Joint moments of discounted claims and discounted perturbation until ruin in the compound Poisson risk model with diffusion

IF 0.7 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL Probability in the Engineering and Informational Sciences Pub Date : 2022-03-31 DOI:10.1017/S0269964822000080
Eric C. K. Cheung, Haibo Liu
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引用次数: 1

Abstract

This paper studies a generalization of the Gerber-Shiu expected discounted penalty function [Gerber and Shiu (1998). On the time value of ruin. North American Actuarial Journal 2(1): 48–72] in the context of the perturbed compound Poisson insurance risk model, where the moments of the total discounted claims and the discounted small fluctuations (arising from the Brownian motion) until ruin are also included. In particular, the latter quantity is represented by a stochastic integral and has never been analyzed in the literature to the best of our knowledge. Recursive integro-differential equations satisfied by our generalized Gerber-Shiu function are derived, and these are transformed to defective renewal equations where the components are identified. Explicit solutions are given when the individual claim amounts are distributed as a combination of exponentials. Numerical illustrations are provided, including the computation of the covariance between discounted claims and discounted perturbation until ruin.
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带扩散的复合泊松风险模型中索赔折现与扰动折现直至破产的联合矩
本文研究了Gerber-Shiu期望折现惩罚函数[Gerber and Shiu(1998)]的推广。论毁灭的时间价值。北美精算杂志2(1):48-72]在扰动复合泊松保险风险模型的背景下,其中也包括了总贴现索赔和贴现小波动(由布朗运动引起)的矩,直到破产。特别是,后一个量由随机积分表示,据我们所知,在文献中从未对其进行过分析。导出了由广义Gerber-Shiu函数满足的递推积分-微分方程,并将其转化为有缺陷的更新方程。当单个索赔金额作为指数组合分布时,给出显式解决方案。给出了数值实例,包括贴现索赔与贴现扰动之间的协方差计算,直至破产。
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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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