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]

Quantitative Models and Construction Methods 1. Model Name: PB-ROE-50 Combination - **Model Construction Idea**: This model aims to capture excess returns by selecting stocks based on their Price-to-Book (PB) ratio and Return on Equity (ROE), focusing on stocks with favorable valuation and profitability metrics[24][25] - **Model Construction Process**: - Stocks are filtered based on their PB and ROE metrics - The portfolio is rebalanced periodically to maintain alignment with the PB-ROE strategy - The model is applied across different stock pools, including CSI 500, CSI 800, and the entire market[24][25] - **Model Evaluation**: The model demonstrates significant excess returns in the CSI 800 and full-market stock pools, indicating its effectiveness in capturing valuation and profitability-driven opportunities[24][25] 2. Model Name: Block Trade Combination - **Model Construction Idea**: This model leverages the "high transaction, low volatility" principle to identify stocks with favorable post-trade performance based on block trade characteristics[31] - **Model Construction Process**: - Stocks are selected based on two key metrics: "block trade transaction amount ratio" and "6-day transaction amount volatility" - Stocks with higher transaction ratios and lower volatility are included in the portfolio - The portfolio is rebalanced monthly to reflect updated metrics[31] - **Model Evaluation**: The model effectively captures the information embedded in block trades, delivering consistent excess returns relative to the benchmark[31] 3. Model Name: Private Placement Combination - **Model Construction Idea**: This model focuses on the event-driven opportunities surrounding private placements, considering factors such as market value, rebalancing cycles, and position control[37] - **Model Construction Process**: - Stocks involved in private placements are identified using the shareholder meeting announcement date as the event trigger - The portfolio is constructed by integrating market value considerations and rebalancing strategies - Position control mechanisms are applied to manage risk exposure[37] - **Model Evaluation**: The model's performance is sensitive to market conditions, with occasional drawdowns observed during adverse market phases[37] --- Model Backtesting Results 1. PB-ROE-50 Combination - CSI 500: Weekly excess return of -0.44%, absolute return of 3.42%[25] - CSI 800: Weekly excess return of 1.12%, absolute return of 3.92%[25] - Full Market: Weekly excess return of 1.23%, absolute return of 4.18%[25] 2. Block Trade Combination - Weekly excess return of 1.69%, absolute return of 4.65%[32] 3. Private Placement Combination - Weekly excess return of -3.21%, absolute return of -0.39%[38] --- Quantitative Factors and Construction Methods 1. Factor Name: Beta Factor - **Factor Construction Idea**: Measures the sensitivity of a stock's returns to market movements, capturing systematic risk exposure[20] - **Factor Construction Process**: - Beta is calculated using regression analysis of stock returns against market returns over a specified period - Stocks with higher beta values are expected to exhibit greater volatility relative to the market[20] - **Factor Evaluation**: The beta factor delivered a weekly return of 1.35%, indicating a positive contribution to portfolio performance during the observed period[20] 2. Factor Name: Scale Factor - **Factor Construction Idea**: Focuses on the size effect, where smaller-cap stocks tend to outperform larger-cap stocks over time[20] - **Factor Construction Process**: - Stocks are ranked based on their market capitalization - Smaller-cap stocks are given higher weights in the portfolio[20] - **Factor Evaluation**: The scale factor achieved a weekly return of 1.34%, reflecting the market's preference for larger-cap stocks during the observed period[20] 3. Factor Name: BP Factor (Book-to-Price) - **Factor Construction Idea**: Captures valuation opportunities by focusing on stocks with high book-to-price ratios[20] - **Factor Construction Process**: - The book-to-price ratio is calculated as the book value per share divided by the stock price - Stocks with higher BP ratios are included in the portfolio[20] - **Factor Evaluation**: The BP factor recorded a weekly return of -0.16%, indicating underperformance during the observed period[20] 4. Factor Name: Leverage Factor - **Factor Construction Idea**: Measures the financial leverage of a company, with higher leverage potentially indicating higher risk and return[20] - **Factor Construction Process**: - Leverage is calculated as the ratio of total debt to equity - Stocks with higher leverage ratios are included in the portfolio[20] - **Factor Evaluation**: The leverage factor delivered a weekly return of -0.34%, reflecting its sensitivity to market conditions[20] --- Factor Backtesting Results 1. Beta Factor - Weekly return: 1.35%[20] 2. Scale Factor - Weekly return: 1.34%[20] 3. BP Factor - Weekly return: -0.16%[20] 4. Leverage Factor - Weekly return: -0.34%[20]

- 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]

Quantitative Models and Construction - **Model Name**: barra1d **Model Construction Idea**: Focuses on short-term factor performance using daily data **Model Construction Process**: Utilizes historical data to calculate factor exposures and applies industry-neutral adjustments. Stocks are ranked based on factor scores, with the top 10% selected for long positions and the bottom 10% for short positions. Adjustments include equal weighting and monthly rebalancing[19][21][30] **Model Evaluation**: Demonstrates strong performance in short-term factor analysis[19][21][30] - **Model Name**: barra5d **Model Construction Idea**: Focuses on medium-term factor performance using five-day data **Model Construction Process**: Similar to barra1d, but uses a five-day rolling window for factor calculations. Stocks are ranked and selected based on factor scores, with monthly rebalancing and equal weighting applied[19][21][30] **Model Evaluation**: Exhibits robust medium-term factor performance, outperforming other models in cumulative returns[19][21][30] - **Model Name**: open1d **Model Construction Idea**: Focuses on factor performance using daily open prices **Model Construction Process**: Factors are calculated using daily open price data, with industry-neutral adjustments applied. Stocks are ranked based on factor scores, and the top 10% are selected for long positions, while the bottom 10% are shorted. Monthly rebalancing is implemented[19][21][30] **Model Evaluation**: Performs well in certain market conditions but shows higher volatility compared to other models[19][21][30] - **Model Name**: close1d **Model Construction Idea**: Focuses on factor performance using daily close prices **Model Construction Process**: Factors are calculated using daily close price data, with industry-neutral adjustments applied. Stocks are ranked based on factor scores, and the top 10% are selected for long positions, while the bottom 10% are shorted. Monthly rebalancing is implemented[19][21][30] **Model Evaluation**: Demonstrates weaker performance compared to other models, with significant drawdowns observed[19][21][30] Model Backtesting Results - **barra1d**: Weekly excess return 0.17%, monthly excess return 0.32%, six-month excess return 4.09%, year-to-date excess return 3.93%[32] - **barra5d**: Weekly excess return 0.13%, monthly excess return 0.39%, six-month excess return 7.59%, year-to-date excess return 7.56%[32] - **open1d**: Weekly excess return -0.35%, monthly excess return -0.71%, six-month excess return 5.85%, year-to-date excess return 6.30%[32] - **close1d**: Weekly excess return 0.55%, monthly excess return 0.40%, six-month excess return 6.40%, year-to-date excess return 6.31%[32] - **Multi-factor model**: Weekly excess return -0.38%, monthly excess return -0.04%, six-month excess return 3.56%, year-to-date excess return 2.82%[32] Quantitative Factors and Construction - **Factor Name**: Beta **Factor Construction Idea**: Measures historical beta to assess market sensitivity **Factor Construction Process**: Calculated using historical beta values derived from regression analysis of stock returns against market returns[15][16] **Factor Evaluation**: Demonstrates strong performance in high-volatility environments[15][16] - **Factor Name**: Momentum **Factor Construction Idea**: Captures historical excess return trends **Factor Construction Process**: Combines weighted averages of historical excess return volatility, cumulative excess return deviation, and residual return volatility using the formula: $ Momentum = 0.74 * Historical Excess Return Volatility + 0.16 * Cumulative Excess Return Deviation + 0.1 * Residual Return Volatility $[15][16] **Factor Evaluation**: Performs well in trending markets but struggles in reversal scenarios[15][16] - **Factor Name**: Volatility **Factor Construction Idea**: Measures stock price fluctuation intensity **Factor Construction Process**: Combines weighted averages of monthly, quarterly, and annual turnover rates using the formula: $ Volatility = 0.35 * Monthly Turnover Rate + 0.35 * Quarterly Turnover Rate + 0.3 * Annual Turnover Rate $[15][16] **Factor Evaluation**: Strong performance in high-volatility stocks[15][16] - **Factor Name**: Valuation **Factor Construction Idea**: Assesses stock valuation using price-to-book ratio **Factor Construction Process**: Calculated as the inverse of the price-to-book ratio[15][16] **Factor Evaluation**: Performs well in identifying undervalued stocks[15][16] Factor Backtesting Results - **Beta**: Weekly excess return 0.17%, monthly excess return 0.32%, six-month excess return 4.09%, year-to-date excess return 3.93%[32] - **Momentum**: Weekly excess return -0.38%, monthly excess return -0.04%, six-month excess return 3.56%, year-to-date excess return 2.82%[32] - **Volatility**: Weekly excess return 0.55%, monthly excess return 0.40%, six-month excess return 6.40%, year-to-date excess return 6.31%[32] - **Valuation**: Weekly excess return 0.13%, monthly excess return 0.39%, six-month excess return 7.59%, year-to-date excess return 7.56%[32]

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].