A prediction based approach for stock returns using autoregressive neural networks

This paper presents a prediction based neural networks approach for stock returns. An autoregressive neural network predictor is used to predict future stock returns. In this predictor, the differences between the values of the series of stock returns and a specified past value are the regression variables. Various error metrics have been used to evaluate the performance of the predictor. Experiments with real data from National stock exchange of India (NSE) were employed to examine the accuracy of this method.