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

TL;DR

This paper introduces a novel AI-based model combining neural networks and genetic algorithms to accurately predict volatility in emerging stock markets, outperforming traditional methods.

Contribution

It presents a new consolidated model integrating back-propagation neural networks and genetic algorithms for stock market volatility prediction.

Findings

Predicted volatility with low error margins.

Model outperforms traditional volatility estimation methods.

Accurate predictions for emerging stock markets.

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.