上周，小市值、价值风格占优，低波、低换手率因子表现相对较优。量化股票组合 中，沪深 300 增强组合周超额收益率 1.39%，2025 年累计超额收益 7.88%。 投资要点： 低频选股因子周报（2025.12.12-2025.12.19） [Table_Authors] 郑雅斌(分析师) 小市值、低估值风格占优，低波、低换手率因子表现优异 本报告导读： 风险提示：市场环境变动风险，有效因子变动风险。 | | 021-23219395 | | --- | --- | | | zhengyabin@gtht.com | | 登记编号 | S0880525040105 | | | 罗蕾(分析师) | | | 021-23185653 | | | luolei@gtht.com | | 登记编号 | S0880525040014 | [Table_Report] 相关报告 绝对收益产品及策略周报（251208-251212） 2025.12.18 大额买入与资金流向跟踪（20251208-20251212） 2025.12.16 上周大市值风格占优，分析师、盈利因子表现较 好 2025.12.16 风格 Smart ...

- The report mentions the construction of A-share sentiment index based on market volatility and transaction volume changes, dividing the market into four quadrants. Only the quadrant with "volatility up - transaction down" shows significant negative returns, while others show positive returns. This sentiment index includes bottom warning and top warning signals[36][39][42] - The A-share sentiment index currently indicates bearish signals for both bottom warning (price) and top warning (volume), resulting in an overall bearish outlook for the market[39][42] - The A-share prosperity index is constructed using the YoY growth of net profit attributable to the parent company of the Shanghai Composite Index as the Nowcasting target. The index shows a slow upward trend, indicating the current upward cycle[29][33][35] - The prosperity index value as of September 19, 2025, is 21.21, which has increased by 15.79 compared to the end of 2023, confirming the upward cycle[33][35] - The report applies the BARRA factor model to construct ten major style factors for the A-share market, including SIZE, BETA, MOM, RESVOL, NLSIZE, BTOP, LIQUIDITY, EARNINGS_YIELD, GROWTH, and LVRG[57][58][60] - Among style factors, BETA factor shows high excess returns, while RESVOL factor demonstrates significant negative excess returns. High BETA and high growth stocks perform well, whereas non-linear size and value factors underperform[58][59][61] - The report analyzes the performance attribution of major indices using factor models. Indices like CSI 500, ChiNext Index, and Wind All A exhibit strong exposure to BETA factor, leading to favorable performance in style factors. Conversely, indices like Shanghai Composite Index and SSE 50 show weaker exposure to BETA factor, resulting in poor performance in style factors[66][67][73] - The CSI 500 enhanced portfolio has generated a cumulative excess return of 48.55% relative to the CSI 500 index since 2020, with a maximum drawdown of -5.73%. However, its weekly performance is -0.24%, underperforming the benchmark by 0.56%[45][47][49] - The SSE 300 enhanced portfolio has achieved a cumulative excess return of 38.48% relative to the SSE 300 index since 2020, with a maximum drawdown of -5.86%. Its weekly performance is -0.95%, underperforming the benchmark by 0.50%[52][53][55]

- The report mentions the construction of the A-share prosperity index, which is based on the Nowcasting target of the year-on-year net profit of the Shanghai Composite Index's parent company. The details of the index construction can be found in the report "Perspective Analysis: Construction and Observation of A-share Prosperity High-frequency Index" [33][36] - The A-share sentiment index is constructed by dividing the market into four quadrants based on the direction of changes in volatility and trading volume. Among these, the quadrant with rising volatility and declining trading volume shows significant negative returns, while the others show significant positive returns. This index includes bottom-warning and top-warning signals. Relevant research is detailed in the report "Perspective Analysis: Construction and Observation of A-share Sentiment Index" [37][42] - The report evaluates the performance of the Middle 500 Enhanced Portfolio and the CSI 300 Enhanced Portfolio. The Middle 500 Enhanced Portfolio achieved a cumulative excess return of 50.56% relative to the Middle 500 Index since 2020, with a maximum drawdown of -4.99% [48][50]. The CSI 300 Enhanced Portfolio achieved a cumulative excess return of 38.85% relative to the CSI 300 Index since 2020, with a maximum drawdown of -5.86% [55][56] - The report constructs ten style factors for the A-share market based on the BARRA factor model. These include size (SIZE), beta (BETA), momentum (MOM), residual volatility (RESVOL), non-linear size (NLSIZE), valuation (BTOP), liquidity (LIQUIDITY), earnings yield (EARNINGS_YIELD), growth (GROWTH), and leverage (LVRG) [60] - The report highlights the recent performance of style factors. Beta factor showed the highest excess return, while momentum and non-linear size factors exhibited significant negative excess returns. High-beta stocks performed well, while value and profitability factors underperformed [61][64]

Quantitative Models and Construction Methods - **Model Name**: Index Enhanced Portfolio **Construction Idea**: The model aims to outperform benchmark indices by leveraging quantitative strategies and factor exposures[2][48] **Construction Process**: - The portfolio is constructed using a strategy model that selects stocks based on factor exposures and optimization techniques - The model incorporates historical data and factor analysis to identify stocks with high expected returns relative to the benchmark - Portfolio weights are optimized to maximize excess returns while controlling for risk and tracking error[48][49][54] **Evaluation**: The model has demonstrated consistent excess returns over its benchmark indices, showcasing its effectiveness in active management[48][54] - **Model Name**: Factor Attribution Model **Construction Idea**: This model decomposes portfolio or index returns into contributions from various style factors to understand performance drivers[68] **Construction Process**: - The model uses the BARRA factor framework, which includes factors such as size (SIZE), beta (BETA), momentum (MOM), residual volatility (RESVOL), non-linear size (NLSIZE), valuation (BTOP), liquidity (LIQUIDITY), earnings yield (EARNINGS_YIELD), growth (GROWTH), and leverage (LVRG)[58][68] - Factor exposures are calculated for each stock in the portfolio or index - Portfolio returns are attributed to factor contributions using regression-based methods[68] **Evaluation**: The model provides valuable insights into the sources of portfolio performance, aiding in strategy refinement and risk management[68] Model Backtesting Results - **Index Enhanced Portfolio**: - **Mid-Cap Enhanced Portfolio (CSI 500)**: Weekly return of 1.99%, outperforming the benchmark by 0.22%; cumulative excess return since 2020: 50.26%; maximum drawdown: -4.99%[48][49] - **Large-Cap Enhanced Portfolio (CSI 300)**: Weekly return of 1.85%, outperforming the benchmark by 0.61%; cumulative excess return since 2020: 34.90%; maximum drawdown: -5.86%[54][56] Quantitative Factors and Construction Methods - **Factor Name**: Momentum (MOM) **Construction Idea**: Captures the tendency of stocks with strong past performance to continue outperforming in the short term[58][59] **Construction Process**: - Momentum is calculated as the cumulative return over a specified look-back period (e.g., 6 months or 12 months) - Stocks are ranked based on their momentum scores, and portfolios are constructed by overweighting high-momentum stocks[58][59] **Evaluation**: Momentum factor exhibited high excess returns during the week, indicating strong market preference for trending stocks[59] - **Factor Name**: Beta (BETA) **Construction Idea**: Measures the sensitivity of a stock's returns to market movements, capturing risk exposure[58][59] **Construction Process**: - Beta is calculated using regression analysis of stock returns against market returns over a historical period - High-beta stocks are identified and analyzed for their risk-return trade-offs[58][59] **Evaluation**: High-beta stocks performed well during the week, reflecting market preference for riskier assets[59] - **Factor Name**: Growth (GROWTH) **Construction Idea**: Represents the expected earnings growth of a company, capturing future potential[58][59] **Construction Process**: - Growth is estimated using forward-looking metrics such as analyst earnings forecasts and historical growth rates - Stocks are ranked based on growth scores, and portfolios are constructed by overweighting high-growth stocks[58][59] **Evaluation**: Growth factor underperformed during the week, indicating reduced market preference for growth-oriented stocks[59] Factor Backtesting Results - **Momentum Factor**: Weekly excess return was significantly positive, outperforming other style factors[59][66] - **Beta Factor**: High-beta stocks showed strong performance, contributing positively to portfolio returns[59][66] - **Growth Factor**: Underperformed during the week, reflecting weak market sentiment toward growth stocks[59][66] Additional Observations - **Sector Factors**: - Defense, metals, and coal sectors exhibited high excess returns relative to market-cap-weighted benchmarks[59][63] - Sectors such as healthcare, IT, and media experienced significant drawdowns[59][63] - **Market Sentiment**: - Sentiment indicators based on volatility and trading volume suggest a bullish outlook for the market[36][39][41]