Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

Quantifying the impact of different copulas in a generalized CreditRisk+framework An empirical study

100%

Jakob K., Fischer M.

Dependence Modeling

2014

tom 2

nr 1

Without 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.

Dependent defaults and losses with factor copula models

52%

Ackerer D., Vatter T.

Dependence Modeling

2017

tom 5

nr 1

375-399

We present a class of flexible and tractable static factor models for the term structure of joint default probabilities, the factor copula models. These high-dimensional models remain parsimonious with paircopula constructions, and nest many standard models as special cases. The loss distribution of a portfolio of contingent claims can be exactly and efficiently computed when individual losses are discretely supported on a finite grid. Numerical examples study the key features affecting the loss distribution and multi-name credit derivatives prices. An empirical exercise illustrates the flexibility of our approach by fitting credit index tranche prices.

Ograniczanie wyników

2 Dependence Modeling

1 Ackerer D.

1 Fischer M.

1 Jakob K.

1 Vatter T.

1 2017

1 2014

Wyniki wyszukiwania

Quantifying the impact of different copulas in a generalized CreditRisk+framework An empirical study

Dependent defaults and losses with factor copula models