A fuzzy time series-based neural network approach to option price forecasting
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part I
A hybrid modeling approach for forecasting the volatility of S&P 500 index return
Expert Systems with Applications: An International Journal
Using neural network for forecasting TXO price under different volatility models
Expert Systems with Applications: An International Journal
Computers and Electronics in Agriculture
Heavy-tailed mixture GARCH volatility modeling and Value-at-Risk estimation
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
This study integrated new hybrid asymmetric volatility approach into artificial neural networks option-pricing model to improve forecasting ability of derivative securities price. Owing to combines the new hybrid asymmetric volatility method can be reduced the stochastic and nonlinearity of the error term sequence and captured the asymmetric volatility simultaneously. Hence, in the ANNS option-pricing model, the results demonstrate that Grey-GJR-GARCH volatility provides higher predictability than other volatility approaches.