General-to-specific modelling of exchange rate volatility: A forecast evaluation
Luc Bauwens () and
International Journal of Forecasting, 2010, vol. 26, issue 4, 885-907
The general-to-specific (GETS) methodology is widely employed in the modelling of economic series, but less so in financial volatility modelling, due to its computational complexity when many explanatory variables are involved. This study proposes a simple way of avoiding this problem when the conditional mean can appropriately be restricted to zero, and undertakes an out-of-sample forecast evaluation of the methodology applied to the modelling of the weekly exchange rate volatility. Our findings suggest that GETS specifications perform comparatively well in both ex post and ex ante forecasting as long as sufficient care is taken with respect to the functional form and the way in which the conditioning information is used. Also, our forecast comparison provides an example of a discrete time explanatory model being more accurate than the realised volatility ex post in 1-step-ahead forecasting.
Keywords: Exchange; rate; volatility; General-to-specific; Forecasting (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
Working Paper: General-to-specific modelling of exchange rate volatility: a forecast evaluation (2010)
Working Paper: General to specific modelling of exchange rate volatility: a forecast evaluation (2008)
Working Paper: General to specific modelling of exchange rate volatility: a forecast evaluation (2006)
Working Paper: General to Specific Modelling of Exchange Rate Volatility: a Forecast Evaluation (2006)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:26:y::i:4:p:885-907
Access Statistics for this article
International Journal of Forecasting is currently edited by R. J. Hyndman
More articles in International Journal of Forecasting from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().