PREDICTION OF STOCK VALUES IN STOCK MARKET USING ARTIFICIAL NEURAL NETWORK

Abstract

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.