@article{Estimator:1635,
      recid = {1635},
      author = {Diez de los Rios, Antonio},
      title = {A New Linear Estimator for Gaussian Dynamic Term Structure  Models},
      address = {2013},
      pages = {1 online resource (iii, 59 pages)},
      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.},
      url = {http://www.oar-rao.bank-banque-canada.ca/record/1635},
      doi = {https://doi.org/10.34989/swp-2013-10},
}