报告导读： 从技术面来看，情绪模型信号再次回落；均线强弱指数依旧处于历史50%分位 点左右，市场趋势还有待观察。结合以上几点，我们认为，市场在短期内依旧会维持震 荡。 本订阅号所载内容仅面向国泰海通证券研究服务签约客户。因本资料暂时无法设置访问限制，根据《证 券期货投资者适当性管理办法》的要求，若您并非国泰海通证券研究服务签约客户，为保证服务质量、 控制投资风险，还请取消关注，请勿订阅、接收或使用本订阅号中的任何信息。我们对由此给您造成的 不便表示诚挚歉意，非常感谢您的理解与配合！如有任何疑问，敬请按照文末联系方式与我们联系。 法律声明 风险提示： 市场系统性风险、海外市场波动风险、模型误设风险。 报告来源 以上内容节选自国泰海通证券已发布的证券研究报告。 报告名称： 量化择时和拥挤度预警周报（20251205）短期内依旧会维持震荡 ；报告日期：2025.12.07 报告作者： 郑雅斌（分析师），登记编号：S0880525040105 曹君豪(分析师)，登记编号：S0880525040094 重要提醒 下周（20251208-20251212，后文同）市场观点：短期内依旧会维持震荡。 从量化指标上看，基于沪深 ...

- Liquidity shock indicator for CSI 300 index reached 1.86 on Friday, higher than the previous week's 1.33, indicating current market liquidity is 1.86 times the standard deviation above the past year's average level [7] - PUT-CALL ratio for SSE 50ETF options declined to 0.91 on Friday, lower than the previous week's 1.14, reflecting reduced investor caution regarding short-term movements of SSE 50ETF [7] - Five-day average turnover rates for SSE Composite Index and Wind All A Index were 1.27% and 1.91%, respectively, corresponding to the 75.73% and 81.47% percentiles since 2005, showing decreased trading activity [7] - SAR indicator for Wind All A Index showed a positive breakout on September 11 [10] - Moving average strength index for Wind All A Index scored 150, at the 53.3% percentile for 2023, indicating a fluctuating trend [10] - Sentiment model score was 1 out of 5, trend model signal was positive, and weighted model signal was negative [10] - Small-cap factor crowding score was 0.40, low-valuation factor crowding score was -0.67, high-profitability factor crowding score was -0.10, and high-growth factor crowding score was 0.15 [18] - Sub-scores for small-cap factor included valuation spread (1.08), pairwise correlation (0.06), market volatility (-0.42), and return reversal (0.85) [18] - Sub-scores for low-valuation factor included valuation spread (-1.25), pairwise correlation (-0.03), market volatility (-0.09), and return reversal (-1.32) [18] - Sub-scores for high-profitability factor included valuation spread (-0.17), pairwise correlation (0.14), market volatility (-0.84), and return reversal (0.48) [18] - Sub-scores for high-growth factor included valuation spread (1.91), pairwise correlation (0.46), market volatility (-0.94), and return reversal (-0.82) [18]

Market Overview - The market is expected to continue its upward trend next week, with the liquidity shock indicator for the CSI 300 index at 0.77, lower than the previous week's 1.26, indicating current market liquidity is 0.77 standard deviations above the average level over the past year [2] - The PUT-CALL ratio for the SSE 50 ETF options has increased to 0.80 from 0.66, reflecting a rise in investor caution regarding the short-term performance of the SSE 50 ETF [2] - The average turnover rates for the Shanghai Composite Index and Wind All A are at 1.47% and 2.25%, respectively, indicating a decrease in trading activity compared to historical levels [2] Economic Indicators - The onshore and offshore RMB exchange rates saw weekly increases of 0.66% and 0.68%, respectively [2] - The official manufacturing PMI for China in August was reported at 49.3, slightly below the previous value of 49.7 but above the consensus expectation of 49.25; the S&P Global China Manufacturing PMI was at 50.5, up from 49.5 [2] Technical Analysis - The SAR indicator for the Wind All A index has shown a downward breakout, while the sentiment model has issued a negative signal [2] - The moving average strength index currently scores 211, placing it in the 77.0% percentile for 2023 [2] - The sentiment model score is at 0 (out of 5), indicating a negative trend signal [2] Market Performance - For the week of September 1-5, the SSE 50 index fell by 1.15%, the CSI 300 index decreased by 0.81%, and the CSI 500 index dropped by 1.85%, while the ChiNext index rose by 2.35% [3] - The overall market PE (TTM) stands at 21.9 times, which is in the 73.9% percentile since 2005 [3] Factor Analysis - The small-cap factor's congestion level remains stable at 0.68, while the low valuation factor is at -0.66, and the high profitability factor is at -0.23 [4] - The high profitability growth factor has a congestion level of 0.25 [4] Industry Analysis - The congestion levels for the comprehensive, non-ferrous metals, telecommunications, power equipment, and machinery equipment industries are relatively high, with notable increases in the congestion levels for power equipment and comprehensive sectors [5]

Core Viewpoint - The article discusses the quantitative timing and crowding alerts in the financial market, providing insights into market trends and potential investment opportunities [1]. Group 1: Quantitative Timing - The report highlights the importance of quantitative timing in investment strategies, emphasizing its role in identifying optimal entry and exit points in the market [1]. - It presents data on market performance metrics, indicating significant fluctuations in key indices over the past week [1]. Group 2: Crowding Alerts - The article outlines the concept of crowding in investment positions, warning that excessive concentration in certain assets can lead to increased volatility [1]. - It provides statistics on the current levels of crowding in various sectors, suggesting that some sectors are nearing critical thresholds that could trigger market corrections [1]. Group 3: Market Trends - The report analyzes recent market trends, noting shifts in investor sentiment and sector performance [1]. - It includes projections for future market movements based on current data, indicating potential areas for investment growth [1].

Quantitative Factors and Their Construction 1. Factor Name: Small-Cap Factor - **Construction Idea**: The small-cap factor measures the performance of stocks with smaller market capitalization, which historically tend to outperform larger-cap stocks under certain market conditions [17][18] - **Construction Process**: The factor's crowding level is calculated using four indicators: valuation spread, pairwise correlation, long-term return reversal, and factor volatility. These indicators are combined into a composite score to assess the degree of crowding [18] - **Evaluation**: The small-cap factor showed a positive crowding level, indicating relatively strong performance and lower risk of factor failure [19] 2. Factor Name: Low-Valuation Factor - **Construction Idea**: This factor identifies stocks with lower valuation metrics, such as price-to-earnings or price-to-book ratios, which are expected to generate higher returns over time [17][18] - **Construction Process**: Similar to the small-cap factor, the low-valuation factor's crowding level is assessed using the same four indicators (valuation spread, pairwise correlation, long-term return reversal, and factor volatility) and combined into a composite score [18] - **Evaluation**: The low-valuation factor exhibited a slightly negative crowding level, suggesting moderate underperformance or potential risks of factor inefficiency [19] 3. Factor Name: High-Profitability Factor - **Construction Idea**: This factor targets stocks with strong profitability metrics, such as high return on equity (ROE) or net profit margins, which are often associated with stable and superior returns [17][18] - **Construction Process**: The factor's crowding level is calculated using the same methodology as the small-cap and low-valuation factors, combining the four indicators into a composite score [18] - **Evaluation**: The high-profitability factor showed a negative crowding level, indicating potential underperformance or risks of factor inefficiency [19] 4. Factor Name: High-Growth Factor - **Construction Idea**: This factor focuses on stocks with high growth rates in earnings or revenues, which are expected to deliver higher returns in growth-oriented market environments [17][18] - **Construction Process**: The high-growth factor's crowding level is also derived from the four indicators (valuation spread, pairwise correlation, long-term return reversal, and factor volatility) and combined into a composite score [18] - **Evaluation**: The high-growth factor exhibited the most negative crowding level among the factors analyzed, indicating significant underperformance and a higher risk of factor failure [19] --- Backtesting Results of Factors 1. Small-Cap Factor - **Valuation Spread**: 1.74 [19] - **Pairwise Correlation**: -0.32 [19] - **Market Volatility**: -0.38 [19] - **Return Reversal**: 1.43 [19] - **Composite Score**: 0.62 [19] 2. Low-Valuation Factor - **Valuation Spread**: -0.33 [19] - **Pairwise Correlation**: 0.05 [19] - **Market Volatility**: 0.15 [19] - **Return Reversal**: -0.29 [19] - **Composite Score**: -0.10 [19] 3. High-Profitability Factor - **Valuation Spread**: -1.23 [19] - **Pairwise Correlation**: -0.05 [19] - **Market Volatility**: 0.28 [19] - **Return Reversal**: -0.44 [19] - **Composite Score**: -0.36 [19] 4. High-Growth Factor - **Valuation Spread**: -2.04 [19] - **Pairwise Correlation**: 0.08 [19] - **Market Volatility**: -0.65 [19] - **Return Reversal**: -1.02 [19] - **Composite Score**: -0.91 [19]