Closed-Form Likelihood Expansions for Multivariate Diffusions
This paper provides closed-form expansions for the transition density and likelihood function of arbitrary multivariate diffusions. The expansions are based on a Hermite series, whose coefficients are calculated explicitly by exploiting the special structure afforded by the diffusion hypothesis. Because the transition function for most diffusion models is not known explicitly, the expansions of this paper can help make maximum-likelihood a practical estimation method for discretely sampled multivariate diffusions. Examples of interest in financial econometrics are included.
|Date of creation:||May 2002|
|Publication status:||published as Ait-Sahalia, Yacine. "Closed-Form Likelihood Expansions for Multivariate Diffusions," Annals of Statistics, 2008, 36, 906-937. (1,Jan), 223-262.|
|Contact details of provider:|| Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.|
Web page: http://www.nber.org
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- Yacine Aït-Sahalia & Robert Kimmel, 2002.
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NBER Technical Working Papers
0286, National Bureau of Economic Research, Inc.
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- Yacine Ait-Sahalia & Per A. Mykland, 2002.
"The Effects of Random and Discrete Sampling When Estimating Continuous-Time Diffusions,"
NBER Technical Working Papers
0276, National Bureau of Economic Research, Inc.
- Yacine Ait--Sahalia & Per A. Mykland, 2003. "The Effects of Random and Discrete Sampling when Estimating Continuous--Time Diffusions," Econometrica, Econometric Society, vol. 71(2), pages 483-549, March.
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