New hybrid methodology for stock volatility prediction

Authors:
Chih-Hsiung Tseng;Sheng-Tzong Cheng;Yi-Hsien Wang
Affiliations:
Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan, ROC;Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan, ROC;Department of Finance, Yuanpei University, Hsin Chu 300, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Sequential combination of statistics, econometrics and Adaptive Neural-Fuzzy Interface for stock market prediction

Expert Systems with Applications: An International Journal

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Abstract

Modeling and forecasting stock market volatility have received considerable attention by both academics and practitioners. Hence, this paper presents integrated model to improve the variance forecasting ability in variance as compared to the traditional GARCH. Overall, the results show that the new integrated model can enhance the volatility forecasting ability of the traditional GARCH.