Handbook of Exchange Rates

8.3 Statistical Evaluation of Exchange Rate Predictability

The success or failure of empirical exchange rate models is typically determined by statistical tests of OOS predictive ability. Our statistical analysis tests for equal predictive ability between one of the empirical exchange rate models we estimate (UIP, PPP, MF, TR_s, or TR_a) and the benchmark RW model. In effect, we are comparing the performance of a parsimonious restricted null model (the RW, where β = 0) to a set of larger alternative unrestricted models that nest the parsimonious model (where ).⁷

We estimate all empirical exchange rate models using ordinary least squares (OLS) and then run a pseudo-OOS forecasting exercise as follows (Stock and Watson, 2003). Given today's known observables , we define an in-sample (IS) period using observations , and an OOS period using . This exercise produces OOS forecasts. Our empirical analysis uses T − 1 = 413 monthly observations, M = 120, and P = 293.⁸

In what follows, we describe ...