An Examination of Informed Trades in China’s Stock Market

The thesis mainly examines information-driven trading pattern and trading behavior in China's stock market using intraday high-frequency trading data spanning from 2012 to 2014. The first empirical chapter studies the intraday trading pattern in China's stock market. We identify generally similar trading phenomena that have been previously reported in other markets, that is, there is a U-shaped intraday pattern of trading volumes. We explore two main research questions associated with this phenomenon: the manifestation of it in other trading-volume-related variables (return, volatility, liquidity and price discovery) and the main driving forces that may explain this phenomenon. By examining high-frequency quote and trading data of all stocks that comprise the CSI300 index, we find that most trading-volume-related variables, such as volatility, liquidity and price discovery, all show similar U-shaped intraday patterns. This reveals that investors’ preference to trade during particular time periods (e.g. the opening and ending time of a day) have significant impact on other trading-volume-related variables. To further understand the driving forces behind the observed phenomenon, we also examine the intraday pattern of informed trading behavior and find that the probability of informed trading (PIN) as well as the price discovery (measured by Weighted Price Contribution, WPC) are also much higher at the beginning and ending period than during other time periods of a day. Moreover, a clear intraday momentum effect is also observed. Therefore, we argue that the observed U-shaped intraday trading pattern for the CSI300 stocks is mainly driven by the unbalanced information flow over time within a day. The second empirical chapter examines the information-driven trades and informed traders’ order size strategies in China’s stock market. We find the aggregate U-shaped informed trading is not only explained by the time-of-day effect but is also related to the order size strategy, which is shown by intraday variations in the composition of small, medium, and large trades. The evidence of information predictability from early morning to market close and from late afternoon to the next day provides additional insights into the intraday informed trading pattern. We identify the non-negligible price impact (PI) of large trades and propose a modified model, VDPIN-PI, that can better capture the trades with information advantage than the baseline model. Autocorrelation test and information advantage test are applied to ensure the robustness of our main results. The third empirical chapter focuses on the study of informed trading around earnings and M&A announcements in China's stock market. By adopting both indirect and direct informed trading measures, it is found that informed tradings are more pronounced before earnings announcements than before M&A announcements. We further investigate the relation between firm characteristics (size and profitability) and the level of informed tradings. Results show that smaller companies have more informed trading before both earnings announcements and M&A announcements. Companies of both high and low profitability show more informed trading than companies of medium profitability before earnings announcements. Nevertheless, only companies with poor financial performances have higher levels of informed trading before M&A announcements. Moreover, companies with higher level of informed trading seem to have less or even negative long term benefits from M&As on both stock price and financial performance. We argue that this could reveal that the initial motivation of mangers to launch M&A transactions is the gains from insider tradings instead of the long term interests of the companies. We conjecture that informed tradings prior to M&A announcements by small and non-profitable firms could be executed by actual insiders as a result of agency problem and weak market regulation in China