Test for long memory processes. A bootstrap approach
AbstractMany time series in diverse fields have been found to exhibit long memory. This paper analyzes the behavior of some of the most used tests for long memory: the R/S or rescaled R/S, the GPH (Geweke and Porter-Hudak) and the DFA (Detrended Fluctuation Analysis). Some of these tests exhibit size distortions in small-samples. It is well known that the bootstrap procedure may correct this fact. In this paper, size and power for those tests, for finite samples and different distributions such as normal, uniform and log-normal are investigated. In the case of short memory process, such as AR, MA and ARCH and long memory such as ARFIMA, p-values are calculated using the post-blackening, moving block bootstrap. The Monte Carlo studies suggest that the bootstrap critical values perform better. The results are applied to financial return time series.
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2004 with number 111.
Date of creation: 11 Aug 2004
Date of revision:
Long memory; bootstrap; p-value; size correction; Monte Carlo;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-08-16 (All new papers)
- NEP-ECM-2004-08-16 (Econometrics)
- NEP-ETS-2004-08-16 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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3014-89., Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Andersson, Michael K. & Gredenhoff, Mikael P., 1997. "Bootstrap Testing for Fractional Integration," Working Paper Series in Economics and Finance 188, Stockholm School of Economics.
- Davidson, R. & Mackinnon, J.G., 1996.
"The Size Distorsion of Bootstrap Tests,"
96a15, Universite Aix-Marseille III.
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