IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/31841.html

Forecasting an ARIMA (0,2,1) using the random walk model with drift

Author

Listed:
  • Halkos, George
  • Kevork, Ilias

Abstract

In this paper we show that the random walk model with drift behaves like an ARIMA (0,2,1) when its parameter θ is greater but close to –1. Using the random walk for predicting future values of an ARIMA (0,2,1) process, we find out that when θ is not so close to –1, the performance of the prediction interval for the period forecast is not satisfactory. Particularly, for large, the achieved coverage, namely, the probability the prediction interval to include the future value is quite low. Even in the cases of large samples and small , although the random walk coverage approaches that of the ARIMA, the random walk produces wider prediction intervals. This picture changes when we forecast ARIMA (0,2,1) values for θ close to –1. The random walk should be preferred as it produces on average narrower confidence intervals, and its coverage is almost the same with the nominal coverage of the ARIMA (0,2,1).

Suggested Citation

  • Halkos, George & Kevork, Ilias, 2006. "Forecasting an ARIMA (0,2,1) using the random walk model with drift," MPRA Paper 31841, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:31841
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/31841/1/MPRA_paper_31841.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    Full references (including those not matched with items on IDEAS)

    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. Bierens, H.J. & Broersma, L., 1991. "The relation between unemployment and interest rate : some international evidence," Serie Research Memoranda 0112, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    2. Nicholas Taylor, 1998. "Precious metals and inflation," Applied Financial Economics, Taylor & Francis Journals, vol. 8(2), pages 201-210.
    3. Apostolos Serletis & Ricardo Rangel-Ruiz, 2007. "Testing for Common Features in North American Energy Markets," World Scientific Book Chapters, in: Quantitative And Empirical Analysis Of Energy Markets, chapter 14, pages 172-187, World Scientific Publishing Co. Pte. Ltd..
    4. Kleibergen, F., 1996. "Reduced Rank of Regression Using Generalized Method of Moments Estimators," Other publications TiSEM 5caf1c0c-d988-4184-acf7-d, Tilburg University, School of Economics and Management.
    5. Gebre-Mariam, Yohannes Kebede, 2011. "Testing for unit roots, causality, cointegration, and efficiency: The case of the northwest US natural gas market," Energy, Elsevier, vol. 36(5), pages 3489-3500.
    6. Ireland, Peter N., 1999. "Does the time-consistency problem explain the behavior of inflation in the United States?," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 279-291, October.
    7. Isabel Cortés-Jiménez & Manuel Artís, 2005. "The role of the tourism sector in economic development - Lessons from the Spanish experience," ERSA conference papers ersa05p488, European Regional Science Association.
    8. Hondroyiannis, George & Papapetrou, Evangelia, 2001. "Demographic changes, labor effort and economic growth: empirical evidence from Greece," Journal of Policy Modeling, Elsevier, vol. 23(2), pages 169-188, February.
    9. Nadiezhda de la Uz, 2002. "La hipótesis de martingala en el mercado bursátil mexicano," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 17(1), pages 91-127.
    10. João Sousa Andrade, 2006. "Mobilidade do Capital e Sustentabilidade Externa: uma aplicação da tese de F-H a Portugal (1910-2004)," GEMF Working Papers 2006-04, GEMF, Faculty of Economics, University of Coimbra.
    11. Banu Demirhan, 2016. "Financial Development and Investment Amount Nexus: A Case Study of Turkey," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 6(3), pages 127-134, March.
    12. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    13. Eleni Constantinou & Robert Georgiades & Avo Kazandjian & George Kouretas, 2005. "Mean and variance causality between the Cyprus Stock Exchange and major equity markets," Working Papers 0501, University of Crete, Department of Economics.
    14. Geoffrey Booth, G. & Ciner, Cetin, 1997. "International transmission on information in corn futures markets," Journal of Multinational Financial Management, Elsevier, vol. 7(3), pages 175-187, October.
    15. Asongu, Simplice A. & Folarin, Oludele E. & Biekpe, Nicholas, 2019. "The long run stability of money demand in the proposed West African monetary union," Research in International Business and Finance, Elsevier, vol. 48(C), pages 483-495.
    16. Haldrup, Niels & Nielsen, Morten Orregaard, 2006. "A regime switching long memory model for electricity prices," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 349-376.
    17. Tetsushi Homma & Yoshiro Tsutsui & Uri Benzion, 2005. "Exchange rate and stock prices in Japan," Applied Financial Economics, Taylor & Francis Journals, vol. 15(7), pages 469-478.
    18. Arai, Yoichi, 2016. "Testing For Linearity In Regressions With I(1) Processes," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 57(1), pages 111-138, June.
    19. Alexander S. Sangare, 2005. "Efficience des marchés : un siècle après Bachelier," Revue d'Économie Financière, Programme National Persée, vol. 81(4), pages 107-132.
    20. Vicente Meneu & Hipòlit Torró, 2003. "Asymmetric covariance in spot‐futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(11), pages 1019-1046, November.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • 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:pra:mprapa:31841. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.