Copula convergence theorems for tail events

By Alessandro Juri, Mario V. Wüthrich. 2002

139 citations recorded by the source corpus.

Subfields: Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/eb107be0573b19fd52ad68cde155b8434d47657c

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Citations in the corpus

Diversification of aggregate dependent risks (2004, background): “7) have Clayton copula, this is not surprising in view of the results presented in Juri-Wüthrich [13].”
Economic Capital and the Aggregation of Risks Using Copulas (2009, background): “See, for example, Juri and Wüthrich (2002) for some useful asymptotic results leading to Clayton copulas.”
Using copulae to bound the Value-at-Risk for functions of dependent risks (2003, methodology): “A motivation for the use of CCl,α when dealing with conditional bivariate extremes is given in Juri and Wüthrich (2002).”
Tail asymptotics for the sum of two heavy-tailed dependent risks (2006, background): “For Archimedean copulae this result could be exploited in Wüthrich [32] and Alink et al. [2] to give sharp asymptotics of the tail of X1 +X2, see Section 3.3.”
Copulas: A Personal View (2009, unknown): “See Juri and Wüthrich [26] for the original paper on the subject, Alink [2] for several extensions and Balkema and Qi [4] for the ultimate uniqueness result as a closure property.”
Lower tail dependence for Archimedean copulas: Characterizations and pitfalls (2007, methodology): “In Juri and Wüthrich (2002), tail dependence for bivariate Archimedean copulas is described using the concept of lower tail dependence copulas. The lower tail dependence copula of a copula C at level 0 < u < 1 is defined as the copula of the conditional distribution of a random pair (U, V ) with dis”
Spatial contagion between financial markets: a copula-based approach (2010, methodology): “Secondly, the calculation of the threshold copulas is sometimes a difficult task and requires a non-trivial computational effort (although several theoretical results are already available [ 23 , 26, 27, 31]).”
Distorted Copulas: Constructions and Tail Dependence (2010, background): “More general results about the tail dependence coefficients of an Archimedean copula are given by Juri and Wüthrich (2002, 2003) and Charpentier and Segers (2007, 2009) in terms of regularly varying properties of the additive generator.”
Dynamic copula models for multivariate high-frequency data in finance (2004, background): “In the same spirit, Juri and Wüthrich (2002) showed that for a wide class of so-called Archimedean dependence structures, the extreme tail-dependence copula has the Clayton copula as a limit.”
Absolutely Continuous Copulas with Given Diagonal Sections (2008, background): “…tail dependence coefficients) have been largely considered in several financial applications: see, for example, Albrecher et al. (2006), Charpentier and Segers (2007), Frahm et al. (2005), Juri and Wüthrich (2002), Malevergne and Sornette (2006), Schmidt and Stadtmüller (2006), and Zhang (2008).”
Estimating the tail-dependence coefficient: Properties and pitfalls (2005, methodology): “Thus it is absolutely necessary to test for tail dependence in the first instance; see Ledford and Tawn (1996), Draisma et al.”
Limiting dependence structures for tail events, with applications to credit derivatives (2006, methodology): “In fact, there are situations in which the knowledge of the limiting dependence structure reduces the issue of modeling tail events to the estimation of only one parameter (Juri and Wüthrich (2002)).”
Semi‐Parametric Models for the Multivariate Tail Dependence Function – the Asymptotically Dependent Case (2008, methodology): “Then the dependence is completely determined by the copula C of X given by Sklar’s representation (see Nelsen (1998) or Joe (1997) )”