Publication Type
Journal Article
Version
publishedVersion
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
Citation
TSE, Yiu Kuen; ZHANG, Xibin; and YU, Jun.
Estimation of hyperbolic diffusion using Markov chain Monte Carlo method. (2004). Quantitative Finance. 4, (2), 158-169.
Available at: https://ink.library.smu.edu.sg/soe_research/518
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1080/14697680400000020