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Reseach Article

An Association Rule Mining Model for Finding the Interesting Patterns in Stock Market Dataset

by Sachin Kamley, Shailesh Jaloree, R. S. Thakur
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 93 - Number 9
Year of Publication: 2014
Authors: Sachin Kamley, Shailesh Jaloree, R. S. Thakur
10.5120/16242-5792

Sachin Kamley, Shailesh Jaloree, R. S. Thakur . An Association Rule Mining Model for Finding the Interesting Patterns in Stock Market Dataset. International Journal of Computer Applications. 93, 9 ( May 2014), 11-20. DOI=10.5120/16242-5792

@article{ 10.5120/16242-5792,
author = { Sachin Kamley, Shailesh Jaloree, R. S. Thakur },
title = { An Association Rule Mining Model for Finding the Interesting Patterns in Stock Market Dataset },
journal = { International Journal of Computer Applications },
issue_date = { May 2014 },
volume = { 93 },
number = { 9 },
month = { May },
year = { 2014 },
issn = { 0975-8887 },
pages = { 11-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume93/number9/16242-5792/ },
doi = { 10.5120/16242-5792 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:15:21.252994+05:30
%A Sachin Kamley
%A Shailesh Jaloree
%A R. S. Thakur
%T An Association Rule Mining Model for Finding the Interesting Patterns in Stock Market Dataset
%J International Journal of Computer Applications
%@ 0975-8887
%V 93
%N 9
%P 11-20
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In these days, stock market forecasting is one of the most interesting issues, which has gained a more attention due to vast profits. To precisely predict the price of share and making profits has been always challenging task since the longest period of time. This has engrossed the interest and attention of stock brokers, economists and applied researchers. Traditional methods like Fundamental analysis, Technical analysis, and Regression methods are not suitable for this task because these tools and techniques are based on totally different analytical approaches and requiring highly expertise and justification in the area. In this sequence, Association Rule Mining is one of the most interesting research areas for finding the associations, correlations among items in a database. It can discover all useful patterns from stock market dataset. The aim of this research study is to help stock brokers, investors so that they can earn maximum profits for each trading.

References
  1. Abdoh Tabrizi. H, and Jouhare H. "The Investigation of Efficiency of stock price index of T. S. E", Journal of Financial Research; Vol. 13, PP. 11-12, 1996.
  2. Agrawal R. , and Srikant R. "Fast Algorithms for Mining Association Rules in Large Databases", In Proc. 20th VLDB, PP. 478-499, Sept. 1994.
  3. Agrawal R. , Imeielinski T. , and Swami A. "Mining Association Rules between Sets of Items in Large Databases", Proceedings of the ACM SIGMOD Conference on Management of Data", Washington, D. C. , PP. 207-216 ,1993.
  4. Argiddi Rajesh V, and Apte Sulabha S "Fragment Based Approach to Forecast Association Rules from Indian IT Stock Transaction Data", International Journal of Computer Science and Information Technologies(IJCSIT), Vol. 3, Issue (2), PP. 3493-3497, 2012.
  5. Bayardo R. J. "Effcient Mining Long Patterns from Databases", SIGMOD, PP. 85-93, 1998.
  6. Borisov Alexander "Rule Induction for Identifing multilayer Tool Commonalities" , IEEE Transactions on Semiconducter Manufacturing , Vol. 24, PP. 197-201, May 2011.
  7. Brown and Jennings, on Technical Analysis "The Review of Financial Studies", Vol. 2, Issue (4), PP. 527-551, 1989.
  8. Connolly, and Begg T. C. "Database Systems: A Practical Approach to Design, Implementation and Management", Addison-Wesley Longman, ISBN 0201342871, 1998.
  9. Das Ambika Prasad "Security analysis and portfolio Management", I. K. International Publication, 3rd Edition, New Delhi (India), 2008.
  10. Fama Eugene F. "Random Walks in Stock Market Prices", Financial Analysts journal, Vol. 51, Issue (1), PP. 75-80, January -February, 1995.
  11. Hajizadeh E. , Ardakani H. , and Shahrabi J. "Application of Data Mining Techniques in Stock Markets: A Survey", Journal of Economics and International Finance, Vol. 2, Issue (7), PP. 109-118, July 2010.
  12. Han J. , and Kamber M. "Data Mining: Concepts and Techniques", Morgan Kaufmann, 2nd edition, San Francisco, CA, 2006.
  13. Khan Aurangzeb, and Khan Khairullah "Frequent Patterns Mining of Stock Data Using Hybrid Clustering Association Algorithm", University Technology PETRONAS, 2009.
  14. Liu B. , Hsu W. , and M. A. Y. "Mining Association Rules with Multiple Minimum Supports", International Conference on Knowledge Discovery and Data Mining, PP. 337-341, 1999.
  15. Nandagopal S. , Arunachalam V. P. , and Karthik S. "A Novel Approach for Mining Inter-Transaction Itemsets", European Scientific Journal , Vol. 8, PP. 14-22, 2012.
  16. Paranjape Preeti, and Deshpande Umesh "A Stock Market Portfolio Recoommender System Based on Association Rule Mining", Journal of Applied Soft Computing, Vol. 13, Issue (2), PP. 1055-1063, Febrarury 2013.
  17. Saeedmanesh M. , izadi T. , and Ahvar E. "A Hybrid Data Mining Technique for Stock Exchange Prediction", International Multi Conference, China, 2002.
  18. Srikant R. , Vu Q. , and Agrawal R. "Mining Association Rules with Item Constraints", In Proc. 1997 International Conference Knowledge Discovery and Data Mining (KDD '97'), Newport Beach, CA, PP. 67-73, Aug. 1997.
  19. Srisawat "An Application of Association Rule Mining Based on Stock Market", 3rd International Conference on Data Mining and Intelligent Information Technology Applications (ICMIA) , 24-26 Oct. , 2011.
  20. Stock Market Information Available at "http://www. sebi. gov. in".
  21. Stock Market Dataset Available "http://www. bseindia. com".
  22. Tan P. , Kumar V. , and Shrivastava J. "Selecting the Right Interesting Measure for Association Patterns", Inf. Syst. , Vol. 29, Issue (4), PP. 293-331, 2004.
  23. Toivonen H. "Sampling Large Databases for Association Rules", In Proc. 22 nd VLDB, PP. 134-145, Sept. 1996.
Index Terms

Computer Science
Information Sciences

Keywords

Stock Market Data Mining Prediction BSE Association Rule Mining Frequent Pattern SAS 9. 2.