论文标题
重新审视最佳股息：一种基于梯度的方法和进化算法
Optimal dividends revisited: a gradient-based method and evolutionary algorithms
论文作者
论文摘要
我们重新考虑了Cramér-Lundberg风险模型中最佳股息策略的研究。众所周知，经典股息问题的解决方案通常是乐队策略。但是，很难实施文献中可用的最佳带的数值技术，并且仅在很少的情况下才知道明确的数值结果。在本文中，我们制定了一种基于梯度的方法，该方法允许在更一般的情况下确定最佳频段。此外，我们将进化算法适应了这个股息问题，该股息问题不是那么快，但适用于相当多的一般性，可以提供竞争性的基准。我们说明了具体示例中提出的方法，在文献中再现了早期的结果，并为索赔尺寸分布建立了新的，以前无法研究。
We reconsider the study of optimal dividend strategies in the Cramér-Lundberg risk model. It is well-known that the solution of the classical dividend problem is in general a band strategy. However, the numerical techniques for the identification of the optimal bands available in the literature are very hard to implement and explicit numerical results are known for very few cases only. In this paper we put a gradient-based method into place which allows to determine optimal bands in more general situations. In addition, we adapt an evolutionary algorithm to this dividend problem, which is not as fast, but applicable in considerable generality, and can serve for providing a competitive benchmark. We illustrate the proposed methods in concrete examples, reproducing earlier results in the literature as well as establishing new ones for claim size distributions that could not be studied before.
