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Forecast evaluation of nonlinear models: the case of long-span real exchange rates

Research output: Contribution to Journal/MagazineJournal articlepeer-review

<mark>Journal publication date</mark>2012
<mark>Journal</mark>Journal of Forecasting
Issue number7
Number of pages16
Pages (from-to)580-595
Publication StatusPublished
Early online date19/09/11
<mark>Original language</mark>English


This paper deals with the nonlinear modeling and forecasting of the dollar–sterling and franc–sterling real exchange rates using long spans of data. Our contribution is threefold. First, we provide significant evidence of smooth transition dynamics in the series by employing a battery of recently developed in-sample statistical tests. Second, we investigate the small-sample properties of several evaluation measures for comparing recursive forecasts when one of the competing models is nonlinear. Finally, we run a forecasting race for the post-Bretton Woods era between the nonlinear real exchange rate model, the random walk, and the linear autoregressive model. The nonlinear model outperforms all rival models in the dollar–sterling case but cannot beat the linear autoregressive in the franc–sterling.