Estimation of Hyperbolic Diffusion Using Mcmc Method

Estimation of Hyperbolic Diffusion Using Mcmc Method

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...

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Bibliographic Details
Main Authors: TSE, Yiu Kuen, YU, Jun, CHANG, X. B.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2002
Subjects:
Markov Chain Monte Carlo
Hyperbolic diffusion
Milstein approximation
ARCH
Long Memory
Econometrics
Online Access:https://ink.library.smu.edu.sg/soe_research_all/5
https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1004&context=soe_research_all
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Institution: Singapore Management University
Language: English
Description
Summary: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

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