101. Information Efficiency Comparison Between Shanghai and Hongkong Stock Markets
- Author
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Qu, Huan
- Abstract
This thesis starts with the introduction of Shanghai stock market, Hong Kong stock market and efficient market hypothesis. It then tries to compare the information efficiency between Shanghai and Hong Kong stock markets with 2002-2007 Shanghai Composite Index and Hong Seng Index trading data. The model used is a modified GARCH(1,1) model and the data is processed with Excel and the model is run with Stata. The empirical result of the daily trading data shows that the information spread process did not have a significant effect on either Shanghai stock market or Hong Kong stock market. However, the daily trading data of Shanghai Composite Index show sign of the day-of-the-week effect and seasonality effect, though not significant at the 5% level. These effects are not excluded from our data and could potentially bias our empirical result. The empirical result of the weekly trading data doesn’t show significant effect on Hong Kong or Shanghai stock market either. The effect increases greatly however for Shanghai stock market and is significant at 10% level. Our empirical result shows that the Shanghai stock market has improved in terms of information efficiency, which is contrary to the result of Liu and Morimune (2005) and other previous studies of Shanghai stock market. It could be supported by the following facts: —The market has expanded a lot over the years and especially recent years. —The launch of reform of non-tradable shares. —The rapid development of institutional investors. —The convergence of annual turnover rate to that of major stock markets. Although our result shows that the information efficiency of Shanghai stock market has improved a lot, it still indicates that compared to developed stock markets like Hong Kong stock market, it is still less efficient given the information spread process effect significant at the 10% level. However, the paper might suffer from several deficiencies. The daily data regression is influenced by the day-of-the-week effect and seasonality effect to some degree.The fitness of the model for the problem we are discussing has not been proved. And also, our sample data includes a period of abnormal prosperity in Chinese stock market, which might bias our final result.
- Published
- 2008