Core Viewpoint - The article discusses the rise of active quantitative funds in the A-share market, highlighting their ability to combine the advantages of both active and passive investment strategies, thus providing investors with opportunities for excess returns while maintaining a clear investment style [4][5][20]. Group 1: Active Quantitative Funds - Active quantitative funds have gained attention for their unique approach, which integrates mathematical models and vast data analysis, avoiding emotional trading and ensuring strict adherence to investment discipline [6][7]. - These funds offer a broader investment perspective, allowing for efficient stock selection across a larger pool, thus adapting better to rapid market changes [7][8]. - The article emphasizes the collaborative efforts of teams at Guangfa Fund, which have developed a multi-strategy investment system that combines subjective research with quantitative methods to enhance long-term excess returns [9][10]. Group 2: Guangfa Fund's Quantitative Strategy - Guangfa Fund has established a "multi-asset, multi-strategy, multi-team" framework for its quantitative business, with three core teams focusing on different aspects of quantitative investment [9][10]. - The Quantitative Investment Department, led by Zhao Jie, focuses on pure quantitative strategies, utilizing a factor library of approximately 600 effective factors to drive stable excess returns [10][12]. - The Active Quantitative Team, led by Yang Dong, bridges subjective and quantitative approaches, employing a human-machine collaboration model to capture stock alpha across various styles and industries [10][11]. - The Stable Strategy Department, led by Lin Yingrui, emphasizes risk control and value discovery, integrating active fundamental research with a scientific quantitative framework [11][12]. Group 3: Product Offerings and Performance - Guangfa Fund has launched a series of active quantitative products that cater to diverse investor preferences, focusing on style enhancement, industry themes, and risk management [13][17]. - The Small Cap Enhancement product, managed by Li Yuxin and Yi Wei, has achieved a return of 99.98% over the past year, showcasing a strong risk-return profile [14][16]. - The Growth Style Enhancement product, Guangfa Dongcai Big Data Selected, has delivered a return of 73.61%, leveraging internet big data to capture growth alpha [15][16]. - The Value/Dividend Style Enhancement products, such as Guangfa Stable Strategy and Guangfa High Dividend Preferred, have also shown significant returns, with the former achieving a 45.97% return over the past year [15][16]. Group 4: Future Outlook - The article posits that active quantitative investment will evolve from being a supplementary option in asset management to a primary strategy for navigating complex market trends [20][21]. - The integration of human insights with machine precision is expected to create a more robust investment approach, providing investors with a stable and predictable long-term investment path [21].

Core Insights - The article emphasizes the importance of sustainable dividends and high-quality earnings in dividend investment strategies, particularly in the context of a low-interest-rate environment and market volatility [1][2][3] Group 1: Investment Strategy - The high dividend strategy focuses on selecting stocks with high dividends, low valuations, and strong earnings quality, while also considering future profitability and dividend plans [1][2] - The strategy is built around two dimensions: mature, low-valuation leading companies with stable cash flows and high dividend-paying "small but beautiful" companies with growth potential [2][3] - The average dividend yield of the top ten holdings in the fund managed by the company is reported at 6.08% as of the end of Q2 [2] Group 2: Quantitative Approach - The introduction of quantitative methods enhances the high dividend strategy, utilizing multi-factor models and machine learning for stock selection and risk optimization [4][5] - The company employs a "core + satellite" multi-strategy approach, where the core focuses on high dividends and low valuations, while the satellite includes various defensive strategies to diversify risk [5][6] - Machine learning, particularly neural network strategies, is increasingly integrated into quantitative strategies to improve stock selection metrics [5][6] Group 3: Team and Collaboration - The quantitative investment team has been focused on strategy development since 2011, combining expertise from mathematics, computer science, and financial engineering [6] - The team operates on a collaborative platform where data and strategies are shared, allowing for systematic analysis and optimization of investment strategies [6] - The integration of data-driven decision-making reduces subjective influences and enhances the efficiency of investment operations [6]

Core Viewpoint - The article highlights the strong performance of the GF Quantitative Multi-Factor Mixed Fund (005225), which has achieved a cumulative return of 109.93% since its inception on March 21, 2018, significantly outperforming its benchmark across various time frames [1]. Group 1: Fund Performance - The GF Quantitative Multi-Factor Fund has a high equity position of 91.75%, with a diversified portfolio that includes six stocks with a total market capitalization below 10 billion, accounting for 8.35% of the fund's net asset value [2]. - Over the past year, the GF Quantitative Multi-Factor Fund has outperformed the National Securities 2000 Index by 30 percentage points, achieving a return of 54.33% compared to the index's performance [2]. - The fund's monthly win rate against the National Securities 2000 Index is 81%, with an average monthly excess return of 1.20% since the current fund managers took over [3]. Group 2: Investment Strategy - The fund employs a dual-engine model combining traditional quantitative multi-factor models with advanced machine learning techniques to enhance factor discovery and integration [4][5]. - The fund managers utilize AI tools to identify hidden pricing patterns and improve the efficiency of alpha factor extraction, addressing the limitations of traditional models [5]. Group 3: Other Quantitative Funds - The article also discusses other quantitative funds under GF, such as the GF Multi-Factor Mixed Fund (002943), which has consistently outperformed major indices over the past seven years [6][7]. - GF has a diverse range of quantitative products, including Smart Beta strategies, which focus on small-cap style enhancement [7]. Group 4: Dividend and Value Strategies - The GF Stable Strategy Fund (006780) employs a combination of subjective and quantitative approaches to capture dividend opportunities, achieving a return of 25.93% in 2024, outperforming the benchmark by 7.17% [10]. - The GF High Dividend Preferred Fund (008704) focuses on high-dividend, low-valuation stocks, achieving a year-to-date return of 12.10%, significantly surpassing the performance of the benchmark indices [14][15].

Group 1 - The report identifies six main categories of public quantitative products, totaling 919 products with a combined scale of 386.87 billion yuan, with the largest categories being index enhancement, active quantitative, and absolute return funds [4][10][11] - Active quantitative funds have shown a higher correlation with quality, growth, and small-cap factors in 2020, shifting to a stronger correlation with small-cap factors after 2022 [4][22] - The report outlines four main strategies for active quantitative funds, including equity fund enhancement, SmartBeta style strategies, industry rotation/all-industry quantitative stock selection strategies, and quantitative strategies from active equity teams [4][12][17] Group 2 - The report details the distribution of public quantitative products by strategy, highlighting that index enhancement funds account for 374 products with a scale of 194.32 billion yuan, while active quantitative funds consist of 343 products totaling 91.39 billion yuan [10][11] - The active quantitative fund strategies include equity fund enhancement represented by products like Baodao Qihang and Baodao Yuhang, SmartBeta strategies focusing on small-cap and dividend strategies, and industry rotation products like Huashan Event-Driven Quantitative Strategy [4][12][17] - The report emphasizes the differences in active quantitative product layouts among various fund companies, with specific companies focusing on different strategies such as full-industry quantitative stock selection or style funds [13][14] Group 3 - The report lists the top 20 active quantitative products by scale, with notable products including Zhao Shang Quantitative Selection A and Guojin Quantitative Multi-Factor A, highlighting their respective strategies and performance metrics [15][24] - It notes that many of the top-performing active quantitative products in 2025 have a tendency to invest in small-cap stocks, indicating a market trend towards smaller market capitalization [25][26] - The report also discusses the environmental adaptability of different strategies within active quantitative funds, indicating varying performance based on market conditions [26]