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The Tail Probability of Discounted Sums of Pareto-like Losses in Insurance

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  • Marc Goovaerts
  • Rob Kaas
  • Roger Laeven
  • Qihe Tang
  • Raluca Vernic

Abstract

In an insurance context, the discounted sum of losses within a finite or infinite time period can be described as a randomly weighted sum of a sequence of independent random variables. These independent random variables represent the amounts of losses in successive development years, while the weights represent the stochastic discount factors. In this paper, we investigate the problem of approximating the tail probability of this weighted sum in the case when the losses have Pareto-like distributions and the discount factors are mutually dependent. We also give some simulation results.

Suggested Citation

  • Marc Goovaerts & Rob Kaas & Roger Laeven & Qihe Tang & Raluca Vernic, 2005. "The Tail Probability of Discounted Sums of Pareto-like Losses in Insurance," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2005(6), pages 446-461.
    • Handle: RePEc:taf:sactxx:v:2005:y:2005:i:6:p:446-461
    DOI: 10.1080/03461230500361943
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    Cited by:

    1. Xinmei Shen & Kailin Du, 2023. "Uniform Approximation for the Tail Behavior of Bidimensional Randomly Weighted Sums," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-25, March.

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