Optimal probabilistic forecast: when do they work?

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dc.contributor.affiliationUniversidad EAFITspa
dc.contributor.authorMartin, Gael M.
dc.contributor.authorLoaiza Maya, Rubén
dc.contributor.authorManeesoonthorn, Worapree
dc.contributor.authorT.Frazier, David
dc.contributor.authorRamírez Hassan, Andrés
dc.contributor.departmentEscuela de Finanzas, Economía y Gobierno
dc.contributor.researchgroupValor Público EAFIT
dc.date.accessioned2022-11-29T17:00:24Z
dc.date.available2022-11-29T17:00:24Z
dc.date.issued2021-08-12
dc.description.abstractThey use simulation exercises to check the predictive performance of single parametric models, and forecasts produced by linear combinations of predictive distributions to document several novel findings within this paradigm that highlight the important interplay between the true data generating process, the assumed predictive model and the scoring rule''.eng
dc.identifier.instnameinstname: Universidad EAFIT
dc.identifier.reponamereponame: Repositorio Institucional Universidad EAFIT
dc.identifier.urihttps://hdl.handle.net/10784/31969
dc.language.isoengspa
dc.publisherUniversidad EAFITspa
dc.relation.ispartofseriesNota de Política;5
dc.rightsopenAccesseng
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesseng
dc.rights.localAcceso abiertospa
dc.titleOptimal probabilistic forecast: when do they work?eng
dc.typeinfo:eu-repo/semantics/othereng
dc.typeothereng
dc.type.coarhttp://purl.org/coar/resource_type/c_1863eng
dc.type.hasVersionacceptedVersioneng
dc.type.localNoticiaspa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTOTReng

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