国泰海通｜金工：综合量化模型信号和日历效应，11月建议超配小盘风格、价值风格

Core Insights - The report suggests an overweight position in small-cap and value styles for November based on quantitative model signals and calendar effects [1][5] Size and Style Rotation Monthly Strategy - As of the end of October, the quantitative model signal was -0.17, indicating a preference for large-cap stocks; however, historical data shows that small-cap stocks tend to outperform in November [1] - The current market capitalization factor valuation spread is 0.88, which is still below the historical peak range of 1.7 to 2.6, indicating that the market is not overcrowded and small-cap stocks remain attractive in the medium to long term [1] - Year-to-date, the size rotation quantitative model has yielded a return of 27.85%, with an excess return of 2.86% relative to an equal-weight benchmark [1] - The combined strategy, incorporating subjective views, has achieved a return of 26.6% with an excess return of 1.61% [1] Value and Growth Style Rotation Monthly Strategy - The monthly quantitative model signal for October was 1, recommending an overweight position in value stocks [1] - Year-to-date, the value-growth style rotation strategy has returned 18.96%, with an excess return of 1.35% compared to an equal-weight benchmark of growth and value indices [1] Style Factor Performance Tracking - Among eight major factors, the dividend and momentum factors showed high positive returns in October, while large-cap and volatility factors exhibited high negative returns [2] - Year-to-date, the volatility and momentum factors have shown strong positive returns, while liquidity and large-cap factors have shown negative returns [2] - In October, the profitability, dividend yield, and momentum factors had high positive returns, while large-cap, profitability, and beta factors had high negative returns [2] - Year-to-date, the beta, profitability volatility, and momentum factors have shown strong positive returns, while mid-cap, liquidity, and large-cap factors have shown negative returns [2] Factor Covariance Matrix Update - The report updates the latest factor covariance matrix as of October 31, 2025, which is crucial for predicting stock portfolio risks [2]