On a Risk Model With Delayed Claims Under Stochastic Interest Rates
Jie-Hua Xie,
Jian-Wei Gao and
Wei Zou
Communications in Statistics - Theory and Methods, 2015, vol. 44, issue 14, 3022-3041
Abstract:
This article studies a compound binomial risk model where the delayed claims are considered, and defines two types of individual claims, main claims and by-claims, respectively. Each by-claim is induced by the main claim and may be delayed for one time period with a certain probability. An extended definition of the Gerber-Shiu discounted penalty function is proposed to analyze this risk model in the framework of stochastic interest rates which follow a Markov chain with finite state space. By applying generating function and generalized Rouche´${\rm {\acute{e}}}$’s theorem, we derive an explicit expression for this generalized Gerber-Shiu discounted penalty function in terms of the zeros of a determinant. Furthermore, we examine the original Gerber-Shiu discounted penalty function in the compound binomial model with delayed claims. In addition, we prove that the original Gerber-Shiu discounted penalty function satisfies a defective renewal equation, and derive the exact solution of this equation via an associated compound geometric distribution. Moreover, the closed form expressions of ruin probability and the distribution function of the surplus before ruin are obtained for some special cases. Finally, numerical results are provided to illustrate the applicability of our main result and the impact of the delay of by-claims on the Gerber-Shiu discounted penalty functions.
Date: 2015
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2013.799698 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:44:y:2015:i:14:p:3022-3041
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20
DOI: 10.1080/03610926.2013.799698
Access Statistics for this article
Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe
More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().