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China Center for Economic Research, National School of Development
Peking University, Beijing, 100871 We use heterogeneous autoregressive (HAR) model with high-frequency data
of Hu-Shen 300 index to investigate the volatility-volume relationship via
the volatility decomposition approach. Although we find that the continuous
component of daily volatility is positively correlated with trading volume,
the jump component reveals a significant and robust negative relation with
volume. This result suggests that the jump component contains some “public
information” while the continuous components are more likely driven by
“private information”. Discussion of the intertemporal relationship supports
the information-driven trading hypothesis. Lagged realized skewness only
significantly affects the continuous component.
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