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arXiv 2107.01730q-fin.RMmath.PR
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风险测度诱导的风险溢价的渐近分析

Asymptotic Analysis of Risk Premia Under Linear Risk Sharing with Law-Invariant Risk Measures

Berlin School of Economics and Law(柏林经济法律学院);Leibniz University Hannover(汉诺威莱布尼茨大学)

Thomas Knispel, Roger J. A. Laeven, Gregor Svindland

AI总结:

研究无限扩展的风险池中帕累托最优风险分担合同的风险溢价极限行为,揭示收敛速度通常为n^{1/2}而非常规n,取决于具体风险偏好。

摘要:

我们分析了在无限扩展的风险池中,由一般类别的法不变风险测度所涵盖的秩依赖效用偏好所诱导的风险溢价的极限行为。我们证明对应的收敛速度通常仅为n^{1/2}而非常规的n,其中n是风险池中风险的乘数,取决于具体的风险偏好。

英文摘要:

We investigate the asymptotic behavior of the risk premium associated with a linear risk sharing contract in an infinitely expanding risk pool. We consider general preferences represented by law-invariant robust utility functionals. These preferences encompass the rank-dependent utility model as a special case. We also examine Pareto optimality of general and, in particular, linear risk sharing rules with these preferences. Our analysis is not limited to the classical i.i.d. setting, but allows for heterogeneous risks. Two case studies on actuarial pricing for independent but heterogeneous risks illustrate our results.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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