Journal article
Reducing risk by merging counter-monotonic risks
Insurance, mathematics & economics, Vol.54(1), pp.58-65
01/2014
DOI: 10.1016/j.insmatheco.2013.10.014
Abstract
In this article, we show that some important implications concerning comonotonic couples and corresponding convex order relations for their sums cannot be translated to counter-monotonicity in general. In a financial context, it amounts to saying that merging counter-monotonic positions does not necessarily reduce the overall level of risk. We propose a simple necessary and sufficient condition for such a merge to be effective. Natural interpretations and various characterizations of this condition are given. As applications, we develop cancelation laws for convex order and identify desirable structural properties of insurance indemnities that make an insurance contract universally marketable, in the sense that it is appealing to both the policyholder and the insurer.
•A condition for merging counter-monotonic positions to be risk-reducing is formulated.•New additivity and cancelation laws of convex order are established.•Various characterizations of a risk reducer are given.•Structural properties of universally marketable insurance indemnities are studied.
Details
- Title: Subtitle
- Reducing risk by merging counter-monotonic risks
- Creators
- Ka Chun Cheung - Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong KongJan Dhaene - Department of Accountancy, Finance and Insurance, KU Leuven, Naamsestraat 69, B-3000 Leuven, BelgiumAmbrose Lo - Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong KongQihe Tang - Department of Statistics and Actuarial Science, The University of Iowa, 241 Schaeffer Hall, Iowa City, IA 52242, USA
- Resource Type
- Journal article
- Publication Details
- Insurance, mathematics & economics, Vol.54(1), pp.58-65
- Publisher
- Elsevier B.V
- DOI
- 10.1016/j.insmatheco.2013.10.014
- ISSN
- 0167-6687
- eISSN
- 1873-5959
- Language
- English
- Date published
- 01/2014
- Academic Unit
- Statistics and Actuarial Science
- Record Identifier
- 9984083806402771
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