Abstract : Copulas are increasingly studied both in theory and practice as they are a convenient tool to construct multivariate distribution functions. However the material essentially covers the bi-variate case while in applications the number of variables is much higher. Furthermore, when one wants to take into account tail dependence, a desirable property is to have enough flexibility in the tails while avoiding the exponential growth of the number of parameters. We propose in this communication a one-factor model which exhibits this feature.
https://hal.archives-ouvertes.fr/hal-00863540
Contributeur : Stephane Girard
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Soumis le : jeudi 19 septembre 2013 - 10:36:54
Dernière modification le : mercredi 11 avril 2018 - 01:58:14
Document(s) archivé(s) le : vendredi 20 décembre 2013 - 15:06:34
