Overnight Momentum, Informational Shocks, and Late-Informed Trading in China

43 Pages Posted: 5 Nov 2019

See all articles by Ya Gao

Ya Gao

Tianjin University - College of Management and Economics

Xing Han

University of Otago - Department of Accountancy and Finance; Ghent University - Department of Financial Economics

Youwei Li

Hull University Business School

Xiong Xiong

College of Management and Economics and China Center for Social Computing and Analytics

Date Written: October 26, 2019

Abstract

Based on high-frequency firm-level data, this paper uncovers new empirical patterns on intraday momentum in China. First, there exists a strong intraday momentum effect at the firm level. Second, the intraday predictability stems mainly from the overnight component rather than the opening half-hour component, which is consistent with the microstructure features of the Chinese market. Third, the intraday predictability attenuates (strengthens) following large positive (negative) informational shocks, implying a striking asymmetric reaction by market participants. Finally, we document that late-informed traders are relatively less experienced or skillful. Overall, the empirical results lend support to the model of late-informed trading.

Keywords: intraday momentum, overnight return, price jump, late-informed trading

JEL Classification: G12, G14, G15, G17

Suggested Citation

Gao, Ya and Han, Xing and Li, Youwei and Xiong, Xiong, Overnight Momentum, Informational Shocks, and Late-Informed Trading in China (October 26, 2019). Available at SSRN: https://ssrn.com/abstract=3475882 or http://dx.doi.org/10.2139/ssrn.3475882

Ya Gao

Tianjin University - College of Management and Economics

NO.92 Weijin Road
Nankai District
Tianjin, 300072
China

Xing Han

University of Otago - Department of Accountancy and Finance ( email )

PO Box 56
Dunedin, 9054
New Zealand

Ghent University - Department of Financial Economics ( email )

Sint-Pietersplein 5
Ghent, 9000
Belgium

Youwei Li (Contact Author)

Hull University Business School ( email )

University of Hull
Hull, HU6 7RX
United Kingdom

Xiong Xiong

College of Management and Economics and China Center for Social Computing and Analytics ( email )

92, Weijin Road
Nankai District
Tianjin, Tianjin 300072
China

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