Most of recent and important algorithms in signal processing (for blind identification or separation, etc) are based on higher order statistics (HOS). And most of them use a criteria based on the fourth order statistics (moment or cumulant). The problem of using HOS consists on the estimation of the statistics. In the literature, three different estimators of the fourth order cumulant were used. In this paper, we show by an experimental study that the performance of these estimators depend on the nature of the real stochastic signal (stationary or non-stationary). We found that when choosing the estimator, one must take in consideration the signal statistical properties.