Publication Type
Journal Article
Version
acceptedVersion
Publication Date
8-2014
Abstract
Whether or not there is a unit root persistence in volatility of financial assets has been a long-standing topic of interest to financial econometricians and empirical economists. The purpose of this article is to provide a Bayesian approach for testing the volatility persistence in the context of stochastic volatility with Merton jump and correlated Merton jump. The Shanghai Composite Index daily return data is used for empirical illustration. The result of Bayesian hypothesis testing strongly indicates that the volatility process doesn’t have unit root volatility persistence in this stock market.
Keywords
Bayesian analysis, Calibration of stochastic volatility, Bayesian statistics, Financial time series, Financial econometrics, Volatility modelling
Discipline
Finance
Publication
Quantitative Finance
Volume
14
Issue
8
First Page
1415
Last Page
1426
ISSN
1469-7688
Identifier
10.1080/14697688.2014.880124
Publisher
Taylor & Francis (Routledge): SSH Titles
Citation
LIU, Xiaobin and LI, Yong.
Bayesian testing volatility persistence in stochastic volatility models with jumps. (2014). Quantitative Finance. 14, (8), 1415-1426.
Available at: https://ink.library.smu.edu.sg/soe_research/2202
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1080/14697688.2014.880124