Using fuzzy logic to interpret dependent risks

Sibel Acik Kemaloglu, Arnold F. Shapiro, Fatih Tank and Aysen Apaydin

Insurance: Mathematics and Economics, 2018, vol. 79, issue C, 101-106

Abstract: One reason why an independent claim amounts assumption underlies classic risk models is because it simplifies calculations. As an alternative, this paper investigates the dependence structure via the Farlie–Gumbel–Morgenstern (FGM) Copula and its interpretation given a fuzzy logic approach for claim amounts arising from a Pareto distribution.

Keywords: Linear programming; Dependent risk; Fuzzy membership function; Pareto distribution; FGM copula (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167668717302548
Full text for ScienceDirect subscribers only

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:eee:insuma:v:79:y:2018:i:c:p:101-106

DOI: 10.1016/j.insmatheco.2018.01.001

Access Statistics for this article

Insurance: Mathematics and Economics is currently edited by R. Kaas, Hansjoerg Albrecher, M. J. Goovaerts and E. S. W. Shiu

More articles in Insurance: Mathematics and Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().