Abstract
Tail dependence and conditional tail dependence functions describe, respectively, the tail probabilities and conditional tail probabilities of a copula at various relative scales. The properties as well as the interplay of these two functions are established based upon their homogeneous structures. The extremal dependence of a copula, as described by its extreme value copulas, is shown to be completely determined by its tail dependence functions. For a vine copula built from a set of bivariate copulas, its tail dependence function can be expressed recursively by the tail dependence and conditional tail dependence functions of lower-dimensional margins. The effect of tail dependence of bivariate linking copulas on that of a vine copula is also investigated.
Original language | English |
---|---|
Pages (from-to) | 252-270 |
Number of pages | 19 |
Journal | Journal of Multivariate Analysis |
Volume | 101 |
Issue number | 1 |
DOIs | |
Publication status | Published - Jan 2010 |