Forecasting compositional risk allocations
Tim J. Boonen,
Montserrat Guillen and
Insurance: Mathematics and Economics, 2019, vol. 84, issue C, 79-86
We analyse models for panel data that arise in risk allocation problems, when a given set of sources are the cause of an aggregate risk value. We focus on the modelling and forecasting of proportional contributions to risk over time. Compositional data methods are proposed and the time-series regression is flexible to incorporate external information from other variables. We guarantee that projected proportional contributions add up to 100%, and we introduce a method to generate confidence regions with the same restriction. An illustration is provided for risk capital allocations.
Keywords: Simplex; Capital allocation; Dynamic risk management; Isometric logratio; Aitchison geometry (search for similar items in EconPapers)
JEL-codes: C02 G22 D81 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:84:y:2019:i:c:p:79-86
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 Dana Niculescu ().