贝叶斯保险基础

Liang Hong, Ryan Martin, Zhiqiang Yan
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引用次数: 0

摘要

精算学、保险和风险管理方面的专家都很好地理解了频率论框架下保险的基础。在过去的二十年中,贝叶斯分析在保险领域的应用激增。然而,保险在贝叶斯框架下的基础仍未被探索。本文通过研究保险在贝叶斯模型中的基础来填补这一空白。我们证明了在贝叶斯世界中保险的基础对应于在真参数值处后验分布的一致性。我们讨论了后验一致性的几个关键结果,并给出了参数和非参数情况下的保险实例来说明它们的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bayesian Foundations of Insurance
The foundation of insurance in the frequentist framework is well-understood by experts in actuarial science, insurance and risk management. In the past two decades there has been a surge in the application of Bayesian analysis in insurance. However, the foundation of insurance under the Bayesian framework remains unexplored. This paper fills the gap by investigating the foundation of insurance in the Bayesian setup. We demonstrate that the foundation of insurance in the Bayesian world corresponds to the consistency of the posterior distribution at the true parameter value. We discuss several key results of posterior consistency and give insurance examples in both parametric and nonparametric cases to illustrate their applications.
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