Beyond Trend Following: Deep Learning for Market Trend Prediction
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866911960873828352 |
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| author | Berzal, Fernando Garcia, Alberto |
| author_facet | Berzal, Fernando Garcia, Alberto |
| contents | Trend following and momentum investing are common strategies employed by asset managers. Even though they can be helpful in the proper situations, they are limited in the sense that they work just by looking at past, as if we were driving with our focus on the rearview mirror. In this paper, we advocate for the use of Artificial Intelligence and Machine Learning techniques to predict future market trends. These predictions, when done properly, can improve the performance of asset managers by increasing returns and reducing drawdowns. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_13685 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Beyond Trend Following: Deep Learning for Market Trend Prediction Berzal, Fernando Garcia, Alberto Trading and Market Microstructure Artificial Intelligence Machine Learning Computational Finance Trend following and momentum investing are common strategies employed by asset managers. Even though they can be helpful in the proper situations, they are limited in the sense that they work just by looking at past, as if we were driving with our focus on the rearview mirror. In this paper, we advocate for the use of Artificial Intelligence and Machine Learning techniques to predict future market trends. These predictions, when done properly, can improve the performance of asset managers by increasing returns and reducing drawdowns. |
| title | Beyond Trend Following: Deep Learning for Market Trend Prediction |
| topic | Trading and Market Microstructure Artificial Intelligence Machine Learning Computational Finance |
| url | https://arxiv.org/abs/2407.13685 |