Estimation of Hyperbolic Diffusion Using MCMC Method

Y. K. Tse (), Xibin Zhang () and Jun Yu

No 18/02, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

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 slowly declining autocorrelation function of absolute terms. 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. (search for similar items in EconPapers)
JEL-codes: C11 C15 C63 G15 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2002-09
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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Working Paper: Estimation of Hyperbolic Diffusion using MCMC Method (2002)
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