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dc.contributor.authorCasas I.en_US
dc.contributor.authorFerreira E.en_US
dc.contributor.authorSusan O.en_US
dc.date.accessioned2018-05-22T18:31:19Z
dc.date.available2018-05-22T18:31:19Z
dc.date.issued2017-01-01
dc.identifier.urihttp://hdl.handle.net/20.500.11824/796
dc.description.abstractThis paper provides a detailed analysis of the asymptotic properties of a kernel estimator for a Seemingly Unrelated Regression Equations model with time-varying coefficients (tv-SURE) under very general conditions. Theoretical results together with a simulation study differentiates the cases for which the estimation of a tv-SURE outperforms the estimation of a Single Regression Equations model with time-varying coefficients (tv-SRE). The study shows that Zellner's results cannot be straightforwardly extended to the time-varying case. The tv-SURE is applied to the Fama and French five-factor model using data from four different international markets. Finally, we provide the estimation under cross-restriction and discuss a testing procedure.en_US
dc.formatapplication/pdfen_US
dc.language.isoengen_US
dc.relationinfo:eu-repo/grantAgreement/EC/FP7/657182en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/en_US
dc.titleTime-varying coefficient estimation in SURE models. Application to portfolio management.en_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.typeinfo:eu-repo/semantics/submittedVersionen_US


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