Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/28323
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dc.contributor.authorKitanovski, Dimitaren_US
dc.contributor.authorMirchev, Miroslaven_US
dc.contributor.authorChorbev, Ivanen_US
dc.contributor.authorMishkovski, Igoren_US
dc.date.accessioned2023-10-27T06:47:50Z-
dc.date.available2023-10-27T06:47:50Z-
dc.date.issued2022-12-22-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/28323-
dc.description.abstractAs of the end of 2013 till now we are witnessing huge volatility and risk in the cryptocurrency market compared to flat currency or stock market. Thus, in this market the portfolio diversification is of big importance in order to reduce volatility and keep the optimal return for the investors. A usual approach for portfolio construction is to keep a balance between returns and volatility, based on their interdependence and individual returns. One way of diversification is employing clustering or community detection algorithms to select a more diverse set of assets. We study the utilization of the Louvain algorithm and affinity propagation for community detection, based on correlation and mutual information between cryptocurrencies, for potential application in portfolio diversification.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relationEPMAIen_US
dc.subjectCryptocurrenciesen_US
dc.subjectPortfolio selectionen_US
dc.subjectCommunity detectionen_US
dc.subjectFinancial analysisen_US
dc.titleCryptocurrency Portfolio Diversification Using Network Community Detectionen_US
dc.typeProceeding articleen_US
dc.relation.conference30th Telecommunications Forum (TELFOR)en_US
dc.identifier.doi10.1109/TELFOR56187.2022.9983742-
item.fulltextWith Fulltext-
item.grantfulltextopen-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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