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dc.contributor.authorMendes, R. R. A.
dc.contributor.authorPaiva, A. P.
dc.contributor.authorPeruchi, R. S.
dc.contributor.authorBalestrassi, P. P.
dc.contributor.authorLeme, R. C.
dc.contributor.authorSilva, M. B. [UNESP]
dc.date.accessioned2018-11-26T15:28:23Z
dc.date.available2018-11-26T15:28:23Z
dc.date.issued2016-02-01
dc.identifierhttp://dx.doi.org/10.1016/j.cor.2015.05.001
dc.identifier.citationComputers & Operations Research. Oxford: Pergamon-elsevier Science Ltd, v. 66, p. 434-444, 2016.
dc.identifier.issn0305-0548
dc.identifier.urihttp://hdl.handle.net/11449/158628
dc.description.abstractThe modern portfolio theory has been trying to determine how an investor might allocate assets among the possible investments options. Since the seminal contribution provided by Harry Markowitz's theory of portfolio selection, several other tools and procedures have been proposed to deal with return-risk trade-off. Furthermore, diversification across sources of returns and risks based on entropy indexes is another pivotal aspect in portfolio management. An efficient approach to model these portfolio. properties with the proportion of each asset can be obtained according to mixture design of experiments. Desirability method can be applied to optimize this nonlinear multiobjective problem. Nevertheless, a tuning procedure is required, since preference articulation parameters in desirability algorithm are unknown a priori. As a result, a computer-aided desirability tuning method is proposed to find an optimal portfolio with time series of returns and risks modeled by ARMA-GARCH models. To assess the proposal feasibility, the method is tested with a heteroskedastic dataset formed by weekly world crude oil spot prices and returns. Computer-aided desirability tuning was able to enhance the global desirability by 79% in relation to the result with no tuning procedure. (c) 2015 Elsevier Ltd. All rights reserved.en
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG)
dc.format.extent434-444
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofComputers & Operations Research
dc.sourceWeb of Science
dc.subjectMixture design of experiments
dc.subjectARMA-GARCH models
dc.subjectMultiobjective portfolio optimization
dc.subjectEntropy
dc.titleMultiobjective portfolio optimization of ARMA-GARCH time series based on experimental designsen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderElsevier B.V.
dc.contributor.institutionFed Inst Educ Sci & Technol South Minas Gerais
dc.contributor.institutionUniv Fed Itajuba
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.description.affiliationFed Inst Educ Sci & Technol South Minas Gerais, BR-37550000 Pouso Alegre, MG, Brazil
dc.description.affiliationUniv Fed Itajuba, BR-37500903 Itajuba, MG, Brazil
dc.description.affiliationSao Paulo State Univ, BR-12516410 Guaratingueta, SP, Brazil
dc.description.affiliationUnespSao Paulo State Univ, BR-12516410 Guaratingueta, SP, Brazil
dc.identifier.doi10.1016/j.cor.2015.05.001
dc.identifier.wosWOS:000366779900039
dc.rights.accessRightsAcesso aberto
dc.relation.ispartofsjr1,916
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