Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics

Andre Lucas, Bernd Schwaab and Xin Zhang

Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: Forthcoming in the 'Journal of Applied Econometrics'.

We develop a novel high-dimensional non-Gaussian modeling framework to infer conditional and joint risk measures 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 demonstrate how to apply a conditional law of large numbers in this setting to define risk measures that can be evaluated quickly and reliably. We apply the modeling framework to assess the joint risk from multiple financial firm defaults in the euro area during the 2008-2012 financial and sovereign debt crisis. We document unprecedented tail risks during 2011-12, as well as their steep decline after subsequent policy actions.

Keywords: systemic risk; dynamic equicorrelation model; generalized hyperbolic distribution; Law of Large Numbers (search for similar items in EconPapers)
JEL-codes: C32 G21 (search for similar items in EconPapers)
Date: 2013-05-13, Revised 2014-10-13
New Economics Papers: this item is included in nep-ban, nep-ecm and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20130063

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