dc.contributor
Xarxa de Referència en Economia Aplicada (XREAP)
dc.contributor.author
Boonen, Tim. J.
dc.contributor.author
Guillén, Montserrat
dc.contributor.author
Santolino, Miguel
dc.date.accessioned
2018-11-15T17:51:14Z
dc.date.accessioned
2021-01-20T16:45:34Z
dc.date.accessioned
2024-11-29T09:40:35Z
dc.date.available
2018-11-15T17:51:14Z
dc.date.available
2021-01-20T16:45:34Z
dc.date.available
2024-11-29T09:40:35Z
dc.identifier.uri
http://hdl.handle.net/2072/336133
dc.description.abstract
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 modeling and forecasting of proportional contributions to risk. Compositional data methods are proposed and the 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 using data from the stock exchange is provided.
cat
dc.publisher
Xarxa de Referència en Economia Aplicada (XREAP)
dc.relation.ispartofseries
XREAP;2017-04
dc.rights
info:eu-repo/semantics/openAccess
dc.rights
L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons: http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.source
RECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.other
Risc (Economia)
dc.subject.other
Models matemàtics
dc.subject.other
Mathematical models
dc.title
Forecasting compositional risk allocations
dc.type
info:eu-repo/semantics/patent
