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dc.contributor.advisorRamírez Hassan, Andrés
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.date.available2016-03-08T15:26:43Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/10784/8156
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.language.isospaspa
dc.publisherUniversidad EAFITspa
dc.rightsinfo:eu-repo/semantics/openAccesseng
dc.titlePrediction of Federal Funds Target Rate: a dynamic logistic Bayesian Model averaging approachspa
dc.typemasterThesiseng
dc.typeinfo:eu-repo/semantics/masterThesiseng
dc.rights.accessRightsopenAccesseng
dc.publisher.programMaestría en Economíaspa
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.publisher.departmentEscuela de Economía y Finanzasspa
dc.creator.degreeMagíster en Economíaspa
dc.type.spaTesis de Maestríaspa
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.rights.accesoLibre accesospa
dc.date.accessioned2016-03-08T15:26:43Z
dc.type.hasVersionacceptedVersioneng
dc.creator.emailhalzatea@eafit.edu.cospa
dc.contributor.authorAlzate Arias, Hernán Alonso


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