Trading Volume Anomaly And Macro-economy

Most of the early verifications support CAPM pricing theory（Jin Yunhui and Liu Lin,2001）.However,with the development of research and market,more and more anomalies that cannot be explained by CAPM model appear.Price and trading volume are the two most basic variables in the stock market.The anomalies formed on the basis of trading volume have gradually attracted the attention of scholars and investors,and are widely used by institutional investors in the field of professional investment（Rao Pingui and Jiang Guohua,2008）.A large number of micro literature studies have also verified this point.They have studied the contemporaneous and dynamic relationship between transaction volume and return.Relevant research found that trading volume or turnover rate contains useful information for predicting future stock prices,and investors can construct relevant investment strategies according to it（Blume,1994）.Barinov and Alexander（2014）called this phenomenon of negative correlation between cross-sectional trading volume differences and expected returns as trading volume anomalies.The mainstream explanations of trading volume anomalies mainly include the liquidity premium theory proposed by Amihud and Mendelson（1986）,the investor recognition hypothesis proposed by Merton（1987）,the heterogeneous belief theory of investors proposed by Miller（1977）,and the risk-taking theory.The market microstructure theory shows that the trading volume and price changes are related to the arrival of market information.Cochrane（2013）believes that a large number of transactions...are obviously to provide information to the market.The trading volume indicates how investors share risks or view information,which further leads to different reversal or continuation modes（Llorente,Michaely,Saar and Wang,2002）.According to the theory of risk sharing,investors trade based on the information they acquire.When investors acquire new information,they will trade based on the perspective of risk sharing.The trading behavior represents the investors’view of risk.The premium obtained by investors in exchange based on the risk information is actually a risk premium.Based on the research of scholars at home and abroad,this paper explores whether the cross-sectional trading volume anomalies in China’s A-share market are related to China’s macroeconomic risks.More generally,this paper discusses whether the trading volume anomalies（or parts）can be priced by common risk factors based on the risk-taking mechanism,and linked to economic risks.First of all,this paper takes 2407 non-financial stocks in the A-share market from June 2006 to June 2022 as research samples,and preliminarily verifies that there are significant trading volume anomalies in the A-share market.On average,after controlling the scale factor,the stocks with equal weight and low trading volume can achieve 3.176%of the excess monthly return（the value weighted low trading volume premium is 2.976%）in the sample range compared with the stocks with high trading volume,and this anomaly still exists significantly after controlling the value effect,dynamic effect,reversal effect,liquidity premium,beta factor and other effects.Secondly,inspired by Fama（1991）on the relationship between the cross section and the predictability of stock returns in time series,we assume that if the trading volume anomaly constructed from the cross section of stocks is indeed related to the macro economy,it is helpful to predict the time changes of future actual economic activities.At the same time,the factors representing economic risks can help explain the changes in the expected return of stocks sorted by trading volume.The research results show that the trading volume anomaly does contain effective information that can help predict future economic growth.We selected eight macroeconomic indicators,including,industrial value-added IP of enterprises above designated size,and consumer price index.The research found that in addition to China’s manufacturing purchasing manager index,The low volume premium(1has significant leading and forecasting effects on the other seven macroeconomic variables,and verifies that this leading is one-way.In particular,(1has a statistically significant predictive effect on the industrial added value IP of enterprises above designated size.The low transaction volume premium increased by one unit in the month,and the industrial added value of enterprises above designated size decreased by 7.4%on average after four months.Finally,this paper introduces the economic policy uncertainty indexas the proxy variable of the macro risk into the model,and uses the common risk pricing factor and the macro risk factor to price the(1of the trading volume anomalies in China.The results show that the capital market pricing factor liquidity factor,market factor,and management factorhave a significant impact on the trading volume anomalies under the significance level of less than 5%.More importantly,the economic policy uncertainty index₊₁ represents the proxy variable of macroeconomic risk expected by investors at the significance level of 1%,is positively correlated with the low trading volume premium,which provides an explanation for the trading volume anomalies based on the risk-taking mechanism.