A Study on Determining the Prediction Models for Predicting Stock Price Movement

주가 운동양태 예측을 위한 예측 모델결정에 관한 연구

  • 전진호 (단국대학교 전자계산학과) ;
  • 조영희 (단국대학교 전자계산학과) ;
  • 이계성 (단국대학교 전자계산학과)
  • Published : 2006.06.01


Predictions on stock prices have been a hot issue in stock market as people get more interested in stock investments. Assuming that the stock price is moving by a trend in a specific pattern, we believe that a model can be derived from past data to describe the change of the price. The best model can help predict the future stock price. In this paper, our model derivation is based on automata over temporal data to which the model is explicable. We use Bayesian Information Criterion(BIC) to determine the best number of states of the model. We confirm the validity of Bayesian Information Criterion and apply it to building models over stock price indices. The model derived for predicting daily stock price are compared with real price. The comparisons show the predictions have been found to be successful over the data sets we chose.