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| Volume 7, No. 1,
April 2008 |
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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 |
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University of Rhode Island,
Faculty of Management Science and Finance, U.S.A. |
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| Abstract |
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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. |
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Key words:
market efficiency; prediction; stock returns; daily effects; time
series |
| JEL
classification:
G10 |
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