The Relationship Between The CSI 300 Stock Index Futures Volatility And Trading Volume

Chinese financial derivatives market expanded rapidly in 2015 with Shanghai Stock Exchange 50ETF share option, Shanghai Stock Exchange 50 and China Securities Information 500 Equity Index Futures coming to being in succession, which greatly enriched the market trades. The pace of the development is closely related with the 5 consecutive years’stable expression since the launch of the futures contract of CSI-300. Since 2001, Chinese A-share market has experienced several ups and downs and thanks to the CSI-300 stock-index futures, market systematic risk significantly reduced, which was indicated by that CSI-300 stock-index volatility and the trading days of price variation more than 2% are dramatically less than the previous ones. However, as the trading systems between T+1 system of A-share market and T+0 system of stock index futures market are non-synchronized, the underlying index of existing contracts can’t cover all shares in the A-share market, and investors would take advantage the hedging portfolio of the establishment of doing more small-cap stocks and going short the CSI-300 stock index futures, it’s hard to meet the strict market neutral objectively. In this case, making further research about the operation law of CSI-300 stock-index futures is of great significance for the traders to improve the trading strategy and those regulators to set up the trade category and the corresponding trading rules; besides, the research result shall also has enlightenment meaning to the correlational research of listed contracts such as SSE-50 and SCI-500, etc.Based on the mixture distribution model of considering the accident message and the normal information as the theoretical basis, with CSI-300 stock index futures as the study object, this paper aims at studying the correlation and causality of volume and volatility. In order to verify the applicability of the above theory in CSI-300 stock index futures market, this paper makes a comprehensive utilization of Granger causal test, impulse response function and the GARCH model with quantile regression; besides, the author thinks over the insufficiency of the above theory in differentiating the normal information and the abnormal ones and introduces multi-fractal volatility and smooth transition auto-regression model for further empirical analysis.The empirical results of this paper verify the following conclusions:1. There is two-dimensional linear and nonlinear causality between the CSI-300 index futures volatility and the volume of business; besides, the overall guiding function of trading volume is better than the volatility which explains the inapplicability of efficient market hypothesis in CSI-300 index market and investors can predict the future price movements according to the past market information like trading volume.2. Significant correlation is demonstrated between volume and volatility and there are two kinds of correlativity in high and low volatility. This indicates that the influence mode of accident information is different from that of normal message, which validates that the mixture distribution model improved by Park (2010) can be applied into the CSI-300 stock index futures market. With the increase of trading volume, the corresponding changes in volatility gradually increased with the unit volume. The correlation has a smooth transformation mechanism of trading volume and volatility in high and low volatility with no definite borderline in normal and accident information, which shows that distribution function form of Park still has room for improvement.