Quantitative Factors and Models Summary Quantitative Factors and Construction - **Factor Name**: Beta Factor **Construction Idea**: Measures the sensitivity of a stock's returns to market movements, capturing systematic risk **Performance**: Achieved a positive return of 0.73% this week, indicating a preference for high-beta stocks in the market [18] - **Factor Name**: Market Capitalization Factor **Construction Idea**: Captures the size effect, favoring large-cap stocks **Performance**: Delivered a positive return of 0.58%, reflecting a large-cap style in the market this week [18] - **Factor Name**: Growth Factor **Construction Idea**: Identifies stocks with high growth potential based on financial metrics **Performance**: Generated a positive return of 0.21% this week [18] - **Factor Name**: Non-linear Market Capitalization Factor **Construction Idea**: Aims to capture non-linear effects of market capitalization on stock returns **Performance**: Achieved a positive return of 0.21% this week [18] - **Factor Name**: Leverage Factor **Construction Idea**: Measures the financial leverage of a company, often linked to risk and return trade-offs **Performance**: Recorded a negative return of -0.25% this week [18] - **Factor Name**: Total Asset Growth Rate **Construction Idea**: Measures the growth in total assets, indicating expansion and investment **Performance**: Positive returns across multiple stock pools: - 2.41% in CSI 300 [12][13] - 2.12% in CSI 500 [14][15] - 1.09% in Liquidity 1500 [16][17] - **Factor Name**: Total Asset Gross Profit Margin (TTM) **Construction Idea**: Evaluates profitability relative to total assets over a trailing twelve-month period **Performance**: Positive returns across stock pools: - 2.02% in CSI 300 [12][13] - -0.54% in CSI 500 [14][15] - -0.02% in Liquidity 1500 [16][17] - **Factor Name**: ROE Stability **Construction Idea**: Measures the consistency of return on equity over time **Performance**: Positive returns across stock pools: - 1.53% in CSI 500 [14][15] - 1.22% in Liquidity 1500 [16][17] - **Factor Name**: ROA Stability **Construction Idea**: Measures the consistency of return on assets over time **Performance**: Positive returns across stock pools: - 0.76% in CSI 500 [14][15] - 1.89% in Liquidity 1500 [16][17] Quantitative Models and Construction - **Model Name**: PB-ROE-50 Portfolio **Construction Idea**: Combines price-to-book (PB) and return on equity (ROE) metrics to select stocks with strong valuation and profitability characteristics **Construction Process**: - Stocks are ranked based on PB and ROE metrics - Top 50 stocks are selected to form the portfolio - Portfolio is rebalanced periodically [23][24] **Performance**: - 1.04% excess return in CSI 500 - -0.28% excess return in CSI 800 - -0.03% excess return in the overall market [23][24] - **Model Name**: Institutional Research Portfolio **Construction Idea**: Tracks stocks frequently researched by public and private institutions, assuming their research signals potential outperformance **Performance**: - Public research strategy: 2.22% excess return relative to CSI 800 - Private research strategy: 1.51% excess return relative to CSI 800 [25][26] - **Model Name**: Block Trade Portfolio **Construction Idea**: Focuses on stocks with high block trade ratios and low short-term volatility, assuming these characteristics indicate informed trading **Construction Process**: - Stocks are ranked based on block trade ratios and 6-day trading volume volatility - Portfolio is rebalanced monthly [29][30] **Performance**: -0.98% excess return relative to CSI All Share Index [29][30] - **Model Name**: Private Placement Portfolio **Construction Idea**: Leverages event-driven strategies around private placements, considering factors like market capitalization and timing **Construction Process**: - Stocks involved in private placements are selected based on shareholder meeting announcements - Portfolio is adjusted for market capitalization and rebalanced periodically [34][35] **Performance**: -0.21% excess return relative to CSI All Share Index [34][35] Factor Backtesting Results - **Beta Factor**: Weekly return of 0.73% [18] - **Market Capitalization Factor**: Weekly return of 0.58% [18] - **Growth Factor**: Weekly return of 0.21% [18] - **Non-linear Market Capitalization Factor**: Weekly return of 0.21% [18] - **Leverage Factor**: Weekly return of -0.25% [18] - **Total Asset Growth Rate**: - CSI 300: 2.41% [12][13] - CSI 500: 2.12% [14][15] - Liquidity 1500: 1.09% [16][17] - **Total Asset Gross Profit Margin (TTM)**: - CSI 300: 2.02% [12][13] - CSI 500: -0.54% [14][15] - Liquidity 1500: -0.02% [16][17] - **ROE Stability**: - CSI 500: 1.53% [14][15] - Liquidity 1500: 1.22% [16][17] - **ROA Stability**: - CSI 500: 0.76% [14][15] - Liquidity 1500: 1.89% [16][17] Model Backtesting Results - **PB-ROE-50 Portfolio**: - CSI 500: 1.04% excess return - CSI 800: -0.28% excess return - Overall market: -0.03% excess return [23][24] - **Institutional Research Portfolio**: - Public strategy: 2.22% excess return relative to CSI 800 - Private strategy: 1.51% excess return relative to CSI 800 [25][26] - **Block Trade Portfolio**: -0.98% excess return relative to CSI All Share Index [29][30] - **Private Placement Portfolio**: -0.21% excess return relative to CSI All Share Index [34][35]

Quantitative Models and Construction Methods 1. Model Name: PB-ROE-50 Combination - **Model Construction Idea**: This model focuses on selecting stocks with low Price-to-Book (PB) ratios and high Return on Equity (ROE) to construct a portfolio that aims to achieve excess returns[24] - **Model Construction Process**: The portfolio is constructed by screening stocks based on their PB and ROE metrics. Stocks with the lowest PB ratios and highest ROE values are selected to form the top 50 stocks in the portfolio. The portfolio is rebalanced periodically to maintain the selection criteria[24] - **Model Evaluation**: The model demonstrates significant excess returns in the all-market stock pool, though it underperforms in specific indices like the CSI 500 and CSI 800[24][25] 2. Model Name: Public and Private Institutional Research Combination - **Model Construction Idea**: This model leverages the stock selection strategies of public and private institutional research to identify stocks with potential for excess returns[27] - **Model Construction Process**: The portfolio is constructed by tracking the stocks that public and private institutions have recently researched. Stocks with higher research frequency or positive sentiment are included in the portfolio. The portfolio is rebalanced periodically to reflect updated research data[27] - **Model Evaluation**: The public institutional research strategy shows significant excess returns compared to the CSI 800 index, while the private institutional research strategy also achieves positive but smaller excess returns[27][28] 3. Model Name: Block Trade Combination - **Model Construction Idea**: This model identifies stocks with high block trade activity and low volatility, as these characteristics are associated with better subsequent performance[31] - **Model Construction Process**: The portfolio is constructed 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 selected. The portfolio is rebalanced monthly[31] - **Model Evaluation**: The model experienced a drawdown in the past week, with negative excess returns relative to the CSI All Share Index[31][32] 4. Model Name: Directed Issuance Combination - **Model Construction Idea**: This model focuses on stocks involved in directed issuance events, which are analyzed for their potential investment value based on event-driven factors[37] - **Model Construction Process**: The portfolio is constructed by identifying stocks with directed issuance announcements. Factors such as market capitalization, rebalancing cycles, and position control are considered. The portfolio is rebalanced periodically to reflect new issuance events[37] - **Model Evaluation**: The model experienced a drawdown in the past week, with negative excess returns relative to the CSI All Share Index[37][38] --- Model Backtesting Results 1. PB-ROE-50 Combination - **Weekly Excess Return**: All-market stock pool: +0.79%; CSI 500: -0.57%; CSI 800: -0.02%[24][25] - **Year-to-Date Excess Return**: All-market stock pool: +22.30%; CSI 500: +3.00%; CSI 800: +16.16%[25] - **Weekly Absolute Return**: All-market stock pool: +2.87%; CSI 500: +2.79%; CSI 800: +1.89%[25] - **Year-to-Date Absolute Return**: All-market stock pool: +48.27%; CSI 500: +28.59%; CSI 800: +36.42%[25] 2. Public and Private Institutional Research Combination - **Weekly Excess Return**: Public research: +3.82%; Private research: +0.51%[27][28] - **Year-to-Date Excess Return**: Public research: +8.10%; Private research: +12.02%[28] - **Weekly Absolute Return**: Public research: +5.81%; Private research: +2.44%[28] - **Year-to-Date Absolute Return**: Public research: +26.96%; Private research: +31.56%[28] 3. Block Trade Combination - **Weekly Excess Return**: -1.77%[31][32] - **Year-to-Date Excess Return**: +0.26%[32] - **Weekly Absolute Return**: Not explicitly stated - **Year-to-Date Absolute Return**: +62.65%[32] 4. Directed Issuance Combination - **Weekly Excess Return**: -1.71%[37][38] - **Year-to-Date Excess Return**: -0.77%[38] - **Weekly Absolute Return**: Not explicitly stated - **Year-to-Date Absolute Return**: +20.29%[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[20] - **Factor Construction Process**: Beta is calculated using regression analysis of a stock's returns against the market index over a specified period[20] - **Factor Evaluation**: Demonstrated significant positive returns in the past week, indicating a preference for high-beta stocks[20] 2. Factor Name: Momentum Factor - **Factor Construction Idea**: Captures the tendency of stocks with strong past performance to continue performing well in the short term[20] - **Factor Construction Process**: Momentum is calculated based on the cumulative returns of a stock over a specific lookback period, such as 1 month or 5 days[20][22] - **Factor Evaluation**: Significant positive returns were observed, with notable momentum effects in sectors like media, real estate, and agriculture[20][22] 3. Factor Name: Scale Factor - **Factor Construction Idea**: Reflects the size effect, where larger-cap stocks tend to outperform smaller-cap stocks in certain market conditions[20] - **Factor Construction Process**: Scale is measured using market capitalization, with adjustments for sector and industry effects[20] - **Factor Evaluation**: Demonstrated positive returns, indicating a preference for large-cap stocks in the past week[20] --- Factor Backtesting Results 1. Beta Factor - **Weekly Return**: +0.70%[20] 2. Momentum Factor - **Weekly Return**: +0.46%[20] 3. Scale Factor - **Weekly Return**: +0.16%[20]

Quantitative Models and Construction PB-ROE-50 Model - **Model Name**: PB-ROE-50 - **Model Construction Idea**: The model combines Price-to-Book (PB) and Return on Equity (ROE) metrics to identify stocks with strong profitability and reasonable valuation[24] - **Model Construction Process**: The PB-ROE-50 portfolio is constructed by selecting 50 stocks based on a combination of PB and ROE metrics. The portfolio is rebalanced periodically to maintain the desired exposure to these factors[24] - **Model Evaluation**: The model demonstrates consistent positive excess returns across different stock pools, indicating its effectiveness in capturing value and profitability signals[24] --- Quantitative Factors and Construction Standardized Unexpected Earnings (SUE) - **Factor Name**: Standardized Unexpected Earnings (SUE) - **Factor Construction Idea**: Measures the deviation of actual earnings from expected earnings, standardized by historical earnings volatility[12] - **Factor Construction Process**: $ SUE = \frac{E_{actual} - E_{expected}}{\sigma_{earnings}} $ Where: $E_{actual}$ = Actual earnings $E_{expected}$ = Expected earnings $\sigma_{earnings}$ = Standard deviation of historical earnings[12] - **Factor Evaluation**: Demonstrates strong positive returns in the CSI 300 stock pool, indicating its ability to capture earnings surprises effectively[12] Single-Quarter ROE YoY Growth - **Factor Name**: Single-Quarter ROE YoY Growth - **Factor Construction Idea**: Measures the year-over-year growth in Return on Equity (ROE) for a single quarter[14] - **Factor Construction Process**: $ ROE_{YoY} = \frac{ROE_{current\_quarter} - ROE_{same\_quarter\_last\_year}}{ROE_{same\_quarter\_last\_year}} $ Where: $ROE_{current\_quarter}$ = ROE for the current quarter $ROE_{same\_quarter\_last\_year}$ = ROE for the same quarter in the previous year[14] - **Factor Evaluation**: Shows strong positive returns in the CSI 500 stock pool, highlighting its effectiveness in identifying growth trends[14] Total Asset Growth Rate - **Factor Name**: Total Asset Growth Rate - **Factor Construction Idea**: Measures the growth rate of total assets over a specific period[16] - **Factor Construction Process**: $ Growth_{assets} = \frac{Assets_{current} - Assets_{previous}}{Assets_{previous}} $ Where: $Assets_{current}$ = Total assets in the current period $Assets_{previous}$ = Total assets in the previous period[16] - **Factor Evaluation**: Demonstrates strong positive returns across multiple stock pools, indicating its robustness in capturing growth signals[16] --- Backtesting Results of Models PB-ROE-50 Model - **Excess Return (Weekly)**: - CSI 500: 0.47% - CSI 800: 0.25% - All Market: 1.02%[25] - **Excess Return (YTD)**: - CSI 500: 3.22% - CSI 800: 11.76% - All Market: 14.28%[25] --- Backtesting Results of Factors Standardized Unexpected Earnings (SUE) - **Excess Return (Weekly)**: - CSI 300: 4.12% - CSI 500: 0.34% - Liquidity 1500: 1.16%[12][15][17] Single-Quarter ROE YoY Growth - **Excess Return (Weekly)**: - CSI 300: 0.84% - CSI 500: 2.28% - Liquidity 1500: 1.27%[12][15][17] Total Asset Growth Rate - **Excess Return (Weekly)**: - CSI 300: 2.39% - CSI 500: 0.50% - Liquidity 1500: 2.12%[12][15][17]

Core Viewpoint - The article emphasizes the potential of smart beta index funds, which utilize more sophisticated stock selection rules compared to traditional index funds, to achieve long-term excess returns in the market [3][4][11]. Group 1: Smart Beta Index Funds - Smart beta index funds represent a small portion of the market, with only 1.7 trillion yuan, accounting for approximately 0.5% of the total public fund size of 32.24 trillion yuan in China by the end of 2024 [2]. - These funds employ stock selection based on proven financial metrics or price characteristics, rather than just market capitalization [4][5]. - Common factors used in smart beta strategies include dividend yield, quality, value, low volatility, and momentum [15]. Group 2: Performance of Smart Beta Strategies - Historical data from 1927 to 2023 indicates that smart beta strategies can outperform the market, with various factors showing significant annualized returns above the overall market return of 9.5% [17][18]. - The long-term performance of factor-based strategies demonstrates that almost all factor long portfolios yield returns significantly higher than the market index, suggesting that holding a good smart beta fund is likely to provide better returns than traditional indices like the CSI 300 [20][23]. Group 3: Challenges and Considerations - Despite the effectiveness of smart beta strategies, they can experience prolonged periods of underperformance, which may lead to investor skepticism [24][26]. - Historical data shows that some factors can have long periods of underperformance, with the longest being four years for several factors [28][29]. - Diversifying across multiple factors can help mitigate risks associated with individual factor underperformance, as different factors may perform well at different times [30]. Group 4: Insights from Historical Data - Long-term data supports the reliability of smart beta index funds, indicating that missing out on these investment opportunities could be regrettable [32]. - Investors are advised to construct multi-factor portfolios to balance risk and return, incorporating defensive and aggressive strategies [35]. - A long-term investment horizon is essential for realizing the excess returns from smart beta strategies, as they may require enduring periods of underperformance [37][39]. - Risk management is crucial, as smart beta funds are still subject to market fluctuations and can decline during bear markets [40][41].

Quantitative Models and Construction Methods Style Factors 1. **Factor Name**: Beta Factor - **Construction Idea**: Captures the market sensitivity of stocks - **Construction Process**: - Calculate the daily returns of individual stocks and the market index (CSI All Share Index) over the past 252 trading days - Perform an exponentially weighted regression with a half-life of 63 trading days - The regression coefficient is taken as the Beta factor - **Evaluation**: High Beta stocks outperformed low Beta stocks in the recent week, indicating a preference for market-sensitive stocks[15][16] 2. **Factor Name**: Leverage Factor - **Construction Idea**: Measures the financial leverage of companies - **Construction Process**: - Calculate three sub-factors: Market Leverage (MLEV), Debt to Assets (DTOA), and Book Leverage (BLEV) - MLEV = Non-current liabilities / Total market value - DTOA = Total liabilities / Total assets - BLEV = Non-current liabilities / Shareholders' equity - Combine the three sub-factors equally to form the Leverage factor - **Evaluation**: Low leverage companies outperformed high leverage companies, indicating a market preference for financially stable companies[15][16] 3. **Factor Name**: Growth Factor - **Construction Idea**: Measures the growth potential of companies - **Construction Process**: - Calculate two sub-factors: Sales Growth (SGRO) and Earnings Growth (EGRO) - SGRO = Regression slope of past five years' annual sales per share divided by the average sales per share - EGRO = Regression slope of past five years' annual earnings per share divided by the average earnings per share - Combine the two sub-factors equally to form the Growth factor - **Evaluation**: The Growth factor showed a negative return, indicating a decline in market preference for high-growth stocks[15][16] Stock Selection Factors 1. **Factor Name**: Single Quarter ROA - **Construction Idea**: Measures the return on assets for a single quarter - **Construction Process**: - Single Quarter ROA = Net income attributable to parent company / Total assets - **Evaluation**: Performed well in the CSI 300 stock pool over the past week[21][24] 2. **Factor Name**: 240-Day Skewness - **Construction Idea**: Measures the skewness of daily returns over the past 240 trading days - **Construction Process**: - Calculate the skewness of daily returns over the past 240 trading days - **Evaluation**: Performed well in the CSI 300 stock pool over the past week[21][24] 3. **Factor Name**: Single Quarter ROE - **Construction Idea**: Measures the return on equity for a single quarter - **Construction Process**: - Single Quarter ROE = Net income attributable to parent company / Shareholders' equity - **Evaluation**: Performed well in the CSI 300 stock pool over the past week[21][24] Factor Backtesting Results 1. **Beta Factor**: Weekly long-short return: 1.86%, Monthly long-short return: 1.64%[17] 2. **Leverage Factor**: Weekly long-short return: -3.07%, Monthly long-short return: -1.58%[17] 3. **Growth Factor**: Weekly long-short return: -1.73%, Monthly long-short return: -5.13%[17] Stock Selection Factor Backtesting Results 1. **Single Quarter ROA**: Weekly excess return: 0.98%, Monthly excess return: 2.61%, Annual excess return: 9.49%, Ten-year annualized return: 3.69%[22] 2. **240-Day Skewness**: Weekly excess return: 0.75%, Monthly excess return: 2.48%, Annual excess return: 6.40%, Ten-year annualized return: 2.85%[22] 3. **Single Quarter ROE**: Weekly excess return: 0.74%, Monthly excess return: 1.55%, Annual excess return: 8.96%, Ten-year annualized return: 3.46%[22]

Core Viewpoint - The article provides an analysis of market performance, highlighting the positive and negative returns of various factors across different stock pools and industries, indicating a mixed market sentiment and specific investment opportunities [2][3][4]. Group 1: Market Factor Performance - In the overall market stock pool, the Beta factor and valuation factor achieved positive returns of 0.48% and 0.26% respectively, while the market capitalization factor and profit factor recorded negative returns of -0.24% and -0.42%, suggesting a small-cap style market [2]. - The momentum factor yielded a negative return of -0.44%, indicating a reversal style in the market [2]. Group 2: Single Factor Performance - In the CSI 300 stock pool, the best-performing factors included quarterly net profit year-on-year growth rate (1.83%), quarterly operating profit year-on-year growth rate (1.75%), and net profit margin TTM (1.52%) [3]. - In the CSI 500 stock pool, the top factors were price-to-book ratio (2.57%), downside volatility ratio (2.07%), and inverse of price-to-sales ratio TTM (1.33%) [3]. - In the liquidity 1500 stock pool, the leading factors were downside volatility ratio (0.74%), net profit gap (0.49%), and quarterly ROE year-on-year (0.46%) [3]. Group 3: Industry Factor Performance - The 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 transportation industry [4]. - Among valuation factors, the BP factor performed well, showing significant positive returns in the real estate industry [4]. - Residual volatility and liquidity factors demonstrated notable positive returns in the non-ferrous metals industry [4]. Group 4: Investment Strategy Performance - The PB-ROE-50 combination achieved positive excess returns in the overall market stock pool, while it recorded excess returns of -0.56% in the CSI 500 stock pool and -0.38% in the CSI 800 stock pool [5]. - Public and private fund research selection strategies both gained positive excess returns, with public strategies outperforming the CSI 800 by 0.80% and private strategies by 1.21% [6]. - The block trading combination also achieved positive excess returns relative to the CSI All Index, with an excess return of 1.22% [7]. - The targeted issuance combination gained positive excess returns relative to the CSI All Index, with an excess return of 0.05% [8].

Quantitative Models and Construction Methods 1. Model Name: PB-ROE-50 - **Model Construction Idea**: The PB-ROE-50 model selects stocks based on a combination of Price-to-Book (PB) ratio and Return on Equity (ROE), aiming to capture value and profitability factors[23] - **Model Construction Process**: - Stocks are ranked based on their PB and ROE metrics - A portfolio is constructed by selecting the top 50 stocks with the best combined PB and ROE scores - The portfolio is rebalanced periodically to maintain the factor exposure[23] - **Model Evaluation**: The model demonstrates the ability to generate excess returns in certain market conditions, particularly in capturing value and profitability factors[23] 2. Model Name: Block Trade Portfolio - **Model Construction Idea**: This model leverages the information embedded in block trades, focusing on stocks with high block trade transaction amounts and low volatility in transaction amounts[29] - **Model Construction Process**: - Identify stocks with high "block trade transaction amount ratio" and low "6-day transaction amount volatility" - Construct a portfolio based on these criteria and rebalance monthly[29] - **Model Evaluation**: The model effectively captures the excess return potential of block trade-related stocks, particularly those with high transaction amounts and low volatility[29] 3. Model Name: Private Placement Portfolio - **Model Construction Idea**: This model focuses on stocks involved in private placements, aiming to capture the event-driven effects of private placements on stock performance[35] - **Model Construction Process**: - Use the shareholder meeting announcement date as the event trigger - Incorporate market capitalization, rebalancing frequency, and position control into the portfolio construction process - Construct a portfolio based on these parameters[35] - **Model Evaluation**: The model captures the investment opportunities arising from private placement events, though its effectiveness may vary depending on market conditions[35] --- Model Backtesting Results 1. PB-ROE-50 Model - **Excess Return (This Week)**: - CSI 500: -0.56% - CSI 800: -0.38% - All Market: 0.92%[24] - **Year-to-Date Excess Return**: - CSI 500: 2.99% - CSI 800: 6.41% - All Market: 9.28%[24] - **Absolute Return (This Week)**: - CSI 500: 1.39% - CSI 800: 0.73% - All Market: 2.47%[24] - **Year-to-Date Absolute Return**: - CSI 500: 8.41% - CSI 800: 9.44% - All Market: 16.07%[24] 2. Block Trade Portfolio - **Excess Return (This Week)**: 1.22% - **Year-to-Date Excess Return**: 25.89% - **Absolute Return (This Week)**: 2.78% - **Year-to-Date Absolute Return**: 33.71%[30] 3. Private Placement Portfolio - **Excess Return (This Week)**: 0.05% - **Year-to-Date Excess Return**: 8.72% - **Absolute Return (This Week)**: 1.59% - **Year-to-Date Absolute Return**: 15.48%[36] --- Quantitative Factors and Construction Methods 1. Factor Name: Beta Factor - **Factor Construction Idea**: Measures the sensitivity of a stock's returns to market returns, capturing systematic risk[18] - **Factor Construction Process**: - Calculate the covariance between the stock's returns and market returns - Divide by the variance of market returns to derive the beta coefficient - $ \beta = \frac{\text{Cov}(R_i, R_m)}{\text{Var}(R_m)} $ - Where $R_i$ is the stock return, and $R_m$ is the market return[18] - **Factor Evaluation**: The factor captures systematic risk effectively and is widely used in portfolio construction and risk management[18] 2. Factor Name: Momentum Factor - **Factor Construction Idea**: Measures the tendency of stocks with high past returns to continue performing well in the future[18] - **Factor Construction Process**: - Calculate the cumulative return of a stock over a specific look-back period (e.g., 6 months or 12 months) - Rank stocks based on their cumulative returns and construct a portfolio of top-ranked stocks[18] - **Factor Evaluation**: The factor is effective in capturing trends in stock performance but may underperform in reversal markets[18] 3. Factor Name: Valuation Factor (e.g., PB, PE, PS) - **Factor Construction Idea**: Measures the relative valuation of stocks based on financial metrics like Price-to-Book (PB), Price-to-Earnings (PE), and Price-to-Sales (PS)[18] - **Factor Construction Process**: - Calculate the PB, PE, or PS ratio for each stock - Rank stocks based on these ratios and construct a portfolio of low-ratio stocks (value stocks)[18] - **Factor Evaluation**: Valuation factors are effective in identifying undervalued stocks but may underperform during growth-driven market phases[18] --- Factor Backtesting Results 1. Beta Factor - **Weekly Return**: 0.48%[18] 2. Momentum Factor - **Weekly Return**: -0.44%[18] 3. Valuation Factor - **Weekly Return**: - PB: 2.57% (CSI 500)[14] - PE: 0.37% (CSI 300)[13] - PS: 1.26% (CSI 300)[13]

Core Viewpoint - The report highlights the performance of various investment factors and strategies over the week, indicating a mixed market environment with specific factors yielding positive and negative returns [3][4][5]. Factor Performance - BP factor and profit factor achieved positive returns of 0.30% and 0.27% respectively, while non-linear market capitalization factor and size factor showed significant negative returns of -0.31% and -0.29%, indicating a clear small-cap market style [3]. - In the CSI 300 stock pool, the best-performing factors included TTM P/E ratio (0.70%), TTM P/S ratio (0.59%), and 5-minute return skewness (0.57%), while the worst performers were 6-day trading volume moving average (-1.24%), 5-day average turnover rate (-1.44%), and TTM gross profit margin (-1.62%) [4]. - In the CSI 500 stock pool, the top factors were quarterly ROE (1.70%), TTM gross profit margin (1.54%), and 5-day trading volume standard deviation (1.36%), with poor performers including early trading return factor (-0.39%), 5-minute return skewness (-0.44%), and log market capitalization factor (-0.73%) [4]. - In the liquidity 1500 stock pool, the best factors were 5-day reversal (1.62%), quarterly ROE (1.53%), and P/E factor (1.41%), while the worst were 6-day trading volume moving average (-0.61%), early trading return factor (-0.70%), and 5-day index moving average of trading volume (-0.72%) [4]. Industry Factor Performance - The net asset growth rate factor showed significant positive returns in the comprehensive industry, while the net profit growth rate factor performed well across the same sector [5]. - The 5-day momentum factor exhibited strong momentum effects in the comprehensive, steel, and public utility industries, while reversal effects were notable in non-bank financials, non-ferrous metals, and telecommunications [5]. - Valuation factors like BP factor performed well in the comprehensive, steel, and banking industries, while EP factor excelled in the comprehensive, media, and non-bank financial sectors [5]. Strategy Performance - The PB-ROE-50 combination achieved excess returns across various stock pools, with excess returns of 1.17% in the CSI 500 pool, 1.21% in the CSI 800 pool, and 1.36% in the overall market stock pool [6]. - Public fund research selection strategy and private fund research tracking strategy both gained positive excess returns, with public fund strategy achieving 0.02% excess return relative to CSI 800 and private fund strategy achieving 0.25% [7]. - The block trading combination experienced a relative excess return drawdown of -0.24% compared to the CSI All Index [8]. - The directed issuance combination also faced a relative excess return drawdown of -0.69% compared to the CSI All Index [9].

Quantitative Models and Construction Methods - **Model Name**: Neutral Constraint Maximum Factor Exposure Portfolio **Model Construction Idea**: The model aims to maximize the exposure of the target factor in the portfolio while maintaining neutrality in industry and style exposures relative to the benchmark index[60][61] **Model Construction Process**: 1. The objective function is to maximize the portfolio's exposure to the target factor $ \text{Max} \quad w^{\prime} X_{\text{target}} $ 2. Constraints include: - Industry neutrality: $ (w - w_b)^{\prime} X_{\text{inad}} = 0 $ - Style neutrality: $ (w - w_b)^{\prime} X_{\text{Beta}} = 0 $ - Weight deviation limit: $ |w - w_b| \leq 1\% $ - No short selling: $ w \geq 0 $ - Full investment: $ w^{\prime} B = 1 $ and $ w^{\prime} 1 = 1 $ 3. Factors are neutralized to remove correlations with industry and style factors (e.g., size, valuation, growth) 4. Factor directions are adjusted to be positive before optimization[60][62][63] **Model Evaluation**: The model effectively balances factor exposure maximization with risk control, ensuring alignment with the benchmark index[63] --- Quantitative Factors and Construction Methods - **Factor Name**: Valuation Factor (BP) **Factor Construction Idea**: Captures the valuation level of stocks based on book-to-price ratio[14][15] **Factor Construction Process**: - Formula: $ \text{BP} = \frac{\text{Shareholders' Equity}}{\text{Market Capitalization}} $ **Factor Evaluation**: Demonstrates strong performance in capturing undervalued stocks, particularly in defensive market environments[14][15] - **Factor Name**: Growth Factor **Factor Construction Idea**: Measures the growth potential of stocks based on sales and earnings growth rates[14][15] **Factor Construction Process**: - Formula: $ \text{Growth Factor} = \frac{\text{SGRO} + \text{EGRO}}{2} $ - $ \text{SGRO} $: Regression slope of past 5 years' annual sales divided by average sales - $ \text{EGRO} $: Regression slope of past 5 years' annual earnings divided by average earnings[14][15] **Factor Evaluation**: Useful in identifying high-growth stocks, though performance may vary across market cycles[14][15] - **Factor Name**: Beta Factor **Factor Construction Idea**: Reflects the sensitivity of a stock's returns to market movements[14][15] **Factor Construction Process**: - Formula: $ \text{Beta} = \text{Regression Coefficient of Stock Returns on Market Returns} $ - Regression uses 252 trading days with a half-life of 63 days[14][15] **Factor Evaluation**: Effective in capturing market risk preferences, with low-beta stocks outperforming in risk-averse environments[14][15] - **Factor Name**: Momentum Factor (RSTR) **Factor Construction Idea**: Identifies stocks with strong relative strength over a specific period[14][15] **Factor Construction Process**: - Formula: $ \text{RSTR} = \text{Cumulative Returns over 504 Days (Excluding Last 21 Days)} $ - Returns are weighted using a half-life of 126 days[14][15] **Factor Evaluation**: Performs well in trending markets but may underperform during reversals[14][15] --- Factor Backtesting Results - **Valuation Factor (BP)**: - Recent 1-week long-short return: 1.90% - Recent 1-month long-short return: -0.58%[17] - **Growth Factor**: - Recent 1-week long-short return: -0.79% - Recent 1-month long-short return: -0.99%[17] - **Beta Factor**: - Recent 1-week long-short return: -2.89% - Recent 1-month long-short return: 5.63%[17] - **Momentum Factor (RSTR)**: - Recent 1-week long-short return: -1.03% - Recent 1-month long-short return: -2.31%[17] --- Index Enhancement Portfolio Backtesting Results - **CSI 300 Enhanced Portfolio**: - 1-week excess return: 0.63% - 1-month excess return: 2.22% - 1-year excess return: 2.43%[57][58] - **CSI 500 Enhanced Portfolio**: - 1-week excess return: 0.10% - 1-month excess return: -1.25% - 1-year excess return: -2.90%[57][58] - **CSI 800 Enhanced Portfolio**: - 1-week excess return: 0.70% - 1-month excess return: 1.47% - 1-year excess return: 1.03%[57][58] - **CSI 1000 Enhanced Portfolio**: - 1-week excess return: 0.16% - 1-month excess return: 0.21% - 1-year excess return: 12.99%[57][58] - **CSI 300 ESG Enhanced Portfolio**: - 1-week excess return: 0.36% - 1-month excess return: 2.64% - 1-year excess return: 7.88%[57][58]

- 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]