Article thumbnail
Location of Repository

A Monte Carlo study of the forecasting performance of empirical SETAR models

By Michael P. Clements and Jeremy Smith


In this paper we investigate the multi-period forecast performance of a number of empirical self-exciting threshold autoregressive (SETAR) models that have been proposed in the literature for modelling exchange rates acid GNP, among other variables. We take each of the empirical SETAR models in turn as the DGP to ensure that the 'non-linearity' characterizes the future, and compare the forecast performance of SETAR and linear autoregressive models on a number of quantitative and qualitative criteria. Our results indicate that non-linear models have an edge in certain states of nature but not in others, and that this can be highlighted by evaluating forecasts conditional upon the regime. Copyright (C) 1999 John Wiley & Sons, Ltd

Topics: HC, H
Publisher: Wiley-Blackwell Publishing, Inc
Year: 1999
DOI identifier: 10.1002/(sici)1099-1255(199903/04)14:2<123::aid-jae493>;2-k
OAI identifier:
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.