Quasi-likelihood analysis for nonsynchronously observed diffusion processes

STOCHASTIC PROCESSES AND THEIR APPLICATIONS

卷:124

Article

Ogihara, Teppei^1,2  Yoshida, Nakahiro³ 

[1] Osaka Univ, Ctr Study Finance & Insurance, Toyonaka, Osaka 5608531, Japan

[2] Japan Sci & Technol Agcy, CREST, Tokyo, Japan

[3] Univ Tokyo, Grad Sch Math Sci, Meguro Ku, Tokyo 1538914, Japan

关键词: Asymptotic mixed normality;    Bayes type estimators;    Diffusion processes;    Nonsynchronous observations;    Polynomial type large deviation inequality;    Quasi-likelihood analysis;    Quasi-maximum likelihood estimators;   

DOI  :  10.1016/j.spa.2014.03.014

来源: Elsevier

【 摘 要 】

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. (C) 2014 Elsevier B.V. All rights reserved.

【 授权许可】

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