Estimating catastrophic quantile levels for heavy-tailed distributions

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Bias-reduced estimators of the Weibull tail-coefficient (2008, methodology): “which is similar to the estimator proposed by [20] in the case of Pareto-type distributions.”
Improved reduced-bias tail index and quantile estimators (2008, background): “Alternatively, trying to reduce the bias of the classical quantile estimator by going directly into the second-order framework, in Matthys et al. (2004) the semi-parametric estimator defined as”
A Sturdy Reduced-Bias Extreme Quantile (VaR) Estimator (2007, methodology): “…Q(p) H (k) := ln Xn−k+1:n + H(k) ln ( k np ) , (3.9) with H given in (3.5), and, for comparison, estimators of the type in Gomes and Figueiredo (2006) and Matthys et al. (2004), the ln-VaR class of estimators, ln Q(p) Ĥ (k), with ln Q(p)γ̂ (k) and Ĥ given in (1.5) and (3.7), respectively.”