"The book can be recommended to EVT specialists and Ph.D. students in probability and statistics who wish to specialize in that field. It can provide a useful complement to more practically oriented textbooks …"
—Christian Genest, Journal of the American Statistical Association, September 2013
"Each chapter is well structured with the main propositions, lemmas, theorems, and subsequent corollaries outlined and discussed first, with the proofs given towards the end of the chapter to keep the reader from getting bogged down in details. Each chapter has a set of exercises, useful to an advanced graduate class … Some chapters provide a handful of open questions, which will be of interest to new researchers in the field. … The book provides a useful complement to Resnick (1987, 2007) and De Haan & Ferreira (2006). For those interested in financial applications, it provides the next stage of depth compared to Embrechts, Kluppelberg, & Mikosch (2003) and the wide range of application-oriented books of extremes for finance applications. This book will be of interest to researchers interested in the asymptotic probability theory underlying univariate extreme value theory, including non-parametric tail index estimation."
—Carl Scarrott, Australian & New Zealand Journal of Statistics, 2013
"The book covers modern topics in EVT such as processes of exceedances, compound Poisson approximation, Poisson cluster approximation, nonparametric estimation methods, extremes in samples of random size, methods of estimating extreme quantiles and tail probabilities, self-normalized sums of random variables and measures of market risk. The novelty of this book in comparison to others on the EVT area is detailed coverage of the above-mentioned topics. The author is an expert on the topic of EVT and many results from his own scientific papers are included in the book. … Theoretical results in the book are illustrated by examples and applications to particular problems of financial risk management. Exercises and open problems are given in all chapters. The list of references includes 407 items and can serve as an excellent source of new results on the topics presented in the book."
—Pavle Mladenović, Mathematical Reviews, January 2013
"Though the first part of the book covers the well-known asymptotic theory for extremes, there are many new techniques and results which do not exist in other books on extreme value theory. These chapters will be particularly interesting to probabilists and other experts working on extreme value theory. … Those who want to learn extreme value theory and in particular, those who want to study in detail the non-parametric methods for heavy tailed distributions, will find this book a very valuable contribution. … I would strongly recommend this book to PhD students working on extreme value theory [and] to mathematicians, probabilists and statisticians who want to know about extreme value theory and non-parametric methods of inference for extremes."
—K.F. Turkman, Journal of Times Series Analysis, March 2012
