A Statistical Methodology for Assessing the Maximal Strength of Tail Dependence

29 Pages Posted: 23 Mar 2020 Last revised: 20 Mar 2023

See all articles by Ning Sun

Ning Sun

Agri-Food Analytics Lab; Dalhousie University

Chen Yang

Wuhan University

Ricardas Zitikis

Western University

Date Written: February 27, 2020

Abstract

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 tail dependence. For those problems when assessing the maximal strength of dependence is important (e.g., co-movements of financial instruments), the maximal tail dependence index was introduced, but it has so far lacked empirical estimators and statistical inference results, thus hindering its practical use. In the present paper we suggest an empirical estimator for the index, explore its statistical properties, and illustrate its performance on simulated data.

Keywords: copula, maximal tail dependence, statistical estimation, Kendall's distribution

JEL Classification: C02, C13, C14, C18

Suggested Citation

Sun, Ning and Yang, Chen and Zitikis, Ricardas, A Statistical Methodology for Assessing the Maximal Strength of Tail Dependence (February 27, 2020). Available at SSRN: https://ssrn.com/abstract=3545598 or http://dx.doi.org/10.2139/ssrn.3545598

Ning Sun

Agri-Food Analytics Lab ( email )

6100 University Avenue
Halifax, Nova Scotial
Halifax
Canada

Dalhousie University ( email )

6100 University Avenue
Halifax, Nova Scotia
Canada

Chen Yang

Wuhan University ( email )

Wuhan
China

Ricardas Zitikis (Contact Author)

Western University ( email )

1151 Richmond Street
Suite 2
London, Ontario N6A 5B8
Canada

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