On log-normal convolutions: An analytical–numerical method with applications to economic capital determination
Edward Furman,
Daniel Hackmann and
Alexey Kuznetsov
Insurance: Mathematics and Economics, 2020, vol. 90, issue C, 120-134
Abstract:
We put forward an efficient algorithm for approximating the sums of independent and log-normally distributed random variables. Namely, by combining tools from probability theory and numerical analysis, we are able to compute the cumulative distribution functions of the just-mentioned sums to a high precision and in a relatively short computing time. We illustrate the effectiveness of the new method in the contexts of the individual and collective risk models, aggregate economic capital determination, and economic capital allocation.
Keywords: Log-normal distribution; Convolution; Generalized gamma convolution; Padé approximation; Individual risk model; Collective risk model; Economic capital (search for similar items in EconPapers)
JEL-codes: C02 C46 C63 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167668719303993
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:90:y:2020:i:c:p:120-134
DOI: 10.1016/j.insmatheco.2019.10.003
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 ().