A Consolidated Volatility Prediction with Back Propagation Neural Network and Genetic Algorithm
This addresses volatility prediction for investors in emerging markets, but it appears incremental as it combines existing AI methods.
The paper tackled predicting volatility in emerging stock markets by designing a consolidated model using back-propagation neural network and genetic algorithm, resulting in accurate predictions with low errors.
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.