Beating the random walk in Central and Eastern Europe

Crespo-Cuaresma, Jesús and Hlouskova, JaroslavaORCID: (2005) Beating the random walk in Central and Eastern Europe. Journal of Forecasting, 24 (3), pp. 189-201. DOI: 10.1002/for.952

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We compare the accuracy of vector autoregressive (VAR), restricted vector autoregressive (RVAR), Bayesian vector autoregressive (BVAR), vector error correction (VEC) and Bayesian error correction (BVEC) models in forecasting the exchange rates of five Central and Eastern European currencies (Czech Koruna, Hungarian Forint, Slovak Koruna, Slovenian Tolar and Polish Zloty) against the US Dollar and the Euro. Although these models tend to outperform the random walk model for long-term predictions (6 months ahead and beyond), even the best models in terms of average prediction error fail to reject the test of equality of forecasting accuracy against the random walk model in short-term predictions.

Item Type: Article in Academic Journal
Keywords: vector autoregression, cointegration, Bayesian methods, forecasting, exchange rates, transition economies
Date Deposited: 22 May 2015 08:36
Last Modified: 13 Dec 2023 12:45
DOI: 10.1002/for.952
ISSN: 0277-6693 (Print), 1099-131X (Online)

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