Modelling the VaR Using Integral Probability and Tail Dependence

Authors

  • Wengoundi Benjamin Nikiéma Department of Applied Mathematics, Joseph Kizebo University, BP 7021 Ouagadougou 03, Burkina Faso
  • Barro Diakarya Training and Research Units of the Faculty of Economics and Management, Thomas Sankara University, BP 417 Ouagadougou 12, Burkina Faso https://orcid.org/0000-0003-3311-3645 (unauthenticated)

DOI:

https://doi.org/10.37256/cm.5320242842

Keywords:

copulas, stochastic finance, risk measures, extreme values theory, tail dependence, probability integral transformation (PIT)

Abstract

In this paper, a method is proposed to estimate value at risk (VaR) in a multivariate context by employing the probability integral transformation (PIT) and tail dependence function to model extreme dependence structure. The proposed method involves two vectorial measures of VaR, which use either the distribution function or the survival function. Moreover, properties of these risk measures are analysed, and a connection between them and tail dependence functions is established.

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Published

2024-08-13

Issue

Contemporary Mathematics, Volume 5 Issue 3 (2024), 2593-4131

Section

Research Article

License

Copyright (c) 2024 Diakarya Barro, et al.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

1.
Modelling the VaR Using Integral Probability and Tail Dependence. Contemp. Math. [Internet]. 2024 Aug. 13 [cited 2025 Dec. 24];5(3):3184-97. Available from: https://ojs353.mebyme.cn/index.php/CM/article/view/2842