Comparison of GARCH, Neural Network and Support Vector Machine in Financial Time Series Prediction

Authors:
Altaf Hossain;Faisal Zaman;M. Nasser;M. Mufakhkharul Islam
Affiliations:
Department of Statistics, Rajshahi University, Rajshahi, Bangladesh 6205;Department of System Design and Informatics, Kyushu Institute of Technology, Fukuka, Japan 820-8502;Department of Statistics, Rajshahi University, Rajshahi, Bangladesh 6205;Department of Computer Science & Engineering, BUET, Dhaka, Bangladesh 1000
Venue:
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Year:
2009

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Abstract

This article applied GARCH model instead AR or ARMA model to compare with the standard BP and SVM in forecasting of the four international including two Asian stock markets indices.These models were evaluated on five performance metrics or criteria. Our experimental results showed the superiority of SVM and GARCH models, compared to the standard BP in forecasting of the four international stock markets indices.