Quantitative Models and Construction 1. Model Name: GRU Model - **Model Construction Idea**: The GRU model is used to capture temporal dependencies in financial data, leveraging its recurrent structure to predict stock movements and generate long-short signals[4][5][6] - **Model Construction Process**: - Input data includes historical stock prices, technical indicators, and fundamental factors - The GRU network processes sequential data to learn patterns over time - Outputs are used to construct long-short portfolios based on predicted returns[4][5][6] - **Model Evaluation**: The GRU model demonstrates strong performance in certain market conditions, though its results vary across different stock pools[4][5][6] 2. Model Name: Barra Models (barra1d, barra5d) - **Model Construction Idea**: Barra models are factor-based models designed to decompose stock returns into systematic and idiosyncratic components, enabling factor-based portfolio construction[4][5][6] - **Model Construction Process**: - Factors such as size, value, momentum, and volatility are calculated for each stock - Stocks are ranked based on factor scores, and portfolios are constructed by going long the top 10% and short the bottom 10% of stocks based on factor rankings - barra1d uses daily data, while barra5d aggregates data over a 5-day window[4][5][6] - **Model Evaluation**: barra1d shows consistent strong performance, while barra5d experiences significant drawdowns in certain periods[4][5][6] --- Backtesting Results of Models GRU Model - **Open1d**: Weekly excess return: -1.80%, Monthly: -1.96%, YTD: 5.24%[33] - **Close1d**: Weekly excess return: -2.40%, Monthly: -3.10%, YTD: 4.04%[33] Barra Models - **Barra1d**: Weekly excess return: -0.63%, Monthly: -0.34%, YTD: 3.13%[33] - **Barra5d**: Weekly excess return: -1.80%, Monthly: -2.08%, YTD: 6.42%[33] --- Quantitative Factors and Construction 1. Factor Name: Beta - **Factor Construction Idea**: Measures the sensitivity of a stock's returns to market movements[15] - **Factor Construction Process**: Calculated as the historical beta of the stock relative to the market index[15] 2. Factor Name: Size - **Factor Construction Idea**: Captures the size effect, where smaller firms tend to outperform larger firms[15] - **Factor Construction Process**: Natural logarithm of total market capitalization[15] 3. Factor Name: Momentum - **Factor Construction Idea**: Stocks with strong past performance tend to continue performing well in the short term[15] - **Factor Construction Process**: - Weighted combination of historical excess return volatility (0.74), cumulative excess return deviation (0.16), and residual return volatility (0.10)[15] 4. Factor Name: Volatility - **Factor Construction Idea**: Measures the risk or variability in stock returns[15] - **Factor Construction Process**: Weighted combination of historical residual return volatility and other metrics[15] 5. Factor Name: Valuation - **Factor Construction Idea**: Identifies undervalued stocks based on fundamental metrics[15] - **Factor Construction Process**: Inverse of price-to-book ratio[15] 6. Factor Name: Liquidity - **Factor Construction Idea**: Measures the ease of trading a stock[15] - **Factor Construction Process**: Weighted combination of monthly turnover (0.35), quarterly turnover (0.35), and annual turnover (0.30)[15] 7. Factor Name: Profitability - **Factor Construction Idea**: Captures the financial health and earnings quality of a firm[15] - **Factor Construction Process**: Weighted combination of analyst-predicted earnings yield, cash flow yield, and other profitability metrics[15] 8. Factor Name: Growth - **Factor Construction Idea**: Identifies firms with strong earnings and revenue growth[15] - **Factor Construction Process**: Weighted combination of earnings growth rate (0.24) and revenue growth rate (0.47)[15] 9. Factor Name: Leverage - **Factor Construction Idea**: Measures the financial risk associated with a firm's debt levels[15] - **Factor Construction Process**: Weighted combination of market leverage (0.38), book leverage (0.35), and debt-to-asset ratio (0.27)[15] --- Backtesting Results of Factors Fundamental Factors - **Growth**: Weekly excess return: 2.41%, Monthly: -2.18%, YTD: 3.20%[28] - **Profitability**: Weekly excess return: 0.22%, Monthly: 40.98%, YTD: 6.12%[28] Technical Factors - **Momentum (20-day)**: Weekly excess return: 1.72%, Monthly: 4.23%, YTD: -5.29%[30] - **Volatility (120-day)**: Weekly excess return: 4.85%, Monthly: 8.64%, YTD: -14.60%[30]

2025 年 8 月 16 日 总量研究 市场大市值风格显著，机构调研组合表现欠佳 ——量化组合跟踪周报 20250816 要点 量化市场跟踪 大类因子表现：本周（2025.08.11-2025.08.15，下同）beta 因子和规模因子获 得正收益（1.35%和 1.34%），市场大市值风格显著，杠杆因子和 BP 因子取得 负收益（-0.34%和-0.16%）。 单因子表现：沪深 300 股票池中，本周表现较好的因子有单季度总资产毛利率 (3.79%)、单季度 ROE(3.44%)、总资产增长率(3.29%),表现较差的因子有市净 率因子(-1.16%)、下行波动率占比(-1.50%)、大单净流入(-2.23%)。 中证 500 股票池中，本周表现较好的因子有总资产增长率(1.97%)、单季度净利 润同比增长率(0.37%)、单季度营业收入同比增长率(0.23%),表现较差的因子有 毛利率 TTM(-2.16%)、营业利润率 TTM(-2.38%)、下行波动率占比(-2.57%)。 流动性 1500 股票池中，本周表现较好的因子有总资产增长率(1.66%)、标准化 预期外收入(1.19%)、单季度 EPS( ...

- The report tracks the performance of style factors, including momentum, beta, and liquidity factors, which showed strong long positions, while leverage, market capitalization, and valuation factors exhibited strong short positions[3][16] - The report includes the performance of fundamental factors across different stock pools, such as the CSI 300, CSI 500, and CSI 1000, highlighting that low valuation and high growth stocks were generally strong[5][6][7][20][22][25] - Technical factors' performance was mostly positive, with high volatility and long-term momentum stocks performing well, except for the 20-day momentum factor which showed negative performance[4][18][23][26] - The GRU factors' performance was weak overall, with the close1d model showing strong performance, while other models like open1d and barra1d experienced drawdowns[4][5][6][7][18][20][23][26] - The report details the construction and recent performance of the GRU long-only portfolios, noting that the barra1d model outperformed the CSI 1000 index by 0.38%, while the open1d and close1d models underperformed by 0.40%-0.53%[8][31][32] Factor Construction and Performance - **Barra Style Factors**: The report lists several style factors such as Beta, Market Cap, Momentum, Volatility, Non-linear Size, Valuation, Liquidity, Profitability, Growth, and Leverage, with detailed formulas for each[14][15] - **Fundamental Factors**: The report tracks various fundamental factors, including unexpected growth and growth-related financial factors, with mixed performance across different stock pools[4][5][6][7][18][20][22][25] - **Technical Factors**: The report includes several technical factors, such as 20-day momentum, 60-day momentum, 120-day momentum, and various volatility measures, with detailed performance metrics[4][18][23][26] Factor Performance Metrics - **Fundamental Factors**: - Operating Turnover: -1.14% (1 week), 4.19% (1 month), -11.23% (6 months), -11.52% (YTD), -1.86% (3-year annualized), 3.31% (5-year annualized)[19] - ROC: -0.68% (1 week), 0.89% (1 month), -10.51% (6 months), -10.59% (YTD), -13.06% (3-year annualized), -11.85% (5-year annualized)[19] - ROE Growth: 0.36% (1 week), 2.01% (1 month), 10.43% (6 months), 2.27% (YTD), 0.38% (3-year annualized), 2.61% (5-year annualized)[19] - **Technical Factors**: - 20-day Momentum: -0.73% (1 week), 0.66% (1 month), -8.17% (6 months), -12.18% (YTD), -13.19% (3-year annualized), -13.77% (5-year annualized)[19] - Median Deviation: -0.38% (1 week), -3.25% (1 month), -5.83% (6 months), -4.72% (YTD), -15.12% (3-year annualized), -15.62% (5-year annualized)[19] - 60-day Momentum: 0.35% (1 week), -3.31% (1 month), 2.64% (6 months), 5.08% (YTD), -12.82% (3-year annualized), -16.17% (5-year annualized)[19] GRU Model Performance - **GRU Long-Only Portfolios**: - open1d: -0.40% (1 week), -0.20% (1 month), 2.37% (3 months), 6.32% (6 months), 7.16% (YTD)[32] - close1d: -0.53% (1 week), -0.83% (1 month), 4.38% (3 months), 6.80% (6 months), 6.59% (YTD)[32] - barra1d: 0.38% (1 week), -0.25% (1 month), 0.85% (3 months), 2.85% (6 months), 3.78% (YTD)[32] - barra5d: 0.00% (1 week), -0.36% (1 month), 3.59% (3 months), 7.41% (6 months), 8.37% (YTD)[32] - Multi-Factor: -0.38% (1 week), -0.30% (1 month), 1.62% (3 months), 2.54% (6 months), 2.54% (YTD)[32]

Core Viewpoint - The report provides a comprehensive analysis of market performance, highlighting the positive and negative returns of various factors across different stock pools, indicating a mixed market sentiment and potential investment opportunities in specific sectors [3][4][5][6]. Group 1: Market Factor Performance - The overall market showed a positive return of 0.49% for the Beta factor, while momentum and liquidity factors experienced negative returns of -0.60% and -0.49% respectively, suggesting a reversal effect in the market [3]. - In the CSI 300 stock pool, the best-performing factors included quarterly operating profit growth rate (2.40%), price-to-book ratio (2.30%), and turnover rate relative volatility (2.19%), while the worst performers were operating profit margin TTM (-0.95%), total asset gross margin TTM (-0.76%), and net profit margin TTM (-0.71%) [4]. - The CSI 500 stock pool saw strong performance from the downside volatility ratio (3.85%), intraday volatility and trading volume correlation (3.44%), and inverse price-to-earnings ratio TTM (2.31%), with poor performance from quarterly ROE (-1.66%), post-opening return factor (-1.42%), and ROIC enhancement factor (-1.31%) [4]. Group 2: Liquidity and Industry Performance - In the liquidity 1500 stock pool, the best-performing factors were price-to-book ratio (1.67%), inverse price-to-earnings ratio TTM (1.20%), and price-to-earnings ratio (0.97%), while the worst performers included 5-day reversal (-2.11%), post-opening return factor (-1.69%), and logarithmic market value factor (-1.69%) [5]. - Fundamental factors showed varied performance across industries, with net asset growth rate, net profit growth rate, earnings per share, and operating profit TTM factors yielding consistent positive returns in the non-ferrous metals, beauty care, and diversified industries [6]. - Valuation factors, particularly the BP factor, performed well in the coal and diversified industries, while residual volatility and liquidity factors showed significant positive returns in agriculture, forestry, animal husbandry, and beauty care sectors [6]. Group 3: Strategy Performance Tracking - The PB-ROE-50 combination achieved positive excess returns in the overall market stock pool, with excess returns of -0.57% in the CSI 500 stock pool and -0.45% in the CSI 800 stock pool, while the overall market stock pool saw an excess return of 0.06% [7]. - Public and private fund research selection strategies yielded positive excess returns, with public research selection strategy outperforming the CSI 800 by 1.02% and private research tracking strategy outperforming by 2.72% [8]. - The block trading combination achieved positive excess returns relative to the CSI All Index, with an excess return of 0.83% [9]. - The targeted issuance combination, however, recorded negative excess returns relative to the CSI All Index, with an excess return of -0.46% [10].

Quantitative Models and Construction Methods Model: PB-ROE-50 Combination - **Construction Idea**: The PB-ROE-50 combination aims to capture excess returns by selecting stocks with favorable Price-to-Book (PB) and Return on Equity (ROE) metrics. - **Construction Process**: The combination is constructed by selecting the top 50 stocks based on their PB and ROE metrics from the entire market stock pool, the CSI 500 stock pool, and the CSI 800 stock pool. The selection is updated periodically to maintain the combination's effectiveness.[23][24] - **Evaluation**: The PB-ROE-50 combination has shown the ability to generate positive excess returns in the overall market stock pool, although it has underperformed in the CSI 500 and CSI 800 stock pools this week.[23][24] Model: Institutional Research Combination - **Construction Idea**: This model leverages the insights from public and private institutional research to select stocks that are expected to outperform. - **Construction Process**: The combination is constructed by tracking the stocks that have been researched by public and private institutions. The performance of these stocks is then compared to the CSI 800 index to measure excess returns.[25][26] - **Evaluation**: Both the public and private institutional research strategies have generated positive excess returns this week, indicating the effectiveness of institutional insights in stock selection.[25][26] Model: Block Trade Combination - **Construction Idea**: This model aims to capture the information embedded in block trades, which are large transactions that can indicate significant investor interest. - **Construction Process**: The combination is constructed by selecting stocks with high block trade transaction amounts and low 6-day transaction amount volatility. The combination is rebalanced monthly to maintain its effectiveness.[29][30] - **Evaluation**: The block trade combination has generated positive excess returns this week, suggesting that the "high transaction, low volatility" principle is effective in identifying outperforming stocks.[29][30] Model: Private Placement Combination - **Construction Idea**: This model focuses on the event-driven opportunities presented by private placements, which can indicate significant corporate actions and investor interest. - **Construction Process**: The combination is constructed by selecting stocks involved in private placements, considering factors such as market capitalization, rebalancing cycle, and position control. The combination is updated based on the announcement date of the shareholders' meeting.[35][36] - **Evaluation**: The private placement combination has underperformed this week, generating negative excess returns, which raises questions about the current effectiveness of private placement event-driven strategies.[35][36] Model Backtesting Results PB-ROE-50 Combination - **CSI 500**: Excess return this week: -0.57%, Year-to-date excess return: 2.97%, Absolute return this week: 2.69%, Year-to-date absolute return: 13.29%[24] - **CSI 800**: Excess return this week: -0.45%, Year-to-date excess return: 7.47%, Absolute return this week: 1.64%, Year-to-date absolute return: 14.12%[24] - **Overall Market**: Excess return this week: 0.06%, Year-to-date excess return: 9.34%, Absolute return this week: 2.22%, Year-to-date absolute return: 20.17%[24] Institutional Research Combination - **Public Research**: Excess return this week: 1.02%, Year-to-date excess return: 7.37%, Absolute return this week: 3.15%, Year-to-date absolute return: 14.02%[26] - **Private Research**: Excess return this week: 2.72%, Year-to-date excess return: 18.45%, Absolute return this week: 4.88%, Year-to-date absolute return: 25.78%[26] Block Trade Combination - **Excess return this week**: 0.83%, Year-to-date excess return: 27.95%, Absolute return this week: 3.01%, Year-to-date absolute return: 40.62%[30] Private Placement Combination - **Excess return this week**: -0.46%, Year-to-date excess return: 7.55%, Absolute return this week: 1.69%, Year-to-date absolute return: 18.19%[36] Quantitative Factors and Construction Methods Single Factors - **Top Performing Factors in CSI 300**: Single-quarter operating profit YoY growth rate (2.40%), Price-to-Book ratio (2.30%), Turnover rate relative volatility (2.19%)[12][13] - **Top Performing Factors in CSI 500**: Downside volatility proportion (3.85%), Intraday volatility and transaction amount correlation (3.44%), Price-to-Earnings TTM inverse (2.31%)[14][15] - **Top Performing Factors in Liquidity 1500**: Price-to-Book ratio (1.67%), Price-to-Earnings TTM inverse (1.20%), Price-to-Earnings ratio (0.97%)[16][17] Factor Backtesting Results CSI 300 - **Single-quarter operating profit YoY growth rate**: 2.40%[12][13] - **Price-to-Book ratio**: 2.30%[12][13] - **Turnover rate relative volatility**: 2.19%[12][13] CSI 500 - **Downside volatility proportion**: 3.85%[14][15] - **Intraday volatility and transaction amount correlation**: 3.44%[14][15] - **Price-to-Earnings TTM inverse**: 2.31%[14][15] Liquidity 1500 - **Price-to-Book ratio**: 1.67%[16][17] - **Price-to-Earnings TTM inverse**: 1.20%[16][17] - **Price-to-Earnings ratio**: 0.97%[16][17]

证券研究报告：金融工程报告 发布时间：2025-06-30 研究所 分析师:肖承志 SAC 登记编号:S1340524090001 Email:xiaochengzhi@cnpsec.com 研究助理:金晓杰 SAC 登记编号:S1340124100010 Email:jinxiaojie@cnpsec.com 近期研究报告 《基于相对强弱视角下的扩散指数择 时模型》 - 2025.06.25 《调整仍不充分——微盘股指数周报 20250622》 - 2025.06.23 《短期上涨动能枯竭，控制仓位做好 防御——微盘股指数周报 20250615》 - 2025.06.16 《为何微盘股基金仓位下降指数却不 断新高？——微盘股指数周报 20250608》 - 2025.06.09 《小盘股成交占比高意味着拥挤度高 吗？——微盘股指数周报 20250601》 - 2025.06.02 《微盘股容易被忽略的"看空成本" ——微盘股指数周报 20250525》 - 2025.05.26 《证监会修改《重组办法》，深化并购 重组改革——微盘股指数周报 20250518》 - 2025.05.19 《微盘股会涨到什么时 ...

Quantitative Factors and Construction Methods 1. Factor Name: **bp** - **Factor Construction Idea**: Measures the valuation level of a stock based on its book-to-price ratio [13] - **Factor Construction Process**: Calculated as the current net asset divided by the current total market value $ bp = \frac{\text{Current Net Asset}}{\text{Current Total Market Value}} $ [13] 2. Factor Name: **bp Three-Year Percentile** - **Factor Construction Idea**: Evaluates the relative valuation of a stock over the past three years [13] - **Factor Construction Process**: Represents the percentile rank of the current bp value within the stock's bp distribution over the last three years [13] 3. Factor Name: **Quarterly EP** - **Factor Construction Idea**: Reflects the profitability of a stock relative to its equity [13] - **Factor Construction Process**: Calculated as the quarterly net profit divided by the net asset $ \text{Quarterly EP} = \frac{\text{Quarterly Net Profit}}{\text{Net Asset}} $ [13] 4. Factor Name: **Quarterly EP One-Year Percentile** - **Factor Construction Idea**: Measures the relative profitability of a stock over the past year [13] - **Factor Construction Process**: Represents the percentile rank of the current quarterly EP value within the stock's EP distribution over the last year [13] 5. Factor Name: **Quarterly SP** - **Factor Construction Idea**: Indicates the revenue generation efficiency of a stock relative to its equity [13] - **Factor Construction Process**: Calculated as the quarterly operating revenue divided by the net asset $ \text{Quarterly SP} = \frac{\text{Quarterly Operating Revenue}}{\text{Net Asset}} $ [13] 6. Factor Name: **Quarterly SP One-Year Percentile** - **Factor Construction Idea**: Evaluates the relative revenue efficiency of a stock over the past year [13] - **Factor Construction Process**: Represents the percentile rank of the current quarterly SP value within the stock's SP distribution over the last year [13] 7. Factor Name: **Fama-French Three-Factor One-Month Residual Volatility** - **Factor Construction Idea**: Measures the idiosyncratic risk of a stock based on its residual volatility after regressing against the Fama-French three-factor model [13] - **Factor Construction Process**: Calculated as the standard deviation of the residuals from the regression of daily returns over the past 20 trading days on the Fama-French three factors $ \text{Residual Volatility} = \sqrt{\frac{\sum (\text{Actual Return} - \text{Predicted Return})^2}{n}} $ where "Predicted Return" is derived from the Fama-French three-factor model [13] 8. Factor Name: **One-Month Excess Return Volatility** - **Factor Construction Idea**: Captures the volatility of a stock's excess return over the past month [13] - **Factor Construction Process**: Calculated as the standard deviation of the excess returns over the past 20 trading days $ \text{Excess Return Volatility} = \sqrt{\frac{\sum (\text{Excess Return} - \text{Mean Excess Return})^2}{n}} $ [13] --- Factor Backtesting Results IC Performance - **bp**: Weekly IC = 9.73%, Monthly IC = 2.21%, Yearly IC = 1.64%, Historical IC = 2.27% [9] - **bp Three-Year Percentile**: Weekly IC = 14.75%, Monthly IC = 3.36%, Yearly IC = 2.85%, Historical IC = 1.69% [9] - **Quarterly EP**: Weekly IC = -4.31%, Monthly IC = 0.38%, Yearly IC = -0.58%, Historical IC = 1.13% [9] - **Quarterly EP One-Year Percentile**: Weekly IC = 7.25%, Monthly IC = 3.57%, Yearly IC = 0.94%, Historical IC = 1.73% [9] - **Quarterly SP**: Weekly IC = -0.92%, Monthly IC = 0.38%, Yearly IC = 0.23%, Historical IC = 0.71% [9] - **Quarterly SP One-Year Percentile**: Weekly IC = 11.79%, Monthly IC = 4.40%, Yearly IC = 3.08%, Historical IC = 1.86% [9] - **Fama-French Three-Factor One-Month Residual Volatility**: Weekly IC = 14.50%, Monthly IC = 5.11%, Yearly IC = 3.29%, Historical IC = 2.54% [9] - **One-Month Excess Return Volatility**: Weekly IC = 14.87%, Monthly IC = 5.14%, Yearly IC = 3.26%, Historical IC = 2.22% [9] Long-Only Portfolio Excess Returns - **bp**: Weekly Excess Return = 0.52%, Monthly Excess Return = -0.36%, Yearly Excess Return = 1.57%, Historical Cumulative Excess Return = 30.39% [11] - **bp Three-Year Percentile**: Weekly Excess Return = 0.75%, Monthly Excess Return = -0.59%, Yearly Excess Return = 3.19%, Historical Cumulative Excess Return = -1.63% [11] - **Quarterly EP**: Weekly Excess Return = 0.13%, Monthly Excess Return = 1.56%, Yearly Excess Return = 1.05%, Historical Cumulative Excess Return = 30.66% [11] - **Quarterly EP One-Year Percentile**: Weekly Excess Return = 0.81%, Monthly Excess Return = 0.32%, Yearly Excess Return = 3.53%, Historical Cumulative Excess Return = 33.78% [11] - **Quarterly SP**: Weekly Excess Return = -0.30%, Monthly Excess Return = 0.33%, Yearly Excess Return = 0.34%, Historical Cumulative Excess Return = -2.98% [11] - **Quarterly SP One-Year Percentile**: Weekly Excess Return = 0.56%, Monthly Excess Return = 1.09%, Yearly Excess Return = 9.91%, Historical Cumulative Excess Return = 1.99% [11] - **Fama-French Three-Factor One-Month Residual Volatility**: Weekly Excess Return = 1.33%, Monthly Excess Return = 1.68%, Yearly Excess Return = 8.97%, Historical Cumulative Excess Return = 19.84% [11] - **One-Month Excess Return Volatility**: Weekly Excess Return = 1.34%, Monthly Excess Return = 1.55%, Yearly Excess Return = 10.29%, Historical Cumulative Excess Return = 11.42% [11]

Quantitative Factors and Construction Methods Factor Name: Beta - Construction Idea: Measures the sensitivity of a stock's returns to market returns[14] - Construction Process: Calculated using the weighted regression of individual stock returns against market returns over the last 490 trading days[14] - Evaluation: Beta factor performed well in the recent week[8][10] Factor Name: Turnover Rate and Average Price Correlation (1 Month) - Construction Idea: Measures the correlation between turnover rate and average price over the past month[13] - Construction Process: Calculated as the correlation coefficient between turnover rate and average price over the past 20 trading days[13] - Evaluation: This factor showed good performance in the recent week and month[8][10] Factor Name: Turnover Rate Volatility (1 Month) - Construction Idea: Measures the volatility of turnover rate over the past month[13] - Construction Process: Calculated as the standard deviation of turnover rate over the past 20 trading days[13] - Evaluation: This factor performed well in the recent month and year[8][10] Factor Name: Reversal (1 Month) - Construction Idea: Measures the cumulative returns over the past month[13] - Construction Process: Calculated as the cumulative returns over the past 20 trading days[13] - Evaluation: This factor showed good performance in the recent week and month[8][10] Factor Name: Specificity (1 Month) - Construction Idea: Measures the specificity of stock returns relative to the Fama-French three-factor model[13] - Construction Process: Calculated as 1 minus the R-squared value from the regression of daily returns against the Fama-French three factors over the past 20 trading days[13] - Evaluation: This factor performed well in the recent year[8][10] Factor Name: Residual Volatility (Fama-French Three-Factor Model, 1 Month) - Construction Idea: Measures the residual volatility of stock returns relative to the Fama-French three-factor model[13] - Construction Process: Calculated as the standard deviation of residuals from the regression of daily returns against the Fama-French three factors over the past 20 trading days[13] - Evaluation: This factor showed good performance in the recent year[8][10] Factor Name: Excess Return Volatility (1 Month) - Construction Idea: Measures the volatility of excess returns over the past month[13] - Construction Process: Calculated as the standard deviation of excess returns over the past 20 trading days[13] - Evaluation: This factor performed well in the recent year[8][10] Factor Name: Small Market Capitalization - Construction Idea: Measures the logarithm of market capitalization[13] - Construction Process: Calculated as the logarithm of market capitalization[13] - Evaluation: This factor showed good performance in the recent week and year[8][10] Factor Backtesting Results Information Coefficient (IC) Performance - Beta: Recent week IC: 13.69%, Recent month IC: 0.85%, Recent year IC: 1.73%, Historical IC: 0.44%[9] - Turnover Rate and Average Price Correlation (1 Month): Recent week IC: 11.30%, Recent month IC: 7.07%, Recent year IC: 2.49%, Historical IC: 1.70%[9] - Turnover Rate Volatility (1 Month): Recent week IC: 6.15%, Recent month IC: 5.29%, Recent year IC: 2.99%, Historical IC: 2.51%[9] - Reversal (1 Month): Recent week IC: 11.08%, Recent month IC: 4.52%, Recent year IC: 2.87%, Historical IC: 2.15%[9] - Specificity (1 Month): Recent week IC: 11.05%, Recent month IC: 3.76%, Recent year IC: 3.63%, Historical IC: 2.41%[9] - Residual Volatility (Fama-French Three-Factor Model, 1 Month): Recent week IC: 5.42%, Recent month IC: 3.27%, Recent year IC: 3.62%, Historical IC: 2.48%[9] - Excess Return Volatility (1 Month): Recent week IC: -0.20%, Recent month IC: 1.88%, Recent year IC: 3.29%, Historical IC: 2.18%[9] - Small Market Capitalization: Recent week IC: 7.12%, Recent month IC: 2.70%, Recent year IC: 2.03%, Historical IC: 1.89%[9] Long Portfolio Performance - Beta: Recent week excess return: 1.08%, Recent month excess return: -0.75%, Recent year excess return: 6.46%, Historical cumulative excess return: -5.34%[11] - Turnover Rate and Average Price Correlation (1 Month): Recent week excess return: 1.08%, Recent month excess return: 2.92%, Recent year excess return: 2.72%, Historical cumulative excess return: 16.63%[11] - Turnover Rate Volatility (1 Month): Recent week excess return: 0.93%, Recent month excess return: 1.96%, Recent year excess return: 10.68%, Historical cumulative excess return: 32.01%[11] - Reversal (1 Month): Recent week excess return: 0.37%, Recent month excess return: 0.22%, Recent year excess return: 0.75%, Historical cumulative excess return: -1.18%[11] - Specificity (1 Month): Recent week excess return: 0.67%, Recent month excess return: 0.67%, Recent year excess return: 10.17%, Historical cumulative excess return: 16.91%[11] - Residual Volatility (Fama-French Three-Factor Model, 1 Month): Recent week excess return: 0.34%, Recent month excess return: 0.82%, Recent year excess return: 8.10%, Historical cumulative excess return: 18.57%[11] - Excess Return Volatility (1 Month): Recent week excess return: 0.02%, Recent month excess return: 0.09%, Recent year excess return: 7.20%, Historical cumulative excess return: 10.83%[11] - Small Market Capitalization: Recent week excess return: 0.95%, Recent month excess return: 0.12%, Recent year excess return: 10.84%, Historical cumulative excess return: 59.20%[11]

Quantitative Factors and Construction Methods - **Factor Name**: bp **Construction Idea**: Measures valuation by comparing net assets to market value **Construction Process**: Calculated as: $ bp = \frac{\text{Current Net Assets}}{\text{Current Total Market Value}} $ [13] **Evaluation**: Commonly used valuation factor, straightforward and widely applicable [13] - **Factor Name**: bp three-year percentile **Construction Idea**: Tracks the relative valuation of a stock over the past three years **Construction Process**: Represents the percentile rank of the current bp value within the last three years [13] **Evaluation**: Useful for identifying stocks with consistent valuation trends [13] - **Factor Name**: Quarterly ep **Construction Idea**: Measures profitability relative to net assets **Construction Process**: Calculated as: $ \text{Quarterly ep} = \frac{\text{Quarterly Net Profit}}{\text{Net Assets}} $ [13] **Evaluation**: Reflects short-term profitability, sensitive to quarterly fluctuations [13] - **Factor Name**: Quarterly ep one-year percentile **Construction Idea**: Tracks the relative profitability of a stock over the past year **Construction Process**: Represents the percentile rank of the current quarterly ep value within the last year [13] **Evaluation**: Helps identify stocks with improving or declining profitability trends [13] - **Factor Name**: Quarterly sp **Construction Idea**: Measures revenue generation relative to net assets **Construction Process**: Calculated as: $ \text{Quarterly sp} = \frac{\text{Quarterly Revenue}}{\text{Net Assets}} $ [13] **Evaluation**: Indicates operational efficiency, useful for growth-oriented analysis [13] - **Factor Name**: Quarterly sp one-year percentile **Construction Idea**: Tracks the relative operational efficiency of a stock over the past year **Construction Process**: Represents the percentile rank of the current quarterly sp value within the last year [13] **Evaluation**: Highlights trends in revenue generation efficiency [13] - **Factor Name**: Quarterly asset turnover **Construction Idea**: Measures revenue generation relative to total assets **Construction Process**: Calculated as: $ \text{Quarterly Asset Turnover} = \frac{\text{Quarterly Revenue}}{\text{Total Assets}} $ [13] **Evaluation**: Reflects operational efficiency, sensitive to asset-heavy industries [13] - **Factor Name**: Quarterly gross margin **Construction Idea**: Measures profitability relative to sales revenue **Construction Process**: Calculated as: $ \text{Quarterly Gross Margin} = \frac{\text{Quarterly Gross Profit}}{\text{Quarterly Sales Revenue}} $ [13] **Evaluation**: Indicates pricing power and cost control [13] - **Factor Name**: Quarterly roa **Construction Idea**: Measures profitability relative to total assets **Construction Process**: Calculated as: $ \text{Quarterly ROA} = \frac{\text{Quarterly Net Profit}}{\text{Total Assets}} $ [13] **Evaluation**: Reflects overall asset efficiency [13] - **Factor Name**: Quarterly roe **Construction Idea**: Measures profitability relative to net assets **Construction Process**: Calculated as: $ \text{Quarterly ROE} = \frac{\text{Quarterly Net Profit}}{\text{Net Assets}} $ [13] **Evaluation**: Commonly used profitability metric, sensitive to leverage [13] - **Factor Name**: Standardized unexpected earnings **Construction Idea**: Measures deviation of current earnings from historical growth trends **Construction Process**: Calculated as: $ \text{Standardized Unexpected Earnings} = \frac{\text{Current Quarterly Net Profit} - (\text{Last Year Same Quarter Net Profit} + \text{Average Growth of Last 8 Quarters})}{\text{Standard Deviation of Growth in Last 8 Quarters}} $ [13] **Evaluation**: Useful for identifying earnings surprises [13] - **Factor Name**: Standardized unexpected revenue **Construction Idea**: Measures deviation of current revenue from historical growth trends **Construction Process**: Calculated as: $ \text{Standardized Unexpected Revenue} = \frac{\text{Current Quarterly Revenue} - (\text{Last Year Same Quarter Revenue} + \text{Average Growth of Last 8 Quarters})}{\text{Standard Deviation of Growth in Last 8 Quarters}} $ [13] **Evaluation**: Highlights revenue surprises [13] - **Factor Name**: Dividend yield **Construction Idea**: Measures dividend payout relative to market value **Construction Process**: Calculated as: $ \text{Dividend Yield} = \frac{\text{Annual Dividend}}{\text{Current Market Value}} $ [13] **Evaluation**: Commonly used for income-focused strategies [13] - **Factor Name**: 1-month turnover rate volatility **Construction Idea**: Measures the variability of turnover rates over the past month **Construction Process**: Calculated as the standard deviation of daily turnover rates over the past 20 trading days [13] **Evaluation**: Reflects liquidity and trading activity [13] - **Factor Name**: Fama-French three-factor residual volatility **Construction Idea**: Measures the volatility of residuals from a Fama-French three-factor model regression **Construction Process**: Calculated as the standard deviation of residuals from daily returns regressed on the Fama-French three factors over the past 20 trading days [13] **Evaluation**: Indicates idiosyncratic risk [13] Factor Backtesting Results - **Factor Name**: bp **IC Values**: Weekly: -8.41%, Monthly: 3.48%, Yearly: 1.72% [8] **Excess Return**: Weekly: -0.18%, Monthly: 1.03%, Yearly: 3.10% [11] - **Factor Name**: bp three-year percentile **IC Values**: Weekly: 2.04%, Monthly: 7.90%, Yearly: 2.82% [8] **Excess Return**: Weekly: 0.67%, Monthly: 0.82%, Yearly: 2.55% [11] - **Factor Name**: Quarterly ep **IC Values**: Weekly: -5.19%, Monthly: 3.65%, Yearly: 0.24% [8] **Excess Return**: Weekly: -1.30%, Monthly: -0.08%, Yearly: 1.51% [11] - **Factor Name**: Quarterly ep one-year percentile **IC Values**: Weekly: 1.73%, Monthly: 4.68%, Yearly: 1.02% [8] **Excess Return**: Weekly: -0.35%, Monthly: 0.93%, Yearly: 4.35% [11] - **Factor Name**: Quarterly sp **IC Values**: Weekly: -5.87%, Monthly: -1.49%, Yearly: 0.18% [8] **Excess Return**: Weekly: -0.28%, Monthly: -1.23%, Yearly: 0.24% [11] - **Factor Name**: Quarterly sp one-year percentile **IC Values**: Weekly: 1.93%, Monthly: 7.04%, Yearly: 2.70% [8] **Excess Return**: Weekly: -0.66%, Monthly: 0.55%, Yearly: 3.80% [11] - **Factor Name**: Standardized unexpected earnings **IC Values**: Weekly: 0.24%, Monthly: 2.19%, Yearly: 0.64% [8] **Excess Return**: Weekly: -0.60%, Monthly: -0.75%, Yearly: 3.99% [11] - **Factor Name**: Standardized unexpected revenue **IC Values**: Weekly: -1.03%, Monthly: 0.72%, Yearly: 0.61% [8] **Excess Return**: Weekly: -0.41%, Monthly: -0.72%, Yearly: 1.55% [11] - **Factor Name**: Dividend yield **IC Values**: Weekly: -2.91%, Monthly: 1.85%, Yearly: -0.07% [8] **Excess Return**: Weekly: -0.37%, Monthly: 1.27%, Yearly: -4.85% [11]

Investment Rating - The industry investment rating is "Outperform the Market," indicating an expected industry index increase of over 5% in the next six months [18]. Core Insights - Recent factor performance shows that the average turnover rate, non-liquid shock, and quarterly gross margin factors have performed well, while factors like Beta and one-year momentum have underperformed [2][9]. - Over the past year, small-cap stocks, earnings forecast accuracy, and one-month turnover rate volatility have shown strong performance, while one-year momentum and expected adjustment averages have lagged [2][9]. Factor Tracking Summary Factor IC Performance - In the last week, the one-month average turnover rate, non-liquid shock, and turnover rate volatility factors performed well, while one-year momentum and quarterly asset turnover rate showed poor performance [7]. - Over the last month, the one-month average turnover rate and Fama-French three-factor one-month residual volatility factors performed well, while Beta and one-year momentum lagged [7]. - In the past year, the one-month specificity and Fama-French three-factor one-month residual volatility factors performed well, while one-year momentum and dividend yield factors underperformed [7][8]. Factor Long-Only Portfolio Performance - The long-only portfolio, constructed from the top 10% of factors, has shown cumulative excess returns, with quarterly gross margin and one-month average turnover rate factors performing well recently [9][10]. - Over the last year, small-cap stocks and earnings forecast accuracy have shown strong performance, while one-year momentum and expected adjustment averages have underperformed [9][10]. Factor Introduction - The factors used in the analysis are categorized into valuation, profitability, growth, dividends, reversal, turnover, volatility, and analyst factors, each with specific calculation methods [11][12].