Integrating Generative AI into Financial Market Prediction for Improved Decision Making
Fuente:
arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866911827924877312 |
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| author | Che, Chang Huang, Zengyi Li, Chen Zheng, Haotian Tian, Xinyu |
| author_facet | Che, Chang Huang, Zengyi Li, Chen Zheng, Haotian Tian, Xinyu |
| contents | This study provides an in-depth analysis of the model architecture and key technologies of generative artificial intelligence, combined with specific application cases, and uses conditional generative adversarial networks ( cGAN ) and time series analysis methods to simulate and predict dynamic changes in financial markets. The research results show that the cGAN model can effectively capture the complexity of financial market data, and the deviation between the prediction results and the actual market performance is minimal, showing a high degree of accuracy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_03523 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Integrating Generative AI into Financial Market Prediction for Improved Decision Making Che, Chang Huang, Zengyi Li, Chen Zheng, Haotian Tian, Xinyu Computational Engineering, Finance, and Science This study provides an in-depth analysis of the model architecture and key technologies of generative artificial intelligence, combined with specific application cases, and uses conditional generative adversarial networks ( cGAN ) and time series analysis methods to simulate and predict dynamic changes in financial markets. The research results show that the cGAN model can effectively capture the complexity of financial market data, and the deviation between the prediction results and the actual market performance is minimal, showing a high degree of accuracy. |
| title | Integrating Generative AI into Financial Market Prediction for Improved Decision Making |
| topic | Computational Engineering, Finance, and Science |
| url | https://arxiv.org/abs/2404.03523 |