Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/80737
Authors: 
Diez de los Rios, Antonio
Year of Publication: 
2013
Series/Report no.: 
Bank of Canada Working Paper 2013-10
Abstract: 
This paper proposes a novel regression-based approach to the estimation of Gaussian dynamic term structure models that avoids numerical optimization. This new estimator is an asymptotic least squares estimator defined by the no-arbitrage conditions upon which these models are built. We discuss some efficiency considerations of this estimator, and show that it is asymptotically equivalent to maximum likelihood estimation. Further, we note that our estimator remains easy-to-compute and asymptotically efficient in a variety of situations in which other recently proposed approaches lose their tractability. We provide an empirical application in the context of the Canadian bond market.
Subjects: 
Asset pricing
Econometric and statistical methods
Interest rates
JEL: 
E43
C13
G12
Document Type: 
Working Paper

Files in This Item:
File
Size
648.22 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.