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Benchmarks Performance
Here are the results of each benchmark model running on Qlib's Alpha360 and Alpha158 dataset with China's A shared-stock & CSI300 data respectively. The values of each metric are the mean and std calculated based on 10 runs.
The numbers shown below demonstrate the performance of the entire workflow of each model. We will update the workflow as well as models in the near future for better results.
Alpha360 dataset
| Model Name | Dataset | IC | ICIR | Rank IC | Rank ICIR | Annualized Return | Information Ratio | Max Drawdown |
|---|---|---|---|---|---|---|---|---|
| Linear | Alpha360 | 0.0150±0.00 | 0.1049±0.00 | 0.0284±0.00 | 0.1970±0.00 | -0.0655±0.00 | -0.6985±0.00 | -0.2961±0.00 |
| CatBoost | Alpha360 | 0.0397±0.00 | 0.2878±0.00 | 0.0470±0.00 | 0.3703±0.00 | 0.0342±0.00 | 0.4092±0.00 | -0.1057±0.00 |
| XGBoost | Alpha360 | 0.0400±0.00 | 0.3031±0.00 | 0.0461±0.00 | 0.3862±0.00 | 0.0528±0.00 | 0.6307±0.00 | -0.1113±0.00 |
| LightGBM | Alpha360 | 0.0399±0.00 | 0.3075±0.00 | 0.0492±0.00 | 0.4019±0.00 | 0.0323±0.00 | 0.4370±0.00 | -0.0917±0.00 |
| MLP | Alpha360 | 0.0253±0.01 | 0.1954±0.05 | 0.0329±0.00 | 0.2687±0.04 | 0.0161±0.01 | 0.1989±0.19 | -0.1275±0.03 |
| GRU | Alpha360 | 0.0503±0.01 | 0.3946±0.06 | 0.0588±0.00 | 0.4737±0.05 | 0.0799±0.02 | 1.0940±0.26 | -0.0810±0.03 |
| LSTM | Alpha360 | 0.0466±0.01 | 0.3644±0.06 | 0.0555±0.00 | 0.4451±0.04 | 0.0783±0.05 | 1.0539±0.65 | -0.0844±0.03 |
| ALSTM | Alpha360 | 0.0472±0.00 | 0.3558±0.04 | 0.0577±0.00 | 0.4522±0.04 | 0.0522±0.02 | 0.7090±0.32 | -0.1059±0.03 |
| GATs | Alpha360 | 0.0480±0.00 | 0.3555±0.02 | 0.0598±0.00 | 0.4616±0.01 | 0.0857±0.03 | 1.1317±0.42 | -0.0917±0.01 |
Alpha158 dataset
| Model Name | Dataset | IC | ICIR | Rank IC | Rank ICIR | Annualized Return | Information Ratio | Max Drawdown |
|---|---|---|---|---|---|---|---|---|
| Linear | Alpha158 | 0.0393±0.00 | 0.2980±0.00 | 0.0475±0.00 | 0.3546±0.00 | 0.0795±0.00 | 1.0712±0.00 | -0.1449±0.00 |
| CatBoost | Alpha158 | 0.0503±0.00 | 0.3586±0.00 | 0.0483±0.00 | 0.3667±0.00 | 0.1080±0.00 | 1.1567±0.00 | -0.0787±0.00 |
| XGBoost | Alpha158 | 0.0481±0.00 | 0.3659±0.00 | 0.0495±0.00 | 0.4033±0.00 | 0.1111±0.00 | 1.2915±0.00 | -0.0893±0.00 |
| LightGBM | Alpha158 | 0.0475±0.00 | 0.3979±0.00 | 0.0485±0.00 | 0.4123±0.00 | 0.1143±0.00 | 1.2744±0.00 | -0.0800±0.00 |
| MLP | Alpha158 | 0.0363±0.00 | 0.2770±0.02 | 0.0421±0.00 | 0.3167±0.01 | 0.0856±0.01 | 1.0397±0.12 | -0.1134±0.01 |
| TFT | Alpha158 (with selected 20 features) | 0.0335±0.00 | 0.2009±0.01 | 0.0090±0.00 | 0.0553±0.01 | 0.0605±0.01 | 0.5438±0.12 | -0.1772±0.03 |
| GRU | Alpha158 (with selected 20 features) | 0.0313±0.00 | 0.2427±0.01 | 0.0416±0.00 | 0.3370±0.01 | 0.0335±0.01 | 0.4808±0.22 | -0.1112±0.03 |
| LSTM | Alpha158 (with selected 20 features) | 0.0337±0.01 | 0.2562±0.05 | 0.0427±0.01 | 0.3392±0.04 | 0.0269±0.06 | 0.3385±0.74 | -0.1285±0.04 |
| ALSTM | Alpha158 (with selected 20 features) | 0.0366±0.00 | 0.2803±0.04 | 0.0478±0.00 | 0.3770±0.02 | 0.0520±0.03 | 0.7115±0.30 | -0.0986±0.01 |
| GATs | Alpha158 (with selected 20 features) | 0.0355±0.00 | 0.2576±0.02 | 0.0465±0.00 | 0.3585±0.00 | 0.0509±0.02 | 0.7212±0.22 | -0.0821±0.01 |