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Extremes for multivariate expectiles

Author

Listed:
  • Maume-Deschamps Véronique

    (Institut Camille Jordan UMR 5208, Université de Lyon, Université Lyon 1, Lyon, France)

  • Rullière Didier

    (Laboratoire SAF EA 2429, Université de Lyon, Université Lyon 1, Lyon, France)

  • Said Khalil

    (École d’Actuariat, Université Laval, Québec, Canada)

Abstract

Multivariate expectiles, a new family of vector-valued risk measures, were recently introduced in the literature. [22]. Here we investigate the asymptotic behavior of these measures in a multivariate regular variation context. For models with equivalent tails, we propose an estimator of extreme multivariate expectiles in the Fréchet domain of attraction case with asymptotic independence, or for comonotonic marginal distributions.

Suggested Citation

  • Maume-Deschamps Véronique & Rullière Didier & Said Khalil, 2018. "Extremes for multivariate expectiles," Statistics & Risk Modeling, De Gruyter, vol. 35(3-4), pages 111-140, July.
    • Handle: RePEc:bpj:strimo:v:35:y:2018:i:3-4:p:111-140:n:2
    DOI: 10.1515/strm-2017-0014
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    5. Maume-Deschamps Véronique & Rullière Didier & Said Khalil, 2017. "Multivariate extensions of expectiles risk measures," Dependence Modeling, De Gruyter, vol. 5(1), pages 20-44, January.
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    9. Klaus Herrmann & Marius Hofert & Melina Mailhot, 2017. "Multivariate Geometric Expectiles," Papers 1704.01503, arXiv.org, revised Jan 2018.
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    Cited by:

    1. Beck, Nicholas & Di Bernardino, Elena & Mailhot, Mélina, 2021. "Semi-parametric estimation of multivariate extreme expectiles," Journal of Multivariate Analysis, Elsevier, vol. 184(C).
    2. Said Khalil, 2022. "Expectile-based capital allocation," Working Papers hal-03816525, HAL.

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