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Forecasting exchange rates in transition economies: A comparison of multivariate time series models

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  • Jesús Crespo Cuaresma

    ()

  • Jaroslava Hlouskova

    ()

Abstract

This article compares the accuracy of vector autoregressive (VAR), restricted vector autoregressive (RVAR), Bayesian vector autoregressive (BVAR), vector error correction (VEC) and Bayesian vector error correction (BVEC) models in forecasting the exchange rates for five Central and Eastern European currencies (Czech Koruna, Hungarian Forint, Polish Zloty, Slovak Koruna and Slovenian Tolar) against the Euro and the US dollar. Among the specifications composing this battery of multivariate time series models, those with the smallest prediction error still fail to reject the test of equality of forecasting accuracy against the random walk model in short-term predictions, with the exception of the Slovenian Tolar/Euro exchange rate. Copyright Springer-Verlag 2004

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File URL: http://hdl.handle.net/10.1007/s00181-004-0212-x
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Bibliographic Info

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 29 (2004)
Issue (Month): 4 (December)
Pages: 787-801

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Handle: RePEc:spr:empeco:v:29:y:2004:i:4:p:787-801

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Related research

Keywords: Vector autoregression; cointegration; Bayesian methods; exchange rates; transition economies; C53; P33; C32;

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