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Risk models based on copulas for premiums and claim sizes

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  • Yao Kang
  • Dehui Wang
  • Jianhua Cheng

Abstract

In this article, we generalize the individual risk model by introducing a dependence relationship between premiums and claim sizes. The dependence structure is described by bivariate distribution and copulas. Some statistical properties of the models are obtained. The loss probability, value at risk (VaR) and tail value at risk (TVaR) are applied to quantify the risk of the models. To this end, we use net loss (claim sizes minus premiums) instead of claim sizes to calculate the risk measures. Some numerical examples are given to illustrate the results. The normal approximation method is used to simplify the risk measures for the models.

Suggested Citation

  • Yao Kang & Dehui Wang & Jianhua Cheng, 2021. "Risk models based on copulas for premiums and claim sizes," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(10), pages 2250-2269, May.
    • Handle: RePEc:taf:lstaxx:v:50:y:2021:i:10:p:2250-2269
    DOI: 10.1080/03610926.2019.1662443
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