What do distortion risk measures tell us on excess of loss reinsurance with reinstatements?

Antonella Campana and Paola Ferretti
Additional contact information
Antonella Campana: University of Molise, Department SEGeS

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2010, pp 53-61 from Springer

Abstract: Abstract In this paper we focus our attention on the study of an excess of loss reinsurance with reinstatements, a problem previously studied by Sundt and, more recently, by Mata and Hürlimann. It is well known that the evaluation of pure premiums requires knowledge of the claim size distribution of the insurance risk: in order to face this question, different approaches have been followed in the actuarial literature. In a situation of incomplete information in which only some characteristics of the involved elements are known, it appears to be particularly interesting to set this problem in the framework of risk-adjusted premiums. It is shown that if risk-adjusted premiums satisfy a generalised expected value equation, then the initial premium exhibits some regularity properties as a function of the percentages of reinstatement.

Keywords: excess of loss reinsurance; reinstatements; distortion risk measures (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Working Paper: What do distortion risk measures tell us on excess of loss reinsurance with reinstatements ? (2008)
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:spr:sprchp:978-88-470-1481-7_6

Ordering information: This item can be ordered from
http://www.springer.com/9788847014817

DOI: 10.1007/978-88-470-1481-7_6

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().