Comparing Forecast Performance of Exchange Rate Models

Abstract

Exchange-rate movement is regularly monitored by central banks for macroeconomic analysis and market surveillance purposes. Notwithstanding the pioneering study of Meese and Rogoff (1983), which shows the superiority of the random-walk model in out-of-sample exchange-rate forecast, there is some evidence that exchange-rate movement may be predictable at longer time horizons. This study compares the forecast performance of the Purchasing Power Parity model, Uncovered Interest Rate Party model, Sticky Price Monetary model, the model based on the Bayesian Model Averaging technique, and a combined forecast of all the above models with benchmarks given by the random-walk model and the historical average return. Empirical results suggest that the combined forecast outperforms the benchmarks and generally yields better results than relying on a single model.

Keywords: Bayesian Analysis, Model Evaluatin and Selection, Forecasting and Other Model Application

JEL Classification: C11, C52, C53