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Tracking change-points in multivariate extremes

Author

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  • Miguel de Carvalho
  • Manuele Leonelli
  • Alex Rossi

Abstract

In this paper we devise a statistical method for tracking and modeling change-points on the dependence structure of multivariate extremes. The methods are motivated by and illustrated on a case study on crypto-assets.

Suggested Citation

  • Miguel de Carvalho & Manuele Leonelli & Alex Rossi, 2020. "Tracking change-points in multivariate extremes," Papers 2011.05067, arXiv.org.
    • Handle: RePEc:arx:papers:2011.05067
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    File URL: http://arxiv.org/pdf/2011.05067
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    References listed on IDEAS

    as
    1. Gkillas, Konstantinos & Katsiampa, Paraskevi, 2018. "An application of extreme value theory to cryptocurrencies," Economics Letters, Elsevier, vol. 164(C), pages 109-111.
    2. Mhalla, Linda & Chavez-Demoulin, Valérie & Naveau, Philippe, 2017. "Non-linear models for extremal dependence," Journal of Multivariate Analysis, Elsevier, vol. 159(C), pages 49-66.
    3. Hanson, Timothy E. & de Carvalho, Miguel & Chen, Yuhui, 2017. "Bernstein polynomial angular densities of multivariate extreme value distributions," Statistics & Probability Letters, Elsevier, vol. 128(C), pages 60-66.
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    Cited by:

    1. Yuri Goegebeur & Armelle Guillou & Jing Qin, 2023. "Robust estimation of the conditional stable tail dependence function," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(2), pages 201-231, April.

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