The Study On The Investor's Following Behavior Based On The Herd Theory

In this paper, we expand the classic herd behavior theory. Though analyzing the Chinese specific stock market environment, we treat the stock price, which inferred from the first investor's behavior, as a stochastic process. Using the dynamic theory, we find when one of the herd do invest and analyze the impact factors. After that, we expand our model to include all herds to follow. We compare the outcome of new model to the previous finding. Finally, we take the time-inconsistency preference into consideration, which would occur when the stock price suddenly rise into the upper price limit, and draw interesting findings. Above all, we have six conclusions, which will be empirically tested.According to the Model I and Modelâ…¡'s conclusion, stock market average returns, stock volatility and other factors would impact herd behavior. This provides us the entry point to study the herding of institutional investor. We successfully test the model's conclusion. First, we analyze the characteristics of institutional investors; Second we review of the irrational behavior of institutional investors; then we use the panel data analyze various factors, how which would impact the overall institutional investors herding behavior. Finally, we examine and compare the investment behavior of different types of investor:funds, brokerage, brokerage financial products, QFII, insurance companies, pension funds, annuity, trust companies, finance companies, banks, general corporate, non-financial listed companies.According to the Modelâ…¢'s conclusion, when the stock price rapidly rises to the upper limit, the investor may be surfer the time-inconsistency preference problem, which would strongly trigger herding behavior. So there are someone would utilize this mechanism to get profit. We use high-frequency data to study whether stock rise to the upper limit is manipulated or not. Firstly, we utilizes Markov switching model to study Chinese stock market volatility. Based on Shanghai Composite Index's historical data, we estimate the parameters of Markov switching model and get the figure of the whole sample smooth probability. WE uses this nonlinear method to accurately classify the different period by the volatility. Based the classified period, utilizing the high frequency stock data, we statistically analyze various factors impact the second day's stock price return after the stock up to the limit broad. We empirically verify the stock price's different behaviors respectively caused by new information or price manipulation. According to our conclusion, we propose advises to improve Chinese Stock Price Limit System.