Bias reduction in risk modelling: semi-parametric quantile estimation

DOI10.1007/BF02607058zbMath1110.62066MaRDI QIDQ882935

Fernanda Figueiredo, M. Ivette Gomes

Publication date: 25 May 2007

Published in: Test (Search for Journal in Brave)

zbMATH Keywords

bias reductionheavy tailsstatistics of extremeshigh quantilessemi-parametric estimation

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Statistics of extreme values; tail inference (62G32)

Related Items (12)

Reduced-bias and partially reduced-bias mean-of-order-p value-at-risk estimation: a Monte-Carlo comparison and an application ⋮ Bias correction in extreme value statistics with index around zero ⋮ A Mean-of-Order-$$p$$ Class of Value-at-Risk Estimators ⋮ Kernel-type estimators for the distortion risk premiums of heavy-tailed distributions ⋮ Corrected-Hill versus partially reduced-bias value-at-risk estimation ⋮ Semi-parametric second-order reduced-bias high quantile estimation ⋮ Extreme Value Theory and Statistics of Univariate Extremes: A Review ⋮ Improved reduced-bias tail index and quantile estimators ⋮ Bias reduction for high quantiles ⋮ Statistics of extremes for IID data and breakthroughs in the estimation of the extreme value index: Laurens de Haan leading contributions ⋮ Subsampling techniques and the jackknife methodology in the estimation of the extremal index ⋮ Adaptive Reduced-Bias Tail Index and VaR Estimation via the Bootstrap Methodology

Cites Work

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• Generalizations of the Hill estimator -- asymptotic versus finite sample behaviour
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