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International Journal of Soft Computing And Artificial Intelligence (IJSCAI)-IJSCAI
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Volume Issue
Volume-5,Issue-1  ( May, 2017 )
Paper Title
Artificial Neural Network (ANN) Based Prediction of Stock Closing Price in NSE of India
Author Name
G. G. Rajput, Bhagwat H. Kaulwar
Department of Computer Science, Rani Channamma University, Belagavi, India Deparment of Computer Science, Solapur University, Solapur, India
The profitability of investing and trading in stock market to a large extent depends on predictability. It is of utmost need to develop a system which can consistently predict trends of the dynamic stock market to help investors in decision making. Artificial Neural Network (ANN) is a popular way to identify unknown and hidden patterns in data which is suitable for share market prediction. NARX network, a special class of ANN, can be designed for every company registered at BSE/NSE to predict share prices and thereby help investors in decision making. In this paper, we introduce a method using Multilayer Feed-Forward NARX network to predict closing price of a share listed in NSE, in particular for SBI. NARX network has been trained using stock data of SBI, encompassing trading days from 02nd January 2012 to 31st December 2012 and prediction level has been discussed for year 2013. Keywords - Artificial Neural Network (ANN), Nonlinear Autoregressive with External Input (NARX), stock price prediction, technical analysis, Gradient descent adaptive back-propagation (GDA)
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