Optimal dividend bands revisited: a gradient-based method and evolutionary algorithms

IF 1.6 3区 经济学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
H. Albrecher, Brandon Garcia Flores
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引用次数: 2

Abstract

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.
最优股息带重新审视:基于梯度的方法和进化算法
本文重新考虑了cram - lundberg风险模型中股利最优策略的研究。众所周知,经典股利问题的求解一般采用波段策略。然而,文献中可用的用于识别最佳波段的数值技术很难实现,并且仅在极少数情况下才知道明确的数值结果。在本文中,我们提出了一种基于梯度的方法,可以在更一般的情况下确定最佳波段。此外,我们采用了一种进化算法来解决这个股利问题,该算法的速度没有那么快,但具有相当的通用性,并且可以提供一个有竞争力的基准。我们在具体的例子中说明了所提出的方法,再现了文献中早期的结果,并为以前无法研究的索赔规模分布建立了新的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Scandinavian Actuarial Journal
Scandinavian Actuarial Journal MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
3.30
自引率
11.10%
发文量
38
审稿时长
>12 weeks
期刊介绍: Scandinavian Actuarial Journal is a journal for actuarial sciences that deals, in theory and application, with mathematical methods for insurance and related matters. The bounds of actuarial mathematics are determined by the area of application rather than by uniformity of methods and techniques. Therefore, a paper of interest to Scandinavian Actuarial Journal may have its theoretical basis in probability theory, statistics, operations research, numerical analysis, computer science, demography, mathematical economics, or any other area of applied mathematics; the main criterion is that the paper should be of specific relevance to actuarial applications.
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