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
Contributor : Stephane Girard <>
Submitted on : Thursday, September 19, 2013 - 10:36:54 AM Last modification on : Tuesday, February 9, 2021 - 3:20:20 PM Long-term archiving on: : Friday, December 20, 2013 - 3:06:34 PM