PATHS AND INDICES OF MAXIMAL TAIL DEPENDENCE

@article{Furman2014PATHSAI,
  title={PATHS AND INDICES OF MAXIMAL TAIL DEPENDENCE},
  author={Edward Furman and Jianxi Su and Ri{\vc}ardas Zitikis},
  journal={ASTIN Bulletin},
  year={2014},
  volume={45},
  pages={661 - 678}
}
Abstract We demonstrate both analytically and numerically that the existing methods for measuring tail dependence in copulas may sometimes underestimate the extent of extreme co-movements of dependent risks and, therefore, may not always comply with the new paradigm of prudent risk management. This phenomenon holds in the context of both symmetric and asymmetric copulas with and without singularities. As a remedy, we introduce a notion of paths of maximal (tail) dependence and utilize the… 
View on Cambridge Press
arxiv.org
18 Citations
Highly Influential Citations
2
Background Citations
13
Methods Citations
7

18 Citations

Assessing bivariate tail non-exchangeable dependence

Tail Dependence of the Gaussian Copula Revisited

It is proved that the classical measures of tail dependence in copulas are maximal, and, in spite of the numerous criticisms, the Gaussian copula remains ubiquitous in a great variety of practical applications.

Global and Tail Dependence: A Differential Geometry Approach

Measures of tail dependence between random variables aim to numerically quantify the degree of association between their extreme realizations. Existing tail dependence coefficients (TDCs) are based…

Tail Maximal Dependence in Bivariate Models: Estimation and Applications

Assessing dependence within co-movements of financial instruments has been of much interest in risk management. Typically, indices of tail dependence are used to quantify the strength of such…

Measuring non-exchangeable tail dependence using tail copulas

Abstract Quantifying tail dependence is an important issue in insurance and risk management. The prevalent tail dependence coefficient (TDC), however, is known to underestimate the degree of tail…

Multiple Risk Factor Dependence Structures: Copulas and Related Properties

This paper introduces and study a new class of Multiple Risk Factor (MRF) copula functions, which it is shown are exactly such, and turns out to be surprisingly tractable analytically.

A Statistical Methodology for Assessing the Maximal Strength of Tail Dependence

Several diagonal-based tail dependence indices have been suggested in the literature to quantify tail dependence. They have well-developed statistical inference theories but tend to underestimate…

Assessing Maximal Dependence Within Extreme Co-Movements of Financial Instruments

Assessing dependence within extreme co-movements of financial instruments has been of much interest in risk management. Typically, indices of tail dependence are used to quantify the strength of such…

A new class of tail dependence measures and their maximization

A new class of measures of bivariate tail dependence is proposed, which is defined as a limit of a measure of concordance of the underlying copula restricted to the tail region of interest. The…

Shock models with dependence and asymmetric linkages

46 References

Intermediate Tail Dependence: A Review and Some New Results

The concept of intermediate tail dependence is useful if one wants to quantify the degree of positive dependence in the tails when there is no strong evidence of presence of the usual tail…

Copulas, diagonals, and tail dependence

Characterization of Multivariate Heavy-Tailed Distribution Families via Copula

This paper characterizes the MRV distributions through the tail dependence function of the copula associated with them, indicating that the existence of the lower tail dependencefunction of the survival copula is necessary and sufficient for a random vector with regularly varying univariate marginals to have a MRV tail.

Chapter 8 – Modelling Dependence with Copulas and Applications to Risk Management

Extremal dependence of copulas: A tail density approach

A new class of models for bivariate joint tails

Summary.  A fundamental issue in applied multivariate extreme value analysis is modelling dependence within joint tail regions. The primary focus of this work is to extend the classical pseudopolar…

A Directory of Coefficients of Tail Dependence

Models characterizing the asymptotic dependence structures of bivariate distributions have been introduced by Ledford and Tawn (1996), among others, and diagnostics for such dependence behavior are…

Asymptotics for Risk Capital Allocations Based on Conditional Tail Expectation

Some results on weak and strong tail dependence coefficients for means of copulas

It is shown that every weighted geometric mean of extreme-value copulas produces again an extreme- Value copula, and the second contribution of this paper is to calculate extremal dependence measures for (weighted) geometric and arithmetic means of two copulas.

Model Uncertainty and VaR Aggregation