Core Insights - The report investigates the performance of active equity funds, specifically whether they can outperform the broader A-share market, represented by a market capitalization-weighted portfolio of most A-share stocks [11][12] - The analysis reveals that while most active fund portfolios can outperform the market, the excess returns are not statistically significant, with annualized excess returns ranging from 0.216% to 3.05% across various fund sizes [1][2] Fund Performance Analysis - Active funds show a preference for large-cap stocks and high-valuation stocks, with significant positive exposure to high-valuation stocks impacting performance negatively when considering size and value factors [2][3] - Under a three-factor model, all fund portfolios exhibit positive excess returns, ranging from 1.54% to 6.37%, with small and mid-cap funds showing significant excess returns [2][3] - The growth factor demonstrates a high annualized return of 9.91%, with excess returns reaching 10.5% to 12.5%, indicating a strong correlation between short-term earnings growth and future stock returns [3][4] Factor Contributions - The report highlights that aside from the market factor, the value factor has a significant negative contribution, while the growth factor contributes positively to performance [3][4] - In a five-factor model, the market factor contributes between 6.03% and 6.48%, while the value factor contributes negatively between -3.16% and -2.83%, and the growth factor contributes positively between 1.98% and 2.49% [3][4] Fund Composition and Trends - The report notes a structural shift in the composition of active equity funds, with a significant increase in the number of mixed equity funds since 2015, reflecting a change in regulatory requirements [20][21] - The number of active equity funds has grown from 207 at the end of 2008 to 5508 by the end of 2024, with a compound annual growth rate of 22.8% [15][21] - The report also discusses the impact of market conditions on fund performance, noting that the active equity fund's net asset value reached a peak in 2007 and has only recently surpassed that level [22][21]

Core Insights - Quantitative stock investment is expected to perform exceptionally well in 2025 after years of stagnation, driven by models based on factors and machine learning that have shown strong performance amid market volatility and political noise [1][6] Group 1: Strategy Recovery - Traditional long/short factor models and newer machine learning-based strategies are experiencing a revival, with the global bottom-up stock factor strategy rising over 9% this year, successfully navigating market volatility [2][3] - The top-down factor indices covering regions like Europe, the US, and Japan have also shown robust growth, particularly value and momentum strategies outside the US [2] Group 2: Regional and Strategy Performance - Europe has been the leading region for factor performance in 2025, with value strategies achieving the best relative and absolute returns, although valuation gaps have narrowed significantly [3] - Machine learning models from Société Générale have performed strongly, with a newly launched mean-reversion strategy yielding a return of 4.1%, outperforming basic reversal models [3] Group 3: Investment Themes and Strategy Outlook - Société Générale is optimistic about defensive stock income strategies, focusing on companies with strong balance sheets and high dividend yields, particularly in utilities, telecom, and energy sectors [4] - The US small-cap value strategy, excluding distressed stocks, has outperformed benchmark indices, emphasizing the importance of balance sheet strength as credit conditions tighten [4] - The "strong balance sheet" trade is supported as an alternative hedging strategy against high-yield credit risk, maintaining positive growth in 2025 [4] Group 4: Outlook for the Second Half of 2025 - Despite the strong performance of European value strategies, a cautious outlook is held for the second half of 2025 due to rising market volatility and valuation spreads nearing historical norms [5] - The easy gains from European value stocks may be over, influenced by geopolitical uncertainties and increasing earnings risks [5]

吴欣 榜样投资 创始人及CEO 金焰 友山基金 联合 首席投资官 汪大海 彭博大中华区 总裁 Kumar Gautam 彭博行业研究 股票量化策略师 在机遇与挑战并存的背景下， 彭博将分别在上海、深圳、北京、杭州多地举办2025年私募投资策 略闭门交流会系列活动。 行业领袖将与彭博经济学家、彭博行业专家共同讲述对当前市场走势的 洞察与研判，探讨业界普遍面临的挑战与破局之道，并分享科技助力投资决策更加明智的实践经 在市场波动中进行明智的资产配置 因子模型在A股的交易策略及海外延申 2025年彭博私募投资策略 闭门交流会（上海场） 2025年5月22日（星期四） | 15:30 - 18:00 上海 （详细活动地址将在确认函中提供） 2025年第一季度已落下帷幕，我们见证了美国关税政策、地缘政治博弈等因素频频导致全球宏观 格局震荡，引发市场避险情绪。而中国市场凭借经济复苏、融资需求高涨而备受投资者关注，境 内外多元化资产配置机遇显现，吸引多家国际对冲基金在此落子布局。与此同时，人工智能 （AI）等前沿科技的蓬勃发展不仅使科技股表现亮眼、拉动股指上涨，还为量化投研高效赋能， 成为私募机构在不确定性中破局取胜的关键工 ...

点击小程序查看报告原文 本篇报告，我们参考海外文献的研究思路及方法，并结合自身实践经验， 从Alpha的纯粹度、置信度与异质性维度出发，探寻其底层逻辑原理，并依此提 出及检验选股能力Alpha的多种改进思路，力图提升其延续性及收益预测能力。 开具体讨论与分析。简单总结来看，在不同因子模型中纳入不同数目的潜在因子，绝大多数情形下能够提升截面回归的预测效果；同时，多头组合的相对 风险指标及风险调整后收益也得到同步改善，以FF3为例，纳入kl=1/2/3个潜在因子，信息比率将由截面回归的0.84增加至1.02/1.00/1.24。 图表：时序回归 vs 截面回归 vs 潜在因子Alpha的计算原理 图表：选股能力Alpha的提纯与改进思路框架 资料来源：中金公司研究部 传统时序回归Alpha有何特质？ 1） 历史数据来看，不同因子模型得到具备Alpha获取能力的权益基金数量占比并无明显差异，基本于40%-80%区间浮动， 若进而要求p值显著，比例将大幅降低； 2） 相较累积收益指标而言，具备更佳的延续性； 3） 长期来看，以其构建多头组合能够获取超于市场平均水平 的回报，但因其中杂糅其他并不能够真正刻画基金能力的成 ...