IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-10-00018.html
   My bibliography  Save this article

An examination of the stability of short-run Canadian stock predictability

Author

Listed:
  • Ryan Compton

    () (University of Manitoba)

  • Syeed Khan

    () (University of Manitoba)

Abstract

Using monthly data from 1975-2001, we consider the stability of bivariate and multivariate models for short run in-sample predictability of Canadian stock returns. We test for model stability using a range of tests including the Andrews SupF statistic, Bai subsample procedure, and Bai and Perron sequential SupF procedure. We find evidence of instability in two of our nine bivariate cases considered as well as our preferred multivariate model. When estimated to account for these breaks, we find the degree and direction of predictability can change markedly.

Suggested Citation

  • Ryan Compton & Syeed Khan, 2010. "An examination of the stability of short-run Canadian stock predictability," Economics Bulletin, AccessEcon, vol. 30(2), pages 1293-1306.
  • Handle: RePEc:ebl:ecbull:eb-10-00018
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2010/Volume30/EB-10-V30-I2-P121.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," Review of Financial Studies, Society for Financial Studies, pages 1455-1508.
    3. Todd E. Clark, 2004. "Can out-of-sample forecast comparisons help prevent overfitting?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(2), pages 115-139.
    4. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    5. Hansen, Bruce E., 2000. "Testing for structural change in conditional models," Journal of Econometrics, Elsevier, vol. 97(1), pages 93-115, July.
    6. Goncalves, Silvia & Kilian, Lutz, 2004. "Bootstrapping autoregressions with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, pages 89-120.
    7. Rapach, David E. & Wohar, Mark E. & Rangvid, Jesper, 2005. "Macro variables and international stock return predictability," International Journal of Forecasting, Elsevier, vol. 21(1), pages 137-166.
    8. Adjaoud, Fodil & Rahman, Abdul, 1996. "A note on the temporal variability of Canadian financial services stock returns," Journal of Banking & Finance, Elsevier, vol. 20(1), pages 165-177, January.
    9. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, pages 1383-1414.
    10. Bwo-Nung Huang & Chin-Wei Yang, 2004. "Industrial output and stock price revisited: an application of the multivariate indirect causality model," Manchester School, University of Manchester, vol. 72(3), pages 347-362, June.
    11. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    12. J. Benson Durham, 2001. "The effect of monetary policy on monthly and quarterly stock market returns: cross-country evidence and sensitivity analyses," Finance and Economics Discussion Series 2001-42, Board of Governors of the Federal Reserve System (U.S.).
    13. David E. Rapach & Mark E. Wohar, 2006. "Structural Breaks and Predictive Regression Models of Aggregate U.S. Stock Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(2), pages 238-274.
    14. Giannetti, A., 2007. "The short term predictive ability of earnings-price ratios: The recent evidence (1994-2003)," The Quarterly Review of Economics and Finance, Elsevier, vol. 47(1), pages 26-39, March.
    15. Pesaran, M. Hashem & Timmermann, Allan, 2002. "Market timing and return prediction under model instability," Journal of Empirical Finance, Elsevier, pages 495-510.
    16. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", pages 125-132.
    17. Chan, Louis K. C. & Karceski, Jason & Lakonishok, Josef, 1998. "The Risk and Return from Factors," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(02), pages 159-188, June.
    18. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    19. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    20. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
    21. Atsushi Inoue & Lutz Kilian, 2005. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," Econometric Reviews, Taylor & Francis Journals, vol. 23(4), pages 371-402.
    22. Mark J. Flannery & Aris A. Protopapadakis, 2002. "Macroeconomic Factors Do Influence Aggregate Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 15(3), pages 751-782.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    predictive regression models; structural breaks; real stock returns;

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

    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:ebl:ecbull:eb-10-00018. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (John P. Conley). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.