Comparison of support-vector machines and back propagation neural networks in forecasting the six major Asian stock markets

Authors:
Wun-Hua Chen;Jen-Ying Shih;Soushan Wu
Affiliations:
Graduate Institute of Business Administration, National Taiwan University, No.1, Sec. 4, Roosevelt Road, Taipei 106, Taiwan, ROC.;Graduate Institute of Business Administration, National Taiwan University, No.1, Sec. 4, Roosevelt Road, Taipei 106, Taiwan, ROC.;College of Management, Chang-Gung University, 259, Wen-Hwa 1st Road, Taoyuang, Taiwan, ROC
Venue:
International Journal of Electronic Finance
Year:
2006

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Abstract

Recently, applying the novel data mining techniques for financial time-series forecasting has received much research attention. However, most researches are for the US and European markets, with only a few for Asian markets. This research applies Support-Vector Machines (SVMs) and Back Propagation (BP) neural networks for six Asian stock markets and our experimental results showed the superiority of both models, compared to the early researches.