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dc.contributor.authorCarriero, Andreaen_US
dc.contributor.authorKapetanios, Georgeen_US
dc.contributor.authorMarcellino, Massimilianoen_US
dc.date.accessioned2012-02-09T14:07:09Z-
dc.date.available2012-02-09T14:07:09Z-
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/10419/55186-
dc.description.abstractModels based on economic theory have serious problems at forecasting exchange rates better than simple univariate driftless random walk models, especially at short horizons. Multivariate time series models suffer from the same problem. In this paper, we propose to forecast exchange rates with a large Bayesian VAR (BVAR), using a panel of 33 exchange rates vis-a-vis the US Dollar. Since exchange rates tend to co-move, the use of a large set of them can contain useful information for forecasting. In addition, we adopt a driftless random walk prior, so that cross-dynamics matter for forecasting only if there is strong evidence of them in the data. We produce forecasts for all the 33 exchange rates in the panel, and show that our model produces systematically better forecasts than a random walk for most of the countries, and at any forecast horizon, including at 1-step ahead.en_US
dc.language.isoengen_US
dc.publisherQueen Mary, Univ. of London, School of Economics and Finance Londonen_US
dc.relation.ispartofseriesWorking Paper // School of Economics and Finance, Queen Mary, University of London 634en_US
dc.subject.jelC53en_US
dc.subject.jelC11en_US
dc.subject.jelF31en_US
dc.subject.ddc330en_US
dc.subject.keywordexchange ratesen_US
dc.subject.keywordforecastingen_US
dc.subject.keywordBayesian VARen_US
dc.subject.stwWechselkursen_US
dc.subject.stwPrognoseen_US
dc.subject.stwVAR-Modellen_US
dc.subject.stwBayes-Statistiken_US
dc.subject.stwZeitreihenanalyseen_US
dc.subject.stwUSAen_US
dc.subject.stwWelten_US
dc.titleForecasting exchange rates with a large Bayesian VARen_US
dc.typeWorking Paperen_US
dc.identifier.ppn583815499en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:Working Paper Series, School of Economics and Finance, Queen Mary, University of London

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