Extremes publishes original research on all aspects of statistical extreme value theory and its applications in science, engineering, economics and other fields. Authoritative and timely reviews of theoretical advances and of extreme value methods and problems in important applied areas, including detailed case studies, are welcome and will be a regular feature. All papers are refereed. Publication will be swift: in particular electronic submission and correspondence is encouraged.

Statistical extreme value methods encompass a very wide range of problems: Extreme waves, rainfall, and floods are of basic importance in oceanography and hydrology, as are high windspeeds and extreme temperatures in meteorology and catastrophic claims in insurance. The waveforms and extremes of random loads determine lifelengths in structural safety, corrosion and metal fatigue. High concentrations of pollutants constitute health hazards. Large fluctuations in asset, share and bond prices and in exchange and interest rates have serious consequences for the economy. Much of risk and reliability theory is concerned with extreme occurrences. Methods and problems in tail estimation, statistical process control, sequential analysis, and heavy-tailed models for time series are closely related to extreme value theory. Numerical methods, optimization, simulation, and resampling are of interest for statistical extremes.

Publication of research on statistical extremes is very scattered: e.g. in probability journals like the Annals of Probability or the Applied Probability journals, in statistical journals such as the Annals of Statistics, the Journals of the Royal Statistical Society or Technometrics, and in journals in hydrology, oceanography, meteorology, reliability, civil engineering, economics, finance and physics. The fragmented publication leads to long delays before theoretical advances find their way into practical application. Similarly, important applied problems are slow to gain attention by theoreticians.

The aim of Extremes is to advance and speed up research and applications by providing a unified forum for the best papers on statistical extremes. In Extremesapplied scientists will find comprehensive and up-to-date coverage of theoretical developments, specialists will find authoritative discussions of urgent applied problems, and authors will find the best medium for the dissemination and use of their results.

Editor-in-Chief:
Thomas Mikosch, University of Copenhagen
Area Editors:
Extremes in Environmental Sciences: Philippe Naveau
Extremes in Applied Probability: José Blanchet
High-Dimensional Extremes: Johan Segers
Extremes in Machine-Learning: Oliver Wintenberger
Editorial Board:

José Blanchet, Stanford University; Dan Cooley, Colorado State University; Clément Dombry, l'Université de Franche-Comté, Laboratoire de Mathématiques de Besançon; Holger Drees, University of Hamburg; John Einmahl, Tilburg University; Sebastian Engelke, University of Geneva; Ana Ferreira, University of Lisbon; Ivette Gomes, University of Lisbon; Laurens de Haan, Erasmus University Rotterdam; Enkelejd Hashorva, University of Lausanne; Raphael G. Huser, King Abdullah University of Science and Technology (KAUST); Juerg Hüsler, University of Bern; Anja Janssen, KTH Royal Institute of Technology; Rafal Kulik, University of Ottawa; Jingchen Liu, Columbia University; Philippe Naveau, Lab. des Sciences du Climat et l'Environnement; Simone Padoan, Bocconi University; Vladimir I. Piterbarg, Lomonosov State University; Mathieu Ribatet, Université Montpellier ; Holger Rootzén, Chalmers University of Technology; Gennady Samorodnitsky, Cornell University; Johan Segers, Université Catholique de Louvain; Stilian Stoev, University of Michigan; Kirstin Strokorb, Cardiff University; Jonathan Tawn, University of Lancaster; Olivier Wintenberger, University Pierre and Marie Curie; Chen Zhou, Erasmus University Rotterdam