A Monte Carlo Study of the Forecasting Performance of Empirical Setar Models
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 modeling exchange rates and GNP, amongst other variables. An indicator of when such models are likely to forecast well is suggested based on the serial dependence of regimes, as a means of distinguishing between types of nonlinearities that can be exploited for improved fit versus those that contribute to a better (relative to linear models) out-of-sample forecast performance. In our study the indicator provides a reasonable guide to those models which embody nonlinearities that may yield improved conditional mean forecasts.
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||1996|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: +44 (0) 2476 523202
Fax: +44 (0) 2476 523032
Web page: http://www2.warwick.ac.uk/fac/soc/economics/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:wrk:warwec:464. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Helen Neal)
If references are entirely missing, you can add them using this form.