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Agent based Stock Clustering for Efficient Portfolio Management

by Preeti Baser, Jatinderkumar R. Saini
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 116 - Number 3
Year of Publication: 2015
Authors: Preeti Baser, Jatinderkumar R. Saini
10.5120/20317-2381

Preeti Baser, Jatinderkumar R. Saini . Agent based Stock Clustering for Efficient Portfolio Management. International Journal of Computer Applications. 116, 3 ( April 2015), 35-41. DOI=10.5120/20317-2381

@article{ 10.5120/20317-2381,
author = { Preeti Baser, Jatinderkumar R. Saini },
title = { Agent based Stock Clustering for Efficient Portfolio Management },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 116 },
number = { 3 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 35-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume116/number3/20317-2381/ },
doi = { 10.5120/20317-2381 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:56:04.460986+05:30
%A Preeti Baser
%A Jatinderkumar R. Saini
%T Agent based Stock Clustering for Efficient Portfolio Management
%J International Journal of Computer Applications
%@ 0975-8887
%V 116
%N 3
%P 35-41
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This research paper proposed agent based framework for portfolio management using non-hierarchical clustering method. The framework included various agents such as data agent, clustering agent, ranking agent, portfolio manager and user agent. The data agent collected financial ratio of Nifty 50 companies from financial database. Clustering agents generated clusters and DB index computed to find optimum cluster size of each method. Validation agent evaluated the performance of k-means, k-medoids and fast k-means using intra-class inertia. Clusters generated by k-means used for investment and portfolio analysis using Markowitz model. This research helped to assemble a diversified portfolio of stocks with the use of clustering

References
  1. A. Kumar and N. William. 2002 "Equity portfolio diversification", Working Paper Yale International Center for Finance, November 2002
  2. Blume, E. Marshall and F. Irwin, "The asset structure of individual portfolios and some implications for utitlity functions", Journal of Finance, vol 30, 585-603
  3. C. Bertaut. 1998 "Stockholding behavior of US houseolds: evidence from 1983-1989", Survey of Consumer Finances, Review of Economics and Statistics, vol 80, , pp. 263-275
  4. Cohn , A. Richard et al. 1975 "Individual investor risk aversion and investment portfolio composition", Journal of Finance, vol 30, , pp. 605-620
  5. D. L. Davies and W. Bouldin. 1979 "A cluster separation measure", IEEE PAMI, vol 1, pp. 224-227
  6. E. J. Elton and M. J. Gruber. 1977 "Risk reduction and portfolio size: an analytical solutions", Journal of Business, vol 50, , pp. 415-437
  7. G. Chen et al. 2002. "Evaluation and comparison of clustering algorithms in analyzing ES cell gene expression data", Statistical Sinica, vol 12, pp. 241-262
  8. I. I. Evans and S. H Archer. 1968 "Diversification and reduction of dispersion: an empirical analysis", Journal of Finance, vol 41.
  9. J. C. Dunn, 1974. "Well seperated clusters and optimal fuzzy partitions", Journal of Cybernatics, vol 4, pp. 95-104
  10. J. Heaton and L. Deborah. 2000, "Portfolio choice and asset prices: the importance of entrepreneurial risk", Journal of Finance, vol 55, pp. 1163-1198
  11. L. Fisher and J. H. Lorie, 1970 "Some studies of the variability of returns on investment in common stocks", Journal of Finance, vol 43.
  12. L. Guiso, T. Japelli and D. Terlizze, 1996. "Income risk, borrowing constraints and portfolio choice, American Economic Review", vol 86, pp. 158-172
  13. L. Kaufma and P. J. Rousseeuw, 1990. "Finding groups in data: and introduction to cluster analysis", John Wiley & Sons.
  14. M. Halkidi, Y. Batistakis and M. Vazirgiannis, 2002. " Cluster validity methods part II", SIGMOD Rec, vol 31, issue 2, pp. 40-45
  15. M. Kelly, "All their eggs in one basket: portfolio diversification of US households", Journal of Economic Behavior and Organization, vol 27, pp. 87-96
  16. M. Kim and R. S. Ramakrishna, 2005. "New indices for cluster validity assessment", Pattern Recognition Letters, vol 26, issue 15, pp. 2353-2363
  17. M. Satman, 2002. "How much diversification is enough?", Working Paper, Santa Clara University August 2002
  18. N. Malhotra, 2013. "Determinants of stock prices: Empirical evidence from NSE 100 companies", Int J Res Mangg Technol, vol 3, issue 3, pp. 86-95
  19. P. Baser and J. R. Saini, 2013. "An agglomerative analysis of Nifty companies for an investment perspective", Int J Recent Innov Trends Comput Commun, vol 2 issue 5, pp. 1348–1352.
  20. P. Baser and J. R. Saini, 2013. "A comparative analysis of various clustering techniques used very large datasets", Int J Comput Sci Commun Netw vol 3, issue 4, pp. 271–275
  21. P. Baser and J. R. Saini, 2013. "An intelligent agent based framework for an efficient portfolio management using stock clustering", Int J Inform Comput Technol, vol 3, issue 2, pp. 49–54.
  22. P. Baser and J. R. Saini. 2014 "An Optimum Cluster Size Identification for k-Means using Validity Index for Stock Market Data", Int J Data Mining Emer Technol, vol 4, issue 2, , pp. 107–110
  23. P. Baser and J. R. Saini. 2013 "k-Means analysis of Nifty companies for an investment perspective" Int J Data Mining Emer Technol, vol 3 issue 1, pp. 16–22.
  24. P. S. Nirmal, P. S. Sanju and M. Ramachandran. 2011, "Determinants of share prices in india" J. Emer Trend Econ Mangg Sci, vol 2, issue 2, pp. 124-130
  25. P. Srinivasan, 2011. "Determinant of equity share prices in india : A panel data approach", Romanian Econ J Mangg Sci, vol 2, issue 2, pp. 124-130
  26. S. K. Mehta and M. S. Turan, 2005. "Determinants of stock prices in india : An empirical study", J Ind Mangg Strat, vol 10, issue 4, pp. 37-43.
  27. S. Kambey, R. Thakur and S. Jaalori, 2012. "Application of data mining in stock market: an analysis", International Journal of Computer and Communication Technology(IJCCT), vol 3, issue 3, pp. 52-53.
  28. S. Kaur and V. Mangat, 2012. "Applications of data mining in stock market". Journal of Information and Operations Management vol 3, issue 1, pp. 86-88.
  29. S. Sharma and B. Singh, 2006. "Determinants of equity share prices in indian corporate sector: an empirical study" ICFAI J Appl Fin , vol 12, issue 4, pp. 21-28.
  30. S. Sharma, 2011. "Determinants of equity share prices in india", J Arts Sci Comm, vol 2, issue 4, pp. 51-60
  31. U. Malik and S. Bandopadhyay. 2002. "Performance evaluation of some clustering algorithms and validity indices" IEEE Transc and Pattern Analysis and Machine Intelligence, vol 24, issue 12, , pp. 1650-1654
  32. W. R Perraudin and E. Bent, 2000. "The demand for risky assets: Sample selection and household portfolios", Journal of Econometrics , vol 97, pp. 117-144
  33. W. C. Elkan 2003. "Using the Triangle Inequality to Accelerate k-Means" Proceedings of Twentieth International Conference on Machine Learning, Washington DC,(ICML-2003).
Index Terms

Computer Science
Information Sciences

Keywords

Clustering Data mining (DM) Davis-Bouldin (DB) Index Dunn Index k-means k-medoids Partitioning Around Medoids(PAM) Silhouette index

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