  One of the main goal of extreme value analysis is to estimate the probability
of rare events given a sample from an unknown distribution. The upper tail
behavior of this distribution is described by the extreme value index. We
present a new estimator of the extreme value index adapted to any domain of
attraction. Its construction is similar to the one of Pickands' estimator. its
weak consistency and its asymptotic distribution are established and a bias
reduction method is proposed. Our estimator is compared with classical extreme
value index estimators through a simulation study.
