Comparison of support-vector machines and back propagation neural networks in forecasting the six major Asian stock markets
AbstractRecently, 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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Bibliographic InfoArticle provided by Inderscience Enterprises Ltd in its journal Int. J. of Electronic Finance.
Volume (Year): 1 (2006)
Issue (Month): 1 ()
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Web page: http://www.inderscience.com/browse/index.php?journalID=171
financial forecasting; support vector machines; SVMs; backpropagation neural networks; Asian stock markets; data mining; electronic finance; e-finance.;
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- Duan, Wen-Qi & Stanley, H. Eugene, 2011. "Cross-correlation and the predictability of financial return series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 290-296.
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