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Lower bounds of large deviation for sums of long-tailed claims in a multi-risk model

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  • Lu, Dawei

Abstract

In view of the actual condition of the insurance company, a multi-risk model is proposed. The lower bound for the sums of long-tailed claims in this model is given. The proof method is based on the results of precise large deviation for long-tailed distributions.

Suggested Citation

  • Lu, Dawei, 2012. "Lower bounds of large deviation for sums of long-tailed claims in a multi-risk model," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1242-1250.
    • Handle: RePEc:eee:stapro:v:82:y:2012:i:7:p:1242-1250
    DOI: 10.1016/j.spl.2012.03.020
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    References listed on IDEAS

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    1. Tang, Qihe & Su, Chun & Jiang, Tao & Zhang, Jinsong, 2001. "Large deviations for heavy-tailed random sums in compound renewal model," Statistics & Probability Letters, Elsevier, vol. 52(1), pages 91-100, March.
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    Cited by:

    1. Chen, Zhangting & Cheng, Dongya, 2024. "Precise large deviations for non-centralized sums of partial sums and random sums of heavy-tailed END random variables," Statistics & Probability Letters, Elsevier, vol. 211(C).
    2. He, Wei & Cheng, Dongya & Wang, Yuebao, 2013. "Asymptotic lower bounds of precise large deviations with nonnegative and dependent random variables," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 331-338.
    3. Dimitrios G. Konstantinides, 2018. "Precise Large Deviations for Subexponential Distributions in a Multi Risk Model," Risks, MDPI, vol. 6(2), pages 1-13, March.
    4. Fu, Ke-Ang & Liu, Yang & Wang, Jiangfeng, 2022. "Precise large deviations in a bidimensional risk model with arbitrary dependence between claim-size vectors and waiting times," Statistics & Probability Letters, Elsevier, vol. 184(C).

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