      "compressed_sha256": "047a3b8cd21fbde23a45ed77f444e16f52b31ec64294acf1b81bb6906b429855",
+      "original_bytes": 71979
+    },
+    "tabs_raw/positioninfo.md": {
+      "dataset_file": "raw/positioninfo.md.gz",
+      "original_sha256": "2e84a9b6856d1079b7ef24a3ddace913452650e6d3ed7f1ebda4c606bb982540",
+      "compressed_sha256": "d051b390de0ac7ab1028c8ffad73921af3d4920ba4dbe9593b0858a2c6820b7c",
+      "original_bytes": 46
+    },
+    "tabs_raw/transactioninfo.md": {
+      "dataset_file": "raw/transactioninfo.md.gz",
+      "original_sha256": "aef37d19402efee5cf279ac02e7962f8eacdc8c878fc5ff6265185aaf09e6a8e",
+      "compressed_sha256": "b4b0eae5867c88eeaabb8404edf7c499cbdadef927d80bc4f8e97afdbbbd821d",
+      "original_bytes": 37
+    },
+    "tabs_raw/balances.md": {
+      "dataset_file": "raw/balances.md.gz",
+      "original_sha256": "ee7877994ae8bba34c4f473a8486c5735751380e0d895811c34bc3b4c999af0f",
+      "compressed_sha256": "08cb8867e0c9f219c8a89a87f77d0f79bc997c0e78f0fe9f78fe04ef8db02063",
+      "original_bytes": 89075
+    },
+    "tabs_raw/period_risks.md": {
+      "dataset_file": "raw/period_risks.md.gz",
+      "original_sha256": "07dcbe34d02a74d975ee511e851dd632d867e5d7bbf78e0273902c5ee6b7a679",
+      "compressed_sha256": "98f73b5d0a3d9998b7874456af774414660a139bc075a11ec21bbb2dfc8f167c",
+      "original_bytes": 37103
+    },
+    "tabs_raw/logs.md": {
+      "dataset_file": "raw/logs.md.gz",
+      "original_sha256": "d811c3e0aa782563080368e27c8bd9f2aa226afd30972ddc3c7cba7ca0fa2af3",
+      "compressed_sha256": "05269fff42e0b0e739e4003fbb5694a7160ca23692873edd5f4f022b419d0812",
+      "original_bytes": 290
+    }
+  },
+  "superseded_by": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "superseded_reason": "initial no-trade run; s04 is the active reproducible weekend-close variant evidence"
+}
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/raw/source.json.gz b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/raw/source.json.gz
new file mode 100644
index 00000000..55290284
Binary files /dev/null and b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/raw/source.json.gz differ
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/views/profile.json b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/views/profile.json
new file mode 100644
index 00000000..805aad02
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/views/profile.json
@@ -0,0 +1,46 @@
+{
+  "row_count": 1289,
+  "date_range": [
+    "2021-01-04",
+    "2026-04-30"
+  ],
+  "audit_line_count": 1291,
+  "audit_date_range": [
+    "2021-01-01",
+    "2026-04-30"
+  ],
+  "audit_event_counts": {
+    "run_end": 1,
+    "run_start": 1,
+    "weekend_close_signal_skip": 1289
+  },
+  "etf_pool": [
+    "159819.XSHE",
+    "513100.XSHG",
+    "518880.XSHG"
+  ],
+  "summary_metric_keys": [
+    "亏损次数",
+    "信息比率",
+    "基准收益",
+    "基准波动率",
+    "夏普比率",
+    "日胜率",
+    "最大回撤",
+    "最大回撤区间",
+    "盈亏比",
+    "盈利次数",
+    "策略年化收益",
+    "策略收益",
+    "策略波动率",
+    "索提诺比率",
+    "胜率",
+    "贝塔",
+    "超额收益",
+    "阿尔法"
+  ],
+  "report_files": [
+    "backtest_report.md",
+    "data-integrity.md"
+  ]
+}
\ No newline at end of file
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/views/profile.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/views/profile.md
new file mode 100644
index 00000000..0804ab2d
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/views/profile.md
@@ -0,0 +1,22 @@
+# 回测 run 概览
+
+- **行数**: `1289`
+- **日期范围**: `2021-01-04 ~ 2026-04-30`
+- **审计日志行数**: `1291`
+- **审计日期范围**: `2021-01-01 ~ 2026-04-30`
+- **ETF 池**: `159819.XSHE, 513100.XSHG, 518880.XSHG`
+
+## 审计事件分布
+
+| 事件类型 | 数量 |
+| --- | ---: |
+| run_end | 1 |
+| run_start | 1 |
+| weekend_close_signal_skip | 1289 |
+
+## 报告文件
+
+| 报告文件 |
+| --- |
+| backtest_report.md |
+| data-integrity.md |
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/views/sample.csv b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/views/sample.csv
new file mode 100644
index 00000000..56c15740
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/views/sample.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1285e2d033ccbe84f660fd0d3420ce5294be265174cecff5883ff54c57ca42b6
+size 344
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/views/schema.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/views/schema.md
new file mode 100644
index 00000000..14dc0788
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/views/schema.md
@@ -0,0 +1,10 @@
+# 回测 run 快照字段
+
+| 视图 | 说明 |
+| --- | --- |
+| `raw/source.json.gz` | 原始 run 文件清单与哈希 |
+| `raw/*.gz` | 压缩保存的原始回测文件 |
+| `data/data.parquet` | 累计收益序列主存储 |
+| `data/audit_events.parquet` | 审计事件主存储 |
+| `views/sample.csv` | 收益序列小样本 |
+| `views/profile.json` | 行数、日期范围、审计日志和报告文件摘要 |
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/README.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/README.md
new file mode 100644
index 00000000..3b678428
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/README.md
@@ -0,0 +1,9 @@
+# etf_factor_rotation_backtest_runs
+
+- **snapshot**: `20260701-0032-btdcc6252aadef8bb09592538da4dde54c`
+- **run_id**: `20260701-0032-btdcc6252aadef8bb09592538da4dde54c`
+- **fingerprint**: `sha256:6c349f1a89a62304482c4289e10433ad831b4ad6ffc42bb3326ced70e785ac96`
+- **日期范围**: `2021-01-04 ~ 2026-04-30`
+- **审计日志行数**: `4681`
+
+原始文件压缩保存在 `raw/*.gz`；常用轻量索引见 `views/`；程序读取优先使用 `data/data.parquet`。
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/data/audit_events.parquet b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/data/audit_events.parquet
new file mode 100644
index 00000000..1617ad44
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+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/data/audit_events.parquet
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:78fb1106acce069cfdc0600efa73e05d80f7de3b0f031297382beb9f3a35f031
+size 305822
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/data/data.parquet b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/data/data.parquet
new file mode 100644
index 00000000..ed72c4c2
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+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/data/data.parquet
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0b8a48fdd9a0b6985f78fea8db01d95d5a359d3a033d4f686e7e651ed58b6d80
+size 16123
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/dataset.json b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/dataset.json
new file mode 100644
index 00000000..13f82078
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/dataset.json
@@ -0,0 +1,174 @@
+{
+  "schema_version": 1,
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "fingerprint": "sha256:6c349f1a89a62304482c4289e10433ad831b4ad6ffc42bb3326ced70e785ac96",
+  "created_at": "2026-06-30T16:38:35+00:00",
+  "owner": "research-platform",
+  "created_by": "research-platform",
+  "lifecycle": "active",
+  "source": {
+    "kind": "joinquant_backtest_run",
+    "path": "D:/My Project/Quant Trading/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c"
+  },
+  "storage": {
+    "canonical": "parquet",
+    "compression": "zstd",
+    "raw": "json.gz/jsonl.gz/md.gz"
+  },
+  "row_count": 1289,
+  "date_range": [
+    "2021-01-04",
+    "2026-04-30"
+  ],
+  "run_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "partial": false,
+  "missing_required_files": [],
+  "summary_metrics": {
+    "策略收益": "127.57%",
+    "策略年化收益": "17.29%",
+    "基准收益": "-7.75%",
+    "超额收益": "146.70%",
+    "最大回撤": "7.58%",
+    "最大回撤区间": "2021-11-22,2022-01-28",
+    "阿尔法": "0.141",
+    "贝塔": "0.141",
+    "夏普比率": "1.591",
+    "索提诺比率": "2.352",
+    "信息比率": "1.089",
+    "策略波动率": "0.084",
+    "基准波动率": "0.179",
+    "胜率": "0.733",
+    "盈亏比": "5.008",
+    "日胜率": "0.541",
+    "盈利次数": 140,
+    "亏损次数": 51
+  },
+  "source_metadata": {
+    "strategy_name": "etf_factor_rotation",
+    "strategy_file": "",
+    "strategy_dir": "",
+    "start_date_requested": "",
+    "start_date_effective": "2021-01-01",
+    "end_date_requested": "",
+    "end_date_effective": "2026-04-30",
+    "capital": 100000,
+    "backtest_id": "dcc6252aadef8bb09592538da4dde54c",
+    "backtest_url": "",
+    "generated_at": "2026-07-01T00:38:20",
+    "extraction_method": "joinquant_research_get_backtest",
+    "primary_extraction_method": "joinquant_research_get_backtest",
+    "fallback_extraction_method": "",
+    "research_export_path": "jq_auto_exports/research_backtest_dcc6252aadef8bb09592538da4dde54c.json",
+    "research_downloaded": true,
+    "detail_api_used": true,
+    "frequency": "1d",
+    "py_version": "Python3",
+    "internal_backtest_id": "8976d3093b13233b86b7a4c7f33c915e",
+    "audit_token": "etf_factor_rotation-s04-weekend-close-signal-next-open-variant-v2-20260701003223-e458457b",
+    "audit_path": "jq_auto_audit/etf_factor_rotation-s04-weekend-close-signal-next-open-variant-v2-20260701003223-e458457b.jsonl"
+  },
+  "audit_line_count": 4681,
+  "audit_date_range": [
+    "2021-01-01",
+    "2026-04-30"
+  ],
+  "audit_event_counts": {
+    "rebalance_order": 813,
+    "rebalance_signals": 1289,
+    "run_end": 1,
+    "run_start": 1,
+    "weekend_close_execute": 271,
+    "weekend_close_plan_cached": 1289,
+    "weekend_close_plan_discarded": 1017
+  },
+  "etf_pool": [
+    "159819.XSHE",
+    "513100.XSHG",
+    "518880.XSHG"
+  ],
+  "report_files": [
+    "backtest_report.md",
+    "data-integrity.md"
+  ],
+  "files": {
+    "raw": "raw/source.json.gz",
+    "profile_json": "views/profile.json",
+    "audit_events": "data/audit_events.parquet",
+    "daily_returns": "data/data.parquet",
+    "canonical": "data/data.parquet",
+    "sample": "views/sample.csv",
+    "api_export_source": "raw/api_export.json.gz",
+    "detail_api_export_source": "raw/detail_api_export.json.gz",
+    "summary_metrics": "raw/summary_metrics.json.gz",
+    "audit_log_source": "raw/audit_log.jsonl.gz",
+    "daily_returns_source": "raw/daily_returns.md.gz",
+    "positioninfo_source": "raw/positioninfo.md.gz",
+    "transactioninfo_source": "raw/transactioninfo.md.gz",
+    "balances_source": "raw/balances.md.gz",
+    "period_risks_source": "raw/period_risks.md.gz",
+    "logs_source": "raw/logs.md.gz"
+  },
+  "raw_file_integrity": {
+    "api_export.json": {
+      "dataset_file": "raw/api_export.json.gz",
+      "original_sha256": "2bbf6cebbecd26e21ac1f1006b027866d01999577e29080f3cee09dc20a62478",
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+      "original_bytes": 8085596
+    },
+    "detail_api_export.json": {
+      "dataset_file": "raw/detail_api_export.json.gz",
+      "original_sha256": "1dab601403be7c65c47edd17a93fde95c08ec7f9217a018c826e6d6f13e3b5e9",
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+      "original_bytes": 4322026
+    },
+    "summary_metrics.json": {
+      "dataset_file": "raw/summary_metrics.json.gz",
+      "original_sha256": "317b30d9a2b2f3f72bb2dc7210bde94ef9e389e7939d8423c2b1f5ee5df3e21b",
+      "compressed_sha256": "135fb1ab5e2fa8cf0bcebadf03780f0ed8d55c488b02372a3b7ccbd393629cc0",
+      "original_bytes": 520
+    },
+    "tabs_raw/audit_log.jsonl": {
+      "dataset_file": "raw/audit_log.jsonl.gz",
+      "original_sha256": "ceb62476e6ca432598fe3ea267b3158c921375bbb1150672643fd52ba582753a",
+      "compressed_sha256": "49e9ee759d2e965c26d7779e4578024476bdc9a6ad171355f56822f868b46a8d",
+      "original_bytes": 5709740
+    },
+    "tabs_raw/daily_returns.md": {
+      "dataset_file": "raw/daily_returns.md.gz",
+      "original_sha256": "fae7f563d4decde5e0f5e2708b6502e4e712b42cb2ce35e8817779cc40060a50",
+      "compressed_sha256": "8e31e63bf90b2d042d4f045a290db99eb6f3a0892a34462ee3caea975395f468",
+      "original_bytes": 92691
+    },
+    "tabs_raw/positioninfo.md": {
+      "dataset_file": "raw/positioninfo.md.gz",
+      "original_sha256": "b66559bf2f878363ba35fa31fa8fcb6e0ad2f6c7249c723448db04164ba99e6b",
+      "compressed_sha256": "2e8ffe3c2f7a5df3669a203e25084a9e1974f5a5c0a4e6ba18fc817b35ee87da",
+      "original_bytes": 378767
+    },
+    "tabs_raw/transactioninfo.md": {
+      "dataset_file": "raw/transactioninfo.md.gz",
+      "original_sha256": "9231003f977b453cf45f5064d02865af7d04a533f92034c9407db117c9e27c8d",
+      "compressed_sha256": "453d227ceed56221df0fdae0b17a53ebd4ddfd766a6f42cac90eb4d2f46cd011",
+      "original_bytes": 31888
+    },
+    "tabs_raw/balances.md": {
+      "dataset_file": "raw/balances.md.gz",
+      "original_sha256": "7f0d0c1bee6b6572516b623634b2a9d2169fea08f48e8a6aa033984cc1b09872",
+      "compressed_sha256": "aff79e04917b5b162bf6cd1545dbda15100863f97ce46b5a647459a33804fa59",
+      "original_bytes": 90521
+    },
+    "tabs_raw/period_risks.md": {
+      "dataset_file": "raw/period_risks.md.gz",
+      "original_sha256": "661b2d392c210b2a0a17c1b5c5bfdf78e23dd67d577f87e008166997053e106c",
+      "compressed_sha256": "cb4afc7f1a21bf684ce07caa9ddb45476fe0733f6e048c4a5be76cc3fdb923a2",
+      "original_bytes": 62872
+    },
+    "tabs_raw/logs.md": {
+      "dataset_file": "raw/logs.md.gz",
+      "original_sha256": "d811c3e0aa782563080368e27c8bd9f2aa226afd30972ddc3c7cba7ca0fa2af3",
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+      "original_bytes": 290
+    }
+  }
+}
\ No newline at end of file
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/raw/source.json.gz b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/raw/source.json.gz
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index 00000000..280c9527
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diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/views/profile.json b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/views/profile.json
new file mode 100644
index 00000000..78c01895
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/views/profile.json
@@ -0,0 +1,50 @@
+{
+  "row_count": 1289,
+  "date_range": [
+    "2021-01-04",
+    "2026-04-30"
+  ],
+  "audit_line_count": 4681,
+  "audit_date_range": [
+    "2021-01-01",
+    "2026-04-30"
+  ],
+  "audit_event_counts": {
+    "rebalance_order": 813,
+    "rebalance_signals": 1289,
+    "run_end": 1,
+    "run_start": 1,
+    "weekend_close_execute": 271,
+    "weekend_close_plan_cached": 1289,
+    "weekend_close_plan_discarded": 1017
+  },
+  "etf_pool": [
+    "159819.XSHE",
+    "513100.XSHG",
+    "518880.XSHG"
+  ],
+  "summary_metric_keys": [
+    "亏损次数",
+    "信息比率",
+    "基准收益",
+    "基准波动率",
+    "夏普比率",
+    "日胜率",
+    "最大回撤",
+    "最大回撤区间",
+    "盈亏比",
+    "盈利次数",
+    "策略年化收益",
+    "策略收益",
+    "策略波动率",
+    "索提诺比率",
+    "胜率",
+    "贝塔",
+    "超额收益",
+    "阿尔法"
+  ],
+  "report_files": [
+    "backtest_report.md",
+    "data-integrity.md"
+  ]
+}
\ No newline at end of file
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/views/profile.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/views/profile.md
new file mode 100644
index 00000000..e3d22b20
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/views/profile.md
@@ -0,0 +1,26 @@
+# 回测 run 概览
+
+- **行数**: `1289`
+- **日期范围**: `2021-01-04 ~ 2026-04-30`
+- **审计日志行数**: `4681`
+- **审计日期范围**: `2021-01-01 ~ 2026-04-30`
+- **ETF 池**: `159819.XSHE, 513100.XSHG, 518880.XSHG`
+
+## 审计事件分布
+
+| 事件类型 | 数量 |
+| --- | ---: |
+| rebalance_order | 813 |
+| rebalance_signals | 1289 |
+| run_end | 1 |
+| run_start | 1 |
+| weekend_close_execute | 271 |
+| weekend_close_plan_cached | 1289 |
+| weekend_close_plan_discarded | 1017 |
+
+## 报告文件
+
+| 报告文件 |
+| --- |
+| backtest_report.md |
+| data-integrity.md |
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/views/sample.csv b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/views/sample.csv
new file mode 100644
index 00000000..6fcdc0c4
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+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/views/sample.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bfc99a432f44991880db0203cd037969f52c588ec4751f4c5f3d71b47b54dd81
+size 612
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/views/schema.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/views/schema.md
new file mode 100644
index 00000000..14dc0788
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/views/schema.md
@@ -0,0 +1,10 @@
+# 回测 run 快照字段
+
+| 视图 | 说明 |
+| --- | --- |
+| `raw/source.json.gz` | 原始 run 文件清单与哈希 |
+| `raw/*.gz` | 压缩保存的原始回测文件 |
+| `data/data.parquet` | 累计收益序列主存储 |
+| `data/audit_events.parquet` | 审计事件主存储 |
+| `views/sample.csv` | 收益序列小样本 |
+| `views/profile.json` | 行数、日期范围、审计日志和报告文件摘要 |
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/README.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/README.md
new file mode 100644
index 00000000..65a8525b
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/README.md
@@ -0,0 +1,9 @@
+# etf_factor_rotation_backtest_runs
+
+- **snapshot**: `20260701-0246-bt526c312fb836d6e07826ce170809486a`
+- **run_id**: `20260701-0246-bt526c312fb836d6e07826ce170809486a`
+- **fingerprint**: `sha256:cc0f052868017cb487d7811ee5e4de461f0af77b9459546ccc69be8a3c5c82ca`
+- **日期范围**: `2021-01-04 ~ 2026-04-30`
+- **审计日志行数**: `1630`
+
+原始文件压缩保存在 `raw/*.gz`；常用轻量索引见 `views/`；程序读取优先使用 `data/data.parquet`。
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/data/audit_events.parquet b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/data/audit_events.parquet
new file mode 100644
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+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/data/audit_events.parquet
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:960e5fab9e20b0847f6d5c01cfc92f9838ab354b65baf9dba67af4b76ffff058
+size 118224
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/data/data.parquet b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/data/data.parquet
new file mode 100644
index 00000000..ed72c4c2
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/data/data.parquet
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0b8a48fdd9a0b6985f78fea8db01d95d5a359d3a033d4f686e7e651ed58b6d80
+size 16123
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/dataset.json b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/dataset.json
new file mode 100644
index 00000000..ac43a564
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/dataset.json
@@ -0,0 +1,173 @@
+{
+  "schema_version": 1,
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "fingerprint": "sha256:cc0f052868017cb487d7811ee5e4de461f0af77b9459546ccc69be8a3c5c82ca",
+  "created_at": "2026-06-30T18:50:07+00:00",
+  "owner": "research-platform",
+  "created_by": "research-platform",
+  "lifecycle": "active",
+  "source": {
+    "kind": "joinquant_backtest_run",
+    "path": "D:/My Project/Quant Trading/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a"
+  },
+  "storage": {
+    "canonical": "parquet",
+    "compression": "zstd",
+    "raw": "json.gz/jsonl.gz/md.gz"
+  },
+  "row_count": 1289,
+  "date_range": [
+    "2021-01-04",
+    "2026-04-30"
+  ],
+  "run_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "partial": false,
+  "missing_required_files": [],
+  "summary_metrics": {
+    "策略收益": "127.57%",
+    "策略年化收益": "17.29%",
+    "基准收益": "-7.75%",
+    "超额收益": "146.70%",
+    "最大回撤": "7.58%",
+    "最大回撤区间": "2021-11-22,2022-01-28",
+    "阿尔法": "0.141",
+    "贝塔": "0.141",
+    "夏普比率": "1.591",
+    "索提诺比率": "2.352",
+    "信息比率": "1.089",
+    "策略波动率": "0.084",
+    "基准波动率": "0.179",
+    "胜率": "0.733",
+    "盈亏比": "5.008",
+    "日胜率": "0.541",
+    "盈利次数": 140,
+    "亏损次数": 51
+  },
+  "source_metadata": {
+    "strategy_name": "etf_factor_rotation",
+    "strategy_file": "",
+    "strategy_dir": "",
+    "start_date_requested": "",
+    "start_date_effective": "2021-01-01",
+    "end_date_requested": "",
+    "end_date_effective": "2026-04-30",
+    "capital": 100000,
+    "backtest_id": "526c312fb836d6e07826ce170809486a",
+    "backtest_url": "",
+    "generated_at": "2026-07-01T02:49:55",
+    "extraction_method": "joinquant_research_get_backtest",
+    "primary_extraction_method": "joinquant_research_get_backtest",
+    "fallback_extraction_method": "",
+    "research_export_path": "jq_auto_exports/research_backtest_526c312fb836d6e07826ce170809486a.json",
+    "research_downloaded": true,
+    "detail_api_used": true,
+    "frequency": "1d",
+    "py_version": "Python3",
+    "internal_backtest_id": "b6cb7f66e1fd859bcf372f0813ab5d75",
+    "audit_token": "etf_factor_rotation-s04-weekend-close-signal-next-open-variant-v2-20260701024558-124bb940",
+    "audit_path": "jq_auto_audit/etf_factor_rotation-s04-weekend-close-signal-next-open-variant-v2-20260701024558-124bb940.jsonl"
+  },
+  "audit_line_count": 1630,
+  "audit_date_range": [
+    "2021-01-01",
+    "2026-04-30"
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+  "audit_event_counts": {
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+    "rebalance_signals": 272,
+    "run_end": 1,
+    "run_start": 1,
+    "weekend_close_execute": 271,
+    "weekend_close_plan_cached": 272
+  },
+  "etf_pool": [
+    "159819.XSHE",
+    "513100.XSHG",
+    "518880.XSHG"
+  ],
+  "report_files": [
+    "backtest_report.md",
+    "data-integrity.md"
+  ],
+  "files": {
+    "raw": "raw/source.json.gz",
+    "profile_json": "views/profile.json",
+    "audit_events": "data/audit_events.parquet",
+    "daily_returns": "data/data.parquet",
+    "canonical": "data/data.parquet",
+    "sample": "views/sample.csv",
+    "api_export_source": "raw/api_export.json.gz",
+    "detail_api_export_source": "raw/detail_api_export.json.gz",
+    "summary_metrics": "raw/summary_metrics.json.gz",
+    "audit_log_source": "raw/audit_log.jsonl.gz",
+    "daily_returns_source": "raw/daily_returns.md.gz",
+    "positioninfo_source": "raw/positioninfo.md.gz",
+    "transactioninfo_source": "raw/transactioninfo.md.gz",
+    "balances_source": "raw/balances.md.gz",
+    "period_risks_source": "raw/period_risks.md.gz",
+    "logs_source": "raw/logs.md.gz"
+  },
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+      "original_bytes": 1742407
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+    "tabs_raw/daily_returns.md": {
+      "dataset_file": "raw/daily_returns.md.gz",
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+      "original_bytes": 92691
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+      "original_sha256": "b66559bf2f878363ba35fa31fa8fcb6e0ad2f6c7249c723448db04164ba99e6b",
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+      "original_bytes": 378767
+    },
+    "tabs_raw/transactioninfo.md": {
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+      "original_sha256": "9231003f977b453cf45f5064d02865af7d04a533f92034c9407db117c9e27c8d",
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+      "original_bytes": 31888
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+    "tabs_raw/balances.md": {
+      "dataset_file": "raw/balances.md.gz",
+      "original_sha256": "7f0d0c1bee6b6572516b623634b2a9d2169fea08f48e8a6aa033984cc1b09872",
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+      "original_bytes": 90521
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diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/raw/source.json.gz b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/raw/source.json.gz
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index 00000000..46147cf3
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diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/views/profile.json b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/views/profile.json
new file mode 100644
index 00000000..d206e0e5
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/views/profile.json
@@ -0,0 +1,49 @@
+{
+  "row_count": 1289,
+  "date_range": [
+    "2021-01-04",
+    "2026-04-30"
+  ],
+  "audit_line_count": 1630,
+  "audit_date_range": [
+    "2021-01-01",
+    "2026-04-30"
+  ],
+  "audit_event_counts": {
+    "rebalance_order": 813,
+    "rebalance_signals": 272,
+    "run_end": 1,
+    "run_start": 1,
+    "weekend_close_execute": 271,
+    "weekend_close_plan_cached": 272
+  },
+  "etf_pool": [
+    "159819.XSHE",
+    "513100.XSHG",
+    "518880.XSHG"
+  ],
+  "summary_metric_keys": [
+    "亏损次数",
+    "信息比率",
+    "基准收益",
+    "基准波动率",
+    "夏普比率",
+    "日胜率",
+    "最大回撤",
+    "最大回撤区间",
+    "盈亏比",
+    "盈利次数",
+    "策略年化收益",
+    "策略收益",
+    "策略波动率",
+    "索提诺比率",
+    "胜率",
+    "贝塔",
+    "超额收益",
+    "阿尔法"
+  ],
+  "report_files": [
+    "backtest_report.md",
+    "data-integrity.md"
+  ]
+}
\ No newline at end of file
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/views/profile.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/views/profile.md
new file mode 100644
index 00000000..dfd80920
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/views/profile.md
@@ -0,0 +1,25 @@
+# 回测 run 概览
+
+- **行数**: `1289`
+- **日期范围**: `2021-01-04 ~ 2026-04-30`
+- **审计日志行数**: `1630`
+- **审计日期范围**: `2021-01-01 ~ 2026-04-30`
+- **ETF 池**: `159819.XSHE, 513100.XSHG, 518880.XSHG`
+
+## 审计事件分布
+
+| 事件类型 | 数量 |
+| --- | ---: |
+| rebalance_order | 813 |
+| rebalance_signals | 272 |
+| run_end | 1 |
+| run_start | 1 |
+| weekend_close_execute | 271 |
+| weekend_close_plan_cached | 272 |
+
+## 报告文件
+
+| 报告文件 |
+| --- |
+| backtest_report.md |
+| data-integrity.md |
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/views/sample.csv b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/views/sample.csv
new file mode 100644
index 00000000..6fcdc0c4
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/views/sample.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bfc99a432f44991880db0203cd037969f52c588ec4751f4c5f3d71b47b54dd81
+size 612
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/views/schema.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/views/schema.md
new file mode 100644
index 00000000..14dc0788
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/views/schema.md
@@ -0,0 +1,10 @@
+# 回测 run 快照字段
+
+| 视图 | 说明 |
+| --- | --- |
+| `raw/source.json.gz` | 原始 run 文件清单与哈希 |
+| `raw/*.gz` | 压缩保存的原始回测文件 |
+| `data/data.parquet` | 累计收益序列主存储 |
+| `data/audit_events.parquet` | 审计事件主存储 |
+| `views/sample.csv` | 收益序列小样本 |
+| `views/profile.json` | 行数、日期范围、审计日志和报告文件摘要 |
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/README.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/README.md
new file mode 100644
index 00000000..05c4647c
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/README.md
@@ -0,0 +1,17 @@
+# etf_factor_rotation_backtest_runs
+
+
+
+- **snapshot**: `20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d`
+
+- **run_id**: `20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d`
+
+- **fingerprint**: `sha256:a3006b9f096754d0b2876f2138ccba09d0a23e63cffc91a6c3214b73361e0bbb`
+
+- **日期范围**: `2021-01-04 ~ 2026-04-30`
+
+- **审计日志行数**: `1630`
+
+
+
+原始文件压缩保存在 `raw/*.gz`；常用轻量索引见 `views/`；程序读取优先使用 `data/data.parquet`。
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/data/audit_events.parquet b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/data/audit_events.parquet
new file mode 100644
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+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/data/audit_events.parquet
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7a0f53d075da65c3b811cd0a3f39d7ecca119fb5333a49ab71bb2ce62108af52
+size 117948
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/data/data.parquet b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/data/data.parquet
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+version https://git-lfs.github.com/spec/v1
+oid sha256:0b8a48fdd9a0b6985f78fea8db01d95d5a359d3a033d4f686e7e651ed58b6d80
+size 16123
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/dataset.json b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/dataset.json
new file mode 100644
index 00000000..e14c677b
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+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/dataset.json
@@ -0,0 +1,345 @@
+{
+
+  "schema_version": 1,
+
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+
+  "snapshot_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "fingerprint": "sha256:a3006b9f096754d0b2876f2138ccba09d0a23e63cffc91a6c3214b73361e0bbb",
+
+  "created_at": "2026-06-30T19:37:13+00:00",
+
+  "owner": "research-platform",
+
+  "created_by": "research-platform",
+
+  "lifecycle": "active",
+
+  "source": {
+
+    "kind": "joinquant_backtest_run",
+
+    "path": "D:/My Project/Quant Trading/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d"
+
+  },
+
+  "storage": {
+
+    "canonical": "parquet",
+
+    "compression": "zstd",
+
+    "raw": "json.gz/jsonl.gz/md.gz"
+
+  },
+
+  "row_count": 1289,
+
+  "date_range": [
+
+    "2021-01-04",
+
+    "2026-04-30"
+
+  ],
+
+  "run_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "partial": false,
+
+  "missing_required_files": [],
+
+  "summary_metrics": {
+
+    "策略收益": "127.57%",
+
+    "策略年化收益": "17.29%",
+
+    "基准收益": "-7.75%",
+
+    "超额收益": "146.70%",
+
+    "最大回撤": "7.58%",
+
+    "最大回撤区间": "2021-11-22,2022-01-28",
+
+    "阿尔法": "0.141",
+
+    "贝塔": "0.141",
+
+    "夏普比率": "1.591",
+
+    "索提诺比率": "2.352",
+
+    "信息比率": "1.089",
+
+    "策略波动率": "0.084",
+
+    "基准波动率": "0.179",
+
+    "胜率": "0.733",
+
+    "盈亏比": "5.008",
+
+    "日胜率": "0.541",
+
+    "盈利次数": 140,
+
+    "亏损次数": 51
+
+  },
+
+  "source_metadata": {
+
+    "strategy_name": "etf_factor_rotation",
+
+    "strategy_file": "",
+
+    "strategy_dir": "",
+
+    "start_date_requested": "",
+
+    "start_date_effective": "2021-01-01",
+
+    "end_date_requested": "",
+
+    "end_date_effective": "2026-04-30",
+
+    "capital": 100000,
+
+    "backtest_id": "bfc5066102fc7eac2f3dfd3da0276a3d",
+
+    "backtest_url": "",
+
+    "generated_at": "2026-07-01T03:36:53",
+
+    "extraction_method": "joinquant_research_get_backtest",
+
+    "primary_extraction_method": "joinquant_research_get_backtest",
+
+    "fallback_extraction_method": "",
+
+    "research_export_path": "jq_auto_exports/research_backtest_bfc5066102fc7eac2f3dfd3da0276a3d.json",
+
+    "research_downloaded": true,
+
+    "detail_api_used": true,
+
+    "frequency": "1d",
+
+    "py_version": "Python3",
+
+    "internal_backtest_id": "9f29ab61c433f227af01e2ed1cdcff85",
+
+    "audit_token": "etf_factor_rotation-s05-official-current-baseline-20260701033128-41374eef",
+
+    "audit_path": "jq_auto_audit/etf_factor_rotation-s05-official-current-baseline-20260701033128-41374eef.jsonl"
+
+  },
+
+  "audit_line_count": 1630,
+
+  "audit_date_range": [
+
+    "2021-01-01",
+
+    "2026-04-30"
+
+  ],
+
+  "audit_event_counts": {
+
+    "rebalance_order": 813,
+
+    "rebalance_signals": 272,
+
+    "run_end": 1,
+
+    "run_start": 1,
+
+    "weekend_close_execute": 271,
+
+    "weekend_close_plan_cached": 272
+
+  },
+
+  "etf_pool": [
+
+    "159819.XSHE",
+
+    "513100.XSHG",
+
+    "518880.XSHG"
+
+  ],
+
+  "report_files": [
+
+    "backtest_report.md",
+
+    "data-integrity.md"
+
+  ],
+
+  "files": {
+
+    "raw": "raw/source.json.gz",
+
+    "profile_json": "views/profile.json",
+
+    "audit_events": "data/audit_events.parquet",
+
+    "daily_returns": "data/data.parquet",
+
+    "canonical": "data/data.parquet",
+
+    "sample": "views/sample.csv",
+
+    "api_export_source": "raw/api_export.json.gz",
+
+    "detail_api_export_source": "raw/detail_api_export.json.gz",
+
+    "summary_metrics": "raw/summary_metrics.json.gz",
+
+    "audit_log_source": "raw/audit_log.jsonl.gz",
+
+    "daily_returns_source": "raw/daily_returns.md.gz",
+
+    "positioninfo_source": "raw/positioninfo.md.gz",
+
+    "transactioninfo_source": "raw/transactioninfo.md.gz",
+
+    "balances_source": "raw/balances.md.gz",
+
+    "period_risks_source": "raw/period_risks.md.gz",
+
+    "logs_source": "raw/logs.md.gz"
+
+  },
+
+  "raw_file_integrity": {
+
+    "api_export.json": {
+
+      "dataset_file": "raw/api_export.json.gz",
+
+      "original_sha256": "7c347eb465d800422c4f50a761c401156985f1330b3cb90d585b1bd697a89221",
+
+      "compressed_sha256": "ed009f3dcbe7d329e092fa016fe83dc64c3754d1331fc399e6424e059c1f9726",
+
+      "original_bytes": 3784618
+
+    },
+
+    "detail_api_export.json": {
+
+      "dataset_file": "raw/detail_api_export.json.gz",
+
+      "original_sha256": "3ccd53bb53f1e860ba5842f364cc4fec65245e29d8a0f04062d8023fb21047f4",
+
+      "compressed_sha256": "333d4d723204b27a3588141bee9d6b8bf12bc17f2d71a2e855c6d3443d2791b1",
+
+      "original_bytes": 4370413
+
+    },
+
+    "summary_metrics.json": {
+
+      "dataset_file": "raw/summary_metrics.json.gz",
+
+      "original_sha256": "317b30d9a2b2f3f72bb2dc7210bde94ef9e389e7939d8423c2b1f5ee5df3e21b",
+
+      "compressed_sha256": "135fb1ab5e2fa8cf0bcebadf03780f0ed8d55c488b02372a3b7ccbd393629cc0",
+
+      "original_bytes": 520
+
+    },
+
+    "tabs_raw/audit_log.jsonl": {
+
+      "dataset_file": "raw/audit_log.jsonl.gz",
+
+      "original_sha256": "590310655c88b251a25813ac6ddcd0dd7d318bb88f3a5665a4cf61ca40757e51",
+
+      "compressed_sha256": "8f264094a0c5c4b0c9fa2028fad6c1b77c97cb2cbad15e0880f52b32e83d94ac",
+
+      "original_bytes": 1698903
+
+    },
+
+    "tabs_raw/daily_returns.md": {
+
+      "dataset_file": "raw/daily_returns.md.gz",
+
+      "original_sha256": "fae7f563d4decde5e0f5e2708b6502e4e712b42cb2ce35e8817779cc40060a50",
+
+      "compressed_sha256": "8e31e63bf90b2d042d4f045a290db99eb6f3a0892a34462ee3caea975395f468",
+
+      "original_bytes": 92691
+
+    },
+
+    "tabs_raw/positioninfo.md": {
+
+      "dataset_file": "raw/positioninfo.md.gz",
+
+      "original_sha256": "b66559bf2f878363ba35fa31fa8fcb6e0ad2f6c7249c723448db04164ba99e6b",
+
+      "compressed_sha256": "2e8ffe3c2f7a5df3669a203e25084a9e1974f5a5c0a4e6ba18fc817b35ee87da",
+
+      "original_bytes": 378767
+
+    },
+
+    "tabs_raw/transactioninfo.md": {
+
+      "dataset_file": "raw/transactioninfo.md.gz",
+
+      "original_sha256": "9231003f977b453cf45f5064d02865af7d04a533f92034c9407db117c9e27c8d",
+
+      "compressed_sha256": "5eea156208babdd4921f3702c17e435d5b16c015a4e14341cfc546293f948b86",
+
+      "original_bytes": 31888
+
+    },
+
+    "tabs_raw/balances.md": {
+
+      "dataset_file": "raw/balances.md.gz",
+
+      "original_sha256": "7f0d0c1bee6b6572516b623634b2a9d2169fea08f48e8a6aa033984cc1b09872",
+
+      "compressed_sha256": "a56c0800aceb2f51a891f68cd72f8c15229adebf668d89e8d51ef19b9f3d7ad6",
+
+      "original_bytes": 90521
+
+    },
+
+    "tabs_raw/period_risks.md": {
+
+      "dataset_file": "raw/period_risks.md.gz",
+
+      "original_sha256": "661b2d392c210b2a0a17c1b5c5bfdf78e23dd67d577f87e008166997053e106c",
+
+      "compressed_sha256": "ef3869e5e1cab71c32cb054dbd7d8decb3db98a6eb1c186d32983f8655ec4be4",
+
+      "original_bytes": 62872
+
+    },
+
+    "tabs_raw/logs.md": {
+
+      "dataset_file": "raw/logs.md.gz",
+
+      "original_sha256": "d811c3e0aa782563080368e27c8bd9f2aa226afd30972ddc3c7cba7ca0fa2af3",
+
+      "compressed_sha256": "f01427d06d60706892b923f8c27fba870fa5891fe71b9523b5c79748da6ee971",
+
+      "original_bytes": 290
+
+    }
+
+  }
+
+}
\ No newline at end of file
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/raw/source.json.gz b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/raw/source.json.gz
new file mode 100644
index 00000000..891241d1
Binary files /dev/null and b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/raw/source.json.gz differ
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/views/profile.json b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/views/profile.json
new file mode 100644
index 00000000..d206e0e5
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/views/profile.json
@@ -0,0 +1,49 @@
+{
+  "row_count": 1289,
+  "date_range": [
+    "2021-01-04",
+    "2026-04-30"
+  ],
+  "audit_line_count": 1630,
+  "audit_date_range": [
+    "2021-01-01",
+    "2026-04-30"
+  ],
+  "audit_event_counts": {
+    "rebalance_order": 813,
+    "rebalance_signals": 272,
+    "run_end": 1,
+    "run_start": 1,
+    "weekend_close_execute": 271,
+    "weekend_close_plan_cached": 272
+  },
+  "etf_pool": [
+    "159819.XSHE",
+    "513100.XSHG",
+    "518880.XSHG"
+  ],
+  "summary_metric_keys": [
+    "亏损次数",
+    "信息比率",
+    "基准收益",
+    "基准波动率",
+    "夏普比率",
+    "日胜率",
+    "最大回撤",
+    "最大回撤区间",
+    "盈亏比",
+    "盈利次数",
+    "策略年化收益",
+    "策略收益",
+    "策略波动率",
+    "索提诺比率",
+    "胜率",
+    "贝塔",
+    "超额收益",
+    "阿尔法"
+  ],
+  "report_files": [
+    "backtest_report.md",
+    "data-integrity.md"
+  ]
+}
\ No newline at end of file
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/views/profile.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/views/profile.md
new file mode 100644
index 00000000..dfd80920
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/views/profile.md
@@ -0,0 +1,25 @@
+# 回测 run 概览
+
+- **行数**: `1289`
+- **日期范围**: `2021-01-04 ~ 2026-04-30`
+- **审计日志行数**: `1630`
+- **审计日期范围**: `2021-01-01 ~ 2026-04-30`
+- **ETF 池**: `159819.XSHE, 513100.XSHG, 518880.XSHG`
+
+## 审计事件分布
+
+| 事件类型 | 数量 |
+| --- | ---: |
+| rebalance_order | 813 |
+| rebalance_signals | 272 |
+| run_end | 1 |
+| run_start | 1 |
+| weekend_close_execute | 271 |
+| weekend_close_plan_cached | 272 |
+
+## 报告文件
+
+| 报告文件 |
+| --- |
+| backtest_report.md |
+| data-integrity.md |
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/views/sample.csv b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/views/sample.csv
new file mode 100644
index 00000000..6fcdc0c4
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/views/sample.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bfc99a432f44991880db0203cd037969f52c588ec4751f4c5f3d71b47b54dd81
+size 612
diff --git a/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/views/schema.md b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/views/schema.md
new file mode 100644
index 00000000..14dc0788
--- /dev/null
+++ b/research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/views/schema.md
@@ -0,0 +1,10 @@
+# 回测 run 快照字段
+
+| 视图 | 说明 |
+| --- | --- |
+| `raw/source.json.gz` | 原始 run 文件清单与哈希 |
+| `raw/*.gz` | 压缩保存的原始回测文件 |
+| `data/data.parquet` | 累计收益序列主存储 |
+| `data/audit_events.parquet` | 审计事件主存储 |
+| `views/sample.csv` | 收益序列小样本 |
+| `views/profile.json` | 行数、日期范围、审计日志和报告文件摘要 |
diff --git a/scripts/joinquant_tools/FeishuRelayTools.py b/scripts/joinquant_tools/FeishuRelayTools.py
index c4c003a8..7a392970 100644
--- a/scripts/joinquant_tools/FeishuRelayTools.py
+++ b/scripts/joinquant_tools/FeishuRelayTools.py
@@ -47,6 +47,7 @@
 }
 
 _print = print
+_execution_notice_suppression = None
 
 
 def _log(message):
@@ -318,6 +319,97 @@ def _format_order_summary(summary):
     )
 
 
+def _as_list(value):
+    if value is None:
+        return []
+    try:
+        if hasattr(value, "tolist"):
+            value = value.tolist()
+    except Exception:
+        pass
+    if isinstance(value, (list, tuple)):
+        return list(value)
+    return [value]
+
+
+def _plan_order_summaries(plan):
+    pool_source = plan.get("pool")
+    if pool_source is None:
+        pool_source = plan.get("etf_pool")
+    weights_source = plan.get("target_weights")
+    if weights_source is None:
+        weights_source = plan.get("final_weights")
+    pool = _as_list(pool_source)
+    weights = _as_list(weights_source)
+    values = _as_list(plan.get("target_values"))
+    params = plan.get("params") if isinstance(plan.get("params"), dict) else {}
+    names = _as_list(plan.get("etf_names") or params.get("etf_names"))
+    total_value = _to_float(plan.get("portfolio_total_value"))
+    signal_time = str(plan.get("signal_date") or plan.get("asof_date") or _format_time(None))
+    run_type = plan.get("run_type") or params.get("run_type")
+    summaries = []
+    for index, security in enumerate(pool):
+        target_weight = weights[index] if index < len(weights) else None
+        target_value = values[index] if index < len(values) else None
+        if target_value in (None, "") and total_value is not None:
+            weight_float = _to_float(target_weight)
+            if weight_float is not None:
+                target_value = total_value * weight_float
+        name = names[index] if index < len(names) else _get_security_name(security)
+        summaries.append({
+            "time": signal_time,
+            "action": "信号",
+            "name": name,
+            "security": str(security),
+            "amount": "--",
+            "price": "--",
+            "signed_amount": "--",
+            "trade_value": target_value,
+            "target_weight": target_weight,
+            "run_type": run_type,
+            "strategy": CURRENT_STRATEGY_NAME,
+        })
+    return summaries
+
+
+def report_signal_plan(plan):
+    if not isinstance(plan, dict):
+        _log("信号通知失败: plan 不是 dict")
+        return False
+    orders = _plan_order_summaries(plan)
+    if not orders:
+        _log("信号通知失败: plan 无标的")
+        return False
+    signal_date = plan.get("signal_date") or plan.get("asof_date") or "--"
+    trade_date = plan.get("trade_date") or "next_open"
+    lines = [
+        "信号日期：%s" % signal_date,
+        "计划交易日：%s" % trade_date,
+    ]
+    lines.extend(_format_order_summary(item) for item in orders)
+    run_type = _resolve_items_run_type(orders)
+    message = _build_message(CURRENT_STRATEGY_NAME, lines, SECURITY_KEYWORD, run_type=run_type)
+    batch_id = plan.get("batch_id") or _make_batch_id(CURRENT_STRATEGY_NAME, signal_date, lines)
+    try:
+        return bool(_sender.send(message, batch_id=batch_id, orders=orders))
+    except Exception as exc:
+        _log("信号通知发送异常: %s" % _safe_error_text(exc))
+        return False
+
+
+def suppress_execution_notice(batch_id=None, reason="signal_notice_already_sent"):
+    global _execution_notice_suppression
+    _execution_notice_suppression = {
+        "batch_id": batch_id,
+        "reason": reason,
+    }
+
+
+def resume_execution_notice():
+    global _execution_notice_suppression
+    _execution_notice_suppression = None
+
+
 def _build_message(strategy_name, lines, security_keyword="", run_type=None):
     title = "【%s】飞书交易通知" % strategy_name
     if security_keyword and security_keyword not in title:
@@ -678,6 +770,8 @@ def _install_wrappers(report_func):
 
 
 def _report_order(order_obj, call_context=None):
+    if _execution_notice_suppression is not None:
+        return
     try:
         summary = _summarize_order(order_obj, CURRENT_STRATEGY_NAME, call_context=call_context)
         _buffer.add(summary)
diff --git a/scripts/joinquant_tools/tests/test_feishu_relay_tools.py b/scripts/joinquant_tools/tests/test_feishu_relay_tools.py
index 12b344e5..85563ea0 100644
--- a/scripts/joinquant_tools/tests/test_feishu_relay_tools.py
+++ b/scripts/joinquant_tools/tests/test_feishu_relay_tools.py
@@ -213,6 +213,64 @@ def place_order(context):
     assert reported[0]["target_weight"] == 0.2476
 
 
+def test_report_signal_plan_sends_signal_notice_with_existing_sender(monkeypatch):
+    module = load_module(monkeypatch)
+    sent = []
+    monkeypatch.setattr(
+        module._sender,
+        "send",
+        lambda message, batch_id=None, orders=None: sent.append((message, batch_id, orders)) or True,
+    )
+
+    result = module.report_signal_plan({
+        "batch_id": "signal-batch-1",
+        "signal_date": "2026-05-15",
+        "trade_date": "next_open",
+        "pool": ["513100.XSHG", "518880.XSHG"],
+        "target_weights": [0.2476, 0.0],
+        "target_values": [247600.0, 0.0],
+        "params": {"ExecutionTimingMode": "weekend-close-signal-next-open"},
+    })
+
+    assert result is True
+    message, batch_id, orders = sent[0]
+    assert batch_id == "signal-batch-1"
+    assert "信号日期：2026-05-15" in message
+    assert "计划交易日：next_open" in message
+    assert "513100.XSHG" in message
+    assert orders[0]["action"] == "信号"
+    assert orders[0]["target_weight"] == 0.2476
+    assert orders[0]["trade_value"] == 247600.0
+
+
+def test_report_signal_plan_returns_false_when_notice_not_sent(monkeypatch):
+    module = load_module(monkeypatch)
+    monkeypatch.setattr(module._sender, "send", lambda message, batch_id=None, orders=None: False)
+
+    result = module.report_signal_plan({
+        "batch_id": "signal-batch-1",
+        "signal_date": "2026-05-15",
+        "pool": ["513100.XSHG"],
+        "target_weights": [0.2476],
+    })
+
+    assert result is False
+
+
+def test_suppressed_execution_notice_skips_order_buffer(monkeypatch):
+    module = load_module(monkeypatch)
+    buffered = []
+    monkeypatch.setattr(module._buffer, "add", lambda summary: buffered.append(summary))
+
+    module.suppress_execution_notice(batch_id="signal-batch-1", reason="signal_notice_already_sent")
+    module._report_order(FakeOrder())
+    module.resume_execution_notice()
+    module._report_order(FakeOrder())
+
+    assert len(buffered) == 1
+    assert buffered[0]["security"] == "513100.XSHG"
+
+
 def test_wrapped_order_captures_run_type_from_caller_context(monkeypatch):
     module = load_module(monkeypatch)
     reported = []
diff --git a/scripts/tools/jq_automation/browser.py b/scripts/tools/jq_automation/browser.py
index 948fad3e..514e7008 100644
--- a/scripts/tools/jq_automation/browser.py
+++ b/scripts/tools/jq_automation/browser.py
@@ -166,7 +166,7 @@ async def click_compile(self) -> None:
                 continue
         raise AutomationError("Could not find the JoinQuant compile button")
 
-    async def wait_compile_complete(self, timeout_ms: int = 120_000, poll_ms: int = 500) -> dict[str, Any]:
+    async def wait_compile_complete(self, timeout_ms: int = 300_000, poll_ms: int = 500) -> dict[str, Any]:
         return await wait_for_compile_completion(
             self._require_page(),
             lambda name: self.snippet_reader(name),
@@ -485,7 +485,7 @@ async def wait_for_compile_completion(
     page: Any,
     snippet_reader: Callable[[str], str],
     *,
-    timeout_ms: int = 120_000,
+    timeout_ms: int = 300_000,
     poll_ms: int = 500,
 ) -> dict[str, Any]:
     source = snippet_reader("compile.js")
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/all_data.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/all_data.json
new file mode 100644
index 00000000..54d457ea
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/all_data.json
@@ -0,0 +1,105 @@
+{
+  "api_export_json": "D:\\My Project\\Quant Trading\\strategies\\etf_factor_rotation\\backtest_runs\\20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0\\api_export.json",
+  "extraction_method": "research_bundle",
+  "generated_at": "2026-06-30T16:14:45.885507+00:00",
+  "counts": {
+    "results": 1289,
+    "positions": 2391,
+    "orders": 379,
+    "records": 0,
+    "balances": 1289,
+    "period_risk_tabs": 10,
+    "audit_log_lines": 1090
+  },
+  "partial": {
+    "results": false,
+    "positions": false,
+    "orders": false,
+    "records": false,
+    "risk": false,
+    "period_risks": false,
+    "balances": false,
+    "logs": true,
+    "audit_log": false
+  },
+  "primary_extraction_method": "joinquant_research_get_backtest",
+  "fallback_extraction_method": "",
+  "research_export_path": "jq_auto_exports/research_backtest_8d074a3098c6308f791ea33d8806d6f0.json",
+  "research_downloaded": true,
+  "detail_api_used": true,
+  "tabs": {
+    "daily_returns": {
+      "path": "tabs_raw/daily_returns.md",
+      "partial": false,
+      "record_count": 1289
+    },
+    "transactioninfo": {
+      "path": "tabs_raw/transactioninfo.md",
+      "partial": false,
+      "record_count": 379
+    },
+    "positioninfo": {
+      "path": "tabs_raw/positioninfo.md",
+      "partial": false,
+      "record_count": 2391
+    },
+    "records": {
+      "path": "tabs_raw/records.md",
+      "partial": false,
+      "record_count": 0
+    },
+    "balances": {
+      "path": "tabs_raw/balances.md",
+      "partial": false,
+      "record_count": 1289
+    },
+    "risk": {
+      "path": "tabs_raw/risk.md",
+      "partial": false,
+      "record_count": 31
+    },
+    "period_risks": {
+      "path": "tabs_raw/period_risks.md",
+      "partial": false,
+      "record_count": 10
+    },
+    "profile": {
+      "path": "tabs_raw/profile.md",
+      "partial": false,
+      "record_count": 7577
+    },
+    "logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true,
+      "record_count": 143
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "partial": false,
+      "record_count": 1090
+    }
+  },
+  "note": "Generated from JoinQuant research get_backtest() schema v3 bundle. Platform logs are not provided by get_backtest().",
+  "integrity_status": "complete",
+  "integrity_issues": [],
+  "sources": {
+    "research": {
+      "path": "api_export.json",
+      "present": true,
+      "method": "joinquant_research_get_backtest"
+    },
+    "detail_api": {
+      "path": "detail_api_export.json",
+      "present": true
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "present": true,
+      "count": 1090
+    },
+    "platform_logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true
+    }
+  }
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/api_export.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/api_export.json
new file mode 100644
index 00000000..08b905ba
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/api_export.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_file": "raw/api_export.json.gz",
+  "original_path": "api_export.json",
+  "original_sha256": "f7a967d3b67c2c52e049aeeaa3dafc0920f3008f0cd495e2ad5cb33eb4ae4221",
+  "compressed_sha256": "7c8fa08bc9602a269a706e74c2d6561377418719ac90c7ec2e2572ce59f5af34",
+  "original_bytes": 3356598
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/detail_api_export.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/detail_api_export.json
new file mode 100644
index 00000000..da9de39e
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/detail_api_export.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_file": "raw/detail_api_export.json.gz",
+  "original_path": "detail_api_export.json",
+  "original_sha256": "82f066ba6c46bf633ff5487715febaee63804667bac0332d4d7da0d0805df0bf",
+  "compressed_sha256": "d96601104c203561628d12a21f6c79dc08ff11f2833fb7d3e3783ab25b6f2488",
+  "original_bytes": 4350900
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/integrity.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/integrity.json
new file mode 100644
index 00000000..eeb967a3
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/integrity.json
@@ -0,0 +1,153 @@
+{
+  "status": "complete",
+  "generated_at": "2026-06-30T16:14:45.927252+00:00",
+  "issues": [],
+  "checks": [
+    {
+      "name": "research_bundle",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": null,
+      "partial": null,
+      "message": "research get_backtest bundle is required"
+    },
+    {
+      "name": "detail_api_bundle",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": null,
+      "partial": null,
+      "message": "detail API bundle is required"
+    },
+    {
+      "name": "metadata",
+      "required": true,
+      "status": "pass",
+      "source": "metadata.json",
+      "count": null,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "summary_metrics",
+      "required": true,
+      "status": "pass",
+      "source": "summary_metrics.json",
+      "count": null,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "research_results",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 1289,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_positions",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 2391,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_orders",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 379,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_risk",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 31,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_results",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 1485,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_transactions",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 379,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_positions",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 3680,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_risk_tabs",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 640,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "platform_logs",
+      "required": false,
+      "status": "warn",
+      "source": "detail_api_export.json",
+      "count": 1000,
+      "partial": true,
+      "message": "platform logs may be partial; audit_log is canonical"
+    },
+    {
+      "name": "audit_log",
+      "required": true,
+      "status": "pass",
+      "source": "tabs_raw/audit_log.jsonl",
+      "count": 1090,
+      "partial": false,
+      "message": ""
+    }
+  ],
+  "sources": {
+    "research": {
+      "path": "api_export.json",
+      "present": true,
+      "method": "joinquant_research_get_backtest"
+    },
+    "detail_api": {
+      "path": "detail_api_export.json",
+      "present": true
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "present": true,
+      "count": 1090
+    },
+    "platform_logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true
+    }
+  }
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/metadata.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/metadata.json
new file mode 100644
index 00000000..e9a30323
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/metadata.json
@@ -0,0 +1,26 @@
+{
+  "strategy_name": "etf_factor_rotation",
+  "run_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "strategy_file": "",
+  "strategy_dir": "",
+  "start_date_requested": "",
+  "start_date_effective": "2021-01-01",
+  "end_date_requested": "",
+  "end_date_effective": "2026-04-30",
+  "capital": 100000,
+  "backtest_id": "8d074a3098c6308f791ea33d8806d6f0",
+  "joinquant_backtest_id": "8d074a3098c6308f791ea33d8806d6f0",
+  "backtest_url": "",
+  "generated_at": "2026-07-01T00:14:34",
+  "extraction_method": "joinquant_research_get_backtest",
+  "primary_extraction_method": "joinquant_research_get_backtest",
+  "fallback_extraction_method": "",
+  "research_export_path": "jq_auto_exports/research_backtest_8d074a3098c6308f791ea33d8806d6f0.json",
+  "research_downloaded": true,
+  "detail_api_used": true,
+  "frequency": "1d",
+  "py_version": "Python3",
+  "internal_backtest_id": "234573daf021757752090358c356f903",
+  "audit_token": "etf_factor_rotation-s01-baseline-original-20260701001028-3e0b4107",
+  "audit_path": "jq_auto_audit/etf_factor_rotation-s01-baseline-original-20260701001028-3e0b4107.jsonl"
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/backtest_report.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/backtest_report.md
new file mode 100644
index 00000000..0a3f24d9
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/backtest_report.md
@@ -0,0 +1,32 @@
+# 回测数据汇总
+
+- 策略名称：etf_factor_rotation
+- 回测 ID：8d074a3098c6308f791ea33d8806d6f0
+- 区间：2021-01-01 至 2026-04-30
+- 提取方式：聚宽研究环境 get_backtest()；详情页接口仅作补充。
+
+## 核心指标
+
+| 指标 | 值 |
+| --- | --- |
+| 策略收益 | 127.12% |
+| 策略年化收益 | 17.25% |
+| 基准收益 | -7.75% |
+| 超额收益 | 146.21% |
+| 最大回撤 | 7.60% |
+| 夏普比率 | 1.582 |
+| 阿尔法 | 0.140 |
+| 贝塔 | 0.139 |
+| 信息比率 | 1.084 |
+
+## 数据覆盖
+
+| 数据 | 记录数 | 完整度 |
+| --- | ---: | --- |
+| 每日收益 | 1289 | 完整 |
+| 每日持仓&收益 | 2391 | 完整 |
+| 订单/交易 | 379 | 完整 |
+| record 记录 | 0 | 完整 |
+| 每日账户市值 | 1289 | 完整 |
+| 分期风险 | 10 | 完整 |
+| 平台日志 |  | 详情页接口部分 |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/data-integrity.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/data-integrity.md
new file mode 100644
index 00000000..49ee492d
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/data-integrity.md
@@ -0,0 +1,26 @@
+# 数据完整性报告
+
+- 状态：complete
+- 生成时间：2026-06-30T16:14:45.927252+00:00
+
+## 问题
+- 无
+
+## 检查项
+
+| 检查项 | 必须 | 状态 | 来源 | 记录数 | partial | 说明 |
+| --- | --- | --- | --- | ---: | --- | --- |
+| research_bundle | 是 | pass | api_export.json |  |  | research get_backtest bundle is required |
+| detail_api_bundle | 是 | pass | detail_api_export.json |  |  | detail API bundle is required |
+| metadata | 是 | pass | metadata.json |  |  |  |
+| summary_metrics | 是 | pass | summary_metrics.json |  |  |  |
+| research_results | 是 | pass | api_export.json | 1289 | False |  |
+| research_positions | 是 | pass | api_export.json | 2391 | False |  |
+| research_orders | 是 | pass | api_export.json | 379 | False |  |
+| research_risk | 是 | pass | api_export.json | 31 | False |  |
+| detail_results | 是 | pass | detail_api_export.json | 1485 | False |  |
+| detail_transactions | 是 | pass | detail_api_export.json | 379 | False |  |
+| detail_positions | 是 | pass | detail_api_export.json | 3680 | False |  |
+| detail_risk_tabs | 是 | pass | detail_api_export.json | 640 |  |  |
+| platform_logs | 否 | warn | detail_api_export.json | 1000 | True | platform logs may be partial; audit_log is canonical |
+| audit_log | 是 | pass | tabs_raw/audit_log.jsonl | 1090 | False |  |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/summary_metrics.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/summary_metrics.json
new file mode 100644
index 00000000..943b224b
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/summary_metrics.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_file": "raw/summary_metrics.json.gz",
+  "original_path": "summary_metrics.json",
+  "original_sha256": "74e9b525f50b3d66d1fdd881ac3cff7fa27b499260ba211f5392035121d16ea2",
+  "compressed_sha256": "b57ad5f2a7632af8588e874104c77b85537c143cbd613f9e7c3035081d7764a1",
+  "original_bytes": 520
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/audit_log.jsonl b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/audit_log.jsonl
new file mode 100644
index 00000000..856b76a2
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/audit_log.jsonl
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_file": "raw/audit_log.jsonl.gz",
+  "original_path": "tabs_raw/audit_log.jsonl",
+  "original_sha256": "4b9c3166531201de33fccec8dce07ad33e80f4f70420cc15bb7aa2c9c56620ff",
+  "compressed_sha256": "424c1b1d9800c7a7c50d489ca18d8325b34a4bcd6013e8c8c978649c56fa0a3c",
+  "original_bytes": 1318032
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/balances.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/balances.md
new file mode 100644
index 00000000..725ade46
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/balances.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_file": "raw/balances.md.gz",
+  "original_path": "tabs_raw/balances.md",
+  "original_sha256": "5d4c2b9f53deda2fbdd7e5f7c1cd0f8f9e13cc5b3540fea21d12e263a7937d74",
+  "compressed_sha256": "9bff925058a9f54ab8623d4ec4efa31ba12a76621731f5e532f9e546dbc03be8",
+  "original_bytes": 90889
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/daily_returns.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/daily_returns.md
new file mode 100644
index 00000000..70ff19a9
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/daily_returns.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_file": "raw/daily_returns.md.gz",
+  "original_path": "tabs_raw/daily_returns.md",
+  "original_sha256": "73afb8b1c7783773a152041e2d7fd3a96ff1fec6cfc3bc7a8758f63c08073970",
+  "compressed_sha256": "c4b51782dd103013d6239ea85b91f3892829ad21546b10ffc05cc520457e5578",
+  "original_bytes": 92875
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/logs.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/logs.md
new file mode 100644
index 00000000..be91cd0b
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/logs.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_file": "raw/logs.md.gz",
+  "original_path": "tabs_raw/logs.md",
+  "original_sha256": "d811c3e0aa782563080368e27c8bd9f2aa226afd30972ddc3c7cba7ca0fa2af3",
+  "compressed_sha256": "05269fff42e0b0e739e4003fbb5694a7160ca23692873edd5f4f022b419d0812",
+  "original_bytes": 290
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/period_risks.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/period_risks.md
new file mode 100644
index 00000000..3e357b93
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/period_risks.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_file": "raw/period_risks.md.gz",
+  "original_path": "tabs_raw/period_risks.md",
+  "original_sha256": "00b68a33695b80da0837551ca441973d343584a66a44c0a43844f7412ddc7036",
+  "compressed_sha256": "90a9e983600498389a278aa856e10118fd99a6fe2e42eb61f046667a8d8afab6",
+  "original_bytes": 62839
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/positioninfo.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/positioninfo.md
new file mode 100644
index 00000000..4d531020
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/positioninfo.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_file": "raw/positioninfo.md.gz",
+  "original_path": "tabs_raw/positioninfo.md",
+  "original_sha256": "e2f334231893babfb1b91d1076f5f407d541713c23a841a9443216e1a6057e8e",
+  "compressed_sha256": "3245ae8b76e39d33c4d89e7014de3980458d6da40764819dfb754ee08bc73f74",
+  "original_bytes": 379897
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/profile.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/profile.md
new file mode 100644
index 00000000..77019b4d
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/profile.md
@@ -0,0 +1,501 @@
+# 性能分析
+
+## fund_code
+
+- 总耗时：0.012156s
+
+```text
+Total time: 0.012156 s
+File: /tmp/strategy/user_code.py
+Function: fund_code at line 128
+```
+
+## format_etf_name
+
+- 总耗时：0.080615s
+
+```text
+Total time: 0.080615 s
+File: /tmp/strategy/user_code.py
+Function: format_etf_name at line 130
+```
+
+## build_etf_display_names
+
+- 总耗时：0.156018s
+
+```text
+Total time: 0.156018 s
+File: /tmp/strategy/user_code.py
+Function: build_etf_display_names at line 143
+```
+
+## fetch_etf_official_name
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: fetch_etf_official_name at line 150
+```
+
+## load_etf_display_names
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: load_etf_display_names at line 160
+```
+
+## _audit_jsonable
+
+- 总耗时：0.281633s
+
+```text
+Total time: 0.281633 s
+File: /tmp/strategy/user_code.py
+Function: _audit_jsonable at line 168
+```
+
+## _context_time_fields
+
+- 总耗时：0.197152s
+
+```text
+Total time: 0.197152 s
+File: /tmp/strategy/user_code.py
+Function: _context_time_fields at line 197
+```
+
+## audit_event
+
+- 总耗时：19.0657s
+
+```text
+Total time: 19.0657 s
+File: /tmp/strategy/user_code.py
+Function: audit_event at line 204
+```
+
+## _copy_runtime_default
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: _copy_runtime_default at line 218
+```
+
+## _runtime_param
+
+- 总耗时：0.028346s
+
+```text
+Total time: 0.028346 s
+File: /tmp/strategy/user_code.py
+Function: _runtime_param at line 226
+```
+
+## _runtime_list_param
+
+- 总耗时：0.012896s
+
+```text
+Total time: 0.012896 s
+File: /tmp/strategy/user_code.py
+Function: _runtime_list_param at line 230
+```
+
+## snapshot_params
+
+- 总耗时：0.129582s
+
+```text
+Total time: 0.129582 s
+File: /tmp/strategy/user_code.py
+Function: snapshot_params at line 235
+```
+
+## validate_params
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: validate_params at line 325
+```
+
+## resolve_ma_long_windows
+
+- 总耗时：0.001979s
+
+```text
+Total time: 0.001979 s
+File: /tmp/strategy/user_code.py
+Function: resolve_ma_long_windows at line 413
+```
+
+## resolve_crowd_thresholds
+
+- 总耗时：0.003219s
+
+```text
+Total time: 0.003219 s
+File: /tmp/strategy/user_code.py
+Function: resolve_crowd_thresholds at line 418
+```
+
+## resolve_crowd_ret_windows
+
+- 总耗时：0.001763s
+
+```text
+Total time: 0.001763 s
+File: /tmp/strategy/user_code.py
+Function: resolve_crowd_ret_windows at line 427
+```
+
+## initialize
+
+- 总耗时：0.05712s
+
+```text
+Total time: 0.05712 s
+File: /tmp/strategy/user_code.py
+Function: initialize at line 434
+```
+
+## set_parameter
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: set_parameter at line 491
+```
+
+## _log_step
+
+- 总耗时：0.907857s
+
+```text
+Total time: 0.907857 s
+File: /tmp/strategy/user_code.py
+Function: _log_step at line 560
+```
+
+## compose_raw_weights
+
+- 总耗时：0.004493s
+
+```text
+Total time: 0.004493 s
+File: /tmp/strategy/user_code.py
+Function: compose_raw_weights at line 566
+```
+
+## _context_trade_date
+
+- 总耗时：0.023234s
+
+```text
+Total time: 0.023234 s
+File: /tmp/strategy/user_code.py
+Function: _context_trade_date at line 576
+```
+
+## build_rebalance_plan
+
+- 总耗时：63.4462s
+
+```text
+Total time: 63.4462 s
+File: /tmp/strategy/user_code.py
+Function: build_rebalance_plan at line 581
+```
+
+## weekly_check
+
+- 总耗时：79.5893s
+
+```text
+Total time: 79.5893 s
+File: /tmp/strategy/user_code.py
+Function: weekly_check at line 646
+```
+
+## prepare_delay_only_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: prepare_delay_only_rebalance at line 649
+```
+
+## execute_pending_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: execute_pending_rebalance at line 660
+```
+
+## mark_live_like_signal_day
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: mark_live_like_signal_day at line 688
+```
+
+## execute_live_like_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: execute_live_like_rebalance at line 697
+```
+
+## normalize_field_frame
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: normalize_field_frame at line 735
+```
+
+## compute_history_count
+
+- 总耗时：0.004626s
+
+```text
+Total time: 0.004626 s
+File: /tmp/strategy/user_code.py
+Function: compute_history_count at line 744
+```
+
+## fetch_field
+
+- 总耗时：30.9272s
+
+```text
+Total time: 30.9272 s
+File: /tmp/strategy/user_code.py
+Function: fetch_field at line 754
+```
+
+## get_history_data
+
+- 总耗时：32.0145s
+
+```text
+Total time: 32.0145 s
+File: /tmp/strategy/user_code.py
+Function: get_history_data at line 774
+```
+
+## compute_trend_gates
+
+- 总耗时：0.79665s
+
+```text
+Total time: 0.79665 s
+File: /tmp/strategy/user_code.py
+Function: compute_trend_gates at line 786
+```
+
+## compute_momentum_scores
+
+- 总耗时：1.96928s
+
+```text
+Total time: 1.96928 s
+File: /tmp/strategy/user_code.py
+Function: compute_momentum_scores at line 802
+```
+
+## select_topk
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: select_topk at line 828
+```
+
+## compute_rp_weights
+
+- 总耗时：0.463371s
+
+```text
+Total time: 0.463371 s
+File: /tmp/strategy/user_code.py
+Function: compute_rp_weights at line 837
+```
+
+## compute_rsrs_multipliers
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_multipliers at line 866
+```
+
+## compute_rsrs_adjusted_scores
+
+- 总耗时：10.4507s
+
+```text
+Total time: 10.4507 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_adjusted_scores at line 875
+```
+
+## compute_momentum_tilt_multipliers
+
+- 总耗时：0.029982s
+
+```text
+Total time: 0.029982 s
+File: /tmp/strategy/user_code.py
+Function: compute_momentum_tilt_multipliers at line 918
+```
+
+## compute_rsrs_tilt_multipliers
+
+- 总耗时：10.5222s
+
+```text
+Total time: 10.5222 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_tilt_multipliers at line 939
+```
+
+## apply_relative_tilts
+
+- 总耗时：0.01544s
+
+```text
+Total time: 0.01544 s
+File: /tmp/strategy/user_code.py
+Function: apply_relative_tilts at line 956
+```
+
+## compute_crowd_penalties
+
+- 总耗时：9.32494s
+
+```text
+Total time: 9.32494 s
+File: /tmp/strategy/user_code.py
+Function: compute_crowd_penalties at line 972
+```
+
+## percentile_rank
+
+- 总耗时：2.23243s
+
+```text
+Total time: 2.23243 s
+File: /tmp/strategy/user_code.py
+Function: percentile_rank at line 1040
+```
+
+## compute_portfolio_vol_scale_detail
+
+- 总耗时：0.36691s
+
+```text
+Total time: 0.36691 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_scale_detail at line 1045
+```
+
+## compute_portfolio_vol_scale
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_scale at line 1076
+```
+
+## compute_portfolio_vol_asset_scales
+
+- 总耗时：0.922613s
+
+```text
+Total time: 0.922613 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_asset_scales at line 1079
+```
+
+## apply_fixed_gold_vol_relief
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: apply_fixed_gold_vol_relief at line 1096
+```
+
+## apply_dynamic_marginal_vol_relief
+
+- 总耗时：0.522912s
+
+```text
+Total time: 0.522912 s
+File: /tmp/strategy/user_code.py
+Function: apply_dynamic_marginal_vol_relief at line 1119
+```
+
+## select_dynamic_marginal_relief_asset
+
+- 总耗时：0.50953s
+
+```text
+Total time: 0.50953 s
+File: /tmp/strategy/user_code.py
+Function: select_dynamic_marginal_relief_asset at line 1140
+```
+
+## apply_weight_constraints
+
+- 总耗时：0.009596s
+
+```text
+Total time: 0.009596 s
+File: /tmp/strategy/user_code.py
+Function: apply_weight_constraints at line 1175
+```
+
+## execute_rebalance
+
+- 总耗时：16.039s
+
+```text
+Total time: 16.039 s
+File: /tmp/strategy/user_code.py
+Function: execute_rebalance at line 1190
+```
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/records.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/records.md
new file mode 100644
index 00000000..8043b956
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/records.md
@@ -0,0 +1,3 @@
+# Record 记录
+
+(无数据)
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/risk.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/risk.md
new file mode 100644
index 00000000..8a0e3018
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/risk.md
@@ -0,0 +1,37 @@
+# 风险指标
+
+- 记录数：31
+
+| metric | value |
+| --- | --- |
+| __version | 101 |
+| algorithm_return | 1.2711970657999987 |
+| algorithm_volatility | 0.0837151468155677 |
+| alpha | 0.14018014573154694 |
+| annual_algo_return | 0.1724523289382165 |
+| annual_bm_return | -0.01552798313301329 |
+| avg_excess_return | 0.0007593171623250612 |
+| avg_position_days | 797.0 |
+| avg_trade_return | 0.05033239407731931 |
+| benchmark_return | -0.07752074822165167 |
+| benchmark_volatility | 0.17880949192018716 |
+| beta | 0.13916977273997175 |
+| day_win_ratio | 0.5415050426687354 |
+| excess_return | 1.4620576142190638 |
+| excess_return_max_drawdown | 0.21387413831505275 |
+| excess_return_max_drawdown_period | ['2024-09-13', '2024-10-08'] |
+| excess_return_sharpe | 0.8701734691377453 |
+| information | 1.0838290169189766 |
+| lose_count | 50 |
+| max_drawdown | 0.07598434316029279 |
+| max_drawdown_period | ['2021-11-22', '2022-01-28'] |
+| max_leverage | 0.0 |
+| period_label | 2026-04 |
+| profit_loss_ratio | 4.96608883055434 |
+| sharpe | 1.5821787809799983 |
+| sortino | 2.3459743826632042 |
+| trading_days | 1289 |
+| treasury_return | 0.21282191780821919 |
+| turnover_rate | 0.02053831413513158 |
+| win_count | 142 |
+| win_ratio | 0.7395833333333334 |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/transactioninfo.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/transactioninfo.md
new file mode 100644
index 00000000..30495f02
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/tabs_raw/transactioninfo.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+  "dataset_file": "raw/transactioninfo.md.gz",
+  "original_path": "tabs_raw/transactioninfo.md",
+  "original_sha256": "ec6ada5cd42a5306b4b1f739dce3be3df953f16ffc40a6262dc3c6579ac1809b",
+  "compressed_sha256": "a342acd478bf91911ecf7f9258321e5b305c5f5a651bc9dd04863eb104842620",
+  "original_bytes": 31967
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/all_data.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/all_data.json
new file mode 100644
index 00000000..77b10f0b
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/all_data.json
@@ -0,0 +1,105 @@
+{
+  "api_export_json": "D:\\My Project\\Quant Trading\\strategies\\etf_factor_rotation\\backtest_runs\\20260701-0025-bt0d4e21c752867aa36b89ee13d7540352\\api_export.json",
+  "extraction_method": "research_bundle",
+  "generated_at": "2026-06-30T16:27:44.127711+00:00",
+  "counts": {
+    "results": 1289,
+    "positions": 2415,
+    "orders": 373,
+    "records": 0,
+    "balances": 1289,
+    "period_risk_tabs": 10,
+    "audit_log_lines": 1903
+  },
+  "partial": {
+    "results": false,
+    "positions": false,
+    "orders": false,
+    "records": false,
+    "risk": false,
+    "period_risks": false,
+    "balances": false,
+    "logs": true,
+    "audit_log": false
+  },
+  "primary_extraction_method": "joinquant_research_get_backtest",
+  "fallback_extraction_method": "",
+  "research_export_path": "jq_auto_exports/research_backtest_0d4e21c752867aa36b89ee13d7540352.json",
+  "research_downloaded": true,
+  "detail_api_used": true,
+  "tabs": {
+    "daily_returns": {
+      "path": "tabs_raw/daily_returns.md",
+      "partial": false,
+      "record_count": 1289
+    },
+    "transactioninfo": {
+      "path": "tabs_raw/transactioninfo.md",
+      "partial": false,
+      "record_count": 373
+    },
+    "positioninfo": {
+      "path": "tabs_raw/positioninfo.md",
+      "partial": false,
+      "record_count": 2415
+    },
+    "records": {
+      "path": "tabs_raw/records.md",
+      "partial": false,
+      "record_count": 0
+    },
+    "balances": {
+      "path": "tabs_raw/balances.md",
+      "partial": false,
+      "record_count": 1289
+    },
+    "risk": {
+      "path": "tabs_raw/risk.md",
+      "partial": false,
+      "record_count": 31
+    },
+    "period_risks": {
+      "path": "tabs_raw/period_risks.md",
+      "partial": false,
+      "record_count": 10
+    },
+    "profile": {
+      "path": "tabs_raw/profile.md",
+      "partial": false,
+      "record_count": 8331
+    },
+    "logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true,
+      "record_count": 143
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "partial": false,
+      "record_count": 1903
+    }
+  },
+  "note": "Generated from JoinQuant research get_backtest() schema v3 bundle. Platform logs are not provided by get_backtest().",
+  "integrity_status": "complete",
+  "integrity_issues": [],
+  "sources": {
+    "research": {
+      "path": "api_export.json",
+      "present": true,
+      "method": "joinquant_research_get_backtest"
+    },
+    "detail_api": {
+      "path": "detail_api_export.json",
+      "present": true
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "present": true,
+      "count": 1903
+    },
+    "platform_logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true
+    }
+  }
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/api_export.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/api_export.json
new file mode 100644
index 00000000..c1e72d4c
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/api_export.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_file": "raw/api_export.json.gz",
+  "original_path": "api_export.json",
+  "original_sha256": "9bbff9ea33c7a3eefad1611590f0a759af491ef9a17819a873b228c6a74b48c3",
+  "compressed_sha256": "86eeeea86d10eabf501fd49cb8a9853f45547d03ac43242f24bce433ca7c89da",
+  "original_bytes": 3657616
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/detail_api_export.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/detail_api_export.json
new file mode 100644
index 00000000..d31cc19f
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/detail_api_export.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_file": "raw/detail_api_export.json.gz",
+  "original_path": "detail_api_export.json",
+  "original_sha256": "e312b3f0bcd00a020c98131ff2a1178cc34ce07ca929b366d49f4098931a70da",
+  "compressed_sha256": "061144d15485e32f095850bc9afc983e604e6a14ef02cfee08625e34ea5d8c5a",
+  "original_bytes": 4383483
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/integrity.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/integrity.json
new file mode 100644
index 00000000..7ddcbb6c
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/integrity.json
@@ -0,0 +1,153 @@
+{
+  "status": "complete",
+  "generated_at": "2026-06-30T16:27:44.168833+00:00",
+  "issues": [],
+  "checks": [
+    {
+      "name": "research_bundle",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": null,
+      "partial": null,
+      "message": "research get_backtest bundle is required"
+    },
+    {
+      "name": "detail_api_bundle",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": null,
+      "partial": null,
+      "message": "detail API bundle is required"
+    },
+    {
+      "name": "metadata",
+      "required": true,
+      "status": "pass",
+      "source": "metadata.json",
+      "count": null,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "summary_metrics",
+      "required": true,
+      "status": "pass",
+      "source": "summary_metrics.json",
+      "count": null,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "research_results",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 1289,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_positions",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 2415,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_orders",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 373,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_risk",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 31,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_results",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 1485,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_transactions",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 373,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_positions",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 3704,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_risk_tabs",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 640,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "platform_logs",
+      "required": false,
+      "status": "warn",
+      "source": "detail_api_export.json",
+      "count": 1000,
+      "partial": true,
+      "message": "platform logs may be partial; audit_log is canonical"
+    },
+    {
+      "name": "audit_log",
+      "required": true,
+      "status": "pass",
+      "source": "tabs_raw/audit_log.jsonl",
+      "count": 1903,
+      "partial": false,
+      "message": ""
+    }
+  ],
+  "sources": {
+    "research": {
+      "path": "api_export.json",
+      "present": true,
+      "method": "joinquant_research_get_backtest"
+    },
+    "detail_api": {
+      "path": "detail_api_export.json",
+      "present": true
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "present": true,
+      "count": 1903
+    },
+    "platform_logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true
+    }
+  }
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/metadata.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/metadata.json
new file mode 100644
index 00000000..604512e0
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/metadata.json
@@ -0,0 +1,26 @@
+{
+  "strategy_name": "etf_factor_rotation",
+  "run_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "strategy_file": "",
+  "strategy_dir": "",
+  "start_date_requested": "",
+  "start_date_effective": "2021-01-01",
+  "end_date_requested": "",
+  "end_date_effective": "2026-04-30",
+  "capital": 100000,
+  "backtest_id": "0d4e21c752867aa36b89ee13d7540352",
+  "joinquant_backtest_id": "0d4e21c752867aa36b89ee13d7540352",
+  "backtest_url": "",
+  "generated_at": "2026-07-01T00:27:32",
+  "extraction_method": "joinquant_research_get_backtest",
+  "primary_extraction_method": "joinquant_research_get_backtest",
+  "fallback_extraction_method": "",
+  "research_export_path": "jq_auto_exports/research_backtest_0d4e21c752867aa36b89ee13d7540352.json",
+  "research_downloaded": true,
+  "detail_api_used": true,
+  "frequency": "1d",
+  "py_version": "Python3",
+  "internal_backtest_id": "d79fe48b94af96dafe698c1361f19fa9",
+  "audit_token": "etf_factor_rotation-s02-logic3-code-variant-20260701002504-55d17183",
+  "audit_path": "jq_auto_audit/etf_factor_rotation-s02-logic3-code-variant-20260701002504-55d17183.jsonl"
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/backtest_report.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/backtest_report.md
new file mode 100644
index 00000000..908dabfd
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/backtest_report.md
@@ -0,0 +1,32 @@
+# 回测数据汇总
+
+- 策略名称：etf_factor_rotation
+- 回测 ID：0d4e21c752867aa36b89ee13d7540352
+- 区间：2021-01-01 至 2026-04-30
+- 提取方式：聚宽研究环境 get_backtest()；详情页接口仅作补充。
+
+## 核心指标
+
+| 指标 | 值 |
+| --- | --- |
+| 策略收益 | 120.85% |
+| 策略年化收益 | 16.61% |
+| 基准收益 | -7.75% |
+| 超额收益 | 139.41% |
+| 最大回撤 | 11.66% |
+| 夏普比率 | 1.543 |
+| 阿尔法 | 0.134 |
+| 贝塔 | 0.134 |
+| 信息比率 | 1.047 |
+
+## 数据覆盖
+
+| 数据 | 记录数 | 完整度 |
+| --- | ---: | --- |
+| 每日收益 | 1289 | 完整 |
+| 每日持仓&收益 | 2415 | 完整 |
+| 订单/交易 | 373 | 完整 |
+| record 记录 | 0 | 完整 |
+| 每日账户市值 | 1289 | 完整 |
+| 分期风险 | 10 | 完整 |
+| 平台日志 |  | 详情页接口部分 |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/data-integrity.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/data-integrity.md
new file mode 100644
index 00000000..bde036c3
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/report/data-integrity.md
@@ -0,0 +1,26 @@
+# 数据完整性报告
+
+- 状态：complete
+- 生成时间：2026-06-30T16:27:44.168833+00:00
+
+## 问题
+- 无
+
+## 检查项
+
+| 检查项 | 必须 | 状态 | 来源 | 记录数 | partial | 说明 |
+| --- | --- | --- | --- | ---: | --- | --- |
+| research_bundle | 是 | pass | api_export.json |  |  | research get_backtest bundle is required |
+| detail_api_bundle | 是 | pass | detail_api_export.json |  |  | detail API bundle is required |
+| metadata | 是 | pass | metadata.json |  |  |  |
+| summary_metrics | 是 | pass | summary_metrics.json |  |  |  |
+| research_results | 是 | pass | api_export.json | 1289 | False |  |
+| research_positions | 是 | pass | api_export.json | 2415 | False |  |
+| research_orders | 是 | pass | api_export.json | 373 | False |  |
+| research_risk | 是 | pass | api_export.json | 31 | False |  |
+| detail_results | 是 | pass | detail_api_export.json | 1485 | False |  |
+| detail_transactions | 是 | pass | detail_api_export.json | 373 | False |  |
+| detail_positions | 是 | pass | detail_api_export.json | 3704 | False |  |
+| detail_risk_tabs | 是 | pass | detail_api_export.json | 640 |  |  |
+| platform_logs | 否 | warn | detail_api_export.json | 1000 | True | platform logs may be partial; audit_log is canonical |
+| audit_log | 是 | pass | tabs_raw/audit_log.jsonl | 1903 | False |  |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/summary_metrics.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/summary_metrics.json
new file mode 100644
index 00000000..3e4efc77
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/summary_metrics.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_file": "raw/summary_metrics.json.gz",
+  "original_path": "summary_metrics.json",
+  "original_sha256": "98d1bf471f920ed60c2e5b707c6ee82a302cda99ba5019d128585bfc2b298125",
+  "compressed_sha256": "77876f051fe717cab7f6fd148ef2ae02be048c0ed4206decdea1bc8e12a2c2c0",
+  "original_bytes": 521
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/audit_log.jsonl b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/audit_log.jsonl
new file mode 100644
index 00000000..b89f5aa0
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/audit_log.jsonl
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_file": "raw/audit_log.jsonl.gz",
+  "original_path": "tabs_raw/audit_log.jsonl",
+  "original_sha256": "03b8321df76348480a1607a310b405d2a36e7893369f0c78106c82b85aeddca7",
+  "compressed_sha256": "caadfa85f8580e5666266e67582a5c70692a7f0fb360d4a7af126647f9c90bca",
+  "original_bytes": 1573538
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/balances.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/balances.md
new file mode 100644
index 00000000..e915f228
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/balances.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_file": "raw/balances.md.gz",
+  "original_path": "tabs_raw/balances.md",
+  "original_sha256": "bb42c190a0c193426c36e3cae105bd27ce891614abf7f9e10f94dcb9a0aa6274",
+  "compressed_sha256": "eaf4d539a8607ab70f1d5bbab538b693c50d0d0854119e19b1cc42bebda8a378",
+  "original_bytes": 90295
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/daily_returns.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/daily_returns.md
new file mode 100644
index 00000000..49d46b3b
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/daily_returns.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_file": "raw/daily_returns.md.gz",
+  "original_path": "tabs_raw/daily_returns.md",
+  "original_sha256": "3fe98f5676b51e9130b70628e7e4825777a354162acd2f36ea57e2c5d67128ce",
+  "compressed_sha256": "80b833a3f380632b700e3465a6f7152eb2ace77e9be03bd7afcfc9309185c20d",
+  "original_bytes": 92608
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/logs.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/logs.md
new file mode 100644
index 00000000..64a36b42
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/logs.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_file": "raw/logs.md.gz",
+  "original_path": "tabs_raw/logs.md",
+  "original_sha256": "d811c3e0aa782563080368e27c8bd9f2aa226afd30972ddc3c7cba7ca0fa2af3",
+  "compressed_sha256": "05269fff42e0b0e739e4003fbb5694a7160ca23692873edd5f4f022b419d0812",
+  "original_bytes": 290
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/period_risks.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/period_risks.md
new file mode 100644
index 00000000..451b2933
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/period_risks.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_file": "raw/period_risks.md.gz",
+  "original_path": "tabs_raw/period_risks.md",
+  "original_sha256": "12b8099715fc56c767744c28dd4a581e2245ba7f789cd44365fcfcaf3b55c7d1",
+  "compressed_sha256": "90f7def05b8d70d47e07c67810585f126e549cad52a7ede29c767ff3d01c1b3e",
+  "original_bytes": 62815
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/positioninfo.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/positioninfo.md
new file mode 100644
index 00000000..5c8df49e
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/positioninfo.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_file": "raw/positioninfo.md.gz",
+  "original_path": "tabs_raw/positioninfo.md",
+  "original_sha256": "a3215e23b1ff949da0b0f11f24322d98f995f097c65ea821ff7ba849d4e7fb68",
+  "compressed_sha256": "14b9310ec01355c6aa1e012fabfc15a71e0df847de00122774e13ebfd3aad8af",
+  "original_bytes": 379635
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/profile.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/profile.md
new file mode 100644
index 00000000..38620882
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/profile.md
@@ -0,0 +1,551 @@
+# 性能分析
+
+## fund_code
+
+- 总耗时：0.013006s
+
+```text
+Total time: 0.013006 s
+File: /tmp/strategy/user_code.py
+Function: fund_code at line 129
+```
+
+## format_etf_name
+
+- 总耗时：0.086733s
+
+```text
+Total time: 0.086733 s
+File: /tmp/strategy/user_code.py
+Function: format_etf_name at line 131
+```
+
+## build_etf_display_names
+
+- 总耗时：0.169459s
+
+```text
+Total time: 0.169459 s
+File: /tmp/strategy/user_code.py
+Function: build_etf_display_names at line 144
+```
+
+## fetch_etf_official_name
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: fetch_etf_official_name at line 151
+```
+
+## load_etf_display_names
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: load_etf_display_names at line 161
+```
+
+## _audit_jsonable
+
+- 总耗时：0.264367s
+
+```text
+Total time: 0.264367 s
+File: /tmp/strategy/user_code.py
+Function: _audit_jsonable at line 169
+```
+
+## _context_time_fields
+
+- 总耗时：0.304284s
+
+```text
+Total time: 0.304284 s
+File: /tmp/strategy/user_code.py
+Function: _context_time_fields at line 198
+```
+
+## audit_event
+
+- 总耗时：26.9545s
+
+```text
+Total time: 26.9545 s
+File: /tmp/strategy/user_code.py
+Function: audit_event at line 205
+```
+
+## _copy_runtime_default
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: _copy_runtime_default at line 219
+```
+
+## _runtime_param
+
+- 总耗时：0.078164s
+
+```text
+Total time: 0.078164 s
+File: /tmp/strategy/user_code.py
+Function: _runtime_param at line 227
+```
+
+## _runtime_list_param
+
+- 总耗时：0.034155s
+
+```text
+Total time: 0.034155 s
+File: /tmp/strategy/user_code.py
+Function: _runtime_list_param at line 231
+```
+
+## snapshot_params
+
+- 总耗时：0.385082s
+
+```text
+Total time: 0.385082 s
+File: /tmp/strategy/user_code.py
+Function: snapshot_params at line 236
+```
+
+## validate_params
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: validate_params at line 326
+```
+
+## resolve_ma_long_windows
+
+- 总耗时：0.001854s
+
+```text
+Total time: 0.001854 s
+File: /tmp/strategy/user_code.py
+Function: resolve_ma_long_windows at line 414
+```
+
+## resolve_crowd_thresholds
+
+- 总耗时：0.003031s
+
+```text
+Total time: 0.003031 s
+File: /tmp/strategy/user_code.py
+Function: resolve_crowd_thresholds at line 419
+```
+
+## resolve_crowd_ret_windows
+
+- 总耗时：0.001444s
+
+```text
+Total time: 0.001444 s
+File: /tmp/strategy/user_code.py
+Function: resolve_crowd_ret_windows at line 428
+```
+
+## initialize
+
+- 总耗时：0.041832s
+
+```text
+Total time: 0.041832 s
+File: /tmp/strategy/user_code.py
+Function: initialize at line 435
+```
+
+## set_parameter
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: set_parameter at line 503
+```
+
+## _log_step
+
+- 总耗时：0.785075s
+
+```text
+Total time: 0.785075 s
+File: /tmp/strategy/user_code.py
+Function: _log_step at line 572
+```
+
+## compose_raw_weights
+
+- 总耗时：0.003935s
+
+```text
+Total time: 0.003935 s
+File: /tmp/strategy/user_code.py
+Function: compose_raw_weights at line 578
+```
+
+## _as_date
+
+- 总耗时：0.004534s
+
+```text
+Total time: 0.004534 s
+File: /tmp/strategy/user_code.py
+Function: _as_date at line 588
+```
+
+## _context_trade_date
+
+- 总耗时：0.103082s
+
+```text
+Total time: 0.103082 s
+File: /tmp/strategy/user_code.py
+Function: _context_trade_date at line 599
+```
+
+## _next_trade_date
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: _next_trade_date at line 601
+```
+
+## _same_iso_week
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: _same_iso_week at line 619
+```
+
+## build_rebalance_plan
+
+- 总耗时：51.9012s
+
+```text
+Total time: 51.9012 s
+File: /tmp/strategy/user_code.py
+Function: build_rebalance_plan at line 625
+```
+
+## weekly_check
+
+- 总耗时：66.0101s
+
+```text
+Total time: 66.0101 s
+File: /tmp/strategy/user_code.py
+Function: weekly_check at line 694
+```
+
+## prepare_delay_only_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: prepare_delay_only_rebalance at line 697
+```
+
+## execute_pending_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: execute_pending_rebalance at line 708
+```
+
+## mark_live_like_signal_day
+
+- 总耗时：3.72377s
+
+```text
+Total time: 3.72377 s
+File: /tmp/strategy/user_code.py
+Function: mark_live_like_signal_day at line 736
+```
+
+## execute_live_like_rebalance
+
+- 总耗时：73.3181s
+
+```text
+Total time: 73.3181 s
+File: /tmp/strategy/user_code.py
+Function: execute_live_like_rebalance at line 745
+```
+
+## prepare_weekend_close_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: prepare_weekend_close_rebalance at line 783
+```
+
+## execute_weekend_close_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: execute_weekend_close_rebalance at line 822
+```
+
+## normalize_field_frame
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: normalize_field_frame at line 853
+```
+
+## compute_history_count
+
+- 总耗时：0.004012s
+
+```text
+Total time: 0.004012 s
+File: /tmp/strategy/user_code.py
+Function: compute_history_count at line 862
+```
+
+## fetch_field
+
+- 总耗时：24.5892s
+
+```text
+Total time: 24.5892 s
+File: /tmp/strategy/user_code.py
+Function: fetch_field at line 872
+```
+
+## get_history_data
+
+- 总耗时：25.3159s
+
+```text
+Total time: 25.3159 s
+File: /tmp/strategy/user_code.py
+Function: get_history_data at line 892
+```
+
+## compute_trend_gates
+
+- 总耗时：0.658139s
+
+```text
+Total time: 0.658139 s
+File: /tmp/strategy/user_code.py
+Function: compute_trend_gates at line 905
+```
+
+## compute_momentum_scores
+
+- 总耗时：1.60766s
+
+```text
+Total time: 1.60766 s
+File: /tmp/strategy/user_code.py
+Function: compute_momentum_scores at line 921
+```
+
+## select_topk
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: select_topk at line 947
+```
+
+## compute_rp_weights
+
+- 总耗时：0.394105s
+
+```text
+Total time: 0.394105 s
+File: /tmp/strategy/user_code.py
+Function: compute_rp_weights at line 956
+```
+
+## compute_rsrs_multipliers
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_multipliers at line 985
+```
+
+## compute_rsrs_adjusted_scores
+
+- 总耗时：8.77132s
+
+```text
+Total time: 8.77132 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_adjusted_scores at line 994
+```
+
+## compute_momentum_tilt_multipliers
+
+- 总耗时：0.025801s
+
+```text
+Total time: 0.025801 s
+File: /tmp/strategy/user_code.py
+Function: compute_momentum_tilt_multipliers at line 1037
+```
+
+## compute_rsrs_tilt_multipliers
+
+- 总耗时：8.83197s
+
+```text
+Total time: 8.83197 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_tilt_multipliers at line 1058
+```
+
+## apply_relative_tilts
+
+- 总耗时：0.013144s
+
+```text
+Total time: 0.013144 s
+File: /tmp/strategy/user_code.py
+Function: apply_relative_tilts at line 1075
+```
+
+## compute_crowd_penalties
+
+- 总耗时：8.08886s
+
+```text
+Total time: 8.08886 s
+File: /tmp/strategy/user_code.py
+Function: compute_crowd_penalties at line 1091
+```
+
+## percentile_rank
+
+- 总耗时：1.95519s
+
+```text
+Total time: 1.95519 s
+File: /tmp/strategy/user_code.py
+Function: percentile_rank at line 1159
+```
+
+## compute_portfolio_vol_scale_detail
+
+- 总耗时：0.325778s
+
+```text
+Total time: 0.325778 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_scale_detail at line 1164
+```
+
+## compute_portfolio_vol_scale
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_scale at line 1195
+```
+
+## compute_portfolio_vol_asset_scales
+
+- 总耗时：0.823519s
+
+```text
+Total time: 0.823519 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_asset_scales at line 1198
+```
+
+## apply_fixed_gold_vol_relief
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: apply_fixed_gold_vol_relief at line 1215
+```
+
+## apply_dynamic_marginal_vol_relief
+
+- 总耗时：0.469061s
+
+```text
+Total time: 0.469061 s
+File: /tmp/strategy/user_code.py
+Function: apply_dynamic_marginal_vol_relief at line 1238
+```
+
+## select_dynamic_marginal_relief_asset
+
+- 总耗时：0.456829s
+
+```text
+Total time: 0.456829 s
+File: /tmp/strategy/user_code.py
+Function: select_dynamic_marginal_relief_asset at line 1259
+```
+
+## apply_weight_constraints
+
+- 总耗时：0.008202s
+
+```text
+Total time: 0.008202 s
+File: /tmp/strategy/user_code.py
+Function: apply_weight_constraints at line 1294
+```
+
+## execute_rebalance
+
+- 总耗时：14.0182s
+
+```text
+Total time: 14.0182 s
+File: /tmp/strategy/user_code.py
+Function: execute_rebalance at line 1309
+```
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/records.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/records.md
new file mode 100644
index 00000000..8043b956
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/records.md
@@ -0,0 +1,3 @@
+# Record 记录
+
+(无数据)
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/risk.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/risk.md
new file mode 100644
index 00000000..dbaa8a5a
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/risk.md
@@ -0,0 +1,37 @@
+# 风险指标
+
+- 记录数：31
+
+| metric | value |
+| --- | --- |
+| __version | 101 |
+| algorithm_return | 1.2084720048999968 |
+| algorithm_volatility | 0.08171770998671299 |
+| alpha | 0.13353282713269088 |
+| annual_algo_return | 0.1661011131707033 |
+| annual_bm_return | -0.01552798313301329 |
+| avg_excess_return | 0.0007376028973042972 |
+| avg_position_days | 805.0 |
+| avg_trade_return | 0.04831229742308037 |
+| benchmark_return | -0.07752074822165167 |
+| benchmark_volatility | 0.17880949192018716 |
+| beta | 0.13383727523806196 |
+| day_win_ratio | 0.5446082234290147 |
+| excess_return | 1.394061438934834 |
+| excess_return_max_drawdown | 0.2099277608370691 |
+| excess_return_max_drawdown_period | ['2024-09-13', '2024-10-08'] |
+| excess_return_sharpe | 0.8327248575800921 |
+| information | 1.047026560009065 |
+| lose_count | 55 |
+| max_drawdown | 0.11659213666185808 |
+| max_drawdown_period | ['2021-09-06', '2022-10-21'] |
+| max_leverage | 0.0 |
+| period_label | 2026-04 |
+| profit_loss_ratio | 4.223695667978375 |
+| sharpe | 1.543130775338747 |
+| sortino | 2.2760548147608937 |
+| trading_days | 1289 |
+| treasury_return | 0.21282191780821919 |
+| turnover_rate | 0.020794991631749023 |
+| win_count | 132 |
+| win_ratio | 0.7058823529411765 |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/transactioninfo.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/transactioninfo.md
new file mode 100644
index 00000000..28868216
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352/tabs_raw/transactioninfo.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+  "dataset_file": "raw/transactioninfo.md.gz",
+  "original_path": "tabs_raw/transactioninfo.md",
+  "original_sha256": "e782081b37742ef6b6be217827ed0afb4429871c018b0baf58a77329cb30704d",
+  "compressed_sha256": "37c49aa9b9d47b49651e4e6cdf114c06dbf0be15fe5c8ead933c576b0968944c",
+  "original_bytes": 31319
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/all_data.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/all_data.json
new file mode 100644
index 00000000..bd09934d
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/all_data.json
@@ -0,0 +1,105 @@
+{
+  "api_export_json": "D:\\My Project\\Quant Trading\\strategies\\etf_factor_rotation\\backtest_runs\\20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5\\api_export.json",
+  "extraction_method": "research_bundle",
+  "generated_at": "2026-06-30T16:29:20.801482+00:00",
+  "counts": {
+    "results": 1289,
+    "positions": 0,
+    "orders": 0,
+    "records": 0,
+    "balances": 1289,
+    "period_risk_tabs": 10,
+    "audit_log_lines": 1291
+  },
+  "partial": {
+    "results": false,
+    "positions": false,
+    "orders": false,
+    "records": false,
+    "risk": false,
+    "period_risks": false,
+    "balances": false,
+    "logs": true,
+    "audit_log": false
+  },
+  "primary_extraction_method": "joinquant_research_get_backtest",
+  "fallback_extraction_method": "",
+  "research_export_path": "jq_auto_exports/research_backtest_cb35093c739b769b0c7cebb1bbe141b5.json",
+  "research_downloaded": true,
+  "detail_api_used": true,
+  "tabs": {
+    "daily_returns": {
+      "path": "tabs_raw/daily_returns.md",
+      "partial": false,
+      "record_count": 1289
+    },
+    "transactioninfo": {
+      "path": "tabs_raw/transactioninfo.md",
+      "partial": false,
+      "record_count": 0
+    },
+    "positioninfo": {
+      "path": "tabs_raw/positioninfo.md",
+      "partial": false,
+      "record_count": 0
+    },
+    "records": {
+      "path": "tabs_raw/records.md",
+      "partial": false,
+      "record_count": 0
+    },
+    "balances": {
+      "path": "tabs_raw/balances.md",
+      "partial": false,
+      "record_count": 1289
+    },
+    "risk": {
+      "path": "tabs_raw/risk.md",
+      "partial": false,
+      "record_count": 31
+    },
+    "period_risks": {
+      "path": "tabs_raw/period_risks.md",
+      "partial": false,
+      "record_count": 10
+    },
+    "profile": {
+      "path": "tabs_raw/profile.md",
+      "partial": false,
+      "record_count": 8013
+    },
+    "logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true,
+      "record_count": 143
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "partial": false,
+      "record_count": 1291
+    }
+  },
+  "note": "Generated from JoinQuant research get_backtest() schema v3 bundle. Platform logs are not provided by get_backtest().",
+  "integrity_status": "complete",
+  "integrity_issues": [],
+  "sources": {
+    "research": {
+      "path": "api_export.json",
+      "present": true,
+      "method": "joinquant_research_get_backtest"
+    },
+    "detail_api": {
+      "path": "detail_api_export.json",
+      "present": true
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
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+      "count": 1291
+    },
+    "platform_logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true
+    }
+  }
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/api_export.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/api_export.json
new file mode 100644
index 00000000..1590e605
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/api_export.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_file": "raw/api_export.json.gz",
+  "original_path": "api_export.json",
+  "original_sha256": "c229ecd0a002776c46a8ac61b45afe338320d96f56256f86fba24ae5d1913675",
+  "compressed_sha256": "4a0508b9259be6e1c383b046076360cf9d4bb33584736686522a9fdfd22b3117",
+  "original_bytes": 1195328
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/detail_api_export.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/detail_api_export.json
new file mode 100644
index 00000000..0d13e015
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/detail_api_export.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_file": "raw/detail_api_export.json.gz",
+  "original_path": "detail_api_export.json",
+  "original_sha256": "cf5dbcd96ca03765831910e39f65b0dd4677bbdc53d0cd81183fab54e1c1c077",
+  "compressed_sha256": "f30a669cd2bf68d772ffe54597f4bd96cd469b580511c438af482e39ce850dc0",
+  "original_bytes": 1929553
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/integrity.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/integrity.json
new file mode 100644
index 00000000..5d61e7f1
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/integrity.json
@@ -0,0 +1,153 @@
+{
+  "status": "complete",
+  "generated_at": "2026-06-30T16:29:20.812415+00:00",
+  "issues": [],
+  "checks": [
+    {
+      "name": "research_bundle",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": null,
+      "partial": null,
+      "message": "research get_backtest bundle is required"
+    },
+    {
+      "name": "detail_api_bundle",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": null,
+      "partial": null,
+      "message": "detail API bundle is required"
+    },
+    {
+      "name": "metadata",
+      "required": true,
+      "status": "pass",
+      "source": "metadata.json",
+      "count": null,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "summary_metrics",
+      "required": true,
+      "status": "pass",
+      "source": "summary_metrics.json",
+      "count": null,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "research_results",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 1289,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_positions",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 0,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_orders",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 0,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_risk",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 31,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_results",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 1485,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_transactions",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 0,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_positions",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 1289,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_risk_tabs",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 640,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "platform_logs",
+      "required": false,
+      "status": "warn",
+      "source": "detail_api_export.json",
+      "count": 1000,
+      "partial": true,
+      "message": "platform logs may be partial; audit_log is canonical"
+    },
+    {
+      "name": "audit_log",
+      "required": true,
+      "status": "pass",
+      "source": "tabs_raw/audit_log.jsonl",
+      "count": 1291,
+      "partial": false,
+      "message": ""
+    }
+  ],
+  "sources": {
+    "research": {
+      "path": "api_export.json",
+      "present": true,
+      "method": "joinquant_research_get_backtest"
+    },
+    "detail_api": {
+      "path": "detail_api_export.json",
+      "present": true
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "present": true,
+      "count": 1291
+    },
+    "platform_logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true
+    }
+  }
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/metadata.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/metadata.json
new file mode 100644
index 00000000..bc8c9cbf
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/metadata.json
@@ -0,0 +1,26 @@
+{
+  "strategy_name": "etf_factor_rotation",
+  "run_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "strategy_file": "",
+  "strategy_dir": "",
+  "start_date_requested": "",
+  "start_date_effective": "2021-01-01",
+  "end_date_requested": "",
+  "end_date_effective": "2026-04-30",
+  "capital": 100000,
+  "backtest_id": "cb35093c739b769b0c7cebb1bbe141b5",
+  "joinquant_backtest_id": "cb35093c739b769b0c7cebb1bbe141b5",
+  "backtest_url": "",
+  "generated_at": "2026-07-01T00:29:10",
+  "extraction_method": "joinquant_research_get_backtest",
+  "primary_extraction_method": "joinquant_research_get_backtest",
+  "fallback_extraction_method": "",
+  "research_export_path": "jq_auto_exports/research_backtest_cb35093c739b769b0c7cebb1bbe141b5.json",
+  "research_downloaded": true,
+  "detail_api_used": true,
+  "frequency": "1d",
+  "py_version": "Python3",
+  "internal_backtest_id": "34a1ef4f300c8c4763d455b4dd5fdc1f",
+  "audit_token": "etf_factor_rotation-s03-weekend-close-signal-next-open-variant-20260701002745-dae632f4",
+  "audit_path": "jq_auto_audit/etf_factor_rotation-s03-weekend-close-signal-next-open-variant-20260701002745-dae632f4.jsonl"
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/backtest_report.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/backtest_report.md
new file mode 100644
index 00000000..cd963ebc
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/backtest_report.md
@@ -0,0 +1,32 @@
+# 回测数据汇总
+
+- 策略名称：etf_factor_rotation
+- 回测 ID：cb35093c739b769b0c7cebb1bbe141b5
+- 区间：2021-01-01 至 2026-04-30
+- 提取方式：聚宽研究环境 get_backtest()；详情页接口仅作补充。
+
+## 核心指标
+
+| 指标 | 值 |
+| --- | --- |
+| 策略收益 | 0.00% |
+| 策略年化收益 | 0.00% |
+| 基准收益 | -7.75% |
+| 超额收益 | 8.40% |
+| 最大回撤 | 0.00% |
+| 夏普比率 | 0.000 |
+| 阿尔法 | -0.040 |
+| 贝塔 | 0.000 |
+| 信息比率 | 0.087 |
+
+## 数据覆盖
+
+| 数据 | 记录数 | 完整度 |
+| --- | ---: | --- |
+| 每日收益 | 1289 | 完整 |
+| 每日持仓&收益 | 0 | 完整 |
+| 订单/交易 | 0 | 完整 |
+| record 记录 | 0 | 完整 |
+| 每日账户市值 | 1289 | 完整 |
+| 分期风险 | 10 | 完整 |
+| 平台日志 |  | 详情页接口部分 |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/data-integrity.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/data-integrity.md
new file mode 100644
index 00000000..6928ce73
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/report/data-integrity.md
@@ -0,0 +1,26 @@
+# 数据完整性报告
+
+- 状态：complete
+- 生成时间：2026-06-30T16:29:20.812415+00:00
+
+## 问题
+- 无
+
+## 检查项
+
+| 检查项 | 必须 | 状态 | 来源 | 记录数 | partial | 说明 |
+| --- | --- | --- | --- | ---: | --- | --- |
+| research_bundle | 是 | pass | api_export.json |  |  | research get_backtest bundle is required |
+| detail_api_bundle | 是 | pass | detail_api_export.json |  |  | detail API bundle is required |
+| metadata | 是 | pass | metadata.json |  |  |  |
+| summary_metrics | 是 | pass | summary_metrics.json |  |  |  |
+| research_results | 是 | pass | api_export.json | 1289 | False |  |
+| research_positions | 是 | pass | api_export.json | 0 | False |  |
+| research_orders | 是 | pass | api_export.json | 0 | False |  |
+| research_risk | 是 | pass | api_export.json | 31 | False |  |
+| detail_results | 是 | pass | detail_api_export.json | 1485 | False |  |
+| detail_transactions | 是 | pass | detail_api_export.json | 0 | False |  |
+| detail_positions | 是 | pass | detail_api_export.json | 1289 | False |  |
+| detail_risk_tabs | 是 | pass | detail_api_export.json | 640 |  |  |
+| platform_logs | 否 | warn | detail_api_export.json | 1000 | True | platform logs may be partial; audit_log is canonical |
+| audit_log | 是 | pass | tabs_raw/audit_log.jsonl | 1291 | False |  |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/summary_metrics.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/summary_metrics.json
new file mode 100644
index 00000000..0e543eca
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/summary_metrics.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_file": "raw/summary_metrics.json.gz",
+  "original_path": "summary_metrics.json",
+  "original_sha256": "1441610d84c772df69020a9b419b6a0d93d17925a536a0da73302043f938622c",
+  "compressed_sha256": "d93b7bc879c5078a26700fa2537df9dccb923afaa938a58b2b2fb65c8c3effc5",
+  "original_bytes": 513
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/audit_log.jsonl b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/audit_log.jsonl
new file mode 100644
index 00000000..70cdd7be
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/audit_log.jsonl
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_file": "raw/audit_log.jsonl.gz",
+  "original_path": "tabs_raw/audit_log.jsonl",
+  "original_sha256": "c2bc4e50e30b7d10d5e4442072d4c941a72ad973444e5f280f79185fdba4bdb7",
+  "compressed_sha256": "8666e944cd6e4c73d8110c1285e631d5e7f19923bf06479d59ce80097cc82695",
+  "original_bytes": 457444
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/balances.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/balances.md
new file mode 100644
index 00000000..fe1bf791
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/balances.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_file": "raw/balances.md.gz",
+  "original_path": "tabs_raw/balances.md",
+  "original_sha256": "ee7877994ae8bba34c4f473a8486c5735751380e0d895811c34bc3b4c999af0f",
+  "compressed_sha256": "08cb8867e0c9f219c8a89a87f77d0f79bc997c0e78f0fe9f78fe04ef8db02063",
+  "original_bytes": 89075
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/daily_returns.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/daily_returns.md
new file mode 100644
index 00000000..c9f04737
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/daily_returns.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_file": "raw/daily_returns.md.gz",
+  "original_path": "tabs_raw/daily_returns.md",
+  "original_sha256": "280364f893898ccb15f694c6d4100181227cc07f7286799990f3490b5a1bce6c",
+  "compressed_sha256": "047a3b8cd21fbde23a45ed77f444e16f52b31ec64294acf1b81bb6906b429855",
+  "original_bytes": 71979
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/logs.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/logs.md
new file mode 100644
index 00000000..71b7b09d
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/logs.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_file": "raw/logs.md.gz",
+  "original_path": "tabs_raw/logs.md",
+  "original_sha256": "d811c3e0aa782563080368e27c8bd9f2aa226afd30972ddc3c7cba7ca0fa2af3",
+  "compressed_sha256": "05269fff42e0b0e739e4003fbb5694a7160ca23692873edd5f4f022b419d0812",
+  "original_bytes": 290
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/period_risks.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/period_risks.md
new file mode 100644
index 00000000..eb78cad7
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/period_risks.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_file": "raw/period_risks.md.gz",
+  "original_path": "tabs_raw/period_risks.md",
+  "original_sha256": "07dcbe34d02a74d975ee511e851dd632d867e5d7bbf78e0273902c5ee6b7a679",
+  "compressed_sha256": "98f73b5d0a3d9998b7874456af774414660a139bc075a11ec21bbb2dfc8f167c",
+  "original_bytes": 37103
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/positioninfo.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/positioninfo.md
new file mode 100644
index 00000000..7410794c
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/positioninfo.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_file": "raw/positioninfo.md.gz",
+  "original_path": "tabs_raw/positioninfo.md",
+  "original_sha256": "2e84a9b6856d1079b7ef24a3ddace913452650e6d3ed7f1ebda4c606bb982540",
+  "compressed_sha256": "d051b390de0ac7ab1028c8ffad73921af3d4920ba4dbe9593b0858a2c6820b7c",
+  "original_bytes": 46
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/profile.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/profile.md
new file mode 100644
index 00000000..f46bd3fd
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/profile.md
@@ -0,0 +1,551 @@
+# 性能分析
+
+## fund_code
+
+- 总耗时：0.004261s
+
+```text
+Total time: 0.004261 s
+File: /tmp/strategy/user_code.py
+Function: fund_code at line 129
+```
+
+## format_etf_name
+
+- 总耗时：0.03124s
+
+```text
+Total time: 0.03124 s
+File: /tmp/strategy/user_code.py
+Function: format_etf_name at line 131
+```
+
+## build_etf_display_names
+
+- 总耗时：0.060627s
+
+```text
+Total time: 0.060627 s
+File: /tmp/strategy/user_code.py
+Function: build_etf_display_names at line 144
+```
+
+## fetch_etf_official_name
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: fetch_etf_official_name at line 151
+```
+
+## load_etf_display_names
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: load_etf_display_names at line 161
+```
+
+## _audit_jsonable
+
+- 总耗时：0.034697s
+
+```text
+Total time: 0.034697 s
+File: /tmp/strategy/user_code.py
+Function: _audit_jsonable at line 169
+```
+
+## _context_time_fields
+
+- 总耗时：0.225254s
+
+```text
+Total time: 0.225254 s
+File: /tmp/strategy/user_code.py
+Function: _context_time_fields at line 198
+```
+
+## audit_event
+
+- 总耗时：18.3511s
+
+```text
+Total time: 18.3511 s
+File: /tmp/strategy/user_code.py
+Function: audit_event at line 205
+```
+
+## _copy_runtime_default
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: _copy_runtime_default at line 219
+```
+
+## _runtime_param
+
+- 总耗时：0.090604s
+
+```text
+Total time: 0.090604 s
+File: /tmp/strategy/user_code.py
+Function: _runtime_param at line 227
+```
+
+## _runtime_list_param
+
+- 总耗时：0.041924s
+
+```text
+Total time: 0.041924 s
+File: /tmp/strategy/user_code.py
+Function: _runtime_list_param at line 231
+```
+
+## snapshot_params
+
+- 总耗时：0.447207s
+
+```text
+Total time: 0.447207 s
+File: /tmp/strategy/user_code.py
+Function: snapshot_params at line 236
+```
+
+## validate_params
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: validate_params at line 326
+```
+
+## resolve_ma_long_windows
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: resolve_ma_long_windows at line 414
+```
+
+## resolve_crowd_thresholds
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: resolve_crowd_thresholds at line 419
+```
+
+## resolve_crowd_ret_windows
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: resolve_crowd_ret_windows at line 428
+```
+
+## initialize
+
+- 总耗时：0.045607s
+
+```text
+Total time: 0.045607 s
+File: /tmp/strategy/user_code.py
+Function: initialize at line 435
+```
+
+## set_parameter
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: set_parameter at line 503
+```
+
+## _log_step
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: _log_step at line 572
+```
+
+## compose_raw_weights
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compose_raw_weights at line 578
+```
+
+## _as_date
+
+- 总耗时：0.008862s
+
+```text
+Total time: 0.008862 s
+File: /tmp/strategy/user_code.py
+Function: _as_date at line 588
+```
+
+## _context_trade_date
+
+- 总耗时：0.093882s
+
+```text
+Total time: 0.093882 s
+File: /tmp/strategy/user_code.py
+Function: _context_trade_date at line 599
+```
+
+## _next_trade_date
+
+- 总耗时：0.30164s
+
+```text
+Total time: 0.30164 s
+File: /tmp/strategy/user_code.py
+Function: _next_trade_date at line 601
+```
+
+## _same_iso_week
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: _same_iso_week at line 619
+```
+
+## build_rebalance_plan
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: build_rebalance_plan at line 625
+```
+
+## weekly_check
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: weekly_check at line 694
+```
+
+## prepare_delay_only_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: prepare_delay_only_rebalance at line 697
+```
+
+## execute_pending_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: execute_pending_rebalance at line 708
+```
+
+## mark_live_like_signal_day
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: mark_live_like_signal_day at line 736
+```
+
+## execute_live_like_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: execute_live_like_rebalance at line 745
+```
+
+## prepare_weekend_close_rebalance
+
+- 总耗时：19.4619s
+
+```text
+Total time: 19.4619 s
+File: /tmp/strategy/user_code.py
+Function: prepare_weekend_close_rebalance at line 783
+```
+
+## execute_weekend_close_rebalance
+
+- 总耗时：0.009116s
+
+```text
+Total time: 0.009116 s
+File: /tmp/strategy/user_code.py
+Function: execute_weekend_close_rebalance at line 822
+```
+
+## normalize_field_frame
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: normalize_field_frame at line 853
+```
+
+## compute_history_count
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_history_count at line 862
+```
+
+## fetch_field
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: fetch_field at line 872
+```
+
+## get_history_data
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: get_history_data at line 892
+```
+
+## compute_trend_gates
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_trend_gates at line 905
+```
+
+## compute_momentum_scores
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_momentum_scores at line 921
+```
+
+## select_topk
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: select_topk at line 947
+```
+
+## compute_rp_weights
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_rp_weights at line 956
+```
+
+## compute_rsrs_multipliers
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_multipliers at line 985
+```
+
+## compute_rsrs_adjusted_scores
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_adjusted_scores at line 994
+```
+
+## compute_momentum_tilt_multipliers
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_momentum_tilt_multipliers at line 1037
+```
+
+## compute_rsrs_tilt_multipliers
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_tilt_multipliers at line 1058
+```
+
+## apply_relative_tilts
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: apply_relative_tilts at line 1075
+```
+
+## compute_crowd_penalties
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_crowd_penalties at line 1091
+```
+
+## percentile_rank
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: percentile_rank at line 1159
+```
+
+## compute_portfolio_vol_scale_detail
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_scale_detail at line 1164
+```
+
+## compute_portfolio_vol_scale
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_scale at line 1195
+```
+
+## compute_portfolio_vol_asset_scales
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_asset_scales at line 1198
+```
+
+## apply_fixed_gold_vol_relief
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: apply_fixed_gold_vol_relief at line 1215
+```
+
+## apply_dynamic_marginal_vol_relief
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: apply_dynamic_marginal_vol_relief at line 1238
+```
+
+## select_dynamic_marginal_relief_asset
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: select_dynamic_marginal_relief_asset at line 1259
+```
+
+## apply_weight_constraints
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: apply_weight_constraints at line 1294
+```
+
+## execute_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: execute_rebalance at line 1309
+```
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/records.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/records.md
new file mode 100644
index 00000000..8043b956
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/records.md
@@ -0,0 +1,3 @@
+# Record 记录
+
+(无数据)
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/risk.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/risk.md
new file mode 100644
index 00000000..07b42ec6
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/risk.md
@@ -0,0 +1,37 @@
+# 风险指标
+
+- 记录数：31
+
+| metric | value |
+| --- | --- |
+| __version | 101 |
+| algorithm_return | 0.0 |
+| algorithm_volatility | 0.0 |
+| alpha | -0.04 |
+| annual_algo_return | 0.0 |
+| annual_bm_return | -0.01552798313301329 |
+| avg_excess_return | 0.00012648312541689298 |
+| avg_position_days | 0 |
+| avg_trade_return | 0.0 |
+| benchmark_return | -0.07752074822165167 |
+| benchmark_volatility | 0.17880949192018716 |
+| beta | 0.0 |
+| day_win_ratio | 0.5050426687354539 |
+| excess_return | 0.0840352214667277 |
+| excess_return_max_drawdown | 0.34323862055018295 |
+| excess_return_max_drawdown_period | ['2024-09-13', '2026-04-29'] |
+| excess_return_sharpe | -0.13545975391258516 |
+| information | 0.08684093314209691 |
+| lose_count | 0 |
+| max_drawdown | 0.0 |
+| max_drawdown_period | ['2021-01-04', '2021-01-04'] |
+| max_leverage | 0.0 |
+| period_label | 2026-04 |
+| profit_loss_ratio | 0.0 |
+| sharpe | 0.0 |
+| sortino | 0.0 |
+| trading_days | 1289 |
+| treasury_return | 0.21282191780821919 |
+| turnover_rate | 0.0 |
+| win_count | 0 |
+| win_ratio | 0 |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/transactioninfo.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/transactioninfo.md
new file mode 100644
index 00000000..05d72590
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5/tabs_raw/transactioninfo.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+  "dataset_file": "raw/transactioninfo.md.gz",
+  "original_path": "tabs_raw/transactioninfo.md",
+  "original_sha256": "aef37d19402efee5cf279ac02e7962f8eacdc8c878fc5ff6265185aaf09e6a8e",
+  "compressed_sha256": "b4b0eae5867c88eeaabb8404edf7c499cbdadef927d80bc4f8e97afdbbbd821d",
+  "original_bytes": 37
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/all_data.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/all_data.json
new file mode 100644
index 00000000..c4133145
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/all_data.json
@@ -0,0 +1,105 @@
+{
+  "api_export_json": "D:\\My Project\\Quant Trading\\strategies\\etf_factor_rotation\\backtest_runs\\20260701-0032-btdcc6252aadef8bb09592538da4dde54c\\api_export.json",
+  "extraction_method": "research_bundle",
+  "generated_at": "2026-06-30T16:38:34.484953+00:00",
+  "counts": {
+    "results": 1289,
+    "positions": 2386,
+    "orders": 378,
+    "records": 0,
+    "balances": 1289,
+    "period_risk_tabs": 10,
+    "audit_log_lines": 4681
+  },
+  "partial": {
+    "results": false,
+    "positions": false,
+    "orders": false,
+    "records": false,
+    "risk": false,
+    "period_risks": false,
+    "balances": false,
+    "logs": true,
+    "audit_log": false
+  },
+  "primary_extraction_method": "joinquant_research_get_backtest",
+  "fallback_extraction_method": "",
+  "research_export_path": "jq_auto_exports/research_backtest_dcc6252aadef8bb09592538da4dde54c.json",
+  "research_downloaded": true,
+  "detail_api_used": true,
+  "tabs": {
+    "daily_returns": {
+      "path": "tabs_raw/daily_returns.md",
+      "partial": false,
+      "record_count": 1289
+    },
+    "transactioninfo": {
+      "path": "tabs_raw/transactioninfo.md",
+      "partial": false,
+      "record_count": 378
+    },
+    "positioninfo": {
+      "path": "tabs_raw/positioninfo.md",
+      "partial": false,
+      "record_count": 2386
+    },
+    "records": {
+      "path": "tabs_raw/records.md",
+      "partial": false,
+      "record_count": 0
+    },
+    "balances": {
+      "path": "tabs_raw/balances.md",
+      "partial": false,
+      "record_count": 1289
+    },
+    "risk": {
+      "path": "tabs_raw/risk.md",
+      "partial": false,
+      "record_count": 31
+    },
+    "period_risks": {
+      "path": "tabs_raw/period_risks.md",
+      "partial": false,
+      "record_count": 10
+    },
+    "profile": {
+      "path": "tabs_raw/profile.md",
+      "partial": false,
+      "record_count": 8179
+    },
+    "logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true,
+      "record_count": 143
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "partial": false,
+      "record_count": 4681
+    }
+  },
+  "note": "Generated from JoinQuant research get_backtest() schema v3 bundle. Platform logs are not provided by get_backtest().",
+  "integrity_status": "complete",
+  "integrity_issues": [],
+  "sources": {
+    "research": {
+      "path": "api_export.json",
+      "present": true,
+      "method": "joinquant_research_get_backtest"
+    },
+    "detail_api": {
+      "path": "detail_api_export.json",
+      "present": true
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "present": true,
+      "count": 4681
+    },
+    "platform_logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true
+    }
+  }
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/api_export.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/api_export.json
new file mode 100644
index 00000000..4b10c24c
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/api_export.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_file": "raw/api_export.json.gz",
+  "original_path": "api_export.json",
+  "original_sha256": "2bbf6cebbecd26e21ac1f1006b027866d01999577e29080f3cee09dc20a62478",
+  "compressed_sha256": "41b6846050158d62ea66c163542735e8d5da246f99f8a47d98dbd53f7eab4a92",
+  "original_bytes": 8085596
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/detail_api_export.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/detail_api_export.json
new file mode 100644
index 00000000..65e06db9
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/detail_api_export.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_file": "raw/detail_api_export.json.gz",
+  "original_path": "detail_api_export.json",
+  "original_sha256": "1dab601403be7c65c47edd17a93fde95c08ec7f9217a018c826e6d6f13e3b5e9",
+  "compressed_sha256": "08da94376bf4d659b4021d34f4fcbbebcde6ec36dbf5f6ba69ad81156d823c6a",
+  "original_bytes": 4322026
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/integrity.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/integrity.json
new file mode 100644
index 00000000..a7cc206d
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/integrity.json
@@ -0,0 +1,153 @@
+{
+  "status": "complete",
+  "generated_at": "2026-06-30T16:38:34.562603+00:00",
+  "issues": [],
+  "checks": [
+    {
+      "name": "research_bundle",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": null,
+      "partial": null,
+      "message": "research get_backtest bundle is required"
+    },
+    {
+      "name": "detail_api_bundle",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": null,
+      "partial": null,
+      "message": "detail API bundle is required"
+    },
+    {
+      "name": "metadata",
+      "required": true,
+      "status": "pass",
+      "source": "metadata.json",
+      "count": null,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "summary_metrics",
+      "required": true,
+      "status": "pass",
+      "source": "summary_metrics.json",
+      "count": null,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "research_results",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 1289,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_positions",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 2386,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_orders",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 378,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_risk",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 31,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_results",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 1485,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_transactions",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 378,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_positions",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 3675,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_risk_tabs",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 640,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "platform_logs",
+      "required": false,
+      "status": "warn",
+      "source": "detail_api_export.json",
+      "count": 1000,
+      "partial": true,
+      "message": "platform logs may be partial; audit_log is canonical"
+    },
+    {
+      "name": "audit_log",
+      "required": true,
+      "status": "pass",
+      "source": "tabs_raw/audit_log.jsonl",
+      "count": 4681,
+      "partial": false,
+      "message": ""
+    }
+  ],
+  "sources": {
+    "research": {
+      "path": "api_export.json",
+      "present": true,
+      "method": "joinquant_research_get_backtest"
+    },
+    "detail_api": {
+      "path": "detail_api_export.json",
+      "present": true
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "present": true,
+      "count": 4681
+    },
+    "platform_logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true
+    }
+  }
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/metadata.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/metadata.json
new file mode 100644
index 00000000..3da24d09
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/metadata.json
@@ -0,0 +1,26 @@
+{
+  "strategy_name": "etf_factor_rotation",
+  "run_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "strategy_file": "",
+  "strategy_dir": "",
+  "start_date_requested": "",
+  "start_date_effective": "2021-01-01",
+  "end_date_requested": "",
+  "end_date_effective": "2026-04-30",
+  "capital": 100000,
+  "backtest_id": "dcc6252aadef8bb09592538da4dde54c",
+  "joinquant_backtest_id": "dcc6252aadef8bb09592538da4dde54c",
+  "backtest_url": "",
+  "generated_at": "2026-07-01T00:38:20",
+  "extraction_method": "joinquant_research_get_backtest",
+  "primary_extraction_method": "joinquant_research_get_backtest",
+  "fallback_extraction_method": "",
+  "research_export_path": "jq_auto_exports/research_backtest_dcc6252aadef8bb09592538da4dde54c.json",
+  "research_downloaded": true,
+  "detail_api_used": true,
+  "frequency": "1d",
+  "py_version": "Python3",
+  "internal_backtest_id": "8976d3093b13233b86b7a4c7f33c915e",
+  "audit_token": "etf_factor_rotation-s04-weekend-close-signal-next-open-variant-v2-20260701003223-e458457b",
+  "audit_path": "jq_auto_audit/etf_factor_rotation-s04-weekend-close-signal-next-open-variant-v2-20260701003223-e458457b.jsonl"
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/backtest_report.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/backtest_report.md
new file mode 100644
index 00000000..2960b486
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/backtest_report.md
@@ -0,0 +1,32 @@
+# 回测数据汇总
+
+- 策略名称：etf_factor_rotation
+- 回测 ID：dcc6252aadef8bb09592538da4dde54c
+- 区间：2021-01-01 至 2026-04-30
+- 提取方式：聚宽研究环境 get_backtest()；详情页接口仅作补充。
+
+## 核心指标
+
+| 指标 | 值 |
+| --- | --- |
+| 策略收益 | 127.57% |
+| 策略年化收益 | 17.29% |
+| 基准收益 | -7.75% |
+| 超额收益 | 146.70% |
+| 最大回撤 | 7.58% |
+| 夏普比率 | 1.591 |
+| 阿尔法 | 0.141 |
+| 贝塔 | 0.141 |
+| 信息比率 | 1.089 |
+
+## 数据覆盖
+
+| 数据 | 记录数 | 完整度 |
+| --- | ---: | --- |
+| 每日收益 | 1289 | 完整 |
+| 每日持仓&收益 | 2386 | 完整 |
+| 订单/交易 | 378 | 完整 |
+| record 记录 | 0 | 完整 |
+| 每日账户市值 | 1289 | 完整 |
+| 分期风险 | 10 | 完整 |
+| 平台日志 |  | 详情页接口部分 |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/data-integrity.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/data-integrity.md
new file mode 100644
index 00000000..53571070
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/report/data-integrity.md
@@ -0,0 +1,26 @@
+# 数据完整性报告
+
+- 状态：complete
+- 生成时间：2026-06-30T16:38:34.562603+00:00
+
+## 问题
+- 无
+
+## 检查项
+
+| 检查项 | 必须 | 状态 | 来源 | 记录数 | partial | 说明 |
+| --- | --- | --- | --- | ---: | --- | --- |
+| research_bundle | 是 | pass | api_export.json |  |  | research get_backtest bundle is required |
+| detail_api_bundle | 是 | pass | detail_api_export.json |  |  | detail API bundle is required |
+| metadata | 是 | pass | metadata.json |  |  |  |
+| summary_metrics | 是 | pass | summary_metrics.json |  |  |  |
+| research_results | 是 | pass | api_export.json | 1289 | False |  |
+| research_positions | 是 | pass | api_export.json | 2386 | False |  |
+| research_orders | 是 | pass | api_export.json | 378 | False |  |
+| research_risk | 是 | pass | api_export.json | 31 | False |  |
+| detail_results | 是 | pass | detail_api_export.json | 1485 | False |  |
+| detail_transactions | 是 | pass | detail_api_export.json | 378 | False |  |
+| detail_positions | 是 | pass | detail_api_export.json | 3675 | False |  |
+| detail_risk_tabs | 是 | pass | detail_api_export.json | 640 |  |  |
+| platform_logs | 否 | warn | detail_api_export.json | 1000 | True | platform logs may be partial; audit_log is canonical |
+| audit_log | 是 | pass | tabs_raw/audit_log.jsonl | 4681 | False |  |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/summary_metrics.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/summary_metrics.json
new file mode 100644
index 00000000..9b1f51da
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/summary_metrics.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_file": "raw/summary_metrics.json.gz",
+  "original_path": "summary_metrics.json",
+  "original_sha256": "317b30d9a2b2f3f72bb2dc7210bde94ef9e389e7939d8423c2b1f5ee5df3e21b",
+  "compressed_sha256": "135fb1ab5e2fa8cf0bcebadf03780f0ed8d55c488b02372a3b7ccbd393629cc0",
+  "original_bytes": 520
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/audit_log.jsonl b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/audit_log.jsonl
new file mode 100644
index 00000000..27ca1ed1
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/audit_log.jsonl
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_file": "raw/audit_log.jsonl.gz",
+  "original_path": "tabs_raw/audit_log.jsonl",
+  "original_sha256": "ceb62476e6ca432598fe3ea267b3158c921375bbb1150672643fd52ba582753a",
+  "compressed_sha256": "49e9ee759d2e965c26d7779e4578024476bdc9a6ad171355f56822f868b46a8d",
+  "original_bytes": 5709740
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/balances.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/balances.md
new file mode 100644
index 00000000..fb5770b8
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/balances.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_file": "raw/balances.md.gz",
+  "original_path": "tabs_raw/balances.md",
+  "original_sha256": "7f0d0c1bee6b6572516b623634b2a9d2169fea08f48e8a6aa033984cc1b09872",
+  "compressed_sha256": "aff79e04917b5b162bf6cd1545dbda15100863f97ce46b5a647459a33804fa59",
+  "original_bytes": 90521
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/daily_returns.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/daily_returns.md
new file mode 100644
index 00000000..0dc918e9
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/daily_returns.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_file": "raw/daily_returns.md.gz",
+  "original_path": "tabs_raw/daily_returns.md",
+  "original_sha256": "fae7f563d4decde5e0f5e2708b6502e4e712b42cb2ce35e8817779cc40060a50",
+  "compressed_sha256": "8e31e63bf90b2d042d4f045a290db99eb6f3a0892a34462ee3caea975395f468",
+  "original_bytes": 92691
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/logs.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/logs.md
new file mode 100644
index 00000000..0162a32d
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/logs.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_file": "raw/logs.md.gz",
+  "original_path": "tabs_raw/logs.md",
+  "original_sha256": "d811c3e0aa782563080368e27c8bd9f2aa226afd30972ddc3c7cba7ca0fa2af3",
+  "compressed_sha256": "da2d0526c6e8ab4e76a9654f7b2dbb3cb3dea37e4f30cedb17eac65b7e92368c",
+  "original_bytes": 290
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/period_risks.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/period_risks.md
new file mode 100644
index 00000000..122383d1
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/period_risks.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_file": "raw/period_risks.md.gz",
+  "original_path": "tabs_raw/period_risks.md",
+  "original_sha256": "661b2d392c210b2a0a17c1b5c5bfdf78e23dd67d577f87e008166997053e106c",
+  "compressed_sha256": "cb4afc7f1a21bf684ce07caa9ddb45476fe0733f6e048c4a5be76cc3fdb923a2",
+  "original_bytes": 62872
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/positioninfo.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/positioninfo.md
new file mode 100644
index 00000000..434b6cf7
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/positioninfo.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_file": "raw/positioninfo.md.gz",
+  "original_path": "tabs_raw/positioninfo.md",
+  "original_sha256": "b66559bf2f878363ba35fa31fa8fcb6e0ad2f6c7249c723448db04164ba99e6b",
+  "compressed_sha256": "2e8ffe3c2f7a5df3669a203e25084a9e1974f5a5c0a4e6ba18fc817b35ee87da",
+  "original_bytes": 378767
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/profile.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/profile.md
new file mode 100644
index 00000000..59be9c2b
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/profile.md
@@ -0,0 +1,541 @@
+# 性能分析
+
+## fund_code
+
+- 总耗时：0.044457s
+
+```text
+Total time: 0.044457 s
+File: /tmp/strategy/user_code.py
+Function: fund_code at line 129
+```
+
+## format_etf_name
+
+- 总耗时：0.293356s
+
+```text
+Total time: 0.293356 s
+File: /tmp/strategy/user_code.py
+Function: format_etf_name at line 131
+```
+
+## build_etf_display_names
+
+- 总耗时：0.57098s
+
+```text
+Total time: 0.57098 s
+File: /tmp/strategy/user_code.py
+Function: build_etf_display_names at line 144
+```
+
+## fetch_etf_official_name
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: fetch_etf_official_name at line 151
+```
+
+## load_etf_display_names
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: load_etf_display_names at line 161
+```
+
+## _audit_jsonable
+
+- 总耗时：0.906061s
+
+```text
+Total time: 0.906061 s
+File: /tmp/strategy/user_code.py
+Function: _audit_jsonable at line 169
+```
+
+## _context_time_fields
+
+- 总耗时：0.665808s
+
+```text
+Total time: 0.665808 s
+File: /tmp/strategy/user_code.py
+Function: _context_time_fields at line 198
+```
+
+## audit_event
+
+- 总耗时：66.6509s
+
+```text
+Total time: 66.6509 s
+File: /tmp/strategy/user_code.py
+Function: audit_event at line 205
+```
+
+## _copy_runtime_default
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: _copy_runtime_default at line 219
+```
+
+## _runtime_param
+
+- 总耗时：0.169145s
+
+```text
+Total time: 0.169145 s
+File: /tmp/strategy/user_code.py
+Function: _runtime_param at line 227
+```
+
+## _runtime_list_param
+
+- 总耗时：0.07164s
+
+```text
+Total time: 0.07164 s
+File: /tmp/strategy/user_code.py
+Function: _runtime_list_param at line 231
+```
+
+## snapshot_params
+
+- 总耗时：0.847107s
+
+```text
+Total time: 0.847107 s
+File: /tmp/strategy/user_code.py
+Function: snapshot_params at line 236
+```
+
+## validate_params
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: validate_params at line 326
+```
+
+## resolve_ma_long_windows
+
+- 总耗时：0.006776s
+
+```text
+Total time: 0.006776 s
+File: /tmp/strategy/user_code.py
+Function: resolve_ma_long_windows at line 414
+```
+
+## resolve_crowd_thresholds
+
+- 总耗时：0.012223s
+
+```text
+Total time: 0.012223 s
+File: /tmp/strategy/user_code.py
+Function: resolve_crowd_thresholds at line 419
+```
+
+## resolve_crowd_ret_windows
+
+- 总耗时：0.006518s
+
+```text
+Total time: 0.006518 s
+File: /tmp/strategy/user_code.py
+Function: resolve_crowd_ret_windows at line 428
+```
+
+## initialize
+
+- 总耗时：0.043361s
+
+```text
+Total time: 0.043361 s
+File: /tmp/strategy/user_code.py
+Function: initialize at line 435
+```
+
+## set_parameter
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: set_parameter at line 503
+```
+
+## _log_step
+
+- 总耗时：3.36736s
+
+```text
+Total time: 3.36736 s
+File: /tmp/strategy/user_code.py
+Function: _log_step at line 572
+```
+
+## compose_raw_weights
+
+- 总耗时：0.016803s
+
+```text
+Total time: 0.016803 s
+File: /tmp/strategy/user_code.py
+Function: compose_raw_weights at line 578
+```
+
+## _as_date
+
+- 总耗时：0.02396s
+
+```text
+Total time: 0.02396 s
+File: /tmp/strategy/user_code.py
+Function: _as_date at line 588
+```
+
+## _context_trade_date
+
+- 总耗时：0.316054s
+
+```text
+Total time: 0.316054 s
+File: /tmp/strategy/user_code.py
+Function: _context_trade_date at line 599
+```
+
+## _same_iso_week
+
+- 总耗时：0.017228s
+
+```text
+Total time: 0.017228 s
+File: /tmp/strategy/user_code.py
+Function: _same_iso_week at line 601
+```
+
+## build_rebalance_plan
+
+- 总耗时：234.817s
+
+```text
+Total time: 234.817 s
+File: /tmp/strategy/user_code.py
+Function: build_rebalance_plan at line 607
+```
+
+## weekly_check
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: weekly_check at line 676
+```
+
+## prepare_delay_only_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: prepare_delay_only_rebalance at line 679
+```
+
+## execute_pending_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: execute_pending_rebalance at line 690
+```
+
+## mark_live_like_signal_day
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: mark_live_like_signal_day at line 718
+```
+
+## execute_live_like_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: execute_live_like_rebalance at line 727
+```
+
+## prepare_weekend_close_rebalance
+
+- 总耗时：252.025s
+
+```text
+Total time: 252.025 s
+File: /tmp/strategy/user_code.py
+Function: prepare_weekend_close_rebalance at line 765
+```
+
+## execute_weekend_close_rebalance
+
+- 总耗时：30.2285s
+
+```text
+Total time: 30.2285 s
+File: /tmp/strategy/user_code.py
+Function: execute_weekend_close_rebalance at line 791
+```
+
+## normalize_field_frame
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: normalize_field_frame at line 832
+```
+
+## compute_history_count
+
+- 总耗时：0.015492s
+
+```text
+Total time: 0.015492 s
+File: /tmp/strategy/user_code.py
+Function: compute_history_count at line 841
+```
+
+## fetch_field
+
+- 总耗时：110.149s
+
+```text
+Total time: 110.149 s
+File: /tmp/strategy/user_code.py
+Function: fetch_field at line 851
+```
+
+## get_history_data
+
+- 总耗时：113.442s
+
+```text
+Total time: 113.442 s
+File: /tmp/strategy/user_code.py
+Function: get_history_data at line 871
+```
+
+## compute_trend_gates
+
+- 总耗时：2.97831s
+
+```text
+Total time: 2.97831 s
+File: /tmp/strategy/user_code.py
+Function: compute_trend_gates at line 884
+```
+
+## compute_momentum_scores
+
+- 总耗时：7.50479s
+
+```text
+Total time: 7.50479 s
+File: /tmp/strategy/user_code.py
+Function: compute_momentum_scores at line 900
+```
+
+## select_topk
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: select_topk at line 926
+```
+
+## compute_rp_weights
+
+- 总耗时：1.84971s
+
+```text
+Total time: 1.84971 s
+File: /tmp/strategy/user_code.py
+Function: compute_rp_weights at line 935
+```
+
+## compute_rsrs_multipliers
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_multipliers at line 964
+```
+
+## compute_rsrs_adjusted_scores
+
+- 总耗时：39.7464s
+
+```text
+Total time: 39.7464 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_adjusted_scores at line 973
+```
+
+## compute_momentum_tilt_multipliers
+
+- 总耗时：0.11612s
+
+```text
+Total time: 0.11612 s
+File: /tmp/strategy/user_code.py
+Function: compute_momentum_tilt_multipliers at line 1016
+```
+
+## compute_rsrs_tilt_multipliers
+
+- 总耗时：40.0151s
+
+```text
+Total time: 40.0151 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_tilt_multipliers at line 1037
+```
+
+## apply_relative_tilts
+
+- 总耗时：0.059453s
+
+```text
+Total time: 0.059453 s
+File: /tmp/strategy/user_code.py
+Function: apply_relative_tilts at line 1054
+```
+
+## compute_crowd_penalties
+
+- 总耗时：36.7677s
+
+```text
+Total time: 36.7677 s
+File: /tmp/strategy/user_code.py
+Function: compute_crowd_penalties at line 1070
+```
+
+## percentile_rank
+
+- 总耗时：8.98988s
+
+```text
+Total time: 8.98988 s
+File: /tmp/strategy/user_code.py
+Function: percentile_rank at line 1138
+```
+
+## compute_portfolio_vol_scale_detail
+
+- 总耗时：1.56437s
+
+```text
+Total time: 1.56437 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_scale_detail at line 1143
+```
+
+## compute_portfolio_vol_scale
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_scale at line 1174
+```
+
+## compute_portfolio_vol_asset_scales
+
+- 总耗时：3.82152s
+
+```text
+Total time: 3.82152 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_asset_scales at line 1177
+```
+
+## apply_fixed_gold_vol_relief
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: apply_fixed_gold_vol_relief at line 1194
+```
+
+## apply_dynamic_marginal_vol_relief
+
+- 总耗时：2.12634s
+
+```text
+Total time: 2.12634 s
+File: /tmp/strategy/user_code.py
+Function: apply_dynamic_marginal_vol_relief at line 1217
+```
+
+## select_dynamic_marginal_relief_asset
+
+- 总耗时：2.07143s
+
+```text
+Total time: 2.07143 s
+File: /tmp/strategy/user_code.py
+Function: select_dynamic_marginal_relief_asset at line 1238
+```
+
+## apply_weight_constraints
+
+- 总耗时：0.040995s
+
+```text
+Total time: 0.040995 s
+File: /tmp/strategy/user_code.py
+Function: apply_weight_constraints at line 1273
+```
+
+## execute_rebalance
+
+- 总耗时：13.8405s
+
+```text
+Total time: 13.8405 s
+File: /tmp/strategy/user_code.py
+Function: execute_rebalance at line 1288
+```
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/records.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/records.md
new file mode 100644
index 00000000..8043b956
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/records.md
@@ -0,0 +1,3 @@
+# Record 记录
+
+(无数据)
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/risk.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/risk.md
new file mode 100644
index 00000000..8b40eebd
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/risk.md
@@ -0,0 +1,37 @@
+# 风险指标
+
+- 记录数：31
+
+| metric | value |
+| --- | --- |
+| __version | 101 |
+| algorithm_return | 1.2757260135000044 |
+| algorithm_volatility | 0.08355847327292946 |
+| alpha | 0.14071401978170212 |
+| annual_algo_return | 0.1729054101184353 |
+| annual_bm_return | -0.01552798313301329 |
+| avg_excess_return | 0.0007606280372008427 |
+| avg_position_days | 795.3333333333334 |
+| avg_trade_return | 0.0504205778963544 |
+| benchmark_return | -0.07752074822165167 |
+| benchmark_volatility | 0.17880949192018716 |
+| beta | 0.1406247665174847 |
+| day_win_ratio | 0.5407292474786657 |
+| excess_return | 1.466967153042067 |
+| excess_return_max_drawdown | 0.2138423055497961 |
+| excess_return_max_drawdown_period | ['2024-09-13', '2024-10-08'] |
+| excess_return_sharpe | 0.8745209669226747 |
+| information | 1.0886011443852281 |
+| lose_count | 51 |
+| max_drawdown | 0.07577864706331894 |
+| max_drawdown_period | ['2021-11-22', '2022-01-28'] |
+| max_leverage | 0.0 |
+| period_label | 2026-04 |
+| profit_loss_ratio | 5.008322011146711 |
+| sharpe | 1.5905677175829014 |
+| sortino | 2.351794463723918 |
+| trading_days | 1289 |
+| treasury_return | 0.21282191780821919 |
+| turnover_rate | 0.020487745186870018 |
+| win_count | 140 |
+| win_ratio | 0.7329842931937173 |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/transactioninfo.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/transactioninfo.md
new file mode 100644
index 00000000..3299236c
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c/tabs_raw/transactioninfo.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0032-btdcc6252aadef8bb09592538da4dde54c",
+  "dataset_file": "raw/transactioninfo.md.gz",
+  "original_path": "tabs_raw/transactioninfo.md",
+  "original_sha256": "9231003f977b453cf45f5064d02865af7d04a533f92034c9407db117c9e27c8d",
+  "compressed_sha256": "453d227ceed56221df0fdae0b17a53ebd4ddfd766a6f42cac90eb4d2f46cd011",
+  "original_bytes": 31888
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/all_data.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/all_data.json
new file mode 100644
index 00000000..da026f50
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/all_data.json
@@ -0,0 +1,105 @@
+{
+  "api_export_json": "D:\\My Project\\Quant Trading\\strategies\\etf_factor_rotation\\backtest_runs\\20260701-0246-bt526c312fb836d6e07826ce170809486a\\api_export.json",
+  "extraction_method": "research_bundle",
+  "generated_at": "2026-06-30T18:50:06.737318+00:00",
+  "counts": {
+    "results": 1289,
+    "positions": 2386,
+    "orders": 378,
+    "records": 0,
+    "balances": 1289,
+    "period_risk_tabs": 10,
+    "audit_log_lines": 1630
+  },
+  "partial": {
+    "results": false,
+    "positions": false,
+    "orders": false,
+    "records": false,
+    "risk": false,
+    "period_risks": false,
+    "balances": false,
+    "logs": true,
+    "audit_log": false
+  },
+  "primary_extraction_method": "joinquant_research_get_backtest",
+  "fallback_extraction_method": "",
+  "research_export_path": "jq_auto_exports/research_backtest_526c312fb836d6e07826ce170809486a.json",
+  "research_downloaded": true,
+  "detail_api_used": true,
+  "tabs": {
+    "daily_returns": {
+      "path": "tabs_raw/daily_returns.md",
+      "partial": false,
+      "record_count": 1289
+    },
+    "transactioninfo": {
+      "path": "tabs_raw/transactioninfo.md",
+      "partial": false,
+      "record_count": 378
+    },
+    "positioninfo": {
+      "path": "tabs_raw/positioninfo.md",
+      "partial": false,
+      "record_count": 2386
+    },
+    "records": {
+      "path": "tabs_raw/records.md",
+      "partial": false,
+      "record_count": 0
+    },
+    "balances": {
+      "path": "tabs_raw/balances.md",
+      "partial": false,
+      "record_count": 1289
+    },
+    "risk": {
+      "path": "tabs_raw/risk.md",
+      "partial": false,
+      "record_count": 31
+    },
+    "period_risks": {
+      "path": "tabs_raw/period_risks.md",
+      "partial": false,
+      "record_count": 10
+    },
+    "profile": {
+      "path": "tabs_raw/profile.md",
+      "partial": false,
+      "record_count": 9131
+    },
+    "logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true,
+      "record_count": 143
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "partial": false,
+      "record_count": 1630
+    }
+  },
+  "note": "Generated from JoinQuant research get_backtest() schema v3 bundle. Platform logs are not provided by get_backtest().",
+  "integrity_status": "complete",
+  "integrity_issues": [],
+  "sources": {
+    "research": {
+      "path": "api_export.json",
+      "present": true,
+      "method": "joinquant_research_get_backtest"
+    },
+    "detail_api": {
+      "path": "detail_api_export.json",
+      "present": true
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "present": true,
+      "count": 1630
+    },
+    "platform_logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true
+    }
+  }
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/api_export.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/api_export.json
new file mode 100644
index 00000000..acf38afc
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/api_export.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_file": "raw/api_export.json.gz",
+  "original_path": "api_export.json",
+  "original_sha256": "5ca0d57eddc4d68c0666a648fa8ae947e7e245376b79a0bbe27889859a46166b",
+  "compressed_sha256": "0f220177b98c9168e238171dcd67d2fa097cf0246d03b49f5c890e88bc261704",
+  "original_bytes": 3827821
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/detail_api_export.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/detail_api_export.json
new file mode 100644
index 00000000..6e0f096f
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/detail_api_export.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_file": "raw/detail_api_export.json.gz",
+  "original_path": "detail_api_export.json",
+  "original_sha256": "12c70ee14b6d0ae1b37613abb337844620a44a3ca3261e301f7f2de6a54b1eff",
+  "compressed_sha256": "7fc77f963819736f60d350045885ab71908ed41be5a0a9c44e00ef4be7d74905",
+  "original_bytes": 4370080
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/integrity.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/integrity.json
new file mode 100644
index 00000000..2653b7cc
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/integrity.json
@@ -0,0 +1,153 @@
+{
+  "status": "complete",
+  "generated_at": "2026-06-30T18:50:06.780422+00:00",
+  "issues": [],
+  "checks": [
+    {
+      "name": "research_bundle",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": null,
+      "partial": null,
+      "message": "research get_backtest bundle is required"
+    },
+    {
+      "name": "detail_api_bundle",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": null,
+      "partial": null,
+      "message": "detail API bundle is required"
+    },
+    {
+      "name": "metadata",
+      "required": true,
+      "status": "pass",
+      "source": "metadata.json",
+      "count": null,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "summary_metrics",
+      "required": true,
+      "status": "pass",
+      "source": "summary_metrics.json",
+      "count": null,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "research_results",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 1289,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_positions",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 2386,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_orders",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 378,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_risk",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 31,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_results",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 1485,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_transactions",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 378,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_positions",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 3675,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_risk_tabs",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 640,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "platform_logs",
+      "required": false,
+      "status": "warn",
+      "source": "detail_api_export.json",
+      "count": 1000,
+      "partial": true,
+      "message": "platform logs may be partial; audit_log is canonical"
+    },
+    {
+      "name": "audit_log",
+      "required": true,
+      "status": "pass",
+      "source": "tabs_raw/audit_log.jsonl",
+      "count": 1630,
+      "partial": false,
+      "message": ""
+    }
+  ],
+  "sources": {
+    "research": {
+      "path": "api_export.json",
+      "present": true,
+      "method": "joinquant_research_get_backtest"
+    },
+    "detail_api": {
+      "path": "detail_api_export.json",
+      "present": true
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "present": true,
+      "count": 1630
+    },
+    "platform_logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true
+    }
+  }
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/metadata.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/metadata.json
new file mode 100644
index 00000000..8e194938
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/metadata.json
@@ -0,0 +1,26 @@
+{
+  "strategy_name": "etf_factor_rotation",
+  "run_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "strategy_file": "",
+  "strategy_dir": "",
+  "start_date_requested": "",
+  "start_date_effective": "2021-01-01",
+  "end_date_requested": "",
+  "end_date_effective": "2026-04-30",
+  "capital": 100000,
+  "backtest_id": "526c312fb836d6e07826ce170809486a",
+  "joinquant_backtest_id": "526c312fb836d6e07826ce170809486a",
+  "backtest_url": "",
+  "generated_at": "2026-07-01T02:49:55",
+  "extraction_method": "joinquant_research_get_backtest",
+  "primary_extraction_method": "joinquant_research_get_backtest",
+  "fallback_extraction_method": "",
+  "research_export_path": "jq_auto_exports/research_backtest_526c312fb836d6e07826ce170809486a.json",
+  "research_downloaded": true,
+  "detail_api_used": true,
+  "frequency": "1d",
+  "py_version": "Python3",
+  "internal_backtest_id": "b6cb7f66e1fd859bcf372f0813ab5d75",
+  "audit_token": "etf_factor_rotation-s04-weekend-close-signal-next-open-variant-v2-20260701024558-124bb940",
+  "audit_path": "jq_auto_audit/etf_factor_rotation-s04-weekend-close-signal-next-open-variant-v2-20260701024558-124bb940.jsonl"
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/backtest_report.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/backtest_report.md
new file mode 100644
index 00000000..ee6e37ed
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/backtest_report.md
@@ -0,0 +1,32 @@
+# 回测数据汇总
+
+- 策略名称：etf_factor_rotation
+- 回测 ID：526c312fb836d6e07826ce170809486a
+- 区间：2021-01-01 至 2026-04-30
+- 提取方式：聚宽研究环境 get_backtest()；详情页接口仅作补充。
+
+## 核心指标
+
+| 指标 | 值 |
+| --- | --- |
+| 策略收益 | 127.57% |
+| 策略年化收益 | 17.29% |
+| 基准收益 | -7.75% |
+| 超额收益 | 146.70% |
+| 最大回撤 | 7.58% |
+| 夏普比率 | 1.591 |
+| 阿尔法 | 0.141 |
+| 贝塔 | 0.141 |
+| 信息比率 | 1.089 |
+
+## 数据覆盖
+
+| 数据 | 记录数 | 完整度 |
+| --- | ---: | --- |
+| 每日收益 | 1289 | 完整 |
+| 每日持仓&收益 | 2386 | 完整 |
+| 订单/交易 | 378 | 完整 |
+| record 记录 | 0 | 完整 |
+| 每日账户市值 | 1289 | 完整 |
+| 分期风险 | 10 | 完整 |
+| 平台日志 |  | 详情页接口部分 |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/data-integrity.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/data-integrity.md
new file mode 100644
index 00000000..ddf34b60
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/report/data-integrity.md
@@ -0,0 +1,26 @@
+# 数据完整性报告
+
+- 状态：complete
+- 生成时间：2026-06-30T18:50:06.780422+00:00
+
+## 问题
+- 无
+
+## 检查项
+
+| 检查项 | 必须 | 状态 | 来源 | 记录数 | partial | 说明 |
+| --- | --- | --- | --- | ---: | --- | --- |
+| research_bundle | 是 | pass | api_export.json |  |  | research get_backtest bundle is required |
+| detail_api_bundle | 是 | pass | detail_api_export.json |  |  | detail API bundle is required |
+| metadata | 是 | pass | metadata.json |  |  |  |
+| summary_metrics | 是 | pass | summary_metrics.json |  |  |  |
+| research_results | 是 | pass | api_export.json | 1289 | False |  |
+| research_positions | 是 | pass | api_export.json | 2386 | False |  |
+| research_orders | 是 | pass | api_export.json | 378 | False |  |
+| research_risk | 是 | pass | api_export.json | 31 | False |  |
+| detail_results | 是 | pass | detail_api_export.json | 1485 | False |  |
+| detail_transactions | 是 | pass | detail_api_export.json | 378 | False |  |
+| detail_positions | 是 | pass | detail_api_export.json | 3675 | False |  |
+| detail_risk_tabs | 是 | pass | detail_api_export.json | 640 |  |  |
+| platform_logs | 否 | warn | detail_api_export.json | 1000 | True | platform logs may be partial; audit_log is canonical |
+| audit_log | 是 | pass | tabs_raw/audit_log.jsonl | 1630 | False |  |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/summary_metrics.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/summary_metrics.json
new file mode 100644
index 00000000..7ca89e31
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/summary_metrics.json
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_file": "raw/summary_metrics.json.gz",
+  "original_path": "summary_metrics.json",
+  "original_sha256": "317b30d9a2b2f3f72bb2dc7210bde94ef9e389e7939d8423c2b1f5ee5df3e21b",
+  "compressed_sha256": "135fb1ab5e2fa8cf0bcebadf03780f0ed8d55c488b02372a3b7ccbd393629cc0",
+  "original_bytes": 520
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/audit_log.jsonl b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/audit_log.jsonl
new file mode 100644
index 00000000..b54363ee
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/audit_log.jsonl
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_file": "raw/audit_log.jsonl.gz",
+  "original_path": "tabs_raw/audit_log.jsonl",
+  "original_sha256": "b673ad3c49c5782fee85e5d062b55ff081a029eb3f58dda4d87ac2dc2b28525b",
+  "compressed_sha256": "2dd4f6c4a4b5c439e14dd8d30560557c2788de087cd8b7864ad0f22b03b9210c",
+  "original_bytes": 1742407
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/balances.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/balances.md
new file mode 100644
index 00000000..d85b3cec
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/balances.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_file": "raw/balances.md.gz",
+  "original_path": "tabs_raw/balances.md",
+  "original_sha256": "7f0d0c1bee6b6572516b623634b2a9d2169fea08f48e8a6aa033984cc1b09872",
+  "compressed_sha256": "aff79e04917b5b162bf6cd1545dbda15100863f97ce46b5a647459a33804fa59",
+  "original_bytes": 90521
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/daily_returns.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/daily_returns.md
new file mode 100644
index 00000000..a36e8952
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/daily_returns.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_file": "raw/daily_returns.md.gz",
+  "original_path": "tabs_raw/daily_returns.md",
+  "original_sha256": "fae7f563d4decde5e0f5e2708b6502e4e712b42cb2ce35e8817779cc40060a50",
+  "compressed_sha256": "8e31e63bf90b2d042d4f045a290db99eb6f3a0892a34462ee3caea975395f468",
+  "original_bytes": 92691
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/logs.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/logs.md
new file mode 100644
index 00000000..1af1c61c
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/logs.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_file": "raw/logs.md.gz",
+  "original_path": "tabs_raw/logs.md",
+  "original_sha256": "d811c3e0aa782563080368e27c8bd9f2aa226afd30972ddc3c7cba7ca0fa2af3",
+  "compressed_sha256": "da2d0526c6e8ab4e76a9654f7b2dbb3cb3dea37e4f30cedb17eac65b7e92368c",
+  "original_bytes": 290
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/period_risks.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/period_risks.md
new file mode 100644
index 00000000..c99ad2ec
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/period_risks.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_file": "raw/period_risks.md.gz",
+  "original_path": "tabs_raw/period_risks.md",
+  "original_sha256": "661b2d392c210b2a0a17c1b5c5bfdf78e23dd67d577f87e008166997053e106c",
+  "compressed_sha256": "cb4afc7f1a21bf684ce07caa9ddb45476fe0733f6e048c4a5be76cc3fdb923a2",
+  "original_bytes": 62872
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/positioninfo.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/positioninfo.md
new file mode 100644
index 00000000..57ab0ab5
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/positioninfo.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_file": "raw/positioninfo.md.gz",
+  "original_path": "tabs_raw/positioninfo.md",
+  "original_sha256": "b66559bf2f878363ba35fa31fa8fcb6e0ad2f6c7249c723448db04164ba99e6b",
+  "compressed_sha256": "2e8ffe3c2f7a5df3669a203e25084a9e1974f5a5c0a4e6ba18fc817b35ee87da",
+  "original_bytes": 378767
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/profile.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/profile.md
new file mode 100644
index 00000000..45b31840
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/profile.md
@@ -0,0 +1,601 @@
+# 性能分析
+
+## fund_code
+
+- 总耗时：0.010966s
+
+```text
+Total time: 0.010966 s
+File: /tmp/strategy/user_code.py
+Function: fund_code at line 129
+```
+
+## format_etf_name
+
+- 总耗时：0.069979s
+
+```text
+Total time: 0.069979 s
+File: /tmp/strategy/user_code.py
+Function: format_etf_name at line 131
+```
+
+## build_etf_display_names
+
+- 总耗时：0.135742s
+
+```text
+Total time: 0.135742 s
+File: /tmp/strategy/user_code.py
+Function: build_etf_display_names at line 144
+```
+
+## fetch_etf_official_name
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: fetch_etf_official_name at line 151
+```
+
+## load_etf_display_names
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: load_etf_display_names at line 161
+```
+
+## _audit_jsonable
+
+- 总耗时：0.292948s
+
+```text
+Total time: 0.292948 s
+File: /tmp/strategy/user_code.py
+Function: _audit_jsonable at line 169
+```
+
+## _context_time_fields
+
+- 总耗时：0.273677s
+
+```text
+Total time: 0.273677 s
+File: /tmp/strategy/user_code.py
+Function: _context_time_fields at line 198
+```
+
+## audit_event
+
+- 总耗时：27.3032s
+
+```text
+Total time: 27.3032 s
+File: /tmp/strategy/user_code.py
+Function: audit_event at line 205
+```
+
+## _copy_runtime_default
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: _copy_runtime_default at line 219
+```
+
+## _runtime_param
+
+- 总耗时：0.036228s
+
+```text
+Total time: 0.036228 s
+File: /tmp/strategy/user_code.py
+Function: _runtime_param at line 227
+```
+
+## _runtime_list_param
+
+- 总耗时：0.015368s
+
+```text
+Total time: 0.015368 s
+File: /tmp/strategy/user_code.py
+Function: _runtime_list_param at line 231
+```
+
+## snapshot_params
+
+- 总耗时：0.178768s
+
+```text
+Total time: 0.178768 s
+File: /tmp/strategy/user_code.py
+Function: snapshot_params at line 236
+```
+
+## validate_params
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: validate_params at line 326
+```
+
+## resolve_ma_long_windows
+
+- 总耗时：0.001585s
+
+```text
+Total time: 0.001585 s
+File: /tmp/strategy/user_code.py
+Function: resolve_ma_long_windows at line 414
+```
+
+## resolve_crowd_thresholds
+
+- 总耗时：0.002929s
+
+```text
+Total time: 0.002929 s
+File: /tmp/strategy/user_code.py
+Function: resolve_crowd_thresholds at line 419
+```
+
+## resolve_crowd_ret_windows
+
+- 总耗时：0.001343s
+
+```text
+Total time: 0.001343 s
+File: /tmp/strategy/user_code.py
+Function: resolve_crowd_ret_windows at line 428
+```
+
+## initialize
+
+- 总耗时：0.039548s
+
+```text
+Total time: 0.039548 s
+File: /tmp/strategy/user_code.py
+Function: initialize at line 435
+```
+
+## set_parameter
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: set_parameter at line 505
+```
+
+## _log_step
+
+- 总耗时：0.756459s
+
+```text
+Total time: 0.756459 s
+File: /tmp/strategy/user_code.py
+Function: _log_step at line 574
+```
+
+## compose_raw_weights
+
+- 总耗时：0.00355s
+
+```text
+Total time: 0.00355 s
+File: /tmp/strategy/user_code.py
+Function: compose_raw_weights at line 580
+```
+
+## _as_date
+
+- 总耗时：0.005303s
+
+```text
+Total time: 0.005303 s
+File: /tmp/strategy/user_code.py
+Function: _as_date at line 590
+```
+
+## _context_trade_date
+
+- 总耗时：0.079189s
+
+```text
+Total time: 0.079189 s
+File: /tmp/strategy/user_code.py
+Function: _context_trade_date at line 601
+```
+
+## _same_iso_week
+
+- 总耗时：0.003889s
+
+```text
+Total time: 0.003889 s
+File: /tmp/strategy/user_code.py
+Function: _same_iso_week at line 603
+```
+
+## _float_list
+
+- 总耗时：0.002569s
+
+```text
+Total time: 0.002569 s
+File: /tmp/strategy/user_code.py
+Function: _float_list at line 609
+```
+
+## _weekend_close_batch_id
+
+- 总耗时：0.00255s
+
+```text
+Total time: 0.00255 s
+File: /tmp/strategy/user_code.py
+Function: _weekend_close_batch_id at line 616
+```
+
+## _enrich_weekend_close_plan
+
+- 总耗时：0.186498s
+
+```text
+Total time: 0.186498 s
+File: /tmp/strategy/user_code.py
+Function: _enrich_weekend_close_plan at line 619
+```
+
+## _report_signal_plan
+
+- 总耗时：79.9831s
+
+```text
+Total time: 79.9831 s
+File: /tmp/strategy/user_code.py
+Function: _report_signal_plan at line 635
+```
+
+## _suppress_execution_notice
+
+- 总耗时：0.002315s
+
+```text
+Total time: 0.002315 s
+File: /tmp/strategy/user_code.py
+Function: _suppress_execution_notice at line 646
+```
+
+## _resume_execution_notice
+
+- 总耗时：0.002269s
+
+```text
+Total time: 0.002269 s
+File: /tmp/strategy/user_code.py
+Function: _resume_execution_notice at line 658
+```
+
+## build_rebalance_plan
+
+- 总耗时：51.4301s
+
+```text
+Total time: 51.4301 s
+File: /tmp/strategy/user_code.py
+Function: build_rebalance_plan at line 668
+```
+
+## weekly_check
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: weekly_check at line 737
+```
+
+## prepare_delay_only_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: prepare_delay_only_rebalance at line 740
+```
+
+## execute_pending_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: execute_pending_rebalance at line 751
+```
+
+## mark_live_like_signal_day
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: mark_live_like_signal_day at line 779
+```
+
+## execute_live_like_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: execute_live_like_rebalance at line 788
+```
+
+## prepare_weekend_close_rebalance
+
+- 总耗时：136.37s
+
+```text
+Total time: 136.37 s
+File: /tmp/strategy/user_code.py
+Function: prepare_weekend_close_rebalance at line 826
+```
+
+## execute_weekend_close_rebalance
+
+- 总耗时：19.7858s
+
+```text
+Total time: 19.7858 s
+File: /tmp/strategy/user_code.py
+Function: execute_weekend_close_rebalance at line 855
+```
+
+## normalize_field_frame
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: normalize_field_frame at line 906
+```
+
+## compute_history_count
+
+- 总耗时：0.003345s
+
+```text
+Total time: 0.003345 s
+File: /tmp/strategy/user_code.py
+Function: compute_history_count at line 915
+```
+
+## fetch_field
+
+- 总耗时：24.0671s
+
+```text
+Total time: 24.0671 s
+File: /tmp/strategy/user_code.py
+Function: fetch_field at line 925
+```
+
+## get_history_data
+
+- 总耗时：24.8426s
+
+```text
+Total time: 24.8426 s
+File: /tmp/strategy/user_code.py
+Function: get_history_data at line 945
+```
+
+## compute_trend_gates
+
+- 总耗时：0.64189s
+
+```text
+Total time: 0.64189 s
+File: /tmp/strategy/user_code.py
+Function: compute_trend_gates at line 958
+```
+
+## compute_momentum_scores
+
+- 总耗时：1.58835s
+
+```text
+Total time: 1.58835 s
+File: /tmp/strategy/user_code.py
+Function: compute_momentum_scores at line 974
+```
+
+## select_topk
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: select_topk at line 1000
+```
+
+## compute_rp_weights
+
+- 总耗时：0.38362s
+
+```text
+Total time: 0.38362 s
+File: /tmp/strategy/user_code.py
+Function: compute_rp_weights at line 1009
+```
+
+## compute_rsrs_multipliers
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_multipliers at line 1038
+```
+
+## compute_rsrs_adjusted_scores
+
+- 总耗时：8.67028s
+
+```text
+Total time: 8.67028 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_adjusted_scores at line 1047
+```
+
+## compute_momentum_tilt_multipliers
+
+- 总耗时：0.025009s
+
+```text
+Total time: 0.025009 s
+File: /tmp/strategy/user_code.py
+Function: compute_momentum_tilt_multipliers at line 1090
+```
+
+## compute_rsrs_tilt_multipliers
+
+- 总耗时：8.7307s
+
+```text
+Total time: 8.7307 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_tilt_multipliers at line 1111
+```
+
+## apply_relative_tilts
+
+- 总耗时：0.012662s
+
+```text
+Total time: 0.012662 s
+File: /tmp/strategy/user_code.py
+Function: apply_relative_tilts at line 1128
+```
+
+## compute_crowd_penalties
+
+- 总耗时：7.88395s
+
+```text
+Total time: 7.88395 s
+File: /tmp/strategy/user_code.py
+Function: compute_crowd_penalties at line 1144
+```
+
+## percentile_rank
+
+- 总耗时：1.93572s
+
+```text
+Total time: 1.93572 s
+File: /tmp/strategy/user_code.py
+Function: percentile_rank at line 1212
+```
+
+## compute_portfolio_vol_scale_detail
+
+- 总耗时：0.31576s
+
+```text
+Total time: 0.31576 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_scale_detail at line 1217
+```
+
+## compute_portfolio_vol_scale
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_scale at line 1248
+```
+
+## compute_portfolio_vol_asset_scales
+
+- 总耗时：0.804712s
+
+```text
+Total time: 0.804712 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_asset_scales at line 1251
+```
+
+## apply_fixed_gold_vol_relief
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: apply_fixed_gold_vol_relief at line 1268
+```
+
+## apply_dynamic_marginal_vol_relief
+
+- 总耗时：0.460663s
+
+```text
+Total time: 0.460663 s
+File: /tmp/strategy/user_code.py
+Function: apply_dynamic_marginal_vol_relief at line 1291
+```
+
+## select_dynamic_marginal_relief_asset
+
+- 总耗时：0.448597s
+
+```text
+Total time: 0.448597 s
+File: /tmp/strategy/user_code.py
+Function: select_dynamic_marginal_relief_asset at line 1312
+```
+
+## apply_weight_constraints
+
+- 总耗时：0.008117s
+
+```text
+Total time: 0.008117 s
+File: /tmp/strategy/user_code.py
+Function: apply_weight_constraints at line 1347
+```
+
+## execute_rebalance
+
+- 总耗时：15.5078s
+
+```text
+Total time: 15.5078 s
+File: /tmp/strategy/user_code.py
+Function: execute_rebalance at line 1362
+```
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/records.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/records.md
new file mode 100644
index 00000000..8043b956
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/records.md
@@ -0,0 +1,3 @@
+# Record 记录
+
+(无数据)
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/risk.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/risk.md
new file mode 100644
index 00000000..8b40eebd
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/risk.md
@@ -0,0 +1,37 @@
+# 风险指标
+
+- 记录数：31
+
+| metric | value |
+| --- | --- |
+| __version | 101 |
+| algorithm_return | 1.2757260135000044 |
+| algorithm_volatility | 0.08355847327292946 |
+| alpha | 0.14071401978170212 |
+| annual_algo_return | 0.1729054101184353 |
+| annual_bm_return | -0.01552798313301329 |
+| avg_excess_return | 0.0007606280372008427 |
+| avg_position_days | 795.3333333333334 |
+| avg_trade_return | 0.0504205778963544 |
+| benchmark_return | -0.07752074822165167 |
+| benchmark_volatility | 0.17880949192018716 |
+| beta | 0.1406247665174847 |
+| day_win_ratio | 0.5407292474786657 |
+| excess_return | 1.466967153042067 |
+| excess_return_max_drawdown | 0.2138423055497961 |
+| excess_return_max_drawdown_period | ['2024-09-13', '2024-10-08'] |
+| excess_return_sharpe | 0.8745209669226747 |
+| information | 1.0886011443852281 |
+| lose_count | 51 |
+| max_drawdown | 0.07577864706331894 |
+| max_drawdown_period | ['2021-11-22', '2022-01-28'] |
+| max_leverage | 0.0 |
+| period_label | 2026-04 |
+| profit_loss_ratio | 5.008322011146711 |
+| sharpe | 1.5905677175829014 |
+| sortino | 2.351794463723918 |
+| trading_days | 1289 |
+| treasury_return | 0.21282191780821919 |
+| turnover_rate | 0.020487745186870018 |
+| win_count | 140 |
+| win_ratio | 0.7329842931937173 |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/transactioninfo.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/transactioninfo.md
new file mode 100644
index 00000000..bed5c08e
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a/tabs_raw/transactioninfo.md
@@ -0,0 +1,11 @@
+{
+  "kind": "data_center_pointer",
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+  "snapshot_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0246-bt526c312fb836d6e07826ce170809486a",
+  "dataset_file": "raw/transactioninfo.md.gz",
+  "original_path": "tabs_raw/transactioninfo.md",
+  "original_sha256": "9231003f977b453cf45f5064d02865af7d04a533f92034c9407db117c9e27c8d",
+  "compressed_sha256": "453d227ceed56221df0fdae0b17a53ebd4ddfd766a6f42cac90eb4d2f46cd011",
+  "original_bytes": 31888
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/all_data.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/all_data.json
new file mode 100644
index 00000000..a516963e
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/all_data.json
@@ -0,0 +1,209 @@
+{
+
+  "api_export_json": "D:\\My Project\\Quant Trading\\strategies\\etf_factor_rotation\\backtest_runs\\20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d\\api_export.json",
+
+  "extraction_method": "research_bundle",
+
+  "generated_at": "2026-06-30T19:37:11.537380+00:00",
+
+  "counts": {
+
+    "results": 1289,
+
+    "positions": 2386,
+
+    "orders": 378,
+
+    "records": 0,
+
+    "balances": 1289,
+
+    "period_risk_tabs": 10,
+
+    "audit_log_lines": 1630
+
+  },
+
+  "partial": {
+
+    "results": false,
+
+    "positions": false,
+
+    "orders": false,
+
+    "records": false,
+
+    "risk": false,
+
+    "period_risks": false,
+
+    "balances": false,
+
+    "logs": true,
+
+    "audit_log": false
+
+  },
+
+  "primary_extraction_method": "joinquant_research_get_backtest",
+
+  "fallback_extraction_method": "",
+
+  "research_export_path": "jq_auto_exports/research_backtest_bfc5066102fc7eac2f3dfd3da0276a3d.json",
+
+  "research_downloaded": true,
+
+  "detail_api_used": true,
+
+  "tabs": {
+
+    "daily_returns": {
+
+      "path": "tabs_raw/daily_returns.md",
+
+      "partial": false,
+
+      "record_count": 1289
+
+    },
+
+    "transactioninfo": {
+
+      "path": "tabs_raw/transactioninfo.md",
+
+      "partial": false,
+
+      "record_count": 378
+
+    },
+
+    "positioninfo": {
+
+      "path": "tabs_raw/positioninfo.md",
+
+      "partial": false,
+
+      "record_count": 2386
+
+    },
+
+    "records": {
+
+      "path": "tabs_raw/records.md",
+
+      "partial": false,
+
+      "record_count": 0
+
+    },
+
+    "balances": {
+
+      "path": "tabs_raw/balances.md",
+
+      "partial": false,
+
+      "record_count": 1289
+
+    },
+
+    "risk": {
+
+      "path": "tabs_raw/risk.md",
+
+      "partial": false,
+
+      "record_count": 31
+
+    },
+
+    "period_risks": {
+
+      "path": "tabs_raw/period_risks.md",
+
+      "partial": false,
+
+      "record_count": 10
+
+    },
+
+    "profile": {
+
+      "path": "tabs_raw/profile.md",
+
+      "partial": false,
+
+      "record_count": 9137
+
+    },
+
+    "logs": {
+
+      "path": "tabs_raw/logs.md",
+
+      "partial": true,
+
+      "record_count": 143
+
+    },
+
+    "audit_log": {
+
+      "path": "tabs_raw/audit_log.jsonl",
+
+      "partial": false,
+
+      "record_count": 1630
+
+    }
+
+  },
+
+  "note": "Generated from JoinQuant research get_backtest() schema v3 bundle. Platform logs are not provided by get_backtest().",
+
+  "integrity_status": "complete",
+
+  "integrity_issues": [],
+
+  "sources": {
+
+    "research": {
+
+      "path": "api_export.json",
+
+      "present": true,
+
+      "method": "joinquant_research_get_backtest"
+
+    },
+
+    "detail_api": {
+
+      "path": "detail_api_export.json",
+
+      "present": true
+
+    },
+
+    "audit_log": {
+
+      "path": "tabs_raw/audit_log.jsonl",
+
+      "present": true,
+
+      "count": 1630
+
+    },
+
+    "platform_logs": {
+
+      "path": "tabs_raw/logs.md",
+
+      "partial": true
+
+    }
+
+  }
+
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/api_export.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/api_export.json
new file mode 100644
index 00000000..34d8316d
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/api_export.json
@@ -0,0 +1,21 @@
+{
+
+  "kind": "data_center_pointer",
+
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+
+  "snapshot_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_file": "raw/api_export.json.gz",
+
+  "original_path": "api_export.json",
+
+  "original_sha256": "7c347eb465d800422c4f50a761c401156985f1330b3cb90d585b1bd697a89221",
+
+  "compressed_sha256": "ed009f3dcbe7d329e092fa016fe83dc64c3754d1331fc399e6424e059c1f9726",
+
+  "original_bytes": 3784618
+
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/detail_api_export.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/detail_api_export.json
new file mode 100644
index 00000000..fa8d0096
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/detail_api_export.json
@@ -0,0 +1,21 @@
+{
+
+  "kind": "data_center_pointer",
+
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+
+  "snapshot_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_file": "raw/detail_api_export.json.gz",
+
+  "original_path": "detail_api_export.json",
+
+  "original_sha256": "3ccd53bb53f1e860ba5842f364cc4fec65245e29d8a0f04062d8023fb21047f4",
+
+  "compressed_sha256": "333d4d723204b27a3588141bee9d6b8bf12bc17f2d71a2e855c6d3443d2791b1",
+
+  "original_bytes": 4370413
+
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/integrity.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/integrity.json
new file mode 100644
index 00000000..6bc75065
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/integrity.json
@@ -0,0 +1,153 @@
+{
+  "status": "complete",
+  "generated_at": "2026-06-30T19:37:11.606499+00:00",
+  "issues": [],
+  "checks": [
+    {
+      "name": "research_bundle",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": null,
+      "partial": null,
+      "message": "research get_backtest bundle is required"
+    },
+    {
+      "name": "detail_api_bundle",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": null,
+      "partial": null,
+      "message": "detail API bundle is required"
+    },
+    {
+      "name": "metadata",
+      "required": true,
+      "status": "pass",
+      "source": "metadata.json",
+      "count": null,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "summary_metrics",
+      "required": true,
+      "status": "pass",
+      "source": "summary_metrics.json",
+      "count": null,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "research_results",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 1289,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_positions",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 2386,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_orders",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 378,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "research_risk",
+      "required": true,
+      "status": "pass",
+      "source": "api_export.json",
+      "count": 31,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_results",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 1485,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_transactions",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 378,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_positions",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 3675,
+      "partial": false,
+      "message": ""
+    },
+    {
+      "name": "detail_risk_tabs",
+      "required": true,
+      "status": "pass",
+      "source": "detail_api_export.json",
+      "count": 640,
+      "partial": null,
+      "message": ""
+    },
+    {
+      "name": "platform_logs",
+      "required": false,
+      "status": "warn",
+      "source": "detail_api_export.json",
+      "count": 1000,
+      "partial": true,
+      "message": "platform logs may be partial; audit_log is canonical"
+    },
+    {
+      "name": "audit_log",
+      "required": true,
+      "status": "pass",
+      "source": "tabs_raw/audit_log.jsonl",
+      "count": 1630,
+      "partial": false,
+      "message": ""
+    }
+  ],
+  "sources": {
+    "research": {
+      "path": "api_export.json",
+      "present": true,
+      "method": "joinquant_research_get_backtest"
+    },
+    "detail_api": {
+      "path": "detail_api_export.json",
+      "present": true
+    },
+    "audit_log": {
+      "path": "tabs_raw/audit_log.jsonl",
+      "present": true,
+      "count": 1630
+    },
+    "platform_logs": {
+      "path": "tabs_raw/logs.md",
+      "partial": true
+    }
+  }
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/metadata.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/metadata.json
new file mode 100644
index 00000000..7d0d874d
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/metadata.json
@@ -0,0 +1,44 @@
+{
+
+  "strategy_name": "etf_factor_rotation",
+  "run_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+  "strategy_file": "",
+  "strategy_dir": "",
+
+  "start_date_requested": "",
+
+  "start_date_effective": "2021-01-01",
+
+  "end_date_requested": "",
+
+  "end_date_effective": "2026-04-30",
+
+  "capital": 100000,
+  "backtest_id": "bfc5066102fc7eac2f3dfd3da0276a3d",
+  "joinquant_backtest_id": "bfc5066102fc7eac2f3dfd3da0276a3d",
+  "backtest_url": "",
+  "generated_at": "2026-07-01T03:36:53",
+
+  "extraction_method": "joinquant_research_get_backtest",
+
+  "primary_extraction_method": "joinquant_research_get_backtest",
+
+  "fallback_extraction_method": "",
+
+  "research_export_path": "jq_auto_exports/research_backtest_bfc5066102fc7eac2f3dfd3da0276a3d.json",
+
+  "research_downloaded": true,
+
+  "detail_api_used": true,
+
+  "frequency": "1d",
+
+  "py_version": "Python3",
+
+  "internal_backtest_id": "9f29ab61c433f227af01e2ed1cdcff85",
+
+  "audit_token": "etf_factor_rotation-s05-official-current-baseline-20260701033128-41374eef",
+
+  "audit_path": "jq_auto_audit/etf_factor_rotation-s05-official-current-baseline-20260701033128-41374eef.jsonl"
+
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/backtest_report.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/backtest_report.md
new file mode 100644
index 00000000..ae9c2f9c
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/backtest_report.md
@@ -0,0 +1,32 @@
+# 回测数据汇总
+
+- 策略名称：etf_factor_rotation
+- 回测 ID：bfc5066102fc7eac2f3dfd3da0276a3d
+- 区间：2021-01-01 至 2026-04-30
+- 提取方式：聚宽研究环境 get_backtest()；详情页接口仅作补充。
+
+## 核心指标
+
+| 指标 | 值 |
+| --- | --- |
+| 策略收益 | 127.57% |
+| 策略年化收益 | 17.29% |
+| 基准收益 | -7.75% |
+| 超额收益 | 146.70% |
+| 最大回撤 | 7.58% |
+| 夏普比率 | 1.591 |
+| 阿尔法 | 0.141 |
+| 贝塔 | 0.141 |
+| 信息比率 | 1.089 |
+
+## 数据覆盖
+
+| 数据 | 记录数 | 完整度 |
+| --- | ---: | --- |
+| 每日收益 | 1289 | 完整 |
+| 每日持仓&收益 | 2386 | 完整 |
+| 订单/交易 | 378 | 完整 |
+| record 记录 | 0 | 完整 |
+| 每日账户市值 | 1289 | 完整 |
+| 分期风险 | 10 | 完整 |
+| 平台日志 |  | 详情页接口部分 |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/data-integrity.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/data-integrity.md
new file mode 100644
index 00000000..a2faf395
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/report/data-integrity.md
@@ -0,0 +1,26 @@
+# 数据完整性报告
+
+- 状态：complete
+- 生成时间：2026-06-30T19:37:11.606499+00:00
+
+## 问题
+- 无
+
+## 检查项
+
+| 检查项 | 必须 | 状态 | 来源 | 记录数 | partial | 说明 |
+| --- | --- | --- | --- | ---: | --- | --- |
+| research_bundle | 是 | pass | api_export.json |  |  | research get_backtest bundle is required |
+| detail_api_bundle | 是 | pass | detail_api_export.json |  |  | detail API bundle is required |
+| metadata | 是 | pass | metadata.json |  |  |  |
+| summary_metrics | 是 | pass | summary_metrics.json |  |  |  |
+| research_results | 是 | pass | api_export.json | 1289 | False |  |
+| research_positions | 是 | pass | api_export.json | 2386 | False |  |
+| research_orders | 是 | pass | api_export.json | 378 | False |  |
+| research_risk | 是 | pass | api_export.json | 31 | False |  |
+| detail_results | 是 | pass | detail_api_export.json | 1485 | False |  |
+| detail_transactions | 是 | pass | detail_api_export.json | 378 | False |  |
+| detail_positions | 是 | pass | detail_api_export.json | 3675 | False |  |
+| detail_risk_tabs | 是 | pass | detail_api_export.json | 640 |  |  |
+| platform_logs | 否 | warn | detail_api_export.json | 1000 | True | platform logs may be partial; audit_log is canonical |
+| audit_log | 是 | pass | tabs_raw/audit_log.jsonl | 1630 | False |  |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/summary_metrics.json b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/summary_metrics.json
new file mode 100644
index 00000000..5d6c9898
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/summary_metrics.json
@@ -0,0 +1,21 @@
+{
+
+  "kind": "data_center_pointer",
+
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+
+  "snapshot_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_file": "raw/summary_metrics.json.gz",
+
+  "original_path": "summary_metrics.json",
+
+  "original_sha256": "317b30d9a2b2f3f72bb2dc7210bde94ef9e389e7939d8423c2b1f5ee5df3e21b",
+
+  "compressed_sha256": "135fb1ab5e2fa8cf0bcebadf03780f0ed8d55c488b02372a3b7ccbd393629cc0",
+
+  "original_bytes": 520
+
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/audit_log.jsonl b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/audit_log.jsonl
new file mode 100644
index 00000000..7ec0f5a4
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/audit_log.jsonl
@@ -0,0 +1,21 @@
+{
+
+  "kind": "data_center_pointer",
+
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+
+  "snapshot_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_file": "raw/audit_log.jsonl.gz",
+
+  "original_path": "tabs_raw/audit_log.jsonl",
+
+  "original_sha256": "590310655c88b251a25813ac6ddcd0dd7d318bb88f3a5665a4cf61ca40757e51",
+
+  "compressed_sha256": "8f264094a0c5c4b0c9fa2028fad6c1b77c97cb2cbad15e0880f52b32e83d94ac",
+
+  "original_bytes": 1698903
+
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/balances.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/balances.md
new file mode 100644
index 00000000..b067f58f
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/balances.md
@@ -0,0 +1,21 @@
+{
+
+  "kind": "data_center_pointer",
+
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+
+  "snapshot_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_file": "raw/balances.md.gz",
+
+  "original_path": "tabs_raw/balances.md",
+
+  "original_sha256": "7f0d0c1bee6b6572516b623634b2a9d2169fea08f48e8a6aa033984cc1b09872",
+
+  "compressed_sha256": "a56c0800aceb2f51a891f68cd72f8c15229adebf668d89e8d51ef19b9f3d7ad6",
+
+  "original_bytes": 90521
+
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/daily_returns.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/daily_returns.md
new file mode 100644
index 00000000..c39df5ea
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/daily_returns.md
@@ -0,0 +1,21 @@
+{
+
+  "kind": "data_center_pointer",
+
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+
+  "snapshot_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_file": "raw/daily_returns.md.gz",
+
+  "original_path": "tabs_raw/daily_returns.md",
+
+  "original_sha256": "fae7f563d4decde5e0f5e2708b6502e4e712b42cb2ce35e8817779cc40060a50",
+
+  "compressed_sha256": "8e31e63bf90b2d042d4f045a290db99eb6f3a0892a34462ee3caea975395f468",
+
+  "original_bytes": 92691
+
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/logs.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/logs.md
new file mode 100644
index 00000000..7e5e2a86
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/logs.md
@@ -0,0 +1,21 @@
+{
+
+  "kind": "data_center_pointer",
+
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+
+  "snapshot_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_file": "raw/logs.md.gz",
+
+  "original_path": "tabs_raw/logs.md",
+
+  "original_sha256": "d811c3e0aa782563080368e27c8bd9f2aa226afd30972ddc3c7cba7ca0fa2af3",
+
+  "compressed_sha256": "f01427d06d60706892b923f8c27fba870fa5891fe71b9523b5c79748da6ee971",
+
+  "original_bytes": 290
+
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/period_risks.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/period_risks.md
new file mode 100644
index 00000000..196683fc
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/period_risks.md
@@ -0,0 +1,21 @@
+{
+
+  "kind": "data_center_pointer",
+
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+
+  "snapshot_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_file": "raw/period_risks.md.gz",
+
+  "original_path": "tabs_raw/period_risks.md",
+
+  "original_sha256": "661b2d392c210b2a0a17c1b5c5bfdf78e23dd67d577f87e008166997053e106c",
+
+  "compressed_sha256": "ef3869e5e1cab71c32cb054dbd7d8decb3db98a6eb1c186d32983f8655ec4be4",
+
+  "original_bytes": 62872
+
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/positioninfo.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/positioninfo.md
new file mode 100644
index 00000000..5ee0b985
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/positioninfo.md
@@ -0,0 +1,21 @@
+{
+
+  "kind": "data_center_pointer",
+
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+
+  "snapshot_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_file": "raw/positioninfo.md.gz",
+
+  "original_path": "tabs_raw/positioninfo.md",
+
+  "original_sha256": "b66559bf2f878363ba35fa31fa8fcb6e0ad2f6c7249c723448db04164ba99e6b",
+
+  "compressed_sha256": "2e8ffe3c2f7a5df3669a203e25084a9e1974f5a5c0a4e6ba18fc817b35ee87da",
+
+  "original_bytes": 378767
+
+}
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/profile.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/profile.md
new file mode 100644
index 00000000..9a5a43e7
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/profile.md
@@ -0,0 +1,601 @@
+# 性能分析
+
+## fund_code
+
+- 总耗时：0.011969s
+
+```text
+Total time: 0.011969 s
+File: /tmp/strategy/user_code.py
+Function: fund_code at line 129
+```
+
+## format_etf_name
+
+- 总耗时：0.085193s
+
+```text
+Total time: 0.085193 s
+File: /tmp/strategy/user_code.py
+Function: format_etf_name at line 131
+```
+
+## build_etf_display_names
+
+- 总耗时：0.158997s
+
+```text
+Total time: 0.158997 s
+File: /tmp/strategy/user_code.py
+Function: build_etf_display_names at line 144
+```
+
+## fetch_etf_official_name
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: fetch_etf_official_name at line 151
+```
+
+## load_etf_display_names
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: load_etf_display_names at line 161
+```
+
+## _audit_jsonable
+
+- 总耗时：0.378645s
+
+```text
+Total time: 0.378645 s
+File: /tmp/strategy/user_code.py
+Function: _audit_jsonable at line 169
+```
+
+## _context_time_fields
+
+- 总耗时：0.308122s
+
+```text
+Total time: 0.308122 s
+File: /tmp/strategy/user_code.py
+Function: _context_time_fields at line 198
+```
+
+## audit_event
+
+- 总耗时：31.6594s
+
+```text
+Total time: 31.6594 s
+File: /tmp/strategy/user_code.py
+Function: audit_event at line 205
+```
+
+## _copy_runtime_default
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: _copy_runtime_default at line 219
+```
+
+## _runtime_param
+
+- 总耗时：0.041921s
+
+```text
+Total time: 0.041921 s
+File: /tmp/strategy/user_code.py
+Function: _runtime_param at line 227
+```
+
+## _runtime_list_param
+
+- 总耗时：0.017167s
+
+```text
+Total time: 0.017167 s
+File: /tmp/strategy/user_code.py
+Function: _runtime_list_param at line 231
+```
+
+## snapshot_params
+
+- 总耗时：0.231506s
+
+```text
+Total time: 0.231506 s
+File: /tmp/strategy/user_code.py
+Function: snapshot_params at line 236
+```
+
+## validate_params
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: validate_params at line 326
+```
+
+## resolve_ma_long_windows
+
+- 总耗时：0.001621s
+
+```text
+Total time: 0.001621 s
+File: /tmp/strategy/user_code.py
+Function: resolve_ma_long_windows at line 414
+```
+
+## resolve_crowd_thresholds
+
+- 总耗时：0.003103s
+
+```text
+Total time: 0.003103 s
+File: /tmp/strategy/user_code.py
+Function: resolve_crowd_thresholds at line 419
+```
+
+## resolve_crowd_ret_windows
+
+- 总耗时：0.001539s
+
+```text
+Total time: 0.001539 s
+File: /tmp/strategy/user_code.py
+Function: resolve_crowd_ret_windows at line 428
+```
+
+## initialize
+
+- 总耗时：0.148887s
+
+```text
+Total time: 0.148887 s
+File: /tmp/strategy/user_code.py
+Function: initialize at line 435
+```
+
+## set_parameter
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: set_parameter at line 505
+```
+
+## _log_step
+
+- 总耗时：0.705124s
+
+```text
+Total time: 0.705124 s
+File: /tmp/strategy/user_code.py
+Function: _log_step at line 576
+```
+
+## compose_raw_weights
+
+- 总耗时：0.00395s
+
+```text
+Total time: 0.00395 s
+File: /tmp/strategy/user_code.py
+Function: compose_raw_weights at line 582
+```
+
+## _as_date
+
+- 总耗时：0.006395s
+
+```text
+Total time: 0.006395 s
+File: /tmp/strategy/user_code.py
+Function: _as_date at line 592
+```
+
+## _context_trade_date
+
+- 总耗时：0.089695s
+
+```text
+Total time: 0.089695 s
+File: /tmp/strategy/user_code.py
+Function: _context_trade_date at line 603
+```
+
+## _same_iso_week
+
+- 总耗时：0.00428s
+
+```text
+Total time: 0.00428 s
+File: /tmp/strategy/user_code.py
+Function: _same_iso_week at line 605
+```
+
+## _float_list
+
+- 总耗时：0.002799s
+
+```text
+Total time: 0.002799 s
+File: /tmp/strategy/user_code.py
+Function: _float_list at line 611
+```
+
+## _weekend_close_batch_id
+
+- 总耗时：0.002712s
+
+```text
+Total time: 0.002712 s
+File: /tmp/strategy/user_code.py
+Function: _weekend_close_batch_id at line 618
+```
+
+## _enrich_weekend_close_plan
+
+- 总耗时：0.198788s
+
+```text
+Total time: 0.198788 s
+File: /tmp/strategy/user_code.py
+Function: _enrich_weekend_close_plan at line 621
+```
+
+## _report_signal_plan
+
+- 总耗时：82.7943s
+
+```text
+Total time: 82.7943 s
+File: /tmp/strategy/user_code.py
+Function: _report_signal_plan at line 637
+```
+
+## _suppress_execution_notice
+
+- 总耗时：0.002616s
+
+```text
+Total time: 0.002616 s
+File: /tmp/strategy/user_code.py
+Function: _suppress_execution_notice at line 648
+```
+
+## _resume_execution_notice
+
+- 总耗时：0.002481s
+
+```text
+Total time: 0.002481 s
+File: /tmp/strategy/user_code.py
+Function: _resume_execution_notice at line 660
+```
+
+## build_rebalance_plan
+
+- 总耗时：59.8797s
+
+```text
+Total time: 59.8797 s
+File: /tmp/strategy/user_code.py
+Function: build_rebalance_plan at line 670
+```
+
+## weekly_check
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: weekly_check at line 739
+```
+
+## prepare_delay_only_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: prepare_delay_only_rebalance at line 742
+```
+
+## execute_pending_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: execute_pending_rebalance at line 753
+```
+
+## mark_live_like_signal_day
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: mark_live_like_signal_day at line 781
+```
+
+## execute_live_like_rebalance
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: execute_live_like_rebalance at line 790
+```
+
+## prepare_weekend_close_rebalance
+
+- 总耗时：148.299s
+
+```text
+Total time: 148.299 s
+File: /tmp/strategy/user_code.py
+Function: prepare_weekend_close_rebalance at line 828
+```
+
+## execute_weekend_close_rebalance
+
+- 总耗时：23.9867s
+
+```text
+Total time: 23.9867 s
+File: /tmp/strategy/user_code.py
+Function: execute_weekend_close_rebalance at line 857
+```
+
+## normalize_field_frame
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: normalize_field_frame at line 908
+```
+
+## compute_history_count
+
+- 总耗时：0.00371s
+
+```text
+Total time: 0.00371 s
+File: /tmp/strategy/user_code.py
+Function: compute_history_count at line 917
+```
+
+## fetch_field
+
+- 总耗时：29.1131s
+
+```text
+Total time: 29.1131 s
+File: /tmp/strategy/user_code.py
+Function: fetch_field at line 927
+```
+
+## get_history_data
+
+- 总耗时：30.2038s
+
+```text
+Total time: 30.2038 s
+File: /tmp/strategy/user_code.py
+Function: get_history_data at line 947
+```
+
+## compute_trend_gates
+
+- 总耗时：0.714151s
+
+```text
+Total time: 0.714151 s
+File: /tmp/strategy/user_code.py
+Function: compute_trend_gates at line 960
+```
+
+## compute_momentum_scores
+
+- 总耗时：1.79872s
+
+```text
+Total time: 1.79872 s
+File: /tmp/strategy/user_code.py
+Function: compute_momentum_scores at line 976
+```
+
+## select_topk
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: select_topk at line 1002
+```
+
+## compute_rp_weights
+
+- 总耗时：0.408629s
+
+```text
+Total time: 0.408629 s
+File: /tmp/strategy/user_code.py
+Function: compute_rp_weights at line 1011
+```
+
+## compute_rsrs_multipliers
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_multipliers at line 1040
+```
+
+## compute_rsrs_adjusted_scores
+
+- 总耗时：9.99111s
+
+```text
+Total time: 9.99111 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_adjusted_scores at line 1049
+```
+
+## compute_momentum_tilt_multipliers
+
+- 总耗时：0.027213s
+
+```text
+Total time: 0.027213 s
+File: /tmp/strategy/user_code.py
+Function: compute_momentum_tilt_multipliers at line 1092
+```
+
+## compute_rsrs_tilt_multipliers
+
+- 总耗时：10.0563s
+
+```text
+Total time: 10.0563 s
+File: /tmp/strategy/user_code.py
+Function: compute_rsrs_tilt_multipliers at line 1113
+```
+
+## apply_relative_tilts
+
+- 总耗时：0.013963s
+
+```text
+Total time: 0.013963 s
+File: /tmp/strategy/user_code.py
+Function: apply_relative_tilts at line 1130
+```
+
+## compute_crowd_penalties
+
+- 总耗时：9.03816s
+
+```text
+Total time: 9.03816 s
+File: /tmp/strategy/user_code.py
+Function: compute_crowd_penalties at line 1146
+```
+
+## percentile_rank
+
+- 总耗时：2.19101s
+
+```text
+Total time: 2.19101 s
+File: /tmp/strategy/user_code.py
+Function: percentile_rank at line 1214
+```
+
+## compute_portfolio_vol_scale_detail
+
+- 总耗时：0.351456s
+
+```text
+Total time: 0.351456 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_scale_detail at line 1219
+```
+
+## compute_portfolio_vol_scale
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_scale at line 1250
+```
+
+## compute_portfolio_vol_asset_scales
+
+- 总耗时：0.872704s
+
+```text
+Total time: 0.872704 s
+File: /tmp/strategy/user_code.py
+Function: compute_portfolio_vol_asset_scales at line 1253
+```
+
+## apply_fixed_gold_vol_relief
+
+- 总耗时：0s
+
+```text
+Total time: 0 s
+File: /tmp/strategy/user_code.py
+Function: apply_fixed_gold_vol_relief at line 1270
+```
+
+## apply_dynamic_marginal_vol_relief
+
+- 总耗时：0.491186s
+
+```text
+Total time: 0.491186 s
+File: /tmp/strategy/user_code.py
+Function: apply_dynamic_marginal_vol_relief at line 1293
+```
+
+## select_dynamic_marginal_relief_asset
+
+- 总耗时：0.47858s
+
+```text
+Total time: 0.47858 s
+File: /tmp/strategy/user_code.py
+Function: select_dynamic_marginal_relief_asset at line 1314
+```
+
+## apply_weight_constraints
+
+- 总耗时：0.008776s
+
+```text
+Total time: 0.008776 s
+File: /tmp/strategy/user_code.py
+Function: apply_weight_constraints at line 1349
+```
+
+## execute_rebalance
+
+- 总耗时：19.2976s
+
+```text
+Total time: 19.2976 s
+File: /tmp/strategy/user_code.py
+Function: execute_rebalance at line 1364
+```
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/records.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/records.md
new file mode 100644
index 00000000..8043b956
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/records.md
@@ -0,0 +1,3 @@
+# Record 记录
+
+(无数据)
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/risk.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/risk.md
new file mode 100644
index 00000000..8b40eebd
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/risk.md
@@ -0,0 +1,37 @@
+# 风险指标
+
+- 记录数：31
+
+| metric | value |
+| --- | --- |
+| __version | 101 |
+| algorithm_return | 1.2757260135000044 |
+| algorithm_volatility | 0.08355847327292946 |
+| alpha | 0.14071401978170212 |
+| annual_algo_return | 0.1729054101184353 |
+| annual_bm_return | -0.01552798313301329 |
+| avg_excess_return | 0.0007606280372008427 |
+| avg_position_days | 795.3333333333334 |
+| avg_trade_return | 0.0504205778963544 |
+| benchmark_return | -0.07752074822165167 |
+| benchmark_volatility | 0.17880949192018716 |
+| beta | 0.1406247665174847 |
+| day_win_ratio | 0.5407292474786657 |
+| excess_return | 1.466967153042067 |
+| excess_return_max_drawdown | 0.2138423055497961 |
+| excess_return_max_drawdown_period | ['2024-09-13', '2024-10-08'] |
+| excess_return_sharpe | 0.8745209669226747 |
+| information | 1.0886011443852281 |
+| lose_count | 51 |
+| max_drawdown | 0.07577864706331894 |
+| max_drawdown_period | ['2021-11-22', '2022-01-28'] |
+| max_leverage | 0.0 |
+| period_label | 2026-04 |
+| profit_loss_ratio | 5.008322011146711 |
+| sharpe | 1.5905677175829014 |
+| sortino | 2.351794463723918 |
+| trading_days | 1289 |
+| treasury_return | 0.21282191780821919 |
+| turnover_rate | 0.020487745186870018 |
+| win_count | 140 |
+| win_ratio | 0.7329842931937173 |
diff --git a/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/transactioninfo.md b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/transactioninfo.md
new file mode 100644
index 00000000..bfaa388d
--- /dev/null
+++ b/strategies/etf_factor_rotation/backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d/tabs_raw/transactioninfo.md
@@ -0,0 +1,21 @@
+{
+
+  "kind": "data_center_pointer",
+
+  "dataset_id": "etf_factor_rotation_backtest_runs",
+
+  "snapshot_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_snapshot": "research_datasets/etf_factor_rotation_backtest_runs/20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+
+  "dataset_file": "raw/transactioninfo.md.gz",
+
+  "original_path": "tabs_raw/transactioninfo.md",
+
+  "original_sha256": "9231003f977b453cf45f5064d02865af7d04a533f92034c9407db117c9e27c8d",
+
+  "compressed_sha256": "5eea156208babdd4921f3702c17e435d5b16c015a4e14341cfc546293f948b86",
+
+  "original_bytes": 31888
+
+}
diff --git a/strategies/etf_factor_rotation/etf_factor_rotation.py b/strategies/etf_factor_rotation/etf_factor_rotation.py
index 0546bae2..ec965a74 100644
--- a/strategies/etf_factor_rotation/etf_factor_rotation.py
+++ b/strategies/etf_factor_rotation/etf_factor_rotation.py
@@ -113,7 +113,7 @@
     "MinWeight": 0.05,
     "RebalanceThreshold": 0.03,
     "MaxTotalWeight": 1.0,
-    "ExecutionTimingMode": "baseline",
+    "ExecutionTimingMode": "weekend-close-signal-next-open",
     "use_real_price": False,
     "fq_mode": None,
     "history_buffer": 100,
@@ -123,6 +123,7 @@
     "baseline",
     "logic-2-delay-only",
     "logic-3-live-like",
+    "weekend-close-signal-next-open",
 )
 DEFAULT_EXECUTION_TIMING_MODE = PARAM_DEFAULTS["ExecutionTimingMode"]
 PORTFOLIO_VOL_RELIEF_MODES = (
@@ -560,7 +561,7 @@ def initialize(context):
             time='open',
             reference_security='000300.XSHG'
         )
-    else:
+    elif g.ExecutionTimingMode == "logic-3-live-like":
         run_weekly(
             mark_live_like_signal_day,
             weekday=1,
@@ -572,6 +573,18 @@ def initialize(context):
             time='open',
             reference_security='000300.XSHG'
         )
+    else:
+        run_weekly(
+            prepare_weekend_close_rebalance,
+            weekday=-1,
+            time='15:30',
+            force=False,
+        )
+        run_daily(
+            execute_weekend_close_rebalance,
+            time='open',
+            reference_security='000300.XSHG'
+        )
 
 
 def on_strategy_end(context):
@@ -686,8 +699,10 @@ def set_parameter(context):
     g.audit_token = JQ_AUTO_AUDIT_TOKEN
     g.audit_path = "%s/%s.jsonl" % (JQ_AUTO_AUDIT_DIR, g.audit_token)
     g.audit_seq = 0
-    g.pending_rebalances = []
-    g.pending_live_like_signal_days = []
+    if not hasattr(g, "pending_rebalances"):
+        g.pending_rebalances = []
+    if not hasattr(g, "pending_live_like_signal_days"):
+        g.pending_live_like_signal_days = []
 
 
 # ============================================================
@@ -730,15 +745,105 @@ def compose_raw_weights(tilted_weights, trend_gates, crowd_penalties):
 # ============================================================
 # weekly_check — 周频调仓主函数
 # ============================================================
+def _as_date(value):
+    """把聚宽日期、pandas 日期或字符串统一成 date。"""
+    if value is None:
+        return None
+    if isinstance(value, datetime):
+        return value.date()
+    if isinstance(value, date):
+        return value
+    try:
+        return pd.Timestamp(value).date()
+    except Exception:
+        return value
+
+
 def _context_trade_date(context):
     """返回当前任务对应的自然日。"""
-    current_dt = getattr(context, "current_dt", None)
-    if current_dt is not None and hasattr(current_dt, "date"):
-        return current_dt.date()
-    return current_dt
+    return _as_date(getattr(context, "current_dt", None))
+
+
+def _same_iso_week(left, right):
+    left = _as_date(left)
+    right = _as_date(right)
+    if left is None or right is None:
+        return False
+    return left.isocalendar()[:2] == right.isocalendar()[:2]
+
+
+def _float_list(values):
+    try:
+        if hasattr(values, "tolist"):
+            values = values.tolist()
+    except Exception:
+        pass
+    return [float(value) for value in list(values or [])]
+
 
+def _weekend_close_batch_id(signal_date):
+    token = str(getattr(g, "audit_token", "manual")).replace("/", "_").replace("\\", "_")
+    return "%s-weekend-close-%s" % (token, signal_date)
 
-def build_rebalance_plan(context):
+
+def _enrich_weekend_close_plan(context, plan, signal_date):
+    weights = _float_list(plan.get("final_weights"))
+    portfolio = getattr(context, "portfolio", None)
+    total_value = getattr(portfolio, "total_value", None)
+    plan["final_weights"] = weights
+    plan["target_weights"] = weights
+    plan["target_values"] = [total_value * weight for weight in weights] if total_value is not None else []
+    plan["portfolio_total_value"] = total_value
+    plan["signal_date"] = signal_date
+    plan["asof_date"] = signal_date
+    plan["prepared_date"] = signal_date
+    plan["trade_date"] = plan.get("trade_date")
+    plan["batch_id"] = plan.get("batch_id") or _weekend_close_batch_id(signal_date)
+    plan["plan_cached"] = True
+    plan["signal_notice_sent"] = False
+    return plan
+
+
+def _report_signal_plan(plan):
+    if FeishuRelayTools is None:
+        return False
+    reporter = getattr(FeishuRelayTools, "report_signal_plan", None)
+    if not callable(reporter):
+        return False
+    try:
+        return bool(reporter(plan))
+    except Exception as exc:
+        log.warning("feishu signal notice failed: %s", exc)
+        return False
+
+
+def _suppress_execution_notice(batch_id):
+    if FeishuRelayTools is None:
+        return False
+    suppress = getattr(FeishuRelayTools, "suppress_execution_notice", None)
+    if not callable(suppress):
+        return False
+    try:
+        suppress(batch_id=batch_id, reason="signal_notice_already_sent")
+        return True
+    except Exception as exc:
+        log.warning("feishu execution notice suppress failed: %s", exc)
+        return False
+
+
+def _resume_execution_notice():
+    if FeishuRelayTools is None:
+        return
+    resume = getattr(FeishuRelayTools, "resume_execution_notice", None)
+    if not callable(resume):
+        return
+    try:
+        resume()
+    except Exception as exc:
+        log.warning("feishu execution notice resume failed: %s", exc)
+
+
+def build_rebalance_plan(context, asof_date=None):
     """生成一次调仓所需的完整信号快照，但不直接下单。
 
     流程：TrendGate → RPWeight → MomentumScore → MomentumTilt
@@ -750,7 +855,11 @@ def build_rebalance_plan(context):
     etf_names = params["etf_names"]
 
     # 1. 拉取历史数据
-    prices = get_history_data(context, pool, params)
+    if asof_date is not None:
+        asof_date = _as_date(asof_date)
+    else:
+        asof_date = getattr(context, "previous_date", None)
+    prices = get_history_data(context, pool, params, asof_date=asof_date)
 
     # 2. 计算趋势门槛
     trend_gates = compute_trend_gates(prices, pool, params)
@@ -823,7 +932,7 @@ def build_rebalance_plan(context):
         final_weights_before_constraints=final_weights_before_constraints,
         final_weights=final_weights,
         execution_timing_mode=params["ExecutionTimingMode"],
-        asof_date=getattr(context, "previous_date", None),
+        asof_date=asof_date,
         trade_date=_context_trade_date(context),
     )
 
@@ -831,7 +940,7 @@ def build_rebalance_plan(context):
         "pool": pool,
         "final_weights": final_weights,
         "params": params,
-        "asof_date": getattr(context, "previous_date", None),
+        "asof_date": asof_date,
         "prepared_date": _context_trade_date(context),
     }
 
@@ -945,6 +1054,95 @@ def execute_live_like_rebalance(context):
     queue.pop(0)
 
 
+def prepare_weekend_close_rebalance(context):
+    """收盘后生成候选信号 plan，次开盘跨周时执行。"""
+    signal_date = _context_trade_date(context)
+    params = snapshot_params()
+    if signal_date is None:
+        audit_event(
+            "weekend_close_signal_skip",
+            context,
+            execution_timing_mode=params["ExecutionTimingMode"],
+            signal_date=signal_date,
+            reason="signal_date_unavailable",
+        )
+        return
+
+    plan = build_rebalance_plan(context, asof_date=signal_date)
+    plan = _enrich_weekend_close_plan(context, plan, signal_date)
+    plan["signal_notice_sent"] = _report_signal_plan(plan)
+    g.pending_rebalances = [plan]
+    audit_event(
+        "weekend_close_plan_cached",
+        context,
+        execution_timing_mode=plan["params"]["ExecutionTimingMode"],
+        signal_date=signal_date,
+        asof_date=signal_date,
+        batch_id=plan["batch_id"],
+        target_weights=plan["target_weights"],
+        target_values=plan["target_values"],
+        signal_notice_sent=plan["signal_notice_sent"],
+        plan_cached=True,
+        final_weights=plan["final_weights"],
+    )
+
+
+def execute_weekend_close_rebalance(context):
+    """次交易日开盘执行已缓存的收盘信号 plan，不重新计算信号。"""
+    queue = getattr(g, "pending_rebalances", [])
+    if not queue:
+        return
+
+    pending = queue[0]
+    trade_date = _context_trade_date(context)
+    signal_date = pending.get("signal_date")
+    if trade_date is None or signal_date is None:
+        audit_event(
+            "weekend_close_execute_wait",
+            context,
+            execution_timing_mode=pending["params"]["ExecutionTimingMode"],
+            signal_date=signal_date,
+            asof_date=pending.get("asof_date"),
+            trade_date=trade_date,
+        )
+        return
+    if _same_iso_week(signal_date, trade_date):
+        audit_event(
+            "weekend_close_plan_discarded",
+            context,
+            execution_timing_mode=pending["params"]["ExecutionTimingMode"],
+            signal_date=signal_date,
+            asof_date=pending.get("asof_date"),
+            trade_date=trade_date,
+            reason="not_last_trade_day_of_week",
+        )
+        g.pending_rebalances.pop(0)
+        return
+
+    pending["trade_date"] = trade_date
+    suppress_reason = "signal_notice_already_sent" if pending.get("signal_notice_sent") else ""
+    notice_suppressed = _suppress_execution_notice(pending.get("batch_id")) if suppress_reason else False
+    audit_event(
+        "weekend_close_execute",
+        context,
+        execution_timing_mode=pending["params"]["ExecutionTimingMode"],
+        signal_date=signal_date,
+        asof_date=pending.get("asof_date"),
+        batch_id=pending.get("batch_id"),
+        trade_date=trade_date,
+        execution_order_called=True,
+        execution_notice_suppressed=notice_suppressed,
+        suppress_reason=suppress_reason if notice_suppressed else "",
+        final_weights=pending["final_weights"],
+    )
+    try:
+        execute_rebalance(context, pending["pool"], pending["final_weights"], pending["params"])
+    finally:
+        if notice_suppressed:
+            _resume_execution_notice()
+    g.pending_rebalances.pop(0)
+
+
 # ============================================================
 # normalize_field_frame — 数据返回结构归一化
 # ============================================================
@@ -1026,7 +1224,7 @@ def fetch_field(pool, field, count, params, end_date=None):
     return result.dropna(how='all')
 
 
-def get_history_data(context, pool, params):
+def get_history_data(context, pool, params, asof_date=None):
     """
     拉取足够长的历史 OHLC + 成交额数据，并预计算日收益率。
 
@@ -1035,12 +1233,13 @@ def get_history_data(context, pool, params):
       close_ret: DataFrame（index=日期, columns=ETF代码），close 的 pct_change()
     """
     needed = compute_history_count(params)
+    history_end_date = asof_date if asof_date is not None else getattr(context, "previous_date", None)
 
     prices = {}
-    prices['close'] = fetch_field(pool, 'close', needed, params, end_date=context.previous_date)
-    prices['high'] = fetch_field(pool, 'high', needed, params, end_date=context.previous_date)
-    prices['low'] = fetch_field(pool, 'low', needed, params, end_date=context.previous_date)
-    prices['amount'] = fetch_field(pool, 'money', needed, params, end_date=context.previous_date)
+    prices['close'] = fetch_field(pool, 'close', needed, params, end_date=history_end_date)
+    prices['high'] = fetch_field(pool, 'high', needed, params, end_date=history_end_date)
+    prices['low'] = fetch_field(pool, 'low', needed, params, end_date=history_end_date)
+    prices['amount'] = fetch_field(pool, 'money', needed, params, end_date=history_end_date)
 
     # 预计算日收益率，下游风险平价和组合波动率复用同一份
     prices['close_ret'] = prices['close'].pct_change()
@@ -1048,7 +1247,7 @@ def get_history_data(context, pool, params):
     # 数据新鲜度日志：确保历史数据不晚于 context.previous_date
     close_df = prices['close']
     last_dt = close_df.index[-1] if len(close_df) else None
-    log.info("history end_date=%s, context.previous_date=%s", last_dt, context.previous_date)
+    log.info("history end_date=%s, asof_date=%s", last_dt, history_end_date)
 
     return prices
 
diff --git a/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/manifest.json b/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/manifest.json
new file mode 100644
index 00000000..0ffe6933
--- /dev/null
+++ b/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/manifest.json
@@ -0,0 +1,68 @@
+{
+  "batch_id": "20260701-live-aligned-execution-gate",
+  "strategy": "etf_factor_rotation",
+  "created": "2026-07-01T00:00:00+08:00",
+  "status": "pending",
+  "scenarios": {
+    "s01-baseline-original": {
+      "status": "completed",
+      "runs": [
+        {
+          "run_id": "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0",
+          "label": "default",
+          "params_diff": {
+            "ExecutionTimingMode": "baseline"
+          },
+          "status": "completed"
+        }
+      ]
+    },
+    "s02-logic3-code-variant": {
+      "status": "completed",
+      "runs": [
+        {
+          "run_id": "20260701-0025-bt0d4e21c752867aa36b89ee13d7540352",
+          "label": "default",
+          "params_diff": {},
+          "status": "completed"
+        }
+      ]
+    },
+    "s03-weekend-close-signal-next-open-variant": {
+      "status": "superseded",
+      "superseded_by": "s04-weekend-close-signal-next-open-variant-v2",
+      "superseded_reason": "initial no-trade run; s04 is the active reproducible weekend-close variant evidence",
+      "runs": [
+        {
+          "run_id": "20260701-0028-btcb35093c739b769b0c7cebb1bbe141b5",
+          "label": "default",
+          "params_diff": {},
+          "status": "superseded"
+        }
+      ]
+    },
+    "s04-weekend-close-signal-next-open-variant-v2": {
+      "status": "completed",
+      "runs": [
+        {
+          "run_id": "20260701-0246-bt526c312fb836d6e07826ce170809486a",
+          "label": "default",
+          "params_diff": {},
+          "status": "completed"
+        }
+      ]
+    },
+    "s05-official-current-baseline": {
+      "runs": [
+        {
+          "run_id": "20260701-0332-btbfc5066102fc7eac2f3dfd3da0276a3d",
+          "label": "default",
+          "params_diff": {},
+          "status": "completed"
+        }
+      ],
+      "status": "completed"
+    }
+  },
+  "updated": "2026-07-01T03:37:13"
+}
diff --git a/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s01-baseline-original/scenario.json b/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s01-baseline-original/scenario.json
new file mode 100644
index 00000000..14aa6ab5
--- /dev/null
+++ b/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s01-baseline-original/scenario.json
@@ -0,0 +1,17 @@
+{
+  "strategy_file": "../../../../etf_factor_rotation.py",
+  "strategy": "etf_factor_rotation",
+  "scenario_id": "s01-baseline-original",
+  "start_date": "2021-01-01",
+  "end_date": "2026-04-30",
+  "capital": 100000,
+  "frequency": "1d",
+  "py_version": "Python3",
+  "batch_id": "20260701-live-aligned-execution-gate",
+  "estimated_minutes": 6,
+  "result_source": "auto",
+  "allow_partial": false,
+  "params_diff": {
+    "ExecutionTimingMode": "baseline"
+  }
+}
diff --git a/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s02-logic3-code-variant/scenario.json b/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s02-logic3-code-variant/scenario.json
new file mode 100644
index 00000000..c490ea94
--- /dev/null
+++ b/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s02-logic3-code-variant/scenario.json
@@ -0,0 +1,15 @@
+{
+  "strategy_file": "../../../../variants/code/logic3_code_variant.py",
+  "strategy": "etf_factor_rotation",
+  "strategy_name": "etf_factor_rotation",
+  "scenario_id": "s02-logic3-code-variant",
+  "start_date": "2021-01-01",
+  "end_date": "2026-04-30",
+  "capital": 100000,
+  "frequency": "1d",
+  "py_version": "Python3",
+  "batch_id": "20260701-live-aligned-execution-gate",
+  "estimated_minutes": 6,
+  "result_source": "auto",
+  "allow_partial": false
+}
diff --git a/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s03-weekend-close-signal-next-open-variant/scenario.json b/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s03-weekend-close-signal-next-open-variant/scenario.json
new file mode 100644
index 00000000..a4997b6b
--- /dev/null
+++ b/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s03-weekend-close-signal-next-open-variant/scenario.json
@@ -0,0 +1,18 @@
+{
+  "strategy_file": "../../../../variants/code/weekend_close_signal_next_open_variant.py",
+  "strategy": "etf_factor_rotation",
+  "strategy_name": "etf_factor_rotation",
+  "scenario_id": "s03-weekend-close-signal-next-open-variant",
+  "start_date": "2021-01-01",
+  "end_date": "2026-04-30",
+  "capital": 100000,
+  "frequency": "1d",
+  "py_version": "Python3",
+  "batch_id": "20260701-live-aligned-execution-gate",
+  "estimated_minutes": 6,
+  "result_source": "auto",
+  "allow_partial": false,
+  "status": "superseded",
+  "superseded_by": "s04-weekend-close-signal-next-open-variant-v2",
+  "superseded_reason": "initial no-trade run; s04 is the active reproducible weekend-close variant evidence"
+}
diff --git a/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s04-weekend-close-signal-next-open-variant-v2/scenario.json b/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s04-weekend-close-signal-next-open-variant-v2/scenario.json
new file mode 100644
index 00000000..81676fe0
--- /dev/null
+++ b/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s04-weekend-close-signal-next-open-variant-v2/scenario.json
@@ -0,0 +1,15 @@
+{
+  "strategy_file": "../../../../variants/code/weekend_close_signal_next_open_variant.py",
+  "strategy": "etf_factor_rotation",
+  "strategy_name": "etf_factor_rotation",
+  "scenario_id": "s04-weekend-close-signal-next-open-variant-v2",
+  "start_date": "2021-01-01",
+  "end_date": "2026-04-30",
+  "capital": 100000,
+  "frequency": "1d",
+  "py_version": "Python3",
+  "batch_id": "20260701-live-aligned-execution-gate",
+  "estimated_minutes": 6,
+  "result_source": "auto",
+  "allow_partial": false
+}
diff --git a/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s05-official-current-baseline/scenario.json b/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s05-official-current-baseline/scenario.json
new file mode 100644
index 00000000..50c9696a
--- /dev/null
+++ b/strategies/etf_factor_rotation/test_batches/20260701-live-aligned-execution-gate/scenarios/s05-official-current-baseline/scenario.json
@@ -0,0 +1,15 @@
+{
+  "strategy_file": "../../../../etf_factor_rotation.py",
+  "strategy": "etf_factor_rotation",
+  "strategy_name": "etf_factor_rotation",
+  "scenario_id": "s05-official-current-baseline",
+  "start_date": "2021-01-01",
+  "end_date": "2026-04-30",
+  "capital": 100000,
+  "frequency": "1d",
+  "py_version": "Python3",
+  "batch_id": "20260701-live-aligned-execution-gate",
+  "estimated_minutes": 6,
+  "result_source": "auto",
+  "allow_partial": false
+}
diff --git a/strategies/etf_factor_rotation/tests/conftest.py b/strategies/etf_factor_rotation/tests/conftest.py
index 0bd13577..78ff4a20 100644
--- a/strategies/etf_factor_rotation/tests/conftest.py
+++ b/strategies/etf_factor_rotation/tests/conftest.py
@@ -24,7 +24,7 @@
 
 # 策略文件第 1 行调用 enable_profile()，必须提前注入
 builtins.enable_profile = Mock()
-sys.modules['FeishuRelayTools'] = MagicMock()
+sys.modules['FeishuRelayTools'] = SimpleNamespace()
 
 
 # ============================================================
@@ -206,7 +206,7 @@ def mock_g(strategy):
         MinWeight=0.05,
         RebalanceThreshold=0.03,
         MaxTotalWeight=1.0,
-        ExecutionTimingMode='baseline',
+        ExecutionTimingMode='weekend-close-signal-next-open',
         live_days=1250,
         history_buffer=100,
         benchmark='000300.XSHG',
@@ -255,3 +255,5 @@ def _auto_reset_mocks(strategy):
     strategy.set_slippage.reset_mock()
     strategy.run_weekly.reset_mock()
     strategy.run_daily.reset_mock()
+    strategy._mock_portfolio.total_value = 100000.0
+    strategy._mock_portfolio.positions = {}
diff --git a/strategies/etf_factor_rotation/tests/test_etf_factor_rotation.py b/strategies/etf_factor_rotation/tests/test_etf_factor_rotation.py
index e46c6056..42fbd042 100644
--- a/strategies/etf_factor_rotation/tests/test_etf_factor_rotation.py
+++ b/strategies/etf_factor_rotation/tests/test_etf_factor_rotation.py
@@ -12,6 +12,7 @@
 import inspect
 import json
 import math
+from pathlib import Path
 from types import SimpleNamespace
 from unittest.mock import MagicMock, Mock, patch, call
 
@@ -37,6 +38,28 @@ def test_strategy_loads_without_feishu_relay_tools(monkeypatch):
     assert module.FeishuRelayTools is None
 
 
+def test_fixed_time_weekly_schedules_do_not_pass_reference_security():
+    strategy_root = Path(__file__).resolve().parent.parent
+    strategy_files = [
+        strategy_root / "etf_factor_rotation.py",
+        strategy_root / "variants" / "code" / "weekend_close_signal_next_open_variant.py",
+    ]
+
+    for strategy_file in strategy_files:
+        tree = ast.parse(strategy_file.read_text(encoding="utf-8"))
+        for node in ast.walk(tree):
+            if not isinstance(node, ast.Call):
+                continue
+            if getattr(node.func, "id", "") != "run_weekly":
+                continue
+            kwargs = {keyword.arg: keyword.value for keyword in node.keywords if keyword.arg}
+            time_node = kwargs.get("time")
+            is_fixed_time = isinstance(time_node, ast.Constant) and time_node.value != "open"
+            assert not (is_fixed_time and "reference_security" in kwargs), (
+                "%s has fixed-time run_weekly with reference_security" % strategy_file
+            )
+
+
 # ============================================================
 # 可复用的价格序列生成工具
 # ============================================================
@@ -122,7 +145,8 @@ def test_all_core_functions_exist(self, strategy):
             'initialize', 'set_parameter', 'weekly_check',
             'build_rebalance_plan', 'prepare_delay_only_rebalance',
             'execute_pending_rebalance', 'mark_live_like_signal_day',
-            'execute_live_like_rebalance',
+            'execute_live_like_rebalance', 'prepare_weekend_close_rebalance',
+            'execute_weekend_close_rebalance',
             'get_history_data', 'compute_trend_gates', 'compute_momentum_scores',
             'select_topk', 'compute_rp_weights', 'compute_rsrs_multipliers',
             'compute_rsrs_adjusted_scores',
@@ -192,6 +216,17 @@ def test_portfolio_vol_relief_params_default_to_dyn_marginal(self, strategy):
         assert g.DynamicVolReliefMomentumWindow == 20
         assert g.DynamicVolReliefCovWindow == 40
 
+    def test_set_parameter_preserves_pending_rebalance_state(self, strategy):
+        pending = [{"signal_date": "2026-05-15", "pool": ["159819.XSHE"]}]
+        live_like = ["2026-05-18"]
+        strategy.g.pending_rebalances = pending
+        strategy.g.pending_live_like_signal_days = live_like
+
+        strategy.set_parameter(strategy)
+
+        assert strategy.g.pending_rebalances is pending
+        assert strategy.g.pending_live_like_signal_days is live_like
+
 
 class TestEtfDisplayNames:
     """测试基金展示名始终保留编号，供报告和日志检索。"""
@@ -266,15 +301,21 @@ def test_initialize_calls_set_option(self, strategy):
         strategy.set_option.assert_any_call('use_real_price', False)
         strategy.set_option.assert_any_call('avoid_future_data', True)
 
-    def test_initialize_registers_weekly_task(self, strategy):
+    def test_initialize_registers_default_weekend_close_task(self, strategy):
         context = SimpleNamespace()
         context.portfolio = strategy._mock_portfolio
         strategy.initialize(context)
-        strategy.run_weekly.assert_called_once()
-        args, kwargs = strategy.run_weekly.call_args
-        assert kwargs['weekday'] == 1
-        assert kwargs['time'] == 'open'
-        strategy.run_daily.assert_not_called()
+        strategy.run_weekly.assert_called_once_with(
+            strategy.prepare_weekend_close_rebalance,
+            weekday=-1,
+            time='15:30',
+            force=False,
+        )
+        strategy.run_daily.assert_called_once_with(
+            strategy.execute_weekend_close_rebalance,
+            time='open',
+            reference_security='000300.XSHG',
+        )
 
     def test_initialize_registers_delay_only_tasks(self, strategy):
         original_set_parameter = strategy.set_parameter
@@ -316,6 +357,30 @@ def set_live_like(context):
         _, daily_kwargs = strategy.run_daily.call_args
         assert daily_kwargs['time'] == 'open'
 
+    def test_initialize_registers_weekend_close_task(self, strategy):
+        original_set_parameter = strategy.set_parameter
+
+        def set_weekend_close(context):
+            original_set_parameter(context)
+            strategy.g.ExecutionTimingMode = "weekend-close-signal-next-open"
+
+        context = SimpleNamespace()
+        context.portfolio = strategy._mock_portfolio
+        with patch.object(strategy, 'set_parameter', side_effect=set_weekend_close):
+            strategy.initialize(context)
+
+        strategy.run_weekly.assert_called_once_with(
+            strategy.prepare_weekend_close_rebalance,
+            weekday=-1,
+            time='15:30',
+            force=False,
+        )
+        strategy.run_daily.assert_called_once_with(
+            strategy.execute_weekend_close_rebalance,
+            time='open',
+            reference_security='000300.XSHG',
+        )
+
     def test_initialize_calls_set_order_cost(self, strategy):
         """验证 initialize 调用了 set_order_cost 并传递正确的费率参数。"""
         context = SimpleNamespace()
@@ -334,13 +399,15 @@ def test_initialize_calls_set_slippage(self, strategy):
         kwargs = strategy.set_slippage.call_args[1]
         assert kwargs['type'] == 'fund'
 
-    def test_initialize_registers_reference_security(self, strategy):
-        """验证 run_weekly 注册了 reference_security='000300.XSHG'。"""
+    def test_initialize_keeps_reference_security_on_open_execution_only(self, strategy):
+        """固定时间收盘信号不传 reference_security，开盘执行保留参照标的。"""
         context = SimpleNamespace()
         context.portfolio = strategy._mock_portfolio
         strategy.initialize(context)
-        kwargs = strategy.run_weekly.call_args[1]
-        assert kwargs['reference_security'] == '000300.XSHG'
+        weekly_kwargs = strategy.run_weekly.call_args[1]
+        daily_kwargs = strategy.run_daily.call_args[1]
+        assert 'reference_security' not in weekly_kwargs
+        assert daily_kwargs['reference_security'] == '000300.XSHG'
 
     def test_initialize_calls_set_parameter(self, strategy):
         """验证 initialize 后 g 对象包含了 set_parameter 写入的关键参数。"""
@@ -2184,6 +2251,118 @@ def test_live_like_executes_after_holiday_gap(self, strategy, mock_g):
             pd.Timestamp("2021-10-11").date()
         ]
 
+    def test_weekend_close_prepares_last_trade_day_and_executes_cached_plan_next_open(self, strategy, mock_g):
+        mock_g.ExecutionTimingMode = "weekend-close-signal-next-open"
+        friday_date = pd.Timestamp("2026-05-15").date()
+        monday_date = pd.Timestamp("2026-05-18").date()
+        plan = {
+            "pool": list(mock_g.etf_pool),
+            "final_weights": np.array([0.4, 0.3, 0.0]),
+            "params": strategy.snapshot_params(),
+            "signal_date": friday_date,
+            "asof_date": friday_date,
+            "prepared_date": friday_date,
+        }
+        friday_close = SimpleNamespace(
+            current_dt=pd.Timestamp("2026-05-15 15:30:00").to_pydatetime(),
+            previous_date=pd.Timestamp("2026-05-14").date(),
+            portfolio=strategy._mock_portfolio,
+        )
+        monday_open = SimpleNamespace(
+            current_dt=pd.Timestamp("2026-05-18 09:30:00").to_pydatetime(),
+            previous_date=friday_date,
+            portfolio=strategy._mock_portfolio,
+        )
+
+        with patch.object(strategy, 'build_rebalance_plan', return_value=plan) as build:
+            strategy.prepare_weekend_close_rebalance(friday_close)
+
+        build.assert_called_once_with(friday_close, asof_date=friday_date)
+        assert strategy.g.pending_rebalances == [plan]
+
+        with patch.object(strategy, 'build_rebalance_plan') as build_again:
+            with patch.object(strategy, 'execute_rebalance') as execute:
+                strategy.execute_weekend_close_rebalance(monday_open)
+
+        build_again.assert_not_called()
+        execute.assert_called_once_with(
+            monday_open,
+            plan["pool"],
+            plan["final_weights"],
+            plan["params"],
+        )
+        assert strategy.g.pending_rebalances == []
+
+    def test_weekend_close_reports_signal_plan_and_suppresses_execution_notice(self, strategy, mock_g):
+        mock_g.ExecutionTimingMode = "weekend-close-signal-next-open"
+        friday_date = pd.Timestamp("2026-05-15").date()
+        monday_date = pd.Timestamp("2026-05-18").date()
+        params = strategy.snapshot_params()
+        plan = {
+            "pool": list(mock_g.etf_pool),
+            "final_weights": np.array([0.4, 0.3, 0.0]),
+            "params": params,
+            "signal_date": friday_date,
+            "asof_date": friday_date,
+            "prepared_date": friday_date,
+        }
+        feishu = SimpleNamespace(
+            report_signal_plan=Mock(return_value=True),
+            suppress_execution_notice=Mock(),
+            resume_execution_notice=Mock(),
+        )
+        friday_close = SimpleNamespace(
+            current_dt=pd.Timestamp("2026-05-15 15:30:00").to_pydatetime(),
+            previous_date=pd.Timestamp("2026-05-14").date(),
+            portfolio=strategy._mock_portfolio,
+        )
+        monday_open = SimpleNamespace(
+            current_dt=pd.Timestamp("2026-05-18 09:30:00").to_pydatetime(),
+            previous_date=friday_date,
+            portfolio=strategy._mock_portfolio,
+        )
+
+        with patch.object(strategy, "FeishuRelayTools", feishu):
+            with patch.object(strategy, "build_rebalance_plan", return_value=plan):
+                strategy.prepare_weekend_close_rebalance(friday_close)
+
+            cached = strategy.g.pending_rebalances[0]
+            feishu.report_signal_plan.assert_called_once_with(cached)
+            assert cached["signal_notice_sent"] is True
+            assert cached["plan_cached"] is True
+            assert cached["batch_id"]
+            assert cached["target_weights"] == [0.4, 0.3, 0.0]
+            assert cached["target_values"] == [40000.0, 30000.0, 0.0]
+
+            with patch.object(strategy, "execute_rebalance") as execute:
+                strategy.execute_weekend_close_rebalance(monday_open)
+
+        feishu.suppress_execution_notice.assert_called_once_with(
+            batch_id=cached["batch_id"],
+            reason="signal_notice_already_sent",
+        )
+        feishu.resume_execution_notice.assert_called_once_with()
+        execute.assert_called_once_with(
+            monday_open,
+            cached["pool"],
+            cached["final_weights"],
+            cached["params"],
+        )
+        events = [
+            json.loads(call_args[0][1])
+            for call_args in strategy.write_file.call_args_list
+        ]
+        cached_event = next(event for event in events if event["event"] == "weekend_close_plan_cached")
+        execute_event = next(event for event in events if event["event"] == "weekend_close_execute")
+        assert cached_event["batch_id"] == cached["batch_id"]
+        assert cached_event["signal_notice_sent"] is True
+        assert cached_event["plan_cached"] is True
+        assert execute_event["batch_id"] == cached["batch_id"]
+        assert execute_event["trade_date"] == monday_date.isoformat()
+        assert execute_event["execution_order_called"] is True
+        assert execute_event["execution_notice_suppressed"] is True
+        assert execute_event["suppress_reason"] == "signal_notice_already_sent"
+
 
 # ============================================================
 # 10. R3 修复验证 — get_history_data 显式 end_date=context.previous_date
@@ -2774,8 +2953,8 @@ def test_snapshot_backfills_missing_execution_timing_mode(self, strategy, mock_g
 
         params = strategy.snapshot_params()
 
-        assert params["ExecutionTimingMode"] == "baseline"
-        assert mock_g.ExecutionTimingMode == "baseline"
+        assert params["ExecutionTimingMode"] == "weekend-close-signal-next-open"
+        assert mock_g.ExecutionTimingMode == "weekend-close-signal-next-open"
 
     def test_snapshot_backfills_all_missing_runtime_params(self, strategy, mock_g):
         """新增策略参数必须能兼容模拟盘保留的旧 g。"""
diff --git a/strategies/etf_factor_rotation/variants/baseline_original.json b/strategies/etf_factor_rotation/variants/baseline_original.json
new file mode 100644
index 00000000..cfffdd7e
--- /dev/null
+++ b/strategies/etf_factor_rotation/variants/baseline_original.json
@@ -0,0 +1,42 @@
+{
+  "schema_version": 1,
+  "variant_id": "baseline_original",
+  "variant_type": "structural",
+  "status": "candidate",
+  "merge_status": "not_merged",
+  "description": "原始正式基线代码：本次实验对照组，来源为本分支起点 origin/main 的正式策略脚本。",
+  "code_source": {
+    "type": "git",
+    "path": "strategies/etf_factor_rotation/etf_factor_rotation.py",
+    "commit": "a2119d8e8a841e35af915abff625ce93e905e24a"
+  },
+  "params_diff": {},
+  "research_refs": [],
+  "backtest_refs": [
+    "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0"
+  ],
+  "report_refs": [
+    "strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/backtest_report.md"
+  ],
+  "created_at": "2026-06-30T20:21:17+00:00",
+  "updated_at": "2026-06-30T20:21:17+00:00",
+  "owner": "research-platform",
+  "created_by": "research-platform",
+  "updated_by": "research-platform",
+  "lifecycle": "active",
+  "payload": {
+    "code_source": {
+      "type": "git",
+      "path": "strategies/etf_factor_rotation/etf_factor_rotation.py",
+      "commit": "a2119d8e8a841e35af915abff625ce93e905e24a"
+    },
+    "owner": "research-platform",
+    "research_refs": [],
+    "backtest_refs": [
+      "20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0"
+    ],
+    "report_refs": [
+      "strategies/etf_factor_rotation/backtest_runs/20260701-0012-bt8d074a3098c6308f791ea33d8806d6f0/report/backtest_report.md"
+    ]
+  }
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/variants/code/logic3_code_variant.py b/strategies/etf_factor_rotation/variants/code/logic3_code_variant.py
new file mode 100644
index 00000000..2530689f
--- /dev/null
+++ b/strategies/etf_factor_rotation/variants/code/logic3_code_variant.py
@@ -0,0 +1,2024 @@
+# 策略名：ETF多因子轮动
+enable_profile()
+STRATEGY_NAME = "ETF多因子轮动"
+try:
+    import FeishuRelayTools
+except ImportError:
+    FeishuRelayTools = None
+
+"""
+============================================================
+策略名称：ETF 多因子轮动策略（相对倾斜版）
+策略类型：周线级别、场内基金、多因子动态配置
+适用标的：159819.XSHE、513100.XSHG、518880.XSHG（中文名运行时通过聚宽 API 读取）
+
+核心思想：
+  趋势门槛判断"能不能买"，风险平价分配基础仓位，
+  动量和 RSRS 作为资产间相对倾斜信号调整权重分配（不改变组合总仓位），
+  拥挤度惩罚和组合波动率控制在过热或高波时平滑降仓。
+  剩余仓位保留现金，不重新归一化到满仓。
+
+模块分工：
+  - 趋势门槛（硬过滤）：按 ETF 专属趋势均线以上才可入选，0/1 离散
+  - 风险平价（逆波动率）：所有趋势成立资产参与，σ 越小权重越大
+  - 动量倾斜（相对信号）：多周期排名分数去均值，clip 到 [TiltMin, TiltMax]；
+    可选将极端高分资产的动量倾斜压回中性
+  - RSRS 倾斜（相对信号）：High~Low 回归 β 标准化 × R² 去均值，clip 到 [TiltMin, TiltMax]
+  - 倾斜合成：RPWeight × MomentumTilt × RSRSTilt，活跃资产内重新归一化
+  - 拥挤度惩罚（只减不加）：五指标分位数均值，超阈值线性打折
+  - 组合波动率控制（只缩不放）：RawWeight 组合波动率超目标时等比缩放
+
+核心公式：
+  TiltedWeight_i = normalize(RPWeight_i × MomentumTilt_i × RSRSTilt_i)
+  RawWeight_i = TiltedWeight_i × TrendGate_i × CrowdPenalty_i
+  FinalWeight_i = RawWeight_i × PortfolioVolAssetScale_i
+
+调仓频率：每周开盘检查一次
+============================================================
+"""
+
+import json
+from datetime import date, datetime
+
+import numpy as np
+import pandas as pd
+
+
+# ============================================================
+# 常量 — 内部字段名到聚宽字段名的映射
+# ============================================================
+FIELD_MAP = {
+    "close": "close",
+    "high": "high",
+    "low": "low",
+    "amount": "money",
+}
+
+JQ_AUTO_AUDIT_TOKEN = "manual"
+JQ_AUTO_AUDIT_DIR = "jq_auto_audit"
+PARAM_DEFAULTS = {
+    "etf_pool": (
+        "159819.XSHE",
+        "513100.XSHG",
+        "518880.XSHG",
+    ),
+    "MA_long": 120,
+    "MA_long_by_etf": (20, 40, 100),
+    "MomShort": 20,
+    "MomMid": 60,
+    "MomLong": 120,
+    "w20": 0.2,
+    "w60": 0.3,
+    "w120": 0.5,
+    "TopK": 3,
+    "VolWindow": 60,
+    "annual_factor": 252,
+    "RSRS_N": 18,
+    "RSRS_M": 600,
+    "RSRS_NegativeFullCut": 1.8,
+    "RSRSMinMultiplier": 0.0,
+    "RSRSMaxMultiplier": 1.3,
+    "MomentumTiltStrength": 0.50,
+    "MomentumTiltMin": 0.70,
+    "MomentumTiltMax": 1.30,
+    "MomentumExtremeScoreStart": None,
+    "MomentumExtremeTiltCap": 1.00,
+    "RSRSTiltMin": 0.70,
+    "RSRSTiltMax": 1.30,
+    "CrowdWindow": 500,
+    "CrowdRetShort": 20,
+    "CrowdRetMid": 60,
+    "AmountMAWindow": 20,
+    "DeviationMAWindow": 20,
+    "CrowdVolWindow": 20,
+    "CrowdStart": 0.60,
+    "CrowdEnd": 0.95,
+    "MinCrowdPenalty": 0.30,
+    "CrowdStart_by_etf": (0.60, 0.60, 0.80),
+    "CrowdEnd_by_etf": None,
+    "MinCrowdPenalty_by_etf": None,
+    "CrowdRetShort_by_etf": None,
+    "CrowdRetMid_by_etf": None,
+    "PortfolioVolWindow": 40,
+    "TargetVol": 0.08,
+    "MaxPortfolioVolScale": 1.0,
+    "PortfolioVolReliefMode": "dyn_marginal",
+    "GoldVolReliefFraction": 0.5,
+    "GoldVolReliefMaxRatio": 2.0,
+    "DynamicVolReliefFraction": 1.0,
+    "DynamicVolReliefMaxRatio": 1.5,
+    "DynamicVolReliefMomentumWindow": 20,
+    "DynamicVolReliefCovWindow": 40,
+    "MaxWeight": 0.60,
+    "MinWeight": 0.05,
+    "RebalanceThreshold": 0.03,
+    "MaxTotalWeight": 1.0,
+    "ExecutionTimingMode": "logic-3-live-like",
+    "use_real_price": False,
+    "fq_mode": None,
+    "history_buffer": 100,
+    "benchmark": "000300.XSHG",
+}
+EXECUTION_TIMING_MODES = (
+    "baseline",
+    "logic-2-delay-only",
+    "logic-3-live-like",
+    "weekend-close-signal-next-open",
+)
+DEFAULT_EXECUTION_TIMING_MODE = PARAM_DEFAULTS["ExecutionTimingMode"]
+PORTFOLIO_VOL_RELIEF_MODES = (
+    "baseline",
+    "fixed_gold",
+    "dyn_marginal",
+)
+PORTFOLIO_VOL_RELIEF_DEFAULTS = {
+    "PortfolioVolReliefMode": PARAM_DEFAULTS["PortfolioVolReliefMode"],
+    "GoldVolReliefFraction": PARAM_DEFAULTS["GoldVolReliefFraction"],
+    "GoldVolReliefMaxRatio": PARAM_DEFAULTS["GoldVolReliefMaxRatio"],
+    "DynamicVolReliefFraction": PARAM_DEFAULTS["DynamicVolReliefFraction"],
+    "DynamicVolReliefMaxRatio": PARAM_DEFAULTS["DynamicVolReliefMaxRatio"],
+    "DynamicVolReliefMomentumWindow": PARAM_DEFAULTS["DynamicVolReliefMomentumWindow"],
+    "DynamicVolReliefCovWindow": PARAM_DEFAULTS["DynamicVolReliefCovWindow"],
+}
+
+
+def fund_code(security):
+    """从聚宽证券代码中提取 6 位基金代码，用于报告和日志展示。"""
+    return str(security).split(".")[0]
+
+
+def format_etf_name(security, name):
+    """保证基金显示名使用 中文名(聚宽代码) 标准格式。"""
+    security = str(security)
+    code = fund_code(security)
+    display_name = str(name).strip() if name is not None else str(security)
+    full_suffix = "(%s)" % security
+    short_suffix = "(%s)" % code
+    if display_name == security:
+        return display_name
+    if display_name.endswith(full_suffix):
+        return display_name
+    if code and display_name.endswith(short_suffix):
+        display_name = display_name[:-len(short_suffix)].strip()
+    return "%s%s" % (display_name, full_suffix)
+
+
+def build_etf_display_names(pool, names=None):
+    """按 etf_pool 顺序生成带编号的基金显示名列表。"""
+    names = names or []
+    result = []
+    for i, etf in enumerate(pool):
+        base_name = names[i] if i < len(names) else etf
+        result.append(format_etf_name(etf, base_name))
+    return result
+
+
+def fetch_etf_official_name(security, fallback_name=None):
+    """通过聚宽 API 读取基金官方中文名，失败时回退到已有名称或代码。"""
+    try:
+        info = get_security_info(security)
+        for attr in ("display_name", "name"):
+            value = getattr(info, attr, None)
+            if value:
+                return str(value).strip()
+    except Exception as exc:
+        log.warning("fetch ETF official name failed: security=%s error=%s", security, exc)
+
+    return fallback_name or str(security)
+
+
+def load_etf_display_names(pool, fallback_names=None):
+    """从聚宽官方证券信息生成标准 ETF 显示名。"""
+    fallback_names = fallback_names or []
+    names = []
+    for i, etf in enumerate(pool):
+        fallback_name = fallback_names[i] if i < len(fallback_names) else None
+        official_name = fetch_etf_official_name(etf, fallback_name=fallback_name)
+        names.append(format_etf_name(etf, official_name))
+    return names
+
+
+def _audit_jsonable(value):
+    """Convert strategy/runtime values to JSON-safe audit payloads."""
+    if value is None or isinstance(value, (str, bool, int, float)):
+        return value
+    if isinstance(value, (date, datetime)):
+        return value.isoformat()
+    try:
+        if isinstance(value, np.generic):
+            return _audit_jsonable(value.item())
+        if isinstance(value, np.ndarray):
+            return [_audit_jsonable(item) for item in value.tolist()]
+    except Exception:
+        pass
+    try:
+        if isinstance(value, pd.Timestamp):
+            return value.isoformat()
+        if isinstance(value, (pd.Series, pd.Index)):
+            return [_audit_jsonable(item) for item in value.tolist()]
+        if isinstance(value, pd.DataFrame):
+            return [
+                {str(k): _audit_jsonable(v) for k, v in row.items()}
+                for row in value.reset_index().to_dict(orient="records")
+            ]
+    except Exception:
+        pass
+    if isinstance(value, dict):
+        return {str(k): _audit_jsonable(v) for k, v in value.items()}
+    if isinstance(value, (list, tuple, set)):
+        return [_audit_jsonable(item) for item in value]
+    return str(value)
+
+
+def _context_time_fields(context):
+    result = {}
+    for name in ("current_dt", "previous_date"):
+        value = getattr(context, name, None) if context is not None else None
+        if value is not None:
+            result[name] = _audit_jsonable(value)
+    return result
+
+
+def audit_event(event, context=None, **payload):
+    """Write one complete business-audit event to JoinQuant research storage."""
+    path = getattr(g, "audit_path", "")
+    if not path:
+        return
+    seq = getattr(g, "audit_seq", 0) + 1
+    g.audit_seq = seq
+    row = {
+        "seq": seq,
+        "event": event,
+        "audit_token": getattr(g, "audit_token", ""),
+    }
+    row.update(_context_time_fields(context))
+    row.update({key: _audit_jsonable(value) for key, value in payload.items()})
+    write_file(path, json.dumps(row, ensure_ascii=False, sort_keys=True) + "\n", append=True)
+
+
+def _copy_runtime_default(value):
+    if isinstance(value, tuple):
+        return list(value)
+    if isinstance(value, list):
+        return list(value)
+    if isinstance(value, dict):
+        return dict(value)
+    return value
+
+
+def _runtime_param(name, default):
+    if not hasattr(g, name):
+        setattr(g, name, _copy_runtime_default(default))
+    return getattr(g, name)
+
+
+def _runtime_list_param(name):
+    value = _runtime_param(name, PARAM_DEFAULTS[name])
+    if value is None:
+        return None
+    return list(value)
+
+
+# ============================================================
+# snapshot_params — 参数快照
+# ============================================================
+def snapshot_params():
+    """
+    从 g 读取全部策略参数，返回只读快照 dict。
+
+    核心计算函数通过接收 params 而非直接读 g，实现解耦。
+    """
+    etf_pool = _runtime_list_param("etf_pool")
+    raw_etf_names = _runtime_param("etf_names", etf_pool)
+    etf_names = build_etf_display_names(etf_pool, list(raw_etf_names))
+    return {
+        "etf_pool": etf_pool,
+        "etf_names": etf_names,
+        "benchmark": _runtime_param("benchmark", PARAM_DEFAULTS["benchmark"]),
+        "MA_long": _runtime_param("MA_long", PARAM_DEFAULTS["MA_long"]),
+        "MA_long_by_etf": _runtime_list_param("MA_long_by_etf"),
+        "MomShort": _runtime_param("MomShort", PARAM_DEFAULTS["MomShort"]),
+        "MomMid": _runtime_param("MomMid", PARAM_DEFAULTS["MomMid"]),
+        "MomLong": _runtime_param("MomLong", PARAM_DEFAULTS["MomLong"]),
+        "w20": _runtime_param("w20", PARAM_DEFAULTS["w20"]),
+        "w60": _runtime_param("w60", PARAM_DEFAULTS["w60"]),
+        "w120": _runtime_param("w120", PARAM_DEFAULTS["w120"]),
+        "TopK": _runtime_param("TopK", PARAM_DEFAULTS["TopK"]),
+        "VolWindow": _runtime_param("VolWindow", PARAM_DEFAULTS["VolWindow"]),
+        "annual_factor": _runtime_param("annual_factor", PARAM_DEFAULTS["annual_factor"]),
+        "RSRS_N": _runtime_param("RSRS_N", PARAM_DEFAULTS["RSRS_N"]),
+        "RSRS_M": _runtime_param("RSRS_M", PARAM_DEFAULTS["RSRS_M"]),
+        "RSRS_NegativeFullCut": _runtime_param("RSRS_NegativeFullCut", PARAM_DEFAULTS["RSRS_NegativeFullCut"]),
+        "RSRSMinMultiplier": _runtime_param("RSRSMinMultiplier", PARAM_DEFAULTS["RSRSMinMultiplier"]),
+        "RSRSMaxMultiplier": _runtime_param("RSRSMaxMultiplier", PARAM_DEFAULTS["RSRSMaxMultiplier"]),
+        "MomentumTiltStrength": _runtime_param("MomentumTiltStrength", PARAM_DEFAULTS["MomentumTiltStrength"]),
+        "MomentumTiltMin": _runtime_param("MomentumTiltMin", PARAM_DEFAULTS["MomentumTiltMin"]),
+        "MomentumTiltMax": _runtime_param("MomentumTiltMax", PARAM_DEFAULTS["MomentumTiltMax"]),
+        "MomentumExtremeScoreStart": _runtime_param("MomentumExtremeScoreStart", PARAM_DEFAULTS["MomentumExtremeScoreStart"]),
+        "MomentumExtremeTiltCap": _runtime_param("MomentumExtremeTiltCap", PARAM_DEFAULTS["MomentumExtremeTiltCap"]),
+        "RSRSTiltMin": _runtime_param("RSRSTiltMin", PARAM_DEFAULTS["RSRSTiltMin"]),
+        "RSRSTiltMax": _runtime_param("RSRSTiltMax", PARAM_DEFAULTS["RSRSTiltMax"]),
+        "CrowdWindow": _runtime_param("CrowdWindow", PARAM_DEFAULTS["CrowdWindow"]),
+        "CrowdRetShort": _runtime_param("CrowdRetShort", PARAM_DEFAULTS["CrowdRetShort"]),
+        "CrowdRetMid": _runtime_param("CrowdRetMid", PARAM_DEFAULTS["CrowdRetMid"]),
+        "AmountMAWindow": _runtime_param("AmountMAWindow", PARAM_DEFAULTS["AmountMAWindow"]),
+        "DeviationMAWindow": _runtime_param("DeviationMAWindow", PARAM_DEFAULTS["DeviationMAWindow"]),
+        "CrowdVolWindow": _runtime_param("CrowdVolWindow", PARAM_DEFAULTS["CrowdVolWindow"]),
+        "CrowdStart": _runtime_param("CrowdStart", PARAM_DEFAULTS["CrowdStart"]),
+        "CrowdEnd": _runtime_param("CrowdEnd", PARAM_DEFAULTS["CrowdEnd"]),
+        "MinCrowdPenalty": _runtime_param("MinCrowdPenalty", PARAM_DEFAULTS["MinCrowdPenalty"]),
+        "CrowdStart_by_etf": _runtime_list_param("CrowdStart_by_etf"),
+        "CrowdEnd_by_etf": _runtime_list_param("CrowdEnd_by_etf"),
+        "MinCrowdPenalty_by_etf": _runtime_list_param("MinCrowdPenalty_by_etf"),
+        "CrowdRetShort_by_etf": _runtime_list_param("CrowdRetShort_by_etf"),
+        "CrowdRetMid_by_etf": _runtime_list_param("CrowdRetMid_by_etf"),
+        "PortfolioVolWindow": _runtime_param("PortfolioVolWindow", PARAM_DEFAULTS["PortfolioVolWindow"]),
+        "TargetVol": _runtime_param("TargetVol", PARAM_DEFAULTS["TargetVol"]),
+        "MaxPortfolioVolScale": _runtime_param("MaxPortfolioVolScale", PARAM_DEFAULTS["MaxPortfolioVolScale"]),
+        "PortfolioVolReliefMode": _runtime_param(
+            "PortfolioVolReliefMode",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["PortfolioVolReliefMode"],
+        ),
+        "GoldVolReliefFraction": _runtime_param(
+            "GoldVolReliefFraction",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["GoldVolReliefFraction"],
+        ),
+        "GoldVolReliefMaxRatio": _runtime_param(
+            "GoldVolReliefMaxRatio",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["GoldVolReliefMaxRatio"],
+        ),
+        "DynamicVolReliefFraction": _runtime_param(
+            "DynamicVolReliefFraction",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["DynamicVolReliefFraction"],
+        ),
+        "DynamicVolReliefMaxRatio": _runtime_param(
+            "DynamicVolReliefMaxRatio",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["DynamicVolReliefMaxRatio"],
+        ),
+        "DynamicVolReliefMomentumWindow": _runtime_param(
+            "DynamicVolReliefMomentumWindow",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["DynamicVolReliefMomentumWindow"],
+        ),
+        "DynamicVolReliefCovWindow": _runtime_param(
+            "DynamicVolReliefCovWindow",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["DynamicVolReliefCovWindow"],
+        ),
+        "MaxWeight": _runtime_param("MaxWeight", PARAM_DEFAULTS["MaxWeight"]),
+        "MinWeight": _runtime_param("MinWeight", PARAM_DEFAULTS["MinWeight"]),
+        "RebalanceThreshold": _runtime_param("RebalanceThreshold", PARAM_DEFAULTS["RebalanceThreshold"]),
+        "MaxTotalWeight": _runtime_param("MaxTotalWeight", PARAM_DEFAULTS["MaxTotalWeight"]),
+        "ExecutionTimingMode": _runtime_param(
+            "ExecutionTimingMode",
+            DEFAULT_EXECUTION_TIMING_MODE,
+        ),
+        "use_real_price": _runtime_param("use_real_price", PARAM_DEFAULTS["use_real_price"]),
+        "fq_mode": _runtime_param("fq_mode", PARAM_DEFAULTS["fq_mode"]),
+        "history_buffer": _runtime_param("history_buffer", PARAM_DEFAULTS["history_buffer"]),
+        "audit_token": getattr(g, "audit_token", ""),
+        "audit_path": getattr(g, "audit_path", ""),
+    }
+
+
+# ============================================================
+# validate_params — 参数校验
+# ============================================================
+def validate_params(params):
+    """
+    校验参数合法性，不合法时抛出 ValueError。
+
+    校验规则来自技术实现方案 4.1 节参数校验表。
+    """
+    errors = []
+
+    if params["MA_long"] <= 0:
+        errors.append("MA_long must be positive")
+    ma_long_by_etf = params.get("MA_long_by_etf")
+    if ma_long_by_etf is not None:
+        if not isinstance(ma_long_by_etf, (list, tuple)):
+            errors.append("MA_long_by_etf must be a list or tuple when provided")
+        else:
+            if len(ma_long_by_etf) != len(params["etf_pool"]):
+                errors.append("MA_long_by_etf length must match etf_pool")
+            for window in ma_long_by_etf:
+                if not isinstance(window, (int, float)) or window <= 0:
+                    errors.append("MA_long_by_etf values must be positive")
+                    break
+    if abs(params["w20"] + params["w60"] + params["w120"] - 1.0) > 1e-8:
+        errors.append("momentum weights must sum to 1")
+    if params["TopK"] < 1:
+        errors.append("TopK must be >= 1")
+    if not (0 < params["MaxWeight"] <= params["MaxTotalWeight"] <= 1):
+        errors.append("MaxWeight must be in (0, MaxTotalWeight] and MaxTotalWeight <= 1")
+    if not (0 <= params["MinWeight"] <= params["MaxWeight"]):
+        errors.append("MinWeight must be in [0, MaxWeight]")
+    if params["TargetVol"] <= 0:
+        errors.append("TargetVol must be positive")
+    if params["PortfolioVolReliefMode"] not in PORTFOLIO_VOL_RELIEF_MODES:
+        errors.append("PortfolioVolReliefMode must be one of %s" % (PORTFOLIO_VOL_RELIEF_MODES,))
+    for fraction_name in ("GoldVolReliefFraction", "DynamicVolReliefFraction"):
+        value = params[fraction_name]
+        if not (0.0 <= value <= 1.0):
+            errors.append("%s must be in [0.0, 1.0]" % fraction_name)
+    for ratio_name in ("GoldVolReliefMaxRatio", "DynamicVolReliefMaxRatio"):
+        value = params[ratio_name]
+        if value <= 1.0:
+            errors.append("%s must be > 1.0" % ratio_name)
+    for window_name in ("DynamicVolReliefMomentumWindow", "DynamicVolReliefCovWindow"):
+        value = params[window_name]
+        if isinstance(value, bool) or not isinstance(value, int) or value <= 0:
+            errors.append("%s must be a positive integer" % window_name)
+    if params["RSRS_M"] <= 0 or params["RSRS_N"] <= 1:
+        errors.append("RSRS_M must be positive and RSRS_N must be > 1")
+    if not (0 <= params["CrowdStart"] < params["CrowdEnd"] <= 1):
+        errors.append("Crowd thresholds must satisfy 0 <= CrowdStart < CrowdEnd <= 1")
+    for per_etf_name in ("CrowdStart_by_etf", "CrowdEnd_by_etf", "MinCrowdPenalty_by_etf",
+                         "CrowdRetShort_by_etf", "CrowdRetMid_by_etf"):
+        per_etf_val = params.get(per_etf_name)
+        if per_etf_val is not None:
+            if not isinstance(per_etf_val, (list, tuple)):
+                errors.append("%s must be a list or tuple when provided" % per_etf_name)
+            elif len(per_etf_val) != len(params["etf_pool"]):
+                errors.append("%s length must match etf_pool" % per_etf_name)
+    starts_etf = params.get("CrowdStart_by_etf")
+    ends_etf = params.get("CrowdEnd_by_etf")
+    if starts_etf is not None and ends_etf is not None:
+        for idx, (s, e) in enumerate(zip(starts_etf, ends_etf)):
+            if not (0 <= s < e <= 1):
+                errors.append("CrowdStart_by_etf[%d]=%s must satisfy 0 <= start < end <= 1, got end=%s" % (idx, s, e))
+                break
+    elif starts_etf is not None:
+        for idx, s in enumerate(starts_etf):
+            if not (0 <= s < params["CrowdEnd"] <= 1):
+                errors.append("CrowdStart_by_etf[%d]=%s must satisfy 0 <= start < CrowdEnd=%s" % (idx, s, params["CrowdEnd"]))
+                break
+    elif ends_etf is not None:
+        for idx, e in enumerate(ends_etf):
+            if not (params["CrowdStart"] < e <= 1):
+                errors.append("CrowdEnd_by_etf[%d]=%s must satisfy CrowdStart=%s < end <= 1" % (idx, e, params["CrowdStart"]))
+                break
+    if params["MomentumTiltStrength"] < 0:
+        errors.append("MomentumTiltStrength must be >= 0")
+    if not (0 < params["MomentumTiltMin"] <= 1 <= params["MomentumTiltMax"]):
+        errors.append("Momentum tilt bounds must satisfy 0 < min <= 1 <= max")
+    extreme_start = params["MomentumExtremeScoreStart"]
+    if extreme_start is not None and not (0 < extreme_start <= 1):
+        errors.append("MomentumExtremeScoreStart must be None or satisfy 0 < start <= 1")
+    if not (1 <= params["MomentumExtremeTiltCap"] <= params["MomentumTiltMax"]):
+        errors.append("MomentumExtremeTiltCap must satisfy 1 <= cap <= MomentumTiltMax")
+    if not (0 < params["RSRSTiltMin"] <= 1 <= params["RSRSTiltMax"]):
+        errors.append("RSRS tilt bounds must satisfy 0 < min <= 1 <= max")
+    if params["ExecutionTimingMode"] not in EXECUTION_TIMING_MODES:
+        errors.append("ExecutionTimingMode must be one of %s" % (EXECUTION_TIMING_MODES,))
+    if len(params["etf_pool"]) != len(params["etf_names"]):
+        errors.append("etf_pool and etf_names must have the same length")
+    for etf, name in zip(params["etf_pool"], params["etf_names"]):
+        if str(etf) not in str(name):
+            errors.append("etf_names must include JoinQuant security code: %s" % etf)
+
+    if errors:
+        raise ValueError("; ".join(errors))
+
+
+def resolve_ma_long_windows(params):
+    """返回与 etf_pool 对齐的趋势均线窗口。"""
+    ma_long_by_etf = params.get("MA_long_by_etf")
+    if ma_long_by_etf is None:
+        return [params["MA_long"]] * len(params["etf_pool"])
+    return list(ma_long_by_etf)
+
+
+def resolve_crowd_thresholds(params):
+    """返回与 etf_pool 对齐的 (CrowdStart, CrowdEnd, MinCrowdPenalty) 三元组列表。"""
+    n = len(params["etf_pool"])
+    starts = params.get("CrowdStart_by_etf")
+    starts = list(starts) if starts is not None else [params["CrowdStart"]] * n
+    ends = params.get("CrowdEnd_by_etf")
+    ends = list(ends) if ends is not None else [params["CrowdEnd"]] * n
+    mins = params.get("MinCrowdPenalty_by_etf")
+    mins = list(mins) if mins is not None else [params["MinCrowdPenalty"]] * n
+    return list(zip(starts, ends, mins))
+
+
+def resolve_crowd_ret_windows(params):
+    """返回与 etf_pool 对齐的 (CrowdRetShort, CrowdRetMid) 二元组列表。"""
+    n = len(params["etf_pool"])
+    shorts = params.get("CrowdRetShort_by_etf")
+    shorts = list(shorts) if shorts is not None else [params["CrowdRetShort"]] * n
+    mids = params.get("CrowdRetMid_by_etf")
+    mids = list(mids) if mids is not None else [params["CrowdRetMid"]] * n
+    return list(zip(shorts, mids))
+
+
+# ============================================================
+# initialize — 策略初始化
+# ============================================================
+def initialize(context):
+    """
+    由聚宽框架在回测/模拟启动时自动调用一次。
+
+    作用：
+    - 向 g 对象写入全部策略参数
+    - 设置交易费用（场内基金免印花税，佣金万分之一）
+    - 设置固定滑点 0
+    - 注册每周开盘调仓任务
+    """
+    set_parameter(context)
+    validate_params(snapshot_params())
+    write_file(g.audit_path, "", append=False)
+    audit_event("run_start", context, params=snapshot_params())
+    set_option('use_real_price', g.use_real_price)
+    set_option("avoid_future_data", True)
+
+    set_order_cost(
+        OrderCost(
+            open_tax=0,
+            close_tax=0,
+            open_commission=0.0001,
+            close_commission=0.0001,
+            min_commission=0
+        ),
+        type='fund'
+    )
+
+    set_slippage(FixedSlippage(0.0), type='fund')
+
+    if g.ExecutionTimingMode == "baseline":
+        run_weekly(
+            weekly_check,
+            weekday=1,
+            time='open',
+            reference_security='000300.XSHG'
+        )
+    elif g.ExecutionTimingMode == "logic-2-delay-only":
+        run_weekly(
+            prepare_delay_only_rebalance,
+            weekday=1,
+            time='open',
+            reference_security='000300.XSHG'
+        )
+        run_daily(
+            execute_pending_rebalance,
+            time='open',
+            reference_security='000300.XSHG'
+        )
+    elif g.ExecutionTimingMode == "logic-3-live-like":
+        run_weekly(
+            mark_live_like_signal_day,
+            weekday=1,
+            time='open',
+            reference_security='000300.XSHG'
+        )
+        run_daily(
+            execute_live_like_rebalance,
+            time='open',
+            reference_security='000300.XSHG'
+        )
+    else:
+        run_daily(
+            prepare_weekend_close_rebalance,
+            time='15:30',
+            reference_security='000300.XSHG'
+        )
+        run_daily(
+            execute_weekend_close_rebalance,
+            time='open',
+            reference_security='000300.XSHG'
+        )
+
+
+def on_strategy_end(context):
+    """Record the final audit marker used by local completeness checks."""
+    portfolio = getattr(context, "portfolio", None)
+    audit_event(
+        "run_end",
+        context,
+        total_value=getattr(portfolio, "total_value", None),
+        cash=getattr(portfolio, "cash", None),
+    )
+
+
+# ============================================================
+# set_parameter — 策略参数集中设置
+# ============================================================
+def set_parameter(context):
+    """
+    将所有策略参数写入 g 全局对象，便于集中管理和回测参数扫描。
+
+    参数类别：资产池、趋势门槛、动量选择、风险平价、RSRS 修正、
+    拥挤度惩罚、组合波动率控制、仓位交易约束。
+    """
+
+    # ---- 资产池 ----
+    g.etf_pool = _copy_runtime_default(PARAM_DEFAULTS["etf_pool"])
+    g.etf_names = load_etf_display_names(g.etf_pool)
+
+    # ---- 趋势门槛 ----
+    g.MA_long = PARAM_DEFAULTS["MA_long"]
+    g.MA_long_by_etf = _copy_runtime_default(PARAM_DEFAULTS["MA_long_by_etf"])
+
+    # ---- 动量选择 ----
+    g.MomShort = PARAM_DEFAULTS["MomShort"]
+    g.MomMid = PARAM_DEFAULTS["MomMid"]
+    g.MomLong = PARAM_DEFAULTS["MomLong"]
+    g.w20 = PARAM_DEFAULTS["w20"]
+    g.w60 = PARAM_DEFAULTS["w60"]
+    g.w120 = PARAM_DEFAULTS["w120"]
+    g.TopK = PARAM_DEFAULTS["TopK"]
+
+    # ---- 风险平价 ----
+    g.VolWindow = PARAM_DEFAULTS["VolWindow"]
+    g.annual_factor = PARAM_DEFAULTS["annual_factor"]
+
+    # ---- RSRS 修正 ----
+    g.RSRS_N = PARAM_DEFAULTS["RSRS_N"]        # 回归窗口
+    g.RSRS_M = PARAM_DEFAULTS["RSRS_M"]        # 标准化窗口
+    g.RSRS_NegativeFullCut = PARAM_DEFAULTS["RSRS_NegativeFullCut"]
+    g.RSRSMinMultiplier = PARAM_DEFAULTS["RSRSMinMultiplier"]
+    g.RSRSMaxMultiplier = PARAM_DEFAULTS["RSRSMaxMultiplier"]
+
+    # ---- 动量倾斜（资产间相对信号） ----
+    g.MomentumTiltStrength = PARAM_DEFAULTS["MomentumTiltStrength"]
+    g.MomentumTiltMin = PARAM_DEFAULTS["MomentumTiltMin"]
+    g.MomentumTiltMax = PARAM_DEFAULTS["MomentumTiltMax"]
+    g.MomentumExtremeScoreStart = PARAM_DEFAULTS["MomentumExtremeScoreStart"]
+    g.MomentumExtremeTiltCap = PARAM_DEFAULTS["MomentumExtremeTiltCap"]
+
+    # ---- RSRS 倾斜（资产间相对信号） ----
+    g.RSRSTiltMin = PARAM_DEFAULTS["RSRSTiltMin"]
+    g.RSRSTiltMax = PARAM_DEFAULTS["RSRSTiltMax"]
+
+    # ---- 拥挤度惩罚 ----
+    g.CrowdWindow = PARAM_DEFAULTS["CrowdWindow"]
+    g.CrowdRetShort = PARAM_DEFAULTS["CrowdRetShort"]
+    g.CrowdRetMid = PARAM_DEFAULTS["CrowdRetMid"]
+    g.AmountMAWindow = PARAM_DEFAULTS["AmountMAWindow"]
+    g.DeviationMAWindow = PARAM_DEFAULTS["DeviationMAWindow"]
+    g.CrowdVolWindow = PARAM_DEFAULTS["CrowdVolWindow"]
+    g.CrowdStart = PARAM_DEFAULTS["CrowdStart"]
+    g.CrowdEnd = PARAM_DEFAULTS["CrowdEnd"]
+    g.MinCrowdPenalty = PARAM_DEFAULTS["MinCrowdPenalty"]
+    g.CrowdStart_by_etf = _copy_runtime_default(PARAM_DEFAULTS["CrowdStart_by_etf"])
+    g.CrowdEnd_by_etf = PARAM_DEFAULTS["CrowdEnd_by_etf"]
+    g.MinCrowdPenalty_by_etf = PARAM_DEFAULTS["MinCrowdPenalty_by_etf"]
+    g.CrowdRetShort_by_etf = PARAM_DEFAULTS["CrowdRetShort_by_etf"]
+    g.CrowdRetMid_by_etf = PARAM_DEFAULTS["CrowdRetMid_by_etf"]
+
+    # ---- 组合波动率控制 ----
+    g.PortfolioVolWindow = PARAM_DEFAULTS["PortfolioVolWindow"]
+    g.TargetVol = PARAM_DEFAULTS["TargetVol"]
+    g.MaxPortfolioVolScale = PARAM_DEFAULTS["MaxPortfolioVolScale"]
+    g.PortfolioVolReliefMode = PARAM_DEFAULTS["PortfolioVolReliefMode"]
+    g.GoldVolReliefFraction = PARAM_DEFAULTS["GoldVolReliefFraction"]
+    g.GoldVolReliefMaxRatio = PARAM_DEFAULTS["GoldVolReliefMaxRatio"]
+    g.DynamicVolReliefFraction = PARAM_DEFAULTS["DynamicVolReliefFraction"]
+    g.DynamicVolReliefMaxRatio = PARAM_DEFAULTS["DynamicVolReliefMaxRatio"]
+    g.DynamicVolReliefMomentumWindow = PARAM_DEFAULTS["DynamicVolReliefMomentumWindow"]
+    g.DynamicVolReliefCovWindow = PARAM_DEFAULTS["DynamicVolReliefCovWindow"]
+
+    # ---- 仓位与交易约束 ----
+    g.MaxWeight = PARAM_DEFAULTS["MaxWeight"]
+    g.MinWeight = PARAM_DEFAULTS["MinWeight"]
+    g.RebalanceThreshold = PARAM_DEFAULTS["RebalanceThreshold"]
+    g.MaxTotalWeight = PARAM_DEFAULTS["MaxTotalWeight"]
+    g.ExecutionTimingMode = DEFAULT_EXECUTION_TIMING_MODE
+
+    # ---- 数据与基准 ----
+    # 复权模式：fq='pre' 在 FQ A/B 对比测试中证实对场内基金会
+    # 导致 get_price 返回空数据（2025-04~2026-04 区间复现）。
+    # 故默认关闭复权。参考 FQ comparison: R2/backtest_runs/*/report/fq-comparison.md
+    g.use_real_price = PARAM_DEFAULTS["use_real_price"]
+    g.fq_mode = PARAM_DEFAULTS["fq_mode"]        # 不复权（场内基金默认）
+    ma_long_max = max(g.MA_long_by_etf) if g.MA_long_by_etf else g.MA_long
+    g.live_days = max(
+        ma_long_max, g.MomLong, g.RSRS_M,
+        g.CrowdWindow, g.PortfolioVolWindow
+    ) + 50
+    g.history_buffer = PARAM_DEFAULTS["history_buffer"]
+    g.benchmark = PARAM_DEFAULTS["benchmark"]
+    g.audit_token = JQ_AUTO_AUDIT_TOKEN
+    g.audit_path = "%s/%s.jsonl" % (JQ_AUTO_AUDIT_DIR, g.audit_token)
+    g.audit_seq = 0
+    g.pending_rebalances = []
+    g.pending_live_like_signal_days = []
+
+
+# ============================================================
+# _log_step — 调仓中间量诊断日志
+# ============================================================
+def _log_step(name, cn_name, pool, values, fmt=".4f", etf_names=None):
+    """
+    以 "[中文名] name: 基金名(聚宽代码)=value" 格式逐只打印调仓中间量，便于云端回测诊断。
+
+    不在本地单测中验证日志格式，只保证聚宽云端 log.info 可输出。
+    """
+    labels = build_etf_display_names(pool, etf_names)
+    parts = ["%s=%%s" % label for label in labels]
+    template = "[%s] %s: " % (cn_name, name) + ", ".join(parts)
+    formatted = tuple(format(v, fmt) for v in values)
+    log.info(template, *formatted)
+
+
+# ============================================================
+# compose_raw_weights — 权重合成
+# ============================================================
+def compose_raw_weights(tilted_weights, trend_gates, crowd_penalties):
+    """
+    合成各模块输出为 RawWeight。
+
+    动量与 RSRS 已经体现在 TiltedWeight 中，不再作为独立乘数。
+    TrendGate 仍保留作为二次保护。不重新归一化。
+    """
+    n = len(tilted_weights)
+    raw = np.zeros(n)
+    for i in range(n):
+        raw[i] = (
+            tilted_weights[i]
+            * trend_gates[i]
+            * crowd_penalties[i]
+        )
+    return raw
+
+
+# ============================================================
+# weekly_check — 周频调仓主函数
+# ============================================================
+def _as_date(value):
+    """把聚宽日期、pandas 日期或字符串统一成 date。"""
+    if value is None:
+        return None
+    if isinstance(value, datetime):
+        return value.date()
+    if isinstance(value, date):
+        return value
+    try:
+        return pd.Timestamp(value).date()
+    except Exception:
+        return value
+
+
+def _context_trade_date(context):
+    """返回当前任务对应的自然日。"""
+    return _as_date(getattr(context, "current_dt", None))
+
+
+def _same_iso_week(left, right):
+    left = _as_date(left)
+    right = _as_date(right)
+    if left is None or right is None:
+        return False
+    return left.isocalendar()[:2] == right.isocalendar()[:2]
+
+
+def _float_list(values):
+    try:
+        if hasattr(values, "tolist"):
+            values = values.tolist()
+    except Exception:
+        pass
+    return [float(value) for value in list(values or [])]
+
+
+def _weekend_close_batch_id(signal_date):
+    token = str(getattr(g, "audit_token", "manual")).replace("/", "_").replace("\\", "_")
+    return "%s-weekend-close-%s" % (token, signal_date)
+
+
+def _enrich_weekend_close_plan(context, plan, signal_date):
+    weights = _float_list(plan.get("final_weights"))
+    portfolio = getattr(context, "portfolio", None)
+    total_value = getattr(portfolio, "total_value", None)
+    plan["final_weights"] = weights
+    plan["target_weights"] = weights
+    plan["target_values"] = [total_value * weight for weight in weights] if total_value is not None else []
+    plan["portfolio_total_value"] = total_value
+    plan["signal_date"] = signal_date
+    plan["asof_date"] = signal_date
+    plan["prepared_date"] = signal_date
+    plan["trade_date"] = plan.get("trade_date")
+    plan["batch_id"] = plan.get("batch_id") or _weekend_close_batch_id(signal_date)
+    plan["plan_cached"] = True
+    plan["signal_notice_sent"] = False
+    return plan
+
+
+def _report_signal_plan(plan):
+    if FeishuRelayTools is None:
+        return False
+    reporter = getattr(FeishuRelayTools, "report_signal_plan", None)
+    if not callable(reporter):
+        return False
+    try:
+        return bool(reporter(plan))
+    except Exception as exc:
+        log.warning("feishu signal notice failed: %s", exc)
+        return False
+
+
+def _suppress_execution_notice(batch_id):
+    if FeishuRelayTools is None:
+        return False
+    suppress = getattr(FeishuRelayTools, "suppress_execution_notice", None)
+    if not callable(suppress):
+        return False
+    try:
+        suppress(batch_id=batch_id, reason="signal_notice_already_sent")
+        return True
+    except Exception as exc:
+        log.warning("feishu execution notice suppress failed: %s", exc)
+        return False
+
+
+def _resume_execution_notice():
+    if FeishuRelayTools is None:
+        return
+    resume = getattr(FeishuRelayTools, "resume_execution_notice", None)
+    if not callable(resume):
+        return
+    try:
+        resume()
+    except Exception as exc:
+        log.warning("feishu execution notice resume failed: %s", exc)
+
+
+def build_rebalance_plan(context, asof_date=None):
+    """生成一次调仓所需的完整信号快照，但不直接下单。
+
+    流程：TrendGate → RPWeight → MomentumScore → MomentumTilt
+         → RSRSTilt → TiltedWeight → CrowdPenalty
+         → PortfolioVolScale → FinalWeight
+    """
+    params = snapshot_params()
+    pool = params["etf_pool"]
+    etf_names = params["etf_names"]
+
+    # 1. 拉取历史数据
+    if asof_date is not None:
+        asof_date = _as_date(asof_date)
+    else:
+        asof_date = getattr(context, "previous_date", None)
+    prices = get_history_data(context, pool, params, asof_date=asof_date)
+
+    # 2. 计算趋势门槛
+    trend_gates = compute_trend_gates(prices, pool, params)
+    _log_step("TrendGate", "趋势门槛", pool, trend_gates, fmt=".0f", etf_names=etf_names)
+
+    # 3. 风险平价基础权重（所有趋势成立资产参与）
+    active_mask = [gate > 0 for gate in trend_gates]
+    rp_weights = compute_rp_weights(prices, pool, active_mask, params)
+    _log_step("RPWeight", "风险平价权重", pool, rp_weights, fmt=".4f", etf_names=etf_names)
+
+    # 4. 计算动量分数
+    momentum_scores = compute_momentum_scores(prices, pool, trend_gates, params)
+    _log_step("MomentumScore", "动量分数", pool, momentum_scores, fmt=".4f", etf_names=etf_names)
+
+    # 5. 动量倾斜乘数
+    momentum_tilts = compute_momentum_tilt_multipliers(momentum_scores, trend_gates, params)
+    _log_step("MomentumTilt", "动量倾斜乘数", pool, momentum_tilts, fmt=".4f", etf_names=etf_names)
+
+    # 6. RSRS 倾斜乘数
+    rsrs_tilts = compute_rsrs_tilt_multipliers(prices, pool, trend_gates, params)
+    _log_step("RSRSTilt", "RSRS倾斜乘数", pool, rsrs_tilts, fmt=".4f", etf_names=etf_names)
+
+    # 7. 合成倾斜权重（动量 + RSRS 同时参与相对倾斜，活跃资产内重新归一化）
+    tilted_weights = apply_relative_tilts(rp_weights, trend_gates, momentum_tilts, rsrs_tilts)
+    _log_step("TiltedWeight", "倾斜合成权重", pool, tilted_weights, fmt=".4f", etf_names=etf_names)
+
+    # 8. 拥挤度线性惩罚乘数
+    crowd_penalties = compute_crowd_penalties(prices, pool, params)
+    _log_step("CrowdPenalty", "拥挤度惩罚", pool, crowd_penalties, fmt=".4f", etf_names=etf_names)
+
+    # 9. 合成 RawWeight（不重新归一化）
+    raw_weights = compose_raw_weights(tilted_weights, trend_gates, crowd_penalties)
+
+    # 10. 组合波动率缩放
+    portfolio_vol_asset_scales, portfolio_vol_meta = compute_portfolio_vol_asset_scales(
+        prices, pool, raw_weights, params
+    )
+    portfolio_vol_scale = portfolio_vol_meta["base_scale"]
+    log.info("[组合波动率缩放] PortfolioVolScale=%.4f", portfolio_vol_scale)
+
+    # 11. 最终权重
+    final_weights = raw_weights * portfolio_vol_asset_scales
+    _log_step("FinalWeight", "最终权重", pool, final_weights, fmt=".4f", etf_names=etf_names)
+
+    # 12. 应用交易约束
+    final_weights_before_constraints = np.copy(final_weights)
+    final_weights = apply_weight_constraints(final_weights, params)
+    audit_event(
+        "rebalance_signals",
+        context,
+        pool=pool,
+        etf_names=etf_names,
+        params=params,
+        trend_gates=trend_gates,
+        rp_weights=rp_weights,
+        momentum_scores=momentum_scores,
+        momentum_tilts=momentum_tilts,
+        rsrs_tilts=rsrs_tilts,
+        tilted_weights=tilted_weights,
+        crowd_penalties=crowd_penalties,
+        raw_weights=raw_weights,
+        portfolio_vol_scale=portfolio_vol_scale,
+        portfolio_vol_relief_mode=portfolio_vol_meta["mode"],
+        portfolio_vol_ratio=portfolio_vol_meta["vol_ratio"],
+        portfolio_vol_base_scale=portfolio_vol_meta["base_scale"],
+        portfolio_vol_asset_scales=portfolio_vol_asset_scales,
+        portfolio_vol_relief_asset=portfolio_vol_meta["relief_asset"],
+        portfolio_vol_relief_weight=portfolio_vol_meta["relief_weight"],
+        portfolio_vol_relief_reason=portfolio_vol_meta["reason"],
+        final_weights_before_constraints=final_weights_before_constraints,
+        final_weights=final_weights,
+        execution_timing_mode=params["ExecutionTimingMode"],
+        asof_date=asof_date,
+        trade_date=_context_trade_date(context),
+    )
+
+    return {
+        "pool": pool,
+        "final_weights": final_weights,
+        "params": params,
+        "asof_date": asof_date,
+        "prepared_date": _context_trade_date(context),
+    }
+
+
+def weekly_check(context):
+    """每周开盘时生成信号并立即执行调仓。"""
+    plan = build_rebalance_plan(context)
+    execute_rebalance(context, plan["pool"], plan["final_weights"], plan["params"])
+
+
+def prepare_delay_only_rebalance(context):
+    """按 baseline 口径先生成信号，延后到下一交易日开盘执行。"""
+    plan = build_rebalance_plan(context)
+    g.pending_rebalances.append(plan)
+    audit_event(
+        "rebalance_prepared",
+        context,
+        execution_timing_mode=plan["params"]["ExecutionTimingMode"],
+        asof_date=plan["asof_date"],
+        prepared_date=plan["prepared_date"],
+        final_weights=plan["final_weights"],
+    )
+
+
+def execute_pending_rebalance(context):
+    """执行 logic-2 中已缓存、且至少延后一交易日的调仓。"""
+    queue = getattr(g, "pending_rebalances", [])
+    if not queue:
+        return
+
+    pending = queue[0]
+    trade_date = _context_trade_date(context)
+    prepared_date = pending.get("prepared_date")
+    if trade_date is None or prepared_date is None or trade_date <= prepared_date:
+        audit_event(
+            "pending_rebalance_wait",
+            context,
+            execution_timing_mode=pending["params"]["ExecutionTimingMode"],
+            asof_date=pending.get("asof_date"),
+            prepared_date=prepared_date,
+            trade_date=trade_date,
+        )
+        return
+
+    audit_event(
+        "pending_rebalance_execute",
+        context,
+        execution_timing_mode=pending["params"]["ExecutionTimingMode"],
+        asof_date=pending.get("asof_date"),
+        prepared_date=prepared_date,
+        trade_date=trade_date,
+        final_weights=pending["final_weights"],
+    )
+    execute_rebalance(context, pending["pool"], pending["final_weights"], pending["params"])
+    g.pending_rebalances.pop(0)
+
+
+def mark_live_like_signal_day(context):
+    """记录本周首个交易日，供下一交易日开盘生成并执行 logic-3 信号。"""
+    signal_date = _context_trade_date(context)
+    g.pending_live_like_signal_days.append(signal_date)
+    audit_event(
+        "live_like_signal_marked",
+        context,
+        execution_timing_mode=snapshot_params()["ExecutionTimingMode"],
+        signal_date=signal_date,
+    )
+
+
+def execute_live_like_rebalance(context):
+    """在首个交易日之后的下一交易日开盘，生成并执行 logic-3 信号。"""
+    queue = getattr(g, "pending_live_like_signal_days", [])
+    if not queue:
+        return
+
+    signal_date = queue[0]
+    trade_date = _context_trade_date(context)
+    if trade_date is None or signal_date is None or trade_date <= signal_date:
+        audit_event(
+            "live_like_wait",
+            context,
+            execution_timing_mode=snapshot_params()["ExecutionTimingMode"],
+            signal_date=signal_date,
+            trade_date=trade_date,
+        )
+        return
+
+    asof_date = getattr(context, "previous_date", None)
+    if asof_date != signal_date:
+        audit_event(
+            "live_like_skip",
+            context,
+            execution_timing_mode=snapshot_params()["ExecutionTimingMode"],
+            signal_date=signal_date,
+            asof_date=asof_date,
+            trade_date=trade_date,
+            reason="previous_date_not_signal_date",
+        )
+        queue.pop(0)
+        return
+
+    audit_event(
+        "live_like_rebalance_execute",
+        context,
+        execution_timing_mode=snapshot_params()["ExecutionTimingMode"],
+        signal_date=signal_date,
+        asof_date=asof_date,
+        trade_date=trade_date,
+    )
+    weekly_check(context)
+    queue.pop(0)
+
+
+def prepare_weekend_close_rebalance(context):
+    """收盘后生成候选信号 plan，次开盘跨周时执行。"""
+    signal_date = _context_trade_date(context)
+    params = snapshot_params()
+    if signal_date is None:
+        audit_event(
+            "weekend_close_signal_skip",
+            context,
+            execution_timing_mode=params["ExecutionTimingMode"],
+            signal_date=signal_date,
+            reason="signal_date_unavailable",
+        )
+        return
+
+    plan = build_rebalance_plan(context, asof_date=signal_date)
+    plan = _enrich_weekend_close_plan(context, plan, signal_date)
+    plan["signal_notice_sent"] = _report_signal_plan(plan)
+    g.pending_rebalances = [plan]
+    audit_event(
+        "weekend_close_plan_cached",
+        context,
+        execution_timing_mode=plan["params"]["ExecutionTimingMode"],
+        signal_date=signal_date,
+        asof_date=signal_date,
+        batch_id=plan["batch_id"],
+        target_weights=plan["target_weights"],
+        target_values=plan["target_values"],
+        signal_notice_sent=plan["signal_notice_sent"],
+        plan_cached=True,
+        final_weights=plan["final_weights"],
+    )
+
+
+def execute_weekend_close_rebalance(context):
+    """次交易日开盘执行已缓存的收盘信号 plan，不重新计算信号。"""
+    queue = getattr(g, "pending_rebalances", [])
+    if not queue:
+        return
+
+    pending = queue[0]
+    trade_date = _context_trade_date(context)
+    signal_date = pending.get("signal_date")
+    if trade_date is None or signal_date is None:
+        audit_event(
+            "weekend_close_execute_wait",
+            context,
+            execution_timing_mode=pending["params"]["ExecutionTimingMode"],
+            signal_date=signal_date,
+            asof_date=pending.get("asof_date"),
+            trade_date=trade_date,
+        )
+        return
+    if _same_iso_week(signal_date, trade_date):
+        audit_event(
+            "weekend_close_plan_discarded",
+            context,
+            execution_timing_mode=pending["params"]["ExecutionTimingMode"],
+            signal_date=signal_date,
+            asof_date=pending.get("asof_date"),
+            trade_date=trade_date,
+            reason="not_last_trade_day_of_week",
+        )
+        g.pending_rebalances.pop(0)
+        return
+
+    pending["trade_date"] = trade_date
+    suppress_reason = "signal_notice_already_sent" if pending.get("signal_notice_sent") else ""
+    notice_suppressed = _suppress_execution_notice(pending.get("batch_id")) if suppress_reason else False
+    audit_event(
+        "weekend_close_execute",
+        context,
+        execution_timing_mode=pending["params"]["ExecutionTimingMode"],
+        signal_date=signal_date,
+        asof_date=pending.get("asof_date"),
+        batch_id=pending.get("batch_id"),
+        trade_date=trade_date,
+        execution_order_called=True,
+        execution_notice_suppressed=notice_suppressed,
+        suppress_reason=suppress_reason if notice_suppressed else "",
+        final_weights=pending["final_weights"],
+    )
+    try:
+        execute_rebalance(context, pending["pool"], pending["final_weights"], pending["params"])
+    finally:
+        if notice_suppressed:
+            _resume_execution_notice()
+    g.pending_rebalances.pop(0)
+
+
+# ============================================================
+# normalize_field_frame — 数据返回结构归一化
+# ============================================================
+def normalize_field_frame(raw, field, pool):
+    """
+    将 get_price 返回的单 ETF 结果归一化，辅助测试与本地诊断。
+
+    处理规则：
+      - None 或空 DataFrame → 返回 columns=pool 的空 DataFrame
+      - 普通 DataFrame → reindex(columns=pool) 补全缺列
+    """
+    if raw is None:
+        return pd.DataFrame(columns=pool)
+    if not isinstance(raw, pd.DataFrame):
+        return pd.DataFrame(columns=pool)
+    if len(raw) == 0:
+        return pd.DataFrame(columns=pool)
+
+    raw = raw.reindex(columns=pool)
+    return raw.dropna(how='all')
+
+
+# ============================================================
+# compute_history_count — 计算所需历史数据长度
+# ============================================================
+def compute_history_count(params):
+    """
+    按模块显式计算所需历史数据长度。
+
+    说明：
+      - 动量和收益率类计算需要多取 1 日
+      - RSRS 至少需要 RSRS_M + RSRS_N - 1
+      - buffer 用于容忍停牌、缺失值、上市初期数据不足
+    """
+    requirements = [
+        max(resolve_ma_long_windows(params)),
+        max(params["MomShort"], params["MomMid"], params["MomLong"]) + 1,
+        params["VolWindow"] + 1,
+        params["RSRS_M"] + params["RSRS_N"] - 1,
+        params["CrowdWindow"],
+        params["PortfolioVolWindow"] + 1,
+    ]
+    return max(requirements) + params.get("history_buffer", 50)
+
+
+# ============================================================
+# fetch_field + get_history_data — 拉取历史行情数据
+# ============================================================
+def fetch_field(pool, field, count, params, end_date=None):
+    """
+    逐 ETF 拉取单字段数据，返回 DataFrame（index=日期, columns=ETF代码）。
+
+    单标的 + panel=False 在聚宽云端稳定返回 DataFrame（columns=字段名），
+    多标的传入 panel=False 可能仍返回 Panel，因此改为逐只拉取后手工组装。
+
+    end_date: 历史数据截止日期。开盘调仓时需传入 context.previous_date
+              以避免当日收盘价未来数据。
+    """
+    series_map = {}
+    for etf in pool:
+        df = get_price(
+            etf,
+            count=count,
+            end_date=end_date,
+            frequency='daily',
+            fields=[field],
+            skip_paused=True,
+            fq=params["fq_mode"],
+            panel=False,
+        )
+        if df is not None and len(df) > 0:
+            series_map[etf] = df[field]
+
+    if not series_map:
+        return pd.DataFrame(columns=pool)
+
+    result = pd.DataFrame(series_map)
+    result = result.reindex(columns=pool)
+    return result.dropna(how='all')
+
+
+def get_history_data(context, pool, params, asof_date=None):
+    """
+    拉取足够长的历史 OHLC + 成交额数据，并预计算日收益率。
+
+    返回 dict：
+      close/high/low/amount: DataFrame（index=日期, columns=ETF代码）
+      close_ret: DataFrame（index=日期, columns=ETF代码），close 的 pct_change()
+    """
+    needed = compute_history_count(params)
+    history_end_date = asof_date if asof_date is not None else getattr(context, "previous_date", None)
+
+    prices = {}
+    prices['close'] = fetch_field(pool, 'close', needed, params, end_date=history_end_date)
+    prices['high'] = fetch_field(pool, 'high', needed, params, end_date=history_end_date)
+    prices['low'] = fetch_field(pool, 'low', needed, params, end_date=history_end_date)
+    prices['amount'] = fetch_field(pool, 'money', needed, params, end_date=history_end_date)
+
+    # 预计算日收益率，下游风险平价和组合波动率复用同一份
+    prices['close_ret'] = prices['close'].pct_change()
+
+    # 数据新鲜度日志：确保历史数据不晚于 context.previous_date
+    close_df = prices['close']
+    last_dt = close_df.index[-1] if len(close_df) else None
+    log.info("history end_date=%s, asof_date=%s", last_dt, history_end_date)
+
+    return prices
+
+
+# ============================================================
+# compute_trend_gates — 趋势门槛（硬过滤）
+# ============================================================
+def compute_trend_gates(prices, pool, params):
+    """
+    使用趋势均线判断方向，支持按 ETF 分别设置窗口。
+
+    返回: list[float]，1.0 表示通过，0.0 表示剔除
+    """
+    close = prices['close']
+    ma_windows = resolve_ma_long_windows(params)
+
+    gates = np.zeros(len(pool))
+    for i, etf in enumerate(pool):
+        if etf not in close.columns:
+            continue
+        ma_window = ma_windows[i]
+        series = close[etf].dropna()
+        if len(series) < ma_window:
+            continue
+        ma = series.iloc[-ma_window:].mean()
+        current_close = series.iloc[-1]
+        if current_close > ma:
+            gates[i] = 1.0
+    return gates
+
+
+# ============================================================
+# compute_momentum_scores — 多周期排名动量分数
+# ============================================================
+def compute_momentum_scores(prices, pool, trend_gates, params):
+    """
+    在趋势成立的资产中，计算多周期排名动量分数。
+
+    对 close DataFrame 批量取各周期终点收益，再用 rank(pct=True)
+    在截面上生成 0~1 排名分数，最后按权重线性组合。
+
+    返回: np.array，未通过趋势门槛的资产分数为 0
+    """
+    close = prices['close']
+    n = len(pool)
+    scores = np.zeros(n)
+
+    windows = [params["MomShort"], params["MomMid"], params["MomLong"]]
+    period_weights = [params["w20"], params["w60"], params["w120"]]
+
+    active_indices = [i for i in range(n) if trend_gates[i] > 0]
+    if not active_indices:
+        return scores
+
+    active_pool = [pool[i] for i in active_indices if pool[i] in close.columns]
+    if not active_pool:
+        return scores
+    active_close = close[active_pool]
+    if len(active_close) <= max(windows):
+        return scores
+
+    for j, w in enumerate(windows):
+        if len(active_close) <= w:
+            continue
+        latest = active_close.iloc[-1]
+        past = active_close.iloc[-(w + 1)]
+        period_ret = latest / past - 1  # pd.Series, index=ETF代码
+
+        # rank(pct=True) 将收益率映射到 [0, 1]，收益率越高排名越接近 1
+        ranks = period_ret.rank(pct=True).fillna(0.0)
+
+        for idx_pos, active_i in enumerate(active_indices):
+            etf_code = pool[active_i]
+            scores[active_i] += period_weights[j] * float(ranks.get(etf_code, 0.0))
+
+    return scores
+
+
+# ============================================================
+# select_topk — TopK 入选
+# ============================================================
+def select_topk(momentum_scores, trend_gates, params):
+    """
+    在趋势成立资产中按动量分数从高到低选择前 TopK 只。
+
+    返回: list[bool]，入选为 True
+    """
+    n = len(momentum_scores)
+    selected = [False] * n
+
+    active = [(i, momentum_scores[i]) for i in range(n) if trend_gates[i] > 0]
+    active.sort(key=lambda x: x[1], reverse=True)
+
+    k = min(params["TopK"], len(active))
+    for idx, _ in active[:k]:
+        selected[idx] = True
+
+    return selected
+
+
+# ============================================================
+# compute_rp_weights — 逆波动率风险平价
+# ============================================================
+def compute_rp_weights(prices, pool, active_mask, params):
+    """
+    对活跃资产计算逆波动率风险平价权重。
+
+    所有趋势成立资产均参与基础权重计算，不再受 TopK 限制。
+    使用 get_history_data 预计算的 close_ret，避免重复 pct_change()。
+
+    返回: np.array
+    """
+    close_ret = prices['close_ret']
+    n = len(pool)
+    vol_window = params["VolWindow"]
+    annual_factor = params["annual_factor"]
+
+    weights = np.zeros(n)
+    active_indices = [i for i in range(n) if active_mask[i]]
+
+    if not active_indices:
+        return weights
+
+    vols = np.zeros(n)
+    for i in active_indices:
+        etf = pool[i]
+        if etf not in close_ret.columns:
+            continue
+        daily_ret = close_ret[etf].dropna().iloc[-vol_window:]
+        if len(daily_ret) < 5:
+            vols[i] = 1.0
+        else:
+            vols[i] = daily_ret.std() * np.sqrt(annual_factor)
+            if vols[i] < 1e-8:
+                vols[i] = 1e-8
+
+    inverse_vols = np.zeros(n)
+    for i in active_indices:
+        if vols[i] > 0:
+            inverse_vols[i] = 1.0 / vols[i]
+
+    total_inv_vol = inverse_vols.sum()
+    if total_inv_vol > 0:
+        weights = inverse_vols / total_inv_vol
+
+    return weights
+
+
+# ============================================================
+# compute_rsrs_multipliers — RSRS 线性修正乘数
+# ============================================================
+def compute_rsrs_multipliers(prices, pool, params):
+    """
+    对每只 ETF 计算 RSRS 截断线性乘数（旧接口，保留兼容）。
+
+    委托 compute_rsrs_adjusted_scores 获取原始信号，
+    再按旧公式 clip(1 + RSRS_Adj / NegativeFullCut, Min, Max)。
+
+    只减仓，不加仓。
+    """
+    rsrs_adj = compute_rsrs_adjusted_scores(prices, pool, params)
+    full_cut = params["RSRS_NegativeFullCut"]
+    n = len(pool)
+
+    multipliers = np.ones(n)
+    for i in range(n):
+        raw_mult = 1.0 + rsrs_adj[i] / full_cut
+        multipliers[i] = np.clip(raw_mult, params["RSRSMinMultiplier"], params["RSRSMaxMultiplier"])
+
+    return multipliers
+
+
+# ============================================================
+# compute_rsrs_adjusted_scores — RSRS 原始结构信号
+# ============================================================
+def compute_rsrs_adjusted_scores(prices, pool, params):
+    """
+    计算每只 ETF 的 RSRS 原始调整信号：RSRSAdj_i = RSRS_Z_i × R2_i。
+
+    返回: np.array，数据不足时对应位置为 0。
+    """
+    high = prices['high']
+    low = prices['low']
+    n = len(pool)
+
+    N = params["RSRS_N"]
+    M = params["RSRS_M"]
+
+    scores = np.zeros(n)
+
+    for i, etf in enumerate(pool):
+        if etf not in high.columns or etf not in low.columns:
+            continue
+        h = high[etf].dropna()
+        l = low[etf].dropna()
+
+        common_idx = h.index.intersection(l.index)
+        h = h.loc[common_idx]
+        l = l.loc[common_idx]
+
+        min_len = M + N - 1
+        if len(h) < min_len:
+            continue
+
+        h_roll = h.rolling(N)
+        l_roll = l.rolling(N)
+        cov_vals = h_roll.cov(l).dropna().values
+        var_l_vals = l_roll.var().dropna().values
+        var_h_vals = h_roll.var().dropna().values
+
+        betas = cov_vals / var_l_vals
+        r2s = cov_vals ** 2 / (var_h_vals * var_l_vals)
+
+        bad = (
+            (var_l_vals < 1e-10) | (var_h_vals < 1e-10)
+            | (~np.isfinite(betas)) | (~np.isfinite(r2s))
+        )
+        betas[bad] = 1.0
+        r2s[bad] = 0.0
+
+        if len(betas) < M:
+            continue
+
+        beta_series = betas[-M:]
+        mean_beta = np.mean(beta_series)
+        std_beta = np.std(beta_series)
+
+        if std_beta < 1e-10:
+            rsrs_z = 0.0
+        else:
+            rsrs_z = (beta_series[-1] - mean_beta) / std_beta
+
+        latest_r2 = r2s[-1]
+        scores[i] = rsrs_z * latest_r2
+
+    return scores
+
+
+# ============================================================
+# compute_momentum_tilt_multipliers — 动量相对倾斜乘数
+# ============================================================
+def compute_momentum_tilt_multipliers(momentum_scores, trend_gates, params):
+    """
+    将动量分数转换为资产间相对倾斜乘数。
+
+    活跃资产围绕均值上下倾斜，非活跃资产返回 0。
+    倾斜公式：clip(1 + strength × (score_i - mean_active), min, max)
+    若启用极端高动量弱化，则 score_i 达到阈值后再将高位倾斜压到 cap。
+    """
+    n = len(momentum_scores)
+    tilts = np.zeros(n)
+
+    active_indices = [i for i in range(n) if trend_gates[i] > 0]
+    if not active_indices:
+        return tilts
+
+    active_scores = momentum_scores[active_indices]
+    mean_score = np.mean(active_scores)
+
+    strength = params["MomentumTiltStrength"]
+    tilt_min = params["MomentumTiltMin"]
+    tilt_max = params["MomentumTiltMax"]
+    extreme_start = params["MomentumExtremeScoreStart"]
+    extreme_cap = params["MomentumExtremeTiltCap"]
+
+    for i in active_indices:
+        edge = momentum_scores[i] - mean_score
+        raw_tilt = 1.0 + strength * edge
+        tilt = np.clip(raw_tilt, tilt_min, tilt_max)
+        if extreme_start is not None and momentum_scores[i] >= extreme_start:
+            tilt = min(tilt, extreme_cap)
+        tilts[i] = tilt
+
+    return tilts
+
+
+# ============================================================
+# compute_rsrs_tilt_multipliers — RSRS 相对倾斜乘数
+# ============================================================
+def compute_rsrs_tilt_multipliers(prices, pool, trend_gates, params):
+    """
+    计算 RSRS 原始结构信号，并转换为资产间相对倾斜乘数。
+
+    活跃资产围绕均值上下倾斜，非活跃资产返回 0。
+    倾斜公式：clip(1 + (RSRSAdj_i - mean_active) / NegativeFullCut, min, max)
+    """
+    rsrs_adj = compute_rsrs_adjusted_scores(prices, pool, params)
+    n = len(pool)
+    tilts = np.zeros(n)
+
+    active_indices = [i for i in range(n) if trend_gates[i] > 0]
+    if not active_indices:
+        return tilts
+
+    active_adj = rsrs_adj[active_indices]
+    mean_adj = np.mean(active_adj)
+
+    full_cut = params["RSRS_NegativeFullCut"]
+    tilt_min = params["RSRSTiltMin"]
+    tilt_max = params["RSRSTiltMax"]
+
+    for i in active_indices:
+        edge = rsrs_adj[i] - mean_adj
+        raw_tilt = 1.0 + edge / full_cut
+        tilts[i] = np.clip(raw_tilt, tilt_min, tilt_max)
+
+    return tilts
+
+
+# ============================================================
+# apply_relative_tilts — 倾斜权重合成与归一化
+# ============================================================
+def apply_relative_tilts(rp_weights, trend_gates, momentum_tilts, rsrs_tilts):
+    """
+    将风险平价基础权重、动量倾斜和 RSRS 倾斜合成，并在活跃资产内归一化。
+
+    tilted_raw_i = RPWeight_i × MomentumTilt_i × RSRSTilt_i
+    归一化到 sum(RPWeight_active)，非活跃资产权重为 0。
+    """
+    n = len(rp_weights)
+    tilted = np.zeros(n)
+
+    active_indices = [i for i in range(n) if trend_gates[i] > 0 and rp_weights[i] > 0]
+    if not active_indices:
+        return tilted
+
+    tilted_raw = np.zeros(n)
+    for i in active_indices:
+        tilted_raw[i] = rp_weights[i] * momentum_tilts[i] * rsrs_tilts[i]
+
+    total_raw = tilted_raw[active_indices].sum()
+    base_total = rp_weights[active_indices].sum()
+
+    if total_raw <= 0 or base_total <= 0:
+        return np.copy(rp_weights)
+
+    for i in active_indices:
+        tilted[i] = tilted_raw[i] / total_raw * base_total
+
+    return tilted
+
+
+# ============================================================
+# compute_crowd_penalties — 拥挤度线性惩罚乘数
+# ============================================================
+def compute_crowd_penalties(prices, pool, params):
+    """
+    对每只 ETF 计算拥挤度线性惩罚乘数。
+
+    先在 DataFrame 级批量计算五类指标（ret20/ret60/amt_ma20/deviation/vol20），
+    再逐 ETF 取最后一行做分位排名，减少 Python 层逐列 rolling/pct_change 开销。
+
+    只减仓，不加仓。
+
+    返回: np.array
+    """
+    close = prices['close']
+    amount = prices['amount']
+    n = len(pool)
+
+    crowd_window = params["CrowdWindow"]
+    thresholds = resolve_crowd_thresholds(params)    # [(start, end, min_penalty), ...]
+    ret_windows = resolve_crowd_ret_windows(params)  # [(short, mid), ...]
+
+    penalties = np.ones(n)
+
+    # 过滤数据不足的 ETF
+    eligible_etfs = []
+    for i, etf in enumerate(pool):
+        if etf in close.columns and len(close[etf].dropna()) >= crowd_window:
+            eligible_etfs.append(etf)
+        else:
+            penalties[i] = 1.0
+
+    if not eligible_etfs:
+        return penalties
+
+    # ---- DataFrame 级批量计算：一次算完所有 ETF 的指标 ----
+    close_recent = close[eligible_etfs].iloc[-crowd_window:]
+
+    # 1-2) 短/中期涨幅（按 per-ETF 窗口预计算，避免重复 shift）
+    ret_short_map = {}
+    ret_mid_map = {}
+    for i, etf in enumerate(pool):
+        if etf not in eligible_etfs:
+            continue
+        short_w, mid_w = ret_windows[i]
+        if short_w not in ret_short_map:
+            ret_short_map[short_w] = close_recent / close_recent.shift(short_w) - 1
+        if mid_w not in ret_mid_map:
+            ret_mid_map[mid_w] = close_recent / close_recent.shift(mid_w) - 1
+
+    # 3) 成交额 MA20（仅对有 amount 数据的 ETF）
+    eligible_amount_cols = [e for e in eligible_etfs if e in amount.columns]
+    amt_ma20_df = None
+    if eligible_amount_cols:
+        amt_aligned = amount[eligible_amount_cols].loc[
+            amount.index.intersection(close_recent.index)
+        ]
+        if len(amt_aligned) >= params["AmountMAWindow"]:
+            amt_ma20_df = amt_aligned.rolling(params["AmountMAWindow"]).mean()
+
+    # 4) 偏离均线程度
+    ma20_df = close_recent.rolling(params["DeviationMAWindow"]).mean()
+    deviation_df = close_recent / ma20_df - 1
+
+    # 5) 短期波动率
+    vol20_df = close_recent.pct_change().rolling(params["CrowdVolWindow"]).std() * np.sqrt(params["annual_factor"])
+
+    # ---- 逐 ETF 从预计算 DataFrame 中取列做分位排名 ----
+    for i, etf in enumerate(pool):
+        if etf not in eligible_etfs:
+            continue
+
+        indicators = []
+
+        # ret short (per-ETF window)
+        short_w = ret_windows[i][0]
+        col_short = ret_short_map[short_w][etf].dropna()
+        indicators.append(percentile_rank(col_short.iloc[-1], col_short) if len(col_short) > 1 else 0.5)
+
+        # ret mid (per-ETF window)
+        mid_w = ret_windows[i][1]
+        col_mid = ret_mid_map[mid_w][etf].dropna()
+        indicators.append(percentile_rank(col_mid.iloc[-1], col_mid) if len(col_mid) > 1 else 0.5)
+
+        # amt_ma20
+        if amt_ma20_df is not None and etf in amt_ma20_df.columns:
+            col_amt = amt_ma20_df[etf].dropna()
+            indicators.append(percentile_rank(col_amt.iloc[-1], col_amt) if len(col_amt) > 1 else 0.5)
+        else:
+            indicators.append(0.5)
+
+        # deviation
+        col_dev = deviation_df[etf].dropna()
+        indicators.append(percentile_rank(col_dev.iloc[-1], col_dev) if len(col_dev) > 1 else 0.5)
+
+        # vol20
+        col_vol = vol20_df[etf].dropna()
+        indicators.append(percentile_rank(col_vol.iloc[-1], col_vol) if len(col_vol) > 1 else 0.5)
+
+        crowd_score = np.mean(indicators)
+
+        etf_start, etf_end, etf_min = thresholds[i]
+        if crowd_score <= etf_start:
+            penalty = 1.0
+        elif crowd_score >= etf_end:
+            penalty = etf_min
+        else:
+            penalty = 1.0 - (crowd_score - etf_start) / (etf_end - etf_start) * (1.0 - etf_min)
+            penalty = max(etf_min, min(1.0, penalty))
+
+        penalties[i] = penalty
+
+    return penalties
+
+
+# ============================================================
+# percentile_rank — 计算分位数排名（0~1）
+# ============================================================
+def percentile_rank(value, series):
+    """
+    计算 value 在 series 中的分位数（0~1）。
+
+    返回 0 表示 value 是序列中最小值，返回 1 表示最大值。
+    """
+    if len(series) == 0:
+        return 0.5
+    ranked = (series < value).mean()
+    return float(ranked)
+
+
+# ============================================================
+# compute_portfolio_vol_scale — 组合波动率缩放系数
+# ============================================================
+def compute_portfolio_vol_scale_detail(prices, pool, raw_weights, params):
+    """
+    根据 RawWeight 和协方差矩阵计算组合波动率，按目标波动率缩放。
+
+    使用 get_history_data 预计算的 close_ret，避免重复 pct_change()。
+    只缩不放（最大系数为 1.0）。
+
+    返回: (scale, vol_ratio)
+    """
+    close_ret = prices['close_ret']
+    vol_window = params["PortfolioVolWindow"]
+    target_vol = params["TargetVol"]
+    annual_factor = params["annual_factor"]
+
+    n = len(pool)
+    active_indices = [i for i in range(n) if raw_weights[i] > 1e-8]
+
+    if not active_indices:
+        return 1.0, None
+
+    returns_list = []
+    for i in active_indices:
+        etf = pool[i]
+        if etf not in close_ret.columns:
+            return 1.0, None
+        ret = close_ret[etf].dropna().iloc[-vol_window:]
+        if len(ret) < vol_window:
+            return 1.0, None
+        returns_list.append(ret.values)
+
+    if not returns_list:
+        return 1.0, None
+
+    ret_matrix = np.column_stack(returns_list)
+    cov_daily = np.atleast_2d(np.cov(ret_matrix, rowvar=False))
+    cov_annual = cov_daily * annual_factor
+
+    active_weights = np.array([raw_weights[i] for i in active_indices])
+    portfolio_var = active_weights @ cov_annual @ active_weights
+    portfolio_vol = np.sqrt(max(portfolio_var, 0))
+    vol_ratio = float(portfolio_vol / target_vol)
+
+    if portfolio_vol <= target_vol or portfolio_vol < 1e-8:
+        return 1.0, vol_ratio
+
+    scale = target_vol / portfolio_vol
+    return min(scale, params["MaxPortfolioVolScale"]), vol_ratio
+
+
+def compute_portfolio_vol_scale(prices, pool, raw_weights, params):
+    """返回原有组合级波动率缩放标量。"""
+    scale, _vol_ratio = compute_portfolio_vol_scale_detail(prices, pool, raw_weights, params)
+    return scale
+
+
+def compute_portfolio_vol_asset_scales(prices, pool, raw_weights, params):
+    """返回每只 ETF 的组合波控缩放系数和审计元数据。"""
+    base_scale, vol_ratio = compute_portfolio_vol_scale_detail(prices, pool, raw_weights, params)
+    asset_scales = np.full(len(pool), base_scale)
+    mode = params["PortfolioVolReliefMode"]
+    meta = {
+        "mode": mode,
+        "vol_ratio": vol_ratio,
+        "base_scale": base_scale,
+        "relief_asset": None,
+        "relief_weight": 0.0,
+        "reason": "baseline",
+    }
+    if mode == "fixed_gold":
+        return apply_fixed_gold_vol_relief(pool, raw_weights, asset_scales, meta, params)
+    if mode == "dyn_marginal":
+        return apply_dynamic_marginal_vol_relief(prices, pool, raw_weights, asset_scales, meta, params)
+    return asset_scales, meta
+
+
+def apply_fixed_gold_vol_relief(pool, raw_weights, asset_scales, meta, params):
+    """固定黄金弱缩放：按参数恢复黄金被组合波控压掉的部分仓位。"""
+    gold_code = "518880.XSHG"
+    vol_ratio = meta["vol_ratio"]
+    base_scale = meta["base_scale"]
+
+    if vol_ratio is None or vol_ratio <= 1.0:
+        meta["reason"] = "vol_not_above_target"
+        return asset_scales, meta
+    if vol_ratio > params["GoldVolReliefMaxRatio"]:
+        meta["reason"] = "ratio_too_high"
+        return asset_scales, meta
+    if gold_code not in pool:
+        meta["reason"] = "gold_not_in_pool"
+        return asset_scales, meta
+
+    gold_idx = pool.index(gold_code)
+    if raw_weights[gold_idx] <= 1e-8:
+        meta["reason"] = "gold_not_active"
+        return asset_scales, meta
+
+    new_scale = min(1.0, base_scale + (1.0 - base_scale) * params["GoldVolReliefFraction"])
+    asset_scales[gold_idx] = new_scale
+    meta["relief_asset"] = gold_code
+    meta["relief_weight"] = float(raw_weights[gold_idx] * (new_scale - base_scale))
+    meta["reason"] = "fixed_gold"
+    return asset_scales, meta
+
+
+def apply_dynamic_marginal_vol_relief(prices, pool, raw_weights, asset_scales, meta, params):
+    """动态弱缩放：在正动量持仓中选择边际风险最低资产恢复仓位。"""
+    vol_ratio = meta["vol_ratio"]
+    base_scale = meta["base_scale"]
+
+    if vol_ratio is None or vol_ratio <= 1.0:
+        meta["reason"] = "vol_not_above_target"
+        return asset_scales, meta
+    if vol_ratio > params["DynamicVolReliefMaxRatio"]:
+        meta["reason"] = "ratio_too_high"
+        return asset_scales, meta
+
+    selected_idx, reason = select_dynamic_marginal_relief_asset(
+        prices, pool, raw_weights, params
+    )
+    if selected_idx is None:
+        meta["reason"] = reason
+        return asset_scales, meta
+
+    new_scale = min(1.0, base_scale + (1.0 - base_scale) * params["DynamicVolReliefFraction"])
+    asset_scales[selected_idx] = new_scale
+    meta["relief_asset"] = pool[selected_idx]
+    meta["relief_weight"] = float(raw_weights[selected_idx] * (new_scale - base_scale))
+    meta["reason"] = "selected_low_marginal_risk"
+    return asset_scales, meta
+
+
+def select_dynamic_marginal_relief_asset(prices, pool, raw_weights, params):
+    """返回动态弱缩放资产下标和原因。"""
+    active_indices = [i for i, weight in enumerate(raw_weights) if weight > 1e-8]
+    if not active_indices:
+        return None, "no_active_asset"
+
+    close_ret = prices.get("close_ret")
+    if close_ret is None:
+        return None, "insufficient_cov_data"
+
+    active_codes = [pool[i] for i in active_indices]
+    for code in active_codes:
+        if code not in close_ret.columns:
+            return None, "insufficient_cov_data"
+
+    cov_window = params["DynamicVolReliefCovWindow"]
+    active_returns = close_ret[active_codes].dropna().iloc[-cov_window:]
+    if len(active_returns) < cov_window:
+        return None, "insufficient_cov_data"
+
+    momentum_window = params["DynamicVolReliefMomentumWindow"]
+    positive_candidates = []
+    for active_pos, code in enumerate(active_codes):
+        momentum_ret = close_ret[code].dropna().iloc[-momentum_window:]
+        if len(momentum_ret) < momentum_window:
+            continue
+        momentum = float(np.prod(1.0 + momentum_ret.values) - 1.0)
+        if momentum >= 0.0:
+            positive_candidates.append(active_pos)
+
+    if not positive_candidates:
+        return None, "no_positive_momentum_asset"
+
+    cov_daily = np.atleast_2d(np.cov(active_returns.values, rowvar=False))
+    cov_annual = cov_daily * params["annual_factor"]
+    active_weights = np.array([raw_weights[i] for i in active_indices])
+    marginal_scores = cov_annual @ active_weights
+    best_active_pos = min(
+        positive_candidates,
+        key=lambda active_pos: marginal_scores[active_pos],
+    )
+    return active_indices[best_active_pos], "selected_low_marginal_risk"
+
+
+# ============================================================
+# apply_weight_constraints — 应用仓位约束
+# ============================================================
+def apply_weight_constraints(final_weights, params):
+    """
+    应用单资产最大仓位、最小有效仓位和总仓位上限约束。
+
+    总仓位约束在单资产约束之后应用，缩放后不重新归一化。
+    """
+    max_w = params["MaxWeight"]
+    min_w = params["MinWeight"]
+    max_total = params["MaxTotalWeight"]
+    n = len(final_weights)
+
+    result = np.copy(final_weights)
+
+    for i in range(n):
+        if result[i] > max_w:
+            result[i] = max_w
+        if result[i] < min_w:
+            result[i] = 0.0
+
+    total = result.sum()
+    if total > max_total:
+        result = result * max_total / total
+
+    return result
+
+
+# ============================================================
+# execute_rebalance — 执行调仓
+# ============================================================
+def execute_rebalance(context, pool, final_weights, params):
+    """
+    根据最终目标权重执行调仓，应用最小调仓阈值。
+    剩余仓位保留为现金。
+
+    执行前检查停牌状态，执行后记录订单结果，便于审计和故障定位。
+    """
+    account_value = context.portfolio.total_value
+    current_data = get_current_data()
+    etf_names = build_etf_display_names(pool, params.get("etf_names"))
+
+    for i, etf in enumerate(pool):
+        etf_name = etf_names[i]
+        target_value = account_value * final_weights[i]
+        current_pos = context.portfolio.positions[etf]
+        current_value = current_pos.total_amount * current_pos.price if current_pos.total_amount > 0 else 0
+        current_weight = current_value / account_value if account_value > 0 else 0
+
+        # 如果目标权重为 0 且当前仓位为 0，跳过
+        if final_weights[i] == 0 and current_weight == 0:
+            audit_event(
+                "rebalance_order",
+                context,
+                action="skip_zero_target_zero_position",
+                etf=etf,
+                etf_name=etf_name,
+                target_weight=final_weights[i],
+                current_weight=current_weight,
+                target_value=target_value,
+            )
+            continue
+
+        # 最小调仓阈值
+        if abs(final_weights[i] - current_weight) < params["RebalanceThreshold"]:
+            audit_event(
+                "rebalance_order",
+                context,
+                action="skip_threshold",
+                etf=etf,
+                etf_name=etf_name,
+                target_weight=final_weights[i],
+                current_weight=current_weight,
+                target_value=target_value,
+                rebalance_threshold=params["RebalanceThreshold"],
+            )
+            continue
+
+        # 停牌检查
+        data = current_data[etf]
+        if data.paused:
+            log.warning("skip paused ETF: %s security=%s", etf_name, etf)
+            audit_event(
+                "rebalance_order",
+                context,
+                action="skip_paused",
+                etf=etf,
+                etf_name=etf_name,
+                target_weight=final_weights[i],
+                current_weight=current_weight,
+                target_value=target_value,
+            )
+            continue
+
+        order_obj = order_target_value(etf, target_value)
+        if order_obj is None:
+            log.error(
+                "order failed: %s security=%s target_value=%.2f target_weight=%.4f current_weight=%.4f",
+                etf_name, etf, target_value, final_weights[i], current_weight
+            )
+            audit_event(
+                "rebalance_order",
+                context,
+                action="order_failed",
+                etf=etf,
+                etf_name=etf_name,
+                target_weight=final_weights[i],
+                current_weight=current_weight,
+                target_value=target_value,
+            )
+        else:
+            log.info(
+                "order sent: %s security=%s target_weight=%.4f current_weight=%.4f target_value=%.2f",
+                etf_name, etf, final_weights[i], current_weight, target_value
+            )
+            audit_event(
+                "rebalance_order",
+                context,
+                action="order_sent",
+                etf=etf,
+                etf_name=etf_name,
+                target_weight=final_weights[i],
+                current_weight=current_weight,
+                target_value=target_value,
+                order=order_obj,
+            )
diff --git a/strategies/etf_factor_rotation/variants/code/weekend_close_signal_next_open_variant.py b/strategies/etf_factor_rotation/variants/code/weekend_close_signal_next_open_variant.py
new file mode 100644
index 00000000..06a6cb54
--- /dev/null
+++ b/strategies/etf_factor_rotation/variants/code/weekend_close_signal_next_open_variant.py
@@ -0,0 +1,2025 @@
+# 策略名：ETF多因子轮动
+enable_profile()
+STRATEGY_NAME = "ETF多因子轮动"
+try:
+    import FeishuRelayTools
+except ImportError:
+    FeishuRelayTools = None
+
+"""
+============================================================
+策略名称：ETF 多因子轮动策略（相对倾斜版）
+策略类型：周线级别、场内基金、多因子动态配置
+适用标的：159819.XSHE、513100.XSHG、518880.XSHG（中文名运行时通过聚宽 API 读取）
+
+核心思想：
+  趋势门槛判断"能不能买"，风险平价分配基础仓位，
+  动量和 RSRS 作为资产间相对倾斜信号调整权重分配（不改变组合总仓位），
+  拥挤度惩罚和组合波动率控制在过热或高波时平滑降仓。
+  剩余仓位保留现金，不重新归一化到满仓。
+
+模块分工：
+  - 趋势门槛（硬过滤）：按 ETF 专属趋势均线以上才可入选，0/1 离散
+  - 风险平价（逆波动率）：所有趋势成立资产参与，σ 越小权重越大
+  - 动量倾斜（相对信号）：多周期排名分数去均值，clip 到 [TiltMin, TiltMax]；
+    可选将极端高分资产的动量倾斜压回中性
+  - RSRS 倾斜（相对信号）：High~Low 回归 β 标准化 × R² 去均值，clip 到 [TiltMin, TiltMax]
+  - 倾斜合成：RPWeight × MomentumTilt × RSRSTilt，活跃资产内重新归一化
+  - 拥挤度惩罚（只减不加）：五指标分位数均值，超阈值线性打折
+  - 组合波动率控制（只缩不放）：RawWeight 组合波动率超目标时等比缩放
+
+核心公式：
+  TiltedWeight_i = normalize(RPWeight_i × MomentumTilt_i × RSRSTilt_i)
+  RawWeight_i = TiltedWeight_i × TrendGate_i × CrowdPenalty_i
+  FinalWeight_i = RawWeight_i × PortfolioVolAssetScale_i
+
+调仓频率：每周开盘检查一次
+============================================================
+"""
+
+import json
+from datetime import date, datetime
+
+import numpy as np
+import pandas as pd
+
+
+# ============================================================
+# 常量 — 内部字段名到聚宽字段名的映射
+# ============================================================
+FIELD_MAP = {
+    "close": "close",
+    "high": "high",
+    "low": "low",
+    "amount": "money",
+}
+
+JQ_AUTO_AUDIT_TOKEN = "manual"
+JQ_AUTO_AUDIT_DIR = "jq_auto_audit"
+PARAM_DEFAULTS = {
+    "etf_pool": (
+        "159819.XSHE",
+        "513100.XSHG",
+        "518880.XSHG",
+    ),
+    "MA_long": 120,
+    "MA_long_by_etf": (20, 40, 100),
+    "MomShort": 20,
+    "MomMid": 60,
+    "MomLong": 120,
+    "w20": 0.2,
+    "w60": 0.3,
+    "w120": 0.5,
+    "TopK": 3,
+    "VolWindow": 60,
+    "annual_factor": 252,
+    "RSRS_N": 18,
+    "RSRS_M": 600,
+    "RSRS_NegativeFullCut": 1.8,
+    "RSRSMinMultiplier": 0.0,
+    "RSRSMaxMultiplier": 1.3,
+    "MomentumTiltStrength": 0.50,
+    "MomentumTiltMin": 0.70,
+    "MomentumTiltMax": 1.30,
+    "MomentumExtremeScoreStart": None,
+    "MomentumExtremeTiltCap": 1.00,
+    "RSRSTiltMin": 0.70,
+    "RSRSTiltMax": 1.30,
+    "CrowdWindow": 500,
+    "CrowdRetShort": 20,
+    "CrowdRetMid": 60,
+    "AmountMAWindow": 20,
+    "DeviationMAWindow": 20,
+    "CrowdVolWindow": 20,
+    "CrowdStart": 0.60,
+    "CrowdEnd": 0.95,
+    "MinCrowdPenalty": 0.30,
+    "CrowdStart_by_etf": (0.60, 0.60, 0.80),
+    "CrowdEnd_by_etf": None,
+    "MinCrowdPenalty_by_etf": None,
+    "CrowdRetShort_by_etf": None,
+    "CrowdRetMid_by_etf": None,
+    "PortfolioVolWindow": 40,
+    "TargetVol": 0.08,
+    "MaxPortfolioVolScale": 1.0,
+    "PortfolioVolReliefMode": "dyn_marginal",
+    "GoldVolReliefFraction": 0.5,
+    "GoldVolReliefMaxRatio": 2.0,
+    "DynamicVolReliefFraction": 1.0,
+    "DynamicVolReliefMaxRatio": 1.5,
+    "DynamicVolReliefMomentumWindow": 20,
+    "DynamicVolReliefCovWindow": 40,
+    "MaxWeight": 0.60,
+    "MinWeight": 0.05,
+    "RebalanceThreshold": 0.03,
+    "MaxTotalWeight": 1.0,
+    "ExecutionTimingMode": "weekend-close-signal-next-open",
+    "use_real_price": False,
+    "fq_mode": None,
+    "history_buffer": 100,
+    "benchmark": "000300.XSHG",
+}
+EXECUTION_TIMING_MODES = (
+    "baseline",
+    "logic-2-delay-only",
+    "logic-3-live-like",
+    "weekend-close-signal-next-open",
+)
+DEFAULT_EXECUTION_TIMING_MODE = PARAM_DEFAULTS["ExecutionTimingMode"]
+PORTFOLIO_VOL_RELIEF_MODES = (
+    "baseline",
+    "fixed_gold",
+    "dyn_marginal",
+)
+PORTFOLIO_VOL_RELIEF_DEFAULTS = {
+    "PortfolioVolReliefMode": PARAM_DEFAULTS["PortfolioVolReliefMode"],
+    "GoldVolReliefFraction": PARAM_DEFAULTS["GoldVolReliefFraction"],
+    "GoldVolReliefMaxRatio": PARAM_DEFAULTS["GoldVolReliefMaxRatio"],
+    "DynamicVolReliefFraction": PARAM_DEFAULTS["DynamicVolReliefFraction"],
+    "DynamicVolReliefMaxRatio": PARAM_DEFAULTS["DynamicVolReliefMaxRatio"],
+    "DynamicVolReliefMomentumWindow": PARAM_DEFAULTS["DynamicVolReliefMomentumWindow"],
+    "DynamicVolReliefCovWindow": PARAM_DEFAULTS["DynamicVolReliefCovWindow"],
+}
+
+
+def fund_code(security):
+    """从聚宽证券代码中提取 6 位基金代码，用于报告和日志展示。"""
+    return str(security).split(".")[0]
+
+
+def format_etf_name(security, name):
+    """保证基金显示名使用 中文名(聚宽代码) 标准格式。"""
+    security = str(security)
+    code = fund_code(security)
+    display_name = str(name).strip() if name is not None else str(security)
+    full_suffix = "(%s)" % security
+    short_suffix = "(%s)" % code
+    if display_name == security:
+        return display_name
+    if display_name.endswith(full_suffix):
+        return display_name
+    if code and display_name.endswith(short_suffix):
+        display_name = display_name[:-len(short_suffix)].strip()
+    return "%s%s" % (display_name, full_suffix)
+
+
+def build_etf_display_names(pool, names=None):
+    """按 etf_pool 顺序生成带编号的基金显示名列表。"""
+    names = names or []
+    result = []
+    for i, etf in enumerate(pool):
+        base_name = names[i] if i < len(names) else etf
+        result.append(format_etf_name(etf, base_name))
+    return result
+
+
+def fetch_etf_official_name(security, fallback_name=None):
+    """通过聚宽 API 读取基金官方中文名，失败时回退到已有名称或代码。"""
+    try:
+        info = get_security_info(security)
+        for attr in ("display_name", "name"):
+            value = getattr(info, attr, None)
+            if value:
+                return str(value).strip()
+    except Exception as exc:
+        log.warning("fetch ETF official name failed: security=%s error=%s", security, exc)
+
+    return fallback_name or str(security)
+
+
+def load_etf_display_names(pool, fallback_names=None):
+    """从聚宽官方证券信息生成标准 ETF 显示名。"""
+    fallback_names = fallback_names or []
+    names = []
+    for i, etf in enumerate(pool):
+        fallback_name = fallback_names[i] if i < len(fallback_names) else None
+        official_name = fetch_etf_official_name(etf, fallback_name=fallback_name)
+        names.append(format_etf_name(etf, official_name))
+    return names
+
+
+def _audit_jsonable(value):
+    """Convert strategy/runtime values to JSON-safe audit payloads."""
+    if value is None or isinstance(value, (str, bool, int, float)):
+        return value
+    if isinstance(value, (date, datetime)):
+        return value.isoformat()
+    try:
+        if isinstance(value, np.generic):
+            return _audit_jsonable(value.item())
+        if isinstance(value, np.ndarray):
+            return [_audit_jsonable(item) for item in value.tolist()]
+    except Exception:
+        pass
+    try:
+        if isinstance(value, pd.Timestamp):
+            return value.isoformat()
+        if isinstance(value, (pd.Series, pd.Index)):
+            return [_audit_jsonable(item) for item in value.tolist()]
+        if isinstance(value, pd.DataFrame):
+            return [
+                {str(k): _audit_jsonable(v) for k, v in row.items()}
+                for row in value.reset_index().to_dict(orient="records")
+            ]
+    except Exception:
+        pass
+    if isinstance(value, dict):
+        return {str(k): _audit_jsonable(v) for k, v in value.items()}
+    if isinstance(value, (list, tuple, set)):
+        return [_audit_jsonable(item) for item in value]
+    return str(value)
+
+
+def _context_time_fields(context):
+    result = {}
+    for name in ("current_dt", "previous_date"):
+        value = getattr(context, name, None) if context is not None else None
+        if value is not None:
+            result[name] = _audit_jsonable(value)
+    return result
+
+
+def audit_event(event, context=None, **payload):
+    """Write one complete business-audit event to JoinQuant research storage."""
+    path = getattr(g, "audit_path", "")
+    if not path:
+        return
+    seq = getattr(g, "audit_seq", 0) + 1
+    g.audit_seq = seq
+    row = {
+        "seq": seq,
+        "event": event,
+        "audit_token": getattr(g, "audit_token", ""),
+    }
+    row.update(_context_time_fields(context))
+    row.update({key: _audit_jsonable(value) for key, value in payload.items()})
+    write_file(path, json.dumps(row, ensure_ascii=False, sort_keys=True) + "\n", append=True)
+
+
+def _copy_runtime_default(value):
+    if isinstance(value, tuple):
+        return list(value)
+    if isinstance(value, list):
+        return list(value)
+    if isinstance(value, dict):
+        return dict(value)
+    return value
+
+
+def _runtime_param(name, default):
+    if not hasattr(g, name):
+        setattr(g, name, _copy_runtime_default(default))
+    return getattr(g, name)
+
+
+def _runtime_list_param(name):
+    value = _runtime_param(name, PARAM_DEFAULTS[name])
+    if value is None:
+        return None
+    return list(value)
+
+
+# ============================================================
+# snapshot_params — 参数快照
+# ============================================================
+def snapshot_params():
+    """
+    从 g 读取全部策略参数，返回只读快照 dict。
+
+    核心计算函数通过接收 params 而非直接读 g，实现解耦。
+    """
+    etf_pool = _runtime_list_param("etf_pool")
+    raw_etf_names = _runtime_param("etf_names", etf_pool)
+    etf_names = build_etf_display_names(etf_pool, list(raw_etf_names))
+    return {
+        "etf_pool": etf_pool,
+        "etf_names": etf_names,
+        "benchmark": _runtime_param("benchmark", PARAM_DEFAULTS["benchmark"]),
+        "MA_long": _runtime_param("MA_long", PARAM_DEFAULTS["MA_long"]),
+        "MA_long_by_etf": _runtime_list_param("MA_long_by_etf"),
+        "MomShort": _runtime_param("MomShort", PARAM_DEFAULTS["MomShort"]),
+        "MomMid": _runtime_param("MomMid", PARAM_DEFAULTS["MomMid"]),
+        "MomLong": _runtime_param("MomLong", PARAM_DEFAULTS["MomLong"]),
+        "w20": _runtime_param("w20", PARAM_DEFAULTS["w20"]),
+        "w60": _runtime_param("w60", PARAM_DEFAULTS["w60"]),
+        "w120": _runtime_param("w120", PARAM_DEFAULTS["w120"]),
+        "TopK": _runtime_param("TopK", PARAM_DEFAULTS["TopK"]),
+        "VolWindow": _runtime_param("VolWindow", PARAM_DEFAULTS["VolWindow"]),
+        "annual_factor": _runtime_param("annual_factor", PARAM_DEFAULTS["annual_factor"]),
+        "RSRS_N": _runtime_param("RSRS_N", PARAM_DEFAULTS["RSRS_N"]),
+        "RSRS_M": _runtime_param("RSRS_M", PARAM_DEFAULTS["RSRS_M"]),
+        "RSRS_NegativeFullCut": _runtime_param("RSRS_NegativeFullCut", PARAM_DEFAULTS["RSRS_NegativeFullCut"]),
+        "RSRSMinMultiplier": _runtime_param("RSRSMinMultiplier", PARAM_DEFAULTS["RSRSMinMultiplier"]),
+        "RSRSMaxMultiplier": _runtime_param("RSRSMaxMultiplier", PARAM_DEFAULTS["RSRSMaxMultiplier"]),
+        "MomentumTiltStrength": _runtime_param("MomentumTiltStrength", PARAM_DEFAULTS["MomentumTiltStrength"]),
+        "MomentumTiltMin": _runtime_param("MomentumTiltMin", PARAM_DEFAULTS["MomentumTiltMin"]),
+        "MomentumTiltMax": _runtime_param("MomentumTiltMax", PARAM_DEFAULTS["MomentumTiltMax"]),
+        "MomentumExtremeScoreStart": _runtime_param("MomentumExtremeScoreStart", PARAM_DEFAULTS["MomentumExtremeScoreStart"]),
+        "MomentumExtremeTiltCap": _runtime_param("MomentumExtremeTiltCap", PARAM_DEFAULTS["MomentumExtremeTiltCap"]),
+        "RSRSTiltMin": _runtime_param("RSRSTiltMin", PARAM_DEFAULTS["RSRSTiltMin"]),
+        "RSRSTiltMax": _runtime_param("RSRSTiltMax", PARAM_DEFAULTS["RSRSTiltMax"]),
+        "CrowdWindow": _runtime_param("CrowdWindow", PARAM_DEFAULTS["CrowdWindow"]),
+        "CrowdRetShort": _runtime_param("CrowdRetShort", PARAM_DEFAULTS["CrowdRetShort"]),
+        "CrowdRetMid": _runtime_param("CrowdRetMid", PARAM_DEFAULTS["CrowdRetMid"]),
+        "AmountMAWindow": _runtime_param("AmountMAWindow", PARAM_DEFAULTS["AmountMAWindow"]),
+        "DeviationMAWindow": _runtime_param("DeviationMAWindow", PARAM_DEFAULTS["DeviationMAWindow"]),
+        "CrowdVolWindow": _runtime_param("CrowdVolWindow", PARAM_DEFAULTS["CrowdVolWindow"]),
+        "CrowdStart": _runtime_param("CrowdStart", PARAM_DEFAULTS["CrowdStart"]),
+        "CrowdEnd": _runtime_param("CrowdEnd", PARAM_DEFAULTS["CrowdEnd"]),
+        "MinCrowdPenalty": _runtime_param("MinCrowdPenalty", PARAM_DEFAULTS["MinCrowdPenalty"]),
+        "CrowdStart_by_etf": _runtime_list_param("CrowdStart_by_etf"),
+        "CrowdEnd_by_etf": _runtime_list_param("CrowdEnd_by_etf"),
+        "MinCrowdPenalty_by_etf": _runtime_list_param("MinCrowdPenalty_by_etf"),
+        "CrowdRetShort_by_etf": _runtime_list_param("CrowdRetShort_by_etf"),
+        "CrowdRetMid_by_etf": _runtime_list_param("CrowdRetMid_by_etf"),
+        "PortfolioVolWindow": _runtime_param("PortfolioVolWindow", PARAM_DEFAULTS["PortfolioVolWindow"]),
+        "TargetVol": _runtime_param("TargetVol", PARAM_DEFAULTS["TargetVol"]),
+        "MaxPortfolioVolScale": _runtime_param("MaxPortfolioVolScale", PARAM_DEFAULTS["MaxPortfolioVolScale"]),
+        "PortfolioVolReliefMode": _runtime_param(
+            "PortfolioVolReliefMode",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["PortfolioVolReliefMode"],
+        ),
+        "GoldVolReliefFraction": _runtime_param(
+            "GoldVolReliefFraction",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["GoldVolReliefFraction"],
+        ),
+        "GoldVolReliefMaxRatio": _runtime_param(
+            "GoldVolReliefMaxRatio",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["GoldVolReliefMaxRatio"],
+        ),
+        "DynamicVolReliefFraction": _runtime_param(
+            "DynamicVolReliefFraction",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["DynamicVolReliefFraction"],
+        ),
+        "DynamicVolReliefMaxRatio": _runtime_param(
+            "DynamicVolReliefMaxRatio",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["DynamicVolReliefMaxRatio"],
+        ),
+        "DynamicVolReliefMomentumWindow": _runtime_param(
+            "DynamicVolReliefMomentumWindow",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["DynamicVolReliefMomentumWindow"],
+        ),
+        "DynamicVolReliefCovWindow": _runtime_param(
+            "DynamicVolReliefCovWindow",
+            PORTFOLIO_VOL_RELIEF_DEFAULTS["DynamicVolReliefCovWindow"],
+        ),
+        "MaxWeight": _runtime_param("MaxWeight", PARAM_DEFAULTS["MaxWeight"]),
+        "MinWeight": _runtime_param("MinWeight", PARAM_DEFAULTS["MinWeight"]),
+        "RebalanceThreshold": _runtime_param("RebalanceThreshold", PARAM_DEFAULTS["RebalanceThreshold"]),
+        "MaxTotalWeight": _runtime_param("MaxTotalWeight", PARAM_DEFAULTS["MaxTotalWeight"]),
+        "ExecutionTimingMode": _runtime_param(
+            "ExecutionTimingMode",
+            DEFAULT_EXECUTION_TIMING_MODE,
+        ),
+        "use_real_price": _runtime_param("use_real_price", PARAM_DEFAULTS["use_real_price"]),
+        "fq_mode": _runtime_param("fq_mode", PARAM_DEFAULTS["fq_mode"]),
+        "history_buffer": _runtime_param("history_buffer", PARAM_DEFAULTS["history_buffer"]),
+        "audit_token": getattr(g, "audit_token", ""),
+        "audit_path": getattr(g, "audit_path", ""),
+    }
+
+
+# ============================================================
+# validate_params — 参数校验
+# ============================================================
+def validate_params(params):
+    """
+    校验参数合法性，不合法时抛出 ValueError。
+
+    校验规则来自技术实现方案 4.1 节参数校验表。
+    """
+    errors = []
+
+    if params["MA_long"] <= 0:
+        errors.append("MA_long must be positive")
+    ma_long_by_etf = params.get("MA_long_by_etf")
+    if ma_long_by_etf is not None:
+        if not isinstance(ma_long_by_etf, (list, tuple)):
+            errors.append("MA_long_by_etf must be a list or tuple when provided")
+        else:
+            if len(ma_long_by_etf) != len(params["etf_pool"]):
+                errors.append("MA_long_by_etf length must match etf_pool")
+            for window in ma_long_by_etf:
+                if not isinstance(window, (int, float)) or window <= 0:
+                    errors.append("MA_long_by_etf values must be positive")
+                    break
+    if abs(params["w20"] + params["w60"] + params["w120"] - 1.0) > 1e-8:
+        errors.append("momentum weights must sum to 1")
+    if params["TopK"] < 1:
+        errors.append("TopK must be >= 1")
+    if not (0 < params["MaxWeight"] <= params["MaxTotalWeight"] <= 1):
+        errors.append("MaxWeight must be in (0, MaxTotalWeight] and MaxTotalWeight <= 1")
+    if not (0 <= params["MinWeight"] <= params["MaxWeight"]):
+        errors.append("MinWeight must be in [0, MaxWeight]")
+    if params["TargetVol"] <= 0:
+        errors.append("TargetVol must be positive")
+    if params["PortfolioVolReliefMode"] not in PORTFOLIO_VOL_RELIEF_MODES:
+        errors.append("PortfolioVolReliefMode must be one of %s" % (PORTFOLIO_VOL_RELIEF_MODES,))
+    for fraction_name in ("GoldVolReliefFraction", "DynamicVolReliefFraction"):
+        value = params[fraction_name]
+        if not (0.0 <= value <= 1.0):
+            errors.append("%s must be in [0.0, 1.0]" % fraction_name)
+    for ratio_name in ("GoldVolReliefMaxRatio", "DynamicVolReliefMaxRatio"):
+        value = params[ratio_name]
+        if value <= 1.0:
+            errors.append("%s must be > 1.0" % ratio_name)
+    for window_name in ("DynamicVolReliefMomentumWindow", "DynamicVolReliefCovWindow"):
+        value = params[window_name]
+        if isinstance(value, bool) or not isinstance(value, int) or value <= 0:
+            errors.append("%s must be a positive integer" % window_name)
+    if params["RSRS_M"] <= 0 or params["RSRS_N"] <= 1:
+        errors.append("RSRS_M must be positive and RSRS_N must be > 1")
+    if not (0 <= params["CrowdStart"] < params["CrowdEnd"] <= 1):
+        errors.append("Crowd thresholds must satisfy 0 <= CrowdStart < CrowdEnd <= 1")
+    for per_etf_name in ("CrowdStart_by_etf", "CrowdEnd_by_etf", "MinCrowdPenalty_by_etf",
+                         "CrowdRetShort_by_etf", "CrowdRetMid_by_etf"):
+        per_etf_val = params.get(per_etf_name)
+        if per_etf_val is not None:
+            if not isinstance(per_etf_val, (list, tuple)):
+                errors.append("%s must be a list or tuple when provided" % per_etf_name)
+            elif len(per_etf_val) != len(params["etf_pool"]):
+                errors.append("%s length must match etf_pool" % per_etf_name)
+    starts_etf = params.get("CrowdStart_by_etf")
+    ends_etf = params.get("CrowdEnd_by_etf")
+    if starts_etf is not None and ends_etf is not None:
+        for idx, (s, e) in enumerate(zip(starts_etf, ends_etf)):
+            if not (0 <= s < e <= 1):
+                errors.append("CrowdStart_by_etf[%d]=%s must satisfy 0 <= start < end <= 1, got end=%s" % (idx, s, e))
+                break
+    elif starts_etf is not None:
+        for idx, s in enumerate(starts_etf):
+            if not (0 <= s < params["CrowdEnd"] <= 1):
+                errors.append("CrowdStart_by_etf[%d]=%s must satisfy 0 <= start < CrowdEnd=%s" % (idx, s, params["CrowdEnd"]))
+                break
+    elif ends_etf is not None:
+        for idx, e in enumerate(ends_etf):
+            if not (params["CrowdStart"] < e <= 1):
+                errors.append("CrowdEnd_by_etf[%d]=%s must satisfy CrowdStart=%s < end <= 1" % (idx, e, params["CrowdStart"]))
+                break
+    if params["MomentumTiltStrength"] < 0:
+        errors.append("MomentumTiltStrength must be >= 0")
+    if not (0 < params["MomentumTiltMin"] <= 1 <= params["MomentumTiltMax"]):
+        errors.append("Momentum tilt bounds must satisfy 0 < min <= 1 <= max")
+    extreme_start = params["MomentumExtremeScoreStart"]
+    if extreme_start is not None and not (0 < extreme_start <= 1):
+        errors.append("MomentumExtremeScoreStart must be None or satisfy 0 < start <= 1")
+    if not (1 <= params["MomentumExtremeTiltCap"] <= params["MomentumTiltMax"]):
+        errors.append("MomentumExtremeTiltCap must satisfy 1 <= cap <= MomentumTiltMax")
+    if not (0 < params["RSRSTiltMin"] <= 1 <= params["RSRSTiltMax"]):
+        errors.append("RSRS tilt bounds must satisfy 0 < min <= 1 <= max")
+    if params["ExecutionTimingMode"] not in EXECUTION_TIMING_MODES:
+        errors.append("ExecutionTimingMode must be one of %s" % (EXECUTION_TIMING_MODES,))
+    if len(params["etf_pool"]) != len(params["etf_names"]):
+        errors.append("etf_pool and etf_names must have the same length")
+    for etf, name in zip(params["etf_pool"], params["etf_names"]):
+        if str(etf) not in str(name):
+            errors.append("etf_names must include JoinQuant security code: %s" % etf)
+
+    if errors:
+        raise ValueError("; ".join(errors))
+
+
+def resolve_ma_long_windows(params):
+    """返回与 etf_pool 对齐的趋势均线窗口。"""
+    ma_long_by_etf = params.get("MA_long_by_etf")
+    if ma_long_by_etf is None:
+        return [params["MA_long"]] * len(params["etf_pool"])
+    return list(ma_long_by_etf)
+
+
+def resolve_crowd_thresholds(params):
+    """返回与 etf_pool 对齐的 (CrowdStart, CrowdEnd, MinCrowdPenalty) 三元组列表。"""
+    n = len(params["etf_pool"])
+    starts = params.get("CrowdStart_by_etf")
+    starts = list(starts) if starts is not None else [params["CrowdStart"]] * n
+    ends = params.get("CrowdEnd_by_etf")
+    ends = list(ends) if ends is not None else [params["CrowdEnd"]] * n
+    mins = params.get("MinCrowdPenalty_by_etf")
+    mins = list(mins) if mins is not None else [params["MinCrowdPenalty"]] * n
+    return list(zip(starts, ends, mins))
+
+
+def resolve_crowd_ret_windows(params):
+    """返回与 etf_pool 对齐的 (CrowdRetShort, CrowdRetMid) 二元组列表。"""
+    n = len(params["etf_pool"])
+    shorts = params.get("CrowdRetShort_by_etf")
+    shorts = list(shorts) if shorts is not None else [params["CrowdRetShort"]] * n
+    mids = params.get("CrowdRetMid_by_etf")
+    mids = list(mids) if mids is not None else [params["CrowdRetMid"]] * n
+    return list(zip(shorts, mids))
+
+
+# ============================================================
+# initialize — 策略初始化
+# ============================================================
+def initialize(context):
+    """
+    由聚宽框架在回测/模拟启动时自动调用一次。
+
+    作用：
+    - 向 g 对象写入全部策略参数
+    - 设置交易费用（场内基金免印花税，佣金万分之一）
+    - 设置固定滑点 0
+    - 注册每周开盘调仓任务
+    """
+    set_parameter(context)
+    validate_params(snapshot_params())
+    write_file(g.audit_path, "", append=False)
+    audit_event("run_start", context, params=snapshot_params())
+    set_option('use_real_price', g.use_real_price)
+    set_option("avoid_future_data", True)
+
+    set_order_cost(
+        OrderCost(
+            open_tax=0,
+            close_tax=0,
+            open_commission=0.0001,
+            close_commission=0.0001,
+            min_commission=0
+        ),
+        type='fund'
+    )
+
+    set_slippage(FixedSlippage(0.0), type='fund')
+
+    if g.ExecutionTimingMode == "baseline":
+        run_weekly(
+            weekly_check,
+            weekday=1,
+            time='open',
+            reference_security='000300.XSHG'
+        )
+    elif g.ExecutionTimingMode == "logic-2-delay-only":
+        run_weekly(
+            prepare_delay_only_rebalance,
+            weekday=1,
+            time='open',
+            reference_security='000300.XSHG'
+        )
+        run_daily(
+            execute_pending_rebalance,
+            time='open',
+            reference_security='000300.XSHG'
+        )
+    elif g.ExecutionTimingMode == "logic-3-live-like":
+        run_weekly(
+            mark_live_like_signal_day,
+            weekday=1,
+            time='open',
+            reference_security='000300.XSHG'
+        )
+        run_daily(
+            execute_live_like_rebalance,
+            time='open',
+            reference_security='000300.XSHG'
+        )
+    else:
+        run_weekly(
+            prepare_weekend_close_rebalance,
+            weekday=-1,
+            time='15:30',
+            force=False,
+        )
+        run_daily(
+            execute_weekend_close_rebalance,
+            time='open',
+            reference_security='000300.XSHG'
+        )
+
+
+def on_strategy_end(context):
+    """Record the final audit marker used by local completeness checks."""
+    portfolio = getattr(context, "portfolio", None)
+    audit_event(
+        "run_end",
+        context,
+        total_value=getattr(portfolio, "total_value", None),
+        cash=getattr(portfolio, "cash", None),
+    )
+
+
+# ============================================================
+# set_parameter — 策略参数集中设置
+# ============================================================
+def set_parameter(context):
+    """
+    将所有策略参数写入 g 全局对象，便于集中管理和回测参数扫描。
+
+    参数类别：资产池、趋势门槛、动量选择、风险平价、RSRS 修正、
+    拥挤度惩罚、组合波动率控制、仓位交易约束。
+    """
+
+    # ---- 资产池 ----
+    g.etf_pool = _copy_runtime_default(PARAM_DEFAULTS["etf_pool"])
+    g.etf_names = load_etf_display_names(g.etf_pool)
+
+    # ---- 趋势门槛 ----
+    g.MA_long = PARAM_DEFAULTS["MA_long"]
+    g.MA_long_by_etf = _copy_runtime_default(PARAM_DEFAULTS["MA_long_by_etf"])
+
+    # ---- 动量选择 ----
+    g.MomShort = PARAM_DEFAULTS["MomShort"]
+    g.MomMid = PARAM_DEFAULTS["MomMid"]
+    g.MomLong = PARAM_DEFAULTS["MomLong"]
+    g.w20 = PARAM_DEFAULTS["w20"]
+    g.w60 = PARAM_DEFAULTS["w60"]
+    g.w120 = PARAM_DEFAULTS["w120"]
+    g.TopK = PARAM_DEFAULTS["TopK"]
+
+    # ---- 风险平价 ----
+    g.VolWindow = PARAM_DEFAULTS["VolWindow"]
+    g.annual_factor = PARAM_DEFAULTS["annual_factor"]
+
+    # ---- RSRS 修正 ----
+    g.RSRS_N = PARAM_DEFAULTS["RSRS_N"]        # 回归窗口
+    g.RSRS_M = PARAM_DEFAULTS["RSRS_M"]        # 标准化窗口
+    g.RSRS_NegativeFullCut = PARAM_DEFAULTS["RSRS_NegativeFullCut"]
+    g.RSRSMinMultiplier = PARAM_DEFAULTS["RSRSMinMultiplier"]
+    g.RSRSMaxMultiplier = PARAM_DEFAULTS["RSRSMaxMultiplier"]
+
+    # ---- 动量倾斜（资产间相对信号） ----
+    g.MomentumTiltStrength = PARAM_DEFAULTS["MomentumTiltStrength"]
+    g.MomentumTiltMin = PARAM_DEFAULTS["MomentumTiltMin"]
+    g.MomentumTiltMax = PARAM_DEFAULTS["MomentumTiltMax"]
+    g.MomentumExtremeScoreStart = PARAM_DEFAULTS["MomentumExtremeScoreStart"]
+    g.MomentumExtremeTiltCap = PARAM_DEFAULTS["MomentumExtremeTiltCap"]
+
+    # ---- RSRS 倾斜（资产间相对信号） ----
+    g.RSRSTiltMin = PARAM_DEFAULTS["RSRSTiltMin"]
+    g.RSRSTiltMax = PARAM_DEFAULTS["RSRSTiltMax"]
+
+    # ---- 拥挤度惩罚 ----
+    g.CrowdWindow = PARAM_DEFAULTS["CrowdWindow"]
+    g.CrowdRetShort = PARAM_DEFAULTS["CrowdRetShort"]
+    g.CrowdRetMid = PARAM_DEFAULTS["CrowdRetMid"]
+    g.AmountMAWindow = PARAM_DEFAULTS["AmountMAWindow"]
+    g.DeviationMAWindow = PARAM_DEFAULTS["DeviationMAWindow"]
+    g.CrowdVolWindow = PARAM_DEFAULTS["CrowdVolWindow"]
+    g.CrowdStart = PARAM_DEFAULTS["CrowdStart"]
+    g.CrowdEnd = PARAM_DEFAULTS["CrowdEnd"]
+    g.MinCrowdPenalty = PARAM_DEFAULTS["MinCrowdPenalty"]
+    g.CrowdStart_by_etf = _copy_runtime_default(PARAM_DEFAULTS["CrowdStart_by_etf"])
+    g.CrowdEnd_by_etf = PARAM_DEFAULTS["CrowdEnd_by_etf"]
+    g.MinCrowdPenalty_by_etf = PARAM_DEFAULTS["MinCrowdPenalty_by_etf"]
+    g.CrowdRetShort_by_etf = PARAM_DEFAULTS["CrowdRetShort_by_etf"]
+    g.CrowdRetMid_by_etf = PARAM_DEFAULTS["CrowdRetMid_by_etf"]
+
+    # ---- 组合波动率控制 ----
+    g.PortfolioVolWindow = PARAM_DEFAULTS["PortfolioVolWindow"]
+    g.TargetVol = PARAM_DEFAULTS["TargetVol"]
+    g.MaxPortfolioVolScale = PARAM_DEFAULTS["MaxPortfolioVolScale"]
+    g.PortfolioVolReliefMode = PARAM_DEFAULTS["PortfolioVolReliefMode"]
+    g.GoldVolReliefFraction = PARAM_DEFAULTS["GoldVolReliefFraction"]
+    g.GoldVolReliefMaxRatio = PARAM_DEFAULTS["GoldVolReliefMaxRatio"]
+    g.DynamicVolReliefFraction = PARAM_DEFAULTS["DynamicVolReliefFraction"]
+    g.DynamicVolReliefMaxRatio = PARAM_DEFAULTS["DynamicVolReliefMaxRatio"]
+    g.DynamicVolReliefMomentumWindow = PARAM_DEFAULTS["DynamicVolReliefMomentumWindow"]
+    g.DynamicVolReliefCovWindow = PARAM_DEFAULTS["DynamicVolReliefCovWindow"]
+
+    # ---- 仓位与交易约束 ----
+    g.MaxWeight = PARAM_DEFAULTS["MaxWeight"]
+    g.MinWeight = PARAM_DEFAULTS["MinWeight"]
+    g.RebalanceThreshold = PARAM_DEFAULTS["RebalanceThreshold"]
+    g.MaxTotalWeight = PARAM_DEFAULTS["MaxTotalWeight"]
+    g.ExecutionTimingMode = DEFAULT_EXECUTION_TIMING_MODE
+
+    # ---- 数据与基准 ----
+    # 复权模式：fq='pre' 在 FQ A/B 对比测试中证实对场内基金会
+    # 导致 get_price 返回空数据（2025-04~2026-04 区间复现）。
+    # 故默认关闭复权。参考 FQ comparison: R2/backtest_runs/*/report/fq-comparison.md
+    g.use_real_price = PARAM_DEFAULTS["use_real_price"]
+    g.fq_mode = PARAM_DEFAULTS["fq_mode"]        # 不复权（场内基金默认）
+    ma_long_max = max(g.MA_long_by_etf) if g.MA_long_by_etf else g.MA_long
+    g.live_days = max(
+        ma_long_max, g.MomLong, g.RSRS_M,
+        g.CrowdWindow, g.PortfolioVolWindow
+    ) + 50
+    g.history_buffer = PARAM_DEFAULTS["history_buffer"]
+    g.benchmark = PARAM_DEFAULTS["benchmark"]
+    g.audit_token = JQ_AUTO_AUDIT_TOKEN
+    g.audit_path = "%s/%s.jsonl" % (JQ_AUTO_AUDIT_DIR, g.audit_token)
+    g.audit_seq = 0
+    g.pending_rebalances = []
+    g.pending_live_like_signal_days = []
+
+
+# ============================================================
+# _log_step — 调仓中间量诊断日志
+# ============================================================
+def _log_step(name, cn_name, pool, values, fmt=".4f", etf_names=None):
+    """
+    以 "[中文名] name: 基金名(聚宽代码)=value" 格式逐只打印调仓中间量，便于云端回测诊断。
+
+    不在本地单测中验证日志格式，只保证聚宽云端 log.info 可输出。
+    """
+    labels = build_etf_display_names(pool, etf_names)
+    parts = ["%s=%%s" % label for label in labels]
+    template = "[%s] %s: " % (cn_name, name) + ", ".join(parts)
+    formatted = tuple(format(v, fmt) for v in values)
+    log.info(template, *formatted)
+
+
+# ============================================================
+# compose_raw_weights — 权重合成
+# ============================================================
+def compose_raw_weights(tilted_weights, trend_gates, crowd_penalties):
+    """
+    合成各模块输出为 RawWeight。
+
+    动量与 RSRS 已经体现在 TiltedWeight 中，不再作为独立乘数。
+    TrendGate 仍保留作为二次保护。不重新归一化。
+    """
+    n = len(tilted_weights)
+    raw = np.zeros(n)
+    for i in range(n):
+        raw[i] = (
+            tilted_weights[i]
+            * trend_gates[i]
+            * crowd_penalties[i]
+        )
+    return raw
+
+
+# ============================================================
+# weekly_check — 周频调仓主函数
+# ============================================================
+def _as_date(value):
+    """把聚宽日期、pandas 日期或字符串统一成 date。"""
+    if value is None:
+        return None
+    if isinstance(value, datetime):
+        return value.date()
+    if isinstance(value, date):
+        return value
+    try:
+        return pd.Timestamp(value).date()
+    except Exception:
+        return value
+
+
+def _context_trade_date(context):
+    """返回当前任务对应的自然日。"""
+    return _as_date(getattr(context, "current_dt", None))
+
+
+def _same_iso_week(left, right):
+    left = _as_date(left)
+    right = _as_date(right)
+    if left is None or right is None:
+        return False
+    return left.isocalendar()[:2] == right.isocalendar()[:2]
+
+
+def _float_list(values):
+    try:
+        if hasattr(values, "tolist"):
+            values = values.tolist()
+    except Exception:
+        pass
+    return [float(value) for value in list(values or [])]
+
+
+def _weekend_close_batch_id(signal_date):
+    token = str(getattr(g, "audit_token", "manual")).replace("/", "_").replace("\\", "_")
+    return "%s-weekend-close-%s" % (token, signal_date)
+
+
+def _enrich_weekend_close_plan(context, plan, signal_date):
+    weights = _float_list(plan.get("final_weights"))
+    portfolio = getattr(context, "portfolio", None)
+    total_value = getattr(portfolio, "total_value", None)
+    plan["final_weights"] = weights
+    plan["target_weights"] = weights
+    plan["target_values"] = [total_value * weight for weight in weights] if total_value is not None else []
+    plan["portfolio_total_value"] = total_value
+    plan["signal_date"] = signal_date
+    plan["asof_date"] = signal_date
+    plan["prepared_date"] = signal_date
+    plan["trade_date"] = plan.get("trade_date")
+    plan["batch_id"] = plan.get("batch_id") or _weekend_close_batch_id(signal_date)
+    plan["plan_cached"] = True
+    plan["signal_notice_sent"] = False
+    return plan
+
+
+def _report_signal_plan(plan):
+    if FeishuRelayTools is None:
+        return False
+    reporter = getattr(FeishuRelayTools, "report_signal_plan", None)
+    if not callable(reporter):
+        return False
+    try:
+        return bool(reporter(plan))
+    except Exception as exc:
+        log.warning("feishu signal notice failed: %s", exc)
+        return False
+
+
+def _suppress_execution_notice(batch_id):
+    if FeishuRelayTools is None:
+        return False
+    suppress = getattr(FeishuRelayTools, "suppress_execution_notice", None)
+    if not callable(suppress):
+        return False
+    try:
+        suppress(batch_id=batch_id, reason="signal_notice_already_sent")
+        return True
+    except Exception as exc:
+        log.warning("feishu execution notice suppress failed: %s", exc)
+        return False
+
+
+def _resume_execution_notice():
+    if FeishuRelayTools is None:
+        return
+    resume = getattr(FeishuRelayTools, "resume_execution_notice", None)
+    if not callable(resume):
+        return
+    try:
+        resume()
+    except Exception as exc:
+        log.warning("feishu execution notice resume failed: %s", exc)
+
+
+def build_rebalance_plan(context, asof_date=None):
+    """生成一次调仓所需的完整信号快照，但不直接下单。
+
+    流程：TrendGate → RPWeight → MomentumScore → MomentumTilt
+         → RSRSTilt → TiltedWeight → CrowdPenalty
+         → PortfolioVolScale → FinalWeight
+    """
+    params = snapshot_params()
+    pool = params["etf_pool"]
+    etf_names = params["etf_names"]
+
+    # 1. 拉取历史数据
+    if asof_date is not None:
+        asof_date = _as_date(asof_date)
+    else:
+        asof_date = getattr(context, "previous_date", None)
+    prices = get_history_data(context, pool, params, asof_date=asof_date)
+
+    # 2. 计算趋势门槛
+    trend_gates = compute_trend_gates(prices, pool, params)
+    _log_step("TrendGate", "趋势门槛", pool, trend_gates, fmt=".0f", etf_names=etf_names)
+
+    # 3. 风险平价基础权重（所有趋势成立资产参与）
+    active_mask = [gate > 0 for gate in trend_gates]
+    rp_weights = compute_rp_weights(prices, pool, active_mask, params)
+    _log_step("RPWeight", "风险平价权重", pool, rp_weights, fmt=".4f", etf_names=etf_names)
+
+    # 4. 计算动量分数
+    momentum_scores = compute_momentum_scores(prices, pool, trend_gates, params)
+    _log_step("MomentumScore", "动量分数", pool, momentum_scores, fmt=".4f", etf_names=etf_names)
+
+    # 5. 动量倾斜乘数
+    momentum_tilts = compute_momentum_tilt_multipliers(momentum_scores, trend_gates, params)
+    _log_step("MomentumTilt", "动量倾斜乘数", pool, momentum_tilts, fmt=".4f", etf_names=etf_names)
+
+    # 6. RSRS 倾斜乘数
+    rsrs_tilts = compute_rsrs_tilt_multipliers(prices, pool, trend_gates, params)
+    _log_step("RSRSTilt", "RSRS倾斜乘数", pool, rsrs_tilts, fmt=".4f", etf_names=etf_names)
+
+    # 7. 合成倾斜权重（动量 + RSRS 同时参与相对倾斜，活跃资产内重新归一化）
+    tilted_weights = apply_relative_tilts(rp_weights, trend_gates, momentum_tilts, rsrs_tilts)
+    _log_step("TiltedWeight", "倾斜合成权重", pool, tilted_weights, fmt=".4f", etf_names=etf_names)
+
+    # 8. 拥挤度线性惩罚乘数
+    crowd_penalties = compute_crowd_penalties(prices, pool, params)
+    _log_step("CrowdPenalty", "拥挤度惩罚", pool, crowd_penalties, fmt=".4f", etf_names=etf_names)
+
+    # 9. 合成 RawWeight（不重新归一化）
+    raw_weights = compose_raw_weights(tilted_weights, trend_gates, crowd_penalties)
+
+    # 10. 组合波动率缩放
+    portfolio_vol_asset_scales, portfolio_vol_meta = compute_portfolio_vol_asset_scales(
+        prices, pool, raw_weights, params
+    )
+    portfolio_vol_scale = portfolio_vol_meta["base_scale"]
+    log.info("[组合波动率缩放] PortfolioVolScale=%.4f", portfolio_vol_scale)
+
+    # 11. 最终权重
+    final_weights = raw_weights * portfolio_vol_asset_scales
+    _log_step("FinalWeight", "最终权重", pool, final_weights, fmt=".4f", etf_names=etf_names)
+
+    # 12. 应用交易约束
+    final_weights_before_constraints = np.copy(final_weights)
+    final_weights = apply_weight_constraints(final_weights, params)
+    audit_event(
+        "rebalance_signals",
+        context,
+        pool=pool,
+        etf_names=etf_names,
+        params=params,
+        trend_gates=trend_gates,
+        rp_weights=rp_weights,
+        momentum_scores=momentum_scores,
+        momentum_tilts=momentum_tilts,
+        rsrs_tilts=rsrs_tilts,
+        tilted_weights=tilted_weights,
+        crowd_penalties=crowd_penalties,
+        raw_weights=raw_weights,
+        portfolio_vol_scale=portfolio_vol_scale,
+        portfolio_vol_relief_mode=portfolio_vol_meta["mode"],
+        portfolio_vol_ratio=portfolio_vol_meta["vol_ratio"],
+        portfolio_vol_base_scale=portfolio_vol_meta["base_scale"],
+        portfolio_vol_asset_scales=portfolio_vol_asset_scales,
+        portfolio_vol_relief_asset=portfolio_vol_meta["relief_asset"],
+        portfolio_vol_relief_weight=portfolio_vol_meta["relief_weight"],
+        portfolio_vol_relief_reason=portfolio_vol_meta["reason"],
+        final_weights_before_constraints=final_weights_before_constraints,
+        final_weights=final_weights,
+        execution_timing_mode=params["ExecutionTimingMode"],
+        asof_date=asof_date,
+        trade_date=_context_trade_date(context),
+    )
+
+    return {
+        "pool": pool,
+        "final_weights": final_weights,
+        "params": params,
+        "asof_date": asof_date,
+        "prepared_date": _context_trade_date(context),
+    }
+
+
+def weekly_check(context):
+    """每周开盘时生成信号并立即执行调仓。"""
+    plan = build_rebalance_plan(context)
+    execute_rebalance(context, plan["pool"], plan["final_weights"], plan["params"])
+
+
+def prepare_delay_only_rebalance(context):
+    """按 baseline 口径先生成信号，延后到下一交易日开盘执行。"""
+    plan = build_rebalance_plan(context)
+    g.pending_rebalances.append(plan)
+    audit_event(
+        "rebalance_prepared",
+        context,
+        execution_timing_mode=plan["params"]["ExecutionTimingMode"],
+        asof_date=plan["asof_date"],
+        prepared_date=plan["prepared_date"],
+        final_weights=plan["final_weights"],
+    )
+
+
+def execute_pending_rebalance(context):
+    """执行 logic-2 中已缓存、且至少延后一交易日的调仓。"""
+    queue = getattr(g, "pending_rebalances", [])
+    if not queue:
+        return
+
+    pending = queue[0]
+    trade_date = _context_trade_date(context)
+    prepared_date = pending.get("prepared_date")
+    if trade_date is None or prepared_date is None or trade_date <= prepared_date:
+        audit_event(
+            "pending_rebalance_wait",
+            context,
+            execution_timing_mode=pending["params"]["ExecutionTimingMode"],
+            asof_date=pending.get("asof_date"),
+            prepared_date=prepared_date,
+            trade_date=trade_date,
+        )
+        return
+
+    audit_event(
+        "pending_rebalance_execute",
+        context,
+        execution_timing_mode=pending["params"]["ExecutionTimingMode"],
+        asof_date=pending.get("asof_date"),
+        prepared_date=prepared_date,
+        trade_date=trade_date,
+        final_weights=pending["final_weights"],
+    )
+    execute_rebalance(context, pending["pool"], pending["final_weights"], pending["params"])
+    g.pending_rebalances.pop(0)
+
+
+def mark_live_like_signal_day(context):
+    """记录本周首个交易日，供下一交易日开盘生成并执行 logic-3 信号。"""
+    signal_date = _context_trade_date(context)
+    g.pending_live_like_signal_days.append(signal_date)
+    audit_event(
+        "live_like_signal_marked",
+        context,
+        execution_timing_mode=snapshot_params()["ExecutionTimingMode"],
+        signal_date=signal_date,
+    )
+
+
+def execute_live_like_rebalance(context):
+    """在首个交易日之后的下一交易日开盘，生成并执行 logic-3 信号。"""
+    queue = getattr(g, "pending_live_like_signal_days", [])
+    if not queue:
+        return
+
+    signal_date = queue[0]
+    trade_date = _context_trade_date(context)
+    if trade_date is None or signal_date is None or trade_date <= signal_date:
+        audit_event(
+            "live_like_wait",
+            context,
+            execution_timing_mode=snapshot_params()["ExecutionTimingMode"],
+            signal_date=signal_date,
+            trade_date=trade_date,
+        )
+        return
+
+    asof_date = getattr(context, "previous_date", None)
+    if asof_date != signal_date:
+        audit_event(
+            "live_like_skip",
+            context,
+            execution_timing_mode=snapshot_params()["ExecutionTimingMode"],
+            signal_date=signal_date,
+            asof_date=asof_date,
+            trade_date=trade_date,
+            reason="previous_date_not_signal_date",
+        )
+        queue.pop(0)
+        return
+
+    audit_event(
+        "live_like_rebalance_execute",
+        context,
+        execution_timing_mode=snapshot_params()["ExecutionTimingMode"],
+        signal_date=signal_date,
+        asof_date=asof_date,
+        trade_date=trade_date,
+    )
+    weekly_check(context)
+    queue.pop(0)
+
+
+def prepare_weekend_close_rebalance(context):
+    """收盘后生成候选信号 plan，次开盘跨周时执行。"""
+    signal_date = _context_trade_date(context)
+    params = snapshot_params()
+    if signal_date is None:
+        audit_event(
+            "weekend_close_signal_skip",
+            context,
+            execution_timing_mode=params["ExecutionTimingMode"],
+            signal_date=signal_date,
+            reason="signal_date_unavailable",
+        )
+        return
+
+    plan = build_rebalance_plan(context, asof_date=signal_date)
+    plan = _enrich_weekend_close_plan(context, plan, signal_date)
+    plan["signal_notice_sent"] = _report_signal_plan(plan)
+    g.pending_rebalances = [plan]
+    audit_event(
+        "weekend_close_plan_cached",
+        context,
+        execution_timing_mode=plan["params"]["ExecutionTimingMode"],
+        signal_date=signal_date,
+        asof_date=signal_date,
+        batch_id=plan["batch_id"],
+        target_weights=plan["target_weights"],
+        target_values=plan["target_values"],
+        signal_notice_sent=plan["signal_notice_sent"],
+        plan_cached=True,
+        final_weights=plan["final_weights"],
+    )
+
+
+def execute_weekend_close_rebalance(context):
+    """次交易日开盘执行已缓存的收盘信号 plan，不重新计算信号。"""
+    queue = getattr(g, "pending_rebalances", [])
+    if not queue:
+        return
+
+    pending = queue[0]
+    trade_date = _context_trade_date(context)
+    signal_date = pending.get("signal_date")
+    if trade_date is None or signal_date is None:
+        audit_event(
+            "weekend_close_execute_wait",
+            context,
+            execution_timing_mode=pending["params"]["ExecutionTimingMode"],
+            signal_date=signal_date,
+            asof_date=pending.get("asof_date"),
+            trade_date=trade_date,
+        )
+        return
+    if _same_iso_week(signal_date, trade_date):
+        audit_event(
+            "weekend_close_plan_discarded",
+            context,
+            execution_timing_mode=pending["params"]["ExecutionTimingMode"],
+            signal_date=signal_date,
+            asof_date=pending.get("asof_date"),
+            trade_date=trade_date,
+            reason="not_last_trade_day_of_week",
+        )
+        g.pending_rebalances.pop(0)
+        return
+
+    pending["trade_date"] = trade_date
+    suppress_reason = "signal_notice_already_sent" if pending.get("signal_notice_sent") else ""
+    notice_suppressed = _suppress_execution_notice(pending.get("batch_id")) if suppress_reason else False
+    audit_event(
+        "weekend_close_execute",
+        context,
+        execution_timing_mode=pending["params"]["ExecutionTimingMode"],
+        signal_date=signal_date,
+        asof_date=pending.get("asof_date"),
+        batch_id=pending.get("batch_id"),
+        trade_date=trade_date,
+        execution_order_called=True,
+        execution_notice_suppressed=notice_suppressed,
+        suppress_reason=suppress_reason if notice_suppressed else "",
+        final_weights=pending["final_weights"],
+    )
+    try:
+        execute_rebalance(context, pending["pool"], pending["final_weights"], pending["params"])
+    finally:
+        if notice_suppressed:
+            _resume_execution_notice()
+    g.pending_rebalances.pop(0)
+
+
+# ============================================================
+# normalize_field_frame — 数据返回结构归一化
+# ============================================================
+def normalize_field_frame(raw, field, pool):
+    """
+    将 get_price 返回的单 ETF 结果归一化，辅助测试与本地诊断。
+
+    处理规则：
+      - None 或空 DataFrame → 返回 columns=pool 的空 DataFrame
+      - 普通 DataFrame → reindex(columns=pool) 补全缺列
+    """
+    if raw is None:
+        return pd.DataFrame(columns=pool)
+    if not isinstance(raw, pd.DataFrame):
+        return pd.DataFrame(columns=pool)
+    if len(raw) == 0:
+        return pd.DataFrame(columns=pool)
+
+    raw = raw.reindex(columns=pool)
+    return raw.dropna(how='all')
+
+
+# ============================================================
+# compute_history_count — 计算所需历史数据长度
+# ============================================================
+def compute_history_count(params):
+    """
+    按模块显式计算所需历史数据长度。
+
+    说明：
+      - 动量和收益率类计算需要多取 1 日
+      - RSRS 至少需要 RSRS_M + RSRS_N - 1
+      - buffer 用于容忍停牌、缺失值、上市初期数据不足
+    """
+    requirements = [
+        max(resolve_ma_long_windows(params)),
+        max(params["MomShort"], params["MomMid"], params["MomLong"]) + 1,
+        params["VolWindow"] + 1,
+        params["RSRS_M"] + params["RSRS_N"] - 1,
+        params["CrowdWindow"],
+        params["PortfolioVolWindow"] + 1,
+    ]
+    return max(requirements) + params.get("history_buffer", 50)
+
+
+# ============================================================
+# fetch_field + get_history_data — 拉取历史行情数据
+# ============================================================
+def fetch_field(pool, field, count, params, end_date=None):
+    """
+    逐 ETF 拉取单字段数据，返回 DataFrame（index=日期, columns=ETF代码）。
+
+    单标的 + panel=False 在聚宽云端稳定返回 DataFrame（columns=字段名），
+    多标的传入 panel=False 可能仍返回 Panel，因此改为逐只拉取后手工组装。
+
+    end_date: 历史数据截止日期。开盘调仓时需传入 context.previous_date
+              以避免当日收盘价未来数据。
+    """
+    series_map = {}
+    for etf in pool:
+        df = get_price(
+            etf,
+            count=count,
+            end_date=end_date,
+            frequency='daily',
+            fields=[field],
+            skip_paused=True,
+            fq=params["fq_mode"],
+            panel=False,
+        )
+        if df is not None and len(df) > 0:
+            series_map[etf] = df[field]
+
+    if not series_map:
+        return pd.DataFrame(columns=pool)
+
+    result = pd.DataFrame(series_map)
+    result = result.reindex(columns=pool)
+    return result.dropna(how='all')
+
+
+def get_history_data(context, pool, params, asof_date=None):
+    """
+    拉取足够长的历史 OHLC + 成交额数据，并预计算日收益率。
+
+    返回 dict：
+      close/high/low/amount: DataFrame（index=日期, columns=ETF代码）
+      close_ret: DataFrame（index=日期, columns=ETF代码），close 的 pct_change()
+    """
+    needed = compute_history_count(params)
+    history_end_date = asof_date if asof_date is not None else getattr(context, "previous_date", None)
+
+    prices = {}
+    prices['close'] = fetch_field(pool, 'close', needed, params, end_date=history_end_date)
+    prices['high'] = fetch_field(pool, 'high', needed, params, end_date=history_end_date)
+    prices['low'] = fetch_field(pool, 'low', needed, params, end_date=history_end_date)
+    prices['amount'] = fetch_field(pool, 'money', needed, params, end_date=history_end_date)
+
+    # 预计算日收益率，下游风险平价和组合波动率复用同一份
+    prices['close_ret'] = prices['close'].pct_change()
+
+    # 数据新鲜度日志：确保历史数据不晚于 context.previous_date
+    close_df = prices['close']
+    last_dt = close_df.index[-1] if len(close_df) else None
+    log.info("history end_date=%s, asof_date=%s", last_dt, history_end_date)
+
+    return prices
+
+
+# ============================================================
+# compute_trend_gates — 趋势门槛（硬过滤）
+# ============================================================
+def compute_trend_gates(prices, pool, params):
+    """
+    使用趋势均线判断方向，支持按 ETF 分别设置窗口。
+
+    返回: list[float]，1.0 表示通过，0.0 表示剔除
+    """
+    close = prices['close']
+    ma_windows = resolve_ma_long_windows(params)
+
+    gates = np.zeros(len(pool))
+    for i, etf in enumerate(pool):
+        if etf not in close.columns:
+            continue
+        ma_window = ma_windows[i]
+        series = close[etf].dropna()
+        if len(series) < ma_window:
+            continue
+        ma = series.iloc[-ma_window:].mean()
+        current_close = series.iloc[-1]
+        if current_close > ma:
+            gates[i] = 1.0
+    return gates
+
+
+# ============================================================
+# compute_momentum_scores — 多周期排名动量分数
+# ============================================================
+def compute_momentum_scores(prices, pool, trend_gates, params):
+    """
+    在趋势成立的资产中，计算多周期排名动量分数。
+
+    对 close DataFrame 批量取各周期终点收益，再用 rank(pct=True)
+    在截面上生成 0~1 排名分数，最后按权重线性组合。
+
+    返回: np.array，未通过趋势门槛的资产分数为 0
+    """
+    close = prices['close']
+    n = len(pool)
+    scores = np.zeros(n)
+
+    windows = [params["MomShort"], params["MomMid"], params["MomLong"]]
+    period_weights = [params["w20"], params["w60"], params["w120"]]
+
+    active_indices = [i for i in range(n) if trend_gates[i] > 0]
+    if not active_indices:
+        return scores
+
+    active_pool = [pool[i] for i in active_indices if pool[i] in close.columns]
+    if not active_pool:
+        return scores
+    active_close = close[active_pool]
+    if len(active_close) <= max(windows):
+        return scores
+
+    for j, w in enumerate(windows):
+        if len(active_close) <= w:
+            continue
+        latest = active_close.iloc[-1]
+        past = active_close.iloc[-(w + 1)]
+        period_ret = latest / past - 1  # pd.Series, index=ETF代码
+
+        # rank(pct=True) 将收益率映射到 [0, 1]，收益率越高排名越接近 1
+        ranks = period_ret.rank(pct=True).fillna(0.0)
+
+        for idx_pos, active_i in enumerate(active_indices):
+            etf_code = pool[active_i]
+            scores[active_i] += period_weights[j] * float(ranks.get(etf_code, 0.0))
+
+    return scores
+
+
+# ============================================================
+# select_topk — TopK 入选
+# ============================================================
+def select_topk(momentum_scores, trend_gates, params):
+    """
+    在趋势成立资产中按动量分数从高到低选择前 TopK 只。
+
+    返回: list[bool]，入选为 True
+    """
+    n = len(momentum_scores)
+    selected = [False] * n
+
+    active = [(i, momentum_scores[i]) for i in range(n) if trend_gates[i] > 0]
+    active.sort(key=lambda x: x[1], reverse=True)
+
+    k = min(params["TopK"], len(active))
+    for idx, _ in active[:k]:
+        selected[idx] = True
+
+    return selected
+
+
+# ============================================================
+# compute_rp_weights — 逆波动率风险平价
+# ============================================================
+def compute_rp_weights(prices, pool, active_mask, params):
+    """
+    对活跃资产计算逆波动率风险平价权重。
+
+    所有趋势成立资产均参与基础权重计算，不再受 TopK 限制。
+    使用 get_history_data 预计算的 close_ret，避免重复 pct_change()。
+
+    返回: np.array
+    """
+    close_ret = prices['close_ret']
+    n = len(pool)
+    vol_window = params["VolWindow"]
+    annual_factor = params["annual_factor"]
+
+    weights = np.zeros(n)
+    active_indices = [i for i in range(n) if active_mask[i]]
+
+    if not active_indices:
+        return weights
+
+    vols = np.zeros(n)
+    for i in active_indices:
+        etf = pool[i]
+        if etf not in close_ret.columns:
+            continue
+        daily_ret = close_ret[etf].dropna().iloc[-vol_window:]
+        if len(daily_ret) < 5:
+            vols[i] = 1.0
+        else:
+            vols[i] = daily_ret.std() * np.sqrt(annual_factor)
+            if vols[i] < 1e-8:
+                vols[i] = 1e-8
+
+    inverse_vols = np.zeros(n)
+    for i in active_indices:
+        if vols[i] > 0:
+            inverse_vols[i] = 1.0 / vols[i]
+
+    total_inv_vol = inverse_vols.sum()
+    if total_inv_vol > 0:
+        weights = inverse_vols / total_inv_vol
+
+    return weights
+
+
+# ============================================================
+# compute_rsrs_multipliers — RSRS 线性修正乘数
+# ============================================================
+def compute_rsrs_multipliers(prices, pool, params):
+    """
+    对每只 ETF 计算 RSRS 截断线性乘数（旧接口，保留兼容）。
+
+    委托 compute_rsrs_adjusted_scores 获取原始信号，
+    再按旧公式 clip(1 + RSRS_Adj / NegativeFullCut, Min, Max)。
+
+    只减仓，不加仓。
+    """
+    rsrs_adj = compute_rsrs_adjusted_scores(prices, pool, params)
+    full_cut = params["RSRS_NegativeFullCut"]
+    n = len(pool)
+
+    multipliers = np.ones(n)
+    for i in range(n):
+        raw_mult = 1.0 + rsrs_adj[i] / full_cut
+        multipliers[i] = np.clip(raw_mult, params["RSRSMinMultiplier"], params["RSRSMaxMultiplier"])
+
+    return multipliers
+
+
+# ============================================================
+# compute_rsrs_adjusted_scores — RSRS 原始结构信号
+# ============================================================
+def compute_rsrs_adjusted_scores(prices, pool, params):
+    """
+    计算每只 ETF 的 RSRS 原始调整信号：RSRSAdj_i = RSRS_Z_i × R2_i。
+
+    返回: np.array，数据不足时对应位置为 0。
+    """
+    high = prices['high']
+    low = prices['low']
+    n = len(pool)
+
+    N = params["RSRS_N"]
+    M = params["RSRS_M"]
+
+    scores = np.zeros(n)
+
+    for i, etf in enumerate(pool):
+        if etf not in high.columns or etf not in low.columns:
+            continue
+        h = high[etf].dropna()
+        l = low[etf].dropna()
+
+        common_idx = h.index.intersection(l.index)
+        h = h.loc[common_idx]
+        l = l.loc[common_idx]
+
+        min_len = M + N - 1
+        if len(h) < min_len:
+            continue
+
+        h_roll = h.rolling(N)
+        l_roll = l.rolling(N)
+        cov_vals = h_roll.cov(l).dropna().values
+        var_l_vals = l_roll.var().dropna().values
+        var_h_vals = h_roll.var().dropna().values
+
+        betas = cov_vals / var_l_vals
+        r2s = cov_vals ** 2 / (var_h_vals * var_l_vals)
+
+        bad = (
+            (var_l_vals < 1e-10) | (var_h_vals < 1e-10)
+            | (~np.isfinite(betas)) | (~np.isfinite(r2s))
+        )
+        betas[bad] = 1.0
+        r2s[bad] = 0.0
+
+        if len(betas) < M:
+            continue
+
+        beta_series = betas[-M:]
+        mean_beta = np.mean(beta_series)
+        std_beta = np.std(beta_series)
+
+        if std_beta < 1e-10:
+            rsrs_z = 0.0
+        else:
+            rsrs_z = (beta_series[-1] - mean_beta) / std_beta
+
+        latest_r2 = r2s[-1]
+        scores[i] = rsrs_z * latest_r2
+
+    return scores
+
+
+# ============================================================
+# compute_momentum_tilt_multipliers — 动量相对倾斜乘数
+# ============================================================
+def compute_momentum_tilt_multipliers(momentum_scores, trend_gates, params):
+    """
+    将动量分数转换为资产间相对倾斜乘数。
+
+    活跃资产围绕均值上下倾斜，非活跃资产返回 0。
+    倾斜公式：clip(1 + strength × (score_i - mean_active), min, max)
+    若启用极端高动量弱化，则 score_i 达到阈值后再将高位倾斜压到 cap。
+    """
+    n = len(momentum_scores)
+    tilts = np.zeros(n)
+
+    active_indices = [i for i in range(n) if trend_gates[i] > 0]
+    if not active_indices:
+        return tilts
+
+    active_scores = momentum_scores[active_indices]
+    mean_score = np.mean(active_scores)
+
+    strength = params["MomentumTiltStrength"]
+    tilt_min = params["MomentumTiltMin"]
+    tilt_max = params["MomentumTiltMax"]
+    extreme_start = params["MomentumExtremeScoreStart"]
+    extreme_cap = params["MomentumExtremeTiltCap"]
+
+    for i in active_indices:
+        edge = momentum_scores[i] - mean_score
+        raw_tilt = 1.0 + strength * edge
+        tilt = np.clip(raw_tilt, tilt_min, tilt_max)
+        if extreme_start is not None and momentum_scores[i] >= extreme_start:
+            tilt = min(tilt, extreme_cap)
+        tilts[i] = tilt
+
+    return tilts
+
+
+# ============================================================
+# compute_rsrs_tilt_multipliers — RSRS 相对倾斜乘数
+# ============================================================
+def compute_rsrs_tilt_multipliers(prices, pool, trend_gates, params):
+    """
+    计算 RSRS 原始结构信号，并转换为资产间相对倾斜乘数。
+
+    活跃资产围绕均值上下倾斜，非活跃资产返回 0。
+    倾斜公式：clip(1 + (RSRSAdj_i - mean_active) / NegativeFullCut, min, max)
+    """
+    rsrs_adj = compute_rsrs_adjusted_scores(prices, pool, params)
+    n = len(pool)
+    tilts = np.zeros(n)
+
+    active_indices = [i for i in range(n) if trend_gates[i] > 0]
+    if not active_indices:
+        return tilts
+
+    active_adj = rsrs_adj[active_indices]
+    mean_adj = np.mean(active_adj)
+
+    full_cut = params["RSRS_NegativeFullCut"]
+    tilt_min = params["RSRSTiltMin"]
+    tilt_max = params["RSRSTiltMax"]
+
+    for i in active_indices:
+        edge = rsrs_adj[i] - mean_adj
+        raw_tilt = 1.0 + edge / full_cut
+        tilts[i] = np.clip(raw_tilt, tilt_min, tilt_max)
+
+    return tilts
+
+
+# ============================================================
+# apply_relative_tilts — 倾斜权重合成与归一化
+# ============================================================
+def apply_relative_tilts(rp_weights, trend_gates, momentum_tilts, rsrs_tilts):
+    """
+    将风险平价基础权重、动量倾斜和 RSRS 倾斜合成，并在活跃资产内归一化。
+
+    tilted_raw_i = RPWeight_i × MomentumTilt_i × RSRSTilt_i
+    归一化到 sum(RPWeight_active)，非活跃资产权重为 0。
+    """
+    n = len(rp_weights)
+    tilted = np.zeros(n)
+
+    active_indices = [i for i in range(n) if trend_gates[i] > 0 and rp_weights[i] > 0]
+    if not active_indices:
+        return tilted
+
+    tilted_raw = np.zeros(n)
+    for i in active_indices:
+        tilted_raw[i] = rp_weights[i] * momentum_tilts[i] * rsrs_tilts[i]
+
+    total_raw = tilted_raw[active_indices].sum()
+    base_total = rp_weights[active_indices].sum()
+
+    if total_raw <= 0 or base_total <= 0:
+        return np.copy(rp_weights)
+
+    for i in active_indices:
+        tilted[i] = tilted_raw[i] / total_raw * base_total
+
+    return tilted
+
+
+# ============================================================
+# compute_crowd_penalties — 拥挤度线性惩罚乘数
+# ============================================================
+def compute_crowd_penalties(prices, pool, params):
+    """
+    对每只 ETF 计算拥挤度线性惩罚乘数。
+
+    先在 DataFrame 级批量计算五类指标（ret20/ret60/amt_ma20/deviation/vol20），
+    再逐 ETF 取最后一行做分位排名，减少 Python 层逐列 rolling/pct_change 开销。
+
+    只减仓，不加仓。
+
+    返回: np.array
+    """
+    close = prices['close']
+    amount = prices['amount']
+    n = len(pool)
+
+    crowd_window = params["CrowdWindow"]
+    thresholds = resolve_crowd_thresholds(params)    # [(start, end, min_penalty), ...]
+    ret_windows = resolve_crowd_ret_windows(params)  # [(short, mid), ...]
+
+    penalties = np.ones(n)
+
+    # 过滤数据不足的 ETF
+    eligible_etfs = []
+    for i, etf in enumerate(pool):
+        if etf in close.columns and len(close[etf].dropna()) >= crowd_window:
+            eligible_etfs.append(etf)
+        else:
+            penalties[i] = 1.0
+
+    if not eligible_etfs:
+        return penalties
+
+    # ---- DataFrame 级批量计算：一次算完所有 ETF 的指标 ----
+    close_recent = close[eligible_etfs].iloc[-crowd_window:]
+
+    # 1-2) 短/中期涨幅（按 per-ETF 窗口预计算，避免重复 shift）
+    ret_short_map = {}
+    ret_mid_map = {}
+    for i, etf in enumerate(pool):
+        if etf not in eligible_etfs:
+            continue
+        short_w, mid_w = ret_windows[i]
+        if short_w not in ret_short_map:
+            ret_short_map[short_w] = close_recent / close_recent.shift(short_w) - 1
+        if mid_w not in ret_mid_map:
+            ret_mid_map[mid_w] = close_recent / close_recent.shift(mid_w) - 1
+
+    # 3) 成交额 MA20（仅对有 amount 数据的 ETF）
+    eligible_amount_cols = [e for e in eligible_etfs if e in amount.columns]
+    amt_ma20_df = None
+    if eligible_amount_cols:
+        amt_aligned = amount[eligible_amount_cols].loc[
+            amount.index.intersection(close_recent.index)
+        ]
+        if len(amt_aligned) >= params["AmountMAWindow"]:
+            amt_ma20_df = amt_aligned.rolling(params["AmountMAWindow"]).mean()
+
+    # 4) 偏离均线程度
+    ma20_df = close_recent.rolling(params["DeviationMAWindow"]).mean()
+    deviation_df = close_recent / ma20_df - 1
+
+    # 5) 短期波动率
+    vol20_df = close_recent.pct_change().rolling(params["CrowdVolWindow"]).std() * np.sqrt(params["annual_factor"])
+
+    # ---- 逐 ETF 从预计算 DataFrame 中取列做分位排名 ----
+    for i, etf in enumerate(pool):
+        if etf not in eligible_etfs:
+            continue
+
+        indicators = []
+
+        # ret short (per-ETF window)
+        short_w = ret_windows[i][0]
+        col_short = ret_short_map[short_w][etf].dropna()
+        indicators.append(percentile_rank(col_short.iloc[-1], col_short) if len(col_short) > 1 else 0.5)
+
+        # ret mid (per-ETF window)
+        mid_w = ret_windows[i][1]
+        col_mid = ret_mid_map[mid_w][etf].dropna()
+        indicators.append(percentile_rank(col_mid.iloc[-1], col_mid) if len(col_mid) > 1 else 0.5)
+
+        # amt_ma20
+        if amt_ma20_df is not None and etf in amt_ma20_df.columns:
+            col_amt = amt_ma20_df[etf].dropna()
+            indicators.append(percentile_rank(col_amt.iloc[-1], col_amt) if len(col_amt) > 1 else 0.5)
+        else:
+            indicators.append(0.5)
+
+        # deviation
+        col_dev = deviation_df[etf].dropna()
+        indicators.append(percentile_rank(col_dev.iloc[-1], col_dev) if len(col_dev) > 1 else 0.5)
+
+        # vol20
+        col_vol = vol20_df[etf].dropna()
+        indicators.append(percentile_rank(col_vol.iloc[-1], col_vol) if len(col_vol) > 1 else 0.5)
+
+        crowd_score = np.mean(indicators)
+
+        etf_start, etf_end, etf_min = thresholds[i]
+        if crowd_score <= etf_start:
+            penalty = 1.0
+        elif crowd_score >= etf_end:
+            penalty = etf_min
+        else:
+            penalty = 1.0 - (crowd_score - etf_start) / (etf_end - etf_start) * (1.0 - etf_min)
+            penalty = max(etf_min, min(1.0, penalty))
+
+        penalties[i] = penalty
+
+    return penalties
+
+
+# ============================================================
+# percentile_rank — 计算分位数排名（0~1）
+# ============================================================
+def percentile_rank(value, series):
+    """
+    计算 value 在 series 中的分位数（0~1）。
+
+    返回 0 表示 value 是序列中最小值，返回 1 表示最大值。
+    """
+    if len(series) == 0:
+        return 0.5
+    ranked = (series < value).mean()
+    return float(ranked)
+
+
+# ============================================================
+# compute_portfolio_vol_scale — 组合波动率缩放系数
+# ============================================================
+def compute_portfolio_vol_scale_detail(prices, pool, raw_weights, params):
+    """
+    根据 RawWeight 和协方差矩阵计算组合波动率，按目标波动率缩放。
+
+    使用 get_history_data 预计算的 close_ret，避免重复 pct_change()。
+    只缩不放（最大系数为 1.0）。
+
+    返回: (scale, vol_ratio)
+    """
+    close_ret = prices['close_ret']
+    vol_window = params["PortfolioVolWindow"]
+    target_vol = params["TargetVol"]
+    annual_factor = params["annual_factor"]
+
+    n = len(pool)
+    active_indices = [i for i in range(n) if raw_weights[i] > 1e-8]
+
+    if not active_indices:
+        return 1.0, None
+
+    returns_list = []
+    for i in active_indices:
+        etf = pool[i]
+        if etf not in close_ret.columns:
+            return 1.0, None
+        ret = close_ret[etf].dropna().iloc[-vol_window:]
+        if len(ret) < vol_window:
+            return 1.0, None
+        returns_list.append(ret.values)
+
+    if not returns_list:
+        return 1.0, None
+
+    ret_matrix = np.column_stack(returns_list)
+    cov_daily = np.atleast_2d(np.cov(ret_matrix, rowvar=False))
+    cov_annual = cov_daily * annual_factor
+
+    active_weights = np.array([raw_weights[i] for i in active_indices])
+    portfolio_var = active_weights @ cov_annual @ active_weights
+    portfolio_vol = np.sqrt(max(portfolio_var, 0))
+    vol_ratio = float(portfolio_vol / target_vol)
+
+    if portfolio_vol <= target_vol or portfolio_vol < 1e-8:
+        return 1.0, vol_ratio
+
+    scale = target_vol / portfolio_vol
+    return min(scale, params["MaxPortfolioVolScale"]), vol_ratio
+
+
+def compute_portfolio_vol_scale(prices, pool, raw_weights, params):
+    """返回原有组合级波动率缩放标量。"""
+    scale, _vol_ratio = compute_portfolio_vol_scale_detail(prices, pool, raw_weights, params)
+    return scale
+
+
+def compute_portfolio_vol_asset_scales(prices, pool, raw_weights, params):
+    """返回每只 ETF 的组合波控缩放系数和审计元数据。"""
+    base_scale, vol_ratio = compute_portfolio_vol_scale_detail(prices, pool, raw_weights, params)
+    asset_scales = np.full(len(pool), base_scale)
+    mode = params["PortfolioVolReliefMode"]
+    meta = {
+        "mode": mode,
+        "vol_ratio": vol_ratio,
+        "base_scale": base_scale,
+        "relief_asset": None,
+        "relief_weight": 0.0,
+        "reason": "baseline",
+    }
+    if mode == "fixed_gold":
+        return apply_fixed_gold_vol_relief(pool, raw_weights, asset_scales, meta, params)
+    if mode == "dyn_marginal":
+        return apply_dynamic_marginal_vol_relief(prices, pool, raw_weights, asset_scales, meta, params)
+    return asset_scales, meta
+
+
+def apply_fixed_gold_vol_relief(pool, raw_weights, asset_scales, meta, params):
+    """固定黄金弱缩放：按参数恢复黄金被组合波控压掉的部分仓位。"""
+    gold_code = "518880.XSHG"
+    vol_ratio = meta["vol_ratio"]
+    base_scale = meta["base_scale"]
+
+    if vol_ratio is None or vol_ratio <= 1.0:
+        meta["reason"] = "vol_not_above_target"
+        return asset_scales, meta
+    if vol_ratio > params["GoldVolReliefMaxRatio"]:
+        meta["reason"] = "ratio_too_high"
+        return asset_scales, meta
+    if gold_code not in pool:
+        meta["reason"] = "gold_not_in_pool"
+        return asset_scales, meta
+
+    gold_idx = pool.index(gold_code)
+    if raw_weights[gold_idx] <= 1e-8:
+        meta["reason"] = "gold_not_active"
+        return asset_scales, meta
+
+    new_scale = min(1.0, base_scale + (1.0 - base_scale) * params["GoldVolReliefFraction"])
+    asset_scales[gold_idx] = new_scale
+    meta["relief_asset"] = gold_code
+    meta["relief_weight"] = float(raw_weights[gold_idx] * (new_scale - base_scale))
+    meta["reason"] = "fixed_gold"
+    return asset_scales, meta
+
+
+def apply_dynamic_marginal_vol_relief(prices, pool, raw_weights, asset_scales, meta, params):
+    """动态弱缩放：在正动量持仓中选择边际风险最低资产恢复仓位。"""
+    vol_ratio = meta["vol_ratio"]
+    base_scale = meta["base_scale"]
+
+    if vol_ratio is None or vol_ratio <= 1.0:
+        meta["reason"] = "vol_not_above_target"
+        return asset_scales, meta
+    if vol_ratio > params["DynamicVolReliefMaxRatio"]:
+        meta["reason"] = "ratio_too_high"
+        return asset_scales, meta
+
+    selected_idx, reason = select_dynamic_marginal_relief_asset(
+        prices, pool, raw_weights, params
+    )
+    if selected_idx is None:
+        meta["reason"] = reason
+        return asset_scales, meta
+
+    new_scale = min(1.0, base_scale + (1.0 - base_scale) * params["DynamicVolReliefFraction"])
+    asset_scales[selected_idx] = new_scale
+    meta["relief_asset"] = pool[selected_idx]
+    meta["relief_weight"] = float(raw_weights[selected_idx] * (new_scale - base_scale))
+    meta["reason"] = "selected_low_marginal_risk"
+    return asset_scales, meta
+
+
+def select_dynamic_marginal_relief_asset(prices, pool, raw_weights, params):
+    """返回动态弱缩放资产下标和原因。"""
+    active_indices = [i for i, weight in enumerate(raw_weights) if weight > 1e-8]
+    if not active_indices:
+        return None, "no_active_asset"
+
+    close_ret = prices.get("close_ret")
+    if close_ret is None:
+        return None, "insufficient_cov_data"
+
+    active_codes = [pool[i] for i in active_indices]
+    for code in active_codes:
+        if code not in close_ret.columns:
+            return None, "insufficient_cov_data"
+
+    cov_window = params["DynamicVolReliefCovWindow"]
+    active_returns = close_ret[active_codes].dropna().iloc[-cov_window:]
+    if len(active_returns) < cov_window:
+        return None, "insufficient_cov_data"
+
+    momentum_window = params["DynamicVolReliefMomentumWindow"]
+    positive_candidates = []
+    for active_pos, code in enumerate(active_codes):
+        momentum_ret = close_ret[code].dropna().iloc[-momentum_window:]
+        if len(momentum_ret) < momentum_window:
+            continue
+        momentum = float(np.prod(1.0 + momentum_ret.values) - 1.0)
+        if momentum >= 0.0:
+            positive_candidates.append(active_pos)
+
+    if not positive_candidates:
+        return None, "no_positive_momentum_asset"
+
+    cov_daily = np.atleast_2d(np.cov(active_returns.values, rowvar=False))
+    cov_annual = cov_daily * params["annual_factor"]
+    active_weights = np.array([raw_weights[i] for i in active_indices])
+    marginal_scores = cov_annual @ active_weights
+    best_active_pos = min(
+        positive_candidates,
+        key=lambda active_pos: marginal_scores[active_pos],
+    )
+    return active_indices[best_active_pos], "selected_low_marginal_risk"
+
+
+# ============================================================
+# apply_weight_constraints — 应用仓位约束
+# ============================================================
+def apply_weight_constraints(final_weights, params):
+    """
+    应用单资产最大仓位、最小有效仓位和总仓位上限约束。
+
+    总仓位约束在单资产约束之后应用，缩放后不重新归一化。
+    """
+    max_w = params["MaxWeight"]
+    min_w = params["MinWeight"]
+    max_total = params["MaxTotalWeight"]
+    n = len(final_weights)
+
+    result = np.copy(final_weights)
+
+    for i in range(n):
+        if result[i] > max_w:
+            result[i] = max_w
+        if result[i] < min_w:
+            result[i] = 0.0
+
+    total = result.sum()
+    if total > max_total:
+        result = result * max_total / total
+
+    return result
+
+
+# ============================================================
+# execute_rebalance — 执行调仓
+# ============================================================
+def execute_rebalance(context, pool, final_weights, params):
+    """
+    根据最终目标权重执行调仓，应用最小调仓阈值。
+    剩余仓位保留为现金。
+
+    执行前检查停牌状态，执行后记录订单结果，便于审计和故障定位。
+    """
+    account_value = context.portfolio.total_value
+    current_data = get_current_data()
+    etf_names = build_etf_display_names(pool, params.get("etf_names"))
+
+    for i, etf in enumerate(pool):
+        etf_name = etf_names[i]
+        target_value = account_value * final_weights[i]
+        current_pos = context.portfolio.positions[etf]
+        current_value = current_pos.total_amount * current_pos.price if current_pos.total_amount > 0 else 0
+        current_weight = current_value / account_value if account_value > 0 else 0
+
+        # 如果目标权重为 0 且当前仓位为 0，跳过
+        if final_weights[i] == 0 and current_weight == 0:
+            audit_event(
+                "rebalance_order",
+                context,
+                action="skip_zero_target_zero_position",
+                etf=etf,
+                etf_name=etf_name,
+                target_weight=final_weights[i],
+                current_weight=current_weight,
+                target_value=target_value,
+            )
+            continue
+
+        # 最小调仓阈值
+        if abs(final_weights[i] - current_weight) < params["RebalanceThreshold"]:
+            audit_event(
+                "rebalance_order",
+                context,
+                action="skip_threshold",
+                etf=etf,
+                etf_name=etf_name,
+                target_weight=final_weights[i],
+                current_weight=current_weight,
+                target_value=target_value,
+                rebalance_threshold=params["RebalanceThreshold"],
+            )
+            continue
+
+        # 停牌检查
+        data = current_data[etf]
+        if data.paused:
+            log.warning("skip paused ETF: %s security=%s", etf_name, etf)
+            audit_event(
+                "rebalance_order",
+                context,
+                action="skip_paused",
+                etf=etf,
+                etf_name=etf_name,
+                target_weight=final_weights[i],
+                current_weight=current_weight,
+                target_value=target_value,
+            )
+            continue
+
+        order_obj = order_target_value(etf, target_value)
+        if order_obj is None:
+            log.error(
+                "order failed: %s security=%s target_value=%.2f target_weight=%.4f current_weight=%.4f",
+                etf_name, etf, target_value, final_weights[i], current_weight
+            )
+            audit_event(
+                "rebalance_order",
+                context,
+                action="order_failed",
+                etf=etf,
+                etf_name=etf_name,
+                target_weight=final_weights[i],
+                current_weight=current_weight,
+                target_value=target_value,
+            )
+        else:
+            log.info(
+                "order sent: %s security=%s target_weight=%.4f current_weight=%.4f target_value=%.2f",
+                etf_name, etf, final_weights[i], current_weight, target_value
+            )
+            audit_event(
+                "rebalance_order",
+                context,
+                action="order_sent",
+                etf=etf,
+                etf_name=etf_name,
+                target_weight=final_weights[i],
+                current_weight=current_weight,
+                target_value=target_value,
+                order=order_obj,
+            )
diff --git a/strategies/etf_factor_rotation/variants/logic3_code_variant.json b/strategies/etf_factor_rotation/variants/logic3_code_variant.json
new file mode 100644
index 00000000..633a8a52
--- /dev/null
+++ b/strategies/etf_factor_rotation/variants/logic3_code_variant.json
@@ -0,0 +1,29 @@
+{
+  "schema_version": 1,
+  "variant_id": "logic3_code_variant",
+  "variant_type": "structural",
+  "status": "candidate",
+  "merge_status": "not_merged",
+  "description": "旧实盘近似代码变体：周一标记信号，下一交易日开盘生成并执行。",
+  "code_source": {
+    "type": "git",
+    "path": "strategies/etf_factor_rotation/variants/code/logic3_code_variant.py"
+  },
+  "params_diff": {},
+  "research_refs": [],
+  "backtest_refs": [],
+  "report_refs": [],
+  "created_at": "2026-06-30T16:23:28+00:00",
+  "updated_at": "2026-06-30T16:23:28+00:00",
+  "owner": "research-platform",
+  "created_by": "research-platform",
+  "updated_by": "research-platform",
+  "lifecycle": "active",
+  "payload": {
+    "code_source": {
+      "type": "git",
+      "path": "strategies/etf_factor_rotation/variants/code/logic3_code_variant.py"
+    },
+    "owner": "research-platform"
+  }
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/variants/variants.json b/strategies/etf_factor_rotation/variants/variants.json
index b0413729..942e8fdc 100644
--- a/strategies/etf_factor_rotation/variants/variants.json
+++ b/strategies/etf_factor_rotation/variants/variants.json
@@ -1,4 +1,32 @@
 {
   "schema_version": 1,
-  "variants": []
-}
+  "variants": [
+    {
+      "variant_id": "baseline_original",
+      "variant_type": "structural",
+      "status": "candidate",
+      "merge_status": "not_merged",
+      "description": "原始正式基线代码：本次实验对照组，来源为本分支起点 origin/main 的正式策略脚本。",
+      "updated_at": "2026-06-30T20:21:17+00:00",
+      "detail": "baseline_original.json"
+    },
+    {
+      "variant_id": "logic3_code_variant",
+      "variant_type": "structural",
+      "status": "candidate",
+      "merge_status": "not_merged",
+      "description": "旧实盘近似代码变体：周一标记信号，下一交易日开盘生成并执行。",
+      "updated_at": "2026-06-30T16:23:28+00:00",
+      "detail": "logic3_code_variant.json"
+    },
+    {
+      "variant_id": "weekend_close_signal_next_open_variant",
+      "variant_type": "structural",
+      "status": "candidate",
+      "merge_status": "not_merged",
+      "description": "新实盘对齐代码变体：本周最后交易日收盘生成信号，次交易日开盘执行缓存计划。",
+      "updated_at": "2026-06-30T16:23:28+00:00",
+      "detail": "weekend_close_signal_next_open_variant.json"
+    }
+  ]
+}
\ No newline at end of file
diff --git a/strategies/etf_factor_rotation/variants/weekend_close_signal_next_open_variant.json b/strategies/etf_factor_rotation/variants/weekend_close_signal_next_open_variant.json
new file mode 100644
index 00000000..842c1eff
--- /dev/null
+++ b/strategies/etf_factor_rotation/variants/weekend_close_signal_next_open_variant.json
@@ -0,0 +1,29 @@
+{
+  "schema_version": 1,
+  "variant_id": "weekend_close_signal_next_open_variant",
+  "variant_type": "structural",
+  "status": "candidate",
+  "merge_status": "not_merged",
+  "description": "新实盘对齐代码变体：本周最后交易日收盘生成信号，次交易日开盘执行缓存计划。",
+  "code_source": {
+    "type": "git",
+    "path": "strategies/etf_factor_rotation/variants/code/weekend_close_signal_next_open_variant.py"
+  },
+  "params_diff": {},
+  "research_refs": [],
+  "backtest_refs": [],
+  "report_refs": [],
+  "created_at": "2026-06-30T16:23:28+00:00",
+  "updated_at": "2026-06-30T16:23:28+00:00",
+  "owner": "research-platform",
+  "created_by": "research-platform",
+  "updated_by": "research-platform",
+  "lifecycle": "active",
+  "payload": {
+    "code_source": {
+      "type": "git",
+      "path": "strategies/etf_factor_rotation/variants/code/weekend_close_signal_next_open_variant.py"
+    },
+    "owner": "research-platform"
+  }
+}
\ No newline at end of file