Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/95309
Authors: 
Bianchi, Carluccio
Fantazzini, Dean
De Giuli, Maria Elena
Maggi, Mario
Year of Publication: 
2009
Series/Report no.: 
Quaderni di Dipartimento 093
Abstract: 
Copula-GARCH models have been recently proposed in the financial literature as a statistical tool to build flexible multivariate distributions. Our extensive simulation studies investigate the small sample properties of these models and examine how misspecification in the marginals may affect the estimation of the dependence function represented by the copula. We show that the use of normal marginals when the true Data Generating Process is leptokurtic or asymmetric, produces negatively biased estimates of the normal copula correlations. A striking result is that these biases reach their highest value when correlations are strongly negative, and viceversa. This result remains unchanged with both positively skewed and negatively skewed data, while no biases are found if the variables are uncorrelated. Besides, the effect of marginals asymmetry on correlations is smaller than that of leptokurtosis. We finally analyse the performance of these models in terms of numerical convergence and positive definiteness of the estimated copula correlation matrix.
Subjects: 
Copulas
Copula-GARCH models
Maximum Likelihood
Simulation
Small Sample Properties
JEL: 
C15
C32
C51
C63
Document Type: 
Working Paper

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