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Beating the random walk in Central and Eastern Europe
Author(s) -
Cuaresma Jesús Crespo,
Hlouskova Jaroslava
Publication year - 2005
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.952
Subject(s) - random walk , autoregressive model , us dollar , bayesian vector autoregression , bayesian probability , econometrics , autoregressive integrated moving average , vector autoregression , term (time) , random walk hypothesis , error correction model , computer science , statistics , mathematics , exchange rate , economics , time series , cointegration , geography , macroeconomics , physics , context (archaeology) , archaeology , quantum mechanics , stock market
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. Copyright © 2005 John Wiley & Sons, Ltd.