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Sur La Distribution Limite Du Terme Maximum D'Une Serie Aleatoire
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This article is published in Annals of Mathematics.The article was published on 1943-07-01. It has received 2037 citations till now.read more
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Kernel estimators for the second order parameter in extreme value statistics
TL;DR: In this paper, a general class of kernel estimators for the second order parameter ρ, a parameter related to the rate of convergence of a sequence of linearly normalized maximum values towards its limit, was developed and studied in the framework of Pareto-type distributions.
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Maximum likelihood estimation in the 3-parameter weibull distribution: a look through the generalized extreme-value distribution
TL;DR: In this article, a Monte Carlo simulation using the newly developed generalized extreme-value distribution parameter estimation code reveals the property of the percentile point estimates for extreme value type distributions, when the Weibull shape parameter is large.
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Regional parent flood frequency distributions in Europe – Part 1: Is the GEV model suitable as a pan-European parent?
TL;DR: In this paper, a new database of L-moment ratios of flood annual maximum series (AMS) from 4105 catchments was compiled by joining 13 national data sets, and simple exploration of the database presents the generalized extreme value (GEV) distribution as a potential pan-European flood frequency distribution, being the three-parameter statistical model that with the closest resemblance to the estimated average of the sample Lmoment ratio.
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Tail estimation and mean–VaR portfolio selection in markets subject to financial instability
TL;DR: In this paper, the authors focus on the implications of different risk measurement techniques and portfolio optimisation strategies in presence of markets subject to periods of severe instability, resulting in significant deviations of financial returns from the Normality assumption typically adopted in mainstream finance.
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Extreme value theory for singular measures.
TL;DR: An analytical and numerical study of the extreme values of specific observables of dynamical systems possessing an invariant singular measure and it is apparent that the analysis of extremes allows for capturing fundamental information of the geometrical structure of the attractor of the underlying dynamical system.