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upd: 重新运行了执行脚本
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Lines changed: 43 additions & 60 deletions

‎plots/alpha054_backtest.png‎

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‎plots/alpha054_ic.png‎

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‎plots/feature_importance.png‎

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‎plots/ml_alpha_backtest.png‎

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‎plots/ml_alpha_ic.png‎

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‎plots/shap_beeswarm.png‎

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‎plots/synthetic_factor_backtest.png‎

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‎plots/synthetic_factor_ic.png‎

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‎result.txt‎

Lines changed: 12 additions & 30 deletions
Original file line numberDiff line numberDiff line change
@@ -3,7 +3,7 @@
33
Step 1 / 5 — Loading Parquet files
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==============================================================
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[OK] prices.parquet : 361,333 rows | cols: ['trade_date', 'ts_code', 'open', 'high', 'low', 'close', 'volume', 'adj_factor', 'tradable']
6-
[OK] factors_clean : 364,200 rows | factors: ['alpha001', 'alpha003', 'alpha006', 'alpha012', 'alpha038', 'alpha040', 'alpha041', 'alpha042', 'alpha054', 'alpha072', 'alpha088', 'alpha094', 'alpha098', 'alpha101', 'alpha_5_day_reversal']
6+
[OK] factors_clean : 364,200 rows | factors: ['alpha001', 'alpha003', 'alpha006', 'alpha012', 'alpha038', 'alpha040', 'alpha041', 'alpha042', 'alpha072', 'alpha088', 'alpha094', 'alpha098', 'alpha101', 'alpha_5_day_reversal']
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==============================================================
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Step 2 / 5 — Computing 1-day forward return
@@ -149,23 +149,6 @@ G5 0.9105 0.1440 0.1821 0.6257 -0.2039
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L-S 2.2566 0.2780 0.0818 3.0317 -0.0534
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[ ] Backtest plot saved.
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>>> SELECTED [forward] (|IC mean| > 2.0% & |ICIR| > 0.3)
152-
--------------------------------------------------------------
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Factor: alpha054
154-
--------------------------------------------------------------
155-
[ ] IC Mean : +0.0411
156-
[ ] IC Std : 0.0817
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[ ] ICIR : +0.5023
158-
[ ] IC chart saved.
159-
[ ] Backtest metrics:
160-
Cum Return Ann Return Ann Vol Sharpe Max DD
161-
G1 -0.6076 -0.1766 0.1809 -1.1424 -0.6949
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G2 0.0688 0.0139 0.1914 -0.0841 -0.3231
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G3 0.2976 0.0556 0.1940 0.1320 -0.2254
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G4 0.8370 0.1347 0.1958 0.5346 -0.2249
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G5 1.7298 0.2320 0.1928 1.0479 -0.2275
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L-S 5.9245 0.4948 0.0755 6.1584 -0.0416
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[ ] Backtest plot saved.
168-
>>> SELECTED [forward] (|IC mean| > 2.0% & |ICIR| > 0.3)
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--------------------------------------------------------------
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Factor: alpha072
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--------------------------------------------------------------
@@ -272,31 +255,30 @@ L-S -0.6170 -0.1807 0.1039 -2.0284 -0.6419
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==============================================================
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Step 4 / 5 — Results summary
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==============================================================
275-
[OK] Effective alphas (4 / 15):
258+
[OK] Effective alphas (3 / 14):
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* alpha038
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* alpha042
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* alpha054
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* alpha101
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==============================================================
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Step 5 / 5 — Synthetic factor
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==============================================================
284-
[ ] Effective alphas: ['alpha038', 'alpha042', 'alpha054', 'alpha101']
266+
[ ] Effective alphas: ['alpha038', 'alpha042', 'alpha101']
285267
[ ] Rolling window = 3 trading days | orthogonalize = True
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[ ] OLS target: cross-sectional pct-rank of forward_return (per trade_date)
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[OK] Synthetic factor : 356,919 rows (dates: 1209)
288-
[ ] IC Mean : +0.0245
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[ ] IC Std : 0.0860
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[ ] ICIR : +0.2851
270+
[ ] IC Mean : +0.0221
271+
[ ] IC Std : 0.0882
272+
[ ] ICIR : +0.2512
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[ ] IC chart saved.
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[ ] Backtest metrics (synthetic factor):
293275
Cum Return Ann Return Ann Vol Sharpe Max DD
294-
G1 -0.2994 -0.0715 0.1888 -0.5376 -0.4560
295-
G2 -0.0324 -0.0068 0.1935 -0.1904 -0.3147
296-
G3 0.2043 0.0395 0.1913 0.0497 -0.2522
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G4 0.6019 0.1032 0.1945 0.3763 -0.2423
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G5 0.7735 0.1269 0.1870 0.5178 -0.2178
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L-S 1.4863 0.2091 0.0818 2.1899 -0.1054
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G1 -0.2665 -0.0626 0.1880 -0.4924 -0.4327
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G2 0.0353 0.0073 0.1942 -0.1171 -0.3024
278+
G3 0.1772 0.0346 0.1941 0.0236 -0.2576
279+
G4 0.6332 0.1077 0.1910 0.4065 -0.2320
280+
G5 0.5872 0.1011 0.1881 0.3779 -0.2184
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L-S 1.1280 0.1705 0.0833 1.6866 -0.0926
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[ ] Synthetic backtest plot saved.
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==============================================================

‎result_ml.txt‎

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Original file line numberDiff line numberDiff line change
@@ -3,14 +3,14 @@
33
Stage 3 · LightGBM Alpha Synthesis
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======================================================================
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1. Loading factors_clean.parquet and prices.parquet ...
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factors shape : (364200, 17)
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factors shape : (364200, 16)
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prices shape : (361333, 9)
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2. Computing 1-day forward returns ...
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3. Merging factors and target labels ...
12-
merged shape : (357978, 19)
13-
feature cols : ['alpha001', 'alpha003', 'alpha006', 'alpha012', 'alpha038', 'alpha040', 'alpha041', 'alpha042', 'alpha054', 'alpha072', 'alpha088', 'alpha094', 'alpha098', 'alpha101', 'alpha_5_day_reversal']
12+
merged shape : (357978, 18)
13+
feature cols : ['alpha001', 'alpha003', 'alpha006', 'alpha012', 'alpha038', 'alpha040', 'alpha041', 'alpha042', 'alpha072', 'alpha088', 'alpha094', 'alpha098', 'alpha101', 'alpha_5_day_reversal']
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training target : cs_rank_return (cross-sectional pct-rank of forward_return, per trade_date)
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======================================================================
@@ -23,19 +23,19 @@
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Train : 20190102 → 20210126 (n=148,726)
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Val : 20210127 → 20210804 (n=37,069)
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Test : 20210806 → 20220216 (n=37,143)
26-
Best iteration : 256
26+
Best iteration : 375
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--- Fold 2 ---
2929
Train : 20190711 → 20210804 (n=148,587)
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Val : 20210805 → 20220215 (n=37,141)
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Test : 20220217 → 20220819 (n=37,176)
32-
Best iteration : 309
32+
Best iteration : 272
3333

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--- Fold 3 ---
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Train : 20200114 → 20220215 (n=148,263)
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Val : 20220216 → 20220818 (n=37,180)
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Test : 20220822 → 20230301 (n=37,325)
38-
Best iteration : 523
38+
Best iteration : 512
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--- Fold 4 ---
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Train : 20200724 → 20220818 (n=148,506)
@@ -52,9 +52,9 @@
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======================================================================
5353
IC Analysis — ML Synthetic Factor
5454
======================================================================
55-
IC Mean : +0.0487
56-
IC Std : 0.0952
57-
ICIR : +0.5111
55+
IC Mean : +0.0408
56+
IC Std : 0.0976
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ICIR : +0.4181
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IC chart saved: plots/ml_alpha_ic.png
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@@ -65,12 +65,12 @@
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Layered Backtest Performance:
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Cum Return Ann Return Ann Vol Sharpe Max DD
68-
G1 -0.4388 -0.2509 0.1652 -1.7003 -0.5174
69-
G2 -0.1964 -0.1036 0.1705 -0.7836 -0.3163
70-
G3 0.0617 0.0304 0.1764 0.0023 -0.2096
71-
G4 0.2188 0.1040 0.1741 0.4249 -0.1910
72-
G5 0.2576 0.1214 0.1803 0.5072 -0.2516
73-
L-S 1.2341 0.4947 0.0860 5.4008 -0.0465
68+
G1 -0.3554 -0.1971 0.1685 -1.3483 -0.4388
69+
G2 -0.1707 -0.0893 0.1723 -0.6926 -0.3107
70+
G3 0.0052 0.0026 0.1706 -0.1605 -0.2532
71+
G4 0.2430 0.1149 0.1745 0.4867 -0.1900
72+
G5 0.0984 0.0481 0.1810 0.0998 -0.2617
73+
L-S 0.6958 0.3022 0.0937 2.9057 -0.0705
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======================================================================
7676
Feature Importance (Average Across Folds)
@@ -79,21 +79,20 @@ L-S 1.2341 0.4947 0.0860 5.4008 -0.0465
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Average Feature Importance (gain):
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feature importance
82-
alpha054 25110.419238
83-
alpha038 12946.020555
84-
alpha042 11686.292860
85-
alpha001 10953.655643
86-
alpha041 10693.001562
87-
alpha_5_day_reversal 10024.856125
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alpha094 9078.336584
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alpha012 8917.858967
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alpha101 7988.279771
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alpha088 7785.137905
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alpha040 6769.942058
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alpha006 6702.127287
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alpha003 6598.467297
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alpha072 6597.052841
96-
alpha098 5786.490685
82+
alpha038 16416.840166
83+
alpha042 14913.898594
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alpha101 13674.561351
85+
alpha001 11784.384745
86+
alpha_5_day_reversal 11044.904249
87+
alpha094 10820.675615
88+
alpha041 10362.990039
89+
alpha012 9329.971928
90+
alpha006 8006.049540
91+
alpha088 7989.620811
92+
alpha072 7626.667360
93+
alpha040 7525.093853
94+
alpha003 7425.743840
95+
alpha098 6695.153339
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Saved: plots/feature_importance.png
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