Performance Evaluation of Portfolio Stocks Selected with the EU-EV Risk Model

dc.contributor.authorBrito, Irenepor
dc.contributor.authorMachado, Gaspar J.por
dc.date.accessioned2023-09-15T16:06:23Z
dc.date.available2023-09-15T16:06:23Z
dc.date.issued2023
dc.description.abstractIn this paper, the performance of portfolios consisting of stocks selected with the recently proposed expected utility, entropy and variance (EU-EV) risk model is analysed. The portfolios were constructed using data of the PSI 20 index, from January 2019 to December 2020, by reducing the number of stock components to the half with the EU-EV risk model. The effciency of these portfolios in terms of the mean-variance model was shown to be approximately equal to the effciency of portfolios obtained from the whole set of stocks. The aim is to evaluate the performance of the constructed portfolios, by comparing their in-sample and out-of-sample results with those of the benchmark. For that purpose, cumulative returns in the in-sample period from January 2019 to December 2020 and in the out-of-sample period from January 2021 to December 2022, considering both an one-year and a two-year time horizon, as well as different performance metrics, such as Sharpe ratio, Sortino ratio, Beta and Alpha, are analysed. The results reveal that the portfolios constructed with the EU-EV risk model outperform the benchmark portfolio in the given periods, where a better performance was obtained in the one-year out-of-sample period. These results suggest that the strategy of constructing portfolios using the best ranked stocks according to the EU-EV risk model can be useful for short-term investment objectives.por
dc.description.sponsorshipFCT -Fundação para a Ciência e a Tecnologia(UIDB/00013/2020)por
dc.distributioninternationalpor
dc.identifier.citationBrito, I., & Machado, G. J. (2023). Performance Evaluation of Portfolio Stocks Selected with the EU–EV Risk Model. Computational Science and Its Applications – ICCSA 2023 Workshops. Springer Nature Switzerland. http://doi.org/10.1007/978-3-031-37108-0_5por
dc.identifier.doi10.1007/978-3-031-37108-0_5por
dc.identifier.eisbn978-3-031-37108-0por
dc.identifier.isbn978-3-031-37107-3por
dc.identifier.issn0302-9743por
dc.identifier.urihttps://hdl.handle.net/1822/86404
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherSpringer, Champor
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00013%2F2020/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00013%2F2020/PTpor
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-031-37108-0_5por
dc.rightsopenAccesspor
dc.subjectEU-EV risk modelpor
dc.subjectStock selectionpor
dc.subjectPortfolio performance evaluationpor
dc.titlePerformance Evaluation of Portfolio Stocks Selected with the EU-EV Risk Modelpor
dc.typeconferencePaperpor
dspace.entity.typePublicationen
oaire.citationEndPage83por
oaire.citationStartPage69por
oaire.citationVolume14105 LNCSpor
oaire.versionAMpor
sdum.journalLecture Notes in Computer Science (including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)por

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