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
Markov Chain Monte Carlo, Hyperbolic diffusion, Milstein approximation, ARCH, Long Memory
TSE, Yiu Kuen; YU, Jun; and CHANG, X. B..
Estimation of Hyperbolic Diffusion Using Mcmc Method. (2002). Research Collection School of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research_all/5