Estimating the Conditional Tail Expectation in the Case of Heavy-Tailed Losses

Abdelhakim Necir, Abdelaziz Rassoul and Ričardas Zitikis

Journal of Probability and Statistics, 2010, vol. 2010, 1-17

Abstract:

The conditional tail expectation (CTE) is an important actuarial risk measure and a useful tool in financial risk assessment. Under the classical assumption that the second moment of the loss variable is finite, the asymptotic normality of the nonparametric CTE estimator has already been established in the literature. The noted result, however, is not applicable when the loss variable follows any distribution with infinite second moment, which is a frequent situation in practice. With a help of extreme-value methodology, in this paper, we offer a solution to the problem by suggesting a new CTE estimator, which is applicable when losses have finite means but infinite variances.

Date: 2010
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://downloads.hindawi.com/journals/JPS/2010/596839.pdf (application/pdf)
http://downloads.hindawi.com/journals/JPS/2010/596839.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:596839

DOI: 10.1155/2010/596839

Access Statistics for this article

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