Group 1 - Zhongyuan Securities experienced a 5.08% increase in stock price, reaching 4.76 CNY per share, with a trading volume of 463 million CNY and a turnover rate of 2.89%, resulting in a total market capitalization of 22.1 billion CNY [1] - The company, established on November 8, 2002, and listed on January 3, 2017, is based in Zhengzhou, Henan Province, and its main business segments include securities brokerage (48.17%), credit business (24.37%), futures business (23.95%), investment management (9.09%), investment banking (2.83%), and overseas business (1.64%) [1] Group 2 - Guojin Fund has a significant holding in Zhongyuan Securities through its fund, Guojin CSI 1000 Index Enhanced A (017846), which reduced its holdings by 1,900 shares in the second quarter, maintaining 484,100 shares, representing 0.63% of the fund's net value, ranking as the tenth largest holding [2] - The fund, established on March 22, 2023, has a current size of 164 million CNY and has achieved a year-to-date return of 35.17%, ranking 865 out of 4,222 in its category, with a one-year return of 81.61%, ranking 689 out of 3,798 [2] Group 3 - The fund manager of Guojin CSI 1000 Index Enhanced A is Li Hongchao, who has been in the position for 50 days, managing total assets of 779 million CNY, with the best fund return during his tenure being 6.39% and the worst being 4.13% [3]

Group 1: Zhaoyi Innovation - Zhaoyi Innovation reported strong growth across various business lines in Q2 2024, with NOR Flash experiencing high single-digit growth, niche DRAM growing over 50%, MCU close to 20%, and sensor chips growing around 10% [1] - The company anticipates a quarter-on-quarter growth in Q3, with overall demand expected to rise, particularly in niche DRAM, which is projected to face supply tightness throughout the year [1] - The overall gross margin is expected to remain stable, with a slight increase in DRAM gross margin and moderate price increases in Flash products [1] - The demand for NOR Flash is driven by an increase in electronic product code volume, while supply constraints are expected to persist due to tight wafer manufacturing capacity [1] - The company is optimistic about customized storage technology, which is expected to gain traction among various industries and clients, leveraging its first-mover advantage and technological iterations [1] - MCU growth is anticipated in industrial control, energy storage, and high-barrier domestic replacement sectors, with new product revenue contributions expected to rise [1] - DDR4 8Gb revenue contribution is projected to reach one-third of DRAM revenue for the year, while LPDDR4 small-capacity products may see their revenue share increase to double digits [1] - The company has significant R&D investments and a large market potential, aiming to achieve revenue scales comparable to standard interface niche storage [1] - The stable niche market and production cuts by leading manufacturers present growth opportunities, with plans to launch the LPDDR5 product line within two years [1] - The automotive MCU market is promising, with the introduction of multi-core products and AI MCU applications for AI scenarios and algorithms [1] - The 45nm NOR Flash capacity is expected to ramp up, contributing 15% to revenue by year-end, with a complete product line expected by 2026 and a significant cost advantage due to a 20% reduction in chip area [1] Group 2: Liangxin Co., Ltd. - Liangxin's data center business is segmented into three main areas: internet enterprises, operators, and standalone projects, with a market share concentrated in HVDC and UPS [2] - The growth rate of the new energy business may slow in the second half of the year, while the company will continue to focus on digital energy and infrastructure sectors [2] - There is a demand for technical upgrades from overseas clients, with existing suppliers facing capacity bottlenecks, and Liangxin has a good collaboration with these overseas clients [2] - The gross margin for overseas business slightly decreased compared to the same period last year [2] - The new energy business unit includes significant shares from solar, energy storage, and wind energy, along with rapidly growing segments such as electric vehicles, charging piles, and box-type substations, as well as layouts in nuclear power and hydrogen energy [2]

Group 1 - The core viewpoint of the news is that Zhimi Intelligent (001339.SZ) has reported its half-year results for 2025, highlighting the institutional investor landscape and changes in shareholding [1] - As of July 30, 2025, a total of 18 institutional investors hold shares in Zhimi Intelligent, with a combined holding of 6.7219 million shares, representing 2.67% of the total share capital [1] - The top ten institutional investors account for 2.60% of the total shares, with a decrease of 0.85 percentage points compared to the previous quarter [1] Group 2 - In the public fund sector, two funds increased their holdings, while two funds decreased their holdings, indicating a slight change in the overall holding proportions [2] - Nine new public funds disclosed their holdings during this period, including notable funds such as Southern CSI 1000 ETF and Huashang Advantage Industry Mixed Fund [2] - One foreign fund, Hong Kong Central Clearing Limited, reduced its holdings by 0.69% compared to the previous quarter [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: Liquidity - **Construction Idea**: Measures the market's preference for high-liquidity assets, reflecting the demand for stocks with higher turnover rates [9][14] - **Construction Process**: - **TO**: Average logarithmic turnover rate over the past 243 trading days - **Liquidity Beta**: Regression of individual stock turnover rates against market turnover rates over the past 243 trading days [14] - **Evaluation**: Demonstrated the highest positive return among style factors in the recent week, indicating a significant increase in demand for high-liquidity assets [9] - **Performance**: Weekly return of 5.44%, monthly return of 13.08%, and annualized return of 33.79% over the past year [11] Factor Name: Volatility - **Construction Idea**: Captures the market's preference for high-volatility stocks, reflecting risk appetite [9][14] - **Construction Process**: - **Stdvol**: Standard deviation of daily returns over the past 243 trading days - **Ivff**: Fama-French 3-factor idiosyncratic volatility over the past 243 trading days - **Range**: Difference between the highest and lowest prices over the past 243 trading days - **MaxRet_6**: Average return of the six highest daily returns over the past 243 trading days - **MinRet_6**: Average return of the six lowest daily returns over the past 243 trading days [14] - **Evaluation**: Showed a significant improvement in weekly performance, reflecting increased market risk appetite [9] - **Performance**: Weekly return of 5.03%, monthly return of 12.37%, and annualized return of 25.55% over the past year [11] Factor Name: Beta - **Construction Idea**: Represents the market's preference for high-beta stocks, indicating sensitivity to market movements [9][14] - **Construction Process**: Bayesian shrinkage of market beta [14] - **Evaluation**: Significant weekly performance improvement, indicating a strong preference for high-beta stocks [9] - **Performance**: Weekly return of 4.28%, monthly return of 12.51%, and annualized return of 33.02% over the past year [11] Factor Name: Growth - **Construction Idea**: Measures the market's preference for growth-oriented stocks, focusing on financial growth metrics [9][14] - **Construction Process**: - **Delta ROE**: Average change in ROE over the past three years - **Sales Growth**: 3-year compound growth rate of TTM sales revenue - **Na Growth**: 3-year compound growth rate of TTM net assets [14] - **Evaluation**: Improved weekly performance, reflecting increased market interest in growth stocks [9] - **Performance**: Weekly return of 1.65%, monthly return of 0.77%, and annualized return of 1.32% over the past year [11] Factor Name: Certainty - **Construction Idea**: Reflects the market's preference for stocks with higher predictability and stability [10][14] - **Construction Process**: - **Instholder Pct**: Proportion of holdings by mutual funds - **Cov**: Analyst coverage adjusted for market capitalization - **Listdays**: Number of days since the stock's listing [14] - **Evaluation**: Experienced a significant decline in weekly performance, indicating reduced confidence in certainty-based strategies [10] - **Performance**: Weekly return of -3.99%, monthly return of -9.10%, and annualized return of -17.07% over the past year [11] Factor Name: Value - **Construction Idea**: Measures the market's preference for undervalued stocks based on valuation metrics [10][14] - **Construction Process**: - **BP**: Book-to-price ratio - **EP**: Earnings yield [14] - **Evaluation**: Significant decline in weekly performance, reflecting reduced market interest in value-based strategies [10] - **Performance**: Weekly return of -4.75%, monthly return of -8.10%, and annualized return of -16.96% over the past year [11] Factor Name: Size - **Construction Idea**: Captures the market's preference for small-cap stocks [10][14] - **Construction Process**: Logarithm of total market capitalization [14] - **Evaluation**: Experienced the largest decline among style factors, indicating reduced market interest in small-cap stocks [10] - **Performance**: Weekly return of -5.96%, monthly return of -12.84%, and annualized return of -54.81% over the past year [11] --- Factor Backtesting Results Weekly Performance - **Liquidity**: 5.44% - **Volatility**: 5.03% - **Beta**: 4.28% - **Growth**: 1.65% - **Certainty**: -3.99% - **Value**: -4.75% - **Size**: -5.96% [11] Monthly Performance - **Liquidity**: 13.08% - **Volatility**: 12.37% - **Beta**: 12.51% - **Growth**: 0.77% - **Certainty**: -9.10% - **Value**: -8.10% - **Size**: -12.84% [11] Annualized Performance (Past Year) - **Liquidity**: 33.79% - **Volatility**: 25.55% - **Beta**: 33.02% - **Growth**: 1.32% - **Certainty**: -17.07% - **Value**: -16.96% - **Size**: -54.81% [11]