IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v66y2025i2d10.1007_s00362-025-01663-4.html
   My bibliography  Save this article

The limiting distribution of a bivariate random vector under univariate truncation

Author

Listed:
  • F. Durante

    (Università del Salento)

  • C. Ignazzi

    (Università del Salento)

  • P. Jaworski

    (University of Warsaw)

Abstract

The dependence structure in the tails of bivariate random vectors is studied by means of the copula representation. In particular, asymptotic results for the distribution of a random pair under univariate truncation is proved in the spirit of multivariate extensions of the Pickands-Balkema-de Haan Theorem.

Suggested Citation

  • F. Durante & C. Ignazzi & P. Jaworski, 2025. "The limiting distribution of a bivariate random vector under univariate truncation," Statistical Papers, Springer, vol. 66(2), pages 1-28, February.
    • Handle: RePEc:spr:stpapr:v:66:y:2025:i:2:d:10.1007_s00362-025-01663-4
    DOI: 10.1007/s00362-025-01663-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00362-025-01663-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00362-025-01663-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Charpentier, Arthur & Segers, Johan, 2009. "Tails of multivariate Archimedean copulas," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1521-1537, August.
    2. Bernard, Carole & Czado, Claudia, 2015. "Conditional quantiles and tail dependence," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 104-126.
    3. Bernardi, M. & Durante, F. & Jaworski, P., 2017. "CoVaR of families of copulas," Statistics & Probability Letters, Elsevier, vol. 120(C), pages 8-17.
    4. Siburg, Karl Friedrich & Strothmann, Christopher & Weiß, Gregor, 2024. "Comparing and quantifying tail dependence," Insurance: Mathematics and Economics, Elsevier, vol. 118(C), pages 95-103.
    5. Hofert, Marius, 2021. "Right-truncated Archimedean and related copulas," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 79-91.
    6. Hua, Lei & Joe, Harry, 2011. "Tail order and intermediate tail dependence of multivariate copulas," Journal of Multivariate Analysis, Elsevier, vol. 102(10), pages 1454-1471, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jaworski Piotr, 2017. "On Conditional Value at Risk (CoVaR) for tail-dependent copulas," Dependence Modeling, De Gruyter, vol. 5(1), pages 1-19, January.
    2. Kurowicka, Dorota & van Horssen, Wim T., 2015. "On an interaction function for copulas," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 127-142.
    3. Hua, Lei, 2015. "Tail negative dependence and its applications for aggregate loss modeling," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 135-145.
    4. Li, Haijun & Wu, Peiling, 2013. "Extremal dependence of copulas: A tail density approach," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 99-111.
    5. Hua, Lei, 2017. "On a bivariate copula with both upper and lower full-range tail dependence," Insurance: Mathematics and Economics, Elsevier, vol. 73(C), pages 94-104.
    6. Paramahansa Pramanik, 2024. "Dependence on Tail Copula," J, MDPI, vol. 7(2), pages 1-26, April.
    7. Das Bikramjit & Fasen-Hartmann Vicky, 2019. "Conditional excess risk measures and multivariate regular variation," Statistics & Risk Modeling, De Gruyter, vol. 36(1-4), pages 1-23, December.
    8. Harry Joe, 2018. "Dependence Properties of Conditional Distributions of some Copula Models," Methodology and Computing in Applied Probability, Springer, vol. 20(3), pages 975-1001, September.
    9. Hua, Lei & Polansky, Alan & Pramanik, Paramahansa, 2019. "Assessing bivariate tail non-exchangeable dependence," Statistics & Probability Letters, Elsevier, vol. 155(C), pages 1-1.
    10. Su, Jianxi & Hua, Lei, 2017. "A general approach to full-range tail dependence copulas," Insurance: Mathematics and Economics, Elsevier, vol. 77(C), pages 49-64.
    11. Bikramjit Das & Vicky Fasen-Hartmann, 2023. "Aggregating heavy-tailed random vectors: from finite sums to L\'evy processes," Papers 2301.10423, arXiv.org.
    12. Hua, Lei & Joe, Harry, 2011. "Second order regular variation and conditional tail expectation of multiple risks," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 537-546.
    13. Elena Di Bernardino & Didier Rullière, 2016. "On tail dependence coefficients of transformed multivariate Archimedean copulas," Post-Print hal-00992707, HAL.
    14. Roger M. Cooke & Harry Joe & Bo Chang, 2020. "Vine copula regression for observational studies," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(2), pages 141-167, June.
    15. Olukunle O. Owolabi & Kathryn Lawson & Sanhita Sengupta & Yingsi Huang & Lan Wang & Chaopeng Shen & Mila Getmansky Sherman & Deborah A. Sunter, 2022. "A Robust Statistical Analysis of the Role of Hydropower on the System Electricity Price and Price Volatility," Papers 2203.02089, arXiv.org.
    16. Xia Li, 2024. "Unveiling Portfolio Resilience: Harnessing Asymmetric Copulas for Dynamic Risk Assessment in the Knowledge Economy," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 10200-10226, September.
    17. Chen, Yiqing, 2025. "The heavy-tail behavior of the difference of two dependent random variables," Statistics & Probability Letters, Elsevier, vol. 218(C).
    18. Wu, Shaomin, 2014. "Construction of asymmetric copulas and its application in two-dimensional reliability modelling," European Journal of Operational Research, Elsevier, vol. 238(2), pages 476-485.
    19. Hengxin Cui & Ken Seng Tan & Fan Yang, 2024. "Portfolio credit risk with Archimedean copulas: asymptotic analysis and efficient simulation," Annals of Operations Research, Springer, vol. 332(1), pages 55-84, January.
    20. César Garcia-Gomez & Ana Pérez & Mercedes Prieto-Alaiz, 2022. "The evolution of poverty in the EU-28: a further look based on multivariate tail dependence," Working Papers 605, ECINEQ, Society for the Study of Economic Inequality.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:stpapr:v:66:y:2025:i:2:d:10.1007_s00362-025-01663-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.