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

Stan Hurn, K.A. Lindsay and A.J. McClelland

Journal of Econometrics, 2013, vol. 172, issue 1, 106-126

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.

Keywords: Stochastic differential equations; Parameter estimation; Quasi-maximum likelihood; Moments (search for similar items in EconPapers)
JEL-codes: C22 C52 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (8)

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Working Paper: A quasi-maximum likelihood method for estimating the parameters of multivariate diffusions (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:172:y:2013:i:1:p:106-126

DOI: 10.1016/j.jeconom.2012.09.002

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