Quantitative Models and Construction Methods - **Model Name**: PB-ROE-50 **Model Construction Idea**: The model combines Price-to-Book ratio (PB) and Return on Equity (ROE) to select stocks with high profitability and reasonable valuation[3][25] **Model Construction Process**: The PB-ROE-50 portfolio is constructed by selecting 50 stocks with the highest combined scores of PB and ROE within specific stock pools (e.g., CSI 500, CSI 800, and the entire market). The portfolio is rebalanced periodically to maintain its composition[25][26] **Model Evaluation**: The model demonstrates consistent excess returns across different stock pools, indicating its effectiveness in capturing profitable investment opportunities[25][26] - **Model Name**: Institutional Research Portfolio **Model Construction Idea**: The model leverages public and private institutional research data to identify stocks with potential excess returns[28] **Model Construction Process**: The portfolio is constructed based on institutional research data, with public research focusing on CSI 800 stocks and private research tracking broader market stocks. Stocks are selected based on research frequency and sentiment, and the portfolio is rebalanced monthly[28][29] **Model Evaluation**: The model shows positive excess returns, particularly for private research tracking strategies, suggesting its ability to capture valuable insights from institutional activities[28][29] - **Model Name**: Block Trade Portfolio **Model Construction Idea**: The model identifies stocks with high block trade activity and low volatility to capture potential excess returns[31] **Model Construction Process**: Stocks are selected based on "block trade transaction ratio" and "6-day transaction volatility." The portfolio is rebalanced monthly to maintain its focus on high-transaction, low-volatility stocks[31][32] **Model Evaluation**: The model's performance varies, with occasional excess return drawdowns, highlighting the need for careful monitoring and adjustment[31][32] - **Model Name**: Directed Issuance Portfolio **Model Construction Idea**: The model focuses on stocks involved in directed issuance events to capture event-driven investment opportunities[37] **Model Construction Process**: Stocks are selected based on directed issuance announcements, considering factors like market capitalization, rebalancing frequency, and position control. The portfolio is rebalanced periodically to align with event-driven dynamics[37][38] **Model Evaluation**: The model shows mixed results, with occasional excess return drawdowns, indicating the need for further refinement in capturing event-driven effects[37][38] --- Model Backtesting Results - **PB-ROE-50 Model** - CSI 500: Weekly excess return 1.17%, absolute return 1.99%[25][26] - CSI 800: Weekly excess return 1.21%, absolute return 2.58%[25][26] - Entire Market: Weekly excess return 1.36%, absolute return 2.51%[25][26] - **Institutional Research Portfolio** - Public Research: Weekly excess return 0.02%, absolute return 1.37%[28][29] - Private Research: Weekly excess return 0.25%, absolute return 1.61%[28][29] - **Block Trade Portfolio** - Weekly excess return -0.24%, absolute return 0.88%[31][32] - **Directed Issuance Portfolio** - Weekly excess return -0.69%, absolute return 0.43%[37][38] --- Quantitative Factors and Construction Methods - **Factor Name**: BP Factor **Factor Construction Idea**: The factor uses the Book-to-Price ratio to identify undervalued stocks[20] **Factor Construction Process**: BP is calculated as the inverse of the Price-to-Book ratio. Stocks with higher BP values are considered undervalued and selected for portfolios[20] **Factor Evaluation**: BP demonstrates positive returns in multiple industries, indicating its effectiveness in identifying undervalued stocks[23][24] - **Factor Name**: ROE Factor **Factor Construction Idea**: The factor measures profitability using Return on Equity[20] **Factor Construction Process**: ROE is calculated as net income divided by shareholder equity. Stocks with higher ROE values are considered more profitable and selected for portfolios[20] **Factor Evaluation**: ROE shows positive returns across various industries, highlighting its ability to capture profitable investment opportunities[23][24] - **Factor Name**: Nonlinear Market Cap Factor **Factor Construction Idea**: The factor captures the impact of market capitalization on stock returns using a nonlinear approach[20] **Factor Construction Process**: Nonlinear transformations of market capitalization are applied to identify stocks with specific size-related characteristics[20] **Factor Evaluation**: The factor shows negative returns, indicating challenges in capturing size-related effects[20] --- Factor Backtesting Results - **BP Factor** - Weekly return 0.30%[20] - **ROE Factor** - Weekly return 0.27%[20] - **Nonlinear Market Cap Factor** - Weekly return -0.31%[20] - **Scale Factor** - Weekly return -0.29%[20]

Group 1: Monthly Strategy Insights - The report indicates that in July, small-cap stocks are likely to outperform, supported by a monthly quantitative model signal of 0.83, suggesting an overweight position in small-cap stocks [1] - The long-term outlook favors small-cap stocks over the next one to two years, with the current market capitalization factor valuation spread at 1.15, which is lower than historical highs of 1.7 to 2.6 [1] - The report acknowledges a previous misjudgment in June regarding style allocation, where the expected excess return was 0%, and emphasizes a strategy of favoring small-cap stocks unless strong signals for large-cap stocks are present [1] Group 2: Value and Growth Style Rotation - The monthly quantitative model signal for value and growth style rotation is 0.33, indicating a preference for growth stocks in July, which historically tend to outperform during this month [2] - Year-to-date, the value-growth style rotation strategy has achieved an excess return of 6.2% compared to an equal-weight benchmark [2] Group 3: Factor Performance Tracking - Among eight major factors, volatility and value factors showed positive returns this month, while large-cap and liquidity factors exhibited negative returns [2] - Year-to-date, volatility and momentum factors have also shown positive returns, with large-cap and liquidity factors remaining negative [2] - In the analysis of 24 style factors, beta, industry momentum, and short-term reversal factors performed well this month, while large-cap, mid-cap, and liquidity factors did not [2]

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 potential investment opportunities. Group 1: Market Factor Performance - The overall market showed positive returns for Beta and liquidity factors at 1.06% and 0.37% respectively, while market capitalization and residual volatility factors had negative returns of -0.64% and -0.31%, suggesting a small-cap style market [2] - In the CSI 300 stock pool, the best-performing factors included quarterly net profit growth rate at 1.94% and 5-day reversal at 1.83%, while large net inflow and ROIC enhancement factors performed poorly at -0.87% and -0.63% [3] - The CSI 500 stock pool saw total asset growth rate at 1.84% and quarterly operating income growth rate at 1.56% as top performers, while operating profit margin TTM and large net inflow factors lagged at -1.79% and -1.60% [3] Group 2: Industry Factor Performance - Fundamental factors showed varied performance across industries, with net asset growth rate and earnings per share factors yielding significant positive returns in the comprehensive industry [4] - Valuation factors such as EP and BP also demonstrated notable positive returns in the comprehensive industry, while residual volatility and liquidity factors performed well in the non-bank financial sector [4] Group 3: Strategy Performance - The PB-ROE-50 combination achieved positive excess returns in the CSI 800 and overall market stock pools, with excess returns of 0.50% in the CSI 800 and 0.09% in the overall market [5] - Public and private fund research selection strategies both generated positive excess returns, with public strategies outperforming the CSI 800 by 0.40% and private strategies by 0.79% [6] - The block trading combination yielded an excess return of 1.16% relative to the CSI All Index, indicating strong performance in this strategy [7] - The targeted issuance combination also achieved positive excess returns of 1.05% compared to the CSI All Index, reflecting favorable conditions for this investment approach [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[25][26]. - **Model Construction Process**: The model ranks stocks within the China Securities 800 Index (CSI 800) and the broader market based on PB and ROE metrics. Stocks with the best combined scores are selected to form a portfolio of 50 stocks. The portfolio is rebalanced periodically to maintain its factor exposure[25][26]. - **Model Evaluation**: The model demonstrates the ability to generate excess returns over benchmarks, particularly in the CSI 800 and broader market stock pools[25][26]. 2. Model Name: Bulk Transaction Portfolio - **Model Construction Idea**: This model leverages the information embedded in bulk transactions, focusing on stocks with high transaction amounts and low volatility[31]. - **Model Construction Process**: Stocks are selected based on two key metrics: "bulk transaction amount ratio" (higher is better) and "6-day transaction amount volatility" (lower is better). The portfolio is rebalanced monthly to align with these criteria[31]. - **Model Evaluation**: The model effectively captures excess returns by exploiting the "high transaction, low volatility" principle[31]. 3. Model Name: Directed Issuance Portfolio - **Model Construction Idea**: This model identifies investment opportunities in stocks involved in directed issuance events, considering factors like market capitalization and rebalancing cycles[36]. - **Model Construction Process**: Stocks are selected based on their involvement in directed issuance events, with adjustments for market capitalization and portfolio constraints. The portfolio is rebalanced periodically to reflect updated event data[36]. - **Model Evaluation**: The model demonstrates consistent excess returns, indicating the effectiveness of event-driven strategies in the directed issuance space[36]. --- Model Backtesting Results 1. PB-ROE-50 Model - **CSI 500**: Weekly excess return -1.38%, YTD excess return 2.37%, weekly absolute return 2.54%, YTD absolute return 4.84%[26]. - **CSI 800**: Weekly excess return 0.50%, YTD excess return 5.53%, weekly absolute return 2.99%, YTD absolute return 5.92%[26]. - **Broad Market**: Weekly excess return 0.09%, YTD excess return 6.83%, weekly absolute return 3.43%, YTD absolute return 10.50%[26]. 2. Bulk Transaction Portfolio - **Weekly Excess Return**: 1.16% - **YTD Excess Return**: 24.68% - **Weekly Absolute Return**: 4.53% - **YTD Absolute Return**: 28.95%[32]. 3. Directed Issuance Portfolio - **Weekly Excess Return**: 1.05% - **YTD Excess Return**: 9.32% - **Weekly Absolute Return**: 4.42% - **YTD Absolute Return**: 13.07%[37]. --- Quantitative Factors and Construction Methods 1. Factor Name: Beta Factor - **Factor Construction Idea**: Measures a stock's sensitivity to market movements, capturing systematic risk[20]. - **Factor Construction Process**: Calculated as the covariance of a stock's returns with market returns, divided by the variance of market returns. $ \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[20]. - **Factor Evaluation**: Demonstrates positive returns in the current week, indicating favorable market conditions for high-beta stocks[20]. 2. Factor Name: Liquidity Factor - **Factor Construction Idea**: Captures the ease of trading a stock, with higher liquidity stocks expected to perform better in certain market conditions[20]. - **Factor Construction Process**: Measured using metrics like average daily trading volume or bid-ask spread over a specific period[20]. - **Factor Evaluation**: Generated positive returns this week, reflecting a preference for liquid stocks in the market[20]. 3. Factor Name: Residual Volatility Factor - **Factor Construction Idea**: Measures the idiosyncratic risk of a stock, with lower residual volatility stocks often preferred in risk-averse environments[20]. - **Factor Construction Process**: Calculated as the standard deviation of the residuals from a stock's regression on market returns[20]. - **Factor Evaluation**: Negative returns this week, indicating underperformance of low-volatility stocks[20]. --- Factor Backtesting Results 1. Beta Factor - Weekly return: 1.06%[20]. 2. Liquidity Factor - Weekly return: 0.37%[20]. 3. Residual Volatility Factor - Weekly return: -0.31%[20].

Group 1 - The A-share market in the first half of 2025 experienced a rebound despite facing mid-term tariff shocks, with significant trading volume and volatility providing a favorable environment for quantitative strategies [3][6][14] - The return of small-cap stocks has set the tone for quantitative strategy performance, with the ChiNext and CSI 2000 indices outperforming larger indices like the CSI 300 [6][10][18] - The overall A-share environment has been friendly to quantitative strategies, characterized by significant volatility and trading volume exceeding one trillion, which supports high-frequency trading strategies [14][15] Group 2 - Alpha products and managers performed well in the first half of 2025, with most long products achieving positive returns, particularly in quantitative stock selection [16][17] - The average return for quantitative stock selection products exceeded 12%, benefiting from the favorable small-cap market environment [17][19] - New quantitative strategies are emerging, with the CSI 2000 index showing strong performance due to its small-cap focus and lower competition compared to traditional indices [28][29] Group 3 - The risk associated with small-cap stocks needs close attention, as they have shown extreme trading heat and significant divergence from larger indices, indicating potential for a market correction [32][39] - The macroeconomic environment, policy support, liquidity conditions, and technological advancements are driving the performance of small-cap stocks, but caution is warranted due to high valuations and the presence of loss-making companies [34][36][37] - The correlation between quantitative products and small-cap stocks suggests that while there are benefits, there is also a need for careful risk management to avoid potential downturns similar to past market events [40][41]

Group 1 - The core viewpoint of the article highlights the performance of various market factors, indicating a mixed performance across different stock pools with specific factors yielding positive or negative returns [2][3][5]. Group 2 - In the overall market, the profitability factor achieved a positive return of 0.54%, while the residual volatility and beta factors gained 0.28% and 0.23% respectively, indicating a small-cap style market performance [2]. - In the CSI 300 stock pool, the best-performing factors included the price-to-earnings (P/E) ratio (2.85%) and the TTM inverse P/E ratio (2.32%), while the worst performers were the 5-minute return skew (-1.53%) and gross profit margin TTM (-1.03%) [3]. - The CSI 500 stock pool saw the ROIC enhancement factor perform well with a return of 1.46%, while the worst performers included the 5-day reversal (-1.25%) [3]. - The liquidity 1500 stock pool had the TTM inverse P/E ratio as the best performer (1.30%), while early morning return factors showed negative performance [3]. Group 3 - The fundamental factors showed varied performance across industries, with net asset growth rate and net profit growth rate factors performing consistently well in the telecommunications, beauty care, and commercial trade sectors [5]. - Valuation factors, particularly the earnings yield (EP) factor, performed well in the telecommunications, oil and petrochemical, and steel industries [5]. - The small-cap style was notably significant in the beauty care, media, and computer industries this week [5]. Group 4 - The PB-ROE-50 combination achieved positive excess returns across stock pools, with the CSI 500 pool gaining 1.34% and the CSI 800 pool gaining 1.37% [6]. - The public fund research selection strategy and private fund research tracking strategy both recorded negative excess returns relative to the CSI 800, with losses of -1.58% and -1.45% respectively [7]. - The block trading combination underperformed relative to the CSI All Index, with an excess return of -0.62% [8]. - The targeted issuance combination achieved positive excess returns relative to the CSI All Index, with a gain of 1.17% [9].

Quantitative Models and Construction 1. Model Name: GRU (Gated Recurrent Unit) Models - **Model Construction Idea**: GRU models are used to capture sequential patterns in stock price movements and combine fundamental and technical features for prediction[3][4] - **Model Construction Process**: - The GRU models are trained on historical stock data, incorporating both fundamental and technical indicators as input features - Different variations of GRU models are used, such as `open1d`, `close1d`, and `barra1d`, which focus on specific aspects of stock price movements (e.g., open prices, close prices, or Barra-style factor adjustments)[4][5][6] - **Model Evaluation**: GRU models show mixed performance, with some models like `barra1d` performing well, while others like `close1d` exhibit significant drawdowns[5][6][8] --- Backtesting Results of Models GRU Models - **open1d**: Weekly excess return: -0.23%, Monthly: 2.34%, YTD: 6.70%[31][32] - **close1d**: Weekly excess return: 0.06%, Monthly: 3.83%, YTD: 5.55%[31][32] - **barra1d**: Weekly excess return: 0.00%, Monthly: 0.34%, YTD: 3.33%[31][32] - **barra5d**: Weekly excess return: 0.10%, Monthly: 2.88%, YTD: 7.01%[31][32] --- Quantitative Factors and Construction 1. Factor Name: Beta - **Factor Construction Idea**: Measures the historical sensitivity of a stock's returns to market returns[15] - **Factor Construction Process**: Calculated as the historical beta of the stock relative to the market[15] 2. Factor Name: Momentum - **Factor Construction Idea**: Captures the average historical excess returns of a stock over a specific period[15] - **Factor Construction Process**: - Momentum = Mean of historical excess return series[15] 3. Factor Name: Volatility - **Factor Construction Idea**: Measures the variability of a stock's excess returns over time[15] - **Factor Construction Process**: - Volatility = 0.74 * Historical excess return volatility + 0.16 * Cumulative excess return deviation + 0.10 * Residual return volatility[15] 4. Factor Name: Valuation - **Factor Construction Idea**: Represents the inverse of the price-to-book ratio, indicating undervaluation[15] - **Factor Construction Process**: - Valuation = 1 / Price-to-Book Ratio[15] 5. Factor Name: Growth - **Factor Construction Idea**: Measures the growth potential of a stock based on earnings and revenue growth[15] - **Factor Construction Process**: - Growth = 0.24 * Earnings Growth Rate + 0.47 * Revenue Growth Rate[15] 6. Factor Name: Profitability - **Factor Construction Idea**: Combines various profitability metrics to assess a stock's financial health[15] - **Factor Construction Process**: - Profitability = 0.68 * Analyst Forecast Earnings Yield + 0.21 * Inverse of Price-to-Cash Flow Ratio + 0.11 * Inverse of Price-to-Earnings Ratio (TTM) + 0.18 * Analyst Forecast Long-Term Growth Rate + 0.11 * Analyst Forecast Short-Term Growth Rate[15] --- Backtesting Results of Factors Fundamental Factors - **Static Financial Factors**: Weekly excess return: Negative[4][6] - **Growth Factors**: Weekly excess return: Positive[4][6] - **Surprise Growth Factors**: Weekly excess return: Positive[4][6] Technical Factors - **Short-Term Momentum**: Weekly excess return: Negative[4][6] - **Long-Term Momentum**: Weekly excess return: Positive[4][6] - **Volatility**: Weekly excess return: Positive[4][6] GRU Factors - **open1d**: Weekly excess return: Positive[4][6] - **close1d**: Weekly excess return: Negative[5][6] - **barra1d**: Weekly excess return: Positive[5][6]

Group 1 - The A-share market experienced a contraction with major indices declining, indicating a cautious market sentiment amid reduced trading volume [3] - The REITs market showed an upward trend in secondary market prices, with the weighted REITs index closing at 139.74 and a weekly return of 1.36%, outperforming other major asset classes [4] - The copper industry is facing pressure from trade conflicts and rising domestic inventory, but prices may gradually increase with potential domestic stimulus policies and U.S. interest rate cuts [5] Group 2 - In the livestock sector, the average weight of slaughtered pigs has decreased, and the price of pigs has seen a larger decline, indicating a potential turning point in inventory levels and a long-term upward profit cycle post-deinventory [6] - Nobon Co., a leading player in the spunlace non-woven fabric industry, has shown strong performance in 2024 and Q1 2025, with advanced production lines and a focus on high-margin clients [7] - The small-cap style is currently favored in the market, with private equity research strategies showing significant excess returns [8]

Group 1 - The core viewpoint of the article highlights the performance of various market factors during the week of May 19 to May 23, 2025, indicating that momentum and growth factors yielded positive returns while liquidity, beta, and size factors experienced significant negative returns [2][3]. - In the CSI 300 stock pool, the best-performing factors included net profit discontinuity (1.30%), 5-day index moving average of trading volume (1.15%), and total asset gross profit margin TTM (1.02%) [3]. - In the CSI 500 stock pool, the top-performing factors were gross profit margin TTM (1.65%), single-quarter ROA (1.40%), and single-quarter total asset gross profit margin (1.26%) [3]. - The liquidity 1500 stock pool showed that the best-performing factors were 5-day average turnover rate (0.45%), 5-minute return skewness (0.36%), and downward volatility ratio (0.33%) [3]. Group 2 - The net asset growth rate factor performed well across various industries, while the net profit growth rate factor excelled in the steel industry [4]. - The earnings per share factor showed strong performance in the beauty and personal care industry, and the operating profit TTM factor performed well in the coal industry [4]. - The 5-day momentum factor exhibited significant momentum effects in the comprehensive industry, while reversal effects were notable in the oil and petrochemical, and food and beverage industries [4]. Group 3 - The PB-ROE-50 combination achieved significant excess returns in the CSI 500 stock pool, with an excess return of 1.15% [6]. - The public fund research stock selection strategy and private fund research tracking strategy both generated positive excess returns, with the public fund strategy outperforming the CSI 800 by 0.54% and the private fund strategy outperforming by 2.61% [7]. - The block trading combination experienced a decline in excess returns relative to the CSI All Index, with an excess return of -0.61% [8]. - The targeted issuance combination achieved excess returns relative to the CSI All Index, with an excess return of 0.12% [9].

- The PB-ROE-50 portfolio achieved an excess return of 1.15% in the CSI 500 stock pool, 0.29% in the CSI 800 stock pool, and -0.30% in the entire market stock pool[23][24] - The public research stock selection strategy achieved an excess return of 0.54% relative to the CSI 800, while the private research tracking strategy achieved an excess return of 2.61% relative to the CSI 800[25][26] - The block trading portfolio achieved an excess return of -0.61% relative to the CSI All Share Index[29][30] - The directed issuance portfolio achieved an excess return of 0.12% relative to the CSI All Share Index[35][36] - The momentum factor and growth factor achieved positive returns of 0.12% and 0.04% respectively, while the liquidity factor, beta factor, and size factor achieved significant negative returns of -0.56%, -0.52%, and -0.40% respectively[18][20] - In the CSI 500 stock pool, the best-performing factors this week were gross profit margin TTM (1.65%), single-quarter ROA (1.40%), and single-quarter total asset gross profit margin (1.26%)[14][15] - In the liquidity 1500 stock pool, the best-performing factors this week were 5-day average turnover rate (0.45%), 5-minute return skewness (0.36%), and downside volatility ratio (0.33%)[16][17] - In the CSI 500 stock pool, the worst-performing factors this week were single-quarter net profit year-on-year growth rate (-0.42%), 5-day reversal (-0.49%), and post-morning return factor (-0.64%)[14][15] - In the liquidity 1500 stock pool, the worst-performing factors this week were momentum spring factor (-1.07%), 5-day reversal (-1.11%), and single-quarter net profit year-on-year growth rate (-1.19%)[16][17] - In the CSI 300 stock pool, the best-performing factors this week were net profit gap (1.30%), 5-day exponential moving average of trading volume (1.15%), and total asset gross profit margin TTM (1.02%)[12][13] - In the CSI 300 stock pool, the worst-performing factors this week were logarithmic market value factor (-1.02%), momentum spring factor (-1.12%), and post-morning return factor (-1.29%)[12][13] - The net asset growth rate factor performed well in the comprehensive industry, and the net profit growth rate factor performed well in the steel industry[21][22] - The BP factor performed well in the beauty and personal care industry, and the EP factor performed well in the coal industry[21][22]