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 language | English |
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Pages (from-to) | 49-67 |
Number of pages | 19 |
Journal | International Journal of Electronic Finance |
Volume | 1 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2006 |
Externally published | Yes |
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