Intraday Volume-Volatility Dynamics in CSI 300 Futures Market

Abstract

Using 1-min transaction data, this study investigates the relationship between volume and volatility in CSI 300 futures market in China. Unit root test indicates that return series are stationary. LB-Q and ARCH-LM statistics confirm volatility clustering and time-vary volatility. ARMA (2, 2)-EGARCH (1, 1) model find evidence of GARCH effect, and positive shocks have a greater impact on volatility than negative shocks. Furthermore, the coefficients of both contemporaneous and lagged volume are positive and significant statistically, indicate that volume as information flow indicators, may explain the volatility, Both MDH and SIA hypothesizes are verified in China. These findings have significant implications for the traders and policymakers.