Incorporating Transformers and Attention Networks for Stock Movement Prediction
Predicting stock movements is a valuable research field that can help investors earn more profits. As with time-series data, the stock market is time-dependent and the value of historical information may decrease over time. Accurate prediction can be achieved by mining valuable information with word...
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| Principais autores: | , , , |
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| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
Wiley
2022-01-01
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| Serija: | Complexity |
| Online dostop: | http://dx.doi.org/10.1155/2022/7739087 |
| Oznake: |
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