Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Decision Support System for Mongolian Portfolio Selection

  • Bukhsuren, Enkhtuul (Dept. of Information and Computer Sciences, National University of Mongolia) ;
  • Sambuu, Uyanga (Dept. of Information and Computer Sciences, National University of Mongolia) ;
  • Namsrai, Oyun-Erdene (Dept. of Information and Computer Sciences, National University of Mongolia) ;
  • Namsrai, Batnasan (Dept. of Marketing and Trade, National University of Mongolia) ;
  • Ryu, Keun Ho (Database and Bioinformatics Laboratory, School of Electrical and Computer Engineering, Chungbuk National University)
  • Received : 2022.03.08
  • Accepted : 2022.05.13
  • Published : 2022.10.31
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Abstract

Investors aim to increase their profitability by investing in the stock market. An adroit strategy for minimizing related risk lies through diversifying portfolio operationalization. In this paper, we propose a six-step stocks portfolio selection model. This model is based on data mining clustering techniques that reflect the ensuing impact of the political, economic, legal, and corporate governance in Mongolia. As a dataset, we have selected stock exchange trading price, financial statements, and operational reports of top-20 highly capitalized stocks that were traded at the Mongolian Stock Exchange from 2013 to 2017. In order to cluster the stock returns and risks, we have used k-means clustering techniques. We have combined both k-means clustering with Markowitz's portfolio theory to create an optimal and efficient portfolio. We constructed an efficient frontier, creating 15 portfolios, and computed the weight of stocks in each portfolio. From these portfolio options, the investor is given a choice to choose any one option.

Keywords

Acknowledgement

The research has received funding from the National University of Mongolia (Grant No. P2019-3739).

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