EconPapers    
Economics at your fingertips  
 

Nonparametric estimation of ruin probability by complex Fourier series expansion in the compound Poisson model

Jing Li, Wenguang Yu and Chaolin Liu

Communications in Statistics - Theory and Methods, 2022, vol. 51, issue 15, 5048-5063

Abstract: In this paper, we consider the estimation of ruin probability in the classical compound Poisson model. We first show that the ruin probability can be expressed by the complex Fourier series expansion. Then using a random sample on claim number and individual claim sizes we construct a nonparametric estimator of the ruin probability. Error analysis of the new estimator is made when the sample size is large, and simulation results are also provided to show the efficiency of our method when the sample size is finite.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2020.1831542 (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:51:y:2022:i:15:p:5048-5063

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2020.1831542

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 ().

 
Page updated 2025-03-20
Handle: RePEc:taf:lstaxx:v:51:y:2022:i:15:p:5048-5063