AbstractWithout any doubt, credit risk is one of the most important risk types in the classical banking industry.
Consequently, banks are required by supervisory audits to allocate economic capital to cover unexpected
future credit losses. Typically, the amount of economical capital is determined with a credit portfolio model,
e.g. using the popular CreditRisk+ framework (1997) or one of its recent generalizations (e.g. [8] or [15]). Relying
on specific distributional assumptions, the credit loss distribution of the CreditRisk+ class can be determined
analytically and in real time. With respect to the current regulatory requirements (see, e.g. [4, p.
9-16] or [2]), banks are also required to quantify how sensitive their models (and the resulting risk figures) are
if fundamental assumptions are modified. Against this background, we focus on the impact of different dependence
structures (between the counterparties of the bank’s portfolio) within a (generalized) CreditRisk+
framework which can be represented in terms of copulas. Concretely, we present some results on the unknown
(implicit) copula of generalized CreditRisk+ models and quantify the effect of the choice of the copula
(between economic sectors) on the risk figures for a hypothetical loan portfolio and a variety of parametric
copulas.
GCPM: A ?exible package to explore credit portfolio risk