Research On Relationships Between Investor Attention And Stock Trading Volumes And Prices In Second-board Market Based On Baidu Indes

The traditional capital pricing theory won extensive support in massive literatures before the 1960 s. However, along with the constant development and complexity of the financial market, a large amount of market anomalies, such as the momentum effect, reverse effects and the equity premium and so on, which could not be explained by traditional financial theories, have appeared both in theory and practice. In order to more effectively grasp the information changing trend in the market, which plays an undoubtedly important role in perfecting the traditional capital pricing theory.In existing studies on investor attention, indirect measure indexes( such as the rate of returns on excess earnings, stock trading volumes, limit events, news media, advertising costs, etc.) are mainly used to measure investor attention. However, owing to the development of the network and search engine technology, it becomes feasible for scholars to obtain data about investor attention with the help of search engines. Therefore, in this paper, the Baidu index as a new variable measuring investor attention is used for research.After the measure index for investor attention is chosen, research samples are stocks in the second-board market of China. The second-board market is taken as the research object, as its information can be easily obtained from the Baidu database. Companies in the second-board market are mainly “high in growth rates and technological contents” based on new economic modes, new services, new agriculture, new materials, new energy and new business models. These companies are usually objects of some theme and concept hypes, which increases the possibility that individual investors access to information about these companies through the Internet. It indicates that the Baidu search index can well reflect investor attention in a market.Research samples are stock data in the second-board market from January 1, 2013 to June 30, 2014. The statall software is used for make empirical tests from the following three parts.The first part is about the sample design and selection of variables. Daily data during the period from January 1, 2013 to June 30, 2014 is chosen as research samples, on the basis of considering the availability of the second-board market and Baidu indexes. Daily data about the Baidu indexes for each stock in the second-board market is used to measure investor attention. The higher the Baidu index for a stock is, the greater the investor attention to this stock would be. Other variables used in this research include daily rate of return, the rate of return on excess earnings, the absolute value of the rate of return on excess earnings, trading volumes, the stock turnover rate, the volatility, the rate of returns on market portfolios, corporate market values and the price/book value ratio. As no distinction is made between information with different attributes(good or bad one), the absolute value of the rate of return on excess earnings as an index is used in this research, to investigate impact of investor attention on production of stock yields.The second part is about the empirical model and analytical results, which can be further divided into following five sections. In the first section, the correlation between stock market performance and investor attention is investigated. The daily rate of return, the absolute value of the rate of returns on daily excess earnings, the rate of return on excess earnings, the inter-day price volatility, the turnover rate and trading volumes are taken as dependent variables, and investor attention is taken as an independent variable to make a univariate regression of panel data, so as to figure out whether investor attention can independently product impacts on variables mentioned above, thus laying a solid theoretical foundation for research in following sections. In the second section, an empirical study is made to analyze impacts of investor attention on market trading activities. In this section, under the premise that other variables are controlled, an empirical study is made to check whether investor attention would affect the stock liquidity. In this section, two models are built respectively by taking trading volumes and the turnover rate as dependent variables, the Baidu index as the independent variables and the rate of return on market portfolios, corporate market values and price/book value ratio as control variables, to investigate relationships between investor attention and the stock liquidity. In the third section, the impact of investor attention on the stock market volatility is analyzed. In this section, a model is built by taking the inter-day stock price volatility as dependent variables and the Baidu index as independent variables and adding other control variables to investigate impacts of investor attention on stock prices, so as to figure out whether investor attention would cause the stock market volatility and fluctuations in stock prices. In the fourth section, the reversal effect of investor attention on stock returns is discussed. As information gathering and process takes time, investor attention of the current period and investor attention of the lag period may show different performances in the stock market. Therefore,The author takes the rate of daily returns on stocks as a dependent variable, the Baidu indexes as independent variables and the rate of returns on market portfolios, corporate market values and the price/book value ratio as control variables to build a model, so as to investigate relationships between the rate of return on stocks and investor attention. On this basis, Baidu indexes in the model are respectively extended to 1 to(N) periods(N is determined based on empirical tests), so as to figure out whether investor attention would produce reversal effects on the stock market, as a kind of inertia for stock prices.In the third part, a robustness test is conducted. 360 Indexes are used to replace Baidu indexes to measure investor attention. Moreover, the range of samples is reduced. 10 stocks are randomly chosen from the second-board market to test conclusions made in the second part.Following conclusions are drawn. Investor attention is significantly correlated with the stock market performance. Great investor attention will result in an increased in the stock trading volume and turnover rate of the current period, and bring positive returns in the current period. However, positive returns would receive reversal effects in the next period, which would last for some time. That is to say, investor attention can explain the reversal effect of investor attention, to some extent.