大小盘风格轮动月度策略。 月度观点： 2 月底量化模型最新信号为 0.83 ，指向小盘。日历效应上，历史 3 月小盘相对占优；建议 3 月继续超配小盘风格。 中长期观点，当前市值因子估值价差为 0.86 ，近期有所下降，距离历史顶部区域 1.7~2.6 仍有距离，中长期并不拥挤，继续看好小盘。截止 2 月底，模型 本年收益 13.35% ，相对等权基准（ 7.47% ）的超额收益为 5.88% 。结合主观观点的策略收益 13.35% ，超额收益 5.88% 。策略构建详见报告《量化 视角多维度构建大小盘风格轮动策略 _20241102 》。 价值成长风格轮动月度策略。 月度观点： 2 月底量化模型信号为 -0.67 ，建议 3 月超配价值风格。中长期观点，未来一年更看好成长风格。截止 2 月底， 模型收益 5.22% ，相对等权基准（ 5.22% ）的超额收益为 0% 。策略构建详见报告《量化视角多维度构建月度和周度价值成长风格轮动策略 _20250305 》。 风格因子表现跟踪。 8 个大类因子中，本月流动性、动量因子正向收益较高；大市值、质量因子负向收益较高。本年价值、波动率因子正向收益较高；大市 值、质 ...

Core Insights - The report suggests an overweight allocation to large-cap and value styles for December based on quantitative model signals and calendar effects [1][2]. Size and Style Rotation Monthly Strategy - The latest quantitative model signal for the end of November is -0.17, indicating a preference for large-cap stocks. Historically, large-cap stocks have outperformed in December, leading to a recommendation for an overweight allocation in December [1]. - The year-to-date return for the size rotation quantitative model is 24.71%, with an excess return of 1.5% compared to an equal-weight benchmark of 23.21% [1]. - The combined strategy, incorporating subjective views, has yielded a return of 26.1%, with an excess return of 2.89% [1]. Value and Growth Style Rotation Monthly Strategy - The monthly quantitative model signal is -0.33, indicating a preference for value stocks. Historically, value style has slightly outperformed in December, leading to a recommendation for an overweight allocation in December [2]. - The year-to-date return for the value-growth style rotation model is 20.37%, with an excess return of 2.99% compared to an equal-weight benchmark of 16.88% [2]. Style Factor Performance Tracking - Among eight major factors, dividend and quality factors showed high positive returns in November, while large-cap and momentum factors exhibited high negative returns [2]. - For the year, volatility and growth factors had high positive returns, while liquidity and large-cap factors had high negative returns [2]. - In November, residual volatility, short-term reversal, and earnings quality factors had high positive returns, while momentum, profitability, and large-cap factors had high negative returns [2]. Factor Covariance Matrix Update - The report updates the latest factor covariance matrix as of November 28, 2025, which is essential for predicting stock portfolio risks using a multi-factor model [3].