Research Article
GLAD: Global–Local Approach; Disentanglement Learning for Financial Market Prediction
Table 2
Results of univariate price prediction on four datasets.
| Stock | End-to-end learning | Representation learning | Metric | Transformer [3] | Informer [5] | CoST [25] | GLAD_b | GLAD_c | GLAD_a | GLAD |
| S&P 500 index | MSE | 0.0037 | 0.0029 | 0.0038 | 0.0035 | (0.0026) | 0.0027 | 0.0025 | MAE | 0.0131 | 0.0125 | 0.0129 | 0.0128 | (0.0117) | 0.0121 | 0.0111 |
| Nikkei 225 | MSE | 0.0002 | 0.00015 | 0.0004 | 0.00018 | (0.00009) | 0.00012 | 0.00006 | MAE | 0.0017 | 0.0013 | 0.0019 | 0.0015 | 0.0006 | (0.0012) | 0.0006 |
| Hang Seng HSI | MSE | 0.0005 | 0.00045 | 0.00091 | 0.00049 | (0.00028) | 0.00039 | 0.00023 | MAE | 0.0025 | 0.0022 | 0.003 | 0.0023 | 0.0011 | (0.0016) | 0.0011 |
| CSI | MSE | 0.0004 | 0.00029 | 0.0009 | 0.00035 | (0.00019) | 0.00026 | 0.00015 | MAE | 0.0025 | 0.0021 | 0.0029 | 0.0022 | (0.0015) | 0.0018 | 0.0012 |
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The best results are highlighted in boldface, while the second-best results are enclosed within brackets.
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