An End-to-End Deep Learning Model for Clustering-Based Statistical Arbitrage
We propose an end-to-end deep learning framework for statistical arbitrage in the cryptocurrency futures market, which integrates clustering and trading within a unified structure. Statistical arbitrage seeks to exploit price deviations among similar assets to generate market-neutral profits. The cr...
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| Autors principals: | , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
IEEE
2026-01-01
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| Col·lecció: | IEEE Access |
| Matèries: | |
| Accés en línia: | https://ieeexplore.ieee.org/document/11456478/ |
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