کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5076098 1477198 2017 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A general approach to full-range tail dependence copulas
ترجمه فارسی عنوان
یک رویکرد کلی به مخلوط وابستگی کامل به دامنه
کلمات کلیدی
مخلوط مقیاس؛ به طور مرتب متغیر. توزیع پارتو؛ سرعت محاسبات سریع؛ وابستگی مجانبی؛ استقلال مجانبی
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آمار و احتمال
چکیده انگلیسی

Full-range tail dependence copulas have recently been proved very useful for modeling various dependence patterns in the joint distributional tails. However, there are only a few applicable candidate models that have the full-range tail dependence property. In this paper, we present a general approach to constructing bivariate copulas that have full-range tail dependence in both upper and lower tails and are able to account for both reflection symmetry and reflection asymmetry. The general approach is based on mixtures of positive regularly varying random variables, and the full-range tail dependence property is established for such a general model. In order to construct copulas that possess the above dependence properties and are fast to compute, we construct a full-range tail dependence copula based on mixtures of Pareto random variables. We derive dependence properties of the proposed copula, and the extreme value copula based on it. A comparison with the full-range tail dependence copula proposed in Hua (2017) has been conducted, and the computational speed has been largely improved by the copula proposed in the current paper.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Insurance: Mathematics and Economics - Volume 77, November 2017, Pages 49-64
نویسندگان
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