A New Linear Estimator for Gaussian Dynamic Term Structure Models

A-Tier
Journal: Journal of Business & Economic Statistics
Year: 2015
Volume: 33
Issue: 2
Pages: 282-295

Score contribution per author:

4.036 = (α=2.02 / 1 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

This article proposes a novel regression-based approach to the estimation of Gaussian dynamic term structure models. This new estimator is an asymptotic least-square estimator defined by the no-arbitrage conditions upon which these models are built. Further, we note that our estimator remains easy-to-compute and asymptotically efficient in a variety of situations in which other recently proposed approaches might lose their tractability. We provide an empirical application in the context of the Canadian bond market.

Technical Details

RePEc Handle
repec:taf:jnlbes:v:33:y:2015:i:2:p:282-295
Journal Field
Econometrics
Author Count
1
Added to Database
2026-01-25