Quantitative Models and Construction Methods - **Model Name**: Comprehensive Volume-Price Factor **Model Construction Idea**: This factor integrates 11 sub-factors derived from high-frequency data to capture volume and price dynamics in the market. The aim is to smooth high-frequency data into monthly frequency to reduce turnover while maintaining strong stock selection capabilities[6][41] **Model Construction Process**: 1. The 11 sub-factors include "Moderate Adventure," "Complete Tide," "Climbing Peaks," "Team Coin," "Clouds Disperse," "Moth to Flame," "Grass in the Wind," "Sailing in Water," "Hidden in the Forest," "Wait and Rescue," and "Long-Short Game"[6][41] 2. Each sub-factor is calculated using high-frequency data (minute-level), except for "Team Coin," which uses daily data[41] 3. The high-frequency data is smoothed to monthly frequency to reduce turnover[41] 4. The 11 sub-factors are orthogonalized and equally weighted to form the comprehensive volume-price factor[45] **Model Evaluation**: The comprehensive factor significantly outperforms individual sub-factors, demonstrating enhanced performance metrics such as higher information ratios and lower maximum drawdowns[45] - **Model Name**: Expectation Inertia Factor **Model Construction Idea**: This factor analyzes the relationship between analyst expectations, momentum, and valuation, aiming to capture the persistence of expectations in the market[51] **Model Construction Process**: 1. The factor is derived from the analysis of analyst forecast revisions and their impact on stock prices[51] 2. It incorporates momentum and valuation metrics to identify stocks with consistent upward or downward revisions in expectations[51] **Model Evaluation**: The factor maintains stable upward trends in both long-short and long-only portfolios, with no significant drawdowns observed[51] Model Backtesting Results - **Comprehensive Volume-Price Factor**: - Rank IC: -12.64% - Rank ICIR: -5.48 - Annualized Return: 49.23% - Annualized Volatility: 10.66% - Information Ratio (IR): 4.62 - Monthly Win Rate: 91.94% - Maximum Drawdown: -4.84%[45] - **Expectation Inertia Factor**: - Long-Short Portfolio Net Value: Stable upward trend with no significant drawdowns[51][53] - Long-Only Portfolio Net Value: Stable upward trend with no significant drawdowns[51][55] Quantitative Factors and Construction Methods - **Factor Name**: Moderate Adventure **Factor Construction Idea**: Captures alpha information during moments of significant volume surges[41] **Factor Construction Process**: Derived from high-frequency volume data, smoothed to monthly frequency[41] **Factor Evaluation**: Demonstrates strong stock selection ability with a Rank ICIR of -4.87[43] - **Factor Name**: Complete Tide **Factor Construction Idea**: Analyzes tidal changes in individual stock trading volumes[41] **Factor Construction Process**: Derived from high-frequency volume data, smoothed to monthly frequency[41] **Factor Evaluation**: Rank ICIR of -4.15, indicating robust performance[43] - **Factor Name**: Climbing Peaks **Factor Construction Idea**: Focuses on changes in individual stock volatility[41] **Factor Construction Process**: Derived from high-frequency volatility data, smoothed to monthly frequency[41] **Factor Evaluation**: Rank ICIR of 4.89, showcasing strong predictive power[43] - **Factor Name**: Team Coin **Factor Construction Idea**: Identifies momentum effects in individual stocks[41] **Factor Construction Process**: Derived from daily momentum data, smoothed to monthly frequency[41] **Factor Evaluation**: Rank ICIR of -4.62, indicating effective stock selection[43] - **Factor Name**: Clouds Disperse **Factor Construction Idea**: Explores the volatility of volatility and investor ambiguity aversion[41] **Factor Construction Process**: Derived from high-frequency volatility data, smoothed to monthly frequency[41] **Factor Evaluation**: Rank ICIR of -4.72, demonstrating strong performance[43] - **Factor Name**: Moth to Flame **Factor Construction Idea**: Improves amplitude factors by analyzing stock price jumps[41] **Factor Construction Process**: Derived from high-frequency price jump data, smoothed to monthly frequency[41] **Factor Evaluation**: Rank ICIR of -4.69, indicating robust predictive ability[43] - **Factor Name**: Grass in the Wind **Factor Construction Idea**: Examines extreme return distortions and decision-making weights[41] **Factor Construction Process**: Derived from high-frequency return data, smoothed to monthly frequency[41] **Factor Evaluation**: Rank ICIR of -4.49, showcasing strong stock selection ability[43] - **Factor Name**: Sailing in Water **Factor Construction Idea**: Analyzes market-following behavior in individual stock turnover[41] **Factor Construction Process**: Derived from high-frequency turnover data, smoothed to monthly frequency[41] **Factor Evaluation**: Rank ICIR of -5.00, indicating strong performance[43] - **Factor Name**: Hidden in the Forest **Factor Construction Idea**: Decomposes factors driving individual stock price changes[41] **Factor Construction Process**: Derived from high-frequency price data, smoothed to monthly frequency[41] **Factor Evaluation**: Rank ICIR of -5.67, demonstrating robust predictive power[43] - **Factor Name**: Wait and Rescue **Factor Construction Idea**: Analyzes follow-up effects after large trades[41] **Factor Construction Process**: Derived from high-frequency trade data, smoothed to monthly frequency[41] **Factor Evaluation**: Rank ICIR of -4.23, showcasing effective stock selection[43] Factor Backtesting Results - **Moderate Adventure Factor**: - Rank IC: -9.42% - Rank ICIR: -4.87 - Annualized Return: 39.04% - Annualized Volatility: 9.21% - IR: 4.24 - Monthly Win Rate: 90.32% - Maximum Drawdown: -5.58%[43] - **Complete Tide Factor**: - Rank IC: -7.70% - Rank ICIR: -4.15 - Annualized Return: 25.63% - Annualized Volatility: 8.74% - IR: 2.93 - Monthly Win Rate: 81.45% - Maximum Drawdown: -8.19%[43] - **Climbing Peaks Factor**: - Rank IC: 6.07% - Rank ICIR: 4.89 - Annualized Return: 21.03% - Annualized Volatility: 5.75% - IR: 3.65 - Monthly Win Rate: 87.90% - Maximum Drawdown: -2.55%[43] - **Team Coin Factor**: - Rank IC: -9.73% - Rank ICIR: -4.62 - Annualized Return: 39.63% - Annualized Volatility: 10.93% - IR: 3.63 - Monthly Win Rate: 82.26% - Maximum Drawdown: -8.63%[43] - **Clouds Disperse Factor**: - Rank IC: -10.27% - Rank ICIR: -4.72 - Annualized Return: 30.76% - Annualized Volatility: 9.17% - IR: 3.35 - Monthly Win Rate: 83.87% - Maximum Drawdown: -6.86%[43] - **Moth to Flame Factor**: - Rank IC: -9.36% - Rank ICIR: -4.69 - Annualized Return: 38.15% - Annualized Volatility: 10.10% - IR: 3.78 - Monthly Win Rate: 90.32% - Maximum Drawdown: -6.19%[43] - **Grass in the Wind Factor**: - Rank IC: -8.92% - Rank ICIR: -4.49 - Annualized Return: 32.37% - Annualized Volatility: 8.21% - IR: 3.94 - Monthly Win Rate: 85.48% - Maximum Drawdown: -4.05%[43] - **Sailing in Water Factor**: - Rank IC: -9.13% - Rank ICIR: -5.00 - Annualized Return: 34.76% - Annualized Volatility

Group 1: Weekly Index Enhanced Portfolio Performance - The CSI 300 index enhanced portfolio achieved an excess return of 0.73% this week and 19.95% year-to-date [1][7] - The CSI 500 index enhanced portfolio recorded an excess return of -0.02% this week and 7.36% year-to-date [1][7] - The CSI 1000 index enhanced portfolio had an excess return of -0.31% this week and 15.60% year-to-date [1][7] - The CSI A500 index enhanced portfolio saw an excess return of 0.09% this week and 9.62% year-to-date [1][7] Group 2: Factor Performance Tracking - In the CSI 300 component stocks, factors such as three-month earnings adjustments, standardized unexpected earnings, and quarterly net profit year-on-year growth performed well [1][8] - In the CSI 500 component stocks, factors like quarterly ROA, quarterly ROE, and non-liquidity shocks showed strong performance [1][8] - For the CSI 1000 component stocks, factors including quarterly ROA, quarterly revenue year-on-year growth, and quarterly ROE performed well [1][8] - In the CSI A500 index component stocks, factors such as three-month earnings adjustments, one-year momentum, and standardized unexpected earnings performed well [1][8] Group 3: Public Fund Index Enhanced Product Performance Tracking - The CSI 300 index enhanced products had a maximum excess return of 1.75%, a minimum of -0.80%, and a median of 0.21% this week [1][21] - The CSI 500 index enhanced products recorded a maximum excess return of 0.44%, a minimum of -1.50%, and a median of -0.29% this week [1][23] - The CSI 1000 index enhanced products had a maximum excess return of 0.83%, a minimum of -1.22%, and a median of -0.27% this week [1][27] - The CSI A500 index enhanced products achieved a maximum excess return of 1.02%, a minimum of -0.67%, and a median of 0.01% this week [1][28]

证券研究报告 | 2025年12月13日 多因子选股周报 质量因子表现出色，沪深 300 增强组合年内超额 19.95% 核心观点 金融工程周报 国信金工指数增强组合表现跟踪 因子表现监控 以沪深 300 指数为选股空间。最近一周，3 个月盈利上下调、标准化预期外 盈利、单季净利同比增速等因子表现较好，而高管薪酬、股息率、预期 BP 等因子表现较差。 以中证 500 指数为选股空间。最近一周，单季 ROA、单季 ROE、非流动性 冲击等因子表现较好，而 SPTTM、单季 SP、预期 BP 等因子表现较差。 以中证 1000 指数为选股空间。最近一周，单季 ROA、单季营利同比增速、 单季 ROE 等因子表现较好，而 BP、预期 BP、一个月波动等因子表现较差。 以中证 A500 指数为选股空间。最近一周，3 个月盈利上下调、一年动量、 标准化预期外盈利等因子表现较好，而单季 SP、股息率、SPTTM 等因子表 现较差。 以公募重仓指数为选股空间。最近一周，一年动量、预期净利润环比、单季 净利同比增速等因子表现较好，而股息率、SPTTM、BP 等因子表现较差。 公募基金指数增强产品表现跟踪 目前，公募基金沪深 ...

一、本周指数增强组合表现 沪深300指数增强组合本周超额收益0.68%，本年超额收益18.98%。 中证500指数增强组合本周超额收益0.13%，本年超额收益7.30%。 中证1000指数增强组合本周超额收益0.77%，本年超额收益15.97%。 中证A500指数增强组合本周超额收益0.87%，本年超额收益9.47%。 二、本周选股因子表现跟踪 沪深300成分股中单季ROE、三个月机构覆盖、EPTTM等因子表现较好。 中证500成分股中BP、三个月换手、预期BP等因子表现较好。 中证1000成分股中单季EP、预期EPTTM、EPTTM等因子表现较好。 中证A500指数成分股中单季ROE、三个月机构覆盖、单季ROA等因子表现较 好。 公募基金重仓股中预期EPTTM、三个月机构覆盖、预期BP等因子表现较 好。 三、本周公募基金指数增强产品表现跟踪 沪深300指数增强产品本周超额收益最高1.01%，最低-0.79%，中位数 0.18%。 中证500指数增强产品本周超额收益最高1.26%，最低-0.76%，中位数 0.38%。 中证1000指数增强产品本周超额收益最高1.20%，最低-0.85%，中位数 0.54%。 ...

- The report tracks the performance of Guosen's quantitative enhanced index portfolios and public fund enhanced index products, as well as the performance of common stock selection factors in different stock selection spaces[11][12][15] - Guosen's quantitative enhanced index portfolios are constructed based on multi-factor stock selection, targeting benchmarks such as CSI 300, CSI 500, CSI 1000, and CSI A500 indices, aiming to consistently outperform their respective benchmarks[11][12] - The construction process of Guosen's enhanced index portfolios includes three main components: return prediction, risk control, and portfolio optimization[12] - The MFE (Maximized Factor Exposure) portfolio is used to test the effectiveness of individual factors under real-world constraints, such as industry exposure, style exposure, stock weight deviation, and turnover rate. The optimization model maximizes single-factor exposure while adhering to these constraints[41][42][43] - The MFE optimization model is expressed as follows: $\begin{array}{ll}max&f^{T}\ w\\ s.t.&s_{l}\leq X(w-w_{b})\leq s_{h}\\ &h_{l}\leq H(w-w_{b})\leq h_{h}\\ &w_{l}\leq w-w_{b}\leq w_{h}\\ &b_{l}\leq B_{b}w\leq b_{h}\\ &\mathbf{0}\leq w\leq l\\ &\mathbf{1}^{T}\ w=1\end{array}$ where $f$ represents factor values, $w$ is the stock weight vector, and the constraints include limits on style factor exposure ($X$), industry exposure ($H$), stock weight deviation, and component stock weight proportions ($B_b$)[41][42][43] - The report also evaluates the performance of single-factor MFE portfolios across different stock selection spaces, including CSI 300, CSI 500, CSI 1000, CSI A500, and public fund heavy-holding indices[15][18][20][22][24][26] - The factor library includes over 30 factors categorized into valuation, reversal, growth, profitability, liquidity, volatility, corporate governance, and analyst-related dimensions. Examples include BP (Book-to-Price), single-quarter ROE, one-month reversal, and three-month turnover[16][17] - The public fund heavy-holding index is constructed using the holdings of ordinary stock funds and equity-biased hybrid funds. Stocks are selected based on cumulative weight reaching 90% of the average fund holdings[44] - The report tracks the excess returns of public fund enhanced index products for CSI 300, CSI 500, CSI 1000, and CSI A500 indices. For example, in the CSI 300 enhanced products, the highest weekly excess return was 1.01%, and the highest annual excess return was 11.97%[28][32][35][37][40]

Quantitative Models and Construction Methods - **Model Name**: Securities Firm Golden Stock Performance Enhancement Portfolio **Model Construction Idea**: The model aims to optimize the selection of stocks from the securities firm's golden stock pool to outperform the benchmark index, specifically the actively managed equity fund index. It leverages a multi-factor approach and portfolio optimization techniques to control deviations in individual stocks and styles while aligning with the industry distribution of public funds[37][42]. **Model Construction Process**: 1. Use the securities firm's golden stock pool as the stock selection space and constraint benchmark. 2. Apply a multi-factor model to further refine the stock selection within the pool. 3. Optimize the portfolio to control deviations in individual stocks and styles relative to the golden stock pool. 4. Use the industry distribution of all public funds as the industry allocation benchmark. 5. Adjust the portfolio at the beginning of each month based on the latest recommendations and market data[37][42]. **Model Evaluation**: The model demonstrates strong alpha generation potential and consistently outperforms the benchmark index, reflecting the research strength of securities firms[42]. Model Backtesting Results - **Securities Firm Golden Stock Performance Enhancement Portfolio**: - **Absolute Return (Monthly)**: -1.06% (20251103-20251128)[41] - **Excess Return (Monthly)**: +1.39% relative to the actively managed equity fund index[41] - **Absolute Return (Year-to-Date)**: +33.65% (20250102-20251128)[41] - **Excess Return (Year-to-Date)**: +4.42% relative to the actively managed equity fund index[41] - **Ranking in Actively Managed Equity Funds (Year-to-Date)**: 35.37th percentile (1227/3469)[41] - **Annualized Return (2018-2025)**: +19.34%[43] - **Annualized Excess Return (2018-2025)**: +14.38% relative to the actively managed equity fund index[43] - **Performance Ranking (2018-2025)**: Top 30% of actively managed equity funds every year[43] Quantitative Factors and Construction Methods - **Factor Name**: Total Market Capitalization **Factor Construction Idea**: Reflects the size of a company, often used to capture the size effect in stock returns[26][27]. **Factor Construction Process**: Calculate the total market capitalization of each stock in the golden stock pool. Group stocks into quintiles based on their market capitalization and calculate the long-short portfolio returns for each group[26][27]. **Factor Evaluation**: Demonstrates strong performance in both the recent month and year-to-date periods[26][27]. - **Factor Name**: Single-Quarter Revenue Growth **Factor Construction Idea**: Measures the growth in revenue over a single quarter, capturing the growth potential of a company[26][27]. **Factor Construction Process**: Compute the quarter-over-quarter revenue growth for each stock. Group stocks into quintiles based on their growth rates and calculate the long-short portfolio returns for each group[26][27]. **Factor Evaluation**: Exhibits strong performance year-to-date[26][27]. - **Factor Name**: SUR (Surprise) **Factor Construction Idea**: Captures the degree to which a company's earnings or revenue exceed market expectations[26][27]. **Factor Construction Process**: Calculate the difference between actual and expected earnings or revenue for each stock. Group stocks into quintiles based on their surprise levels and calculate the long-short portfolio returns for each group[26][27]. **Factor Evaluation**: Performs well in both the recent month and year-to-date periods[26][27]. - **Factor Name**: EPTTM (Earnings to Price Trailing Twelve Months) **Factor Construction Idea**: A valuation factor that measures the earnings yield of a stock[26][27]. **Factor Construction Process**: Compute the ratio of trailing twelve-month earnings to the current stock price for each stock. Group stocks into quintiles based on their EPTTM values and calculate the long-short portfolio returns for each group[26][27]. **Factor Evaluation**: Underperforms year-to-date[26][27]. - **Factor Name**: Expected Dividend Yield **Factor Construction Idea**: Reflects the expected return from dividends, often used as a value factor[26][27]. **Factor Construction Process**: Calculate the expected dividend yield for each stock. Group stocks into quintiles based on their yields and calculate the long-short portfolio returns for each group[26][27]. **Factor Evaluation**: Underperforms year-to-date[26][27]. - **Factor Name**: BP (Book-to-Price Ratio) **Factor Construction Idea**: A valuation factor that measures the book value relative to the stock price[26][27]. **Factor Construction Process**: Compute the ratio of book value to stock price for each stock. Group stocks into quintiles based on their BP values and calculate the long-short portfolio returns for each group[26][27]. **Factor Evaluation**: Underperforms year-to-date[26][27]. Factor Backtesting Results - **Total Market Capitalization**: Strong performance in the recent month and year-to-date[26][27] - **Single-Quarter Revenue Growth**: Strong performance year-to-date[26][27] - **SUR (Surprise)**: Strong performance in the recent month and year-to-date[26][27] - **EPTTM (Earnings to Price Trailing Twelve Months)**: Weak performance year-to-date[26][27] - **Expected Dividend Yield**: Weak performance year-to-date[26][27] - **BP (Book-to-Price Ratio)**: Weak performance year-to-date[26][27]

Quantitative Models and Construction Methods - **Model Name**: Securities Firm Golden Stock Performance Enhancement Portfolio **Model Construction Idea**: The model aims to optimize the selection of stocks from the securities firm golden stock pool, using a multi-factor approach to achieve stable outperformance relative to the benchmark index (Active Equity Hybrid Fund Index) [37][42] **Model Construction Process**: 1. The securities firm golden stock pool is used as the stock selection space and constraint benchmark [42] 2. The portfolio optimization method is applied to control deviations in individual stocks and styles between the portfolio and the golden stock pool [42] 3. The industry allocation is based on the distribution of all public funds [42] 4. The portfolio's benchmark is the Active Equity Hybrid Fund Index, and the portfolio's position last month was 90.48% [37] **Model Evaluation**: The model demonstrates strong alpha generation potential and stable performance, consistently outperforming the benchmark index over multiple years [42][43] Model Backtesting Results - **Securities Firm Golden Stock Performance Enhancement Portfolio**: - **Absolute Return (Monthly)**: -1.06% [41] - **Excess Return (Monthly)**: 1.39% relative to the Active Equity Hybrid Fund Index [41] - **Absolute Return (Year-to-Date)**: 33.65% [41] - **Excess Return (Year-to-Date)**: 4.42% relative to the Active Equity Hybrid Fund Index [41] - **Ranking in Active Equity Funds (Year-to-Date)**: 35.37% percentile (1227/3469) [41] - **Annualized Return (2018-2025)**: 19.34% [43] - **Annualized Excess Return (2018-2025)**: 14.38% relative to the Active Equity Hybrid Fund Index [43] - **Performance Ranking (2018-2025)**: Top 30% of active equity funds every year [43] Quantitative Factors and Construction Methods - **Factor Name**: Total Market Capitalization **Factor Construction Idea**: Reflects the size of a company, often used to capture size-related effects in stock returns [26][27] **Factor Evaluation**: Demonstrated strong performance both in the past month and year-to-date [26][27] - **Factor Name**: Single-Quarter Surprise (SUR) **Factor Construction Idea**: Measures the degree of earnings surprise in a single quarter, capturing the market's reaction to unexpected earnings [26][27] **Factor Evaluation**: Performed well in both the past month and year-to-date [26][27] - **Factor Name**: Single-Quarter Revenue Growth **Factor Construction Idea**: Tracks the growth rate of revenue in a single quarter, reflecting a company's operational growth [26][27] **Factor Evaluation**: Strong performance year-to-date [26][27] - **Factor Name**: EPTTM (Earnings to Price Trailing Twelve Months) **Factor Construction Idea**: A valuation factor that measures earnings relative to price over the trailing twelve months [26][27] **Factor Evaluation**: Underperformed year-to-date [26][27] - **Factor Name**: Expected Dividend Yield **Factor Construction Idea**: Captures the expected dividend income relative to the stock price, often used as an income-focused valuation metric [26][27] **Factor Evaluation**: Underperformed year-to-date [26][27] - **Factor Name**: BP (Book-to-Price Ratio) **Factor Construction Idea**: A valuation factor that measures the book value of equity relative to the stock price [26][27] **Factor Evaluation**: Underperformed year-to-date [26][27] Factor Backtesting Results - **Total Market Capitalization**: Strong performance in both the past month and year-to-date [26][27] - **Single-Quarter Surprise (SUR)**: Strong performance in both the past month and year-to-date [26][27] - **Single-Quarter Revenue Growth**: Strong performance year-to-date [26][27] - **EPTTM**: Weak performance year-to-date [26][27] - **Expected Dividend Yield**: Weak performance year-to-date [26][27] - **BP (Book-to-Price Ratio)**: Weak performance year-to-date [26][27]

- The report highlights that in November 2025, the top-performing factors in the broker's gold stock pool were total market capitalization, single-quarter revenue surprise, and SUR, while factors like intraday return, analyst net upgrade magnitude, and analyst net upgrade ratio performed poorly[3][26] - For the year 2025, the best-performing factors were total market capitalization, single-quarter revenue growth, and SUR, whereas EPTTM, expected dividend yield, and BP underperformed[3][26] - The broker's gold stock performance enhancement portfolio achieved an absolute return of -1.06% for the month (20251103-20251128) and an excess return of 1.39% relative to the mixed equity fund index[5][41] - For the year (20250102-20251128), the portfolio achieved an absolute return of 33.65% and an excess return of 4.42% relative to the mixed equity fund index, ranking in the 35.37% percentile among active equity funds[5][41] - The broker's gold stock performance enhancement portfolio has consistently outperformed the mixed equity fund index from 2018 to 2022, ranking in the top 30% of active equity funds each year[12][37][43]

Group 1 - The performance of the HuShen 300 index enhanced portfolio achieved an excess return of 0.64% this week and 17.85% year-to-date [5][17] - The performance of the Zhongzheng 500 index enhanced portfolio recorded an excess return of 0.00% this week and 7.07% year-to-date [5][17] - The Zhongzheng 1000 index enhanced portfolio had an excess return of 0.21% this week and 14.89% year-to-date [5][17] - The Zhongzheng A500 index enhanced portfolio achieved an excess return of 0.44% this week and 8.26% year-to-date [5][17] Group 2 - In the HuShen 300 constituent stocks, factors such as three-month institutional coverage, one-year momentum, and single-quarter ROE performed well [6][8] - In the Zhongzheng 500 constituent stocks, factors like one-year momentum, expected net profit month-on-month, and DELTAROE showed strong performance [6][8] - For Zhongzheng 1000 constituent stocks, factors such as single-quarter revenue year-on-year growth, DELTAROA, and standardized expected external income performed well [6][8] - In the Zhongzheng A500 index constituent stocks, one-year momentum, standardized expected external profit, and standardized expected external income were strong factors [6][8] Group 3 - The HuShen 300 index enhanced products had a maximum excess return of 2.01%, a minimum of -0.78%, and a median of 0.19% this week [21] - The Zhongzheng 500 index enhanced products recorded a maximum excess return of 0.93%, a minimum of -2.16%, and a median of 0.05% this week [22] - The Zhongzheng 1000 index enhanced products achieved a maximum excess return of 1.47%, a minimum of -0.59%, and a median of 0.39% this week [23] - The Zhongzheng A500 index enhanced products had a maximum excess return of 1.47%, a minimum of -0.59%, and a median of 0.39% this week [24]

证券研究报告 | 2025年11月29日 2025年11月30日 多因子选股周报 动量因子表现出色，四大指增组合本周均战胜基准 核心观点 金融工程周报 国信金工指数增强组合表现跟踪 因子表现监控 以沪深 300 指数为选股空间。最近一周，三个月机构覆盖、一年动量、单季 ROE 等因子表现较好，而一个月波动、三个月反转、一个月换手等因子表 现较差。 以中证 500 指数为选股空间。最近一周，一年动量、预期净利润环比、 DELTAROE 等因子表现较好，而三个月波动、一个月波动、三个月换手等 因子表现较差。 以中证 1000 指数为选股空间。最近一周，单季营收同比增速、DELTAROA、 标准化预期外收入等因子表现较好，而三个月波动、一个月波动、三个月反 转等因子表现较差。 以中证 A500 指数为选股空间。最近一周，一年动量、标准化预期外盈利、 标准化预期外收入等因子表现较好，而一个月波动、三个月波动、预期 EPTTM 等因子表现较差。 以公募重仓指数为选股空间。最近一周，一年动量、预期净利润环比、单季 超预期幅度等因子表现较好，而一个月波动、三个月波动、一个月换手等因 子表现较差。 公募基金指数增强产品表现跟 ...