D. D. Pawar2, D.S. Daspute3
Professor, MGM’s Medical College, Aurangabad(MS), INDIA
Professor and Chairman of BOS in Statistics,
N.E.S. Science College , Nanded
Maharastra , INDIA
Professor, MIMSR Medical College, Latur(MS), INDIA
Received 26 August
2011; Accepted 30 August 2011
Academic Editor: Dr.
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.