中邮因子周报：价值风格承压，小盘股占优-20251103

• The report tracks the performance of style factors, including liquidity, volatility, and nonlinear market capitalization, which showed strong long positions, while valuation, profitability, and leverage factors exhibited strong short positions [2][16] - Barra style factors are constructed using various financial and technical metrics, such as historical beta, logarithm of total market capitalization, historical excess return momentum, and volatility calculated as a weighted combination of historical excess return volatility, cumulative excess return deviation, and residual return volatility [14][15] - Liquidity factor is calculated as a weighted combination of monthly turnover rate (35%), quarterly turnover rate (35%), and annual turnover rate (30%) [15] - Profitability factor is constructed using a weighted combination of analyst forecast earnings-to-price ratio (68%), inverse cash flow ratio (21%), inverse PE ratio (11%), forecast long-term earnings growth rate (18%), and forecast short-term earnings growth rate (11%) [15] - Growth factor is calculated using a weighted combination of earnings growth rate (24%) and revenue growth rate (47%) [15] - Leverage factor is constructed using market leverage ratio (38%), book leverage (35%), and asset-liability ratio (27%) [15] - GRU models, including open1d, close1d, barra1d, and barra5d, are tracked for their multi-factor performance across different stock pools, showing varied results in terms of long-short returns [3][4][5][6] - GRU models demonstrated strong performance in certain configurations, such as close1d and barra5d, while open1d and barra1d showed weaker returns in specific periods [31][33] - Multi-factor portfolios underperformed this week, with relative excess returns against the CSI 1000 index showing a decline of 0.95% [33][34] - Barra5d model exhibited strong year-to-date performance, achieving an excess return of 5.81% against the CSI 1000 index [33][34] - Technical factors, including short-term and long-term momentum and volatility metrics, showed mixed results across different stock pools, with short-term metrics generally outperforming [19][21][24][26] - Basic financial factors, such as static financial metrics and growth-related metrics, generally showed negative long-short returns, with low-growth stocks outperforming [19][21][24][26] - GRU models' long-short returns varied across stock pools, with close1d and barra5d models showing strong positive returns, while open1d and barra1d models experienced slight pullbacks [31][33] - The liquidity factor achieved a weekly return of 1.39%, while the volatility factor returned 0.92% over the same period [17] - Profitability factor showed a weekly return of -1.31%, and valuation factor returned -1.53% [17] - Growth factor achieved a weekly return of 0.21%, while leverage factor returned -0.83% [17] - GRU models' weekly returns included -0.82% for open1d, 2.88% for close1d, -0.45% for barra1d, and 1.23% for barra5d [31] - Multi-factor portfolio weekly return was -0.95% relative to the CSI 1000 index [34]