Extreme Value Theory: an introductory overview
Isabel Fraga Alves – University of Lisbon

This talk is intended to be an introduction to the most important results in Extreme Value Theory (EVT) and to give a flavour of how they can be applied in practice. The target readership is constituted by students and practitioners who may wish to get acquaintance with EVT. Relying on well founded theory, on which parametric or semiparametric statistical models are built for handling with rare events, EVT is the theorical framework for modeling events which occur with a very small probability. The typical question we would like to answer is

“If things go wrong, how wrong can they go?”

which in a certain sense is the mitigation attitude to Murphy’s law

“If anything can go wrong, it will!”

In fact, the statistical analysis of extremes is the key step in the study of many risk management problems related not only to insurance, reinsurance, and finance in general, but also in other fields as geophysics and environment, where the analysis of extremes is of primordial importance.

Isabel Fraga Alves

Isabel Fraga Alves is Associate Professor at the Department of Statistics and Operations Research, Faculty of Sciences, University of Lisbon. Profile: PhD in Statistics and Computation, Probability and Statistics (Univ. Lisbon, 1992) with PhD Thesis “Statistical Inference in Extreme Value Models”, Habilitation Degree of Statistics and Operations Research, (Univ. Lisbon, 2004), past-Coordinator of Center of Statistics and Applications of University of Lisbon (2006-2009), Elected Member of International Statistical Institute, Member of Bernoulli Society for Mathematical Statistics and Probability, Portuguese Statistical Society and Portuguese Mathematical Society. Organizer of several international conferences: EVT2013 – Extremes in Vimeiro Today, REV2011 – Workshop on Risk & Extreme Values in Insurance and Finance, Extremes, Risk and the Environment (Invited Session to the 56th Session of the ISI, 2007). To know more…


“Every basic course on Statistics is oriented to the main bulk of observations, where Central Limit Theorem is the “king” ruled by the bell curve of Normal distribution. However, in my perspective, all situations in which Extreme Values (EV) are involved are much more interesting and its “domestication” by EV-distributions, allowing to go beyond of the range data and supported by Gnedenko’s theorem, represents a very instructive and challenging “universe” for those that are faced with “black swans” in their day-by-day life.”

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