Bayesian inference with stochastic volatility models using continuous superpositions of non-Gaussian Ornstein-Uhlenbeck processes

Griffin, Jim E., Steel, Mark F.J. (2010) Bayesian inference with stochastic volatility models using continuous superpositions of non-Gaussian Ornstein-Uhlenbeck processes. Computational Statistics and Data Analysis, Online (54). pp. 2594-2608. ISSN 0167-9473. (doi:10.1016/j.csda.2009.06.008) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:24869)

This is the latest version of this item.

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL: http://dx.doi.org/10.1016/j.csda.2009.06.008

Abstract

Continuous superpositions of Ornstein–Uhlenbeck processes are proposed as a model for asset return volatility. An interesting class of continuous superpositions is defined by a Gamma mixing distribution which can define long memory processes. In contrast, previously studied discrete superpositions cannot generate this behaviour. Efficient Markov chain Monte Carlo methods for Bayesian inference are developed which allow the estimation of such models with leverage effects. The continuous superposition model is applied to both stock index and exchange rate data. The continuous superposition model is compared with a two-component superposition on the daily Standard and Poor’s 500 index from 1980 to 2000.

Item Type:	Article
DOI/Identification number:	10.1016/j.csda.2009.06.008
Subjects:	Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User:	Jim Griffin
Date Deposited:	29 Jun 2011 14:35 UTC
Last Modified:	05 Nov 2024 10:04 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/24869 (The current URI for this page, for reference purposes)

Available versions of this item

Bayesian inference with stochastic volatility models using continuous superpositions of non-Gaussian Ornstein-Uhlenbeck processes. (deposited 29 Jun 2011 14:35) [Currently Displayed]

University of Kent Author Information

Griffin, Jim E..

Creator's ORCID:	https://orcid.org/0000-0002-4828-7368
CReDIT Contributor Roles:

Depositors only (login required):

Altmetric

Download Statistics

Total unique views for this document in KAR since July 2020. For more details click on the image.