Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Copulas, stable tail dependence functions, and multivariate monotonicity

Copulas, stable tail dependence functions, and multivariate monotonicity AbstractFor functions of several variables there exist many notions of monotonicity, three of them being characteristic for resp. distribution, survival and co-survival functions. In each case the “degree” of monotonicity is just the basic one of a whole scale.Copulas are special distribution functions, and stable tail dependence functions are special co-survival functions. It will turn out that for both classes the basic degree of monotonicity is the only one possible, apart from the (trivial) independence functions. As a consequence a “nesting” of such functions depends on particular circumstances. For nested Archimedean copulas the rather restrictive conditions known so far are considerably weakened. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Dependence Modeling de Gruyter

Copulas, stable tail dependence functions, and multivariate monotonicity

Ressel, Paul
Dependence Modeling , Volume 7 (1): 12 – Jan 1, 2019
Download PDF
12 pages

Loading next page...
 
/lp/de-gruyter/copulas-stable-tail-dependence-functions-and-multivariate-monotonicity-E0eKGWkHBn
Publisher
de Gruyter
Copyright
© 2019 Paul Ressel, published by De Gruyter
ISSN
2300-2298
eISSN
2300-2298
DOI
10.1515/demo-2019-0013
Publisher site
See Article on Publisher Site

Abstract

AbstractFor functions of several variables there exist many notions of monotonicity, three of them being characteristic for resp. distribution, survival and co-survival functions. In each case the “degree” of monotonicity is just the basic one of a whole scale.Copulas are special distribution functions, and stable tail dependence functions are special co-survival functions. It will turn out that for both classes the basic degree of monotonicity is the only one possible, apart from the (trivial) independence functions. As a consequence a “nesting” of such functions depends on particular circumstances. For nested Archimedean copulas the rather restrictive conditions known so far are considerably weakened.

Journal

Dependence Modeling – de Gruyter

Published: Jan 1, 2019

References

  • Monotonicity properties of multivariate distribution and survival functions With an application to Lévy - frailty copulas
    Ressel
  • Theory of capacities Fourier
    Choquet
  • Functions operating on multivariate distribution and survival functions With applications to classical mean - values and to copulas
    Ressel
  • Constructing hierarchical Archimedean copulas with subordinators
    Hering
  • Mai note on the Galambos copula and its associated Bernstein function Depend Model
  • characterization of absolutely monotonic functions of a fixed order
    Morillas
  • l impossibilité de construire des lois à marges multi - dimensionelles données à partir de copules
    Genest
  • Multivariate copulas
    Charpentier
  • The class of multivariate max - id copulas with ℓ norm symmetric exponent measure
    Genest
  • Higher order monotonic functions of several variables
    Ressel
  • On the construction of nested Archimedean copulas ford - monotone generators
    Rezapour
  • Mai extendible copulas
    Scherer
  • Homogeneous distributions And a spectral representation of classical mean values and stable tail dependence functions
    Ressel