A general approach to full-range tail dependence copulas

DOI10.1016/j.insmatheco.2017.08.009zbMath1404.62059OpenAlexW2751745463MaRDI QIDQ1681085

Jianxi Su, Lei Hua

Publication date: 23 November 2017

Published in: Insurance Mathematics \& Economics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.insmatheco.2017.08.009

zbMATH Keywords

asymptotic independencePareto distributionscale mixturesasymptotic dependenceregularly varyingfast computational speed

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Statistics of extreme values; tail inference (62G32)

Related Items (6)

An asymptotic study of systemic expected shortfall and marginal expected shortfall ⋮ Multiplicative background risk models: setting a course for the idiosyncratic risk factors distributed phase-type ⋮ Multivariate matrix-exponential affine mixtures and their applications in risk theory ⋮ Portfolio risk analysis of excess of loss reinsurance ⋮ Dependence in a background risk model ⋮ Modeling spatial tail dependence with Cauchy convolution processes

Uses Software

• CDVine
• QRM

Cites Work

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