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Modeling claims data with composite Stoppa models

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  • Enrique Calderín-Ojeda
  • Chun Fung Kwok

Abstract

In this paper, a new class of composite model is proposed for modeling actuarial claims data of mixed sizes. The model is developed using the Stoppa distribution and a mode-matching procedure. The use of the Stoppa distribution allows for more flexibility over the thickness of the tail, and the mode-matching procedure gives a simple derivation of the model compositing with a variety of distributions. In particular, the Weibull–Stoppa and the Lognormal–Stoppa distributions are investigated. Their performance is compared with existing composite models in the context of the well-known Danish fire insurance data-set. The results suggest the composite Weibull–Stoppa model outperforms the existing composite models in all seven goodness-of-fit measures considered.

Suggested Citation

  • Enrique Calderín-Ojeda & Chun Fung Kwok, 2016. "Modeling claims data with composite Stoppa models," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2016(9), pages 817-836, October.
    • Handle: RePEc:taf:sactxx:v:2016:y:2016:i:9:p:817-836
    DOI: 10.1080/03461238.2015.1034763
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    Cited by:

    1. Bae, Taehan & Miljkovic, Tatjana, 2024. "Loss modeling with the size-biased lognormal mixture and the entropy regularized EM algorithm," Insurance: Mathematics and Economics, Elsevier, vol. 117(C), pages 182-195.
    2. Johan René van Dorp & Ekundayo Shittu, 2024. "Two-sided distributions with applications in insurance loss modeling," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(3), pages 827-861, July.
    3. Li, Zhengxiao & Wang, Fei & Zhao, Zhengtang, 2024. "A new class of composite GBII regression models with varying threshold for modeling heavy-tailed data," Insurance: Mathematics and Economics, Elsevier, vol. 117(C), pages 45-66.

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