Risk models based on copulas for premiums and claim sizes

Yao Kang, Dehui Wang and Jianhua Cheng

Communications in Statistics - Theory and Methods, 2021, vol. 50, issue 10, 2250-2269

Abstract: In this article, we generalize the individual risk model by introducing a dependence relationship between premiums and claim sizes. The dependence structure is described by bivariate distribution and copulas. Some statistical properties of the models are obtained. The loss probability, value at risk (VaR) and tail value at risk (TVaR) are applied to quantify the risk of the models. To this end, we use net loss (claim sizes minus premiums) instead of claim sizes to calculate the risk measures. Some numerical examples are given to illustrate the results. The normal approximation method is used to simplify the risk measures for the models.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2019.1662443 (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:50:y:2021:i:10:p:2250-2269

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

DOI: 10.1080/03610926.2019.1662443

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 ().