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Assessing the coverage probabilities of fixed-margin confidence intervals for the tail conditional allocation

Author

Listed:
  • N. V. Gribkova

    (Saint Petersburg State University
    Emperor Alexander I St. Petersburg State Transport University)

  • J. Su

    (Purdue University)

  • R. Zitikis

    (Western University)

Abstract

The tail conditional allocation plays an important role in a number of areas, including economics, finance, insurance, and management. Fixed-margin confidence intervals and the assessment of their coverage probabilities are of much interest. In this paper, we offer a convenient way to achieve these goals via resampling. The theoretical part of the paper, which is technically demanding, is rigorously established under minimal conditions to facilitate the widest practical use. A simulation-based study and an analysis of real data illustrate the performance of the developed methodology.

Suggested Citation

  • N. V. Gribkova & J. Su & R. Zitikis, 2024. "Assessing the coverage probabilities of fixed-margin confidence intervals for the tail conditional allocation," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(5), pages 821-850, October.
    • Handle: RePEc:spr:aistmt:v:76:y:2024:i:5:d:10.1007_s10463-024-00904-x
    DOI: 10.1007/s10463-024-00904-x
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    References listed on IDEAS

    as
    1. Gribkova, N.V. & Su, J. & Zitikis, R., 2022. "Inference for the tail conditional allocation: Large sample properties, insurance risk assessment, and compound sums of concomitants," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 199-222.
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    Full references (including those not matched with items on IDEAS)

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