A Consolidated Volatility Prediction with Back Propagation Neural Network and Genetic Algorithm

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.

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Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/icicml63543.2024.10958142
Citations
14
Primary Topic
Advanced Algorithms and Applications
Type
article
Field-Weighted Citation Impact
4.60
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article

A Consolidated Volatility Prediction with Back Propagation Neural Network and Genetic Algorithm

Zong Ke, Jingyun Xu, Yu Cheng, Wenjun Wu et al.
14 citations
Advanced Algorithms and Applications
4.60
article

A Consolidated Volatility Prediction with Back Propagation Neural Network and Genetic Algorithm

Zong Ke, Jingyun Xu, Yu Cheng, Wenjun Wu, Zizhou Zhang
article en
14 citations

Abstract

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.

University of Illinois Urbana-Champaign (US), National University of Singapore (SG), Northern Arizona University (US), Columbia University (US)
Openalex Percentile: Top 5%
Advanced Algorithms and Applications
4.60
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