Analysis Of The Impact Of Order Flow Imbalance On Futures Price Fluctuation Based On Robust Regression

After years of exploration and development,China’s futures market has grown in size and international influence,and has become one of the major futures trading markets in the world.Therefore,in-depth research on the microstructure of Chinese futures markets has important theoretical value and practical significance.With the rapid development of computer science and technology,order driven electronic trading systems have become the mainstream trading mechanism.The complete automation of securities trading not only significantly improves the trading efficiency of the market,but also enhances the availability of high-frequency data.Currently,research on the microstructure of order driven markets is mostly based on trading behavior,and limit order book,as the core of order driven markets,fully record this information.Building models based on high-frequency data from limit order book to study the price discovery mechanism in futures markets,thereby guiding traders in investment and risk aversion,has become an attractive research topic.Based on the high-frequency trading data of six major contracts,including coke,which are the most frequently traded and representative among the listed varieties on the Dalian Commodity Exchange,this paper first establishes a primary order flow imbalance index and a trading imbalance index to measure the degree of imbalance between supply and demand in the market,based on the information on the optimal bid and ask prices in the limit order book,a cross comparison experiment was set up to test the explanatory power of the two indicators on futures price changes.The empirical results show that:1.there is a significant positive correlation between order flow imbalance index and futures price changes;2.compared to the trading imbalance index that only represents the volume-price relationship,the order flow imbalance index has a stronger ability to explain price changes.In order to fully utilize the information in the limit order book,this paper constructs a multi-level order flow imbalance index based on the interaction of transaction events at all levels in the order book.Through empirical testing,it is proved that the fifth-level order flow imbalance index can fully use the information reflecting price changes in the order book,thereby better depicting the price change process.Due to the fact that real market trading data is extremely difficult to satisfy the ordinary least squares hypothesis,and objective factors such as block trading in the futures trading market can lead to outlier in the data.In order to solve the above problems,this paper constructs a distributed uncertainty regression model between multi-level order flow imbalance index and futures market price changes,and uses robust regression methods to solve the model.The empirical results show that using this method can effectively improve the ability of multi-level order flow imbalance index to explain price changes,which can better guide traders to make rational decisions and avoid market risks.