We propose a generalization of the Dynamic Conditional Correlation multivariate GARCH model of Engle (2002) and of the Asymmetric Dynamic Conditional Correlation model of Cappiello et al. (2006). The model we propose introduces a block structure in parameter matrices that allows for interdependence with a reduced number of parameters. Our model nests the Flexible Dynamic Conditional Correlation model of Billio et al. (2006) and is named Quadratic Flexible Dynamic Conditional Correlation Multivariate GARCH. In the paper, we provide conditions for positive definiteness of the conditional correlations. We also present an empirical application to the Italian stock market comparing alternative correlation models for portfolio risk evaluation.
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Paper provided by University of Venice "Ca' Foscari", Department of Economics in its series Working Papers with number
2006_53.
Find related papers by JEL classification: C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
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BAUWENS, Luc & LAURENT, SŽbastien & ROMBOUTS, Jeroen, 2003.
"Multivariate GARCH models: a survey,"
CORE Discussion Papers
2003031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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Cited by: (explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)
Annastiina Silvennoinen & Timo Teräsvirta, 2008.
"Multivariate GARCH models,"
CREATES Research Papers
2008-06, School of Economics and Management, University of Aarhus.
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