Behaviour of multivariate tail dependence coefficients

Authors

  • Gaida Pettere Department of Innovation and Business Management, Riga Technical University, Riga LV1048, Latvia
  • Irina Voronova Department of Innovation and Business Management, Riga Technical University, Riga LV1048, Latvia
  • Ilze Zariņa Department of Innovation and Business Management, Riga Technical University, Riga LV1048, Latvia

DOI:

https://doi.org/10.12697/ACUTM.2018.22.25

Keywords:

bivariate tail dependence, copula, multivariate tail dependence, t-copula, t-distribution

Abstract

In applications tail dependence is an important property of a copula. Bivariate tail dependence is investigated in many papers, but multivariate tail dependence has not been studied widely. We define multivariate upper and lower tail dependence coefficients as limits of the probability that values of one marginal will be large if at least one of other marginals will be as large also. Further we derive some relations between introduced tail dependence and bivariate tail dependence coefficients. Applications have shown that the multivariate t-copula has been successfully used in practice because of its tail dependence property. Therefore, t-copula can be used as an alternative method for risk assessment under Solvency II for insurance models. We have paid attention to the properties of the introduced multivariate tail dependence coefficient for t-copula and examine it in the simulation experiment.

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Published

2019-01-02

Issue

Section

Articles