@article { ISI:000313478200008,
	title = {Tail comonotonicity and conservative risk measures},
	journal = {ASTIN Bulletin},
	volume = {42},
	number = {2},
	year = {2012},
	month = {NOV},
	pages = {601-629},
	publisher = {Peeters},
	type = {Article},
	abstract = {Tail comonotonicity, or asymptotic full dependence, is proposed as a reasonable conservative dependence structure for modeling dependent risks. Some sufficient conditions have been obtained to justify the conservativity of tail comonotonicity. Simulation studies also suggest that, by using tail comonotonicity, one does not lose too much accuracy but gain reasonable conservative risk measures, especially when considering high scenario risks. A copula model with tail comonotonicity is applied to an auto insurance dataset. Particular models for tail comonotonicity for loss data can be based on the BB2 and BB3 copula families and their multivariate extensions.},
	keywords = {Archimedean copula, asymptotic full dependence, conditional tail expectation, Copula, Dependence modeling, Laplace transform, regular variation},
	issn = {0515-0361},
	doi = {10.2143/AST42.2.2182810},
	author = {Hua, Lei and Joe, Harry}
}
@article { ISI:000309028900029,
	title = {Tail comonotonicity: Properties, constructions, and asymptotic additivity of risk measures},
	journal = {Insurance Mathematics \& Economics},
	volume = {51},
	number = {2},
	year = {2012},
	month = {SEP},
	pages = {492-503},
	publisher = {Elsevier Science BV},
	type = {Article},
	abstract = {We investigate properties of a version of tail comonotonicity that can be applied to absolutely continuous distributions, and give several methods for constructions of multivariate distributions with tail comonotonicity or strongest tail dependence. Archimedean copulas as mixtures of powers, and scale mixtures of a non-negative random vector with the mixing distribution having slowly varying tails, lead to a tail comonotonic dependence structure. For random variables that are in the maximum domain of attraction of either Frechet or Gumbel, we prove the asymptotic additivity property of Value at Risk and Conditional Tail Expectation. (C) 2012 Elsevier B.V. All rights reserved.},
	keywords = {Archimedean copula, asymptotic full dependence, Copula, Elliptical distributions, Extreme value distributions, Regularly varying, Slowly varying},
	issn = {0167-6687},
	doi = {10.1016/j.insmatheco.2012.07.006},
	author = {Hua, Lei and Joe, Harry}
}
