Editorial to the special issue on “Random Variables, Joint Distribution Functions, and Copulas”
Fabrizio Durante, Radko Mesiar, Carlo Sempi (2008)
Kybernetika
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Fabrizio Durante, Radko Mesiar, Carlo Sempi (2008)
Kybernetika
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Kevin Jakob, Matthias Fischer (2014)
Dependence Modeling
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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...
Manuel Úbeda-Flores (2008)
Kybernetika
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In this paper we study some properties of the distribution function of the random variable C(X,Y) when the copula of the random pair (X,Y) is M (respectively, W) – the copula for which each of X and Y is almost surely an increasing (respectively, decreasing) function of the other –, and C is any copula. We also study the distribution functions of M(X,Y) and W(X,Y) given that the joint distribution function of the random variables X and Y is any copula.
Hürlimann, Werner (2004)
International Journal of Mathematics and Mathematical Sciences
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Fabrizio Durante, Pier Luigi Papini (2009)
Kybernetika
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The class of componentwise concave copulas is considered, with particular emphasis on its closure under some constructions of copulas (e.g., ordinal sum) and its relations with other classes of copulas characterized by some notions of concavity and/or convexity. Then, a sharp upper bound is given for the -measure of non-exchangeability for copulas belonging to this class.