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Risk forecasting models and optimal portfolio selection

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dc.affiliation.dptoUC3M. Departamento de Economía de la Empresaes
dc.contributor.authorMoreno, David
dc.contributor.authorMarco, Paulina
dc.contributor.authorOlmeda, Ignacio
dc.date.accessioned2010-04-21T16:52:53Z
dc.date.available2010-04-21T16:52:53Z
dc.date.issued2005-06
dc.description.abstractThis study analyses, from an investor's perspective, the performance of several risk forecasting models in obtaining optimal portfolios. The plausibility of the homoscedastic hypothesis implied in the classical Markowitz model is dicussed and more general models which take into account assymetry and time varying risk are analysed. Specifically, it studies whether ARCH-type based models obtain portfolios whose risk-adjusted returns exceed those of the classical Markowitz model. The same analysis is performed with models based on the Lower Partial Moment (LPM) which take into account the assymetry in the distribution of returns. The results suggest that none of the models achieve a clearly superior average performance. It is also found that models based on semivariance perform as well as those based on the variance, but not better than, even if the evaluation criterion is based on the Reward-to-Semivariance ratio. When attention turns to the analysis of worst case performance, the results are clearly different. Models which employ LPM with a high degree of risk aversion (n>2) as the risk measure are consistently superior to those which employ a symmetric measure, either homoscedastic or heteroscedastic.
dc.description.statusPublicado
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationApplied economics, June 2005, Vol. 37, No. 11, p. 1267-1281
dc.identifier.doi10.1080/00036840500109142
dc.identifier.issn1466-4283 (electronic)
dc.identifier.issn0003-6846 (paper)
dc.identifier.publicationfirstpage1267
dc.identifier.publicationissue11
dc.identifier.publicationlastpage1281
dc.identifier.publicationtitleApplied economics
dc.identifier.publicationvolume37
dc.identifier.urihttps://hdl.handle.net/10016/7748
dc.language.isoeng
dc.publisherTaylor & Francis (Routledge)
dc.relation.publisherversionhttp://dx.doi.org/10.1080/00036840500109142
dc.rights©Taylor & Francis (Routledge)
dc.rights.accessRightsopen access
dc.subject.ecienciaEmpresa
dc.titleRisk forecasting models and optimal portfolio selection
dc.typeresearch article*
dc.type.reviewPeerReviewed
dspace.entity.typePublication
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