This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Can GARCH Models Capture Long-Range Dependence?

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
John Maheu (University of Toronto)

Additional information is available for the following registered author(s):

Abstract

This paper investigates if component GARCH models introduced by Engle and Lee(1999) and Ding and Granger(1996) can capture the long-range dependence observed in measures of time-series volatility. Long-range dependence is assessed through the sample autocorrelations, two popular semiparametric estimators of the long-memory parameter, and the parametric fractionally integrated GARCH (FIGARCH) model. Monte Carlo methods are used to characterize the finite sample distributions of these statistics when data are generated from GARCH(1,1), component GARCH and FIGARCH models. For several daily financial return series we find that a two-component GARCH model captures the shape of the autocorrelation function of volatility, and is consistent with long-memory based on semiparametric and parametric estimates. Therefore, GARCH models can in some circumstances account for the long-range dependence found in financial market volatility.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help file. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.bepress.com/cgi/viewcontent.cgi?article=1269&context=snde
File Format: application/pdf
File Function:
Download Restriction: Subscription to the journal may be required to access full texts.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Publisher Info
Article provided by Berkeley Electronic Press in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 9 (2005)
Issue (Month): 4 ()
Pages: 1269-1269
Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Handle: RePEc:bep:sndecm:9:2005:4:1269-1269

Note: oai:bepress:snde-1269
Contact details of provider:
Web page: http://www.bepress.com/snde/

Order Information:
Web: http://www.bepress.com/subscriptions.html

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords: component GARCH FIGARCH fractional integration long-memory

Other versions of this item:

References listed on IDEAS
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.:
  1. Bougerol, Philippe & Picard, Nico, 1992. "Stationarity of Garch processes and of some nonnegative time series," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 115-127. [Downloadable!] (restricted)
  2. Granger, Clive W. J. & Ding, Zhuanxin, 1996. "Varieties of long memory models," Journal of Econometrics, Elsevier, vol. 73(1), pages 61-77, July. [Downloadable!] (restricted)
    Other versions:
  3. Bollerslev, Tim & Ole Mikkelsen, Hans, 1999. "Long-term equity anticipation securities and stock market volatility dynamics," Journal of Econometrics, Elsevier, vol. 92(1), pages 75-99, September. [Downloadable!] (restricted)
  4. Clive W.J. Granger & Namwon Hyung, 1999. "Occasional Structural Breaks and Long Memory," University of California at San Diego, Economics Working Paper Series 99-14, Department of Economics, UC San Diego. [Downloadable!]
  5. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November. [Downloadable!] (restricted)
    Other versions:
  6. Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July. [Downloadable!] (restricted)
    Other versions:
  7. Nelson, Daniel B., 1990. "ARCH models as diffusion approximations," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 7-38. [Downloadable!] (restricted)
  8. Beltratti, Andrea & Morana, Claudio, 1999. "Computing value at risk with high frequency data," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 431-455, December. [Downloadable!] (restricted)
  9. Karanasos, Menelaos, 1999. "The second moment and the autocovariance function of the squared errors of the GARCH model," Journal of Econometrics, Elsevier, vol. 90(1), pages 63-76, May. [Downloadable!] (restricted)
  10. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July. [Downloadable!] (restricted)
  11. Tim Bollerslev & Jeffrey Wooldridge, 1992. "Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances," Econometric Reviews, Taylor and Francis Journals, vol. 11(2), pages 143-172. [Downloadable!] (restricted)
  12. Brunetti, Celso & Gilbert, Christopher L., 2000. "Bivariate FIGARCH and fractional cointegration," Journal of Empirical Finance, Elsevier, vol. 7(5), pages 509-530, December. [Downloadable!] (restricted)
    Other versions:
  13. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September. [Downloadable!] (restricted)
  14. Giraitis, Liudas & Kokoszka, Piotr & Leipus, Remigijus, 2000. "Stationary Arch Models: Dependence Structure And Central Limit Theorem," Econometric Theory, Cambridge University Press, vol. 16(01), pages 3-22, February. [Downloadable!]
  15. 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, July. [Downloadable!]
  16. Gourieroux, Christian & Jasiak, Joann, 2001. "Memory and infrequent breaks," Economics Letters, Elsevier, vol. 70(1), pages 29-41, January. [Downloadable!] (restricted)
  17. Liu, Ming, 2000. "Modeling long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 99(1), pages 139-171, November. [Downloadable!] (restricted)
  18. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April. [Downloadable!] (restricted)
  19. 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. [Downloadable!] (restricted)
  20. Hwang, Y., 2001. "Asymmetric long memory GARCH in exchange return," Economics Letters, Elsevier, vol. 73(1), pages 1-5, October. [Downloadable!] (restricted)
  21. He, Changli & Ter svirta, Timo, 1999. "FOURTH MOMENT STRUCTURE OF THE GARCH(p,q) PROCESS," Econometric Theory, Cambridge University Press, vol. 15(06), pages 824-846, December. [Downloadable!]
  22. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October. [Downloadable!] (restricted)
  23. Robert Engle & Tim Bollerslev, 1986. "Modelling the persistence of conditional variances," Econometric Reviews, Taylor and Francis Journals, vol. 5(1), pages 1-50. [Downloadable!] (restricted)
  24. 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. [Downloadable!] (restricted)
  25. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July. [Downloadable!] (restricted)
Full references

Cited by:
(explanations, 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.)

  1. Peter Christoffersen & Kris Jacobs & Chayawat Ornthanalai & Yintian Wang, 2008. "Option Valuation with Long-run and Short-run Volatility Components," CREATES Research Papers 2008-11, School of Economics and Management, University of Aarhus. [Downloadable!]
    Other versions:
  2. Peter Christoffersen & Kris Dorion & Yintian Wang, 2008. "Volatility Components, Affine Restrictions and Non-Normal Innovations," CREATES Research Papers 2008-10, School of Economics and Management, University of Aarhus. [Downloadable!]
  3. Markus Haas, 2007. "Volatility Components and Long Memory-Effects Revisited," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 11(2), pages 1411-1411. [Downloadable!] (restricted)
  4. Luc, BAUWENS & G., STORTI, 2007. "A Component GARCH Model with Time Varying Weights," Université catholique de Louvain, Département des Sciences Economiques Working Paper 2007012, Université catholique de Louvain, Département des Sciences Economiques. [Downloadable!]
    Other versions:
Statistics
Access and download statistics

Did you know? You can use IDEAS to provide links to papers and articles in your course syllabus.

This page was last updated on 2008-11-19.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.