ON THE EXPECTED DISCOUNTED PENALTY FUNCTION IN A MARKOV-DEPENDENT RISK MODEL WITH CONSTANT DIVIDEND BARRIER  

作　　者：刘娟 徐建成 胡亦钧 

机构地区：[1]College of Mathematics and Statistics,Hubei Normal University [2]School of Mathematics and Statistics,Wuhan University

出　　处：《Acta Mathematica Scientia》2010年第5期1481-1491,共11页数学物理学报（B辑英文版）

基　　金：supported in part by Hubei Normal University Post-graduate Foundation(2007D59 and 2007D60);the Science and Technology foundation of Hubei(D20092207);the National Natural Science Foundation of China(10671149)

摘　　要：This article considers a Markov-dependent risk model with a constant dividend barrier. A system of integro-differential equations with boundary conditions satisfied by the expected discounted penalty function, with given initial environment state, is derived and solved. Explicit formulas for the discounted penalty function are obtained when the initial surplus is zero or when all the claim amount distributions are from rational family. In two state model, numerical illustrations with exponential claim amounts are given.This article considers a Markov-dependent risk model with a constant dividend barrier. A system of integro-differential equations with boundary conditions satisfied by the expected discounted penalty function, with given initial environment state, is derived and solved. Explicit formulas for the discounted penalty function are obtained when the initial surplus is zero or when all the claim amount distributions are from rational family. In two state model, numerical illustrations with exponential claim amounts are given.

关 键 词：Markov-dependent risk model dividend barrier Cerber-Shiu function integro-differential equation Laplace transform 

分 类 号：O242.1[理学—计算数学]