IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v37y2010i9p1569-1584.html
   My bibliography  Save this article

ARFIMA processes and outliers: a weighted likelihood approach

Author

Listed:
  • Claudio Agostinelli
  • Luisa Bisaglia

Abstract

In this paper, we consider the problem of robust estimation of the fractional parameter, d, in long memory autoregressive fractionally integrated moving average processes, when two types of outliers, i.e. additive and innovation, are taken into account without knowing their number, position or intensity. The proposed method is a weighted likelihood estimation (WLE) approach for which needed definitions and algorithm are given. By an extensive Monte Carlo simulation study, we compare the performance of the WLE method with the performance of both the approximated maximum likelihood estimation (MLE) and the robust M-estimator proposed by Beran (Statistics for Long-Memory Processes, Chapman & Hall, London, 1994). We find that robustness against the two types of considered outliers can be achieved without loss of efficiency. Moreover, as a byproduct of the procedure, we can classify the suspicious observations in different kinds of outliers. Finally, we apply the proposed methodology to the Nile River annual minima time series.

Suggested Citation

  • Claudio Agostinelli & Luisa Bisaglia, 2010. "ARFIMA processes and outliers: a weighted likelihood approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(9), pages 1569-1584.
    • Handle: RePEc:taf:japsta:v:37:y:2010:i:9:p:1569-1584
    DOI: 10.1080/02664760903093609
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/02664760903093609
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664760903093609?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ledolter, Johannes, 1989. "The effect of additive outliers on the forecasts from ARIMA models," International Journal of Forecasting, Elsevier, vol. 5(2), pages 231-240.
    2. Baillie, Richard T & Chung, Ching-Fan & Tieslau, Margie A, 1996. "Analysing Inflation by the Fractionally Integrated ARFIMA-GARCH Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(1), pages 23-40, Jan.-Feb..
    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. Paulo M.M. Rodrigues & Matei Demetrescu, 2018. "Testing the fractionally integrated hypothesis using M estimation: With an application to stock market volatility," Working Papers w201817, Banco de Portugal, Economics and Research Department.

    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. Doornik, Jurgen A. & Ooms, Marius, 2008. "Multimodality in GARCH regression models," International Journal of Forecasting, Elsevier, vol. 24(3), pages 432-448.
    2. John Barkoulas & Christopher Baum & Mustafa Caglayan, 1999. "Fractional monetary dynamics," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1393-1400.
    3. Karanasos Menelaos & Schurer Stefanie, 2008. "Is the Relationship between Inflation and Its Uncertainty Linear?," German Economic Review, De Gruyter, vol. 9(3), pages 265-286, August.
    4. Broto Carmen & Ruiz Esther, 2009. "Testing for Conditional Heteroscedasticity in the Components of Inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(2), pages 1-30, May.
    5. Berument, Hakan & Nergiz Dincer, N., 2005. "Inflation and inflation uncertainty in the G-7 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 371-379.
    6. Grané, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Kuang‐Liang Chang & Chi‐Wei He, 2010. "Does The Magnitude Of The Effect Of Inflation Uncertainty On Output Growth Depend On The Level Of Inflation?," Manchester School, University of Manchester, vol. 78(2), pages 126-148, March.
    8. Guglielmo Maria Caporale & Hector Carcel & Luis A. Gil-Alana, 2015. "Modelling African inflation rates: nonlinear deterministic terms and long-range dependence," Applied Economics Letters, Taylor & Francis Journals, vol. 22(5), pages 421-424, March.
    9. Russell, Bill & Chowdhury, Rosen Azad, 2013. "Estimating United States Phillips curves with expectations consistent with the statistical process of inflation," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 24-38.
    10. Hassler, Uwe & Marmol, Francesc, 1998. "Fractional cointegrating regressions in the presence of linear time trends," DES - Working Papers. Statistics and Econometrics. WS 9794, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Juan José Echavarría & Enrique López & Martha Misas, 2011. "La persistencia estadística de la inflación en Colombia," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 29(65), pages 224-266, June.
    12. Anari, Ali & Kolari, James, 2016. "Dynamics of interest and inflation rates," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 129-144.
    13. Liu, Yang & Han, Liyan & Xu, Yang, 2021. "The impact of geopolitical uncertainty on energy volatility," International Review of Financial Analysis, Elsevier, vol. 75(C).
    14. H. W. Wayne Yang & Po-Wei Shen & An-Sing Chen, 2020. "Trimming Effects And Momentum Investing," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 14(2), pages 73-87.
    15. Beatriz Catalan & F. Javier Trivez, 2007. "Forecasting volatility in GARCH models with additive outliers," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 591-596.
    16. Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2017. "Does the ARFIMA really shift?," CREATES Research Papers 2017-16, Department of Economics and Business Economics, Aarhus University.
    17. Onali, Enrico & Goddard, John, 2011. "Are European equity markets efficient? New evidence from fractal analysis," International Review of Financial Analysis, Elsevier, vol. 20(2), pages 59-67, April.
    18. Steffen R. Henzel & Malte Rengel, 2017. "Dimensions Of Macroeconomic Uncertainty: A Common Factor Analysis," Economic Inquiry, Western Economic Association International, vol. 55(2), pages 843-877, April.
    19. Dave, Chetan & Sorge, Marco M., 2021. "Equilibrium indeterminacy and sunspot tales," European Economic Review, Elsevier, vol. 140(C).
    20. Emma Iglesias & Garry Phillips, 2005. "Analysing one-month Euro-market interest rates by fractionally integrated models," Applied Financial Economics, Taylor & Francis Journals, vol. 15(2), pages 95-106.

    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:taf:japsta:v:37:y:2010:i:9:p:1569-1584. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.