The Monetary Model of Exchange Rates is Better than the Random Walk in Out-Of-Sample Forecasting
MetadataShow full item record
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. It is suggested that such a metric is the numerical value of the Wald test statistic for the joint coefficient restriction implied by the line of perfect forecast. The results reveal that the monetary model outperforms the random walk in out-of-sample forecasting for four different exchange rates.
Showing items related by title, author, creator and subject.
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 ...
Burns, Kelly; Moosa, I. (2017)Structural breaks have been suggested by several economists as a possible explanation for the Meese–Rogoff puzzle, in the sense that an exchange rate model can outperform the random walk in terms of the out-of-sample ...
Moosa, I.; Burns, Kelly (2015)For the past 30 years international monetary economists have believed that exchange rate models cannot outperform the random walk in out-of-sample forecasting as a result of the 1983 paper written by Richard Meese and ...