Quantitative Models and Factor Analysis Quantitative Models and Construction Methods Model: DFQ-FactorGCL - **Construction Idea**: This model is based on hypergraph convolutional neural networks and time residual contrastive learning for stock return prediction[7] - **Construction Process**: The detailed construction process is not provided in the document - **Evaluation**: The model is part of the factor stock selection series, indicating its relevance in stock return prediction[7] Model: Neural ODE - **Construction Idea**: This model reconstructs time-series dynamic systems for deep learning factor mining[7] - **Construction Process**: The detailed construction process is not provided in the document - **Evaluation**: The model is part of the factor stock selection series, indicating its relevance in factor mining[7] Model Backtesting Results DFQ-FactorGCL Model - **IR**: Not provided - **Return**: Not provided - **Volatility**: Not provided Neural ODE Model - **IR**: Not provided - **Return**: Not provided - **Volatility**: Not provided Quantitative Factors and Construction Methods Factor: Beta - **Construction Idea**: Measures the sensitivity of a stock's returns to market returns[11] - **Construction Process**: - Bayesian compressed market Beta[16] - **Evaluation**: Beta factor showed a significant positive return of 3.74% this week, indicating a strong market preference for high Beta stocks[11] Factor: Volatility - **Construction Idea**: Measures the degree of variation in a stock's returns[11] - **Construction Process**: - Stdvol: Standard deviation of returns over the past 243 days - Ivff: FF3 idiosyncratic volatility over the past 243 days - Range: Highest price/lowest price - 1 over the past 243 days - MaxRet_6: Average return of the highest six days over the past 243 days - MinRet_6: Average return of the lowest six days over the past 243 days[16] - **Evaluation**: Volatility factor showed a significant positive return of 3.41% this week, indicating increased demand for high volatility assets[11] Factor: Liquidity - **Construction Idea**: Measures the ease with which a stock can be bought or sold without affecting its price[11] - **Construction Process**: - TO: Average log turnover rate over the past 243 days - Liquidity beta: Regression of individual stock log turnover rate against market log turnover rate over the past 243 days[16] - **Evaluation**: Liquidity factor showed a significant positive return of 3.34% this week, indicating increased demand for high liquidity assets[11] Factor: SOE (State-Owned Enterprise) - **Construction Idea**: Measures the proportion of state ownership in a company[11] - **Construction Process**: - State Owned Enterprise: Proportion of state ownership[16] - **Evaluation**: SOE factor showed a positive return of 0.63% this week, indicating a slight increase in market attention to state-owned enterprise stocks[11] Factor: Growth - **Construction Idea**: Measures the growth potential of a company[12] - **Construction Process**: - Delta ROE: Average change in ROE over the past 3 years - Sales_growth: 3-year compound growth rate of sales revenue - Na_growth: 3-year compound growth rate of net assets[16] - **Evaluation**: Growth factor showed a negative return of -0.33% this week, indicating low market preference for growth stocks[12] Factor: Certainty - **Construction Idea**: Measures the certainty of a company's future performance[12] - **Construction Process**: - Instholder Pct: Proportion of public fund holdings - Cov: Analyst coverage (orthogonalized to market value) - Listdays: Number of days listed[16] - **Evaluation**: Certainty factor showed a significant negative return of -0.83% this week, indicating reduced market confidence in certainty investment strategies[12] Factor: Cubic Size - **Construction Idea**: Measures the size of a company using a power function of market value[12] - **Construction Process**: - Market value power term[16] - **Evaluation**: Cubic Size factor showed a significant negative return of -1.51% this week, indicating reduced market attention to extreme market value-related assets[12] Factor: Trend - **Construction Idea**: Measures the trend-following behavior of a stock[12] - **Construction Process**: - Trend_120: EWMA(halflife=20)/EWMA(halflife=120) - Trend_240: EWMA(halflife=20)/EWMA(halflife=240)[16] - **Evaluation**: Trend factor showed a significant negative return of -1.96% this week, indicating reduced market preference for trend investment strategies[12] Factor: Size - **Construction Idea**: Measures the size of a company using the logarithm of market value[12] - **Construction Process**: - Logarithm of market value[16] - **Evaluation**: Size factor showed a significant negative return of -2.14% this week, indicating reduced market attention to small-cap stocks[12] Factor: Value - **Construction Idea**: Measures the value of a company using various valuation metrics[12] - **Construction Process**: - BP: Book-to-market ratio - EP: Earnings yield[16] - **Evaluation**: Value factor showed a significant negative return of -2.40% this week, indicating reduced market recognition of value investment strategies[12] Factor Backtesting Results Beta Factor - **Recent Week**: 3.74%[13] - **Recent Month**: 10.06%[13] - **Year-to-Date**: 27.17%[13] - **Last Year**: 59.45%[13] - **Historical Annualized**: 1.21%[13] Volatility Factor - **Recent Week**: 3.41%[13] - **Recent Month**: 6.01%[13] - **Year-to-Date**: 9.97%[13] - **Last Year**: 35.11%[13] - **Historical Annualized**: -12.85%[13] Liquidity Factor - **Recent Week**: 3.34%[13] - **Recent Month**: 3.92%[13] - **Year-to-Date**: 20.65%[13] - **Last Year**: 32.29%[13] - **Historical Annualized**: -3.28%[13] SOE Factor - **Recent Week**: 0.63%[13] - **Recent Month**: 1.44%[13] - **Year-to-Date**: 7.38%[13] - **Last Year**: 14.87%[13] - **Historical Annualized**: 7.22%[13] Growth Factor - **Recent Week**: -0.33%[13] - **Recent Month**: -2.55%[13] - **Year-to-Date**: -2.67%[13] - **Last Year**: 0.62%[13] - **Historical Annualized**: 2.63%[13] Certainty Factor - **Recent Week**: -0.83%[13] - **Recent Month**: -3.85%[13] - **Year-to-Date**: -14.30%[13] - **Last Year**: -20.88%[13] - **Historical Annualized**: 2.44%[13] Cubic Size Factor - **Recent Week**: -1.51%[13] - **Recent Month**: 0.59%[13] - **Year-to-Date**: -30.87%[13] - **Last Year**: -50.44%[13] - **Historical Annualized**: -26.52%[13] Trend Factor - **Recent Week**: -1.96%[13] - **Recent Month**: -3.40%[13] - **Year-to-Date**: -4.05%[13] - **Last Year**: 18.60%[13] - **Historical Annualized**: 13.97%[13] Size Factor - **Recent Week**: -2.14%[13] - **Recent Month**: -2.79%[13] - **Year-to-Date**: -38.32%[13] - **Last Year**: -59.18%[13] - **Historical Annualized**: -29.70%[13] Value Factor - **Recent Week**: -2.40%[13] - **Recent Month**: -6.37%[13] - **Year-to-Date**: -15.60%[13] - **Last Year**: -29.84%[13] - **Historical Annualized**: 6.76%[13]

Quantitative Factors and Construction Methods 1. Factor Name: Beta - **Construction Idea**: Measures the sensitivity of a stock's return to market movements, capturing the market's preference for high Beta stocks [11] - **Construction Process**: Beta is calculated using Bayesian shrinkage to compress the market Beta [16] - **Evaluation**: Beta factor showed strong performance this week, with a return of 1.94%, indicating a sustained market preference for high Beta stocks [11][13] 2. Factor Name: Volatility - **Construction Idea**: Captures the market's preference for high-volatility assets [11] - **Construction Process**: Includes multiple metrics such as: - Stdvol: Standard deviation of daily returns over the past 243 days - Ivff: Idiosyncratic volatility from Fama-French 3-factor model over 243 days - Range: High/low price range over 243 days - MaxRet_6: Average return of the six highest-return days in the past 243 days - MinRet_6: Average return of the six lowest-return days in the past 243 days [16] - **Evaluation**: Volatility factor rebounded significantly this week, with a return of 0.82%, reflecting increased demand for high-volatility assets [11][13] 3. Factor Name: One-Year Momentum - **Construction Idea**: Measures the cumulative return over the past year, excluding the most recent month, to capture momentum effects [20] - **Construction Process**: Calculated as the cumulative return over the past 12 months, excluding the most recent month [20] - **Evaluation**: One-year momentum factor performed well in multiple indices, including: - CSI 500: Weekly return of 0.90% [27] - CSI 1000: Weekly return of 0.81% [35] - CSI All Share: Weekly return of 2.25% [47] 4. Factor Name: Standardized Unexpected Revenue (SUR) - **Construction Idea**: Measures the deviation of actual revenue from analyst expectations, standardized by the standard deviation of expected revenue [20] - **Construction Process**: $ SUR = \frac{\text{Actual Revenue} - \text{Expected Revenue}}{\text{Standard Deviation of Expected Revenue}} $ [20] - **Evaluation**: SUR factor showed strong performance across indices: - CSI 800: Weekly return of 1.37% [31] - CSI 1000: Weekly return of 0.86% [35] - CSI All Share: Weekly return of 1.53% [47] 5. Factor Name: Three-Month Reversal - **Construction Idea**: Captures short-term mean-reversion effects in stock prices [20] - **Construction Process**: Calculated as the cumulative return over the past three months, with a negative sign to reflect reversal [20] - **Evaluation**: Three-month reversal factor performed well in: - CSI 1000: Weekly return of 1.04% [35] - CNI 2000: Weekly return of 1.76% [39] --- Factor Backtesting Results 1. Beta Factor - Weekly Return: 1.94% - Monthly Return: 7.88% - Year-to-Date Return: 17.34% - Annualized Return (1 Year): 51.27% [13] 2. Volatility Factor - Weekly Return: 0.82% - Monthly Return: 1.86% - Year-to-Date Return: 5.96% - Annualized Return (1 Year): 27.16% [13] 3. One-Year Momentum Factor - CSI 500 Weekly Return: 0.90% [27] - CSI 1000 Weekly Return: 0.81% [35] - CSI All Share Weekly Return: 2.25% [47] 4. Standardized Unexpected Revenue Factor - CSI 800 Weekly Return: 1.37% [31] - CSI 1000 Weekly Return: 0.86% [35] - CSI All Share Weekly Return: 1.53% [47] 5. Three-Month Reversal Factor - CSI 1000 Weekly Return: 1.04% [35] - CNI 2000 Weekly Return: 1.76% [39] --- Factor Portfolio Construction: Maximized Factor Exposure (MFE) Construction Process - **Objective Function**: Maximize single-factor exposure $ \text{max } f^{T}w $ - **Constraints**: - Style exposure limits: $ s_{l} \leq X(w-w_{b}) \leq s_{h} $ - Industry exposure limits: $ h_{l} \leq H(w-w_{b}) \leq h_{h} $ - Stock weight deviation limits: $ w_{l} \leq w-w_{b} \leq w_{h} $ - Component stock weight limits: $ b_{l} \leq B_{b}w \leq b_{h} $ - No short-selling: $ 0 \leq w \leq l $ - Full investment: $ 1^{T}w = 1 $ - Turnover limits: $ \Sigma|w-w_{0}| \leq to_{h} $ [59][60][62] Backtesting Process 1. Set constraints for style, industry, and stock weight deviations 2. Construct MFE portfolios monthly 3. Calculate historical returns and risk metrics, adjusting for transaction costs [63][64]

- The Beta factor showed a significant positive return of 6.95% this week, indicating a strong market preference for high Beta stocks [10] - The Liquidity factor also performed well with a return of 5.53%, reflecting increased demand for highly liquid assets [10] - The Volatility factor improved significantly with a return of 4.19%, showing heightened market interest in high-volatility assets [10] - The Trend factor experienced a notable decline, with a return of -1.76%, indicating a reduced market preference for trend-following strategies [11] - The Size factor showed a significant drop with a return of -3.30%, indicating a decreased market focus on small-cap stocks [11] - The Value factor also declined sharply, with a return of -3.55%, reflecting a reduced market preference for value investment strategies [11] - The one-year momentum factor performed well across various indices, including the CSI 500 and CSI 1000, indicating strong performance in the past year [7][24][30] - The DELTAROE factor showed strong performance in indices like the CSI 800 and CSI 2000, indicating robust profitability growth [27][33] - The three-month reversal factor also performed well in multiple indices, reflecting a strong short-term reversal trend [7][24][27] - The UMR factors, including one-month, three-month, and six-month UMR, generally performed poorly across various indices, indicating weak momentum [7][24][27][30] - The public fund index enhancement products for the CSI 300, CSI 500, and CSI 1000 showed varying levels of excess returns, with the CSI 300 products generally outperforming the others [7][46][48][50] - The MFE (Maximized Factor Exposure) portfolio construction method was used to evaluate the effectiveness of individual factors under various constraints, ensuring controlled industry and style exposures [51][52][54][55]

Group 1 - The core viewpoint of the article is to track the performance of various index enhancement portfolios and stock selection factors across different indices, highlighting their excess returns and factor performance over the recent week and year-to-date [1][2][3]. Group 2 - The performance of the HuShen 300 index enhancement portfolio showed an excess return of -1.26% for the week and 1.88% year-to-date [5]. - The performance of the ZhongZheng 500 index enhancement portfolio showed an excess return of -0.50% for the week and 3.40% year-to-date [5]. - The ZhongZheng 1000 index enhancement portfolio had an excess return of -0.78% for the week and 4.40% year-to-date [5]. - The ZhongZheng A500 index enhancement portfolio reported an excess return of -0.22% for the week and 4.88% year-to-date [5]. Group 3 - In the HuShen 300 component stocks, factors such as one-year momentum, one-month reversal, and DELTAROE performed well [6]. - In the ZhongZheng 500 component stocks, factors like one-month reversal, SPTTM, and executive compensation showed strong performance [6]. - For ZhongZheng 1000 component stocks, factors such as non-liquidity shock, three-month earnings adjustments, and expected net profit month-on-month performed well [6]. - In the ZhongZheng A500 component stocks, one-month reversal, one-year momentum, and executive compensation were among the top-performing factors [6]. Group 4 - The HuShen 300 index enhancement products had a maximum excess return of 0.44%, a minimum of -0.66%, and a median of -0.06% for the week [19]. - The ZhongZheng 500 index enhancement products had a maximum excess return of 0.48%, a minimum of -1.30%, and a median of -0.35% for the week [19]. - The ZhongZheng 1000 index enhancement products had a maximum excess return of 1.09%, a minimum of -0.82%, and a median of -0.06% for the week [19]. - The ZhongZheng A500 index enhancement products had a maximum excess return of 0.46%, a minimum of -0.38%, and a median of -0.22% for the week [19]. Group 5 - The total number of public fund index enhancement products includes 67 for HuShen 300 with a total scale of 77.8 billion, 69 for ZhongZheng 500 with 45.2 billion, 46 for ZhongZheng 1000 with 15 billion, and 35 for ZhongZheng A500 with 22.3 billion [16].