Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/129723
Authors: 
Lucas, André
Schwaab, Bernd
Zhang, Xin
Year of Publication: 
2015
Series/Report no.: 
Sveriges Riksbank Working Paper Series 308
Abstract: 
We develop a novel high-dimensional non-Gaussian modeling framework to infer measures of conditional and joint default risk for many 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 during 2011-2012, as well as their steep decline after subsequent policy actions.
Subjects: 
dynamic equicorrelation
generalized hyperbolic distribution
law of large numbers
large portfolio approximation
JEL: 
C32
G21
Document Type: 
Working Paper

Files in This Item:
File
Size
527.25 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.