Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/87505
Authors: 
Asai, Manabu
Caporin, Massimiliano
McAleer, Michael
Year of Publication: 
2013
Series/Report no.: 
Tinbergen Institute Discussion Paper 13-073/III
Abstract: 
Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on multivariate models with milder restrictions, whose purpose is to combine the need for interpretability and efficiency faced by model users with the computational problems that may emerge when the number of assets can be very large. We contribute to this strand of the literature by proposing a block-type parameterization for multivariate stochastic volatility models. The empirical analysis on stock returns on the US market shows that 1% and 5 % Value-at-Risk thresholds based on one-step-ahead forecasts of covariances by the new specification are satisfactory for the period including the Global Financial Crisis.
Subjects: 
block structures
multivariate stochastic volatility
curse of dimensionality
leverage effects
multi-factors
heavy-tailed distribution
JEL: 
C32
C51
C10
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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