Back Propagation Neural Networks in Financial Analysis Of Stock Market Returns

In this paper, we showed a method to forecast the stock price using neural networks. Predicting the stock market is very difficult since it depends on several known and unknown factors. In recent years, one of the techniques that have been used popularly in this area is artificial neural network. The power of neural network is its ability to model a nonlinear process without a priori knowledge about the nature of the process. We used back propagation neural network, to make the prediction. The objective of this study is to find out the effect of daily Exchange rate, FII Purchase, FII Sales on daily Closing Return of NIFTY by using back propagation Neural Network. The accuracy measure of prediction is defined in terms of the forecasting error, which is the difference between the actual and predicted value.