A Consolidated Volatility Prediction with Back Propagation Neural Network and Genetic Algorithm
Fuente:
arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866914006607855616 |
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| author | Ke, Zong Xu, Jingyu Zhang, Zizhou Cheng, Yu Wu, Wenjun |
| author_facet | Ke, Zong Xu, Jingyu Zhang, Zizhou Cheng, Yu Wu, Wenjun |
| contents | This paper provides a unique approach with AI algorithms to predict emerging stock markets volatility. Traditionally, stock volatility is derived from historical volatility,Monte Carlo simulation and implied volatility as well. In this paper, the writer designs a consolidated model with back-propagation neural network and genetic algorithm to predict future volatility of emerging stock markets and found that the results are quite accurate with low errors. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_07223 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Consolidated Volatility Prediction with Back Propagation Neural Network and Genetic Algorithm Ke, Zong Xu, Jingyu Zhang, Zizhou Cheng, Yu Wu, Wenjun Computational Finance Machine Learning Neural and Evolutionary Computing This paper provides a unique approach with AI algorithms to predict emerging stock markets volatility. Traditionally, stock volatility is derived from historical volatility,Monte Carlo simulation and implied volatility as well. In this paper, the writer designs a consolidated model with back-propagation neural network and genetic algorithm to predict future volatility of emerging stock markets and found that the results are quite accurate with low errors. |
| title | A Consolidated Volatility Prediction with Back Propagation Neural Network and Genetic Algorithm |
| topic | Computational Finance Machine Learning Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2412.07223 |