Tail index estimation for heavy‐tailed models: accommodation of bias in weighted log‐excesses

M. Ivette Gomes, Laurens de Haan and Lígia Henriques Rodrigues

Journal of the Royal Statistical Society Series B, 2008, vol. 70, issue 1, 31-52

Abstract: Summary. We are interested in the derivation of the distributional properties of a weighted log‐excesses estimator of a positive tail index γ. One of the main objectives of such an estimator is the accommodation of the dominant component of asymptotic bias, together with the maintenance of the asymptotic variance of the maximum likelihood estimator of γ, under a strict Pareto model. We consider the external estimation not only of a second‐order shape parameter ρ but also of a second‐order scale parameter β. This will enable us to reduce the asymptotic variance of the final estimators under consideration, compared with second‐order reduced bias estimators that are already available in the literature. The second‐order reduced bias estimators that are considered are also studied for finite samples, through Monte Carlo techniques, as well as applied to real data in the field of finance.

Date: 2008
References: View complete reference list from CitEc
Citations: View citations in EconPapers (30)

Downloads: (external link)
https://doi.org/10.1111/j.1467-9868.2007.00620.x

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:bla:jorssb:v:70:y:2008:i:1:p:31-52

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9868

Access Statistics for this article

Journal of the Royal Statistical Society Series B is currently edited by P. Fryzlewicz and I. Van Keilegom

More articles in Journal of the Royal Statistical Society Series B from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().