STOCK PREDICTION SYSTEM USING ANN

Mahesh Korade, Sujata Gutte, Asha Thorat, Rohini Sonawane

Abstract: Prediction of stock market returns is an important issue in finance. Artificial neural networks have been used in stock market prediction during the last decade. Predicting anything is very hard especially if the relationship between the inputs and outputs are non-linear in nature and stock price prediction is one of them. In this paper we have proposed stock prediction system, in this stock price prediction using multi-layer feed forward Artificial Neural Network (ANN). In this model we have used back propagation algorithm of ANN. As the closing price of any stock market already covers other attributes of the company, we have used historical stock prices (closing) for training the neural network. This paper was aimed at finding the best model for the prediction of Stock Exchange market values

Keywords: Stock market prediction, neural network, back propagation, Client-server architecture, Neuron

DOI: https://doi.org/10.15623/ijret.2014.0304132