Extreme residual dependence for random vectors and processes
De Haan, Laurens ; Zhou, Chen
Adv. in Appl. Probab., Tome 43 (2011) no. 1, p. 217-242 / Harvested from Project Euclid
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A two-dimensional random vector in the domain of attraction of an extreme value distribution G is said to be asymptotically independent (i.e. in the tail) if G is the product of its marginal distribution functions. Ledford and Tawn (1996) discussed a form of residual dependence in this case. In this paper we give a characterization of this phenomenon (see also Ramos and Ledford (2009)), and offer extensions to higher-dimensional spaces and stochastic processes. Systemic risk in the banking system is treated in a similar framework.
Publié le : 2011-03-15
Classification:  Asymptotic independence,  extreme residual dependence,  spectral measure,  62G20 
@article{1300198520,
     author = {De Haan, Laurens and Zhou, Chen},
     title = {Extreme residual dependence for random vectors and processes},
     journal = {Adv. in Appl. Probab.},
     volume = {43},
     number = {1},
     year = {2011},
     pages = { 217-242},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1300198520}
}

De Haan, Laurens; Zhou, Chen. Extreme residual dependence for random vectors and processes. Adv. in Appl. Probab., Tome 43 (2011) no. 1, pp.  217-242. http://gdmltest.u-ga.fr/item/1300198520/