Automating Stock Prediction with Neural Network and Evolutionary Computation

Abstract

In the previous studies [1, 2, 3], it has been found that there is strong correlation between the US market and the Asian markets in the long run. The VAR analysis shows that the US indices lead the Asian ones. But, such correlation is time-dependent and affects the performance of using the historical US data to predict the Asian markets by neural network. Here, a simplified automated system is outlined to overcome this difficulty by employing the evolutionary computation to simulate the markets interactive dynamics. The aim is to supplement the previous studies like [4, 5], which have focused more or less solely on the local stock market's historical data, with additional information from other leading markets' movements. © Springer-Verlag 2003.