dc.contributor |
Xarxa de Referència en Economia Aplicada (XREAP) |
dc.contributor.author |
Alemany Leira, Ramon |
dc.contributor.author |
Bolancé Losilla, Catalina |
dc.contributor.author |
Guillén, Montserrat |
dc.date.accessioned |
2012-10-22T12:46:04Z |
dc.date.accessioned |
2021-01-20T16:45:23Z |
dc.date.available |
2012-10-22T12:46:04Z |
dc.date.available |
2021-01-20T16:45:23Z |
dc.date.created |
2012-10-16 |
dc.date.issued |
2012-10-16 |
dc.identifier.uri |
http://hdl.handle.net/2072/202969 |
dc.format.extent |
40 p. |
dc.language.iso |
eng |
dc.publisher |
Xarxa de Referència en Economia Aplicada (XREAP) |
dc.relation.ispartofseries |
XREAP;2012-19 |
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/3.0/es/ |
dc.source |
RECERCAT (Dipòsit de la Recerca de Catalunya) |
dc.subject.other |
Teoria de l'estimació |
dc.subject.other |
Risc (Economia) |
dc.subject.other |
Estadística no paramétrica |
dc.subject.other |
Estimation theory |
dc.subject.other |
Risk |
dc.subject.other |
Nonparametric statistics |
dc.title |
Nonparametric estimation of Value-at-Risk |
dc.type |
info:eu-repo/semantics/workingPaper |
dc.subject.udc |
33 - Economia |
dc.embargo.terms |
cap |
dc.description.abstract |
A method to estimate an extreme quantile that requires no distributional assumptions is presented. The approach is based on transformed kernel estimation of the cumulative distribution function (cdf). The proposed method consists of a double transformation kernel estimation. We derive optimal bandwidth selection methods that have a direct expression for the smoothing parameter. The bandwidth can accommodate to the given quantile level. The procedure is useful for large data sets and improves quantile estimation compared to other methods in heavy tailed distributions. Implementation is straightforward and R programs are available. |