Arbeitspapier
Some results on weak and strong tail dependence coefficients for means of copulas
Copulas represent the dependence structure of multivariate distributions in a natural way. In order to generate new copulas from given ones, several proposals found its way into statistical literature. One simple approach is to consider convex-combinations (i.e. weighted arithmetic means) of two or more copulas. Similarly, one might consider weighted geometric means. Consider, for instance, the Spearman copula, defined as the geometric mean of the maximum and the independence copula. In general, it is not known whether weighted geometric means of copulas produce copulas, again. However, applying a recent result of Liebscher (2006), we show that every weighted geometric mean of extreme-value copulas produces again an extreme-value copula. The second contribution of this paper is to calculate extremal dependence measures (e.g. weak and strong tail dependence coe±cients) for (weighted) geometric and arithmetic means of two copulas.
- Language
-
Englisch
- Bibliographic citation
-
Series: Diskussionspapier ; No. 78/2007
- Classification
-
Wirtschaft
- Subject
-
Tail Dependence
Extreme-value copulas
arithmetic and geometric mean
Kopula (Mathematik)
Extremwertanalyse
Maßzahl
Theorie
- Event
-
Geistige Schöpfung
- (who)
-
Fischer, Matthias J.
Klein, Ingo
- Event
-
Veröffentlichung
- (who)
-
Friedrich-Alexander-Universität Erlangen-Nürnburg, Lehrstuhl für Statistik und Ökonometrie
- (where)
-
Nürnberg
- (when)
-
2007
- Handle
- Last update
-
10.03.2025, 11:43 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Fischer, Matthias J.
- Klein, Ingo
- Friedrich-Alexander-Universität Erlangen-Nürnburg, Lehrstuhl für Statistik und Ökonometrie
Time of origin
- 2007
Other Objects (12)
Tail dependence of perturbed copulas
Copulas, stable tail dependence functions, and multivariate monotonicity
A new class of copulas with tail dependence and a generalized tail dependence estimator
Modelling dependence of extreme events in energy markets using tail copulas
On modeling financial risk with tail copulas
Multiplier bootstrap of tail copulas - with applications
Dependence modeling using vine copulas in insurance
Copulae and tail dependence
A note on upper tail behavior of Liouville copulas
Joint weak hazard rate order under non-symmetric copulas
Different Coefficients for Studying Dependence
Dependence measure for length-biased survival data using copulas
Tail dependence of perturbed copulas
Copulas, stable tail dependence functions, and multivariate monotonicity
A new class of copulas with tail dependence and a generalized tail dependence estimator
Modelling dependence of extreme events in energy markets using tail copulas
On modeling financial risk with tail copulas
Multiplier bootstrap of tail copulas - with applications
Dependence modeling using vine copulas in insurance
Copulae and tail dependence
A note on upper tail behavior of Liouville copulas
Joint weak hazard rate order under non-symmetric copulas
Different Coefficients for Studying Dependence
Dependence measure for length-biased survival data using copulas
Tail dependence of perturbed copulas
Copulas, stable tail dependence functions, and multivariate monotonicity
A new class of copulas with tail dependence and a generalized tail dependence estimator
Modelling dependence of extreme events in energy markets using tail copulas
On modeling financial risk with tail copulas
Multiplier bootstrap of tail copulas - with applications
Dependence modeling using vine copulas in insurance
Copulae and tail dependence
A note on upper tail behavior of Liouville copulas
Joint weak hazard rate order under non-symmetric copulas
Different Coefficients for Studying Dependence