The Correlation Research Of Chinese State Council Report Top Words And Stock Market

The amount of information is growing amazingly fast worldwide with the rapid development of Internet. For our own convenience, the unit of measurement for one piece of information has being converted from Exabyte to Zettabyte. However, as human beings we have very limited vision compared to extraordinarily huge amount of data, so a large chunk of concurrent data cannot be absorbed on time. In field of behavioral finance, scholars are seen attention as scarce resource. And based on limited attention theory, we can expand our research to investors decision-making behavior, so that we can analyze the influential factors on stock market. On the other hand, from the fluctuation in stock market, we can analyze investors’attention as well. In Chinese stock market, it has a strong background on governmental policies. Also, since most of them are individual investors and they are lacking of analytic skills on stock fundamentals, which makes policies become the most critical factor in stock market. Under this background, the annual report of state council from Chinese government contains huge amount of policy information, which intuitively become the most concerns for investors along the way. After releasing the report, both stock analysts and commentators will review it. However, the interpretations based on empirical experiences from them and no backbones of data somehow are short of objectiveness, hence it becomes suspicious. Utilizing investors limited attention theory, we analyze the report rationally and objectively in order to verify our hypothesis of the correlation between the report and stock market under this circumstance.We primarily based on the annual report 2013 to 2015 from Chinese state council to enable us analyzing the trend of top words by parsing out free-text vocabulary and statistical frequency method in this article. We mainly concentrated on words that are first mentioned in the report. By applying these methods, we selected 11 top words from those reports. Under the method of limited attention theory, we constructed the relation between policies and individual share quantitatively with the help of Baidu searching engine. Furthermore, we selected search volume as our co-variate to analyze the correlation between cross sectional returns and individual shares. Our results indicate that searches are significant coefficient when setting cross sectional returns as outcome and it has hysteria quality. Also, after ranking the search volume into 10 groups in descendant order, by applying t-test between individual shares’rate of returns and monthly average rate of returns, we found that in both high search volume group and low search volume group, the correlation between individual shares’rate of returns and monthly average rate of returns are significant.