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Tweedie multivariate semi-parametric credibility with the exchangeable correlation

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  • Jeong, Himchan

Abstract

This article proposes a framework for determining credibility premiums for multiple coverages in a compound risk model with Tweedie distribution. The framework builds upon previous results on credibility premium and provides an explicit multivariate credibility premium formula that is applicable to the Tweedie family assuming that the unobserved heterogeneity for the multiple coverage have the common correlation. The practical applicability of the proposed framework is evaluated through simulation and empirical analysis using the LGPIF dataset, which includes claims and policy characteristics data for various types of coverages observed over time. The findings suggest that the proposed framework can be useful in ratemaking practice by incorporating a non-trivial dependence structure among the multiple types of claims.

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  • Jeong, Himchan, 2024. "Tweedie multivariate semi-parametric credibility with the exchangeable correlation," Insurance: Mathematics and Economics, Elsevier, vol. 115(C), pages 13-21.
    • Handle: RePEc:eee:insuma:v:115:y:2024:i:c:p:13-21
    DOI: 10.1016/j.insmatheco.2023.12.007
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    1. Tianxing Yan & Yi Lu & Himchan Jeong, 2024. "Dependence Modelling for Heavy-Tailed Multi-Peril Insurance Losses," Risks, MDPI, vol. 12(6), pages 1-17, June.
    2. Dong, Panyi & Quan, Zhiyu, 2025. "Automated machine learning in insurance," Insurance: Mathematics and Economics, Elsevier, vol. 120(C), pages 17-41.

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