An Empirical Study of Volatility and Trading Volume Dynamics Using High-Frequency Data

This paper examines the dynamic relationship of volatility and trading volume using a bivariate vector autoregressive methodology. This study found bidirectional causal relations between trading volume and volatility, which is in accordance with sequential information arrival hypothesis that suggests lagged values of trading volume provide the predictability component of current volatility. Findings also reveal that trading volume shocks significantly contribute to the variability of volatility and then volatility shocks partly account for the variability of trading volume