IDEAS home Printed from https://ideas.repec.org/a/ijb/journl/v7y2008i1p37-51.html
   My bibliography  Save this article

Predicting Daily Stock Returns: A Lengthy Study of the Hong Kong and Tokyo Stock Exchanges

Author

Listed:
  • Jeffrey E. Jarrett

    (University of Rhode Island, Faculty of Management Science and Finance, U.S.A.)

Abstract

If stock markets are efficient then it should not be possible to predict stock returns, i.e., no explanatory variable in a stock market regression model should be statistically significant. In this study, we find results indicating that daily effects exist in stock market returns. These daily or calendar effects previously shown to exist by others clearly indicate the purpose of this study. Researchers often equate stock market efficiency with the non-predictability property of time series of stock returns. We explore whether this line of argument is satisfactory and aids in furthering our understanding of how markets operate. We focus on one definition of capital market efficiency and on the experience of these principles in analyzing the performance of Hong Kong and Tokyo stock exchanges. We observe that stock returns (which include closing prices and dividends) are predictable and there are explanations for short-term predictability. Hong Kong and Japan are the focus of this study because of the maturity of their financial markets and the availability of clean data on these markets from a reputable and available source.

Suggested Citation

  • Jeffrey E. Jarrett, 2008. "Predicting Daily Stock Returns: A Lengthy Study of the Hong Kong and Tokyo Stock Exchanges," International Journal of Business and Economics, College of Business and College of Finance, Feng Chia University, Taichung, Taiwan, vol. 7(1), pages 37-51, April.
  • Handle: RePEc:ijb:journl:v:7:y:2008:i:1:p:37-51
    as

    Download full text from publisher

    File URL: http://www.ijbe.org/table%20of%20content/pdf/vol7-1/vol7-1-03.pdf
    Download Restriction: no

    File URL: http://www.ijbe.org/table%20of%20content/abstract/Vol.7/No.1/03.htm
    Download Restriction: no

    References listed on IDEAS

    as
    1. Cho, Young-Hyun & Linton, Oliver & Whang, Yoon-Jae, 2007. "Are there Monday effects in stock returns: A stochastic dominance approach," Journal of Empirical Finance, Elsevier, vol. 14(5), pages 736-755, December.
    2. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    3. Pesaran, M Hashem & Timmermann, Allan, 2000. "A Recursive Modelling Approach to Predicting UK Stock Returns," Economic Journal, Royal Economic Society, vol. 110(460), pages 159-191, January.
    4. Granger, Clive W. J., 1992. "Forecasting stock market prices: Lessons for forecasters," International Journal of Forecasting, Elsevier, vol. 8(1), pages 3-13, June.
    5. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
    6. Clare, A D & Thomas, S H & Wickens, M R, 1994. "Is the Gilt-Equity Yield Ratio Useful for Predicting UK Stock Returns?," Economic Journal, Royal Economic Society, vol. 104(423), pages 303-315, March.
    7. J. Andrew Coutts & Peter Hayes, 1999. "The weekend effect, the Stock Exchange Account and the Financial Times Industrial Ordinary Shares Index: 1987-1994," Applied Financial Economics, Taylor & Francis Journals, vol. 9(1), pages 67-71.
    8. Shigeyuki Hamori & Akira Tokihisa, 2002. "Some International Evidence on the Seasonality of Stock Prices," International Journal of Business and Economics, College of Business and College of Finance, Feng Chia University, Taichung, Taiwan, vol. 1(1), pages 79-86, April.
    9. Steeley, James M., 2001. "A note on information seasonality and the disappearance of the weekend effect in the UK stock market," Journal of Banking & Finance, Elsevier, vol. 25(10), pages 1941-1956, October.
    10. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    11. Giuseppe Alesii, 2006. "Fundamentals Efficiency of the Italian Stock Market: Some Long Run Evidence," International Journal of Business and Economics, College of Business and College of Finance, Feng Chia University, Taichung, Taiwan, vol. 5(3), pages 245-264, December.
    12. Keiichi Kubota & Hitoshi Takehara, 2003. "Financial Sector Risk and the Stock Returns: Evidence from Tokyo Stock Exchange Firms," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 10(1), pages 1-28.
    13. 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.
    14. Kim-Leng Goh & Kim-Lian Kok, 2006. "Beating the Random Walk: Intraday Seasonality and Volatility in a Developing Stock Market," International Journal of Business and Economics, College of Business and College of Finance, Feng Chia University, Taichung, Taiwan, vol. 5(1), pages 41-59, April.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    market efficiency; prediction; stock returns; daily effects; time series;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    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:ijb:journl:v:7:y:2008:i:1:p:37-51. 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: (Yi-Ju Su). General contact details of provider: http://edirc.repec.org/data/cbfcutw.html .

    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.