Group 1 - The report highlights the performance of the "Xinxuan ETF Absolute Return Strategy," which achieved an annualized return of 14.23% over the past three years, with a maximum drawdown of only 8.6% and a Sharpe ratio of 1.44 [10] - As of 2024, the total return of the Xinxuan ETF portfolio is 54.04%, outperforming the equal-weighted ETF by 11.1%, with a Sharpe ratio of 1.55 and a maximum drawdown of 6.3% [10] - The latest holdings of the Xinxuan ETF strategy include various ETFs such as the Innovation Drug ETF (15%) and the Bank ETF (10%) [11] Group 2 - The "All-Weather Multi-Asset Risk Parity Strategy" has yielded a return of 27.75% since the beginning of 2024, with a maximum drawdown of 3.62% and a Sharpe ratio of 2.56 [13] - This strategy diversifies across different assets and strategies, including gold ETFs and U.S. equity ETFs, to enhance returns while reducing overall portfolio volatility [15] Group 3 - The "Recovery Fixed Income+" strategy aims to balance inflation and credit factors while maintaining liquidity, utilizing a monthly rotation among 15 high-liquidity ETFs in the Hong Kong market [19] - Since 2021, this strategy has achieved an annualized return of 7.63% with a volatility of 7.06% and a Sharpe ratio of 1.07 [19] Group 4 - The "China-U.S. Core Asset Portfolio" includes strong trend assets such as liquor, dividends, gold, and the Nasdaq, achieving an annualized return of 33.66% since early 2015, outperforming equal-weighted indices by 12.11% [21] - The latest holdings in this portfolio include the Dividend ETF [23] Group 5 - The "High Prosperity/Dividend Rotation Strategy" has generated an annualized return of 25.49% since early 2021, significantly outperforming equal-weighted indices by 22.91% [26] - The strategy adjusts holdings based on economic signals, switching between high-growth ETFs and dividend ETFs [26] Group 6 - The "Double Bond LOF Enhancement Strategy" has achieved an annualized return of 6.43% since early 2019, with a Sharpe ratio of 2.48 and a maximum drawdown of 2.42% [29] - This strategy focuses on increasing the weight of bonds in the portfolio while maintaining exposure to other assets [29] Group 7 - The "Structured Risk Parity Strategy (QDII)" has yielded a return of 28.53% since the beginning of 2024, with a maximum drawdown of 2.38% and a Sharpe ratio of 2.57 [32] - This strategy combines domestic long-term bond ETFs with QDII equity products and gold to enhance returns [32] Group 8 - The report indicates that 24 new public funds were established this week, raising a total of 141.73 billion yuan, with 14 new index funds accounting for 65.90 billion yuan of this total [39] - The new index funds include various themes such as technology, agriculture, and energy [39] Group 9 - As of November 14, 2025, A-share, bond, commodity, and cross-border ETFs saw net subscription amounts of 122.0 billion yuan, -2.7 billion yuan, 59.4 billion yuan, and 102.4 billion yuan, respectively [49] - In the A-share ETF segment, the net inflow was led by sectors such as electric power equipment and new energy [50]

- The report constructs an ETF hotspot trend strategy based on the highest and lowest price trends of ETFs, selecting those with both highest and lowest prices in an upward trend. Further, it constructs a support-resistance factor based on the relative steepness of the regression coefficients of the highest and lowest prices over the past 20 days, and selects the top 10 ETFs with the highest turnover rate in the past 5 days/20 days to construct a risk parity portfolio[27][30] - The report tracks the performance of various style factors, noting that the value factor recorded a positive return of 2.36%, the leverage factor recorded a positive return of 1.08%, and the volatility factor slightly rebounded with a return of 0.19%[41][42] - The report evaluates the performance of different alpha factors, highlighting that the quick ratio factor had the best performance with a weekly excess return of 1.32%, followed by the debt-asset ratio factor with a weekly excess return of 1.21%, and the earnings variability over 5 years factor with a weekly excess return of 1.04%[44][46][47] - The ETF hotspot trend strategy recorded a cumulative excess return over the CSI 300 index since the beginning of the year[28][29] - The value factor achieved a weekly return of 2.36%, the leverage factor achieved a weekly return of 1.08%, and the volatility factor achieved a weekly return of 0.19%[41][42] - The quick ratio factor achieved a weekly excess return of 1.32%, the debt-asset ratio factor achieved a weekly excess return of 1.21%, and the earnings variability over 5 years factor achieved a weekly excess return of 1.04%[44][46][47]

- The report does not contain specific quantitative models or factors for analysis [1][2][3] - The report primarily focuses on market performance, style indices, valuation metrics, and fund flows without detailing quantitative models or factor construction [1][2][3] - Key metrics such as PE_TTM, ERP, and style index performance are discussed, but no explicit quantitative model or factor development process is provided [41][51][59]

- The report discusses the microstructure rebalancing in the A-share market, highlighting the increased concentration of stock price movements driven by speculative capital inflows since June 2025, which has impacted quantitative products' portfolio construction and risk exposure adjustments[13][23][24] - Quantitative products have adjusted their exposure to micro-cap stocks, initially reducing their holdings to mitigate nonlinear market cap risks, and later increasing allocations to amplify excess returns as speculative capital inflows weakened post-October 2025[13][23][24] - The report emphasizes the Barra style factor performance, noting that fundamental factors such as BP value and investment quality have shown positive returns, while transaction-related factors like short-term momentum have also delivered strong excess returns during the market's recent fluctuations[23][24][25]

- The report does not contain any specific quantitative models or factors for analysis or construction[1][2][3][4] - The report primarily focuses on market trends, fund flows, and industry performance without detailing quantitative models or factors[5][6][7] - No formulas, construction processes, or evaluations of quantitative models or factors are provided in the report[8][9][10]

Group 1 - The establishment of Shenzhen Junxing Private Securities Fund Management Co., Ltd. was completed, with a registered capital of 10 million yuan and 7 full-time employees [1] - Wang Pei, the legal representative and general manager, holds 60% of the shares and has a background as a fund manager at previous firms [1] - In 2023, Wang Pei was involved in a labor dispute with his former employer, which led to arbitration [1] Group 2 - As of October 31, 2025, 91.33% of the 10,969 private funds achieved positive returns, with an average return rate of 24.32% [2] - Stock strategies led the performance with an average return of 29.52%, and 92.73% of products in this category were profitable [2] - Quantitative long strategies outperformed with an average return of 36.76% and a 96.52% positive return rate [2] Group 3 - Combination funds showed strong profitability stability, with 96.85% of products yielding positive returns [3] - Bond strategies maintained a conservative approach, achieving an average return of 8.77% but with a 90.09% positive return rate [3] Group 4 - Commodity market volatility posed challenges for futures and derivatives strategies, which had an average return of 13.02% and a positive return rate of 82.43% [4]

Core Viewpoint - The A-share market has shown a strong upward trend in 2023, with significant internal style differentiation, particularly between small and large-cap stocks, leading to varying performances among quantitative long strategies [2][3]. Group 1: Market Performance - As of the end of October 2023, the Shanghai Composite Index, Shenzhen Component Index, and ChiNext Index have increased by approximately 17.99%, 28.46%, and 48.84% respectively [2]. - In the first half of the year, small-cap stocks outperformed large-cap stocks, but a style switch occurred in late August, with the CSI 300 Index outperforming small-cap stocks in August and September [2]. Group 2: Quantitative Long Strategy Performance - Quantitative long strategy products faced negative excess returns in the months of August and September, marking the worst monthly performance of the year [2]. - However, since October, the excess returns of quantitative long strategies have begun to recover as institutional investors loosened their collective positions [2]. Group 3: Top Performing Private Equity Firms - For firms with over 10 billion in assets, the top three in terms of average excess returns for quantitative long products are Ming Shi Fund, Ping Fang He Investment, and Meng Xi Investment [3][4]. - Ming Shi Fund leads with four qualifying quantitative long products and a total product scale of approximately 5.62 billion, achieving an average excess return of ***% [4]. - Ping Fang He Investment and Meng Xi Investment follow, with their best-performing products achieving excess returns of ***% [5]. Group 4: Mid-Sized Private Equity Firms - In the 50-100 billion category, Bei Yang Quantitative topped the list with five qualifying products and an average excess return of ***% [7][8]. - The firm is noted for its AI-driven quantitative investment approach, led by a team with significant academic credentials [8][9]. Group 5: Smaller Private Equity Firms - In the 20-50 billion category, Han Rong Investment and Lu Xiu Investment ranked first and second, respectively, with average excess returns of ***% [10][11]. - Han Rong Investment focuses on short-cycle price-volume predictions, while Lu Xiu Investment employs a strategy of diversified holdings to achieve stable excess returns [11][12]. Group 6: Smallest Private Equity Firms - In the 0-20 billion category, Shanghai Zi Jie Private Equity ranked fourth, with three qualifying products and an average excess return of ***% [13][15]. - The firm primarily focuses on small-cap strategies, particularly targeting stocks that have experienced significant declines [15].

点击注册小程序 报告摘要 量化市场跟踪 大类因子表现： 本周（2025.11.10-2025.11.14，下同），残差波动率因子和杠杆因子获得正收益（0.50%和0.36%），beta 因子、规模因子和动量因子获得负收益（-1.10%、-0.92%和-0.70%），市场小市值风格占优、反转效应显 著。 单因子表现： 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。 机构调研组合跟踪： 本周公募调研选股策略和私募调研跟踪策略获取正超额收益。公募调研选股策略相对中证800获得超额收 益1.82%，私募调研跟踪策略相对中证800获得超额收益1.06%。 大宗交易组合跟踪： 沪深300股票池中，本周表现较好的因子有大单净流入(1.63%)、市盈率因子(1.50%)、5日成交量的标准差 (1.40%),表现较差 ...

Quantitative Models and Construction Methods 1. Model Name: PB-ROE-50 Combination - **Model Construction Idea**: The PB-ROE-50 combination is constructed based on the principle of selecting stocks with low price-to-book (PB) ratios and high return on equity (ROE), aiming to capture value and profitability factors[25] - **Model Construction Process**: - Stocks are selected based on their PB and ROE metrics - The portfolio is rebalanced periodically to maintain the desired exposure to these factors - The construction details are referenced in earlier reports[25][26] - **Model Evaluation**: The model experienced a drawdown in excess returns across all stock pools during the week, indicating potential short-term underperformance[25] --- Model Backtesting Results 1. PB-ROE-50 Combination - **Excess Return**: - CSI 500: -0.23% this week, 2.92% year-to-date - CSI 800: -0.98% this week, 15.82% year-to-date - Full Market: -1.39% this week, 18.21% year-to-date[26] - **Absolute Return**: - CSI 500: -1.49% this week, 30.06% year-to-date - CSI 800: -2.10% this week, 38.80% year-to-date - Full Market: -1.91% this week, 46.11% year-to-date[26] --- Quantitative Factors and Construction Methods 1. Factor Name: Residual Volatility Factor - **Factor Construction Idea**: Captures the residual volatility of stocks after controlling for market and sector effects, aiming to identify stocks with stable performance[20] - **Factor Construction Process**: - Calculate the residual volatility of stock returns after regressing against market and sector returns - Rank stocks based on their residual volatility and construct a portfolio with the desired exposure[20] - **Factor Evaluation**: The factor delivered positive returns this week, indicating its effectiveness in capturing stable stocks during the period[20] 2. Factor Name: Leverage Factor - **Factor Construction Idea**: Measures the financial leverage of companies, aiming to capture the risk-return tradeoff associated with leverage[20] - **Factor Construction Process**: - Calculate the leverage ratio of companies (e.g., debt-to-equity ratio) - Rank stocks based on their leverage and construct a portfolio with the desired exposure[20] - **Factor Evaluation**: The factor delivered positive returns this week, suggesting its relevance in the current market environment[20] 3. Factor Name: Beta Factor - **Factor Construction Idea**: Measures the sensitivity of a stock's returns to market returns, aiming to capture systematic risk[20] - **Factor Construction Process**: - Calculate the beta of stocks using historical return data - Rank stocks based on their beta and construct a portfolio with the desired exposure[20] - **Factor Evaluation**: The factor delivered negative returns this week, indicating underperformance in the current market environment[20] 4. Factor Name: Size Factor - **Factor Construction Idea**: Captures the size effect by focusing on small-cap stocks, which tend to outperform large-cap stocks over time[20] - **Factor Construction Process**: - Rank stocks based on their market capitalization - Construct a portfolio with a tilt towards smaller-cap stocks[20] - **Factor Evaluation**: The factor delivered negative returns this week, despite the general preference for small-cap stocks in the market[20] 5. Factor Name: Momentum Factor - **Factor Construction Idea**: Captures the momentum effect by focusing on stocks with strong recent performance[20] - **Factor Construction Process**: - Calculate the past returns of stocks over a specific period (e.g., 6 months or 12 months) - Rank stocks based on their momentum and construct a portfolio with the desired exposure[20] - **Factor Evaluation**: The factor delivered negative returns this week, indicating a reversal effect in the market[20] --- Factor Backtesting Results 1. Residual Volatility Factor - Weekly Return: 0.50%[20] 2. Leverage Factor - Weekly Return: 0.36%[20] 3. Beta Factor - Weekly Return: -1.10%[20] 4. Size Factor - Weekly Return: -0.92%[20] 5. Momentum Factor - Weekly Return: -0.70%[20]

Group 1 - The core viewpoint of the article is to track the performance of various active quantitative strategies developed by GuoXin Securities, focusing on their relative performance against the active equity fund median [2][3][6]. - The report includes four main strategies: Excellent Fund Performance Enhancement Portfolio, Super Expected Selection Portfolio, Broker Golden Stock Performance Enhancement Portfolio, and Growth Stability Portfolio [2][3][6]. Group 2 Excellent Fund Performance Enhancement Portfolio - This portfolio aims to outperform the median return of active equity funds by utilizing a quantitative approach based on the holdings of top-performing funds [7][36]. - As of this week, the portfolio's absolute return is -1.80%, with a year-to-date return of 25.03%, ranking in the 58.46 percentile among active equity funds [11][38]. Super Expected Selection Portfolio - This portfolio selects stocks based on the criteria of exceeding expectations and analyst upgrades, focusing on both fundamental and technical analysis [13][42]. - The portfolio's absolute return this week is -2.36%, with a year-to-date return of 41.40%, ranking in the 27.15 percentile among active equity funds [21][43]. Broker Golden Stock Performance Enhancement Portfolio - This strategy utilizes a stock pool from broker recommendations and aims to optimize the portfolio while controlling deviations in stock selection and style [19][44]. - The portfolio's absolute return this week is -2.34%, with a year-to-date return of 32.74%, ranking in the 42.32 percentile among active equity funds [22][45]. Growth Stability Portfolio - This portfolio employs a two-dimensional evaluation system for growth stocks, prioritizing stocks closer to their earnings report dates to capture potential excess returns [27][48]. - The portfolio's absolute return this week is 0.29%, with a year-to-date return of 54.37%, ranking in the 11.65 percentile among active equity funds [31][49].