A-Share High-Correlation Stock Selection and Smart Beta Indexing

Summary

This research note examines why stocks with high correlation to their benchmark may perform better than low-correlation stocks in the China A-share market, despite findings cited for overseas markets. It explains benchmark correlation in terms of constituent volatility and beta, interpreting the high-correlation effect as combining lower volatility with higher beta exposure.

The proposed factor is each CSI 500 constituent’s correlation between daily returns and index returns over the prior quarter. The note reports a mean information coefficient of 0.07 and an ICIR of 1.46 over 2007–2018. Sorting stocks into five equal-weighted groups and rebalancing quarterly reportedly produced ordered returns; a long-short spread had an information ratio of 1.20. For an index variant, it selects the top fifth by correlation each quarter and weights constituents by correlation. The source says this index outperformed the CSI 500 on return, maximum drawdown, and win rate, but the excerpt gives no detailed performance figures or implementation costs. It warns that market structure, trading behavior, or crowding could weaken the strategy.

Key ideas

• The note interprets high benchmark correlation as exposure combining lower volatility and higher beta.
• The factor ranks CSI 500 constituents by their trailing-quarter correlation with index returns.
• The reported factor tests show a positive mean IC and ICIR over the stated sample period.
• A Smart Beta construction selects the highest-correlation fifth and weights stocks by correlation.
• The source warns that changing market conditions and crowding may undermine the results.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.