Publication Type

Journal Article

Publication Date

7-2004

Abstract

In this paper we propose a Bayesian method to estimate the hyperbolic diffusion model. The approach is based on the Markov chain Monte Carlo (MCMC) method with the likelihood of the discretized process as the approximate posterior likelihood. We demonstrate that the MCMC method Provides a useful tool in analysing hyperbolic diffusions. In particular, quantities of posterior distributions obtained from the MCMC outputs can be used for statistical inference. The MCMC method based on the Milstein scheme is unsatisfactory. Our simulation study shows that the hyperbolic diffusion exhibits many of the stylized facts about asset returns documented in the discrete-time financial econometrics literature, such as the Taylor effect, a slowly declining autocorrelation function of the squared returns, and thick tails.

Discipline

Econometrics

Research Areas

Econometrics

Publication

Quantitative Finance

Volume

4

Issue

2

First Page

158

Last Page

169

ISSN

1469-7688

Identifier

10.1080/14697680400000020

Publisher

Institute of Physics

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1080/14697680400000020

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Econometrics Commons

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