Time and Dynamic Volume-Volatility Relation

Posted: 21 Mar 2006 Last revised: 17 Mar 2011

See all articles by Xiaoqing Eleanor Xu

Xiaoqing Eleanor Xu

Seton Hall University

Huaiyu Peter Chen

Youngstown State University

Chunchi Wu

SUNY at Buffalo - School of Management


This paper examines volume and volatility dynamics by accounting for market activity measured by the time duration between two consecutive transactions. A time-consistent vector autoregressive model (VAR) is employed to test the dynamic relationship between return volatility and trades using intraday irregularly spaced transaction data. The model is used to identify the informed and uninformed components of return volatility and to estimate the speed of price adjustment to new information. It is found that volatility and volume are persistent and highly correlated with past volatility and volume. The time duration between trades has a negative effect on the volatility response to trades and correlation between trades. Consistent with microstructure theory, shorter time duration between trades implies higher probability of news arrival and higher volatility. Furthermore, bid-ask spreads are serially dependent and strongly affected by the informed trading and inventory costs.

Keywords: Time duration, Volatility-volume dynamics, Informed trading, Bid-ask spreads

JEL Classification: G14

Suggested Citation

Xu, Xiaoqing Eleanor and Chen, Huaiyu Peter and Wu, Chunchi, Time and Dynamic Volume-Volatility Relation. Journal of Banking and Finance, Vol. 30, No. 5, pp. 1535-1558, 2006, Available at SSRN: https://ssrn.com/abstract=694182

Xiaoqing Eleanor Xu (Contact Author)

Seton Hall University ( email )

Department of Finance, Stillman School of Business
400 South Orange Avenue
South Orange, NJ 07079
United States
973-761-9209 (Phone)
973-961-9217 (Fax)

Huaiyu Peter Chen

Youngstown State University ( email )

Youngstown, OH 44555
United States

Chunchi Wu

SUNY at Buffalo - School of Management ( email )

Jacobs Management Center
Buffalo, NY 14222
United States

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