||This paper examines whether oil prices have significant predictive ability in forecasting nominal exchange rates out-of-sample, and we compare the linear and non-linear oil price models forecast with those of the random walk, which, to date, is the toughest benchmark to beat. We implement the Diebold and Mariano’s (1995) test of equal predictive ability by comparing the Root Mean Squared Error(RMSE) recorded in the daily and monthly data of ten countries between 2004 and 2017. |
Under rolling regression analysis, empirical results indicate that predictability depends on forecast horizon, frequency of the data, model specification, and forecast evaluation method. Our empirical results suggest that oil prices can predict the nominal exchange rate at a daily frequency and small in-sample estimation window sizes. However, the predictive ability is not evident at monthly frequencies.
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