Prediction of Federal Funds Target Rate: a dynamic logistic Bayesian Model averaging approach
dc.contributor.advisor | Ramírez Hassan, Andrés | |
dc.contributor.author | Alzate Arias, Hernán Alonso | |
dc.coverage.spatial | Medellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees | eng |
dc.creator.degree | Magíster en Economía | spa |
dc.creator.email | halzatea@eafit.edu.co | spa |
dc.date.accessioned | 2016-03-08T15:26:43Z | |
dc.date.available | 2016-03-08T15:26:43Z | |
dc.date.issued | 2015 | |
dc.description.abstract | In 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, respectively | spa |
dc.identifier.uri | http://hdl.handle.net/10784/8156 | |
dc.language.iso | spa | spa |
dc.publisher | Universidad EAFIT | spa |
dc.publisher.department | Escuela de Economía y Finanzas | spa |
dc.publisher.program | Maestría en Economía | spa |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | eng |
dc.rights.local | Acceso abierto | spa |
dc.subject.keyword | Macroeconomics | spa |
dc.subject.keyword | Bayesian statistical decision theory | spa |
dc.subject.keyword | Forecasting | spa |
dc.subject.keyword | Markov processes | spa |
dc.subject.keyword | Uncertainty | spa |
dc.subject.keyword | Econometric models | spa |
dc.subject.keyword | Monte carlo method | spa |
dc.subject.lemb | MACROECONOMÍA | spa |
dc.subject.lemb | TEORÍA BAYESIANA DE DECISIONES ESTADÍSTICAS | spa |
dc.subject.lemb | PREDICCIONES | spa |
dc.subject.lemb | PROCESOS DE MARKOV | spa |
dc.subject.lemb | INCERTIDUMBRE (ECONOMÍA) | spa |
dc.subject.lemb | MODELOS ECONOMÉTRICOS | spa |
dc.subject.lemb | MÉTODO DE MONTECARLO | spa |
dc.title | Prediction of Federal Funds Target Rate: a dynamic logistic Bayesian Model averaging approach | spa |
dc.type | masterThesis | eng |
dc.type | info:eu-repo/semantics/masterThesis | eng |
dc.type.hasVersion | acceptedVersion | eng |
dc.type.local | Tesis de Maestría | spa |
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