点击注册小程序 查看完整报告 特别申明： 本订阅号中所涉及的证券研究信息由光大证券研究所编写，仅面向光大证券专业投资者客户，用作新媒体形势下研究 信息和研究观点的沟通交流。非光大证券专业投资者客户，请勿订阅、接收或使用本订阅号中的任何信息。本订阅号 难以设置访问权限，若给您造成不便，敬请谅解。光大证券研究所不会因关注、收到或阅读本订阅号推送内容而视相 关人员为光大证券的客户。 报告摘要 上周市场核心观点： 上周（2025.09.15-2025.09.19，下同）A股整体宽幅震荡，大市值表现占优。交易情绪方面，主要宽基指数量 能有所收缩，短线观点转向谨慎；沪深300等宽基指数时序波动、横截面波动持续回落，Alpha环境收窄。资金 面方面，融资增加额持续为正，股票型ETF转向净流入，资金面整体乐观。 近期市场从高斜率上涨转向宽幅震荡，主题博弈加剧，成长板块相对占优。从市值风格来看，大市值表现占 优，短线主题博弈把握龙头或更优。中长线仍维持市场震荡上行观点。 上周市场各指数涨跌不一，上证综指下跌1.30%，上证50下跌1.98%，沪深300下跌0.44%，中证500上涨 0.32%，中证1000上涨0.21%，创业 ...

Market Overview - The A-share market experienced a volatile upward trend during the week of September 8-12, 2025, with trading volume initially suppressed but later recovering [4] - The weekly financing increase saw a significant rise compared to the previous period, while ETF funds continued to experience net outflows, indicating that leveraged funds remain in a positive buying state [4] - The market is shifting focus from broad-based indices to thematic indices, with active participation in thematic trading [4] - The Shanghai Composite Index rose by 1.52%, while the ChiNext Index increased by 2.10% during the same period [4] Valuation Analysis - As of September 12, 2025, major broad-based indices such as the Shanghai Composite, SSE 50, CSI 300, and CSI 500 are classified under the "danger" valuation category, while the CSI 1000 and ChiNext are in the "moderate" category [4] - In the CITIC primary industry classification, sectors like coal, steel, building materials, and power equipment are also in the "danger" valuation category, while food and beverage, agriculture, and transportation are in the "safe" category [5] Fund Flow and Institutional Interest - The top five stocks attracting institutional attention this week were Jing Sheng Machinery, Xiamen Tungsten, Duofu Du, Xinji Energy, and Hanzhong Precision, with 237, 186, 167, 139, and 116 institutions respectively [7] - Southbound capital saw a net inflow of 60.822 billion HKD during the week, with the Shanghai Stock Connect contributing 19.406 billion HKD and the Shenzhen Stock Connect contributing 41.416 billion HKD [8] - The median return for stock ETFs was 1.93%, with a net outflow of 4.352 billion CNY, while the median return for Hong Kong stock ETFs was 3.09% with a net inflow of 21.168 billion CNY [8] Market Sentiment - The volume timing signals for major broad-based indices indicate a cautious outlook as of September 12, 2025 [6] - The degree of separation among fund clusters has slightly increased week-on-week, with excess returns for clustered stocks showing a minor rise while excess returns for clustered funds have slightly decreased [8]

- The report discusses the "Volume Timing Signal" model, which is used to gauge market sentiment based on trading volume. The model's construction involves analyzing the volume of trades to determine whether the market sentiment is optimistic or cautious. As of August 29, 2025, the volume timing signals for the CSI 1000, ChiNext Index, and Beijing 50 Index are cautious, while other major broad-based indices show optimistic signals[26][27] - The "Number of Rising Stocks in CSI 300" sentiment indicator is another model mentioned in the report. This model calculates the proportion of stocks in the CSI 300 index that have positive returns over a given period. The formula is: $$ \text{Proportion of Rising Stocks in CSI 300 over N days} = \frac{\text{Number of CSI 300 stocks with positive returns over N days}}{\text{Total number of CSI 300 stocks}} $$ This indicator helps capture market sentiment by identifying periods when a majority of stocks are performing well, which often indicates market optimism. The recent value of this indicator is around 94%[27][28][30] - The "Moving Average Sentiment Indicator" is also discussed. This model uses the eight moving averages of the CSI 300 index to determine market trends. The moving averages used are 8, 13, 21, 34, 55, 89, 144, and 233 days. The model assigns values based on the number of moving averages that the current price exceeds. If the current price exceeds more than five moving averages, the market sentiment is considered optimistic. The formula for the moving average sentiment indicator is: $$ \text{Number of Moving Averages Exceeded by Current Price} $$ The recent analysis shows that the CSI 300 index is in an optimistic sentiment zone[35][36][37] - The "Cross-sectional Volatility" factor is used to measure the dispersion of stock returns within an index. Higher cross-sectional volatility indicates a better environment for alpha generation. The recent values for cross-sectional volatility are: - CSI 300: 1.76% - CSI 500: 1.91% - CSI 1000: 2.23% These values suggest that the short-term alpha environment is improving[41][43] - The "Time-series Volatility" factor measures the volatility of individual stock returns over time. Higher time-series volatility also indicates a better environment for alpha generation. The recent values for time-series volatility are: - CSI 300: 0.53% - CSI 500: 0.38% - CSI 1000: 0.22% These values suggest that the short-term alpha environment is improving[44][46] Model and Factor Performance Metrics - Volume Timing Signal: - CSI 1000: Cautious - ChiNext Index: Cautious - Beijing 50 Index: Cautious - Other major indices: Optimistic[26][27] - Number of Rising Stocks in CSI 300: - Recent value: 94%[27][28][30] - Moving Average Sentiment Indicator: - Recent sentiment: Optimistic[35][36][37] - Cross-sectional Volatility: - CSI 300: 1.76% - CSI 500: 1.91% - CSI 1000: 2.23%[41][43] - Time-series Volatility: - CSI 300: 0.53% - CSI 500: 0.38% - CSI 1000: 0.22%[44][46]

Quantitative Models and Construction Methods 1. Model Name: Volume Timing Signal - **Model Construction Idea**: The model uses volume-based signals to determine market timing, identifying bullish or cautious market views based on volume trends[23][24] - **Model Construction Process**: 1. Analyze the volume trends of major broad-based indices 2. Assign a "bullish" or "cautious" signal based on the volume dynamics 3. For example, as of April 11, 2025, the Beixin 50 index showed a "bullish" signal, while other indices like the Shanghai Composite and CSI 300 showed "cautious" signals[23][24] - **Model Evaluation**: The model provides a straightforward and intuitive approach to market timing but may lack robustness in highly volatile markets[23][24] 2. Model Name: Momentum Sentiment Indicator - **Model Construction Idea**: This model captures market sentiment by analyzing the proportion of stocks with positive returns in the CSI 300 index over a specific period[24][25] - **Model Construction Process**: 1. Calculate the proportion of CSI 300 constituent stocks with positive returns over the past N days $ \text{CSI 300 N-day Upward Proportion} = \frac{\text{Number of stocks with positive returns in N days}}{\text{Total number of stocks in CSI 300}} $ 2. Smooth the indicator using two moving averages with different windows (N1 and N2, where N1 > N2) 3. Generate signals: - If the short-term moving average (fast line) exceeds the long-term moving average (slow line), the market is considered bullish - If the fast line falls below the slow line, the market sentiment is turning cautious[27] - **Model Evaluation**: The indicator is effective in capturing upward opportunities but may fail to avoid risks in declining markets[25][27] 3. Model Name: Moving Average Sentiment Indicator - **Model Construction Idea**: This model uses an eight-moving-average system to assess the trend state of the CSI 300 index[32][33] - **Model Construction Process**: 1. Calculate the closing prices of the CSI 300 index for eight moving averages (parameters: 8, 13, 21, 34, 55, 89, 144, 233) 2. Assign values to the indicator based on the number of moving averages above or below the current price: - If the current price exceeds five or more moving averages, the market is considered bullish - Otherwise, the market is neutral or bearish[32][33] - **Model Evaluation**: The model provides a clear trend-following signal but may lag in rapidly changing markets[35] --- Model Backtesting Results 1. Volume Timing Signal - Beixin 50 Index: Bullish signal[23][24] - Other indices (e.g., Shanghai Composite, CSI 300): Cautious signal[23][24] 2. Momentum Sentiment Indicator - CSI 300 Upward Proportion: Approximately 53% in the most recent week[25] 3. Moving Average Sentiment Indicator - CSI 300 Index: Currently in a non-bullish sentiment zone[35] --- Quantitative Factors and Construction Methods 1. Factor Name: Cross-Sectional Volatility - **Factor Construction Idea**: Measures the dispersion of stock returns within an index to assess the alpha environment[37] - **Factor Construction Process**: 1. Calculate the cross-sectional volatility of constituent stocks in indices like CSI 300, CSI 500, and CSI 1000 2. Compare the recent quarter's average volatility with historical periods to determine the alpha environment[41] - **Factor Evaluation**: Higher cross-sectional volatility indicates a better alpha environment for stock selection[37][41] 2. Factor Name: Time-Series Volatility - **Factor Construction Idea**: Measures the volatility of index returns over time to assess the alpha environment[41][44] - **Factor Construction Process**: 1. Calculate the time-series volatility of indices like CSI 300, CSI 500, and CSI 1000 2. Compare the recent quarter's average volatility with historical periods to evaluate the alpha environment[44] - **Factor Evaluation**: Higher time-series volatility suggests a favorable alpha environment for active strategies[41][44] --- Factor Backtesting Results 1. Cross-Sectional Volatility - CSI 300: 1.90% (recent quarter), 77.80% of the past six months' percentile[41] - CSI 500: 2.16% (recent quarter), 42.06% of the past six months' percentile[41] - CSI 1000: 2.52% (recent quarter), 64.54% of the past six months' percentile[41] 2. Time-Series Volatility - CSI 300: 0.63% (recent quarter), 78.84% of the past six months' percentile[44] - CSI 500: 0.48% (recent quarter), 55.56% of the past six months' percentile[44] - CSI 1000: 0.29% (recent quarter), 70.12% of the past six months' percentile[44]