2026 年 1 月 10 日 总量研究 市场大市值风格占优，反转效应显著 ——量化组合跟踪周报 20260110 要点 量化市场跟踪 大类因子表现：本周（2026.01.05-2026.01.09，下同），beta 因子、残差波动 率因子、规模因子获得正收益（1.07%、1.02%和 0.59%），动量因子获得显著 负收益（-1.08%），市场大市值风格占优、反转效应显著。 单因子表现：沪深 300 股票池中，本周表现较好的因子有 5 日平均换手率 (4.90%)、换手率相对波动率(4.59%)、单季度营业收入同比增长率(3.92%),表现 较差的因子有动量调整大单(-1.11%)、ROA 稳定性(-1.15%)、ROE 稳定性 (-1.43%)。 中证 500 股票池中，本周表现较好的因子有毛利率 TTM(1.29%)、单季度净利润 同比增长率(1.09%)、总资产增长率(0.81%),表现较差的因子有市净率因子 (-3.51%)、市盈率 TTM 倒数(-4.06%)、市盈率因子(-4.69%)。 流动性 1500 股票池中，本周表现较好的因子有毛利率 TTM(2.17%)、单季度营 业收入同比增长率(2 ...

2025 年 12 月 13 日 总量研究 大市值风格占优，私募调研跟踪策略超额收益显著 ——量化组合跟踪周报 20251213 要点 量化市场跟踪 大类因子表现：本周（2025.12.08-2025.12.12，下同），规模因子、beta 因子、 非线性市值因子、获得正收益（1.18%、0.91%和 0.82%），BP 因子和流动性 因子获得负收益（-0.55%和-0.38%），市场大市值风格占优。 单因子表现：沪深 300 股票池中，本周表现较好的因子有总资产增长率(2.05%)、 单季度 ROA(1.71%)、换手率相对波动率(1.59%),表现较差的因子有对数市值因 子(-1.00%)、下行波动率占比(-1.10%)、大单净流入(-1.14%)。 中证 500 股票池中，本周表现较好的因子有单季度 EPS(1.61%)、总资产增长率 (1.39%)、动量弹簧因子(1.22%),表现较差的因子有市销率 TTM 倒数(-2.49%)、 下行波动率占比(-2.55%)、市净率因子(-3.06%)。 流动性 1500 股票池中，本周表现较好的因子有总资产增长率(2.25%)、单季度 营业收入同比增长率(2.0 ...

Core Viewpoint - The article provides a comprehensive 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 the effectiveness of specific investment strategies [4][5][6][7][8][9][10][11]. Factor Performance - In the overall market, the profit factor achieved a positive return of 0.61%, while market capitalization and momentum factors also showed positive returns of 0.25%, 0.24%, and 0.23% respectively, indicating a large-cap style market [4]. - In the CSI 300 stock pool, the best-performing factors included quarterly ROA (1.43%) and TTM sales ratio inverse (1.39%), while the logarithmic market cap factor showed a negative return of -1.70% [5]. - In the CSI 500 stock pool, the top factors were the 5-day average turnover rate (1.68%) and the correlation between intraday volatility and trading volume (1.66%), with the logarithmic market cap factor again underperforming at -1.21% [5]. Liquidity and Industry Performance - In the liquidity 1500 stock pool, the price-to-earnings ratio factor performed well with a return of 2.13%, while the 5-day reversal factor had a negative return of -1.44% [6]. - Across industries, fundamental factors like net asset growth rate and net profit growth rate showed consistent positive returns in textiles and non-bank financial sectors, while valuation factors like EP and BP also performed well in most industries [7]. Strategy Performance - The PB-ROE-50 combination achieved positive excess returns of 0.76% in the CSI 500 stock pool and 0.21% in the CSI 800 stock pool, while the overall market stock pool had a slight negative excess return of -0.09% [8]. - Public and private fund research strategies yielded positive excess returns of 0.42% and 0.29% respectively relative to the CSI 800 [9]. - The block trading combination underperformed with an excess return of -0.16% relative to the CSI All Index [10]. - The targeted issuance combination also showed negative excess returns of -2.30% relative to the CSI All Index [11].

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Core Viewpoint - The A-share market is experiencing a rebound with major indices showing collective weekly gains, and investors are expected to adopt a more cautious approach as the year-end approaches, leading to a focus on dividend and large-cap stocks as preferred investment choices [1][8]. Group 1: Market Trends - The A-share indices, including the Shanghai Composite and ChiNext, have recovered key levels of 3900 and 3100 points respectively [1]. - The market is anticipated to remain in a state of fluctuation and consolidation in the short term, with a lack of strong catalysts [1][7]. - Seasonal effects are expected to favor large-cap and dividend stocks in December, based on historical performance data [9]. Group 2: Investment Opportunities - The adjustment of risk factors for insurance companies' investments in specific indices is expected to unlock significant capital, potentially bringing in hundreds of billions in new funds to the market [2]. - The upcoming important meeting in December is likely to provide policy direction and liquidity signals, with sectors such as new productivity, domestic consumption, and precious metals being highlighted as potential beneficiaries [6][4]. - Analysts suggest focusing on sectors with structural opportunities, including traditional manufacturing, resource sectors, and dividend-paying stocks like banks and energy companies [5][7]. Group 3: Institutional Insights - Citic Securities emphasizes that the market will likely experience a rotation of structural opportunities, with a focus on sectors that can benefit from global exposure and profit margin improvements [5]. - China Galaxy recommends monitoring sectors that may receive policy support during the upcoming meeting, as well as technology growth sectors that may see recovery after previous valuation adjustments [6]. - Morgan Asset Management highlights the potential for growth in robotics and semiconductor sectors, indicating a shift towards fundamentals-driven market dynamics in 2026 [10].

Quantitative Models and Construction Methods 1. Model Name: PB-ROE-50 - **Model Construction Idea**: This model aims to combine the Price-to-Book (PB) ratio and Return on Equity (ROE) to create a portfolio of 50 stocks[23] - **Model Construction Process**: The model selects stocks based on their PB and ROE values, aiming to balance valuation and profitability. The portfolio is rebalanced periodically to maintain the desired characteristics[23] - **Model Evaluation**: The model's performance is tracked across different stock pools, showing its effectiveness in various market conditions[23] - **Model Test Results**: - **CSI 500**: Weekly excess return -1.30%, YTD excess return 1.58%, weekly absolute return -7.01%, YTD absolute return 20.95%[24] - **CSI 800**: Weekly excess return -2.09%, YTD excess return 13.40%, weekly absolute return -6.31%, YTD absolute return 30.05%[24] - **All Market**: Weekly excess return -1.46%, YTD excess return 16.48%, weekly absolute return -6.44%, YTD absolute return 36.70%[24] 2. Model Name: Institutional Research Portfolio - **Model Construction Idea**: This model tracks the stock selection strategies of public and private institutional research[25] - **Model Construction Process**: The model is constructed based on the stock picks of institutional investors, adjusting the portfolio based on their research and investment decisions[25] - **Model Evaluation**: The model's performance is evaluated by comparing its returns to the CSI 800 index[25] - **Model Test Results**: - **Public Research Stock Selection**: Weekly excess return -1.91%, YTD excess return 12.42%, weekly absolute return -6.14%, YTD absolute return 28.92%[26] - **Private Research Tracking**: Weekly excess return -3.65%, YTD excess return 12.06%, weekly absolute return -7.80%, YTD absolute return 28.51%[26] 3. Model Name: Block Trade Portfolio - **Model Construction Idea**: This model leverages the information from block trades, focusing on stocks with high transaction amounts and low volatility[29] - **Model Construction Process**: The portfolio is constructed based on the "high transaction, low volatility" principle, with monthly rebalancing[29] - **Model Evaluation**: The model's performance is tracked relative to the CSI All Share Index[29] - **Model Test Results**: - **Weekly excess return**: -2.84%[30] - **YTD excess return**: 35.29%[30] - **Weekly absolute return**: -7.75%[30] - **YTD absolute return**: 58.77%[30] 4. Model Name: Private Placement Portfolio - **Model Construction Idea**: This model analyzes the event effects of private placements to identify investment opportunities[35] - **Model Construction Process**: The portfolio is constructed around the announcement dates of private placements, considering factors like market capitalization and rebalancing cycles[35] - **Model Evaluation**: The model's performance is evaluated relative to the CSI All Share Index[35] - **Model Test Results**: - **Weekly excess return**: -1.42%[36] - **YTD excess return**: -3.89%[36] - **Weekly absolute return**: -6.40%[36] - **YTD absolute return**: 12.80%[36] Quantitative Factors and Construction Methods 1. Factor Name: Intraday Volatility and Trading Volume Correlation - **Factor Construction Idea**: This factor measures the correlation between intraday volatility and trading volume[12] - **Factor Construction Process**: The factor is calculated by correlating the intraday price volatility with the trading volume over a specified period[12] - **Factor Evaluation**: The factor shows positive returns in the CSI 300 stock pool[12] - **Factor Test Results**: - **Weekly return**: 1.23%[13] - **Monthly return**: 3.14%[13] - **Annual return**: -2.31%[13] - **10-year return**: 22.87%[13] 2. Factor Name: ROE Stability - **Factor Construction Idea**: This factor measures the stability of a company's Return on Equity over time[12] - **Factor Construction Process**: The factor is calculated by assessing the variance in ROE over a specified period[12] - **Factor Evaluation**: The factor shows positive returns in the CSI 300 stock pool[12] - **Factor Test Results**: - **Weekly return**: 1.14%[13] - **Monthly return**: 1.82%[13] - **Annual return**: 0.95%[13] - **10-year return**: 3.68%[13] 3. Factor Name: Downside Volatility Proportion - **Factor Construction Idea**: This factor measures the proportion of downside volatility in the total volatility of a stock[12] - **Factor Construction Process**: The factor is calculated by dividing the downside volatility by the total volatility over a specified period[12] - **Factor Evaluation**: The factor shows positive returns in the CSI 300 stock pool[12] - **Factor Test Results**: - **Weekly return**: 1.13%[13] - **Monthly return**: 2.09%[13] - **Annual return**: -6.82%[13] - **10-year return**: 30.09%[13] 4. Factor Name: Single Quarter Total Asset Gross Profit Margin - **Factor Construction Idea**: This factor measures the gross profit margin of a company's total assets for a single quarter[14] - **Factor Construction Process**: The factor is calculated by dividing the gross profit by the total assets for a single quarter[14] - **Factor Evaluation**: The factor shows positive returns in the CSI 500 stock pool[14] - **Factor Test Results**: - **Weekly return**: 1.82%[15] - **Monthly return**: -0.84%[15] - **Annual return**: 6.56%[15] - **10-year return**: 82.05%[15] 5. Factor Name: Net Profit Margin TTM - **Factor Construction Idea**: This factor measures the trailing twelve months (TTM) net profit margin of a company[16] - **Factor Construction Process**: The factor is calculated by dividing the net profit by the total revenue for the trailing twelve months[16] - **Factor Evaluation**: The factor shows positive returns in the Liquidity 1500 stock pool[16] - **Factor Test Results**: - **Weekly return**: 1.82%[17] - **Monthly return**: -0.58%[17] - **Annual return**: 1.94%[17] - **10-year return**: -17.46%[17] Factor Backtest Results CSI 300 Stock Pool - **Intraday Volatility and Trading Volume Correlation**: Weekly return 1.23%, monthly return 3.14%, annual return -2.31%, 10-year return 22.87%[13] - **ROE Stability**: Weekly return 1.14%, monthly return 1.82%, annual return 0.95%, 10-year return 3.68%[13] - **Downside Volatility Proportion**: Weekly return 1.13%, monthly return 2.09%, annual return -6.82%, 10-year return 30.09%[13] CSI 500 Stock Pool - **Single Quarter Total Asset Gross Profit Margin**: Weekly return 1.82%, monthly return -0.84%, annual return 6.56%, 10-year return 82.05%[15] Liquidity 1500 Stock Pool - **Net Profit Margin TTM**: Weekly return 1.82%, monthly return -0.58%, annual return 1.94%, 10-year return -17.46%[17]

Group 1 - The A-share market saw a significant rally among the top 18 stocks by market capitalization, with Agricultural Bank reaching a historical high and the total market value of these stocks exceeding 20 trillion yuan [2] - Despite the overall market showing some recovery, the number of declining stocks remained high, indicating a mixed performance with over 3,800 stocks falling [2] - Southbound capital experienced a substantial net inflow of 12.748 billion yuan last week, with banks, non-bank financials, and the oil and petrochemical sectors being the main beneficiaries [3] Group 2 - Analysts suggest that the recent shift towards large-cap stocks may be driven by changes in market risk appetite, with macro leverage around 12.46 times and high valuations in the technology sector [4] - The market is experiencing increased valuation and sentiment risks, with a decrease in liquidity for sell orders, indicating heightened selling pressure [4] - Recommendations for asset allocation include increasing exposure to domestic stocks and commodities, with a focus on large-cap stocks and sectors such as coal, photovoltaics, telecommunications, and agriculture showing good investment value [4]

Core Viewpoint - The A-share market has shown a significant shift with large-cap stocks gaining momentum, particularly the top 18 stocks, which collectively exceeded a market capitalization of 20 trillion yuan. This change is attributed to a shift in market risk appetite and a preference for traditional large-cap stocks, especially in the banking and energy sectors [1][2][4]. Market Performance - On November 12, the A-share market initially saw a decline, with major indices like the Shenzhen Component and ChiNext Index dropping over 1%. However, large-cap stocks later rallied, with the Agricultural Bank of China hitting a new historical high, rising by 3%. Other notable performers included Midea Group, China Petroleum, and China Bank, each increasing by around 2% [2][4]. - Despite the overall index recovery, the number of declining stocks remained high, with over 3,800 stocks falling, indicating a mixed market sentiment [2]. Capital Flow - Southbound capital saw a significant net inflow of 12.748 billion yuan during the week of November 3 to November 7, with major inflows directed towards the banking, non-banking financial, and oil and petrochemical sectors, amounting to approximately 184 million yuan [2][4]. Underlying Logic - Analysts suggest that the recent performance of large-cap stocks is likely due to a change in market risk preferences, with a current macro leverage ratio of about 12.46 times. The technology sector is perceived to have high valuations, while the broader market indices exhibit structural risks [4]. - The strengthening of the US dollar, which has surpassed the 99 mark, is expected to influence market dynamics, with traditional sectors showing resilience during market downturns. Analysts predict that sectors previously underweighted, such as coal, photovoltaic, banking, and chemicals, will benefit as the market recovers [4]. - Looking ahead to November 2025, there is a recommendation to increase allocations in domestic stocks and commodities, favoring large-cap stocks and a balanced growth-value approach, particularly in sectors like coal, photovoltaic, telecommunications, and agriculture [4].

Quantitative Models and Construction - **Model Name**: PB-ROE-50 **Model Construction Idea**: The model combines Price-to-Book ratio (PB) and Return on Equity (ROE) to construct a stock selection strategy[25] **Model Construction Process**: The PB-ROE-50 model selects stocks based on their PB and ROE metrics. Stocks with favorable PB and ROE values are included in the portfolio. The model uses a monthly rebalancing approach to optimize the portfolio[25][26] **Model Evaluation**: The model demonstrates positive excess returns in most stock pools, indicating its effectiveness in capturing value and profitability factors[25][26] - **Model Name**: Institutional Research Tracking Strategy **Model Construction Idea**: This strategy leverages institutional research activities (public and private) to identify stocks with potential excess returns[27] **Model Construction Process**: The strategy tracks stocks that are frequently researched by public and private institutions. Stocks with higher research frequency are included in the portfolio. The portfolio is rebalanced periodically to reflect updated research trends[27][28] **Model Evaluation**: The strategy shows consistent positive excess returns, suggesting that institutional research activities can be a reliable indicator for stock selection[27][28] - **Model Name**: Block Trade Strategy **Model Construction Idea**: The strategy identifies stocks with high block trade activity and low volatility to construct a portfolio[31] **Model Construction Process**: Stocks are selected based on two criteria: high block trade transaction ratios and low 6-day transaction volatility. The portfolio is rebalanced monthly to maintain these characteristics[31][32] **Model Evaluation**: The strategy has mixed results, with negative excess returns in the recent 2-week period, but positive performance over the year[31][32] - **Model Name**: Directed Issuance Strategy **Model Construction Idea**: The strategy focuses on stocks involved in directed issuance events to capture potential investment opportunities[36] **Model Construction Process**: Stocks are selected based on the announcement date of directed issuance events. The strategy considers market capitalization, rebalancing frequency, and position control to construct the portfolio[36][37] **Model Evaluation**: The strategy shows negative excess returns in the recent 2-week period, raising questions about its effectiveness under current market conditions[36][37] Model Backtesting Results - **PB-ROE-50 Model**: - Excess return in CSI 500: -0.82% - Excess return in CSI 800: 1.45% - Excess return in the entire market: 0.75%[25][26] - **Institutional Research Tracking Strategy**: - Public research excess return: 1.03% - Private research excess return: 1.89%[27][28] - **Block Trade Strategy**: - Excess return relative to CSI All Index: -0.57%[31][32] - **Directed Issuance Strategy**: - Excess return relative to CSI All Index: -1.13%[36][37] Quantitative Factors and Construction - **Factor Name**: Liquidity Factor **Factor Construction Idea**: Measures the liquidity of stocks to identify those with higher trading activity[20] **Factor Construction Process**: The liquidity factor is calculated using metrics such as turnover rate and trading volume. Stocks with higher liquidity scores are assigned positive weights[20] **Factor Evaluation**: The factor shows positive returns in the recent 2-week period, indicating its effectiveness in capturing market liquidity trends[20] - **Factor Name**: Leverage Factor **Factor Construction Idea**: Evaluates the financial leverage of companies to identify those with higher risk-adjusted returns[20] **Factor Construction Process**: The leverage factor is derived from financial ratios such as debt-to-equity and interest coverage. Companies with optimal leverage levels are favored[20] **Factor Evaluation**: The factor demonstrates positive returns, suggesting its utility in identifying financially stable companies[20] - **Factor Name**: Profitability Factor **Factor Construction Idea**: Captures the profitability of companies to identify those with strong earnings performance[20] **Factor Construction Process**: The profitability factor is calculated using metrics such as ROE, ROA, and net profit margin. Stocks with higher profitability metrics are given positive weights[20] **Factor Evaluation**: The factor shows positive returns, indicating its effectiveness in identifying profitable companies[20] - **Factor Name**: Valuation Factor **Factor Construction Idea**: Measures the relative valuation of stocks to identify undervalued opportunities[20] **Factor Construction Process**: The valuation factor is derived from metrics such as Price-to-Earnings (P/E) and Price-to-Book (P/B) ratios. Stocks with lower valuation scores are assigned positive weights[20] **Factor Evaluation**: The factor demonstrates positive returns, supporting its use in identifying undervalued stocks[20] - **Factor Name**: Non-linear Market Capitalization Factor **Factor Construction Idea**: Captures the non-linear relationship between market capitalization and stock returns[20] **Factor Construction Process**: The factor is constructed using a non-linear transformation of market capitalization data. Stocks with optimal market capitalization are assigned positive weights[20] **Factor Evaluation**: The factor shows positive returns, indicating its ability to capture market capitalization trends effectively[20] - **Factor Name**: Beta Factor **Factor Construction Idea**: Measures the sensitivity of a stock's returns to market movements[20] **Factor Construction Process**: The beta factor is calculated using historical return data and market indices. Stocks with lower beta values are assigned positive weights[20] **Factor Evaluation**: The factor shows negative returns, suggesting its limited effectiveness in the current market environment[20] - **Factor Name**: Residual Volatility Factor **Factor Construction Idea**: Evaluates the idiosyncratic risk of stocks to identify those with stable performance[20] **Factor Construction Process**: The residual volatility factor is derived from the standard deviation of residuals in a regression model of stock returns against market returns[20] **Factor Evaluation**: The factor shows negative returns, indicating its limited utility in the recent market conditions[20] - **Factor Name**: Growth Factor **Factor Construction Idea**: Captures the growth potential of companies based on their financial performance[20] **Factor Construction Process**: The growth factor is calculated using metrics such as revenue growth and earnings growth. Stocks with higher growth rates are assigned positive weights[20] **Factor Evaluation**: The factor shows negative returns, suggesting its limited effectiveness in the current market environment[20] Factor Backtesting Results - **Liquidity Factor**: Return: 0.36%[20] - **Leverage Factor**: Return: 0.34%[20] - **Profitability Factor**: Return: 0.27%[20] - **Valuation Factor**: Return: 0.18%[20] - **Non-linear Market Capitalization Factor**: Return: 0.18%[20] - **Market Capitalization Factor**: Return: 0.11%[20] - **Beta Factor**: Return: -0.65%[20] - **Residual Volatility Factor**: Return: -0.55%[20] - **Growth Factor**: Return: -0.21%[20]

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]