The out-of-sample forecasting performance of non-linear models of real exchange rate behaviour: The case of the South African Rand

Abstract

This paper analyses the out-of-sample forecasting performance of non-linear vs. linear models for the South African rand against the United States dollar and the British pound, in real terms. We compare the forecasting performance of point, interval and density forecasts for non-linear Band-TAR and ESTAR models to linear autoregressive models. Our data spans from 1970:01 to 2012:07, and we found that there are no significant gains from using either the Band-TAR or ESTAR non-linear models, compared to the linear AR model in terms of out-of-sample forecasting performance, especially at short horizons. We draw similar conclusions to other literature, and find that for the South African rand against the United States dollar and British pound, non-linearities are too weak for Band-TAR and ESTAR models to estimate.