Forecasting the term structures of Treasury and corporate yields using dynamic Nelson-Siegel models
AbstractWe extend Diebold and Li’s dynamic Nelson-Siegel three-factor model to a broader empirical prospective by including the evaluation of the state space approach and by using nine different ratings for corporate bonds. We find that the dynamic Nelson-Siegel factor AR(1) model outperforms other competitors on the out-of-sample forecast accuracy, especially on the investment-grade bonds for the short-term forecast horizon and on the high-yield bonds for the long-term forecast horizon. The dynamic Nelson-Siegel factor state space model, however, becomes appealing on the high-yield bonds in the short-term forecast horizon, where the factor dynamics are more likely time-varying and parameter instability is more probable in the model specification.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal International Journal of Forecasting.
Volume (Year): 27 (2011)
Issue (Month): 2 ()
Contact details of provider:
Web page: http://www.elsevier.com/locate/ijforecast
Term structures; Treasury yields; Corporate yields; Nelson-Siegel model; Factor model; AR(1); VAR(1); Out-of-sample forecasting evaluations;
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Cem Çakmakli, 2012. "Bayesian Semiparametric Dynamic Nelson-Siegel Model," Working Paper Series 59_12, The Rimini Centre for Economic Analysis, revised Sep 2012.
- Kaya, Huseyin, 2013. "Forecasting the yield curve and the role of macroeconomic information in Turkey," Economic Modelling, Elsevier, vol. 33(C), pages 1-7.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If references are entirely missing, you can add them using this form.