Core Insights - Jinlei Co., Ltd. (300443.SZ) reported its Q3 2025 results, revealing that 26 institutional investors held a total of 20.03 million A-shares, accounting for 6.26% of the total share capital [1] - The top ten institutional investors collectively held 6.02% of the shares, with a decrease of 0.61 percentage points compared to the previous quarter [1] Institutional Holdings - The number of institutional investors holding Jinlei shares is 26, with a total holding of 20.03 million shares [1] - The top ten institutional investors include notable entities such as Hong Kong Central Clearing Limited and various investment funds, indicating a diversified investor base [1] - The proportion of shares held by the top ten institutional investors decreased from the previous quarter [1] Public Fund Activity - Three public funds increased their holdings in Jinlei, while three others reduced their stakes, indicating mixed sentiment among public fund investors [2] - A total of 12 new public funds disclosed their holdings in Jinlei, reflecting growing interest from new investors [2] - 153 public funds did not disclose their holdings in the current period, suggesting potential shifts in investment strategies [2] Foreign Investment - One foreign fund, Hong Kong Central Clearing Limited, increased its holdings in Jinlei, with an increase percentage of 0.34% [2]

Group 1 - The core viewpoint of the news is that 聚辰股份 (Jucheng Semiconductor) has seen a 5% increase in stock price, reaching 172.55 CNY per share, with a trading volume of 2.092 billion CNY and a turnover rate of 7.91%, resulting in a total market capitalization of 27.31 billion CNY [1] - 聚辰股份 is located in Shanghai and was established on November 13, 2009, with its listing date on December 23, 2019. The company specializes in the research, design, and sales of integrated circuit products, providing application solutions and technical support services, with 100% of its main business revenue coming from chip sales [1] Group 2 - From the perspective of major fund holdings, only one fund under 申万菱信 (Shenwan Hongyuan) has a significant position in 聚辰股份. The fund, 申万菱信中证1000指数增强A (017067), held 16,500 shares in the second quarter, unchanged from the previous period, accounting for 0.95% of the fund's net value, making it the second-largest holding [2] - The fund has a current scale of 87.4876 million CNY and has achieved a year-to-date return of 30.43%, ranking 1653 out of 4219 in its category. Over the past year, it has returned 37.05%, ranking 1214 out of 3877, and since its inception, it has returned 26.44% [2] - The fund manager, 刘敦 (Liu Dun), has a tenure of 8 years and 20 days, managing assets totaling 3.457 billion CNY, with the best return during his tenure being 69.81% and the worst being -70.72%. The co-manager, 夏祥全 (Xia Xiangquan), has a tenure of 5 years and 8 days, managing 922 million CNY, with the best return of 26.44% and the worst of -26.61% during his tenure [2]

Core Viewpoint - Jiangfeng Electronics experienced a 5.09% increase in stock price, reaching 96.90 CNY per share, with a trading volume of 1.478 billion CNY and a turnover rate of 7.00%, resulting in a total market capitalization of 25.71 billion CNY [1] Group 1: Company Overview - Jiangfeng Electronics is located in Yuyao City, Zhejiang Province, and was established on April 14, 2005, with its listing date on June 15, 2017 [1] - The company specializes in the research, production, and sales of high-purity sputtering targets, with its main business revenue composition being: ultra-high purity targets 63.26%, precision components 21.90%, and others 14.84% [1] Group 2: Fund Holdings - According to data, one fund under Shenwan Hongyuan holds a significant position in Jiangfeng Electronics, specifically Shenwan Hongyuan CSI 1000 Index Enhanced A (017067), which held 18,000 shares in the second quarter, unchanged from the previous period, accounting for 0.95% of the fund's net value [2] - The fund has a current scale of 87.4876 million CNY and has achieved a year-to-date return of 29.35%, ranking 1575 out of 4218 in its category [2] - The fund manager Liu Dun has a tenure of 8 years and 17 days, with a total asset scale of 3.457 billion CNY, while the other manager Xia Xiangquan has a tenure of 5 years and 5 days, managing 922 million CNY [2]

Core Insights - Yunda Co., Ltd. experienced a stock price increase of 5.07% on September 17, reaching 19.08 CNY per share, with a trading volume of 465 million CNY and a turnover rate of 3.64%, resulting in a total market capitalization of 15.013 billion CNY [1] Company Overview - Yunda Energy Technology Group Co., Ltd. is located in Hangzhou, Zhejiang Province, and was established on November 30, 2001, with its listing date on April 26, 2019 [1] - The company's main business involves the research, development, production, and sales of large wind turbine generators [1] - Revenue composition includes: wind turbine generators (87.54%), new energy EPC contracting (6.36%), other revenues (4.04%), and power generation income (2.06%) [1] Fund Holdings - According to data, one fund under Shenwan Hongyuan Asset Management holds a significant position in Yunda Co., Ltd. The Shenwan Hongyuan CSI 1000 Index Enhanced A Fund (017067) held 87,300 shares in the second quarter, accounting for 0.8% of the fund's net value, ranking as the tenth largest holding [2] - The fund was established on February 14, 2023, with a latest scale of 87.4876 million CNY, and has achieved a year-to-date return of 27.27%, ranking 1790 out of 4222 in its category [2] - Over the past year, the fund has returned 72.95%, ranking 1213 out of 3804, and since inception, it has achieved a return of 23.38% [2] Fund Manager Performance - The fund manager Liu Dun has a tenure of 7 years and 345 days, managing assets totaling 3.457 billion CNY, with the best fund return during his tenure being 65.03% and the worst being -70.72% [2] - Co-manager Xia Xiangquan has a tenure of 4 years and 333 days, managing assets of 922 million CNY, with the best return of 23.38% and the worst return of -26.61% during his tenure [2]

Core Viewpoint - Yunda Energy Technology Group Co., Ltd. experienced a 5.08% decline in stock price, closing at 17.75 CNY per share, with a total market capitalization of 13.967 billion CNY [1] Company Overview - Yunda Energy was established on November 30, 2001, and went public on April 26, 2019. The company is based in Hangzhou, Zhejiang Province, and specializes in the research, production, and sales of large wind turbine generators [1] - The revenue composition of Yunda Energy is as follows: wind turbine generators account for 87.54%, new energy EPC contracting for 6.36%, other revenues for 4.04%, and power generation income for 2.06% [1] Fund Holdings - According to data, Shenyin Wanguo Fund has a significant holding in Yunda Energy, with the Shenyin Wanguo CSI 1000 Index Enhanced A Fund (017067) holding 87,300 shares, representing 0.8% of the fund's net value, making it the tenth largest holding [2] - The Shenyin Wanguo CSI 1000 Index Enhanced A Fund was established on February 14, 2023, with a current scale of 87.4876 million CNY. Year-to-date, the fund has achieved a return of 26.81%, ranking 1772 out of 4222 in its category [2] - The fund manager, Liu Dun, has a tenure of 7 years and 344 days, with a total asset scale of 3.457 billion CNY. The best return during his tenure is 65.15%, while the worst is -70.72% [2] - Co-manager Xia Xiangquan has a tenure of 4 years and 332 days, managing assets totaling 922 million CNY, with a best return of 23.25% and a worst return of -26.61% during his tenure [2]

Quantitative Models and Construction Methods - **Model Name**: Maximized Factor Exposure (MFE) Portfolio **Model Construction Idea**: The MFE portfolio aims to maximize the exposure of a single factor while controlling for constraints such as industry exposure, style exposure, stock weight deviation, and turnover rate. This approach evaluates the effectiveness of factors under realistic constraints in enhanced index portfolios [56][57][59] **Model Construction Process**: The optimization model is formulated as follows: $ \begin{array}{ll} max & f^{T}w \\ s.t. & s_{l}\leq X(w-w_{b})\leq s_{h} \\ & h_{l}\leq H(w-w_{b})\leq h_{h} \\ & w_{l}\leq w-w_{b}\leq w_{h} \\ & b_{l}\leq B_{b}w\leq b_{h} \\ & 0\leq w\leq l \\ & 1^{T}w=1 \\ & \Sigma|w-w_{0}|\leq to_{h} \end{array} $ - **Objective Function**: Maximize single-factor exposure, where \( f \) represents factor values, and \( w \) is the stock weight vector - **Constraints**: 1. Style exposure deviation (\( X \)): \( s_{l} \) and \( s_{h} \) are the lower and upper bounds for style factor deviation 2. Industry exposure deviation (\( H \)): \( h_{l} \) and \( h_{h} \) are the lower and upper bounds for industry deviation 3. Stock weight deviation (\( w_{l} \) and \( w_{h} \)): Limits on individual stock weight deviation relative to the benchmark 4. Component weight limits (\( b_{l} \) and \( b_{h} \)): Constraints on the weight of benchmark components 5. No short selling and upper limits on stock weights 6. Full investment constraint: \( 1^{T}w=1 \) 7. Turnover constraint: \( \Sigma|w-w_{0}|\leq to_{h} \), where \( w_{0} \) is the previous period's weight [56][57][59] **Model Evaluation**: The model effectively balances factor exposure and practical constraints, ensuring stable returns and avoiding excessive concentration in specific stocks [60] --- Quantitative Factors and Construction Methods - **Factor Name**: Six-Month UMR **Factor Construction Idea**: The six-month UMR factor measures risk-adjusted momentum over a six-month window, capturing medium-term momentum trends [19][8][44] **Factor Construction Process**: - The UMR (Up-Minus-Down Ratio) is calculated as the ratio of upward movements to downward movements in stock prices over a specified period - The six-month UMR specifically uses a six-month window to compute this ratio, adjusted for risk [19][8][44] **Factor Evaluation**: This factor demonstrates strong performance in various index spaces, particularly in the CSI 500 and CSI All Share indices, indicating its effectiveness in capturing medium-term momentum [8][44] - **Factor Name**: Three-Month UMR **Factor Construction Idea**: Similar to the six-month UMR, this factor focuses on shorter-term momentum trends over a three-month window [19][8][44] **Factor Construction Process**: - The three-month UMR is calculated using the same methodology as the six-month UMR but with a three-month window for data aggregation [19][8][44] **Factor Evaluation**: This factor shows consistent performance across multiple indices, including the CSI 500 and CSI All Share indices, making it a reliable short-term momentum indicator [8][44] - **Factor Name**: Pre-Tax Earnings to Total Market Value (EPTTM) **Factor Construction Idea**: This valuation factor evaluates the earnings yield of a stock, providing insights into its relative valuation [19][8][44] **Factor Construction Process**: - EPTTM is calculated as the ratio of pre-tax earnings to the total market value of a stock, with adjustments for rolling time windows (e.g., one year) [19][8][44] **Factor Evaluation**: EPTTM consistently ranks among the top-performing valuation factors, particularly in the CSI 300 and CSI 800 indices, reflecting its robustness in identifying undervalued stocks [8][44] --- Backtesting Results of Models - **MFE Portfolio**: - The MFE portfolio demonstrates strong performance under various constraints, with backtesting results showing significant alpha generation relative to benchmarks like CSI 300, CSI 500, and CSI 1000 [60][61] --- Backtesting Results of Factors - **Six-Month UMR**: - CSI 500: Weekly return of 0.99%, monthly return of 1.65%, annualized return of -4.07% [26] - CSI All Share: Weekly return of 1.23%, monthly return of 1.59%, annualized return of 7.43% [44] - **Three-Month UMR**: - CSI 500: Weekly return of 0.94%, monthly return of 1.31%, annualized return of 0.68% [26] - CSI All Share: Weekly return of 1.02%, monthly return of 1.63%, annualized return of 5.64% [44] - **EPTTM**: - CSI 300: Weekly return of 0.74%, monthly return of 1.42%, annualized return of 3.89% [22] - CSI 800: Weekly return of 1.00%, monthly return of 1.91%, annualized return of 2.87% [30]

Quantitative Factors and Construction Methods - **Factor Name**: Single-quarter ROE **Construction Idea**: This factor measures the return on equity (ROE) for a single quarter, reflecting the profitability of a company relative to its equity base[2][18] **Construction Process**: The formula for single-quarter ROE is: $ Quart\_ROE = \frac{Net\ Income \times 2}{Beginning\ Equity + Ending\ Equity} $ Here, "Net Income" represents the net profit for the quarter, and "Beginning Equity" and "Ending Equity" are the equity values at the start and end of the quarter, respectively[18] **Evaluation**: This factor performed well in the CSI All Share Index space during the past week, indicating its effectiveness in identifying profitable stocks[2][42] - **Factor Name**: Single-quarter ROA **Construction Idea**: This factor evaluates the return on assets (ROA) for a single quarter, assessing how efficiently a company utilizes its assets to generate profits[18] **Construction Process**: The formula for single-quarter ROA is: $ Quart\_ROA = \frac{Net\ Income \times 2}{Beginning\ Assets + Ending\ Assets} $ "Net Income" is the quarterly net profit, while "Beginning Assets" and "Ending Assets" are the total assets at the start and end of the quarter, respectively[18] **Evaluation**: This factor also demonstrated strong performance in the CSI All Share Index space over the past week, highlighting its utility in asset efficiency analysis[2][42] - **Factor Name**: Standardized Unexpected Earnings (SUE) **Construction Idea**: This factor captures the deviation of actual earnings from expected earnings, standardized by the standard deviation of expected earnings, to measure earnings surprises[18] **Construction Process**: The formula for SUE is: $ SUE = \frac{Actual\ Earnings - Expected\ Earnings}{Standard\ Deviation\ of\ Expected\ Earnings} $ "Actual Earnings" refers to the reported earnings, while "Expected Earnings" and their standard deviation are derived from analyst forecasts[18] **Evaluation**: This factor showed significant positive performance in the National SME Index (CSI 2000) and the ChiNext Index spaces, indicating its effectiveness in identifying earnings surprises[36][39] Factor Backtesting Results - **Single-quarter ROE**: - CSI All Share Index: Weekly return of 1.46%, monthly return of 1.95%, annualized return over the past year of -1.73%, and historical annualized return of 4.88%[42][43] - **Single-quarter ROA**: - CSI All Share Index: Weekly return of 1.09%, monthly return of 1.33%, annualized return over the past year of 0.27%, and historical annualized return of 4.14%[42][43] - **Standardized Unexpected Earnings (SUE)**: - National SME Index (CSI 2000): Weekly return of 6.41%, monthly return of 19.22%, annualized return over the past year of 32.33%, and historical annualized return of 10.98%[36] - ChiNext Index: Weekly return of 7.76%, monthly return of 26.34%, annualized return over the past year of 44.74%, and historical annualized return of 7.82%[39] Composite Factor Portfolio Construction - **MFE Portfolio Construction**: **Idea**: The Maximized Factor Exposure (MFE) portfolio is designed to maximize the exposure to a single factor while controlling for constraints such as industry and style exposures, stock weight deviations, and turnover[55][59] **Optimization Model**: The optimization problem is formulated as: $ \begin{array}{ll} max & f^{T}w \\ s.t. & s_{l} \leq X(w-w_{b}) \leq s_{h} \\ & h_{l} \leq H(w-w_{b}) \leq h_{h} \\ & w_{l} \leq w-w_{b} \leq w_{h} \\ & b_{l} \leq B_{b}w \leq b_{h} \\ & 0 \leq w \leq l \\ & 1^{T}w = 1 \\ & \Sigma|w-w_{0}| \leq to_{h} \end{array} $ Here, $f$ represents the factor values, $w$ is the weight vector, and the constraints include style, industry, stock weight, and turnover limits[55][58] **Evaluation**: The MFE portfolio approach ensures that factor effectiveness is tested under realistic constraints, making it a robust method for evaluating factor performance[55][59] MFE Portfolio Backtesting Results - **CSI 300 Index**: - Weekly excess return: Maximum 1.05%, minimum -0.81%, median 0.00%[46][49] - Monthly excess return: Maximum 3.00%, minimum -1.15%, median 0.30%[46][49] - **CSI 500 Index**: - Weekly excess return: Maximum 1.00%, minimum -0.08%, median 0.40%[50][52] - Monthly excess return: Maximum 2.73%, minimum -0.42%, median 0.99%[50][52] - **CSI 1000 Index**: - Weekly excess return: Maximum 0.82%, minimum -0.26%, median 0.28%[53][54] - Monthly excess return: Maximum 3.52%, minimum -0.08%, median 1.72%[53][54]