The Empirical Properties of Some Popular Estimators of Long Memory Processes
AbstractWe present the results of a simulation study into the properties of 12 different estimators of the Hurst parameter, H, or the fractional integration parameter, d, in long memory time series. We compare and contrast their performance on simulated Fractional Gaussian Noises and fractionally integrated series with lengths between 100 and 10,000 data points and H values between 0.55 and 0.90 or d values between 0.05 and 0.40. We apply all 12 estimators to the Campito Mountain data and estimate the accuracy of their estimates using the Beran goodness of t test for long memory time series.
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Bibliographic InfoPaper provided by University of Canterbury, Department of Economics and Finance in its series Working Papers in Economics with number 08/13.
Length: 17 pages
Date of creation: 26 Jun 2008
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Strong dependence; global dependence; long range dependence; Hurst parameter estimators;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: 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-2008-07-30 (All new papers)
- NEP-ECM-2008-07-30 (Econometrics)
- NEP-ETS-2008-07-30 (Econometric Time Series)
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- Baillie, Richard T. & Chung, Sang-Kuck, 2002. "Modeling and forecasting from trend-stationary long memory models with applications to climatology," International Journal of Forecasting, Elsevier, vol. 18(2), pages 215-226.
- Deo, Rohit S. & Chen, Willa W., 2000. "On the integral of the squared periodogram," Stochastic Processes and their Applications, Elsevier, vol. 85(1), pages 159-176, January.
- Giraitis, Liudas & Robinson, Peter M. & Surgailis, Donatas, 1999. "Variance-type estimation of long memory," Stochastic Processes and their Applications, Elsevier, vol. 80(1), pages 1-24, March.
- Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
- Lobato, I. & Robinson, P. M., 1996. "Averaged periodogram estimation of long memory," Journal of Econometrics, Elsevier, vol. 73(1), pages 303-324, July.
- Mark J. Jensen, 1997.
"Using Wavelets to Obtain a Consistent Ordinary Least Squares Estimator of the Long Memory Parameter,"
- Jensen, Mark J, 1999. "Using wavelets to obtain a consistent ordinary least squares estimator of the long-memory parameter," MPRA Paper 39152, University Library of Munich, Germany.
- Michael McAleer & Les Oxley & Felix Chan, 2013.
"Modelling and Simulation: An Overview,"
Documentos del Instituto Complutense de AnÃ¡lisis EconÃ³mico
2013-16, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales.
- Michael McAleer & Felix Chan & Les Oxley, 2013. "Modelling and Simulation: An Overview," Tinbergen Institute Discussion Papers 13-069/III, Tinbergen Institute.
- McAleer, M.J. & Chan, F. & Oxley, L., 2013. "Modelling and Simulation: An Overview," Econometric Institute Research Papers EI2013-19, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Michael McAleer & Felix Chan & Les Oxley, 2013. "Modelling and Simulation: An Overview," KIER Working Papers 865, Kyoto University, Institute of Economic Research.
- Michael McAleer & Felix Chan & Les Oxley, 2013. "Modeling and Simulation: An Overview," Working Papers in Economics 13/18, University of Canterbury, Department of Economics and Finance.
- David Greasley & Les Oxley, 2010.
"Cliometrics And Time Series Econometrics: Some Theory And Applications,"
Journal of Economic Surveys,
Wiley Blackwell, vol. 24(5), pages 970-1042, December.
- David Grreasley, 2010. "Cliometrics and Time Series Econometrics: Some Theory and Applications," Working Papers in Economics 10/56, University of Canterbury, Department of Economics and Finance.
- Les Oxley & Chris Price & William Rea & Marco Reale, 2008. "A New Procedure to Test for H Self-Similarity," Working Papers in Economics 08/16, University of Canterbury, Department of Economics and Finance.
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