- The report does not contain any quantitative models or factors for analysis[1][2][3]

专题：2026年度投资策略|顶级基金公司、基金经理展望马年投资机会 2026年即将到来，如何前瞻布局明年行情？12月26日，方正富邦基金2026年投资策略会在北京举行，本 次策略会以"变局创新"为主题，多位投资大咖及嘉宾发表主旨演讲，共同探讨"十五五"开局之年的投资 机遇和挑战。>>视频直播 会上，方正富邦基金数量投资部行政负责人吴昊发表观点，中国经济坚定迈向高质量发展，科技金融生 态持续优化，资本正加速涌向人工智能、半导体等代表"新质生产力"的核心领域；另一方面，以AI为代 表的技术浪潮也在深刻重塑量化投资的研究范式与决策体系。 在主动+量化的视角下，吴昊在直播中对2026年的投资机会进行了展望。他认为，宏观面整体中性的基 础上，量化模型需要具备主题识别和基本面量化的能力，以适应市场的核心脉络，并对风险进行更好的 控制。在行业配置层面，融合主动研究视角，结合产业/政策趋势等判断，科技成长仍然是中长期市场 主线，当前的AI产业链，类似2014年初创业板、2018年初食品饮料、2021年初新能源，产业趋势大波 段但中小波段有波折；AI产业链投资逻辑将从基础设施建设（训练侧）向端侧应用（推理侧）扩散。 重点关注算 ...

Core Viewpoint - The explosive growth of AI has significantly boosted the popularity of actively managed quantitative funds, which have shown the ability to outperform the market while reducing volatility risk [2][3]. Group 1: Market Trends - The total share of actively managed quantitative funds reached 80.5 billion units by the end of Q3 2025, marking a 27% increase from the previous year [2]. - Institutional investors hold 46.5 billion units of these funds, accounting for over 70% of the total shares [3]. Group 2: Fund Performance - The "Huaan Event-Driven Quantitative Strategy A" fund has outperformed the CSI 300 index for six consecutive years, with a significant lead in 2025 [6]. - In 2025, the fund achieved a return of 35.77%, compared to 14.04% for its benchmark and 17.20% for the CSI 300 [8]. - The fund's risk-return profile is strong, with annualized returns of 33.02% and a maximum drawdown of -9.96%, outperforming peers in all six key metrics [10]. Group 3: Fund Management - The success of the "Huaan Event-Driven" fund is attributed to its manager, Zhang Xu, who employs a multi-faceted strategy that includes industry rotation and event-driven factors [13][18]. - The "Guojin Quantitative Multi-Factor A" fund, managed by Ma Fang, has also shown resilience, achieving positive returns in 2022 and 2023 despite market downturns [26][29]. Group 4: Investment Strategies - Actively managed quantitative funds are increasingly favored for their ability to adapt to market conditions, utilizing diverse strategies to capture excess returns [18][29]. - The focus on risk-adjusted returns and the ability to navigate different market environments are key factors driving institutional interest in these funds [22][23].

Core Insights - The report highlights that during the week of November 17-21, 2025, public quantitative funds showed resilience with positive excess returns across various indices, particularly the CSI 500 index which had an average excess return of 0.35% and a 80.82% positive return rate among funds [1][2][3] - For the month of November 2025, the average excess return for the CSI 500 index was 0.77%, with 81.69% of funds achieving positive returns, indicating a strong performance in the quantitative fund sector [2][3] - Year-to-date performance as of November 21, 2025, shows that the CSI 1000 index had the highest average excess return of 6.69%, with 89.13% of funds generating positive returns, suggesting a favorable environment for this index [3] Group 1: Weekly Performance Statistics - The average excess return for the public quantitative funds tracking the CSI 300 index was 0.22% for the week, with 72.00% of funds achieving positive returns [1] - The average excess return for the public quantitative funds tracking the CSI A500 index was 0.20%, with 70.31% of funds achieving positive returns [1] - The average return for public actively managed quantitative funds was -4.65%, with only 0.49% of funds generating positive returns, indicating challenges in this segment [1] Group 2: Monthly Performance Statistics - For November 2025, the average excess return for the public quantitative funds tracking the CSI 300 index was 0.15%, with 66.22% of funds achieving positive returns [2] - The average excess return for the public quantitative funds tracking the CSI A500 index was 0.19%, with 64.91% of funds achieving positive returns [2] - The average return for public actively managed quantitative funds was -4.49%, with only 4.96% of funds generating positive returns, reflecting ongoing difficulties in this area [2] Group 3: Year-to-Date Performance Statistics - Year-to-date as of November 21, 2025, the average excess return for the public quantitative funds tracking the CSI 300 index was -0.75%, with only 34.43% of funds achieving positive returns [3] - The public quantitative funds tracking the CSI A500 index had an average excess return of 1.18%, with 75.00% of funds achieving positive returns, indicating a strong performance relative to other indices [3] - The public actively managed quantitative funds had an impressive average return of 22.14%, with 97.80% of funds generating positive returns, showcasing the effectiveness of active management strategies in the current market [3]

Group 1 - The issuance and scale of public quantitative funds have reached historical highs, with the number of funds established exceeding last year's total and the fundraising scale also setting new records [1][3]. - As of October 29, 2025, a total of 158 public quantitative strategy funds have been established this year, representing an increase of over 66% compared to last year's 95 funds, marking a record high for annual fund establishment [3]. - The total fundraising scale for quantitative strategy funds this year is 83.064 billion yuan, surpassing any previous year and showing a growth of 125% compared to last year's 36.855 billion yuan [3]. Group 2 - The average issuance scale of quantitative strategy funds this year is 5.26 million yuan, with 21 funds raising over 1 billion yuan, of which 19 are enhanced index funds, accounting for 90% [3]. - The first enhanced index fund was established over 20 years ago, and the public quantitative strategy fund sector has now grown to over 700 funds with a total scale exceeding 380 billion yuan [3]. Group 3 - Public quantitative strategy funds have shown impressive performance this year, with an average net value growth rate exceeding 28%, and 70 funds achieving net value increases of over 50% [5]. - The top-performing funds include Hui'an Growth Preferred, with a return close to 150%, and others like Hongli Performance Growth and Zheshang Huijin Quantitative Selection, both exceeding 80% returns [5]. - The current landscape of quantitative strategy products includes various types of index enhancement, active quantitative stock selection, and long-short strategies, indicating significant development potential in the sector [5].

- The report tracks the weekly performance of quantitative funds, showing that the average excess return of CSI 500 index-enhanced funds was 0.79%, with 94.37% of funds achieving positive excess returns during the week[1][9] - Monthly performance data indicates that CSI 500 index-enhanced funds achieved an average excess return of 1.26%, with 92.96% of funds recording positive excess returns as of October 17, 2025[2][9] - Year-to-date performance reveals that CSI 1000 index-enhanced funds delivered an average excess return of 7.11%, with 89.13% of funds achieving positive excess returns[3][9] - The report includes scatter plots illustrating the absolute and excess performance of quantitative funds over the past year, highlighting the distribution of returns across different fund categories[13][19][15] - The cumulative net value trends of various index-enhanced fund portfolios are presented, showing the performance of CSI 300, CSI 500, CSI 1000, and A500 index-enhanced funds over the year[20][21][22]

- The report does not contain any specific quantitative models or factors, nor does it provide details on their construction, evaluation, or testing results. The content primarily focuses on the performance statistics of various quantitative funds, such as index-enhanced funds, active quantitative funds, and market-neutral funds, across different time periods [1][2][3] - The performance metrics include excess returns, tracking errors, and maximum drawdowns for funds tracking indices like CSI 300, CSI 500, CSI 1000, and CSI A500, as well as active quantitative and market-neutral strategies. These metrics are presented in tabular and graphical formats, segmented by weekly, monthly, and yearly periods [10][11][13] - The report also provides cumulative net value trends for equal-weighted portfolios of quantitative funds over the past year and two years, segmented by fund type (e.g., index-enhanced, active quantitative, market-neutral) [22][28][32]

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 Viewpoint - The article highlights the robust growth of index investment in the current favorable market environment, with public funds accelerating their focus on index and index-enhanced strategies to seize passive investment opportunities and establish market presence [1] Group 1: Market Trends and Strategies - The market's increasing efficiency is leading to a challenge in achieving Alpha returns, which the company acknowledges while emphasizing the importance of risk control [2] - The company plans to enhance returns through three strategies: optimizing traditional quantitative methods, incorporating AI strategies, and expanding data dimensions to include unstructured data [2][3] Group 2: Investment Models and Framework - The index-enhanced strategy relies on three core models: a return model focused on Alpha generation, a risk model to control tracking error, and a portfolio optimization model to maximize risk-adjusted returns [3] - The team emphasizes a balanced approach to Alpha and Beta research, enhancing stock selection and sector allocation capabilities across various investment areas [4] Group 3: Product Structure and Offerings - The company is developing a tiered product structure likened to a star map, with "stars" as core products, "planets" as growth engines, and "satellites" for capturing structural opportunities [6] - The core products include major indices like CSI 300 and CSI 500, while growth indices focus on capturing small-cap growth opportunities [6] Group 4: Future Outlook - The company is optimistic about two main directions: low-volatility dividend stocks appealing to risk-averse investors and high-growth assets aligned with China's economic transformation [7]

Core Insights - The article discusses the robust growth of index investment in a favorable market environment, highlighting the accelerated layout of public funds in index and index-enhanced areas, exemplified by Guotou Ruijin Fund's launch of 7 out of 9 new products as index funds and index-enhanced funds this year [1][9] Group 1: Alpha Decay and Risk Control - The manager emphasizes a clear strategy to address the challenge of Alpha decay due to improved market pricing efficiency, accepting the reality of narrowing Alpha while refusing to compromise on risk control [1][2] - The approach includes traditional methods optimization, broadening investment frameworks with AI strategies, and expanding data dimensions to include non-structured data for better investment decision-making [2][3] Group 2: Research Team and Core Competencies - The team boasts a strong research foundation with members from prestigious institutions, half holding PhDs, covering fields like mathematics, statistics, and data science, which supports high-level quantitative research [4] - The research system balances Alpha and Beta studies, enhancing stock selection and industry allocation capabilities across various domains, including index investment and machine learning [4] Group 3: Business Segmentation and Product Strategy - The manager outlines three business segments: index funds for efficient investment, index-enhanced funds for stable excess returns, and active quantitative funds focusing on deep Alpha extraction [5] - A layered product architecture is being developed, resembling a star map with "stars" as core products, "planets" for growth engines, and "satellites" for capturing structural opportunities [6][7] Group 4: Future Outlook - The manager expresses optimism towards two main directions: low-volatility dividend stocks appealing to risk-averse investors and high-growth assets aligned with China's economic transformation and industry upgrades [8]