کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5077518 | 1374134 | 2010 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A generalized penalty function with the maximum surplus prior to ruin in a MAP risk model
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: A generalized penalty function with the maximum surplus prior to ruin in a MAP risk model A generalized penalty function with the maximum surplus prior to ruin in a MAP risk model](/preview/png/5077518.png)
چکیده انگلیسی
In this paper, a risk model where claims arrive according to a Markovian arrival process (MAP) is considered. A generalization of the well-known Gerber-Shiu function is proposed by incorporating the maximum surplus level before ruin into the penalty function. For this wider class of penalty functions, we show that the generalized Gerber-Shiu function can be expressed in terms of the original Gerber-Shiu function (see e.g. [Gerber, Hans U., Shiu, Elias, S.W., 1998. On the time value of ruin. North American Actuarial Journal 2(1), 48-72]) and the Laplace transform of a first passage time which are both readily available. The generalized Gerber-Shiu function is also shown to be closely related to the original Gerber-Shiu function in the same MAP risk model subject to a dividend barrier strategy. The simplest case of a MAP risk model, namely the classical compound Poisson risk model, will be studied in more detail. In particular, the discounted joint density of the surplus prior to ruin, the deficit at ruin and the maximum surplus before ruin is obtained through analytic Laplace transform inversion of a specific generalized Gerber-Shiu function. Numerical illustrations are then examined.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Insurance: Mathematics and Economics - Volume 46, Issue 1, February 2010, Pages 127-134
Journal: Insurance: Mathematics and Economics - Volume 46, Issue 1, February 2010, Pages 127-134
نویسندگان
Eric C.K. Cheung, David Landriault,