生成的参数组合数量：18
2025-06-25 19:08:34 | INFO | metric_online:run_with_hydra:842 - {'envs': {'env': {'mode': 'prod', 'enable_monitor': False, 'n_jobs': 1}, 'incremental': {'enabled': True, 'lookback_days': 20, 'start_date': None, 'end_date': 'today'}, 'run': {'n_jobs': 1, 'retry_times': 3, 'retry_delay': 2}, 'shard': {'num_shards': 1, 'shard_id': 0}}}
2025-06-25 19:08:34 | INFO | metric_online:run_with_hydra:889 - Total tasks generated: 1
2025-06-25 19:08:34 | INFO | metric_online:run_with_hydra:902 - Starting parallel execution with n_jobs=1...
2025-06-25 19:08:42 | INFO | metric_online:main2:781 - save train test done /root/data/Research1//feature/finalcomd//B8Wstats250412/B8Wstats250412_0--combo52
2025-06-25 19:10:56 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:10:57 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:10:57 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:10:58 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:10:58 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:10:59 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:00 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:00 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:03 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:04 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:04 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:05 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:05 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:05 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:07 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:07 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:08 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:08 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:11 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:11 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:11 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:12 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:12 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:12 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:13 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:13 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:13 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:14 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:14 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:14 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:15 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:15 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:18 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:18 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:19 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:19 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:20 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:20 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:21 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:22 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:22 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:22 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:23 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:23 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:25 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:11:25 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
{'obj': 'Sharpe', 'rm': 'MDD', 'model': 'Classic', 'method_mu': 'hist', 'method_cov': 'hist', 'linkage': 'single', 'leaf_order': True, 'codependence': 'pearson', 'lookback_period': 256, 'every': 10, 'nea': 5, 'split_every': False, 'normalize_every': False}
1%| | 1/105 [00:08<14:45, 8.51s/it, 2020-01-17 → 2021-02-04]
2%|▏ | 2/105 [00:14<12:00, 6.99s/it, 2020-02-08 → 2021-02-25]
3%|▎ | 3/105 [00:20<11:01, 6.48s/it, 2020-02-22 → 2021-03-11]
4%|▍ | 4/105 [00:26<10:29, 6.23s/it, 2020-03-07 → 2021-03-25]
5%|▍ | 5/105 [00:32<10:10, 6.11s/it, 2020-03-21 → 2021-04-09]
6%|▌ | 6/105 [00:38<10:00, 6.07s/it, 2020-04-04 → 2021-04-23]
7%|▋ | 7/105 [00:43<09:50, 6.03s/it, 2020-04-21 → 2021-05-12]
8%|▊ | 8/105 [00:50<09:47, 6.06s/it, 2020-05-08 → 2021-05-26]
9%|▊ | 9/105 [00:56<09:44, 6.08s/it, 2020-05-22 → 2021-06-09]
10%|▉ | 10/105 [01:02<09:38, 6.09s/it, 2020-06-05 → 2021-06-24]
10%|█ | 11/105 [01:08<09:34, 6.11s/it, 2020-06-19 → 2021-07-08]
11%|█▏ | 12/105 [01:14<09:27, 6.10s/it, 2020-07-07 → 2021-07-22]
12%|█▏ | 13/105 [01:20<09:20, 6.09s/it, 2020-07-21 → 2021-08-05]
13%|█▎ | 14/105 [01:26<09:16, 6.11s/it, 2020-08-04 → 2021-08-19]
14%|█▍ | 15/105 [01:33<09:15, 6.17s/it, 2020-08-18 → 2021-09-02]
15%|█▌ | 16/105 [01:39<09:09, 6.17s/it, 2020-09-01 → 2021-09-16]
16%|█▌ | 17/105 [01:45<09:03, 6.17s/it, 2020-09-15 → 2021-10-09]
17%|█▋ | 18/105 [01:51<08:57, 6.17s/it, 2020-09-29 → 2021-10-23]
18%|█▊ | 19/105 [01:57<08:50, 6.17s/it, 2020-10-21 → 2021-11-06]
19%|█▉ | 20/105 [02:04<08:46, 6.20s/it, 2020-11-04 → 2021-11-20]
20%|██ | 21/105 [02:10<08:40, 6.20s/it, 2020-11-18 → 2021-12-04]
21%|██ | 22/105 [02:16<08:31, 6.16s/it, 2020-12-02 → 2021-12-18]
22%|██▏ | 23/105 [02:22<08:22, 6.13s/it, 2020-12-16 → 2022-01-01]
23%|██▎ | 24/105 [02:28<08:18, 6.15s/it, 2020-12-30 → 2022-01-18]
24%|██▍ | 25/105 [02:34<08:15, 6.19s/it, 2021-01-14 → 2022-02-08]
25%|██▍ | 26/105 [02:41<08:08, 6.18s/it, 2021-01-28 → 2022-02-22]
26%|██▌ | 27/105 [02:47<08:02, 6.19s/it, 2021-02-11 → 2022-03-08]
27%|██▋ | 28/105 [02:53<07:56, 6.19s/it, 2021-03-04 → 2022-03-22]
28%|██▊ | 29/105 [02:59<07:52, 6.21s/it, 2021-03-18 → 2022-04-07]
29%|██▊ | 30/105 [03:05<07:44, 6.19s/it, 2021-04-01 → 2022-04-21]
30%|██▉ | 31/105 [03:11<07:35, 6.15s/it, 2021-04-16 → 2022-05-10]
30%|███ | 32/105 [03:17<07:25, 6.11s/it, 2021-04-30 → 2022-05-24]
31%|███▏ | 33/105 [03:23<07:17, 6.08s/it, 2021-05-19 → 2022-06-08]
32%|███▏ | 34/105 [03:30<07:11, 6.08s/it, 2021-06-02 → 2022-06-22]
33%|███▎ | 35/105 [03:36<07:05, 6.07s/it, 2021-06-17 → 2022-07-06]
34%|███▍ | 36/105 [03:42<06:59, 6.08s/it, 2021-07-01 → 2022-07-20]
35%|███▌ | 37/105 [03:48<06:52, 6.06s/it, 2021-07-15 → 2022-08-03]
36%|███▌ | 38/105 [03:54<06:50, 6.12s/it, 2021-07-29 → 2022-08-17]
37%|███▋ | 39/105 [04:00<06:43, 6.12s/it, 2021-08-12 → 2022-08-31]
38%|███▊ | 40/105 [04:06<06:35, 6.09s/it, 2021-08-26 → 2022-09-15]
39%|███▉ | 41/105 [04:12<06:29, 6.09s/it, 2021-09-09 → 2022-09-29]
40%|████ | 42/105 [04:18<06:23, 6.09s/it, 2021-09-25 → 2022-10-20]
41%|████ | 43/105 [04:24<06:16, 6.07s/it, 2021-10-16 → 2022-11-03]
42%|████▏ | 44/105 [04:30<06:10, 6.07s/it, 2021-10-30 → 2022-11-17]
43%|████▎ | 45/105 [04:36<06:05, 6.08s/it, 2021-11-13 → 2022-12-01]
44%|████▍ | 46/105 [04:43<06:04, 6.18s/it, 2021-11-27 → 2022-12-15]
45%|████▍ | 47/105 [04:49<05:57, 6.17s/it, 2021-12-11 → 2022-12-29]
46%|████▌ | 48/105 [04:55<05:49, 6.13s/it, 2021-12-25 → 2023-01-13]
47%|████▋ | 49/105 [05:01<05:38, 6.04s/it, 2022-01-11 → 2023-02-03]
48%|████▊ | 50/105 [05:07<05:29, 5.99s/it, 2022-01-25 → 2023-02-17]
49%|████▊ | 51/105 [05:13<05:23, 5.99s/it, 2022-02-15 → 2023-03-03]
50%|████▉ | 52/105 [05:19<05:19, 6.04s/it, 2022-03-01 → 2023-03-17]
50%|█████ | 53/105 [05:25<05:16, 6.10s/it, 2022-03-15 → 2023-03-31]
51%|█████▏ | 54/105 [05:31<05:12, 6.12s/it, 2022-03-29 → 2023-04-15]
52%|█████▏ | 55/105 [05:37<05:05, 6.11s/it, 2022-04-14 → 2023-04-29]
53%|█████▎ | 56/105 [05:44<05:00, 6.14s/it, 2022-04-28 → 2023-05-18]
54%|█████▍ | 57/105 [05:50<04:55, 6.16s/it, 2022-05-17 → 2023-06-01]
55%|█████▌ | 58/105 [05:56<04:49, 6.17s/it, 2022-05-31 → 2023-06-15]
56%|█████▌ | 59/105 [06:02<04:44, 6.18s/it, 2022-06-15 → 2023-07-01]
57%|█████▋ | 60/105 [06:08<04:38, 6.19s/it, 2022-06-29 → 2023-07-15]
58%|█████▊ | 61/105 [06:15<04:33, 6.21s/it, 2022-07-13 → 2023-07-29]
59%|█████▉ | 62/105 [06:21<04:27, 6.22s/it, 2022-07-27 → 2023-08-12]
60%|██████ | 63/105 [06:27<04:21, 6.24s/it, 2022-08-10 → 2023-08-26]
61%|██████ | 64/105 [06:33<04:16, 6.25s/it, 2022-08-24 → 2023-09-09]
62%|██████▏ | 65/105 [06:39<04:07, 6.18s/it, 2022-09-07 → 2023-09-23]
63%|██████▎ | 66/105 [06:46<03:59, 6.15s/it, 2022-09-22 → 2023-10-17]
64%|██████▍ | 67/105 [06:52<03:53, 6.15s/it, 2022-10-13 → 2023-10-31]
65%|██████▍ | 68/105 [06:58<03:47, 6.15s/it, 2022-10-27 → 2023-11-14]
66%|██████▌ | 69/105 [07:04<03:42, 6.18s/it, 2022-11-10 → 2023-11-28]
67%|██████▋ | 70/105 [07:10<03:37, 6.21s/it, 2022-11-24 → 2023-12-12]
68%|██████▊ | 71/105 [07:17<03:32, 6.24s/it, 2022-12-08 → 2023-12-26]
69%|██████▊ | 72/105 [07:23<03:26, 6.27s/it, 2022-12-22 → 2024-01-10]
70%|██████▉ | 73/105 [07:29<03:21, 6.29s/it, 2023-01-06 → 2024-01-24]
70%|███████ | 74/105 [07:36<03:15, 6.29s/it, 2023-01-20 → 2024-02-07]
71%|███████▏ | 75/105 [07:42<03:08, 6.28s/it, 2023-02-10 → 2024-02-29]
72%|███████▏ | 76/105 [07:48<03:02, 6.29s/it, 2023-02-24 → 2024-03-14]
73%|███████▎ | 77/105 [07:54<02:55, 6.27s/it, 2023-03-10 → 2024-03-28]
74%|███████▍ | 78/105 [08:01<02:49, 6.29s/it, 2023-03-24 → 2024-04-13]
75%|███████▌ | 79/105 [08:07<02:43, 6.30s/it, 2023-04-08 → 2024-04-27]
76%|███████▌ | 80/105 [08:13<02:37, 6.31s/it, 2023-04-22 → 2024-05-16]
77%|███████▋ | 81/105 [08:20<02:31, 6.30s/it, 2023-05-11 → 2024-05-30]
78%|███████▊ | 82/105 [08:26<02:25, 6.34s/it, 2023-05-25 → 2024-06-14]
79%|███████▉ | 83/105 [08:32<02:19, 6.32s/it, 2023-06-08 → 2024-06-28]
80%|████████ | 84/105 [08:39<02:12, 6.33s/it, 2023-06-22 → 2024-07-12]
81%|████████ | 85/105 [08:45<02:07, 6.36s/it, 2023-07-08 → 2024-07-26]
82%|████████▏ | 86/105 [08:52<02:00, 6.36s/it, 2023-07-22 → 2024-08-09]
83%|████████▎ | 87/105 [08:58<01:54, 6.36s/it, 2023-08-05 → 2024-08-23]
84%|████████▍ | 88/105 [09:04<01:48, 6.36s/it, 2023-08-19 → 2024-09-06]
85%|████████▍ | 89/105 [09:11<01:41, 6.37s/it, 2023-09-02 → 2024-09-24]
86%|████████▌ | 90/105 [09:17<01:35, 6.35s/it, 2023-09-16 → 2024-10-15]
87%|████████▋ | 91/105 [09:23<01:28, 6.32s/it, 2023-10-10 → 2024-10-29]
88%|████████▊ | 92/105 [09:30<01:22, 6.34s/it, 2023-10-24 → 2024-11-12]
89%|████████▊ | 93/105 [09:36<01:16, 6.34s/it, 2023-11-07 → 2024-11-26]
90%|████████▉ | 94/105 [09:42<01:09, 6.32s/it, 2023-11-21 → 2024-12-10]
90%|█████████ | 95/105 [09:48<01:02, 6.29s/it, 2023-12-05 → 2024-12-24]
91%|█████████▏| 96/105 [09:55<00:56, 6.29s/it, 2023-12-19 → 2025-01-08]
92%|█████████▏| 97/105 [10:01<00:50, 6.27s/it, 2024-01-03 → 2025-01-22]
93%|█████████▎| 98/105 [10:07<00:44, 6.29s/it, 2024-01-17 → 2025-02-13]
94%|█████████▍| 99/105 [10:14<00:37, 6.29s/it, 2024-01-31 → 2025-02-27]
95%|█████████▌| 100/105 [10:20<00:31, 6.29s/it, 2024-02-22 → 2025-03-13]
96%|█████████▌| 101/105 [10:26<00:25, 6.30s/it, 2024-03-07 → 2025-03-27]
97%|█████████▋| 102/105 [10:33<00:19, 6.34s/it, 2024-03-21 → 2025-04-11]
98%|█████████▊| 103/105 [10:39<00:12, 6.35s/it, 2024-04-04 → 2025-04-26]
99%|█████████▉| 104/105 [10:45<00:06, 6.34s/it, 2024-04-20 → 2025-05-15]
100%|██████████| 105/105 [10:52<00:00, 6.33s/it, 2024-04-20 → 2025-05-15]
100%|██████████| 105/105 [10:52<00:00, 6.21s/it, 2024-04-20 → 2025-05-15]
2025-06-25 19:22:19 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:463 - [v7] 优化前的夏普率: 1.03694
2025-06-25 19:22:19 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:464 - [v7] 优化后的夏普率: 0.71812
2025-06-25 19:22:20 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:21 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:21 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:22 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:24 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:25 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:25 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:26 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:27 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:29 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:29 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:29 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:30 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:30 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:31 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:31 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:33 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:33 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:34 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:35 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:35 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:35 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:22:37 | WARNING | func_backtester_hf:run_sig2pos:979 - The given signal has NaN. Will use 0 to fill
{'obj': 'Sharpe', 'rm': 'MDD', 'model': 'Classic', 'method_mu': 'hist', 'method_cov': 'hist', 'linkage': 'single', 'leaf_order': True, 'codependence': 'pearson', 'lookback_period': 256, 'every': 10, 'nea': 5, 'split_every': False, 'normalize_every': False}
1%| | 1/105 [00:05<10:21, 5.98s/it, 2020-01-18 → 2021-02-05]
2%|▏ | 2/105 [00:11<10:13, 5.96s/it, 2020-02-11 → 2021-02-26]
3%|▎ | 3/105 [00:18<10:13, 6.02s/it, 2020-02-25 → 2021-03-12]
4%|▍ | 4/105 [00:23<10:03, 5.98s/it, 2020-03-10 → 2021-03-26]
5%|▍ | 5/105 [00:29<09:54, 5.95s/it, 2020-03-24 → 2021-04-10]
6%|▌ | 6/105 [00:35<09:50, 5.97s/it, 2020-04-08 → 2021-04-24]
7%|▋ | 7/105 [00:41<09:44, 5.97s/it, 2020-04-22 → 2021-05-13]
8%|▊ | 8/105 [00:47<09:43, 6.01s/it, 2020-05-09 → 2021-05-27]
9%|▊ | 9/105 [00:54<09:41, 6.06s/it, 2020-05-23 → 2021-06-10]
10%|▉ | 10/105 [01:00<09:35, 6.05s/it, 2020-06-06 → 2021-06-25]
10%|█ | 11/105 [01:06<09:27, 6.04s/it, 2020-06-20 → 2021-07-09]
11%|█▏ | 12/105 [01:12<09:24, 6.07s/it, 2020-07-08 → 2021-07-23]
12%|█▏ | 13/105 [01:18<09:18, 6.07s/it, 2020-07-22 → 2021-08-06]
13%|█▎ | 14/105 [01:24<09:14, 6.10s/it, 2020-08-05 → 2021-08-20]
14%|█▍ | 15/105 [01:30<09:08, 6.10s/it, 2020-08-19 → 2021-09-03]
15%|█▌ | 16/105 [01:36<09:04, 6.12s/it, 2020-09-02 → 2021-09-17]
16%|█▌ | 17/105 [01:42<09:01, 6.15s/it, 2020-09-16 → 2021-10-12]
17%|█▋ | 18/105 [01:49<08:55, 6.16s/it, 2020-09-30 → 2021-10-26]
18%|█▊ | 19/105 [01:55<08:49, 6.16s/it, 2020-10-22 → 2021-11-09]
19%|█▉ | 20/105 [02:01<08:46, 6.19s/it, 2020-11-05 → 2021-11-23]
20%|██ | 21/105 [02:07<08:39, 6.19s/it, 2020-11-19 → 2021-12-07]
21%|██ | 22/105 [02:13<08:32, 6.17s/it, 2020-12-03 → 2021-12-21]
22%|██▏ | 23/105 [02:19<08:23, 6.14s/it, 2020-12-17 → 2022-01-05]
23%|██▎ | 24/105 [02:26<08:22, 6.20s/it, 2020-12-31 → 2022-01-19]
24%|██▍ | 25/105 [02:32<08:15, 6.19s/it, 2021-01-15 → 2022-02-09]
25%|██▍ | 26/105 [02:38<08:08, 6.19s/it, 2021-01-29 → 2022-02-23]
26%|██▌ | 27/105 [02:44<08:01, 6.17s/it, 2021-02-19 → 2022-03-09]
27%|██▋ | 28/105 [02:50<07:54, 6.16s/it, 2021-03-05 → 2022-03-23]
28%|██▊ | 29/105 [02:56<07:45, 6.13s/it, 2021-03-19 → 2022-04-08]
29%|██▊ | 30/105 [03:03<07:37, 6.10s/it, 2021-04-02 → 2022-04-22]
30%|██▉ | 31/105 [03:09<07:32, 6.12s/it, 2021-04-17 → 2022-05-11]
30%|███ | 32/105 [03:15<07:27, 6.13s/it, 2021-05-01 → 2022-05-25]
31%|███▏ | 33/105 [03:21<07:19, 6.11s/it, 2021-05-20 → 2022-06-09]
32%|███▏ | 34/105 [03:27<07:15, 6.14s/it, 2021-06-03 → 2022-06-23]
33%|███▎ | 35/105 [03:33<07:09, 6.13s/it, 2021-06-18 → 2022-07-07]
34%|███▍ | 36/105 [03:39<07:03, 6.13s/it, 2021-07-02 → 2022-07-21]
35%|███▌ | 37/105 [03:45<06:56, 6.12s/it, 2021-07-16 → 2022-08-04]
36%|███▌ | 38/105 [03:51<06:47, 6.09s/it, 2021-07-30 → 2022-08-18]
37%|███▋ | 39/105 [03:58<06:41, 6.09s/it, 2021-08-13 → 2022-09-01]
38%|███▊ | 40/105 [04:04<06:34, 6.07s/it, 2021-08-27 → 2022-09-16]
39%|███▉ | 41/105 [04:10<06:29, 6.08s/it, 2021-09-10 → 2022-09-30]
40%|████ | 42/105 [04:16<06:24, 6.11s/it, 2021-09-28 → 2022-10-21]
41%|████ | 43/105 [04:22<06:18, 6.10s/it, 2021-10-19 → 2022-11-04]
42%|████▏ | 44/105 [04:28<06:14, 6.13s/it, 2021-11-02 → 2022-11-18]
43%|████▎ | 45/105 [04:34<06:07, 6.12s/it, 2021-11-16 → 2022-12-02]
44%|████▍ | 46/105 [04:40<06:01, 6.13s/it, 2021-11-30 → 2022-12-16]
45%|████▍ | 47/105 [04:47<05:55, 6.14s/it, 2021-12-14 → 2022-12-30]
46%|████▌ | 48/105 [04:53<05:52, 6.18s/it, 2021-12-28 → 2023-01-14]
47%|████▋ | 49/105 [04:59<05:42, 6.12s/it, 2022-01-12 → 2023-02-04]
48%|████▊ | 50/105 [05:05<05:33, 6.07s/it, 2022-01-26 → 2023-02-18]
49%|████▊ | 51/105 [05:11<05:25, 6.03s/it, 2022-02-16 → 2023-03-04]
50%|████▉ | 52/105 [05:17<05:21, 6.06s/it, 2022-03-02 → 2023-03-18]
50%|█████ | 53/105 [05:23<05:15, 6.06s/it, 2022-03-16 → 2023-04-01]
51%|█████▏ | 54/105 [05:29<05:10, 6.08s/it, 2022-03-30 → 2023-04-18]
52%|█████▏ | 55/105 [05:35<05:06, 6.13s/it, 2022-04-15 → 2023-05-05]
53%|█████▎ | 56/105 [05:41<04:59, 6.11s/it, 2022-04-29 → 2023-05-19]
54%|█████▍ | 57/105 [05:47<04:52, 6.10s/it, 2022-05-18 → 2023-06-02]
55%|█████▌ | 58/105 [05:54<04:47, 6.11s/it, 2022-06-01 → 2023-06-16]
56%|█████▌ | 59/105 [06:00<04:42, 6.14s/it, 2022-06-16 → 2023-07-04]
57%|█████▋ | 60/105 [06:06<04:37, 6.17s/it, 2022-06-30 → 2023-07-18]
58%|█████▊ | 61/105 [06:12<04:31, 6.16s/it, 2022-07-14 → 2023-08-01]
59%|█████▉ | 62/105 [06:18<04:24, 6.16s/it, 2022-07-28 → 2023-08-15]
60%|██████ | 63/105 [06:24<04:19, 6.17s/it, 2022-08-11 → 2023-08-29]
61%|██████ | 64/105 [06:31<04:14, 6.20s/it, 2022-08-25 → 2023-09-12]
62%|██████▏ | 65/105 [06:37<04:05, 6.15s/it, 2022-09-08 → 2023-09-26]
63%|██████▎ | 66/105 [06:43<03:58, 6.12s/it, 2022-09-23 → 2023-10-18]
64%|██████▍ | 67/105 [06:49<03:52, 6.13s/it, 2022-10-14 → 2023-11-01]
65%|██████▍ | 68/105 [06:55<03:47, 6.16s/it, 2022-10-28 → 2023-11-15]
66%|██████▌ | 69/105 [07:01<03:42, 6.19s/it, 2022-11-11 → 2023-11-29]
67%|██████▋ | 70/105 [07:08<03:38, 6.23s/it, 2022-11-25 → 2023-12-13]
68%|██████▊ | 71/105 [07:14<03:32, 6.26s/it, 2022-12-09 → 2023-12-27]
69%|██████▊ | 72/105 [07:20<03:27, 6.29s/it, 2022-12-23 → 2024-01-11]
70%|██████▉ | 73/105 [07:27<03:22, 6.32s/it, 2023-01-07 → 2024-01-25]
70%|███████ | 74/105 [07:33<03:16, 6.34s/it, 2023-01-21 → 2024-02-08]
71%|███████▏ | 75/105 [07:40<03:10, 6.35s/it, 2023-02-11 → 2024-03-01]
72%|███████▏ | 76/105 [07:46<03:03, 6.32s/it, 2023-02-25 → 2024-03-15]
73%|███████▎ | 77/105 [07:52<02:57, 6.35s/it, 2023-03-11 → 2024-03-29]
74%|███████▍ | 78/105 [07:59<02:51, 6.36s/it, 2023-03-25 → 2024-04-16]
75%|███████▌ | 79/105 [08:05<02:44, 6.34s/it, 2023-04-11 → 2024-04-30]
76%|███████▌ | 80/105 [08:11<02:37, 6.31s/it, 2023-04-25 → 2024-05-17]
77%|███████▋ | 81/105 [08:18<02:31, 6.32s/it, 2023-05-12 → 2024-05-31]
78%|███████▊ | 82/105 [08:24<02:25, 6.31s/it, 2023-05-26 → 2024-06-15]
79%|███████▉ | 83/105 [08:30<02:18, 6.30s/it, 2023-06-09 → 2024-06-29]
80%|████████ | 84/105 [08:36<02:12, 6.30s/it, 2023-06-27 → 2024-07-13]
81%|████████ | 85/105 [08:43<02:06, 6.32s/it, 2023-07-11 → 2024-07-27]
82%|████████▏ | 86/105 [08:49<02:00, 6.32s/it, 2023-07-25 → 2024-08-10]
83%|████████▎ | 87/105 [08:55<01:53, 6.32s/it, 2023-08-08 → 2024-08-24]
84%|████████▍ | 88/105 [09:02<01:48, 6.37s/it, 2023-08-22 → 2024-09-07]
85%|████████▍ | 89/105 [09:08<01:41, 6.36s/it, 2023-09-05 → 2024-09-25]
86%|████████▌ | 90/105 [09:15<01:35, 6.35s/it, 2023-09-19 → 2024-10-16]
87%|████████▋ | 91/105 [09:21<01:29, 6.36s/it, 2023-10-11 → 2024-10-30]
88%|████████▊ | 92/105 [09:27<01:22, 6.37s/it, 2023-10-25 → 2024-11-13]
89%|████████▊ | 93/105 [09:34<01:16, 6.39s/it, 2023-11-08 → 2024-11-27]
90%|████████▉ | 94/105 [09:40<01:10, 6.38s/it, 2023-11-22 → 2024-12-11]
90%|█████████ | 95/105 [09:47<01:04, 6.41s/it, 2023-12-06 → 2024-12-25]
91%|█████████▏| 96/105 [09:53<00:57, 6.40s/it, 2023-12-20 → 2025-01-09]
92%|█████████▏| 97/105 [09:59<00:51, 6.39s/it, 2024-01-04 → 2025-01-23]
93%|█████████▎| 98/105 [10:06<00:44, 6.35s/it, 2024-01-18 → 2025-02-14]
94%|█████████▍| 99/105 [10:12<00:38, 6.38s/it, 2024-02-01 → 2025-02-28]
95%|█████████▌| 100/105 [10:18<00:31, 6.37s/it, 2024-02-23 → 2025-03-14]
96%|█████████▌| 101/105 [10:25<00:25, 6.35s/it, 2024-03-08 → 2025-03-28]
97%|█████████▋| 102/105 [10:31<00:18, 6.32s/it, 2024-03-22 → 2025-04-15]
98%|█████████▊| 103/105 [10:37<00:12, 6.31s/it, 2024-04-09 → 2025-04-29]
99%|█████████▉| 104/105 [10:43<00:06, 6.29s/it, 2024-04-23 → 2025-05-16]
100%|██████████| 105/105 [10:50<00:00, 6.27s/it, 2024-04-23 → 2025-05-16]
100%|██████████| 105/105 [10:50<00:00, 6.19s/it, 2024-04-23 → 2025-05-16]
2025-06-25 19:33:28 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:463 - [v8] 优化前的夏普率: 0.74273
2025-06-25 19:33:28 | INFO | metric_online:run_optimize_portfolio_new_with_sector_constraints:464 - [v8] 优化后的夏普率: 0.94095
2025-06-25 19:33:28 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:29 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:29 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:30 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:32 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:33 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:33 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:34 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:35 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:37 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:37 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:37 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:38 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:38 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:38 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:39 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:41 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:41 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:42 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:43 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:43 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:44 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
2025-06-25 19:33:45 | WARNING | func_backtester_hf:run_sig2pos:1020 - The given signal has NaN. Will use 0 to fill
[2025-06-25 19:33:46,509][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:46,510][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:46,519][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:46,520][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:46,527][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:46,528][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:48,580][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:48,581][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:48,589][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:48,590][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:48,597][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:48,598][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:50,425][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:50,426][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:50,433][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:50,434][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:50,441][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
[2025-06-25 19:33:50,442][matplotlib.category][INFO] - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.
2025-06-25 19:33:54 | INFO | metric_online:run_with_hydra:919 - {'action': 'parallel_done', 'success_count': 1, 'fail_count': 0}
2025-06-25 19:33:54 | INFO | metric_online:run_with_hydra:924 - {'action': 'success', 'description': 'metric_online 完成'}