International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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A Comparative Study on the Prediction of KOSPI 200 Using Intelligent Approaches

  • Bae, Hyeon (School of Electrical and Computer Engineering, Pusan National University) ;
  • Kim, Sung-Shin (School of Electrical and Computer Engineering, Pusan National University) ;
  • Kim, Hae-Gyun (Air Conditioning Division, Digital Appliance Company, LG Electronics) ;
  • Woo, Kwang-Bang (Automation Technology Research Institute, Yonsei University)
  • Published : 2003.06.01
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Abstract

In recent years, many attempts have been made to predict the behavior of bonds, currencies, stock or other economic markets. Most previous experiments used the neural network models for the stock market forecasting. The KOSPI 200 (Korea Composite Stock Price Index 200) is modeled by using different neural networks and fuzzy logic. In this paper, the neural network, the dynamic polynomial neural network (DPNN) and the fuzzy logic employed for the prediction of the KOSPI 200. The prediction results are compared by the root mean squared error (RMSE) and scatter plot, respectively. The results show that the performance of the fuzzy system is little bit worse than that of the DPNN but better than that of the neural network. We can develop the desired fuzzy system by optimization methods.

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