Core Insights - Xidi Micro (688173.SH) reported its Q3 2025 results, revealing that 13 institutional investors hold a total of 71.41 million shares, representing 17.38% of the company's total equity [1] - The top ten institutional investors collectively hold 17.36% of the shares, which is a decrease of 2.45 percentage points compared to the previous quarter [1] Institutional Holdings - The number of institutional investors holding Xidi Micro shares has remained stable, with a total of 13 investors disclosing their holdings [1] - The top ten institutional investors include notable entities such as Chongqing Weichun Enterprise Management Consulting Co., Ltd. and Hong Kong Central Clearing Limited [1] Public Fund Activity - Two public funds increased their holdings in this period, including E Fund CSI 1000 Quantitative Enhanced A and Penghua Smart Investment Digital Economy Mixed A, with a slight increase in the proportion of shares held [2] - Six new public funds disclosed their holdings, including notable funds like China Merchants CSI 1000 Enhanced Strategy ETF and Wan Ke Growth Enterprise Board Index Enhanced A [2] - A total of 84 public funds did not disclose their holdings in this period, indicating a significant turnover in public fund participation [2] Foreign Investment - One new foreign institutional investor disclosed its holdings in this period, specifically Hong Kong Central Clearing Limited [2]

Group 1 - G-bits stock price increased by 4.1% on September 23, reaching 578.99 yuan per share, with a trading volume of 1.032 billion yuan and a turnover rate of 2.52%, resulting in a total market capitalization of 41.711 billion yuan [1] - The stock has risen for three consecutive days, with a cumulative increase of 6.15% during this period [1] - G-bits, established on March 26, 2004, specializes in the creative planning, development, and commercialization of online games [1] Group 2 - According to data, one fund from Caitong Fund holds G-bits as a top ten heavy stock, specifically the Caitong CSI 1000 Index Enhanced A (019270), which held 1,900 shares in the second quarter, accounting for 0.8% of the fund's net value, ranking as the sixth largest heavy stock [2] - The fund has generated a floating profit of approximately 43,300 yuan today and 63,800 yuan during the three-day increase [2] - The Caitong CSI 1000 Index Enhanced A fund was established on November 7, 2023, with a latest scale of 18.5268 million yuan, and has achieved a year-to-date return of 31.65% [2]

Group 1 - The core point of the news is that Nanwei Software has experienced a continuous decline in stock price, dropping 12.44% over the last five days, with the current stock price at 12.32 CNY per share and a market capitalization of 7.15 billion CNY [1] - Nanwei Software, established on October 18, 2002, and listed on December 30, 2014, primarily engages in software development, system integration, and technical services for e-government, with its revenue composition being 39.73% from solutions, 24.26% from other services, 16.87% from government software products, 9.78% from urban public safety software products, and 9.20% from innovative businesses [1] Group 2 - From the perspective of fund holdings, the Caifeng Fund has a significant position in Nanwei Software, with its Caifeng CSI 1000 Index Enhanced A Fund holding 45,800 shares, representing 0.8% of the fund's net value, ranking as the fifth-largest holding [2] - The Caifeng CSI 1000 Index Enhanced A Fund has a total scale of 18.53 million CNY and has achieved a year-to-date return of 27.08%, ranking 1411 out of 4222 in its category [2] Group 3 - The fund managers of the Caifeng CSI 1000 Index Enhanced A Fund include Zhu Haidong, Gu Hongyuan, and Guo Xin, with varying tenures and performance records [3] - Zhu Haidong has a tenure of 6 years and 53 days, managing assets of 1.478 billion CNY, with the best return of 61.89% and the worst return of -27.88% during his tenure [3] - Gu Hongyuan has a tenure of 4 years and 103 days, managing assets of 484 million CNY, with the best return of 45.26% and the worst return of -23.03% [3] - Guo Xin has a tenure of 1 year and 181 days, managing assets of 1.351 billion CNY, with the best return of 40.89% and the worst return of 0.31% [3]

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]