dc.contributor.author | CANOVA, Fabio | |
dc.date.accessioned | 2011-04-20T14:03:34Z | |
dc.date.available | 2011-04-20T14:03:34Z | |
dc.date.issued | 1993 | |
dc.identifier.citation | Journal of Economic Dynamics & Control, 1993, 17, 01-feb, 233-261 | |
dc.identifier.issn | 0165-1889 | |
dc.identifier.uri | https://hdl.handle.net/1814/16754 | |
dc.description.abstract | This paper employs a multivariate Bayesian time-varying coefficients (TVC) approach to model and forecast exchange rate data. It is shown that, if used as a data-generating mechanism, a TVC model induces nonlinearities in the conditional moments and leptokurtosis in the unconditional distribution of the series. It is also shown that leptokurtic behavior disappears under time aggregation. As a forecasting device, a Bayesian TVC model improves over a random walk model. The improvements are robust to several changes in the forecasting environment. | |
dc.title | Modeling and Forecasting Exchange-Rates With a Bayesian Time-Varying Coefficient Model | |
dc.type | Article | |
dc.identifier.doi | 10.1016/0165-1889(93)90071-Y | |
dc.neeo.contributor | CANOVA|Fabio|aut| | |
dc.identifier.volume | 17 | |
dc.identifier.startpage | 233 | |
dc.identifier.endpage | 261 | |
eui.subscribe.skip | true | |
dc.identifier.issue | 01-feb | |