Title: 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

Addresses: 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

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.

Keywords: financial forecasting; support vector machines; SVMs; backpropagation neural networks; Asian stock markets; data mining; electronic finance; e-finance.

DOI: 10.1504/IJEF.2006.008837

International Journal of Electronic Finance, 2006 Vol.1 No.1, pp.49 - 67

Published online: 31 Jan 2006 *

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