The random walk as a forecasting benchmark: drift or no drift?
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We examine the proposition that the random walk without drift is more powerful in predicting exchange rates than the random walk with drift. It is demonstrated that there is no theoretical reason why the random walk without drift always outperforms the random walk with drift and that this is an empirical issue. The results show that while the random walk without drift can outperform the random walk with drift in terms of the RMSE, it fails to do so in terms of the ability to predict the direction of change, measures that take into account magnitude and direction, and in terms of profitability. If the drift factor is allowed to change over time by estimating the model in time-varying parameter terms, the random walk with drift performs even better.
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Moosa, I.; Burns, Kelly (2014)It is demonstrated that the conventional monetary model of exchange rates can (irrespective of the specification, estimation method or the forecasting horizon) outperform the random walk in out-of-sample forecasting if ...
Moosa, I.; Burns, Kelly (2015)The Messe-Rogoff puzzle has been a debatable topic since 1983 when Richard Meese and Kenneth Rogoff demonstrated that no exchange rate model can outperform the random walk in out-of-sample forecasting. This finding been ...
Moosa, I.; Burns, Kelly (2014)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 ...