On the dual risk model with Parisian implementation delays under a mixed dividend strategy

IF 0.7 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL
K. Hu, Jingchao Li, Jieming Zhou
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引用次数: 0

Abstract

Abstract In this paper, we consider a mixed dividend strategy in a dual risk model. The mixed dividend strategy is the combination of a threshold dividend and a Parisian implementation delays dividend under periodic observation. Given a series of discrete observation points, when the surplus level is larger than the predetermined bonus barrier at observation point, the Parisian implementation delays dividend is immediately carried out, and the threshold dividend is performed continuously during the delayed period. We study the Gerber-Shiu expected discounted penalty function and the expected discounted dividend payments before ruin in such a dual risk model. Numerical illustrations are given to study the influence of relevant parameters on the ruin-related quantities and the selection of the optimal dividend barrier for a given initial surplus level.
混合股利策略下具有巴黎执行延迟的双重风险模型
摘要本文考虑双重风险模型下的混合股利策略。混合股利策略是阈值股利和巴黎延迟股利在定期观察下的组合。给定一系列离散的观察点,当盈余水平大于观察点上预定的红利障碍时,立即进行巴黎实施延迟分红,并在延迟期间连续执行阈值分红。本文研究了双重风险模型中的Gerber-Shiu期望折现惩罚函数和破产前的期望折现股利支付。通过数值实例研究了在给定初始剩余水平下,相关参数对破产相关量的影响以及最优股利障碍的选择。
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
CiteScore
2.20
自引率
18.20%
发文量
45
审稿时长
>12 weeks
期刊介绍: The primary focus of the journal is on stochastic modelling in the physical and engineering sciences, with particular emphasis on queueing theory, reliability theory, inventory theory, simulation, mathematical finance and probabilistic networks and graphs. Papers on analytic properties and related disciplines are also considered, as well as more general papers on applied and computational probability, if appropriate. Readers include academics working in statistics, operations research, computer science, engineering, management science and physical sciences as well as industrial practitioners engaged in telecommunications, computer science, financial engineering, operations research and management science.
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