Estimating ð ¿ -Functionals for Heavy-Tailed Distributions and Application

Abdelhakim Necir and Djamel Meraghni

Journal of Probability and Statistics, 2010, vol. 2010, 1-34

Abstract:

ð ¿ -functionals summarize numerous statistical parameters and actuarial risk measures. Their sample estimators are linear combinations of order statistics ( ð ¿ -statistics). There exists a class of heavy-tailed distributions for which the asymptotic normality of these estimators cannot be obtained by classical results. In this paper we propose, by means of extreme value theory, alternative estimators for ð ¿ -functionals and establish their asymptotic normality. Our results may be applied to estimate the trimmed ð ¿ -moments and financial risk measures for heavy-tailed distributions.

Date: 2010
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/JPS/2010/707146.pdf (application/pdf)
http://downloads.hindawi.com/journals/JPS/2010/707146.xml (text/xml)

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:hin:jnljps:707146

DOI: 10.1155/2010/707146

Access Statistics for this article

More articles in Journal of Probability and Statistics from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().