The proposition that dynamic exchange rate models can outperform the random walk in out-of-sample forecasting, in the sense that they produce lower mean square errors, is examined and disputed. By using several dynamic versions of three macroeconomic exchange rate models, it is demonstrated that...

Several explanations have been put forward for the Meese--Rogoff puzzle that exchange rate models cannot outperform the random walk in out-of-sample forecasting. We suggest that a simple explanation for the puzzle is the use of the root mean square error (RMSE) to measure forecasting accuracy,...

It is demonstrated that carry trade can be made more profitable by taking into account the drift factor in the random walk behavior of the underlying exchange rate if it is significant. By using four currency combinations we find the drift factor to be significant at horizons longer than one...

It is demonstrated that the monetary model of exchange rates is better than the random walk in out-of-sample forecasting if forecasting accuracy is measured by metrics that take into account the magnitude of the forecasting errors and the ability of the model to predict the direction of change....

A continuous-time dynamic interpolation method for deriving high-frequency data is illustrated by deriving monthly data from quarterly data on two US macroeconomic variables: industrial production as a flow variable and the money supply as a stock variable. Analysis of the actual and...