Investigation Of China Stock Market Trading Behavior And Trading Characteristics, Based On The Perspective Of Asset Price Jump

The stock price jump has been one of the most important research fields in the Market Microstructure theory. The research of stock price jump identification and the study of market transactions, trading characteristics under stock price jump can deeply reveal the "discovery - conduction - integrate- feedback" process, which can also allow investors catch the asset price behavior more accurately and provide the theory and the practice basis for asset pricing, asset allocation and risk management.Under Market Microstructure angle of view, based on the non-parametric method of jump detection frame, this dissertation use China's securities market high frequency transaction data to explore the identification of stock price jump and the change process of market transactions under the jump impaction, reveal the trading characteristics under stock price jump. The detailed contents are as below:The first section briefly described the background of this study, introduced financial market microstructure theory and asset price behavior modeling and theoretical background of the existing problems of China's stock market, proposed the research questions and research significance. The following content presented the progress of asset prices jump identification, and the research status of market transactions, trading characteristics under stock price jump.The second section described asset price jumps identification method in detail, presented the parameters of asset price jumps and non-parametric identification methods. On the basis of the non-parametric asset price jumps identification system, the study then described the current two kinds of more classical non-parametric jump identification method. The following content used high-frequency transaction data to detect the interday and intraday of high-frequency jump of China's securities market, which based on BNS's second power jump identify variation theory framework, the study found that the asset prices jump behavior of China's stock market presented quite frequently, and there are a large number of consecutive jumps during the jump day, the jump frequency and amplitude characteristics showed significance difference during different stocks, and a large number of jump behavior occurs in the opening period. The third section employed the high-frequency stocks jump moment of the Chinese stock market as dummy variables to extend the MRR model, then based the Jump-MRR model researched the impaction process of asset prices jump on the market trading behavior. The study found there was a significant impact on the market trading behavior when the asset prices jump occur. First, the asymmetric information costs and liquidity costs were lower than normal time before the jump occurred. Second, when the jump occurred, the information costs became significantly larger, indicating that the jump is a very severe phenomenon of information integrate into prices, while the cost of liquidity jump showed a significantly reduction, indicating the occurrence of jumps along with the increase in investors' willingness to trade. Third, after the jump occurred about 5 minutes, the impact of information costs and the cost of liquidity showed a rapid response process. Besides, the market trading behavior showed a significant difference between the different groups of stock capitalization, with the company's market capitalization grows in size, the average impact of information and mobility costs become smaller when jump occurred, showed that the high-cap stocks has good liquidity and low level of asymmetric information, and investors has a stronger willingness to trade these high-cap stocks than the low-cap stocks.The fourth part of this dissertation researched on the characteristics of market trading volume and return under the stock price jump, revealed how the information impact on the behavior of stock pricing from a more microcosmic view. The empirical results shows that the market impact often occurs with greatly increase in trading volume, and the trading volume will decrease after the information integrated in the market price. Furthermore, the results also suggest that good news and bad news has asymmetry impact on market trading volume and stock returns, traders are more reactive to bad news in bull market and more sensitive to good news in bear market.