Quasi-Likelihood Analysis for Stochastic Regression Models with Nonsynchronous Observations

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 norm...

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Bibliographic Details
Published in:arXiv.org 2012-12
Main Authors: Ogihara, Teppei, Yoshida, Nakahiro
Format: Article
Language:English
Subjects:
Differential equations
Economic models
Maximum likelihood estimators
Monte Carlo simulation
Regression models
Sampling
Online Access:Get full text
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Summary: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.
ISSN:2331-8422