Modeling financial sector joint tail risk in the euro area
Andre Lucas () and
No 1837, Working Paper Series from European Central Bank
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. JEL Classification: G21, C32
Keywords: dynamic equicorrelation; generalized hyperbolic distribution; large portfolio approximation; law of large numbers (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed
Downloads: (external link)
Journal Article: Modeling Financial Sector Joint Tail Risk in the Euro Area (2017)
Working Paper: Modeling financial sector joint tail risk in the euro area (2015)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbwps:20151837
Access Statistics for this paper
More papers in Working Paper Series from European Central Bank 60640 Frankfurt am Main, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Official Publications ().