Estimators of long-memory: Fourier versus wavelets
Files
First author draft
Date
2009-08-01
Authors
Fay, Gilles
Moulines, Eric
Roueff, Francois
Taqqu, Murad S.
Version
First author draft
OA Version
Citation
Gilles Fay, Eric Moulines, Francois Roueff, Murad S Taqqu. 2009. "Estimators of long-memory: Fourier versus wavelets." JOURNAL OF ECONOMETRICS, Volume 151, Issue 2, pp. 159 - 177 (19). https://doi.org/10.1016/j.jeconom.2009.03.005
Abstract
Semi-parametric estimation methods of the long-memory exponent of a time series have been studied in several papers, some applied, others theoretical, some using Fourier methods, others using a wavelet-based technique. In this paper, we compare the Fourier and wavelet approaches to the local regression method and to the local Whittle method. We provide an overview of these methods, describe what has been done and indicate the available results and the conditions under which they hold. We discuss their relative strengths and weaknesses both from a practical and a theoretical perspective. We also include a simulation-based comparison. The software written to support this work is available on demand and we illustrate its use at the end of the paper.