While many studies document cross-stock predictability where returns of some stocks predict returns of other similar stocks, most evidence comes from US markets. Following Chen et al. (2019), we identify peer firms based on historical return similarity and construct a Peer Return Gap (PRG) measure, defined as the difference between a stock’s lagged return and its peers’ returns. Our empirical evidence from Chinese markets shows that past-return-linked peers strongly predict focal firm returns. A long-short portfolio sorted on PRG generates an equal-weighted monthly return of 1.26% (t = 3.81) and a Fama-French five-factor alpha of 1.10% (t = 2.86). These abnormal returns remain unexplained by several alternative factor models.

Using a comprehensive factor zoo, we document a notable factor MAX premium in the Chinese market. Factors with high maximum daily returns consistently outperform those with low maximum returns by 0.82% per month in the future, on a risk-adjusted basis. This premium remains robust controlling for various factor characteristics, and is not sensitive to the selection of factors. The factor MAX anomaly stands apart from lottery-type stock anomalies and contributes to elucidate most of these anomalies. The factor MAX premium concentrates in high-eigenvalue principal component factors, shedding light on the prevalent lottery preferences for factor investing in China’s A-share market. We document pronounced existence of factor MAX anomaly in the United States and other G7 countries.

Using a comprehensive factor zoo, we document a notable factor MAX premium in the Chinese market. Factors with high maximum daily returns consistently outperform those with low maximum returns by 0.82% per month in the future, on a risk-adjusted basis. This premium remains robust controlling for various factor characteristics, and is not sensitive to the selection of factors. The factor MAX anomaly stands apart from lottery-type stock anomalies and contributes to elucidate most of these anomalies. The factor MAX premium concentrates in high-eigenvalue principal component factors, shedding light on the prevalent lottery preferences for factor investing in China’s A-share market.