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dc.rights.licenseKūrybinių bendrijų licencija / Creative Commons licenceen_US
dc.contributor.authorVilkancas, Renaldas
dc.date.accessioned2024-10-24T08:23:22Z
dc.date.available2024-10-24T08:23:22Z
dc.date.issued2014
dc.date.submitted2014-10-31
dc.identifier.issn2029-7491en_US
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/155415
dc.description.abstractThere is little literature considering effects that the loss-gain threshold used for dividing good and bad outcomes by all downside (upside) risk measures has on portfolio optimization and performance. The purpose of this study is to assess the performance of portfolios optimized with respect to the Omega function developed by Keating and Shadwick at different levels of the threshold returns. The most common choices of the threshold values used in various Omega studies cover the risk-free rate and the average market return or simply a zero return, even though the inventors of this measure for risk warn that “using the values of the Omega function at particular points can be critically misleading” and that “only the entire Omega function contains information on distribution”. The obtained results demonstrate the importance of the selected values of the threshold return on portfolio performance – higher levels of the threshold lead to an increase in portfolio returns, albeit at the expense of a higher risk. In fact, within a certain threshold interval, Omega-optimized portfolios achieved the highest net return, compared with all other strategies for portfolio optimization using three different test datasets. However, beyond a certain limit, high threshold values will actually start hurting portfolio performance while meta-heuristic optimizers typically are able to produce a solution at any level of the threshold, and the obtained results would most likely be financially meaningless.en_US
dc.format.extent21en_US
dc.format.mediumTekstas / Texten_US
dc.language.isoenen_US
dc.relation.urihttps://etalpykla.vilniustech.lt/handle/123456789/155341en_US
dc.rightsAttribution-NonCommercial 4.0 Internationalen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/en_US
dc.source.urihttps://journals.vilniustech.lt/index.php/BMEE/article/view/3517en_US
dc.subjectdownside risken_US
dc.subjectOmega functionen_US
dc.subjectportfolio optimizationen_US
dc.subjectthreshold returnen_US
dc.subjectdifferential evolution (DE)en_US
dc.titleCharacteristics of Omega-optimized portfolios at different levels of threshold returnsen_US
dc.typeKonferencijos publikacija / Conference paperen_US
dcterms.accessRightsLaisvai prieinamas / Openly availableen_US
dcterms.accrualMethodRankinis pateikimas / Manual submissionen_US
dcterms.alternativeFinancial risk management of business developmenten_US
dcterms.dateAccepted2014-11-07
dcterms.issued2014-12-23
dcterms.licenseCC BY NCen_US
dcterms.references50en_US
dc.description.versionTaip / Yesen_US
dc.contributor.institutionVilniaus Gedimino technikos universitetasen_US
dc.contributor.institutionVilnius Gediminas Technical Universityen_US
dc.contributor.facultyVerslo vadybos fakultetas / Faculty of Business Managementen_US
dcterms.sourcetitleBusiness, Management and Educationen_US
dc.description.issueno. 2en_US
dc.description.volumevol. 12en_US
dc.identifier.eissn2029-6169en_US
dc.publisher.nameVilnius Gediminas Technical Universityen_US
dc.publisher.nameVilniaus Gedimino technikos universitetasen_US
dc.publisher.countryLithuaniaen_US
dc.publisher.countryLietuvaen_US
dc.publisher.cityVilniusen_US
dc.identifier.doihttps://doi.org/10.3846/bme.2014.235en_US


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Kūrybinių bendrijų licencija / Creative Commons licence
Except where otherwise noted, this item's license is described as Kūrybinių bendrijų licencija / Creative Commons licence