Abstract The seminal study of Meese et al. (1983) on exchange rate
forecastability had a great impact on the international finance literature.
The authors showed that exchange rate forecasts based on structural models
are worse than a naive random walk. This result is known as the
Meese--Rogoff (MR) puzzle. Although the validity of this result has been
checked for many currencies, studies for the Brazilian currency are not
common. In 1999, Brazil adopted the dirty floating exchange rate regime.
Rossi (2013) ran an extensive study on the MR puzzle but did not analyse
Brazilian data. Our goal is to run a “pseudo real-time experiment” to
investigate whether forecasts based on econometric models that use the
fundamentals suggested by the exchange rate monetary theory of the 80s can
beat the random model for the case of the Brazilian currency. Our work has
three main differences with respect to Rossi (2013). We use a bias
correction technique and forecast combination in an attempt to improve the
forecast accuracy of our projections. We also combine the random walk
projections with the projections of the structural models to investigate if
it is possible to further improve the accuracy of the random walk forecasts.
However, our results are quite in line with Rossi (2013). We show that it is
not difficult to beat the forecasts generated by the random walk with drift
using Brazilian data, but that it is quite difficult to beat the random walk
without drift. Our results suggest that it is advisable to use the random
walk without drift, not only the random walk with drift, as a benchmark in
exercises that claim the MR result is not valid.
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