EconPapers    
Economics at your fingertips  
 

How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?

Andrea Carriero and Raffaella Giacomini ()

Journal of Econometrics, 2011, vol. 164, issue 1, 21-34

Abstract: We develop a general framework for analyzing the usefulness of imposing parameter restrictions on a forecasting model. We propose a measure of the usefulness of the restrictions that depends on the forecaster's loss function and that could be time varying. We show how to conduct inference about this measure. The application of our methodology to analyzing the usefulness of no-arbitrage restrictions for forecasting the term structure of interest rates reveals that: (1)Â the restrictions have become less useful over time; (2)Â when using a statistical measure of accuracy, the restrictions are a useful way to reduce parameter estimation uncertainty, but are dominated by restrictions that do the same without using any theory; (3)Â when using an economic measure of accuracy, the no-arbitrage restrictions are no longer dominated by atheoretical restrictions, but for this to be true it is important that the restrictions incorporate a time-varying risk premium.

Keywords: Forecast; combination; Encompassing; Loss; functions; Instability; Affine; term; structure; models (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (36)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407611000376
Full text for ScienceDirect subscribers only

Related works:
Working Paper: How useful are no-arbitrage restrictions for forecasting the term structure of interest rates? (2011) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:164:y:2011:i:1:p:21-34

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-23
Handle: RePEc:eee:econom:v:164:y:2011:i:1:p:21-34