Forecasting S&P 500 stock index futures with a hybrid AI system
Decision Support Systems
A hybrid genetic-neural architecture for stock indexes forecasting
Information Sciences: an International Journal - Special issue: Computational intelligence in economics and finance
Review: Expert systems and evolutionary computing for financial investing: A review
Expert Systems with Applications: An International Journal
Volatility model based on multi-stock index for TAIEX forecasting
Expert Systems with Applications: An International Journal
Forecasting box office revenue of movies with BP neural network
Expert Systems with Applications: An International Journal
Testing the significance of solar term effect in the Taiwan stock market
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A hybrid forecast marketing timing model based on probabilistic neural network, rough set and C4.5
Expert Systems with Applications: An International Journal
A hybrid model based on rough sets theory and genetic algorithms for stock price forecasting
Information Sciences: an International Journal
A hybrid ANFIS model based on AR and volatility for TAIEX forecasting
Applied Soft Computing
Predicting stock returns by classifier ensembles
Applied Soft Computing
Early warning of enterprise decline in a life cycle using neural networks and rough set theory
Expert Systems with Applications: An International Journal
Using artificial neural network models in stock market index prediction
Expert Systems with Applications: An International Journal
Analysis of chain reaction between two stock indices fluctuations by statistical physics systems
WSEAS Transactions on Mathematics
Expert Systems with Applications: An International Journal
A hybrid modeling approach for forecasting the volatility of S&P 500 index return
Expert Systems with Applications: An International Journal
Application of polynomial projection ensembles to hedging crude oil commodity risk
Expert Systems with Applications: An International Journal
Volatility forecast using hybrid Neural Network models
Expert Systems with Applications: An International Journal
| Hi-index | 12.07 |
Accurate volatility forecasting is the core task in the risk management in which various portfolios' pricing, hedging, and option strategies are exercised. Prior studies on stock market have primarily focused on estimation of stock price index by using financial time series models and data mining techniques. This paper proposes hybrid models with neural network and time series models for forecasting the volatility of stock price index in two view points: deviation and direction. It demonstrates the utility of the hybrid model for volatility forecasting. This model demonstrates the utility of the neural network forecasting combined with time series analysis for the financial goods.