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

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.

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Year of publication:	2006
Authors:	Chen, Wun-Hua ; Shih, Jen-Ying ; Wu, Soushan
Published in:	International Journal of Electronic Finance. - Inderscience Enterprises Ltd, ISSN 1746-0069. - Vol. 1.2006, 1, p. 49-67
Publisher:	Inderscience Enterprises Ltd
Subject:	financial forecasting \| support vector machines \| SVMs \| backpropagation neural networks \| Asian stock markets \| data mining \| electronic finance \| e-finance

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Extent:	text/html
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10008539373