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首页> 外文期刊>Journal of industrial and management optimization >MARKOWITZ'S MEAN-VARIANCE OPTIMIZATION WITH INVESTMENT AND CONSTRAINED REINSURANCE
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MARKOWITZ'S MEAN-VARIANCE OPTIMIZATION WITH INVESTMENT AND CONSTRAINED REINSURANCE

机译:马可维兹的均值优化与投资和约束性再保险

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摘要

This paper deals with the optimal investment-reinsurance strategy for an insurer under the criterion of mean-variance. The risk process is the diffusion approximation of a compound Poisson process and the insurer can invest its wealth into a financial market consisting of one risk-free asset and one risky asset, while short-selling of the risky asset is prohibited. On the side of reinsurance, we require that the proportion of insurer's retained risk belong to [0, 1], is adopted. According to the dynamic programming in stochastic optimal control, the resulting Hamilton-Jacobi-Bellman (HJB) equation may not admit a classical solution. In this paper, we construct a viscosity solution for the HJB equation, and based on this solution we find closed form expressions of efficient strategy and efficient frontier when the expected terminal wealth is greater than a certain level. For other possible expected returns, we apply numerical methods to analyse the efficient frontier. Several numerical examples and comparisons between models with constrained and unconstrained proportional reinsurance are provided to illustrate our results.
机译:本文研究了在均值-方差准则下保险公司的最优投资再保险策略。风险过程是复合泊松过程的扩散近似,保险公司可以将其财富投资到由一种无风险资产和一种风险资产组成的金融市场中,同时禁止卖空该风险资产。在再保险方面,我们要求采用保险人的保留风险比例为[0,1]。根据随机最优控制中的动态规划,所得汉密尔顿-雅各比-贝尔曼(HJB)方程可能不接受经典解。在本文中,我们为HJB方程构造了一个粘性解决方案,并在该解决方案的基础上找到了当预期的最终财富大于一定水平时有效策略和有效边界的闭式表达式。对于其他可能的预期收益,我们采用数值方法来分析有效边界。提供了一些数值示例,以及带有比例和无比例比例再保险的模型之间的比较,以说明我们的结果。

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