Title
Estimating the Gerber-Shiu function in a Lévy risk model by Laguerre series expansion.
Abstract
In this paper, we provide a new method for estimating the Gerber–Shiu function in a pure jump Lévy risk model. First, we show that the Gerber–Shiu function can be expressed on the Laguerre basis and the Laguerre coefficients can be easily obtained by solving a linear system. Next, based on a high-frequency observation of the aggregate claims process, we estimate the Laguerre coefficients and this leads to a new estimator of the Gerber–Shiu function. We derive the consistency property of this estimator when the sample size is large. Finally, we do some simulation studies to illustrate the finite sample size performance.
Year
DOI
Venue
2019
10.1016/j.cam.2018.07.003
Journal of Computational and Applied Mathematics
Keywords
Field
DocType
Gerber–Shiu function,Estimate,Lévy risk model,Laguerre series
Linear system,Laguerre polynomials,Mathematical analysis,Series expansion,Jump,Mathematics,Sample size determination,Risk model,Estimator
Journal
Volume
ISSN
Citations 
346
0377-0427
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
Zhimin Zhang15411.10
Wen Su211513.76