A quasi-maximum likelihood method for estimating the parameters of multivariate diffusions

Hurn, A.S., Lindsay, K.A., & McClelland, A.J. (2013) A quasi-maximum likelihood method for estimating the parameters of multivariate diffusions. Journal of Econometrics, 172(1), pp. 106-126.

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Abstract

A quasi-maximum likelihood procedure for estimating the parameters of multi-dimensional diffusions is developed in which the transitional density is a multivariate Gaussian density with first and second moments approximating the true moments of the unknown density. For affine drift and diffusion functions, the moments are exactly those of the true transitional density and for nonlinear drift and diffusion functions the approximation is extremely good and is as effective as alternative methods based on likelihood approximations. The estimation procedure generalises to models with latent factors. A conditioning procedure is developed that allows parameter estimation in the absence of proxies.

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6 citations in Scopus
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7 citations in Web of Science®

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ID Code: 60148
Item Type: Journal Article
Refereed: Yes
Keywords: Stochastic differential equations, Parameter estimation, Quasi-maximum likelihood, Moments
DOI: 10.1016/j.jeconom.2012.09.002
ISSN: 03044076
Divisions: Current > QUT Faculties and Divisions > QUT Business School
Current > Schools > School of Economics & Finance
Copyright Owner: Copyright 2012 Elsevier B.V.
Copyright Statement: NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Econometrics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Econometrics, [Volume 172, Issue 1, (January 2013)] DOI: 10.1016/j.jeconom.2012.09.002
Deposited On: 21 May 2013 23:13
Last Modified: 01 Feb 2016 20:44

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