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随机保费风险模型下的平均折现罚金函数
引用本文:姚定俊,汪荣明,徐林. 随机保费风险模型下的平均折现罚金函数[J]. 应用概率统计, 2008, 24(3): 319-326
作者姓名:姚定俊  汪荣明  徐林
作者单位:1. 华东师范大学金融与统计学院,上海,200241
2. 华东师范大学金融与统计学院,上海,200241;安徽师范大学数学计算机科学学院,芜湖,241003
基金项目:国家自然科学基金 , 高等学校博士学科点专项科研项目 , 国家重点基础研究发展计划(973计划) , 安徽省教育厅自然科学基金
摘    要:本文研究随机保费风险模型下与破产时刻相关的平均折现罚金函数. 与经典的Cram'{e}r-Lundberg模型相比这里的保费过程不再是时间的线性函数, 而是一个与理赔独立的复合Possion过程. 我们得到了罚金函数所满足的积分方程, 它提供了一种研究破产量的统一方法. 利用该积分方程我们得到了破产时刻, 破产时赤字, 破产前瞬时盈余的Laplace变换; 并在指数分布的特殊情况下求出了他们的显著表达式, 推广了Boikov (2003)的结论.

关 键 词:随机保费  积分方程  罚金函数  破产时刻  破产时赤字  破产前瞬时盈余.

On the Expected Discounted Penalty Function Associated with the Time of Ruin for a Risk Model with Random Income
YAO DINGJUN,WANG RONGMING,XU LIN. On the Expected Discounted Penalty Function Associated with the Time of Ruin for a Risk Model with Random Income[J]. Chinese Journal of Applied Probability and Statisties, 2008, 24(3): 319-326
Authors:YAO DINGJUN  WANG RONGMING  XU LIN
Affiliation:School of Finance and Statistics, East China Normal University; School of Mathematic and Computer Science, Anhui Normal University
Abstract:This paper studies the expected discounted penalty function associated with the time of ruin for a risk model with stochastic premium. The premium process is no longer a linear function of time in contrast with the classical Cram'{e}r-Lundberg model. The aggregate premiums constitute a compound Poisson process which is also independent of the claim process. Integral equation for the penalty function is derived, which provides a unified treatment to the ruin quantities. Applications of the integral equation are given to the Laplace transform of the time of ruin, the deficit at ruin, the surplus immediately before ruin occurs. In some special cases with exponential distributions, closed form expressions for these quantities are obtained, which generalize some known results about the problems of ruin in Boikov (2003).
Keywords:Stochastic premium  integral equation  penalty function  the time of ruin  the deficit at ruin  the surplus immediately before ruin occurs.
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