Robust and asymptotically unbiased estimation of extreme quantiles for heavy tailed distributions

Yuri Goegebeur; Armelle Guillou; Andréhette Verster

doi:10.1016/j.spl.2014.01.010

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Robust and asymptotically unbiased estimation of extreme quantiles for heavy tailed distributions

Yuri Goegebeur Armelle Guillou Andréhette Verster

Year: 2014 Journal: Statistics & Probability Letters Vol: 87 Pages: 108-114 Publisher: Elsevier BV

DOI: 10.1016/j.spl.2014.01.010

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Keywords:

Mathematics Quantile Estimator Applied mathematics Generalized Pareto distribution Statistics Pareto principle Heavy-tailed distribution Minimum-variance unbiased estimator Extreme value theory Unbiased Estimation Probability distribution

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Financial Risk and Volatility Modeling

Social Sciences → Economics, Econometrics and Finance → Finance

Statistical Distribution Estimation and Applications

Physical Sciences → Mathematics → Statistics and Probability

Monetary Policy and Economic Impact

Social Sciences → Economics, Econometrics and Finance → General Economics, Econometrics and Finance

Robust and asymptotically unbiased estimation of extreme quantiles for heavy tailed distributions

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