Template-type: ReDIF-Paper 1.0
Author-Name: Manabu Asai
Author-Email: m-asai@soka.ac.jp
Author-Person: pas73 
Author-Workplace-Name: Soka University / Faculty of Economics
Author-Workplace-Homepage: https://www.soka.ac.jp/economics/
Author-Name: Massimiliano Caporin
Author-Email: massimiliano.caporin@unipd.it
Author-Person: pca441
Author-Workplace-Name: Department of Economics and Management “Marco Fanno” University of Padova, Italy. 
Author-Name: Michael McAleer
Author-Person: pmc90 
Author-Workplace-Name: Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute,
	The Netherlands, Department of Quantitative Economics, Complutense University of Madrid, and Institute of
	Economic Research, Kyoto University
Title: Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models
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 was to combine the need for interpretability and efficiency faced 
	by model users with the computational problems that may emerge when the number of assets is quite large. 
	We contribute to this strand of the literature proposing a block-type parameterization for multivariate 
	stochastic volatility models. The empirical analysis on stock returns on 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 includes the global financial crisis.
Classification-JEL: C32, C51, C10.
Keywords: block structures; multivariate stochastic volatility; curse of dimensionality; leverage effects; multi-factors; 
	heavy-tailed distribution.
Length: 36 pages 
Creation-Date: 2012 
Number: 2012-03 
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/doicae1203.txt
File-URL: https://eprints.ucm.es/id/eprint/14621/1/1203.pdf
File-Format: Application/pdf
Handle: RePEc:ucm:doicae:1203