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International Journal of Statistika And Mathematika, ISSN:2249-8605

Volume 1, Issue 1, 2011 pp 08-15

Date of Publish: 30 Aug 2011


Research Article


Methodologies for Prediction of Stock Market: An Artificial Neural Network


R.K. Dase1, D. D. Pawar2, D.S. Daspute3


1Assistant Professor, MGM�s Medical College, Aurangabad(MS), INDIA


2Associate Professor and Chairman of BOS in Statistics,

N.E.S. Science College , Nanded

Maharastra , INDIA


3Assistant Professor, MIMSR Medical College, Latur(MS), INDIA

Received 26 August 2011; Accepted 30 August 2011

Academic Editor: Dr. Jadhav V.A.



Peoples tend to invest in stocks because of its high returns over time. Stock markets are affected by many highly interrelated economic, social, political and even psychological factors, and these factors interact with each other in a very complicated manner. Therefore it is generally challenging task to predict the movement of stock market.  It is observed that conventional statistical techniques for prediction have reached their limitation in applications with nonlinearities in the data set. Artificial Neural Network, a computing system containing many simple nonlinear computing units as neurons interconnected by links, is a well-tested method for financial analysis on the stock market. This paper explains in detail various prediction methodologies for stock market and found that Artificial Neural network could be useful for stock market prediction.


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