Incorporating skewness and kurtosis in portfolio optimization: A multidimensional efficient set

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dc.contributor.authorGUSTAVO MONTEIRO DE ATHAYDE
dc.contributor.authorFlôres Junior, Renato Galvão
dc.coverage.paisNão Informadopt_BR
dc.creatorFlôres Junior, Renato Galvão
dc.date.accessioned2022-12-09T21:44:03Z
dc.date.available2022-12-09T21:44:03Z
dc.date.issued2003
dc.description.notesEvidênciapt_BR
dc.description.otherThis chapter presents mathematical tools that make the algebra of multivariate higher moments very tractable. Based on them, a multidimensional portfolio frontier is created, incorporating skewness and using kurtosis instead of variance. Most models in finance are based on mean-variance analysis. Therefore, risk premium is derived from the second moment of a random variable. The basic assumption of this kind of modeling is that agents are not so concerned about moments higher than the variance. In fact, all the utility functions that are strictly increasing and concave have expected utilities that increase with odd moments and decrease with even moments. When restricting ourselves to expected utility, mean-variance analysis may be justified by either a quadratic utility function or by a Taylor approximation of a more general and acceptable utility function. Differently from the mean-variance case, which only requires linear algebra, higher moments require the use of the so-called tensors, which can be seen as a generalization of matrices.pt_BR
dc.format.extentp. 243-257pt_BR
dc.format.mediumDigitalpt_BR
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/4868
dc.language.isoInglêspt_BR
dc.publisherQuantitative Financept_BR
dc.relation.isreferencedbyAdvances in portfolio construction and implementationpt_BR
dc.rights.licenseO INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DOS USUÁRIOS INDIVIDUAIS VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITORpt_BR
dc.subject.keywordsNão informadopt_BR
dc.titleIncorporating skewness and kurtosis in portfolio optimization: A multidimensional efficient setpt_BR
dc.typebook part
dspace.entity.typePublication
local.identifier.sourceUrihttps://doi.org/10.1016/B978-075065448-7.50011-2
local.typeCapítulo de Livropt_BR
relation.isAuthorOfPublicationa57614f1-05fc-47e3-88a9-59266040a6dc
relation.isAuthorOfPublication.latestForDiscoverya57614f1-05fc-47e3-88a9-59266040a6dc
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