| Since the block trading system launched the Shenzhen Stock Exchange on February 25th,2002 and the Shanghai Stock Exchange on January 10th,2003, China began to explore the standardization and marketization of block trading. As the proportion of institutional investors continuously increases and with a rapid growth in mergers and acquisitions, there exits more and more large share transfer, and finally results to the increasing active block tradings. In particular, under the influences of the guidance of listed companies of transferring restricted shares announced by the Commission issued in April 2008, "If the shareholders who are going to sale the restriced stocks exceed 1% of the total shares within the next month, they should sale the shares through the block trading system", the block tradings become more and more active under the influence of the policy. By the end of 2010, there were a total of 11234 block tradings, with the cumulative transaction amount reached 3.95x 106 million occurred in Shanghai and Shenzhen Stock Exchange, including stocks, bonds and funds tradings. As a trading pattern with a not very long hostroy, block trading is gradually attracting the attentions and favors of investments in China's stock market.The purpose of this paper is to find out the influences on implicit transaction costs and its compositions brought by block tradings from the perspective of stock market microstructure. In addition, it also focuses on the characteristics of block tradings which may influence the implicit transaction costs. The study takes block trading datas from 2008 to 2010 in Shanghai and Shenzhen 300 Index shares as samples. And it uses Tick classification to calssify the samples as block buyings (755) and block sellings (1205), which is 1960 in total. This paper firstly divides the trading hours into 8 equivalent periods each day, and then calculates the effective bid-ask spread Z of each time period separately both the trading day and the next day. Secondly, it use the model of LSB to decompose the effective bid-ask spread Z into information asymmetric componentλ, command processing component y and the command continuous componentθ. Using the method of the Paired Sample Mean T Test and Wilcoxon Signed Rank Test on Z andλ,γ,θfor mean comparison, it comes out that block buyings make Z decrease significantly at the opening period (9:30-10:00 and 10:00-10:30) of the next trading day, so does the compositons ofλand y. To the opposite,θincreases. Compared to block buyings, block sellings make Z increase significantly in three periods (9:30-10:00,10:00-10:30 and 10:30-11:00), so does the composition of y. However,λandθhaven't taken on significant up or down trends. Since it has been determined that block tradings have significant influences on Z, it uses regression analysis to study whether the characteristics of block tradings are related to the changing of Z. The independent variables are offset levels (Price), the relative trading volume (Volume) and dummy variable of business department of buyers and sellers (Place), and the dependent variable is Z. Besides, the total stock market value of samples (LnSize) and turnover rate (LnTurnover) are controlled. It finds out that Z is negatively conelated with Price and Volume when block buyings occur, while the correlation is positive in the case of block sellings. However, there is no significant relationship between Z and Place nither under the influence of block buyings nor block sellings. Finally, this paper summarizes the conclusions based on empirical study, and proposes recommendations for improvements of China's stock block trading system. |
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