Replicating and Digesting Anomalies in the Chinese A-Share Market

Zhibing Li (), Laura Xiaolei Liu (), Xiaoyu Liu () and K. C. John Wei ()
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Zhibing Li: School of Banking and Finance, University of International Business and Economics, Beijing 100029, China
Laura Xiaolei Liu: Department of Finance, Guanghua School of Management, Peking University, Beijing 100871, China
Xiaoyu Liu: Department of Finance, Guanghua School of Management, Peking University, Beijing 100871, China
K. C. John Wei: School of Accounting and Finance, Faculty of Business, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

Management Science, 2024, vol. 70, issue 8, 5066-5090

Abstract: We replicate 469 anomaly variables similar to those studied by Hou et al. (2020) using Chinese A-share data and a reliable testing procedure with mainboard breakpoints and value-weighted returns. We find that 83.37% of the anomaly variables do not generate significant high-minus-low quintile raw return spreads. Further adjusting risk increases the failure rate slightly to 84.22% based on CAPM alphas and 86.99% based on Fama–French three-factor alphas. We show that the conventional procedure using all A-share breakpoints with equal-weighted returns for the anomaly test is indeed problematic as it assigns too much weight to microcaps and has a very limited investment capacity. The CH3-factor, CH4-factor, and q -factor models show the best performance over the whole sample period. The q -factor model is the best performer in the post-2007 subsample period after significant improvements occurred in China’s financial market environment, such as the completion of the split-share structure reform and the implementation of new accounting standards conforming to the International Financial Reporting Standards. The non–state-owned enterprise subsample in the post-2007 period is a cleaner sample in which the CH4-factor and q -factor models are the best performers.

Keywords: replication; Chinese A-share market; anomalies; factor models; SOEs versus non-SOEs (search for similar items in EconPapers)
Date: 2024
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