Tracking Retail and Institutional Investors Activity in China

41 Pages Posted: 30 Nov 2023 Last revised: 20 Feb 2024

See all articles by Siyang Li

Siyang Li

PBCSF, Tsinghua University

J. (Julie) Wu

University of Nebraska - Lincoln

Xiaoyan Zhang

Tsinghua University - PBC School of Finance

Xinran Zhang

Central University of Finance and Economics (CUFE) - School of Finance

Date Written: October 20, 2023

Abstract

We show that classifying retail and institutional orders based on a commonly adopted order size algorithm in the Chinese stock market is problematic. To improve the accuracy of the algorithm, we explore the order patterns and uncover a higher tendency of retail investors trading in multiples of 500 shares. We modify the order size algorithm by incorporating the feature of share roundedness. Our modified algorithm improves the accuracy of identifying retail and institutional investors. Order imbalances derived from the modified algorithm better predict future stock returns.

Keywords: Order size, round lot, retail investors, institutional investors, Chinese stock market JEL code: G12, G14, G15 Order size, round lot, retail investors, institutional investors, Chinese stock market JEL code: G12, G14, G15

JEL Classification: G12, G14, G15

Suggested Citation

Li, Siyang and Wu, J. (Julie) and Zhang, Xiaoyan and Zhang, Xinran, Tracking Retail and Institutional Investors Activity in China (October 20, 2023). PBCSF-NIFR Research Paper, Available at SSRN: https://ssrn.com/abstract=4630162 or http://dx.doi.org/10.2139/ssrn.4630162

Siyang Li

PBCSF, Tsinghua University ( email )

J. (Julie) Wu

University of Nebraska - Lincoln ( email )

730 N. 14th Street
Lincoln, NE 68588
United States

Xiaoyan Zhang

Tsinghua University - PBC School of Finance ( email )

No. 43, Chengdu Road
Haidian District
Beijing 100083
China

Xinran Zhang (Contact Author)

Central University of Finance and Economics (CUFE) - School of Finance ( email )

Beijing
China

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