Bias reduction in risk modelling: semi-parametric quantile estimation
- Autores: M. Ivette Gomes, Fernanda Figueiredo
- Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 15, Nº. 2, 2006, págs. 375-396
- Idioma: inglés
- DOI: 10.1007/bf02607058
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Resumen
InStatistics of Extremes we are mainly interested in the estimation of quantities related to extreme events. In many areas of application, like for instanceInsurance Mathematics, Finance andStatistical 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 ahigh quantile X p , a value which is overpassed with a small probabilityp. In this paper we deal with the semi-parametric estimation ofX 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.
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