Since market uncertainty,or volatility,serves as a crucial gauge for assessing the traits of market fluctuations,the link between stock market volume and price continues to be a focal point of interest in finance.This study examines the dynamic,nonlinear correlations between Chinese stock volatility,trading volume,and return using a hybrid approach that combines the Markov-switching regime with the vector autoregressive model(MS-VAR).The empirical findings are as follows:(1)The Chinese stock market can be divided into three regional systems:steady downward,steady upward,and high volatility.The three states have similar frequencies of occurrence,and their corresponding stable probabilities are not high,indicating that the Chinese stock market is unstable.(2)Asymmetric dynamic relationships exist between market volatility,investment return,and trading volume.For different regimes,while the effect of trading volume on volatility and return appears to be insignificant,the impacts of volatility and return on trading volume are considerably strong.(3)A regime-dependent,contemporaneous correlation between volatility and return is observed,which also reflects the behavior of the Chinese stock market“chasing up and down”.However,a positive contemporaneous correlation always exists between volatility and trading volumes in different regimes,indicating that uncertainty in the Chinese stock market is closely related to information inflow.
