Date of Original Version
If stock markets are efficient then it should not be possible to predict stock returns, namely, 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. The purpose is to explore whether this line of argument is or is not satisfactory and does or does not aid 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 the two large Asian Stock Market exchanges, which are Japan and Hong Kong. We observe that stock market returns (which include closing prices and dividends) are predictable and there are explanations for short-term predictability. Japan and Hong Kong were 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 resource. Furthermore, to reduce the influence of the Pandemic (2020-2022, the author studied a data base for a large number years prior to the era of the global Pandemic to reduce the argument that the era studed was a large enough sample and the influence of special variation associated variation associated with the unusual health period was reduce to nothing.
Publication Title, e.g., Journal
International Journal of Latest Engineering Science
Jarrett, J. E. (2022). Predicting Daily Stock Returns; A Lengthy Study of the Hong Kong and Japan Stock Exchanges. IJLES, 5(3), 16-35. http://doi.org/10.51386/25816659/ijles-v5i3p103
Available at: http://doi.org/10.51386/25816659/ijles-v5i3p103
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