Korean exchange rate forecasts using Bayesian variable selection

Abstract

Using Bayesian variable selection, we demonstrate that economic variables forecast Korea-US exchange rates better than random walk or random walk with drift model at a short horizon. It implies that the failure of out-of-sample exchange rate forecasts is due to the uncertainties associated with selecting proper predictors, rather than the lack of relationship between the exchange rate and its theoretical determinants. Our results also suggest that time-variant and asymmetric weights on predictors should be taken into account to understand exchange rates dynamics. (JEL classification: C11, C53, F31)