Wavelet transform for log periodogram regression in long memory stochastic volatility model
AbstractWe consider semiparametric log periodogram regression estimation of memory parameter for the latent process in long memory stochastic volatility models. It is known that though widely used among researchers, the Geweke and Porter-Hudak (1983; GPH) LP estimator violates the Gaussian or Martingale assumption, which results in significant negative bias due to the existence of the spectrum of non-Gaussian noise. Through wavelet transform of the squared process, we effectively remove the noise spectrum around zero frequency, and obtain Gaussian-approximate spectral representation at zero frequency. We propose wavelet-based regression estimator, and derive the asymptotic mean squared error and the consistency in line with the asymptotic theory in the long memory literature. Simulation studies show that wavelet-based regression estimation is an effective way in reducing the bias, compared with the GPH estimator
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Econometric Society in its series Econometric Society 2004 Far Eastern Meetings with number 682.
Date of creation: 11 Aug 2004
Date of revision:
Contact details of provider:
Phone: 1 212 998 3820
Fax: 1 212 995 4487
Web page: http://www.econometricsociety.org/pastmeetings.asp
More information through EDIRC
Long memory stochastic volatility; Wavelet transform; Log periodogram regression;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-10-30 (All new papers)
- NEP-ECM-2004-10-30 (Econometrics)
- NEP-ETS-2004-10-30 (Econometric Time Series)
- NEP-FIN-2004-10-30 (Finance)
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.:
- Tanaka, Katsuto, 1999. "The Nonstationary Fractional Unit Root," Econometric Theory, Cambridge University Press, vol. 15(04), pages 549-582, August.
- Katsumi Shimotsu & Peter C.B. Phillips, 2002.
"Exact Local Whittle Estimation of Fractional Integration,"
Economics Discussion Papers
535, University of Essex, Department of Economics.
- Katsumi Shimotsu & Peter C.B. Phillips, 2002. "Exact Local Whittle Estimation of Fractional Integration," Cowles Foundation Discussion Papers 1367, Cowles Foundation for Research in Economics, Yale University, revised Jul 2004.
- Bollerslev, Tim & Wright, Jonathan H., 2000. "Semiparametric estimation of long-memory volatility dependencies: The role of high-frequency data," Journal of Econometrics, Elsevier, vol. 98(1), pages 81-106, September.
- Jin Lee, 2004. "Wavelet transform for regression estimation of non-stationary fractional time series," Econometric Society 2004 North American Summer Meetings 491, Econometric Society.
- Breidt, F. Jay & Crato, Nuno & de Lima, Pedro, 1998. "The detection and estimation of long memory in stochastic volatility," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 325-348.
- Donald W.K. Andrews & Patrik Guggenberger, 2000.
"A Bias-Reduced Log-Periodogram Regression Estimator for the Long-Memory Parameter,"
Cowles Foundation Discussion Papers
1263, Cowles Foundation for Research in Economics, Yale University.
- Donald W. K. Andrews & Patrik Guggenberger, 2003. "A Bias--Reduced Log--Periodogram Regression Estimator for the Long--Memory Parameter," Econometrica, Econometric Society, vol. 71(2), pages 675-712, March.
- Peter C.B. Phillips, 1999.
"Unit Root Log Periodogram Regression,"
Cowles Foundation Discussion Papers
1244, Cowles Foundation for Research in Economics, Yale University.
- Deo, Rohit S. & Hurvich, Clifford M., 2001. "On The Log Periodogram Regression Estimator Of The Memory Parameter In Long Memory Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 17(04), pages 686-710, August.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
If references are entirely missing, you can add them using this form.