Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/154270
Authors: 
Lucas, André
Schwaab, Bernd
Zhang, Xin
Year of Publication: 
2015
Series/Report no.: 
ECB Working Paper 1837
Abstract: 
We develop a novel high-dimensional non-Gaussian modeling framework to infer measures of conditional and joint default risk for numerous financial sector firms. The model is based on a dynamic Generalized Hyperbolic Skewed-t block-equicorrelation copula with time-varying volatility and dependence parameters that naturally accommodates asymmetries, heavy tails, as well as non-linear and time-varying default dependence. We apply a conditional law of large numbers in this setting to define joint and conditional risk measures that can be evaluated quickly and reliably. We apply the modeling framework to assess the joint risk from multiple defaults in the euro area during the 2008-2012 financial and sovereign debt crisis. We document unprecedented tail risks between 2011-2012, as well as their steep decline following subsequent policy actions.
Subjects: 
dynamic equicorrelation
generalized hyperbolic distribution
large portfolio approximation
law of large numbers
JEL: 
G21
C32
ISBN: 
978-92-899-1650-9
Document Type: 
Working Paper

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