中证500指数增强超额难度提升，传统多因子框架如何应对？ ——量化策略演进手记系列之一

Core Insights - The difficulty of achieving excess returns in the CSI 500 index enhancement has increased significantly since 2021, with excess returns declining to levels comparable to the CSI 300 index in recent years [44] Group 1: Index Performance and Trends - As of Q3 2025, the largest index-enhanced funds in China are those tracking the CSI 300 and CSI 500, with total assets exceeding 100 billion yuan [1] - The average annual excess returns for the CSI 500 have been around 2% in the last three years, while the CSI 1000 has maintained an average of over 6% [4][6] - The concentration of individual stock weights in the CSI 500 has increased, leading to a decrease in the margin for error in stock selection [11] Group 2: Factor Performance - The effectiveness of traditional factors in the CSI 500 has declined, with many factors showing reduced Information Coefficient (IC) values since 2015 [12] - The average IC for various factors indicates that the CSI 1000 outperforms the CSI 500 and CSI 300, particularly in growth and value factors [13] - The correlation between the 12-month IC and subsequent month IC has weakened, indicating a decline in the effectiveness of widely used factor momentum strategies [17] Group 3: Improvement Strategies for Index Enhancement - Strategies to enhance the CSI 500 index include stricter limits on individual stock weight deviations to manage concentration risk [19] - Relaxing industry deviation limits is suggested to capture opportunities in rapidly changing market sectors, as industry contributions have shown significant variability [21][22] - Adjustments to factor exposure rules are proposed to better align with changing market conditions and improve overall portfolio performance [30][35] - The adjustment of factor effectiveness assessment methods is necessary, as traditional metrics have shown diminishing returns in recent years [38] - Exploring the dual use of certain factors, particularly those with historical reverse returns, is recommended to enhance strategy robustness [41]