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Testing fractional order of long memory processes: a Monte Carlo study

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Abstract

Testing the fractionally integrated order of seasonal and non-seasonal unit roots is quite important for the economic and financial time series modelling. In this paper, Robinson test (1994) 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, 2008. "Testing fractional order of long memory processes: a Monte Carlo study," Documents de travail du Centre d'Economie de la Sorbonne b08012, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Handle: RePEc:mse:cesdoc:b08012
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    1. 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.
    2. 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.
    3. 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.
    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. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
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    Cited by:

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

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    More about this item

    Keywords

    Long memory processes; test; Monte Carlo simulations;
    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

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