IDEAS home Printed from https://ideas.repec.org/p/nbr/nberte/0090.html
   My bibliography  Save this paper

Spectral Based Testing of the Martingale Hypothesis

Author

Listed:
  • Steven N. Durlauf

Abstract

This paper proposes a method of testing whether a time series is a martingale. The procedure develops an asymptotic theory for the shape of the spectral distribution function of the first differences. Under the null hypothesis, this shape should be a diagonal line. several tests are developed which determine whether the deviation of the sample spectral distribution function from a diagonal line, when treated as an element of a function space, is too erratic to be attributable to sampling error. These tests are consistent against all moving average alternatives. The testing procedure possesses the additional advantage that it eliminates discretion in choosing a particular H[sub 1] by the researcher and therefore guards against data mining, The tests may further be adjusted to analyze subsets of frequencies in isolation, which can enhance power against particular alternatives. Application of the test to stock prices finds some evidence against the random walk theory.

Suggested Citation

  • Steven N. Durlauf, 1992. "Spectral Based Testing of the Martingale Hypothesis," NBER Technical Working Papers 0090, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberte:0090
    Note: EFG
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/t0090.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hall, Robert E, 1978. "Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 86(6), pages 971-987, December.
    2. Bizer, David S. & Durlauf, Steven N., 1990. "Testing the positive theory of government finance," Journal of Monetary Economics, Elsevier, vol. 26(1), pages 123-141, August.
    3. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    4. Campbell, John Y & Mankiw, N Gregory, 1987. "Permanent and Transitory Components in Macroeconomic Fluctuations," American Economic Review, American Economic Association, vol. 77(2), pages 111-117, May.
    5. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
    6. Robert J. Barro, 1981. "On the Predictability of Tax-Rate Changes," NBER Working Papers 0636, National Bureau of Economic Research, Inc.
    7. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    8. Poterba, James M. & Summers, Lawrence H., 1988. "Mean reversion in stock prices : Evidence and Implications," Journal of Financial Economics, Elsevier, vol. 22(1), pages 27-59, October.
    9. Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
    10. Steven N. Durlauf, 1989. "Output Persistence, Economic Structure, and the Choice of Stabilization Policy," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 20(2), pages 69-136.
    11. 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. António Portugal Duarte & João Sousa Andrade & Adelaide Duarte, 2009. "Exchange Rate Mean Reversion within a Target Zone: Evidence from a Country on the Periphery of the ERM," GEMF Working Papers 2009-15, GEMF, Faculty of Economics, University of Coimbra.
    2. Cribari-Neto, Francisco, 1996. "On time series econometrics," The Quarterly Review of Economics and Finance, Elsevier, vol. 36(Supplemen), pages 37-60.
    3. Patrick A. Groenendijk & André Lucas & Casper G. de Vries, 1998. "A Hybrid Joint Moment Ratio Test for Financial Time Series," Tinbergen Institute Discussion Papers 98-104/2, Tinbergen Institute.
    4. Cosme Vodounou, 1998. "Inférence fondée sur les statistiques des rendements de long terme," CIRANO Working Papers 98s-20, CIRANO.
    5. Javier León & Carlos Oliva, 1992. "Componente no Estacionario y la Paridad del Poder de Compra en 12 Países Latinoamericanos," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 29(88), pages 481-504.
    6. Surajit Deb, 2003. "Terms of Trade and Supply Response of Indian Agriculture: Analysis in Cointegration Framework," Working papers 115, Centre for Development Economics, Delhi School of Economics.
    7. Eric Hillebrand, 2003. "The Effects of Japanese Foreign Exchange Intervention: GARCH Estimation and Change Point Detection," Departmental Working Papers 2003-10, Department of Economics, Louisiana State University.
    8. Tim Bollerslev & Robert J. Hodrick, 1992. "Financial Market Efficiency Tests," NBER Working Papers 4108, National Bureau of Economic Research, Inc.
    9. Gourieroux, Christian & Jasiak, Joann, 2019. "Robust analysis of the martingale hypothesis," Econometrics and Statistics, Elsevier, vol. 9(C), pages 17-41.
    10. Ricardo Reis, 2009. "The Time-Series Properties of Aggregate Consumption: Implications for the Costs of Fluctuations," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 722-753, June.
    11. Peter C. B. Phillips & Sainan Jin, 2014. "Testing the Martingale Hypothesis," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 537-554, October.
    12. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    13. Matthew Richardson & James H. Stock, 1990. "Drawing Inferences From Statistics Based on Multi-Year Asset Returns," NBER Working Papers 3335, National Bureau of Economic Research, Inc.
    14. Amélie Charles & Olivier Darné, 2009. "Variance‐Ratio Tests Of Random Walk: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 23(3), pages 503-527, July.
    15. Juncal Cunado & Luis A. Gil-Alana & Fernando Pérez de Gracia, 2002. "Is the US Fiscal Deficit Sustainable? A Fractionally Integrated and Cointegrated Approach," Faculty Working Papers 02/02, School of Economics and Business Administration, University of Navarra.
    16. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know about Unit Roots," NBER Chapters, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220, National Bureau of Economic Research, Inc.
    17. Choi, In, 1999. "Testing the Random Walk Hypothesis for Real Exchange Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(3), pages 293-308, May-June.
    18. Peter C.B. Phillips & Sam Ouliaris & Joon Y. Park, 1988. "Testing for a Unit Root in the Presence of a Maintained Trend," Cowles Foundation Discussion Papers 880, Cowles Foundation for Research in Economics, Yale University.
    19. Noor Ghazali & Shamshubariah Ramlee, 2003. "A long memory test of the long-run Fisher effect in the G7 countries," Applied Financial Economics, Taylor & Francis Journals, vol. 13(10), pages 763-769.
    20. Takatoshi Ito & V. Vance Roley, 1988. "Intraday Yen/Dollar Exchange Rate Movements: News or Noise?," NBER Working Papers 2703, National Bureau of Economic Research, Inc.

    More about this item

    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:nbr:nberte:0090. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.