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! ]

Changing-regime volatility : A fractionally integrated SETAR model

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Anne Peguin-Feissolle () (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - Université de la Méditerranée - Aix-Marseille II - Université Paul Cézanne - Aix-Marseille III - Ecole des Hautes Etudes en Sciences Sociales - CNRS : UMR6579)
Gilles Dufrénot () (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - Université de la Méditerranée - Aix-Marseille II - Université Paul Cézanne - Aix-Marseille III - Ecole des Hautes Etudes en Sciences Sociales - CNRS : UMR6579, DEFI - Centre de Recherche en Developpement Economique et Finance Internationale - Centre de Recherche en Developpement Economique et Finance Internationale)
Dominique Guegan () (ENS - Ecole Normale Supérieure de Cachan - Ecole Normale Supérieure de Cachan)

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

Abstract

This paper presents a 2-regime SETAR model with different longmemory processes in both regimes. We briefly present the memory properties of this model and propose an estimation method. Such a process is applied to the absolute and squared returns of five stock indices. A comparison with simple ARFIMA models is made using some forecastibility criteria. Our empirical results suggest that our model offers an interesting alternative competing framework to describe the persistent dynamics in modeling the returns.

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 page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://halshs.archives-ouvertes.fr/docs/00/41/05/40/PDF/2006-32.pdf
File Format: application/pdf
File Function:
Download Restriction: no
File URL: http://halshs.archives-ouvertes.fr/docs/00/41/05/40/PDF/2006-32s.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by HAL in its series Working Papers with number halshs-00410540_v1.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 2006
Date of revision:
Handle: RePEc:hal:wpaper:halshs-00410540_v1

Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00410540/en/
Contact details of provider:
Web page: http://hal.archives-ouvertes.fr/

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

Related research
Keywords: SETAR - Long-memory - Stock indices - Forecasting;

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. A. Ronald Gallant & Chien-Te Hsu & George Tauchen, 1999. "Using Daily Range Data To Calibrate Volatility Diffusions And Extract The Forward Integrated Variance," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 617-631, November. [Downloadable!] (restricted)
    Other versions:
  2. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    Other versions:
  3. Geetesh Bhardwaj & Norman Swanson, 2004. "An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series," Departmental Working Papers 200422, Rutgers University, Department of Economics. [Downloadable!]
    Other versions:
  4. Coakley, Jerry & Fuertes, Ana-Maria & Perez, Maria-Teresa, 2003. "Numerical issues in threshold autoregressive modeling of time series," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11-12), pages 2219-2242, September. [Downloadable!] (restricted)
    Other versions:
  5. Morana, Claudio & Beltratti, Andrea, 2004. "Structural change and long-range dependence in volatility of exchange rates: either, neither or both?," Journal of Empirical Finance, Elsevier, vol. 11(5), pages 629-658, December. [Downloadable!] (restricted)
  6. So, Mike K P & Lam, K & Li, W K, 1998. "A Stochastic Volatility Model with Markov Switching," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 244-53, April.
  7. Lobato, Ignacio N & Savin, N E, 1998. "Real and Spurious Long-Memory Properties of Stock-Market Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 261-68, July.
    Other versions:
  8. James D. Hamilton & Gang Lin, 1996. "Stock Market Volatility and The Business Cycle," University of California at San Diego, Economics Working Paper Series 96-18, Department of Economics, UC San Diego. [Downloadable!]
    Other versions:
  9. Morana, Claudio & Beltratti, Andrea, 2002. "The effects of the introduction of the euro on the volatility of European stock markets," Journal of Banking & Finance, Elsevier, vol. 26(10), pages 2047-2064, October. [Downloadable!] (restricted)
  10. Hassler, Uwe & Wolters, Jurgen, 1995. "Long Memory in Inflation Rates: International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 37-45, January.
  11. Beltratti, A. & Morana, C., 2006. "Breaks and persistency: macroeconomic causes of stock market volatility," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 151-177. [Downloadable!] (restricted)
  12. Cathy W. S. Chen & Mike K. P. So, 2003. "Subset threshold autoregression," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 49-66. [Downloadable!]
  13. Lobato, Ignacio N & Velasco, Carlos, 2000. "Long Memory in Stock-Market Trading Volume," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 410-27, October.
  14. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333. [Downloadable!] (restricted)
    Other versions:
  15. 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)
  16. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
    Other versions:
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. Mohamed Boutahar & Gilles Dufrénot & Anne Péguin-Feissolle, 2008. "A Simple Fractionally Integrated Model with a Time-varying Long Memory Parameter d t ," Computational Economics, Springer, vol. 31(3), pages 225-241, April. [Downloadable!] (restricted)
Statistics
Access and download statistics

Did you know? IDEAS indexes over 800000 items of research in Economics alone.

This page was last updated on 2009-11-28.

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.