Bias reduction in risk modelling: Semi-parametric quantile estimation

• Type: Article in International Scientific Journal
• Date: 2006

Authors

gomes, mi (Author) Other; figueiredo, f (Author) FEP

Journal

Title: Test

Vol. 15 No. 2

Pages: 375-396

ISSN: 1133-0686

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 21 Citations

Scopus - 21 Citations

Scientific classification

FOS: Natural sciences > Mathematics

Other information

Authenticus ID: P-004-FZF

DOI: 10.1007/bf02607058

Abstract (EN): In Statistics of Extremes we are mainly interested in the estimation of quantities related to extreme events. In many areas of application, like for instance Insurance Mathematics, Finance and Statistical Quality Control, a typical requirement is to find a value, high enough, so that the chance of an exceedance of that value is small. We are then interested in the estimation of a high quantile chi(p), a value which is overpassed with a small probability p. In this paper we deal with the semi-parametric estimation of chi(p) for heavy tails. Since the classical semi-parametric estimators exhibit a reasonably high bias for low thresholds, we shall deal with bias reduction techniques, trying to improve their performance.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 22