Tail dependence functions and vine copulas

Harry Joe, Haijun Li and Aristidis K. Nikoloulopoulos

Journal of Multivariate Analysis, 2010, vol. 101, issue 1, 252-270

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.

Keywords: Archimedean; copulas; Conditional; tail; D-vine; C-vine; Extreme; value (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (112)

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