中国股市20年：因子如何创造Alpha机会？

Core Insights - Style factors serve as a stable foundation for stock portfolios, with changes in factor correlations expected to create tactical Alpha opportunities [2][19] - Chinese stock factors exhibit significant long-term risk-return characteristics, with style factors showing statistically significant risk-adjusted returns exceeding market factors [2][4] Long-term Performance of Pure Factor Portfolios - Over the past 20 years (2005-2024), the annualized return for the market factor is 4.2% with a volatility of 26.9%, resulting in a risk-adjusted return of only 0.16, which is statistically insignificant [2] - Among 14 style factors analyzed, nine demonstrated statistically significant risk-adjusted returns, with a threshold of 0.44 for significance [2] - Notable annualized returns for specific factors include: - Momentum: 4.9% - Earnings: 2.7% - Valuation: 2.1% - Growth: 1.7% - Beta: 6.6% [2] Recent Performance of Style Factors - The returns of style factors vary based on market mechanisms, particularly the beta factor, which shows a return of 1.5% in the top quintile of market returns and drops to -0.1% in the bottom quintile [6] - Earnings yield, beta, momentum, and profit factors exhibit significant volatility depending on market performance [6] Changes in Factor Correlations - The correlation between long-term value and beta has shifted from near zero to a historical low of -0.65, indicating a growing presence of stocks with both value and defensive characteristics [13] - Momentum's correlation with beta also decreased to -0.70 but has since rebounded to -0.40, while the correlation between value and momentum has returned to near zero from a historical high of 0.78 [13] Tactical Alpha Opportunities - The dispersion of style factor returns is currently above average, with a 12-week moving average dispersion of 0.45%, close to the 75th percentile of the past 20 years [19] - High dispersion indicates inconsistent factor performance, potentially allowing skilled active managers to achieve Alpha by deviating from benchmark indices [19]