Retail Trading and Return Predictability in China

Charles M. Jones, cj88@gsb.columbia.edu, was with Columbia Business School, Donghui Shi, dhshi@fudan.edu.cn, is with Fudan University Fanhai International School of Finance, Xiaoyan Zhang (corresponding author), zhangxiaoyan@pbcsf.tsinghua.edu.cn, is with Tsinghua University PBC School of Finance, and Xinran Zhang, zhangxinran@cufe.edu.cn, is with the Central University of Finance and Economics School of Finance. Xiaoyan Zhang acknowledges the financial support from the National Natural Science Foundation of China [Grant No. 72350710220] and [Grant No.71790605]. Xinran Zhang acknowledges the financial support from the National Natural Science Foundation of China [Grant No. 72303268]. We thank an anonymous referee, Terrance Odean, Laruen Cohen, Ron Kaniel, Hao Zhou, Utpal Bhattacharya, Xintong Zhan, Darwin Choi, and seminar participants at Tsinghua PBC School of Finance, Renmin University, Shanghai Jiaotong University, Fudan University, Shanghai University of Finance and Economics, and conference audiences at the CIFFP, CFRC, CICF, and ABFER Annual Conference for their helpful comments and suggestions. All remaining errors are our own. Using comprehensive account-level data, we separate Chinese retail investors into five groups and document strong heterogeneity in trading dynamics and performances. Retail investors with smaller account sizes cannot predict future returns correctly, display daily momentum patterns, fail to process public news, and show overconfidence and gambling preferences; while retail investors with larger account balances predict future returns correctly, display contrarian patterns, and incorporate public news in trading. With Barber et al. (2009) performance measures, smaller retail investors suffer from poor stock selection abilities and trading costs, while large retail investors’ stock selection abilities are offset by trading costs.