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首页> 外文期刊>Journal of Computational and Applied Mathematics >Stochastic differential reinsurance games in diffusion approximation models
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Stochastic differential reinsurance games in diffusion approximation models

机译:随机差分再保险游戏在扩散近似模型中

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摘要

In this paper, we study some noncooperative and cooperative stochastic differential games between two insurers with reinsurance controls. The surplus processes are modeled by diffusion approximation processes and the insurers can purchase reinsurance dynamically (i.e. control the drift and diffusion terms continuously over time). We consider two types of reinsurance: quota-share (QS) reinsurance and excess-of-loss (XL) reinsurance. In the noncooperative game, one insurer tries to minimize the probability that the surplus difference of the two insurers reaches a low target before it hits a high target, while the other aims to maximize the probability. We consider two cases of the game: in the first case, both insurers purchase XL reinsurance; and in the second case, one insurer purchases QS reinsurance while the other purchases XL reinsurance. In some parameter cases, we solve the game by finding the value function and Nash equilibrium strategy explicitly. In some parameter cases, the value function and Nash equilibrium strategy do not exist and we find the sup-value and sub-value functions of the game. We also establish and solve a cooperative game in which both insurers make joint efforts to minimize the probability that the sum of surplus processes reaches a low target before it hits a high target. Numerical examples and economic implications are given to illustrate the results. (C) 2020 Elsevier B.V. All rights reserved.
机译:本文研究了具有再保险控制的两个保险公司之间的非合作和合作随机微分对策。剩余过程由扩散近似过程建模,保险人可以动态购买再保险(即随时间连续控制漂移和扩散项)。我们考虑两种类型的再保险:配额份额(QS)再保险和超额损失(XL)再保险。在非合作博弈中,一家保险公司试图最小化两家保险公司的盈余差额在达到高目标之前达到低目标的概率,而另一家保险公司则试图最大化概率。我们考虑了两个案例:第一种情况下,两个保险公司都购买了XL再保险;在第二种情况下,一家保险公司购买QS再保险,而另一家则购买XL再保险。在某些参数情况下,我们通过明确地找到价值函数和纳什均衡策略来解决博弈。在某些参数情况下,价值函数和纳什均衡策略不存在,我们找到了博弈的上价值函数和下价值函数。我们还建立并解决了一个合作博弈,在该博弈中,两个保险公司共同努力,以最小化剩余过程之和在达到高目标之前达到低目标的概率。文中给出了数值算例和经济意义。(C) 2020爱思唯尔B.V.版权所有。

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