Forecasting Stock Market with Neural Networks

Prediction of stock market returns is an important issue in finance. The aim of this paper is to investigate the profitability of using artificial neural networks (ANNs). In this study, the ANNs predictions are transformed into a simple trading strategy, whose profitability is evaluated against a simple buy-hold strategy. We adopt the neural network approach to analyze the Taiwan Weighted Index and the Samp;P 500 in the States. Consequently, we find that the trading rule based on ANNs generates higher returns than the buy-hold strategy