Publication Type
Journal Article
Version
publishedVersion
Publication Date
3-2006
Abstract
The literature on multivariate stochastic volatility (MSV) models has developed significantly over the last four years. This paper reviews the substantial literature on specification, estimation, and evaluation of MSV models. A wide range of MSV models is presented according to various categories, namely, (i) asymmetric models, (ii) factor models, (iii) time-varying correlation models, and (iv) alternative MSV specifications, including models based on the matrix exponential transformation, the Cholesky decomposition, and the Wishart autoregressive process. Alternative methods of estimation, including quasi-maximum likelihood, simulated maximum likelihood, and Markov chain Monte Carlo methods, are discussed and compared. Various methods of diagnostic checking and model comparison are also reviewed.
Keywords
Asymmetry, Diagnostic checking, Estimation, Factor models, Leverage, Model comparison, Multivariate stochastic volatility, Thresholds, Time-varying correlations, Transformations
Discipline
Econometrics
Research Areas
Econometrics
Publication
Econometric Reviews
Volume
25
Issue
2/3
First Page
145
Last Page
175
ISSN
0747-4938
Identifier
10.1080/07474930600713564
Publisher
Taylor and Francis
Embargo Period
2-22-2017
Citation
ASAI, Manabu; McAleer, Michael; and YU, Jun.
Multivariate stochastic volatility: A review. (2006). Econometric Reviews. 25, (2/3), 145-175.
Available at: https://ink.library.smu.edu.sg/soe_research/1912
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/10.1080/07474930600713564