A novel transformer-based dual attention architecture for the prediction of financial time series
Abstract Financial prediction has gained significant attention due to the complex and non-linear dynamics of the market. A promising approach for generating accurate predictions is Transformers. Encoder-decoder structures efficiently capture complex temporal dependencies and patterns within large-sc...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-06-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44443-025-00045-y |
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