The Predictive Ability of Several Models of Exchange Rate Volatility

Abstract

We compare the out-of-sample forecasting performance of univariate homoskedastic, GARCH, autoregressive, and nonparametric models for conditional variances, using five bilateral weekly exchange rates for the dollar, 1973–1989. For a one-week horizon, GARCH models tend to make slightly more accurate forecasts. For longer horizons, it is difficult to find grounds for choosing between the various models. None of the models perform well in a conventional test of forecast efficiency.