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Bayesian Inference for Discretely Sampled Markov Processes with Closed-Form Likelihood Expansions.

The writers suggest a new Bayesian Markov chain Monte Carlo (MCMC) methodology to estimate a wide class of multidimensional jump-diffusion models. They base their approach on the closed-form (CF) likelihood approximations of Ait-Sahalia. They report that the CF likelihood approximation does not in...

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Published in:Journal of Financial Econometrics Vol. 8; no. 4; pp. 450 - 481
Main Authors: Stramer, Osnat, Bognar, Matthew, Schneider, Paul
Format: Article
Published: Oxford University Press / UK Fall 2010
Subjects:
Bayesian analysis
Markov processes
Monte Carlo method
Diffusion processes
Maximum likelihood statistics
Online Access:View this record in EBSCOhost

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