IDEAS home Printed from https://ideas.repec.org/a/tpr/restat/v79y1997i2p176-183.html
   My bibliography  Save this article

The Predictability Of Stock Returns: A Cross-Sectional Simulation

Author

Listed:
  • Zsuzsanna Fluck
  • Burton G. Malkiel
  • Richard E. Quandt

Abstract

This paper investigates whether predictable patterns that previous empirical work in finance have isolated appear to be persistent and exploitable by portfolio managers. On a sample that is free from survivorship bias we construct a test wherein we simulate the purchases and sales an investor would undertake to exploit the predictable patterns, charging the appropriate transaction costs for buying and selling and using only publicly available information at the time of decision making. We restrict investment to large companies only to assure that the full cost of transactions is properly accounted for. We confirmed on our sample that contrarian strategies yield sizable excess returns after adjusting for risk, as measured by beta. Using analysts' estimates of long - term growth we construct a test of the Lakonishok, Shleifer, and Vishny (1994) hypothesis. We cannot reject the hypothesis that neither the low - expected - growth portfolio nor the high - expected - growth portfolio yielded any risk - adjusted excess return over the 1980s. Our finding suggests that the superior performance of contrarian strategies cannot adequately be explained by the superior performance of stocks with low expected growth. © 1997 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology

Suggested Citation

  • Zsuzsanna Fluck & Burton G. Malkiel & Richard E. Quandt, 1997. "The Predictability Of Stock Returns: A Cross-Sectional Simulation," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 176-183, May.
  • Handle: RePEc:tpr:restat:v:79:y:1997:i:2:p:176-183
    as

    Download full text from publisher

    File URL: http://www.mitpressjournals.org/doi/pdf/10.1162/003465397556764
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    2. Qianwei Ying & Tahir Yousaf & Qurat ul Ain & Yasmeen Akhtar & Muhammad Shahid Rasheed, 2019. "Stock Investment and Excess Returns: A Critical Review in the Light of the Efficient Market Hypothesis," JRFM, MDPI, vol. 12(2), pages 1-22, June.
    3. Varun Sarda & Yamini Karmarkar & Neha Lakhotia Sarda, 2019. "An Empirical Study Applying Log Periodic Structures for Prediction of Realty Market Crashes in India," Vision, , vol. 23(4), pages 357-363, December.
    4. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    5. Adelina Gschwandtner & Michael Hauser, 2016. "Profit persistence and stock returns," Applied Economics, Taylor & Francis Journals, vol. 48(37), pages 3538-3549, August.
    6. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    7. repec:pri:cepsud:91malkiel is not listed on IDEAS
    8. George Furstenberg, 1998. "From Worldwide Capital Mobility to International Financial Integration: A Review Essay," Open Economies Review, Springer, vol. 9(1), pages 53-84, January.
    9. Prince K Sarpong, 2014. "Against the Herd: Contrarian Investment Strategies on the Johannesburg Stock Exchange," Journal of Economics and Behavioral Studies, AMH International, vol. 6(2), pages 120-129.
    10. Fang, Yue & Xu, Daming, 2003. "The predictability of asset returns: an approach combining technical analysis and time series forecasts," International Journal of Forecasting, Elsevier, vol. 19(3), pages 369-385.

    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:tpr:restat:v:79:y:1997:i:2:p:176-183. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Kelly McDougall (email available below). General contact details of provider: https://direct.mit.edu/journals .

    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.