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Clustering Algorithms for Risk Management

Ivana P. MarkoviÃƒÂ³, Jovica M. StankoviÃƒÂ³, Jelena Z. StankoviÃƒÂ³, Milos B. StojanoviÃƒÂ³
Faculty of Economics at the University of Ni, Trg kralja Aleksandra Ujedinitelja 11 & 18000 Ni, Serbia

Abstract: The investments in capital market depends on deeper analysis of yield and risk. The investments depend on the stock market which improve the interest of the people. We intend to study the stock market using cluster algorithms. We found that the cluster algorithms can enable to identify groups of stocks in the existing portfolios and help to the risk diversification.

Keywords: Dynamic Time Warping, K-means, Hierarchical Clustering, Portfolio Optimization Clustering Algorithms for Risk Management

DOI:https://doi.org/10.6025/jmpt/2020/11/4/117-123

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