Long-memory, or more generally fractal, processes are known to play an important role in
many scientific disciplines and applied fields such as physics, geophysics, hydrology …

Research in the statistical analysis of extreme values has flourished over the past decade:
new probability models, inference and data analysis techniques have been introduced; and …

We propose a method for estimating Value at Risk (VaR) and related risk measures
describing the tail of the conditional distribution of a heteroscedastic financial return series …

This is a book on bootstrap and related resampling methods for temporal and spatial data
exhibiting various forms of dependence. Like the resam pling methods for independent data …

This book is concerned with extreme value theory for stochastic processes whose finite-
dimensional distributions are heavy-tailed in the restrictive sense of regular variation. These …

The financial industry, including banking and insurance, is undergoing major changes. The
(re) insurance industry is increasingly exposed to catastrophic losses for which the …

Tail index estimation depends for its accuracy on a precise choice of the sample fraction, ie,
the number of extreme order statistics on which the estimation is based. A complete solution …

This article reviews some of the most important concepts and distributional models that are
used in empirical finance to capture the (almost) ubiquitous stochastic properties of returns …

One of the most important problems involved in the estimation of Pareto indices is the
reduction of bias in case the slowly varying part of the Pareto type model disappears at a …

An abundance of high quality data sets requiring heavy tailed models necessitates reliable
methods of estimating the shape parameter governing the degree of tail heaviness. The Hill …