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Multivariate Stochastic Volatility: A Review

Asai, Manabu ; McAleer, Michael ; Yu, Jun

Econometric reviews, 2006-01, Vol.25 (2-3), p.145-175 [Periódico revisado por pares]

New York: Taylor & Francis Group

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Título:
Multivariate Stochastic Volatility: A Review
Autor: Asai, Manabu ; McAleer, Michael ; Yu, Jun
Assuntos: Asymmetry ; Comparative analysis ; Correlation ; Diagnostic checking ; Econometrics ; Economic models ; Estimating techniques ; Estimation ; Factor models ; Leverage ; Model comparison ; Multivariate analysis ; Multivariate stochastic volatility ; Review articles ; Statistical models ; Stochastic models ; Stochastic processes ; Studies ; Thresholds ; Time series ; Time-varying correlations ; Transformations ; vG12
É parte de: Econometric reviews, 2006-01, Vol.25 (2-3), p.145-175
Notas: ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
Descrição: 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.
Editor: New York: Taylor & Francis Group
Idioma: Inglês

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Multivariate Stochastic Volatility: A Review

Asai, Manabu ; McAleer, Michael ; Yu, Jun

New York: Taylor & Francis Group

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