Cryptocurrency Portfolio Selection—A Multicriteria Approach
This paper proposes the PROMETHEE II based multicriteria approach for cryptocurrency portfolio selection. Such an approach allows considering a number of variables important for cryptocurrencies rather than limiting them to the commonly employed return and risk. The proposed multiobjective decision...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/9/14/1677 |
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| author | Zdravka Aljinović Branka Marasović Tea Šestanović |
| author_facet | Zdravka Aljinović Branka Marasović Tea Šestanović |
| author_sort | Zdravka Aljinović |
| collection | DOAJ |
| description | This paper proposes the PROMETHEE II based multicriteria approach for cryptocurrency portfolio selection. Such an approach allows considering a number of variables important for cryptocurrencies rather than limiting them to the commonly employed return and risk. The proposed multiobjective decision making model gives the best cryptocurrency portfolio considering the daily return, standard deviation, value-at-risk, conditional value-at-risk, volume, market capitalization and attractiveness of nine cryptocurrencies from January 2017 to February 2020. The optimal portfolios are calculated at the first of each month by taking the previous 6 months of daily data for the calculations yielding with 32 optimal portfolios in 32 successive months. The out-of-sample performances of the proposed model are compared with five commonly used optimal portfolio models, i.e., naïve portfolio, two mean-variance models (in the middle and at the end of the efficient frontier), maximum Sharpe ratio and the middle of the mean-CVaR (conditional value-at-risk) efficient frontier, based on the average return, standard deviation and VaR (value-at-risk) of the returns in the next 30 days and the return in the next trading day for all portfolios on 32 dates. The proposed model wins against all other models according to all observed indicators, with the winnings spanning from 50% up to 94%, proving the benefits of employing more criteria and the appropriate multicriteria approach in the cryptocurrency portfolio selection process. |
| first_indexed | 2024-03-10T09:32:40Z |
| format | Article |
| id | doaj.art-b125e30d76494dec88ad94562e6fab4a |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T09:32:40Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-b125e30d76494dec88ad94562e6fab4a2023-11-22T04:20:29ZengMDPI AGMathematics2227-73902021-07-01914167710.3390/math9141677Cryptocurrency Portfolio Selection—A Multicriteria ApproachZdravka Aljinović0Branka Marasović1Tea Šestanović2Faculty of Economics, Business and Tourism, University of Split, 21000 Split, CroatiaFaculty of Economics, Business and Tourism, University of Split, 21000 Split, CroatiaFaculty of Economics, Business and Tourism, University of Split, 21000 Split, CroatiaThis paper proposes the PROMETHEE II based multicriteria approach for cryptocurrency portfolio selection. Such an approach allows considering a number of variables important for cryptocurrencies rather than limiting them to the commonly employed return and risk. The proposed multiobjective decision making model gives the best cryptocurrency portfolio considering the daily return, standard deviation, value-at-risk, conditional value-at-risk, volume, market capitalization and attractiveness of nine cryptocurrencies from January 2017 to February 2020. The optimal portfolios are calculated at the first of each month by taking the previous 6 months of daily data for the calculations yielding with 32 optimal portfolios in 32 successive months. The out-of-sample performances of the proposed model are compared with five commonly used optimal portfolio models, i.e., naïve portfolio, two mean-variance models (in the middle and at the end of the efficient frontier), maximum Sharpe ratio and the middle of the mean-CVaR (conditional value-at-risk) efficient frontier, based on the average return, standard deviation and VaR (value-at-risk) of the returns in the next 30 days and the return in the next trading day for all portfolios on 32 dates. The proposed model wins against all other models according to all observed indicators, with the winnings spanning from 50% up to 94%, proving the benefits of employing more criteria and the appropriate multicriteria approach in the cryptocurrency portfolio selection process.https://www.mdpi.com/2227-7390/9/14/1677cryptocurrencyportfolio selectionreturn and risk measuresmarket capitalizationvolumeattractiveness |
| spellingShingle | Zdravka Aljinović Branka Marasović Tea Šestanović Cryptocurrency Portfolio Selection—A Multicriteria Approach Mathematics cryptocurrency portfolio selection return and risk measures market capitalization volume attractiveness |
| title | Cryptocurrency Portfolio Selection—A Multicriteria Approach |
| title_full | Cryptocurrency Portfolio Selection—A Multicriteria Approach |
| title_fullStr | Cryptocurrency Portfolio Selection—A Multicriteria Approach |
| title_full_unstemmed | Cryptocurrency Portfolio Selection—A Multicriteria Approach |
| title_short | Cryptocurrency Portfolio Selection—A Multicriteria Approach |
| title_sort | cryptocurrency portfolio selection a multicriteria approach |
| topic | cryptocurrency portfolio selection return and risk measures market capitalization volume attractiveness |
| url | https://www.mdpi.com/2227-7390/9/14/1677 |
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