A new bootstrap approach for Gaussian long memory time series.

In this work we introduce a new bootstrap approach based on a result of Ramsey (1974) and on the Durbin-Levinson algorithm to obtain surrogate series from linear Gaussian processes with long range dependence. First we investigate properties of this type of bootstrap, then we apply the method to semi-parametric estimators of the long memory parameter. We find out that the performance of our bootstrap procedure is superior, in terms of MSE, to other established approaches.