2025 年 11 月 22 日 总量研究 ——量化组合跟踪周报 20251122 因子表现分化，市场大市值风格显著 要点 量化市场跟踪 大类因子表现：本周全市场股票池中，市值因子获取正收益 0.99%，市场大市 值风格显著；杠杆因子、流动性因子、残差波动率因子、估值因子分别获取负收 益-0.41%、-0.43%、-0.50%、-0.68%；其余风格因子表现一般。 单因子表现：沪深 300 股票池中，本周表现较好的因子有日内波动率与成交金 额的相关性(1.23%)、ROE 稳定性 (1.14%)、下行波动率占比 (1.13%)。表现较 差的因子有早盘收益因子 (-2.46%)、动量弹簧因子 (-2.21%)、净利润断层 (-1.72%)。 中证 500 股票池中，本周表现较好的因子有单季度总资产毛利率(1.82%)、动量 调整大单(1.66%)、总资产毛利率 TTM (1.63%)。表现较差的因子有单季度 ROA 同比(-0.66%)、单季度 ROE 同比(-0.55%)、ROIC 增强因子(-0.53%)。 流动性 1500 股票池中，本周表现较好的因子有净利润率 TTM (1.82%)、营业利 润率 TT ...

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]

Group 1 - Jin Chengxin (603979.SH) reported a net profit of 1.111 billion yuan for the first half of 2025, an increase of 81.3% year-on-year. The mining service segment achieved a gross profit of 767 million yuan, down 17% [5] - Guodian Nanrui (600406.SH) achieved an operating income of 24.243 billion yuan in the first half of 2025, a year-on-year increase of 19.54%. The net profit attributable to shareholders was 2.952 billion yuan, up 8.82% [5] - Midea Group (000333.SZ) reported total operating revenue of 252.3 billion yuan for the first half of 2025, a year-on-year increase of 16%. The net profit attributable to shareholders was 26 billion yuan, up 25% [7] - Songcheng Performance (300144.SZ) experienced a decline in revenue, reporting 1.08 billion yuan for the first half of 2025, down 8.3% year-on-year, with a net profit of 400 million yuan, down 27.4% [8] - Gushengtang (2273.HK) achieved total operating revenue of 1.495 billion yuan in the first half of 2025, a year-on-year increase of 9.5%, with a net profit of 152 million yuan, up 41.6% [8] Group 2 - The market is currently favoring large-cap stocks, with significant momentum effects observed [8] - The issuance of credit bonds has decreased, and total transaction volume has also declined [8] - The petrochemical industry faced pressure in the first half of 2025, with attention on oil price expectations and the "anti-involution" process [8] - The chemical industry is gradually recovering, with a focus on the implementation of "anti-involution" policies [8] - Lithium battery capital expenditures exceeded expectations, and Alibaba's financial report has sparked interest in AIDC [8]

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 discusses the recent trends in the Consumer Price Index (CPI) and its implications for economic conditions and industry performance, indicating a potential shift towards a mild inflation period driven by policy stimuli and seasonal factors [2][3]. CPI Trends and Economic Phases - In July, the CPI increased by 0.4% month-on-month, reversing a previous decline, suggesting a possible mild inflation phase ahead due to consumption subsidies and social security policies [2]. - Historical data shows that a rising CPI typically indicates economic recovery and increased demand, while a declining CPI reflects insufficient domestic demand and deflationary pressures [3][4]. Industry Performance During CPI Phases - During periods of rising CPI, essential consumer goods tend to perform well due to their price transmission capabilities, while resource sectors benefit from inflation expectations [4]. - Conversely, in declining CPI phases, defensive sectors show resilience, supported by policy easing and infrastructure investments [4]. Historical CPI Trends - The article outlines various CPI phases from 2015 to 2024, highlighting periods of inflation and deflation, with specific CPI ranges and characteristics for each phase [5]. Industry Performance Analysis - In the CPI rising period from March 2016 to February 2017, the CSI 300 index rose by 19.99%, while the CSI 2000 index increased by 31.56%, indicating a preference for small-cap stocks [7]. - From February 2019 to January 2020, both indices showed balanced performance, with the CSI 300 rising by 25.06% and the CSI 2000 by 28.04% [9]. - In the CPI rising period from January 2021 to February 2022, the CSI 300 fell by 12.08%, while the CSI 2000 rose by 18.85%, again favoring small-cap stocks [11]. Market Dynamics and Investment Strategies - The article suggests that during rising CPI periods, small-cap stocks may continue to outperform large-cap indices, indicating a potential shift in investment strategies [12]. - The concept of a "slow bull" market is introduced, emphasizing that market dynamics may favor small-cap and sector-specific performances rather than broad market rallies [12].