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A Review on Data Mining Applications to the Performance of Stock Marketing

by D. Venugopal Setty, T.M.Rangaswamy, K.N.Subramanya
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 3
Year of Publication: 2010
Authors: D. Venugopal Setty, T.M.Rangaswamy, K.N.Subramanya
10.5120/88-187

D. Venugopal Setty, T.M.Rangaswamy, K.N.Subramanya . A Review on Data Mining Applications to the Performance of Stock Marketing. International Journal of Computer Applications. 1, 3 ( February 2010), 24-34. DOI=10.5120/88-187

@article{ 10.5120/88-187,
author = { D. Venugopal Setty, T.M.Rangaswamy, K.N.Subramanya },
title = { A Review on Data Mining Applications to the Performance of Stock Marketing },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 3 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 24-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number3/88-187/ },
doi = { 10.5120/88-187 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:43:55.066211+05:30
%A D. Venugopal Setty
%A T.M.Rangaswamy
%A K.N.Subramanya
%T A Review on Data Mining Applications to the Performance of Stock Marketing
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 3
%P 24-34
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining is the extraction of hidden predictive information from large data bases. Data mining is used to increase revenues and reduce costs. Data mining finds patterns and correlations or relationships in data by using sophisticated techniques. In today’s society of high demanding customers, increasing competitiveness and in order to avoid the initial investment of gathering a data without being certain that it will be successful. A customer-focused approach will discover customer’s preferences, needs and behavioral characteristics. The current approach is described for data development in share market to find the correlations between the customer feelings or perceptions and the physical characteristics of a data. Stock Market is an organized set-up with a regulatory body and the members who trade in shares are registered with the stock market and regulatory body SEBI. The stock market is also called the secondary market as it involves trading between two investors and itis often considered the primary indicator of a country's economic strength and development. The NSE is the largest stock exchange in India in terms of daily turnover and number of trades, for both equities and derivative trading.

References
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  2. 2. Das, S. and Chen, M. 2001. Yahoo for Amazon: Extracting Market Sentiment from Stock Message Boards, Proceedings of the 8th Asia Pacific Finance Association Annual Conference (APFA 2001), Bangkok, Thailand, July 22-25, 2001
  3. 3. Fanning K. and Cogger K., (1998), ‘Neural Network Detection of Management Fraud Using Published Financial Data’, International Journal of Intelligent Systems in Account-ing, Finance & Management, Vol. 7, No. 1, pp. 21-24.
  4. 4. R. Gencay, “Non-linear prediction of security returns with moving average rules,” Journal of Forecasting, vol. 15, no.3, pp. 165-174, 1996
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Index Terms

Computer Science
Information Sciences

Keywords

Data mining Stock Market future trends number of trades