Use of Feed-Forword Neural Network for Stock Market Value Prediction

Neural networks are presenting an interesting alternative to traditional concepts for solving problems with regard to prediction of stock market values. It has ability to identify pattern and has a techniques to accurately solve complex processes, especially in financial forecasting it is very useful tool to predict stock market value. In this paper we evaluate the performance of back- propagation neural networks model and established a stock market value prediction model. The past stock market prices are used in order to predict the values for the future stock market. In order to do that our past data contains not only past companies stock values but also the various factors that make effects on company's stock values. The results obtained lead to the conclusion that neural networks can be considered as useful instruments to analysis or predict values of a companies.