A comparison of forecasting the index of the Korean stock market

Young Geun Shin, Sang Sung Park, Dong Sik Jang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

According to the increase of an impact foreigner investor have on the Korean stock market, it is very importance to analyze the investment pattern of the foreigner investors in order to predict the movement of the Korean stock market. Firstly, in this study we collected various factors which influence the Korean stock market in the previous literatures about the movement of stock market. Secondly, Factors which influence significantly to KOPSI 200 Index among the collected factors are extracted through the stepwise selection used in regression analysis. Finally we predicted the movement of the Korean stock market using Back-Propagation Neural Network (BPN) and Support Vector Machine (SVM). And we have done a comparison analysis of obtained results through these methods. As a result of the experiments, prediction accuracy using SVM showed better result than using BPN.

Original languageEnglish
Title of host publicationComputational Methods in Science and Engineering - Advances in Computational Science, Lectures Presented at the Int. Conference on Computational Methods in Science and Engineering 2008, ICCMSE 2008
Pages225-228
Number of pages4
DOIs
Publication statusPublished - 2009
Event6th International Conference on Computational Methods in Sciences and Engineering 2008, ICCMSE 2008 - Hersonissos, Crete, Greece
Duration: 2008 Sep 252008 Sep 30

Publication series

NameAIP Conference Proceedings
Volume1148 2
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Other

Other6th International Conference on Computational Methods in Sciences and Engineering 2008, ICCMSE 2008
CountryGreece
CityHersonissos, Crete
Period08/9/2508/9/30

Keywords

  • Forecasting
  • Neural Network
  • Stock Market Index
  • Support Vector Machine

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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