Forecasting of Stock Prices Using Multi Layer Perceptron

Prediction of stock market has been a challenging task and of great interest for researchers as the very fact that stock market is a highly volatile in its behavior. For predicting stock price of Bombay Stock Exchange (BSE), Multilayer Networks with dynamic back propagation has been used. The stock prices are determined and compared with two different architectures NN1 (3-16-1) and NN2 (3-6-1). Neural Network based forecasting of stock prices of selected sectors under Bombay Stock Exchange show that neural networks have the power to predict prices albeit the volatility in the markets. The paper is organized as follows. In Section one the volatile nature of stock market is discussed. Section two reviews the literature on the applications of ANNs in predicting the stock prices. Section three gives an overview of forecasting methods. In Section four the concept of Artificial Neural Network presented. Section five presents the methodology adopted in forecasting the stock price. In the final section results, future direction of the study and conclusion are derived