当保费由凸泛函计算时最大化指数效用的最优保险
Optimal Insurance to Maximize Exponential Utility when Premium is Computed by a Convex Functional
AI总结：
本文研究保费由凸泛函计算时指数效用偏好下的最优保险赔付问题，推导出必要条件并设计数值算法，证明其收敛到唯一最优保单。
摘要：
我们寻找最优赔付，以最大化保险购买者终端财富的期望效用，其偏好由指数效用建模。保费由一个凸泛函计算。我们得到了最优赔付的必要条件；然后，由于候选最优赔付是隐式给出的，我们利用该必要条件开发了一种数值算法来计算它。我们证明了该数值算法收敛于一个唯一的赔付，该赔付确实等于最优保单。我们还用数值例子说明了我们的结果。
英文摘要：
We find the optimal indemnity to maximize the expected utility of terminal wealth of a buyer of insurance whose preferences are modeled by an exponential utility. The insurance premium is computed by a convex functional. We obtain a necessary condition for the optimal indemnity; then, because the candidate optimal indemnity is given implicitly, we use that necessary condition to develop a numerical algorithm to compute it. We prove that the numerical algorithm converges to a unique indemnity that, indeed, equals the optimal policy. We also illustrate our results with numerical examples.
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。
