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Decision Support System for Mongolian Portfolio Selection
Enkhtuul Bukhsuren,Uyanga Sambuu,Oyun-Erdene Namsrai,Batnasan Namsrai,류근호 한국정보처리학회 2022 Journal of information processing systems Vol.18 No.5
Investors aim to increase their profitability by investing in the stock market. An adroit strategy for minimizingrelated risk lies through diversifying portfolio operationalization. In this paper, we propose a six-step stocksportfolio selection model. This model is based on data mining clustering techniques that reflect the ensuingimpact of the political, economic, legal, and corporate governance in Mongolia. As a dataset, we have selectedstock exchange trading price, financial statements, and operational reports of top-20 highly capitalized stocksthat were traded at the Mongolian Stock Exchange from 2013 to 2017. In order to cluster the stock returns andrisks, we have used k-means clustering techniques. We have combined both k-means clustering withMarkowitz'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, theinvestor is given a choice to choose any one option.