Estimation of Hyperbolic Diffusion Using Mcmc Method

Author

Yiu Kuen TSE, Singapore Management UniversityFollow
Jun YU, Singapore Management UniversityFollow
X. B. CHANG, National University of Singapore

Publication Type

Working Paper

Publication Date

9-2002

Abstract

In this paper we propose a Bayesian method for estimating hyperbolic diffusion models. The approach is based on the Markov Chain Monte Carlo (MCMC) method after discretization via the Milstein scheme. Our simulation study shows that the hyperbolic diffusion exhibits many of the stylized facts about asset returns documented in the financial econometrics literature, such as a slowly declining autocorrelation function of absolute returns. We demonstrate that the MCMC method provides a useful tool to analyze hyperbolic diffusions. In particular, quantities of posterior distributions obtained from MCMC outputs can be used for statistical inferences

Keywords

Markov Chain Monte Carlo, Hyperbolic diffusion, Milstein approximation, ARCH, Long Memory

Discipline

Econometrics

Research Areas

Econometrics

Citation

TSE, Yiu Kuen; YU, Jun; and CHANG, X. B.. Estimation of Hyperbolic Diffusion Using Mcmc Method. (2002).
Available at: https://ink.library.smu.edu.sg/soe_research_all/5

Creative Commons License

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