We consider the forecasting performance of two SETAR exchange rate models proposed by Krager and Kugler (1993). Assuming that the models are good approximations to the data generating process, we show that whether the non-linearities inherent in the datacan be exploited to forecast better than a random walk depends on both how forecast accuracy is assessed and on the 'state of nature'.
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