2008/12/22 by Christian Y. Robert, Johan Segers, Robert, Christian Y. +3
Economics, Econometrics and Finance · Mathematics · #Financial Risk and Volatility Modeling #Stochastic processes and financial applications #Advanced Statistical Methods and Models
paper · doi:10.48550/arxiv.0812.4233
In extreme value statistics for stationary sequences, blocks estimators are usually constructed by using disjoint blocks because exceedances over high thresholds of different blocks can be assumed asymptotically independent. In this paper we focus on the estimation of the extremal index which measures the degree of clustering of extremes. We consider disjoint and sliding blocks estimators and compare their asymptotic properties. In particular we show that the sliding blocks estimator is more efficient than the disjoint version and has a smaller asymptotic bias. Moreover we propose a method to reduce its bias when considering sufficiently large block sizes.