Forecasting euro exchange rates: How much does model averaging help?
AbstractWe analyze the performance of Bayesian model averaged exchange rate forecasts for euro/US dollar, euro/Japanese yen, euro/Swiss franc and euro/British pound rates using weights based on the out-of-sample predictive likelihood. The paper also presents a simple stratified sampling procedure in the spirit of Sala i Martin et alia (2004) to obtain model weights based on predictive accuracy. Our results indicate that accounting explicitly for model uncertainty when constructing predictions of euro exchange rates leads to improvements in predictive accuracy as measured by the mean square forecast error. While the forecasting error of the combined forecast tends to be systematically smaller than that of the individual model that would have been chosen based on predictive accuracy in a test sample, random walk forecasts cannot be beaten significantly in terms of squared forecast errors. Direction of change statistics, on the other hand, are significantly improved by Bayesian model averaging.
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Bibliographic InfoPaper provided by Faculty of Economics and Statistics, University of Innsbruck in its series Working Papers with number 2007-24.
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Forecasting; model averaging; Bayesian econometrics; exchange rates.;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- F31 - International Economics - - International Finance - - - Foreign Exchange
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- Feldkircher, Martin, 2010.
"Forecast Combination and Bayesian Model Averaging - A Prior Sensitivity Analysis,"
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