  The occurrence of successive extreme observations can have an impact on
society. In extreme value theory there are parameters to evaluate the effect of
clustering of high values, such as the extremal index. The estimation of the
extremal index is a recurrent theme in the literature and there are several
methodologies for this purpose. The majority of existing methods depend on two
parameters whose choice affects the performance of the estimators. Here we
consider a new estimator depending only on one of the parameters, thus
contributing to a decrease in the degree of uncertainty. A simulation study
presents motivating results. An application to financial data will also be
presented.
