Impact Of Internet Information Transmission On The Stock Market Volatility

With the rapid development of the Internet, the stock market has widely appliedinformation technology and information dissemination. Combined with the currentsituation of China’s Internet development, the main concern is the nationalmacro-policy orientation, the stock information and the message delivered by stockforum, blog and other social media. A search engine has collected various ofinformation channels and become the most used tools to obtain information andcommunicate.This paper has used the macroeconomic data (SHIBOR rates), Baidu news index.Through data mining and econometric methods, it can analyze the impact of opensource information on the stock market behavior. Through a series of research, resultsshow that:(1) Whether in the period of fluctuations or rising of SHIBOR, when add thetrading volume into model, the volatility has significantly reduced, indicating thattrading volume can effectively explain the price fluctuations of the stock market.Besides, during the fluctuations of interest rate，information transmission can betterexplain the price fluctuations of the stock market.(2) Information transmission has a positive impact on conditional volatility.When joining the Internet open source information, the volatility persistence is mostdecreased (from0.9850to0.3564), while joining the original trading volume andadjustment values of trading volume, the reduction of the volatility persistence wasnot as obvious as the Internet information. These results mean that, the Internetinformation is the better agent of information transmission.(3) In the concrete research, by nonparametric relevant certificate, it can provethat four period Baidu news and the corresponding abs (abnormal yield) hassignificant nonparametric correlation. For the first period, that is, the abnormal returnsbefore the start of stock market own the most dramatic change, market reaction degreeis bigger. An abnormal return in morning trading is more uniform in afternoon trading,while the reaction in period3is low. On the other hand, this paper also found thatexcept for the first period, the other three periods after period of abnormal returns are Granger result of information transmission, thus illustrates the problem of informationleakage before releasing information.This paper has combined the two channels of information dissemination. Afterhigh frequency data mining, it not only can find intra-day trading behavior, but alsoprovide new train of thought to dig deeper into relationship between informationdissemination and stock price fluctuations. Therefore, it has the good theory value andapplication value.