Publication Type
Working Paper
Version
publishedVersion
Publication Date
12-2006
Abstract
The literature on multivariate stochastic volatility (MSV) models has developed significantly over the last few 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, Cholesky decomposition, Wishart autoregressive process, and the empirical range. Alternative methods of estimation, including quasi-maximum likelihood, simulated maximum likelihood, Monte Carlo likelihood, and Markov chain Monte Carlo methods, are discussed and compared. Various methods of diagnostic checking and model comparison are also examined.
Keywords
multivariate stochastic volatility, asymmetry, leverage, thresholds, factor models, time-varying correlations, transformations, estimation, diagnostic checking, model comparison
Discipline
Econometrics
Research Areas
Econometrics
First Page
1
Last Page
40
Publisher
SMU Economics and Statistics Working Paper Series, No. 33-2006
City or Country
Singapore
Citation
ASAI, Manabu; McAleer, Michael; and YU, Jun.
Multivariate stochastic volatility. (2006). 1-40.
Available at: https://ink.library.smu.edu.sg/soe_research/1130
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.
Comments
Published in Econometric Reviews, 2006. https://doi.org/10.1080/07474930600713564