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H-extendible copulas

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  • Mai, Jan-Frederik
  • Scherer, Matthias

Abstract

We survey recent developments on hierarchical copula models and focus on those arising as factor models. We unify the literature by introducing the notion of h-extendibility, a notion that generalizes dimension-extendible models to hierarchical structures. Special attention is devoted to h-extendible Archimedean and h-extendible Marshall–Olkin copulas.

Suggested Citation

  • Mai, Jan-Frederik & Scherer, Matthias, 2012. "H-extendible copulas," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 151-160.
    • Handle: RePEc:eee:jmvana:v:110:y:2012:i:c:p:151-160
    DOI: 10.1016/j.jmva.2012.03.011
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    References listed on IDEAS

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    1. Capéraà, Philippe & Fougères, Anne-Laure & Genest, Christian, 2000. "Bivariate Distributions with Given Extreme Value Attractor," Journal of Multivariate Analysis, Elsevier, vol. 72(1), pages 30-49, January.
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    7. German Bernhart & Marcos Escobar Anel & Jan-Frederik Mai & Matthias Scherer, 2013. "Default models based on scale mixtures of Marshall-Olkin copulas: properties and applications," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(2), pages 179-203, February.
    8. Joe, Harry & Hu, Taizhong, 1996. "Multivariate Distributions from Mixtures of Max-Infinitely Divisible Distributions," Journal of Multivariate Analysis, Elsevier, vol. 57(2), pages 240-265, May.
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    Citations

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    Cited by:

    1. Romdhani, H. & Lakhal-Chaieb, L. & Rivest, L.-P., 2014. "Kendall’s tau for hierarchical data," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 210-225.
    2. David Blake & Marco Morales & Enrico Biffis & Yijia Lin & Andreas Milidonis, 2017. "Special Edition: Longevity 10 – The Tenth International Longevity Risk and Capital Markets Solutions Conference," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(S1), pages 515-532, April.
    3. Perreault, Samuel & Duchesne, Thierry & Nešlehová, Johanna G., 2019. "Detection of block-exchangeable structure in large-scale correlation matrices," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 400-422.
    4. Zhu, Wenjun & Wang, Chou-Wen & Tan, Ken Seng, 2016. "Structure and estimation of Lévy subordinated hierarchical Archimedean copulas (LSHAC): Theory and empirical tests," Journal of Banking & Finance, Elsevier, vol. 69(C), pages 20-36.
    5. Ressel Paul, 2019. "Copulas, stable tail dependence functions, and multivariate monotonicity," Dependence Modeling, De Gruyter, vol. 7(1), pages 247-258, January.
    6. Mai Jan-Frederik & Scherer Matthias, 2013. "What makes dependence modeling challenging? Pitfalls and ways to circumvent them," Statistics & Risk Modeling, De Gruyter, vol. 30(4), pages 287-306, December.
    7. Damjana Kokol Bukovv{s}ek & Tomav{z} Kov{s}ir & Blav{z} Mojv{s}kerc & Matjav{z} Omladiv{c}, 2018. "Non-exchangeability of copulas arising from shock models," Papers 1808.09698, arXiv.org, revised Jul 2019.
    8. Brigo, Damiano & Mai, Jan-Frederik & Scherer, Matthias, 2016. "Markov multi-variate survival indicators for default simulation as a new characterization of the Marshall–Olkin law," Statistics & Probability Letters, Elsevier, vol. 114(C), pages 60-66.
    9. Martin Magris, 2019. "A Vine-copula extension for the HAR model," Papers 1907.08522, arXiv.org.

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