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dc.creatorPINCHEIRA,PABLO M
dc.date2013-10-01
dc.date.accessioned2019-05-03T14:02:38Z
dc.date.available2019-05-03T14:02:38Z
dc.identifierhttps://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-88702013000200001
dc.identifier.urihttp://revistaschilenas.uchile.cl/handle/2250/89554
dc.descriptionIn this paper we evaluate exchange rate predictability using a framework developed by Giacomini and White (2006). This new framework tests for conditional predictive ability rather than unconditional predictive ability, which has been the standard approach. Using several shrinkage based forecasting methods, including new methods proposed here, we evaluate conditional predictability of five bilateral exchange rates at differing horizons. Our results indicate that for most currencies a random walk would not be the optimal forecasting method in a real time forecasting exercise, at least for some predictive horizons. We also show that our proposed shrinkage methods in general perform on par with Bayesian shrinkage and ridge regressions, and sometimes they even perform better.
dc.formattext/html
dc.languageen
dc.publisherILADES. Universidad Alberto Hurtado.
dc.relation10.4067/S0718-88702013000200001
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceRevista de análisis económico v.28 n.2 2013
dc.subjectExchange rate predictability
dc.subjectconditional predictive ability
dc.subjectBayesian shrinkage
dc.subjectridge regression
dc.subjectforecast evaluation
dc.titleCONDITIONAL PREDICTIVE ABILITY OF EXCHANGE RATES IN LONG RUN REGRESSIONS: UNA EVALUACION CONDICIONAL CON REGRESIONES DE LARGO PLAZO


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