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

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  • 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, School of Management Development, 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
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    References listed on IDEAS

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    More about this item

    Keywords

    market efficiency; prediction; stock returns; daily effects; time series;
    All these keywords.

    JEL classification:

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

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