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Strong consistency of tail value-at-risk estimator and corresponding general results under widely orthant dependent samples

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Abstract

In this paper, strong consistency of tail value-at-risk (TVaR) estimator under widely orthant dependent (WOD) samples is established, and a numerical simulation is performed to verify the validity of the theoretical results. To reveal the essence of the result, theoretical discussion on complete and complete moment convergence corresponding to the Baum–Katz law, as well as the Marcinkiewicz–Zygmund type strong law of large numbers (MZSLLN) for maximal weighted sums and maximal product sums of widely orthant dependent (WOD) random variables are investigated. The results obtained in the context extend the corresponding ones for independent and some dependent random variables.

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  1. School of Mathematical Sciences, Soochow University, Suzhou, 215006, China

    Jinyu Zhou, Jigao Yan & Dongya Cheng

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  1. Jinyu Zhou
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Zhou, J., Yan, J. & Cheng, D. Strong consistency of tail value-at-risk estimator and corresponding general results under widely orthant dependent samples. Stat Papers (2024). https://doi.org/10.1007/s00362-023-01525-x

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