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Multidimensional extremal dependence coefficients

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  • Ferreira, Helena
  • Ferreira, Marta

Abstract

Extreme value modeling has been attracting the attention of researchers in diverse areas such as the environment, engineering, and finance. Multivariate extreme value distributions are particularly suitable to model the tails of multidimensional phenomena. The analysis of the dependence among multivariate maxima is useful to evaluate risk. Here we present new multivariate extreme value models, as well as, coefficients to assess multivariate extremal dependence.

Suggested Citation

  • Ferreira, Helena & Ferreira, Marta, 2018. "Multidimensional extremal dependence coefficients," Statistics & Probability Letters, Elsevier, vol. 133(C), pages 1-8.
    • Handle: RePEc:eee:stapro:v:133:y:2018:i:c:p:1-8
    DOI: 10.1016/j.spl.2017.09.018
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    References listed on IDEAS

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    1. Philippe Naveau & Armelle Guillou & Daniel Cooley & Jean Diebolt, 2009. "Modelling pairwise dependence of maxima in space," Biometrika, Biometrika Trust, vol. 96(1), pages 1-17.
    2. Marcon, Giulia & Padoan, Simone & Naveau, Philippe & Muliere, Pietro & Segers, Johan, 2016. "Multivariate Nonparametric Estimation of the Pickands Dependence Function using Bernstein Polynomials," LIDAM Discussion Papers ISBA 2016020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Jennifer L. Wadsworth & Jonathan A. Tawn, 2012. "Dependence modelling for spatial extremes," Biometrika, Biometrika Trust, vol. 99(2), pages 253-272.
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    Cited by:

    1. Helena Ferreira & Marta Ferreira, 2021. "Tail dependence and smoothness of time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 198-210, March.

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