Proceedings of the Korean Operations and Management Science Society Conference (한국경영과학회:학술대회논문집)
- 1996.04a
- /
- Pages.745-748
- /
- 1996
Cascade-Correlation Network를 이용한 종합주가지수 예측
Abstract
Korea Composite Stock Price Index (KOSPI) was predicted using Cascade Correlation Network (CCN) model. CCN was suggested, by Fahlman and Lebiere [1990], to overcome the limitations of backpropagation algorithm such as step size problem and moving target problem. To test the applicability of CCN as a function approximator to the stock price movements, CCN was used as a tool for univariate time series analysis. The fitting and forecasting performance fo CCN on the KOSPI was compared with those of Multi-Layer Perceptron (MLP).
Keywords