基于学习和歧义规避的稳健再保险契约

IF 1.6 3区 经济学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Duni Hu, Hailong Wang
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引用次数: 3

摘要

研究了学习和歧义规避下的稳健再保险需求和价格。在再保险合同中,保险人是模糊中立的,并且相信他是完全知情的,而再保险人是贝叶斯学习者,并且意识到即使过滤模型是对数据生成过程的最佳描述,也可能无法正确预测未来的索赔。厌恶歧义的再保险人倾向于选择对模型错误规范具有鲁棒性的再保险合同。导出了稳健再保险需求和价格的封闭表达式。研究发现,再保险人的片面学习和歧义厌恶都会影响最优再保险需求和最优再保险价格的结构和水平。此外,如果厌恶模糊性的再保险人将次优再保险合同指定为模糊性中立的决策者,将导致显著的效用损失,且效用损失随厌恶模糊性水平和贝叶斯波动率的增加而增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust reinsurance contract with learning and ambiguity aversion
We investigate the robust reinsurance demand and price under learning and ambiguity aversion. In the reinsurance contract, the insurer is ambiguity neutral and believes that he is perfectly informed, and the reinsurer is a Bayesian learner and is aware that even the filtered model is the best description of the data-generating process, might not forecast the future claims correctly. The ambiguity-averse reinsurer has a preference for reinsurance contract which is robust to model misspecification. Closed-form expressions for the robust reinsurance demand and price are derived. We find that both the reinsurer's one-sided learning and ambiguity aversion influence the structures and levels of the optimal reinsurance demand and price. Moreover, if the ambiguity-averse reinsurer specifies the suboptimal reinsurance contract as an ambiguity-neutral decision-maker, it will result in significant utility loss and the utility loss increases with ambiguity aversion level and Bayesian volatility.
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来源期刊
Scandinavian Actuarial Journal
Scandinavian Actuarial Journal MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
3.30
自引率
11.10%
发文量
38
审稿时长
>12 weeks
期刊介绍: Scandinavian Actuarial Journal is a journal for actuarial sciences that deals, in theory and application, with mathematical methods for insurance and related matters. The bounds of actuarial mathematics are determined by the area of application rather than by uniformity of methods and techniques. Therefore, a paper of interest to Scandinavian Actuarial Journal may have its theoretical basis in probability theory, statistics, operations research, numerical analysis, computer science, demography, mathematical economics, or any other area of applied mathematics; the main criterion is that the paper should be of specific relevance to actuarial applications.
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