Multivariate Stochastic Volatility: A Review

Manabu Asai, Michael McAleer and Jun Yu

Econometric Reviews, 2006, vol. 25, issue 2-3, 145-175

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, 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 (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (232)

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DOI: 10.1080/07474930600713564

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