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

  • Wun-Hua Chen
  • Jen-Ying Shih
  • Soushan Wu
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    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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    File URL: http://www.inderscience.com/link.php?id=8837
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    Article provided by Inderscience Enterprises Ltd in its journal Int. J. of Electronic Finance.

    Volume (Year): 1 (2006)
    Issue (Month): 1 ()
    Pages: 49-67

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    Handle: RePEc:ids:ijelfi:v:1:y:2006:i:1:p:49-67
    Contact details of provider: Web page: http://www.inderscience.com/browse/index.php?journalID=171

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