Predicting Daily Stock Returns: A Lengthy Study of the Hong Kong and Tokyo Stock Exchanges
AbstractIf 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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Bibliographic InfoArticle provided by College of Business, and College of Finance, Feng Chia University, Taichung, Taiwan in its journal International Journal of Business and Economics.
Volume (Year): 7 (2008)
Issue (Month): 1 (April)
market efficiency; prediction; stock returns; daily effects; time series;
Find related papers by JEL classification:
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
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- 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.
- James M. Poterba & Lawrence H. Summers, 1989. "Mean Reversion in Stock Prices: Evidence and Implications," NBER Working Papers 2343, National Bureau of Economic Research, Inc.
- 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.
- Tom Doan, . "VRATIO: RATS procedure to implement variance ratio unit root test procedure," Statistical Software Components RTS00231, Boston College Department of Economics.
- Andrew W. Lo & A. Craig MacKinlay, 1989. "Stock Market Prices Do Not Follow Random Walks: Evidence From a Simple Specification Test," NBER Working Papers 2168, National Bureau of Economic Research, Inc.
- Granger, Clive W. J., 1992. "Forecasting stock market prices: Lessons for forecasters," International Journal of Forecasting, Elsevier, vol. 8(1), pages 3-13, June.
- Pesaran, M Hashem & Timmermann, Allan, 2000.
"A Recursive Modelling Approach to Predicting UK Stock Returns,"
Royal Economic Society, vol. 110(460), pages 159-91, January.
- Pesaran, M. H. & Timmermann, A., 1996. "A Recursive Modelling Approach to Predicting UK Stock Returns'," Cambridge Working Papers in Economics 9625, Faculty of Economics, University of Cambridge.
- Allan Timmermann & M. Hashem Pesaran, 1999. "A Recursive Modelling Approach to Predicting UK Stock Returns," FMG Discussion Papers dp322, Financial Markets Group.
- 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.
- Yoon-Jae Whang & Young-Hyun Cho & Oliver Linton, 2006.
"Are there Monday effects in Stock Returns: A Stochastic Dominance Approach,"
FMG Discussion Papers
dp568, Financial Markets Group.
- 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.
- 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.
- 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.
- Campbell, John, 1987.
"Stock Returns and the Term Structure,"
3207699, Harvard University Department of Economics.
- 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.
- 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.
- 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.
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