IDEAS home Printed from https://ideas.repec.org/p/hal/pseptp/hal-00486655.html
   My bibliography  Save this paper

Testing Fractional Order of Long Memory Processes: A Monte Carlo Study

Author

Listed:
  • Laurent Ferrara

    (DGEI-DAMEP - Banque de France)

  • Dominique Guegan

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Zhiping Lu

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, ECNU - ECNU - East China Normal University [Shangaï])

Abstract

Testing the fractionally integrated order of seasonal and nonseasonal unit roots is quite important for the economic and financial time series modeling. In this article, the widely used Robinson's (1994) test is applied to various well-known long memory models. Via Monte Carlo experiments, we study and compare the performances of this test using several sample sizes.

Suggested Citation

  • Laurent Ferrara & Dominique Guegan & Zhiping Lu, 2010. "Testing Fractional Order of Long Memory Processes: A Monte Carlo Study," PSE-Ecole d'économie de Paris (Postprint) hal-00486655, HAL.
  • Handle: RePEc:hal:pseptp:hal-00486655
    DOI: 10.1080/03610911003646381
    Note: View the original document on HAL open archive server: https://hal.science/hal-00486655
    as

    Download full text from publisher

    File URL: https://hal.science/hal-00486655/document
    Download Restriction: no

    File URL: https://libkey.io/10.1080/03610911003646381?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Diongue, Abdou Kâ & Guégan, Dominique & Vignal, Bertrand, 2009. "Forecasting electricity spot market prices with a k-factor GIGARCH process," Applied Energy, Elsevier, vol. 86(4), pages 505-510, April.
    2. Ray, Bonnie K., 1993. "Long-range forecasting of IBM product revenues using a seasonal fractionally differenced ARMA model," International Journal of Forecasting, Elsevier, vol. 9(2), pages 255-269, August.
    3. Ferrara, Laurent & Guegan, Dominique, 2001. "Forecasting with k-Factor Gegenbauer Processes: Theory and Applications," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(8), pages 581-601, December.
    4. Josu Arteche & Peter M. Robinson, 2000. "Semiparametric Inference in Seasonal and Cyclical Long Memory Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 21(1), pages 1-25, January.
    5. Franses, Philip Hans & Ooms, Marius, 1997. "A periodic long-memory model for quarterly UK inflation," International Journal of Forecasting, Elsevier, vol. 13(1), pages 117-126, March.
    6. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
    7. Vivien Guiraud & Michel Terraza & Olivier Darné, 2004. "Forecasts of the seasonal fractional integrated series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(1), pages 1-17.
    8. 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.
    9. Arteche, Josu & Robinson, Peter M., 1998. "Seasonal and cyclical long memory," LSE Research Online Documents on Economics 2241, London School of Economics and Political Science, LSE Library.
    10. Wayne A. Woodward & Q. C. Cheng & H. L. Gray, 1998. "A k‐Factor GARMA Long‐memory Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 19(4), pages 485-504, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dominique Guegan & Zhiping Lu, 2010. "Testing unit roots and long range dependence of foreign exchange," Post-Print halshs-00505117, HAL.
    2. Laurent Ferrara & Dominique Guegan, 2008. "Business surveys modelling with Seasonal-Cyclical Long Memory models," Post-Print halshs-00283710, HAL.
    3. Laurent Ferrara & Dominique Guégan, 2008. "Business surveys modelling with Seasonal-Cyclical Long Memory models," Economics Bulletin, AccessEcon, vol. 3(29), pages 1-10.
    4. repec:ebl:ecbull:v:3:y:2008:i:29:p:1-10 is not listed on IDEAS
    5. Laurent Ferrara & Dominique Guegan, 2008. "Business surveys modelling with Seasonal-Cyclical Long Memory models," Post-Print halshs-00277379, HAL.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Laurent Ferrara & Dominique Guégan, 2008. "Business surveys modelling with Seasonal-Cyclical Long Memory models," Economics Bulletin, AccessEcon, vol. 3(29), pages 1-10.
    2. Laurent Ferrara & Dominique Guegan & Zhiping Lu, 2008. "Testing fractional order of long memory processes : a Monte Carlo study," Post-Print halshs-00259193, HAL.
    3. Dominique Guegan & Laurent Ferrara, 2008. "Fractional and seasonal filtering," PSE-Ecole d'économie de Paris (Postprint) halshs-00646178, HAL.
    4. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    5. Laurent Ferrara & Dominique Guegan, 2006. "Fractional seasonality: Models and Application to Economic Activity in the Euro Area," Post-Print halshs-00185370, HAL.
    6. Soares, Lacir Jorge & Souza, Leonardo Rocha, 2006. "Forecasting electricity demand using generalized long memory," International Journal of Forecasting, Elsevier, vol. 22(1), pages 17-28.
    7. repec:ebl:ecbull:v:3:y:2008:i:29:p:1-10 is not listed on IDEAS
    8. Rocha Souza, Leonardo & Jorge Soares, Lacir, 2007. "Electricity rationing and public response," Energy Economics, Elsevier, vol. 29(2), pages 296-311, March.
    9. Josu Arteche, 2012. "Standard and seasonal long memory in volatility: an application to Spanish inflation," Empirical Economics, Springer, vol. 42(3), pages 693-712, June.
    10. Dominique Guegan & Zhiping Lu, 2009. "Wavelet Method for Locally Stationary Seasonal Long Memory Processes," Post-Print halshs-00375531, HAL.
    11. Dominique Guegan, 2003. "A prospective study of the k-factor Gegenbauer processes with heteroscedastic errors and an application to inflation rates," Post-Print halshs-00201314, HAL.
    12. Ana Pérez & Esther Ruiz, 2002. "Modelos de memoria larga para series económicas y financieras," Investigaciones Economicas, Fundación SEPI, vol. 26(3), pages 395-445, September.
    13. Laurent Ferrara & Dominique Guegan, 2008. "Business surveys modelling with Seasonal-Cyclical Long Memory models," Post-Print halshs-00283710, HAL.
    14. Souza, Leonardo Rocha & Soares, Lacir Jorge, 2003. "Forecasting electricity load demand: analysis of the 2001 rationing period in Brazil," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 491, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    15. Laurent Ferrara & Dominique Guegan, 2008. "Business surveys modelling with Seasonal-Cyclical Long Memory models," Post-Print halshs-00277379, HAL.
    16. Arteche, Josu, 2004. "Gaussian semiparametric estimation in long memory in stochastic volatility and signal plus noise models," Journal of Econometrics, Elsevier, vol. 119(1), pages 131-154, March.
    17. Nicholas Apergis & Andrea Mervar & James E. Payne, 2017. "Forecasting disaggregated tourist arrivals in Croatia," Tourism Economics, , vol. 23(1), pages 78-98, February.
    18. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    19. Beaumont, Paul & Smallwood, Aaron, 2019. "Inference for likelihood-based estimators of generalized long-memory processes," MPRA Paper 96313, University Library of Munich, Germany.
    20. Voges, Michelle & Leschinski, Christian & Sibbertsen, Philipp, 2017. "Seasonal long memory in intraday volatility and trading volume of Dow Jones stocks," Hannover Economic Papers (HEP) dp-599, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    21. Guglielmo Maria Caporale & Juncal Cuñado & Luis A. Gil-Alana, 2013. "Modelling long-run trends and cycles in financial time series data," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(3), pages 405-421, May.

    More about this item

    Keywords

    Long memory processes; test; Monte Carlo simulations; Processus de longue mémoire; simulation de Monte Carlo;
    All these keywords.

    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; Diffusion Processes

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:pseptp:hal-00486655. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Caroline Bauer (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.