An Examination of Artificial Neural Network Predictions for the Stock Market

Abstract

Since from last 10 to 15 years neural networks are increasingly applied in the field of finance. Neural network is one of the popular methods of Artificial intelligence. Neural network is becoming very popular and important for making predictions in stock market. NN has proved many advantages over contemporary methods. Comparative analysis are done to identify the advantages and limitations of Neural Networks against contemporary methods and it is observed that NN is better suited for stock price forecasting, finding returns on investments, etc. It os observed that Backpropagation method/model is most widely used by researchers. This paper surveys the application of neural networks for stock market predictions. The outcome of this study concludes that ANNs are performing significantly better than multi linear regression analysis, genetic algorithms and other contemporary methods.