Regressions of multiple-period changes in the log exchange rate on the deviation of the log exchange rate from its "fundamental value," display evidence that long-horizon changes in log nominal exchange rates contain an economically significant predictable component. To account for small-sample bias and size distortion in asymptotic tests, inference is drawn from bootstrap distributions generated under the null hypothesis that the log exchange rate is unpredictable. The bias-adjusted slope coefficients and R^2's increase with the forecast horizon, and the out-of-sample point predictions generally outperform the driftless random walk at the longer horizons.

Regressions of multiple-period changes in the log exchange rate on the deviation of the log exchange rate from its 'fundamental value' display evidence that long-horizon changes in log nominal exchange rates contain an economically significant predictable component. To account for small-sample bias and size distortion in asymptotic tests, inference is drawn from bootstrap distributions generated under the null hypothesis that the log exchange rate is unpredictable. The bias-adjusted slope coefficients and R[superscript]2's increase with the forecast horizon, and the out-of-sample point predictions generally outperform the driftless random walk at the longer horizons.