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 Models and Construction Methods Model Name: DFQ-FactorGCL - **Model Construction Idea**: Based on hypergraph convolutional neural networks and temporal residual contrastive learning for stock return prediction[6] - **Model Construction Process**: The model uses hypergraph convolutional neural networks to capture complex relationships between stocks and temporal residual contrastive learning to enhance prediction accuracy[6] - **Model Evaluation**: The model is effective in capturing stock trends and improving prediction accuracy[6] Model Name: Neural ODE - **Model Construction Idea**: Reconstructing time series dynamic systems for deep learning factor mining[6] - **Model Construction Process**: The model uses ordinary differential equations to model the continuous dynamics of stock prices, allowing for more accurate factor extraction[6] - **Model Evaluation**: The model provides a novel approach to factor mining, improving the robustness and accuracy of predictions[6] Model Name: DFQ-FactorVAE-pro - **Model Construction Idea**: Incorporating feature selection and environmental variable modules into the FactorVAE model[6] - **Model Construction Process**: The model uses variational autoencoders with additional modules for feature selection and environmental variables to enhance stock selection[6] - **Model Evaluation**: The model improves stock selection by considering more comprehensive factors and environmental variables[6] Quantitative Factors and Construction Methods Factor Name: Beta - **Factor Construction Idea**: Bayesian compressed market Beta[16] - **Factor Construction Process**: The factor is constructed by compressing the market Beta using Bayesian methods to capture market sensitivity[16] - **Factor Evaluation**: The factor is effective in identifying stocks with high market sensitivity[12] Factor Name: Volatility - **Factor Construction Idea**: Average logarithmic turnover rate over the past 243 days[16] - **Factor Construction Process**: The factor is calculated using the average logarithmic turnover rate and its regression with the market turnover rate over the past 243 days[16] - **Factor Evaluation**: The factor captures the demand for high volatility assets[12] Factor Name: Liquidity - **Factor Construction Idea**: Average logarithmic turnover rate over the past 243 days[16] - **Factor Construction Process**: The factor is calculated using the average logarithmic turnover rate and its regression with the market turnover rate over the past 243 days[16] - **Factor Evaluation**: The factor indicates the demand for high liquidity assets[12] Factor Name: Value - **Factor Construction Idea**: Book-to-market ratio (BP) and earnings yield (EP)[16] - **Factor Construction Process**: The factor is calculated using the book-to-market ratio and earnings yield[16] - **Factor Evaluation**: The factor shows limited recognition of value investment strategies[12] Factor Name: Growth - **Factor Construction Idea**: State-owned enterprise stock proportion[16] - **Factor Construction Process**: The factor is calculated using the proportion of state-owned enterprise stocks[16] - **Factor Evaluation**: The factor indicates the market's attention to state-owned enterprise stocks[12] Factor Name: Cubic Size - **Factor Construction Idea**: Market capitalization power term[16] - **Factor Construction Process**: The factor is calculated using the market capitalization power term[16] - **Factor Evaluation**: The factor shows the market's reduced attention to micro-cap stocks[12] Factor Name: Trend - **Factor Construction Idea**: EWMA with different half-lives[18] - **Factor Construction Process**: The factor is calculated using EWMA with half-lives of 20, 120, and 240 days, standard volatility, FF3 specific volatility, range, and maximum and minimum returns over the past 243 days[18] - **Factor Evaluation**: The factor indicates the market's reduced preference for trend investment strategies[12] Factor Name: Certainty - **Factor Construction Idea**: Sales growth, institutional holding percentage, net asset growth, analyst coverage, and listing days[18] - **Factor Construction Process**: The factor is calculated using sales growth, institutional holding percentage, net asset growth, analyst coverage, and listing days[18] - **Factor Evaluation**: The factor shows the market's reduced confidence in certainty investment strategies[12] Factor Performance Monitoring Performance in Different Index Spaces - **CSI 300 Index**: Factors like expected PEG, DELTAROE, and single-quarter EP performed well, while three-month reversal and one-month volatility performed poorly[7][24][26] - **CSI 500 Index**: Factors like one-year momentum and expected ROE change performed well, while three-month reversal and three-month institutional coverage performed poorly[7][28][30] - **CSI 800 Index**: Factors like expected ROE change and DELTAROE performed well, while one-month volatility and three-month reversal performed poorly[7][32][34] - **CSI 1000 Index**: Factors like DELTAROA and single-quarter net profit growth performed well, while public holding market value and standardized unexpected revenue performed poorly[7][36][37] - **CNI 2000 Index**: Factors like non-liquidity impact and expected PEG performed well, while public holding market value and one-month volatility performed poorly[7][39][41] - **ChiNext Index**: Factors like three-month earnings adjustment and single-quarter EP performed well, while expected net profit change and expected ROE change performed poorly[7][43][45] - **CSI All Index**: Factors like one-month UMR and one-month reversal performed well, while one-month volatility and three-month volatility performed poorly[7][47][50] Factor Backtesting Results CSI 300 Index - **Expected PEG**: 0.75% (recent week), 2.07% (recent month), 7.23% (year-to-date), 5.96% (annualized)[24] - **DELTAROE**: 0.73% (recent week), 2.19% (recent month), 7.91% (year-to-date), 5.07% (annualized)[24] - **Single-quarter EP**: 0.71% (recent week), 0.96% (recent month), 5.93% (year-to-date), 7.58% (annualized)[24] CSI 500 Index - **One-year momentum**: 0.84% (recent week), 2.33% (recent month), 3.83% (year-to-date), 3.00% (annualized)[28] - **Expected ROE change**: 0.76% (recent week), 0.28% (recent month), 6.15% (year-to-date), 7.67% (annualized)[28] - **Three-month UMR**: 0.74% (recent week), -0.38% (recent month), 0.29% (year-to-date), -1.06% (annualized)[28] CSI 800 Index - **Expected ROE change**: 0.93% (recent week), 1.76% (recent month), 2.27% (year-to-date), -3.20% (annualized)[32] - **Expected PEG**: 0.83% (recent week), 2.60% (recent month), 10.99% (year-to-date), 10.96% (annualized)[32] - **DELTAROE**: 0.79% (recent week), 2.64% (recent month), 11.60% (year-to-date), 8.99% (annualized)[32] CSI 1000 Index - **DELTAROA**: 0.63% (recent week), 1.57% (recent month), 8.06% (year-to-date), 15.10% (annualized)[36] - **Single-quarter net profit growth**: 0.57% (recent week), 1.03% (recent month), 8.04% (year-to-date), 10.77% (annualized)[36] - **One-month UMR**: 0.47% (recent week), -0.92% (recent month), 1.13% (year-to-date), -3.13% (annualized)[36] CNI 2000 Index - **Non-liquidity impact**: 1.26% (recent week), 1.99% (recent month), 12.11% (year-to-date), 21.51% (annualized)[39] - **Expected PEG**: 0.54% (recent week), 0.32% (recent month), 10.32% (year-to-date), 36.23% (annualized)[39] - **Three-month institutional coverage**: 0.54% (recent week), 4.56% (recent month), 5.41% (year-to-date), -1.19% (annualized)[39] ChiNext Index - **Three-month earnings adjustment**: 0.66% (recent week), 0.53% (recent month), -12.72% (year-to-date), -28.10% (annualized)[43] - **Single-quarter EP**: 0.66% (recent week), 0.69% (recent month), 2.90% (year-to-date), 24.70% (annualized)[43] - **PB_ROE rank difference**: 0.61% (recent week), -0.26% (

Quantitative Factors and Models Summary Quantitative Factors and Their Construction - **Factor Name**: Standardized Unexpected Revenue (SUR) - **Construction Idea**: Measures the deviation of actual revenue from analysts' expectations, standardized by the standard deviation of expected revenue[20][27][31] - **Construction Process**: $ SUR = \frac{Actual\ Revenue - Expected\ Revenue}{Standard\ Deviation\ of\ Expected\ Revenue} $ - The numerator represents the difference between actual and expected revenue - The denominator is the standard deviation of expected revenue, ensuring comparability across stocks[20][27][31] - **Evaluation**: Demonstrated strong performance across multiple indices, indicating its effectiveness in capturing unexpected revenue trends[8][27][31] - **Factor Name**: Delta ROA - **Construction Idea**: Tracks the year-over-year change in Return on Assets (ROA) to capture profitability trends[20][31][39] - **Construction Process**: $ \Delta ROA = ROA_{Current\ Quarter} - ROA_{Same\ Quarter\ Last\ Year} $ - ROA is calculated as $ \frac{Net\ Income}{Total\ Assets} $ - The factor highlights improvements or deteriorations in asset efficiency[20][31][39] - **Evaluation**: Consistently strong performance, particularly in small-cap indices like the CSI 1000 and CSI 2000, suggesting its relevance in growth-oriented stocks[8][39][43] - **Factor Name**: Standardized Unexpected Earnings (SUE) - **Construction Idea**: Similar to SUR, measures the deviation of actual earnings from analysts' expectations, standardized by the standard deviation of expected earnings[20][31][39] - **Construction Process**: $ SUE = \frac{Actual\ Earnings - Expected\ Earnings}{Standard\ Deviation\ of\ Expected\ Earnings} $ - The numerator captures the earnings surprise - The denominator ensures standardization for comparability[20][31][39] - **Evaluation**: Strong performance in indices like CSI 500 and CSI 800, indicating its ability to capture earnings surprises effectively[8][27][31] - **Factor Name**: Delta ROE - **Construction Idea**: Measures the year-over-year change in Return on Equity (ROE) to identify shifts in shareholder profitability[20][31][39] - **Construction Process**: $ \Delta ROE = ROE_{Current\ Quarter} - ROE_{Same\ Quarter\ Last\ Year} $ - ROE is calculated as $ \frac{Net\ Income}{Shareholders'\ Equity} $ - Highlights changes in equity efficiency over time[20][31][39] - **Evaluation**: Demonstrated strong performance in growth-oriented indices, particularly the CSI 1000 and Growth Enterprise Market (GEM) indices[8][39][43] Factor Backtesting Results - **Standardized Unexpected Revenue (SUR)** - CSI 500: Weekly return 1.43%, monthly return 1.66%, annualized return 12.83%[27] - CSI 800: Weekly return 1.36%, monthly return 2.61%, annualized return 4.26%[31] - CSI All Share: Weekly return 1.37%, monthly return 1.95%, annualized return 6.91%[47] - **Delta ROA** - CSI 1000: Weekly return 0.56%, monthly return 1.67%, annualized return 11.51%[35] - CSI 2000: Weekly return 1.90%, monthly return 1.90%, annualized return 27.67%[39] - CSI All Share: Weekly return 1.10%, monthly return 2.33%, annualized return 7.78%[47] - **Standardized Unexpected Earnings (SUE)** - CSI 500: Weekly return 1.39%, monthly return 2.75%, annualized return 7.19%[27] - CSI 800: Weekly return 0.52%, monthly return 1.33%, annualized return 3.04%[31] - CSI All Share: Weekly return 1.09%, monthly return 2.46%, annualized return 0.72%[47] - **Delta ROE** - CSI 1000: Weekly return 0.30%, monthly return 1.59%, annualized return 8.89%[35] - CSI 2000: Weekly return 1.24%, monthly return 1.21%, annualized return 90.84%[39] - GEM: Weekly return 1.03%, monthly return 2.76%, annualized return 21.85%[43] Quantitative Model Construction - **Model Name**: Maximized Factor Exposure (MFE) Portfolio - **Construction Idea**: Constructs portfolios that maximize exposure to a single factor while controlling for industry, style, and stock-specific constraints[62][63][66] - **Construction Process**: $ \begin{array}{ll} max & f^{T}w \\ s.t. & s_{l} \leq X(w-w_{b}) \leq s_{h} \\ & h_{l} \leq H(w-w_{b}) \leq h_{h} \\ & w_{l} \leq w-w_{b} \leq w_{h} \\ & b_{l} \leq B_{b}w \leq b_{h} \\ & 0 \leq w \leq l \\ & 1^{T}w = 1 \\ & \Sigma|w-w_{0}| \leq to_{h} \end{array} $ - Maximizes factor exposure $ f^{T}w $ - Constraints include style, industry, stock-specific deviations, and turnover limits[62][63][66] - **Evaluation**: Effective in isolating factor performance under realistic portfolio constraints, widely used in index enhancement strategies[62][63][66] Model Backtesting Results - **MFE Portfolio** - CSI 300: Weekly excess return max 1.67%, min -0.65%, median 0.21%[54] - CSI 500: Weekly excess return max 1.13%, min -0.76%, median 0.24%[57] - CSI 1000: Weekly excess return max 1.11%, min -0.52%, median 0.24%[61]

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]