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

Research output: Contribution to journalArticlepeer-review

81 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)49-67
Number of pages19
JournalInternational Journal of Electronic Finance
Volume1
Issue number1
DOIs
Publication statusPublished - 2006
Externally publishedYes

Keywords

  • Asian stock markets
  • Back Propagation (BP) neural networks
  • Financial forecasting
  • Support-Vector Machines (SVMs)

ASJC Scopus subject areas

  • Finance
  • Computer Science Applications
  • Computer Networks and Communications
  • Management of Technology and Innovation

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