Evaluating non-linear models on point and interval forecasts: an application with exchange rates

The aim of this paper is to compare the forecasting performance of SETAR and GARCHmodels against a linear benchmark using historical data for two bilateral dollarexchange rates, namely the Japanese Yen and the British Pound. The analysis is carried out with series sampled at weekly and daily frequencies. The relative performance of the models is evaluated on point forecasts and interval forecasts.Point forecasts evaluation tends to favour on average the linear models, though the analysis produces some evidence of forecasting gains from nonlinear models in sub-samples characterised by stronger non-linearity. Evaluation of interval forecastsclearly favours the GARCH models and shows that they are more accurate than the AR and SETAR models, especially at forecasting events in the tail regions of the distribution.