On differentiability and mass distributions of typical bivariate copulas
Despite the fact that copulas are commonly considered as analytically smooth/regular objects,derivatives of copulas have to be handled with care. Triggered by a recently published resultcharacterizing multivariate copulas via (?? − 1)-increasingness of their partial derivative we studythe bivariate setting in detail and show that the set of non-differentiability points of a copula maybe quite large. We first construct examples of copulas ?? whose first partial derivative ??1??(??, ??)is pathological in the sense that for almost every ?? ∈ (0, 1) it does not exist on a dense subset of?? ∈ (0, 1), and then show that the family of these copulas is dense. Since in commonly consideredsubfamilies more regularity might be typical, we then focus on bivariate Extreme Value copulas(EVCs) and show that a topologically typical EVC is not absolutely continuous but has degenerateddiscrete component, implying that in this class typically ??1??(??, ??) exists in full (0, 1) 2.Considering that regularity of copulas is closely related to their mass distributions we then studymass distributions of topologically typical copulas and prove the surprising fact that topologicallytypical bivariate copulas are mutually completely dependent with full support. Furthermore, weuse the characterization of EVCs in terms of their associated Pickands dependence measures ?? on[0, 1], show that regularity of ?? carries over to the corresponding EVC and prove that the subfamilyof all EVCs whose absolutely continuous, discrete and singular component has full support is densein the class of all EVCs.
Authors
- Wolfgang Trutschnig (ORCID: https://orcid.org/0000-0002-7131-1944)
- Nicolas Dietrich (ORCID: https://orcid.org/0000-0001-6169-3101)
Publication Details
- Journal
- Fuzzy Sets and Systems
- Published
- 2024-10-16
- DOI
- https://doi.org/10.1016/j.fss.2024.109150
- Citations
- 3
- Primary Topic
- Financial Risk and Volatility Modeling
- Type
- article
- Field-Weighted Citation Impact
- 1.62
Funders
- Universität Salzburg