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Prediction of Federal Funds Target Rate: a dynamic logistic Bayesian Model averaging approach

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dc.contributor.advisorRamírez Hassan, Andrés
dc.contributor.authorAlzate Arias, Hernán Alonso
dc.coverage.spatialMedellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degreeseng
dc.creator.emailhalzatea@eafit.edu.cospa
dc.date.accessioned2016-03-08T15:26:43Z
dc.date.available2016-03-08T15:26:43Z
dc.date.issued2015
dc.description.abstractIn this paper we examine which macroeconomic and financial variables have most predictive power for the target repo rate decisions made by the Federal Reserve -- We conduct the analysis for the FOMC decisions during the period June 1998-April 2015 using dynamic logistic models with dynamic Bayesian Model Averaging that allows to perform predictions in real-time with great flexibility -- The computational burden of the algorithm is reduced by adapting a Markov Chain Monte Carlo Model Composition: MC3 -- We found that the outcome of the FOMC meetings during the sample period are predicted well: Logistic DMA-Up and Dynamic Logit-Up models present hit ratios of 87,2 and 88,7; meanwhile, hit ratios for the Logistic DMA-Down and Dynamic Logit-Down models are 79,8 and 68,0, respectivelyspa
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagíster en Economíaspa
dc.format.mimetypeapplication/pdf
dc.identifier.instnameinstname:Universidad EAFIT
dc.identifier.reponamereponame:Repositorio Institucional Universidad EAFIT
dc.identifier.repourlrepourl:https://repository.eafit.edu.co
dc.identifier.urihttps://hdl.handle.net/10784/8156
dc.language.isospa
dc.publisherUniversidad EAFITspa
dc.publisher.departmentDepartamento de Economíaspa
dc.publisher.facultyEscuela de Economía y Finanzasspa
dc.publisher.placeMedellínspa
dc.publisher.programMaestría en Economíaspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2
dc.rights.localAcceso abierto
dc.subject.keywordMacroeconomicsspa
dc.subject.keywordBayesian statistical decision theoryspa
dc.subject.keywordForecastingspa
dc.subject.keywordMarkov processesspa
dc.subject.keywordUncertaintyspa
dc.subject.keywordEconometric modelsspa
dc.subject.keywordMonte carlo methodspa
dc.subject.lembMACROECONOMÍAspa
dc.subject.lembTEORÍA BAYESIANA DE DECISIONES ESTADÍSTICASspa
dc.subject.lembPREDICCIONESspa
dc.subject.lembPROCESOS DE MARKOVspa
dc.subject.lembINCERTIDUMBRE (ECONOMÍA)spa
dc.subject.lembMODELOS ECONOMÉTRICOSspa
dc.subject.lembMÉTODO DE MONTECARLOspa
dc.titlePrediction of Federal Funds Target Rate: a dynamic logistic Bayesian Model averaging approach
dc.typeinfo:eu-repo/semantics/masterThesis
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.localTesis de Maestríaspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TM
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dspace.entity.typePublication

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Maestría en Economía (tesis)