Estimating the term structure with linear regressions: Getting to the roots of the problem

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Abstract

Linear estimators of the affine term structure model are inconsistent since they cannot reproduce the factors used in estimation. This is a serious handicap empirically, giving a worse fit than the conventional ML estimator that ensures consistency. We show that a simple self-consistent estimator can be constructed using the eigenvalue decomposition of a regression estimator. The remaining parameters of the model follow analytically. Estimates from this model are virtually indistinguishable from that of the ML estimator. We apply the method to estimate various models of U.S. Treasury yields. These exercises greatly extend the range of models that can be estimated.
Original languageEnglish
Pages (from-to)1-25
Number of pages25
JournalJournal of Financial Econometrics
Early online date3 Dec 2019
DOIs
Publication statusE-pub ahead of print - 3 Dec 2019

Bibliographical note

The Author(s) 2019. Published by Oxford University Press. All rights reserved. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

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