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MULTIVARIATE STOCHASTIC VOLATILITY: A REVIEW

By Manabu Asai, Michael McAleer and Jun Yu

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

Topics: JEL Classification C11, C15, C32, G12
Year: 2006
OAI identifier: oai:CiteSeerX.psu:10.1.1.135.562
Provided by: CiteSeerX
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