Quasi-likelihood analysis for nonsynchronously observed diffusion processes

We consider nonsynchronous sampling of parameterized stochastic regression models, which contain stochastic differential equations. Constructing a quasi-likelihood function, we prove that the quasi-maximum likelihood estimator and the Bayes type estimator are consistent and asymptotically mixed normal when the sampling frequency of the nonsynchronous data becomes large.

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Year of publication:	2014
Authors:	Ogihara, Teppei ; Yoshida, Nakahiro
Published in:	Stochastic Processes and their Applications. - Elsevier, ISSN 0304-4149. - Vol. 124.2014, 9, p. 2954-3008
Publisher:	Elsevier
Subject:	Asymptotic mixed normality \| Bayes type estimators \| Diffusion processes \| Nonsynchronous observations \| Polynomial type large deviation inequality \| Quasi-likelihood analysis \| Quasi-maximum likelihood estimators

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010785363