量化与主观百亿私募的"分化"仍在继续。 私募排排网最新数据显示，截至2025年7月底，百亿私募总数维持90家不变。其中，量化机构净增2家至 44家，创历史新高，而主观私募则净减2家至39家。 值得注意的是，随着量化私募的超额业绩持续亮眼，资金正在加速流向量化阵营，百亿私募的版图也在 悄然重塑。 此外，百亿私募也交出了一份亮眼的成绩单。截至2025年7月底，纳入统计的55家百亿私募平均收益达 16.60%，量化私募再度跑赢主观机构，不仅实现"全员盈利"，且32家量化私募收益超10%。 百亿量化军团再扩容 百亿私募不仅是规模标杆，更是行业的风向标。 私募排排网数据显示，截至2025年7月底，百亿私募总数为90家，环比持平。但从结构来看，量化与主 观策略呈现明显分化：量化百亿私募增加至44家，占比达49%，净增2家；主观百亿私募降至39家，占 比缩至43%，净减少2家。 一位行业人士指出："不少主观私募，过去靠一波行情可能迅速冲到百亿，但在缺乏明确主线、指数震 荡的阶段，选股型策略的容错空间变小，很容易因一两轮判断失误导致规模滑落。" 当前，随着量化策略加速进化，资金话语权也在悄然转移。不过，从过往来看，若市场持续 ...

Group 1 - The hedge fund industry had a strong start in the first half of 2025, with portfolio managers successfully navigating market volatility to achieve stable returns [2] - The average return for hedge funds in the first half of 2025 was 5.1%, which is still lower than the nearly 9% return of a 60/40 investment portfolio [3] - Long-term annualized returns for hedge funds since 2020 reached 9.4%, outperforming the 6.5% return of a 60/40 portfolio [4] Group 2 - Quantitative strategies outperformed in the first half of the year, with significant inflows of capital, while stock long/short strategies benefited from market rebounds in recent months [5][6] - CTA and systematic macro strategies performed poorly, with the average return being negative, highlighting the challenges faced by trend-following strategies in a volatile market [7][8] Group 3 - There was a notable increase in interest from investors to increase their exposure to hedge funds, with a net inflow equivalent to 1.3% of assets under management in the first half of 2025 [9][24] - The demand for active long-term stock investment strategies has risen, while interest in passive long-term strategies has decreased significantly [18][19] Group 4 - The biotechnology sector faced significant challenges, with a drastic decline in investor demand and performance, marking it as the worst-performing sector in the first half of the year [14][15] - The healthcare and biotechnology industries are experiencing a period of turmoil, influenced by regulatory changes and market dynamics, leading to a substantial drop in investor interest [15][16] Group 5 - The TMT sub-industry performed well within stock long/short strategies, achieving an average return of 7.0% in the first half of 2025, driven by the ongoing AI boom [22][23] - Investors are increasingly cautious about geopolitical tensions and their impact on market stability, leading to a preference for traditional macro strategies that can hedge against market risks [12]

Core Insights - The forum highlighted the innovative development opportunities for FOF and quantitative investment in the AI era, emphasizing the importance of AI in enhancing investment strategies and research frameworks [1][4][5] Group 1: FOF Investment Landscape - The private equity industry is experiencing a survival of the fittest, with a positive overall profit effect, maintaining a scale of over 5 trillion yuan, and expected to return to 6 trillion yuan by year-end [1] - High-net-worth clients are showing lower risk tolerance and a greater focus on return certainty, presenting challenges for FOF in selecting underlying assets [4] - The FOF industry is still in the process of developing a mature investment methodology, indicating a need for a specialized investment framework [4][5] Group 2: AI and Quantitative Investment - AI is expected to play an increasingly important role in financial technology, potentially becoming a competitive advantage for many FOF institutions, while human roles in investment research remain irreplaceable [1][4] - The application of AI in fundamental research can enhance the certainty of future company performance by combining financial data with text analysis [2] - The quant investment sector is characterized by intense competition, requiring initial investments to attract talent and achieve technological accumulation and strategy iteration [1][8] Group 3: Market Dynamics and Strategy - The current A-share market shows significant small-cap effects, with increased volatility providing ample alpha extraction opportunities for quantitative models [8] - The expansion of the quantitative industry must be balanced with market trading volume and activity to avoid compressing excess return potential [8][9] - Addressing the "black box" issue in AI involves improving computational power to identify more factors and understanding the underlying reasons for model trading decisions [9]

Core Viewpoint - The quantitative investment industry is facing a talent shortage and a potential crisis as AI technology increasingly replaces the roles of quantitative researchers [3][9][27]. Group 1: Talent Shortage and Recruitment - The current quantitative investment industry is experiencing a shortage of composite talents who possess skills in data engineering, high-performance computing, and quantitative strategy development [3][17]. - There is a significant disparity in the talent market, where top-tier quantitative talents are in high demand, leading to competitive salaries and benefits offered by firms [7][16]. - Many quantitative private equity firms are actively recruiting senior quantitative researchers, indicating a fierce competition for talent [4][6][12]. Group 2: Impact of AI on Quantitative Research - AI is revolutionizing the development of quantitative strategies, reducing the need for human involvement in certain tasks [8][20]. - The integration of AI technologies allows for more efficient strategy development and testing, enabling quantitative researchers to focus on creating new strategies [21][22]. - Despite the benefits of AI, many quantitative researchers express concerns about job security as AI continues to demonstrate its capabilities in generating successful trading strategies [24][25]. Group 3: Performance Metrics and Market Trends - As of mid-2023, 51 private equity firms reported an average return of 10.87%, with quantitative private equity firms outperforming traditional strategies [13]. - Quantitative long strategies achieved an average return of 15.42%, surpassing the average return of 10% for traditional stock strategies [14]. - The performance of AI-generated strategies in real trading scenarios has been noted to exceed that of strategies developed by human researchers, raising concerns about the future role of quantitative researchers [24].

Core Viewpoint - The private equity stock strategy has achieved a return of 10% in the first half of the year, with quantitative strategies significantly outperforming subjective long strategies [1][2]. Summary by Sections Overall Performance - As of June 30, 2023, the average return of 10,041 private equity securities products was 8.32%, with over 80% achieving positive returns [3]. - Among various strategies, stock strategies led with an average return of 10%, followed by multi-asset strategies at 7.28%, and combination funds, bond strategies, and futures/derivatives strategies at 6.05%, 3.83%, and 3.82% respectively [3]. Quantitative vs. Subjective Strategies - Quantitative long strategies showed a remarkable return of 15.42%, while subjective long strategies had a return of 9.23% [9]. - In the first half of the year, 93.32% of quantitative long strategy products achieved positive returns, compared to less than 80% for subjective long strategies [9]. - The strong performance of quantitative strategies is attributed to their focus on small-cap stocks, which outperformed larger indices [9][10]. Market Conditions and Future Outlook - The market environment has been characterized by high trading volumes and volatility, benefiting quantitative strategies that capitalize on pricing discrepancies in small-cap stocks [9]. - Looking ahead, sectors such as military industry, artificial intelligence hardware and applications, and certain consumer electronics are expected to improve, presenting potential investment opportunities [7].