Quantitative Models and Construction Methods Model Name: Three-Dimensional Timing Model - **Model Construction Idea**: The model uses three dimensions: liquidity, divergence, and prosperity to judge market trends[8] - **Model Construction Process**: - The model evaluates the current liquidity trend, market divergence, and prosperity level - It uses technical indicators to assess the market status, such as the overbought condition of the CSI 300 index[8] - The model's historical performance is visualized to validate its effectiveness[17] - **Model Evaluation**: The model indicates a downward trend in a high turnover market, suggesting a low probability of short-term upward movement[8] Model Name: ETF Hot Trend Strategy - **Model Construction Idea**: The strategy selects ETFs based on their price trends and market attention[28] - **Model Construction Process**: - Identify ETFs with both highest and lowest price trends using K-line highest and lowest price shapes - Construct support and resistance factors based on the relative steepness of the regression coefficients of the highest and lowest prices over the past 20 days - Select the top 10 ETFs with the highest turnover rate in the past 5 and 20 days to form a risk parity portfolio[28] - **Model Evaluation**: The strategy includes ETFs from semiconductor, non-ferrous metals, 5G communication, battery industries, and growth styles[29] Model Name: Capital Flow Resonance Strategy - **Model Construction Idea**: The strategy monitors the resonance of margin trading and large order funds to select favored industries[32] - **Model Construction Process**: - Define the margin trading capital factor as the net buying of financing minus the net selling of securities lending, neutralized by the Barra market value factor - Define the active large order capital factor as the net inflow of the industry, neutralized by the time series of trading volume over the past year - Combine the two factors to construct the strategy, excluding extreme industries and large financial sectors to improve stability[35] - **Model Evaluation**: The strategy has shown stable positive excess returns since 2018, with an annualized excess return of 13.5% and an IR of 1.7[35] Model Backtesting Results - **Three-Dimensional Timing Model**: Historical performance shows a consistent downward trend in high turnover markets[17] - **ETF Hot Trend Strategy**: The strategy has achieved cumulative excess returns over the CSI 300 index this year[30] - **Capital Flow Resonance Strategy**: The strategy recorded a negative excess return last week, with an absolute return of -2.4% and an excess return of -2.0% relative to the industry equal weight[35] Quantitative Factors and Construction Methods Factor Name: Beta Factor - **Factor Construction Idea**: Measures the sensitivity of a stock's returns to market returns[40] - **Factor Construction Process**: - Calculate the beta coefficient of each stock based on its historical returns relative to the market index - Form portfolios of high and low beta stocks to compare their performance[40] - **Factor Evaluation**: High beta stocks significantly outperformed low beta stocks, recording a positive return of 2.19% last week[40] Factor Name: Growth Factor - **Factor Construction Idea**: Measures the growth potential of stocks based on their earnings and revenue growth[40] - **Factor Construction Process**: - Calculate the growth rate of earnings and revenue for each stock - Form portfolios of high and low growth stocks to compare their performance[40] - **Factor Evaluation**: Growth stocks continued to outperform value stocks, with the growth factor achieving a return of 1.51% last week[40] Factor Backtesting Results - **Beta Factor**: - Year-to-date: 26.61% - Last month: 2.39% - Last week: 2.19%[41] - **Growth Factor**: - Year-to-date: -0.44% - Last month: 4.74% - Last week: 1.51%[41]

Group 1 - The chairman of Juewei Food was fined for information disclosure violations, with a proposed penalty of 4 million yuan and warnings for responsible individuals [2] - Some banks are offering large-denomination certificates of deposit with interest rates exceeding 2%, creating a scarcity in the market as most banks have rates below 2% [3] - The National Medical Insurance Administration has released the 11th batch of centralized drug procurement, emphasizing principles of clinical stability, quality assurance, and anti-competitive practices [4] Group 2 - The Cyberspace Administration of China has taken action against Kuaishou for failing to manage harmful content, resulting in penalties and a requirement for corrective measures [5][6] - The film "731" has surpassed 800 million yuan in box office revenue as of September 20 [7] - Google is terminating its corporate subscription service for the Financial Times as part of broader cost-cutting measures, despite strong financial performance [8] Group 3 - Huawei plans to invest 15 billion yuan in ecosystem development, with over 1,300 products compatible with its HarmonyOS and significant growth in its cloud developer community [9] - The city of Jiangmen has initiated a Level III response to a public health emergency due to the current epidemic situation [10] - Haikou will distribute 10 million yuan in tourism consumption vouchers to stimulate local tourism during the upcoming holidays [11] Group 4 - Neuralink is set to begin trials for brain-computer interface implants aimed at individuals who have lost their ability to speak [12] - Xiaomi has launched a 10-year free repair service for its air conditioning products, enhancing customer service and product confidence [13]

本文首发于公众号"私募排排网"。 （点击↑↑ 上图查看详情 ） 2025年第三季度，A股市场迎来系统性慢牛，市场震荡上行。在此期间，量化私募基金成绩亮眼，据私募排排网数据，截至2025年8月底，在私 募排排网有3只以上产品有今年来业绩展示的量化私募共有173家，今年来收益均值约为22.36%，跑赢了同期的上证指数、深证成指（涨幅分别 为15.10%、21.91%）。其中，收益不低于10%的量化私募有148家。 | 排名 | 产品简称 | 公司简称 | 三级策略 | 實要经猛 | 8月超额 | 今年来超额 | | --- | --- | --- | --- | --- | --- | --- | | T | 磐松微盘股指数增强1号 额 | 磐松资产 | 其他指增 | 吴确 高云翔,曹靖康 | 应合规要求 | | | | 倍漾量化选股二期A类份 | 筒蒙量化 | 量化选股 | 蔡其志 | | | | | 正瀛骐骥指数增强17号 | 正演资产 | 其他指增 | | | | | | 大道崔苇 | 大道投资 | 量化选股 | 朱明强 | | | | ട് | 大岩量化选股1号B类份额 | 大岩资本 | 量化选股 | 黄 ...

Core Viewpoint - The discussion at the forum highlighted the evolving landscape of the private equity industry in China, emphasizing the importance of both quantitative and subjective investment strategies in navigating market cycles and identifying investment opportunities [1][2][5]. Group 1: Market Cycles and Investment Strategies - The capital market operates under various cycles, including not only bull and bear markets but also style rotation cycles [2][8]. - Quantitative investment can help stabilize volatility and discover value, while subjective investment allows for deeper industry insights [6][9]. - The current A-share market is characterized by friendly policies, ample liquidity, and reasonable valuations, suggesting that the bull market is progressing well [16]. Group 2: Value of Private Equity - The private equity industry plays a crucial role in enriching the financial market ecosystem and promoting long-term investment philosophies [4][5]. - Private equity is seen as a pioneer in product innovation within China's asset management sector, effectively meeting diverse investment needs [6]. - The industry attracts high-quality talent, which can lead to technological and service innovations, indicating a bright future for private equity [6]. Group 3: Investment Recommendations - Investors are advised to shift their mindset from bear to bull market thinking and avoid chasing past performance when selecting funds [14][15]. - Diversification across various asset classes is recommended to mitigate risks, and professional management should be sought for investment decisions [16]. - The importance of understanding market adjustments within a bull market is emphasized, suggesting that investors should be prepared for periodic corrections [15][16].

Core Viewpoint - The rapid development of index investment in the context of deepening capital market reforms and optimizing investor structure, with the total market ETF scale exceeding 5 trillion yuan by early September this year [1] Group 1: Index Investment Growth - The ETF management scale of Yongying Fund has surpassed 19 billion yuan, launching several industry-first products such as gold stock ETF, general aviation ETF, satellite ETF, and Hong Kong medical ETF [1] - The company emphasizes that index investment requires a deep understanding of industry development trends and forward-looking layouts rather than mere product replication [1] Group 2: Differentiated Development Strategy - Yongying Fund has adopted a unique "cake-cutting" strategy since 2020, focusing on niche opportunities within large industries, such as concentrating on the medical device sector instead of the entire medical industry [2] - This differentiated approach stems from in-depth research on industry trends, aligning with government strategic directions like low-altitude economy and commercial aerospace [2] Group 3: Performance and Growth - The strategy of early positioning in promising but under-explored areas has shown initial success, with products like gold stock ETF and medical device ETF performing well, contributing to the ETF total scale growing nearly threefold from 4.7 billion yuan at the beginning of the year [3] - Specific product performance includes gold stock ETF exceeding 10 billion yuan in scale within two years, medical device ETF nearing 5 billion yuan, and both general aviation ETF and satellite ETF surpassing 1 billion yuan [3] Group 4: Product Matrix Expansion - Following the validation of its differentiated layout, Yongying Fund has accelerated the development of its product matrix, establishing 11 ETF products covering various sectors [4] - The company aims to create a comprehensive "product shelf" to provide suitable investment tools regardless of market conditions, with plans to expand into core sectors like consumption, manufacturing, technology, and finance [4] Group 5: Quantitative Investment Development - Yongying Fund is actively developing its quantitative investment sector, primarily focusing on index enhancement strategies across multiple indices [5] - The company plans to increase investment in active quantitative strategies, including fundamental quantitative, multi-factor quantitative, and machine learning approaches [5] Group 6: Risk Management and Future Outlook - Yongying Fund emphasizes that quantitative investment is a technology-driven model that requires continuous effort and cannot guarantee easy success [6] - The company has established a strict risk management system to proactively manage risks, ensuring a better investment experience for investors [6] - Future plans include further enhancing product layout and research capabilities to provide more high-quality tool-type products, aiming for a differentiated development path through continuous innovation and refined management [6]

证券研究报告 | 基金研究（公募） 2025 年 9 月 20 日 A 股震荡调整，量化基金表现分化 量化基金周度跟踪（20250915-20250919） 本周（9 月 15 日-9 月 19 日）A 股震荡调整，量化基金表现分化。 本报告重点聚焦量化基金市场表现，总结近一周主要指数和量化基金业绩表现、 不同类型公募量化基金整体表现和业绩分布，以及本周收益表现较优的量化基 金，供投资者参考。 ❑市场整体表现： 本周量化基金表现分化，绝对收益方面，除 300 指增，其他指增基金绝对 收益均录得正值；主动量化和市场中性均录得负收益，主动量化平均跌 0.19%，市场中性平均跌 0.17%。超额收益方面，各类指增基金均跑输指 数，沪深 300 指增、中证 500 指增、中证 1000 指增、其他指增分别获得 -0.05%、-0.24%、-0.09%、-0.14%的超额。 ❑风险提示：图表中列示的数据结果仅为对市场及个基历史表现的客观描述，并 不预示其未来表现，亦不构成投资收益的保证或投资建议。 徐燕红 S1090524120003 xuyanhong@cmschina.com.cn 邓畅 S109052507000 ...

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]

- The report does not contain any specific quantitative models or factors, nor does it provide details on their construction, evaluation, or testing results. The content primarily focuses on the performance statistics of various quantitative funds, such as index-enhanced funds, active quantitative funds, and market-neutral funds, across different time periods [1][2][3] - The performance metrics include excess returns, tracking errors, and maximum drawdowns for funds tracking indices like CSI 300, CSI 500, CSI 1000, and CSI A500, as well as active quantitative and market-neutral strategies. These metrics are presented in tabular and graphical formats, segmented by weekly, monthly, and yearly periods [10][11][13] - The report also provides cumulative net value trends for equal-weighted portfolios of quantitative funds over the past year and two years, segmented by fund type (e.g., index-enhanced, active quantitative, market-neutral) [22][28][32]

Core Viewpoint - The report tracks the performance of various active quantitative strategies by GuoXin JinGong, aiming to outperform the median returns of actively managed equity funds, with a focus on four main strategies: Excellent Fund Performance Enhancement, Super Expected Selection, Broker Golden Stock Performance Enhancement, and Growth Stability Combination [2][3]. Group 1: Performance Overview - The Excellent Fund Performance Enhancement strategy had an absolute return of -0.28% this week and a year-to-date return of 27.54%, ranking in the 53.24 percentile among active equity funds [1][10]. - The Super Expected Selection strategy achieved an absolute return of 1.29% this week and 45.51% year-to-date, ranking in the 20.03 percentile among active equity funds [1][19]. - The Broker Golden Stock Performance Enhancement strategy reported an absolute return of 0.39% this week and 33.97% year-to-date, ranking in the 39.18 percentile among active equity funds [1][20]. - The Growth Stability Combination had an absolute return of -1.23% this week and 51.45% year-to-date, ranking in the 14.27 percentile among active equity funds [1][29]. Group 2: Excellent Fund Performance Enhancement - This strategy aims to benchmark against the median returns of actively managed equity funds, utilizing a quantitative approach to enhance performance based on the holdings of top-performing funds [7][34]. - The strategy has shown a historical annualized return of 20.31% from 2012 to mid-2025, outperforming the benchmark by 11.83% [37]. Group 3: Super Expected Selection - The strategy focuses on stocks with super expected events, selecting based on fundamental and technical criteria to build a portfolio that captures significant excess returns [40][41]. - It has achieved an annualized return of 34.49% from 2010 to mid-2025, outperforming the benchmark by 32.62% [41]. Group 4: Broker Golden Stock Performance Enhancement - This strategy leverages the broker's stock pool, reflecting both top-down industry analysis and bottom-up stock selection, aiming to outperform the ordinary equity fund index [42]. - The strategy has recorded an annualized return of 19.34% from 2018 to mid-2025, exceeding the benchmark by 14.38% [43]. Group 5: Growth Stability Combination - This strategy employs a two-dimensional evaluation system for growth stocks, prioritizing those closer to their earnings report dates to maximize excess returns [46]. - It has achieved an annualized return of 39.59% from 2012 to mid-2025, outperforming the benchmark by 34.73% [47].

Core Viewpoint - The article discusses the pressures and coping mechanisms of middle-aged individuals, particularly focusing on the challenges faced by middle-aged men and women in balancing work, family, and personal time [5][21][23]. Group 1: Middle-aged Men's Coping Mechanisms - Middle-aged men often find solace in hobbies such as fishing, gaming, and cycling as a way to relieve stress from work and family responsibilities [7][10]. - Social activities like playing cards are viewed as low-cost and healthy forms of relaxation for middle-aged men [10]. - The article highlights the contrast between men's and women's coping strategies, with men leaning towards hobbies and women seeking brief escapes from their responsibilities [10][14]. Group 2: Middle-aged Women's Challenges - Middle-aged women face significant pressure from multiple roles, including parenting and household responsibilities, leading to feelings of exhaustion and frustration [19][21]. - The article notes that women often feel the need to justify their desire for personal time, frequently using work-related excuses to carve out moments for themselves [25][26]. - A survey indicates that women experience a higher loss of leisure time due to childcare compared to men, particularly in families with multiple children [23][29]. Group 3: Stress Sources and Indices - The article provides a stress index for various sources of pressure, with childcare and household chores being the most significant contributors to stress for middle-aged women [19][20]. - Economic burdens, such as mortgages and loans, also contribute to the overall stress levels experienced by middle-aged individuals [21][19]. - Emotional support and respect are highlighted as critical yet often lacking elements in the lives of middle-aged women, exacerbating their feelings of isolation and stress [19][21].