A Study Of Order Imbalance Volatility Factors In The Chinese Stock Market

The traditional theory of macroeconomics and finance believes that prices are determined by supply and demand,which does not reveal the process of gradual price formation in the market and ignores many factors that affect the actual market,while the microstructure of the market reveals this process.The microstructure of financial market has a broad sense and a narrow sense,the broad sense of market microstructure includes various trading systems,such as price discovery,information dissemination and other mechanisms,while the narrow sense of market microstructure only refers to the price discovery mechanism of the market,which is also the core of market microstructure theory and is the essence of asset pricing theory.The current asset pricing related research has been relatively abundant and the factors have been expanding,however,most of the existing mainstream factors such as Fama-French five factors and momentum factors are extracted from low frequency data such as fundamental information,or the acquisition and processing of high frequency trading data is too complicated,resulting in relatively few factors extracted from high frequency trading data in market microstructure.However,as high-frequency trading has become more frequent in recent years,the significance of studying high-frequency factors and thus improving market pricing efficiency has gradually increased.Chordia et al.(2019)found that order imbalance volatility and its shocks(i.e.,volatility of order imbalance and its shocks)extracted from highfrequency trading data in the market microstructure are new pricing factors in the U.S.stock market,enriching the study of high-frequency factors.Since the differences between the microstructures of the Chinese and U.S.markets may lead to different pricing mechanisms,it is necessary to study order imbalance volatility factors based on high-frequency trading data in the A-share market of China.Against the above background,this paper extends the study of Chordia et al.(2019)to investigate the order imbalance volatility factors in the Chinese stock market based on the tick-by-tick ultra-high-frequency trading data of the A-share market in China.This paper selects the tick-by-tick ultra-high-frequency trading data of China’s A-share market from January 2006 to December 2019 as the research sample,from which order imbalance volatility and its shock indicators are extracted and constructed,including order imbalance volatility VOIB＿SHR constructed based on volume and order imbalance volatility VOIB＿NUM constructed based on number of trades.Through correlation analysis,constructing investment portfolios,conducting Fama-Macbeth regressions,etc.,this paper studies the order imbalance volatility factor in the A-share market of China and draws conclusions.Since some scholars believe that it is liquidity that links order imbalance to return,this paper also studies the relationship between order imbalance volatility and liquidity.Finally,this paper conducts robustness tests on the conclusions obtained earlier and proposes investment strategies based on the order imbalance volatility factor.This study shows that in the A-share market of China,for investors,the order flow volatility VOIB＿NUM constructed based on the number of trades only is the factor.VOIB＿NUM can positively predict the expected returns of individual stocks,and VOIB＿NUM can be used to construct investment strategies.By taking long positions in stocks with higher VOIB＿NUM and short positions in stocks with lower VOIB＿NUM,significant returns can be obtained from the portfolio constructed in holding the portfolio for one month,which gradually decrease afterward.This paper also found that regardless of whether it is the order imbalance volatility factor VOIB＿SHR constructed based on trading volume or VOIB＿NUM constructed based on trading number,the higher the order imbalance volatility,the higher the expected return of individual stocks,while the higher the shock it generates,the lower the expected return of the individual stocks.In addition,this paper finds that order imbalance volatility(shock)is positively correlated with illiquidity(shock),and order imbalance volatility(shock)captures information beyond that contained in liquidity(shock),probably because order imbalance volatility is related to adverse selection.Therefore,this paper suggests that relevant regulatory authorities can encourage the development of high-frequency trading,establish a sound highfrequency trading supervision mechanism,and incorporate VOIB＿NUM into the stock market risk early warning system to promote the healthy development of the stock market,while investors can strengthen their understanding and learning of high-frequency trading related knowledge,and choose investment strategies after comprehensive consideration.