证券研究报告—公募基金周报 撰写日期：2025 年 09 月 15 日 公募基金周报（20250908-20250912） 投资要点 A 股市场本周延续反弹态势，呈现震荡上行走势。成长风格表现亮眼， 带动 TMT 主题基金同步上行。多数量化指数增强型产品本周超额收益表现 平平。从资金面来看，两市周度日均成交额环比下滑 10.63%，在当前结构 性行情下，若成交量持续萎缩，高位板块的筹码必将松动分化，市场将从单 边上涨转为区间震荡格局，建议关注低位板块的补涨行情。四类股指期货合 约基差表现分化，IM 合约基差大幅贴水，而 IF 合约基差升水幅度较大。 主动权益产品根据本周涨幅排序：深度低估策略中排名前三的分别为 融通行业景气 A（9.13%）、华润元大量化优选 A（7.37%）、华安安进灵活配 置 A（7.01%）；高成长策略中排名前三的分别为东方阿尔法优势产业 A （12.19%）、华夏见龙精选（11.90%）、信澳景气优选 A（10.12%）；高质量 策略中排名前三的分别为汇安成长优选 A（7.64%）、易方达中盘成长 （6.73%）、添富核心精选 LOF（6.54%）；质量低估策略中排名前三的分别为 华安 ...

数据说明： 分机构看，宁银理财、兴银理财、民生理财、杭银理财该期限混合类产品表现较好，近三月净值增长率 均值在3%以上。 产品统计范围为理财公司3个月以内期限的混合类公募理财，统计截止日期为2025年8月14日，统计区间 为近三月。 榜单排名来自理财通AI全自动化实时排名，如您对数据有疑问，请在文末联系助理进一步核实。 | র্ব | 富利兴成阿尔法一个 月持有期2号A | 兴银理财 | 8.88% | 3.27% | 7.25% | | --- | --- | --- | --- | --- | --- | | | | 销售机构:兴业银行 | | | | | 5 | 阳光橙优选配置 | 光大理财 | 7.98% | 1.56% | 4.82% | | | | 销售机构:光大银行 | | | | | 6 | 招智泓瑞多资产FOF 进取目开一号 | 招银理财 | 6.89% | 1.81% | 5.25% | | | | 销售机构:招商银行 | | | | | 7 | 兴睿全明星1号 | 兴银理财 | 6.58% | 1.41% | 6.28% | | | | 销售机构:兴业银行 | | | | | 8 | 银 ...

1）参考量化指数增强的优化框架，在选股的同时针对基准指数控制成分股的投资比例、行业权重偏离、个股权重偏 离； 2）分仓位投资，一部分仓位用于基准指数的投资或尽可能跟住指数，另一部分仓位仍按照原来的主动管理思路。 下面部分中，我们将首先讨论这两种方案的效果，另外最后部分中我们也将参考海外绩优产品的实际偏离情况给予启 发。 1. 《行动方案》强化业绩比较基准的约束作用 5月7日，中国证监会发布《推动公募基金高质量发展行动方案》（以下简称"《行动方案》"），提出了推进公募行业 高质量发展的七大项25项具体举措，其中明确提出强化业绩比较基准的约束作用，基金公司评价体系、公司高管的考 核以及基金经理的考核都将与业绩比较基准密切相关。以基金经理为例："对三年以上产品业绩低于业绩比较基准超过 10个百分点的基金经理，要求其绩效薪酬应当明显下降；对三年以上产品业绩显著超过业绩比较基准的基金经理，可 以合理适度提高其绩效薪酬"。 在此前后明星时代公募基金研究的系列报告中我们也曾经测算，过去10年美国主动权益基金相对其业绩比较基准的年 化跟踪误差多数在3~6%之间，平均水平不足5%，而国内偏股基金过去5年平均跟踪误差接近15%， ...

Core Viewpoint - The rapid growth of index-enhanced funds in the market is driven by the evolution of market conditions and the increasing demand from investors for more sophisticated investment tools, with a total scale exceeding 200 billion yuan by the end of Q1 2025, representing an increase of over 80% since the end of 2020 [1]. Group 1: Definition and Characteristics of Quantitative Index Enhancement - Quantitative index enhancement involves tracking benchmark indices while using quantitative models to optimize stock selection and portfolio management to pursue excess returns (Alpha) [1]. - Unlike traditional index funds that passively replicate constituent stocks, index-enhanced products allow fund managers to adjust holdings within certain constraints to achieve returns that exceed the index [1]. - The average return of index-enhanced funds based on the CSI 300 index was 25.48%, compared to 6.07% for ordinary CSI 300 index funds, indicating the effectiveness of the index enhancement strategy [5]. Group 2: Performance Comparison - Over the past decade, the index-enhanced fund index has shown significant excess returns, with a gain of 24.88% compared to -18.05% for the CSI 300 index and 2.26% for stock index funds [2][3]. - The performance of index-enhanced products is particularly notable during periods of market recovery, as they benefit from both beta returns from the underlying index and alpha returns from active management strategies [7]. Group 3: Mechanisms of Index Enhancement - The enhancement is achieved through two core components: modeling stock returns and optimizing the portfolio relative to the benchmark index [8]. - Three primary methods for achieving index enhancement include: 1. Multi-factor stock selection models that assess various factors such as value, momentum, growth, sentiment, and quality to improve stock selection accuracy [10]. 2. AI stock selection techniques that utilize machine learning and deep learning to uncover patterns in historical data and enhance stock selection efficiency [11][12]. 3. Fundamental enhancement strategies that analyze a company's financial health and operational efficiency to identify investment opportunities [13]. Group 4: Key Indicators for Index Enhanced Funds - When selecting index-enhanced funds, important indicators to consider include annualized excess returns, tracking error, information ratio, maximum drawdown, daily and monthly win rates, all centered around the core metric of daily excess returns [13].

1. Report Industry Investment Rating There is no information regarding the industry investment rating in the provided content. 2. Core Views of the Report - The "Action Plan" issued by the China Securities Regulatory Commission on May 7, 2025, emphasizes strengthening the binding effect of performance comparison benchmarks. This is to address the weak benchmark awareness in domestic public - offering funds and avoid widespread underperformance [6]. - Two adjustment strategies are proposed for domestic active managers under the constraint of performance comparison benchmarks. The first is to refer to quantitative index enhancement by controlling the proportion of constituent stocks and industry constraints to reduce deviation. The second is to adopt a split - position investment approach, with part of the position for benchmark index investment and the other part for active management [2][8]. - Overseas high - performing active management products still express clear views on individual stocks. They deviate from the benchmark to some extent in industries while maintaining distinct style characteristics [2][36]. 3. Summary by Relevant Catalog 3.1 《行动方案》强化业绩比较基准的约束作用 - The "Action Plan" proposes 25 specific measures in seven major areas to promote the high - quality development of the public - offering fund industry, with a clear emphasis on strengthening the binding effect of performance comparison benchmarks. Fund company evaluation, executive assessment, and fund manager assessment will be closely related to these benchmarks [6]. - In the past 10 years, the average annualized tracking error of US active equity funds relative to their performance comparison benchmarks was mostly between 3 - 6%, with an average of less than 5%. In contrast, the average tracking error of domestic equity - biased funds in the past 5 years was close to 15%, indicating weak benchmark awareness [6]. 3.2 参考量化指数增强：通过成分股比例、行业约束来降低偏离 - A conventional quantitative index enhancement constraint framework includes constraints on the proportion of constituent stocks, individual stock weight deviation, industry weight deviation, style factor deviation, and tracking error deviation. For active managers, the focus is on adjusting the proportion of constituent stocks, industry deviation, and individual stock deviation [10][11]. - Taking the CSI 300 as an example, when the investment proportion of constituent stocks is 80%, the portfolio is likely to outperform the index within three years at any time point, and industry deviation has little impact. When the proportion drops to 50%, it is recommended that the industry deviation be within 3%. If it further drops to 30%, the probability of underperforming the index by more than 10% within three years increases significantly [2][14][19]. 3.3 跟踪与主动管理并重：用多大仓位主动管理更合适？ - An approach of split - position investment is considered, with part of the position for benchmark index investment (using the top 50 constituent stocks for sampling replication) and the other part for active management. The Shenwan Hongyuan Active Equity High - Position Fund Index is used to represent the average performance of the market's active funds [24]. - When the investment performance of active fund managers is at the market average level, to avoid underperforming the price index by more than 10% within three years, the index investment position should not be less than 20%. To ensure not underperforming the index, a 50% replication position is recommended. For managers in the top 30% of performance, they can have more active management space [29][30]. - For funds with obvious style and industry biases, such as advanced manufacturing funds, at least 50% of the position should be invested in the index replication portfolio to avoid underperforming by 10% within three years [35]. 3.4 海外经验参考：绩优主动管理产品在个股上仍有明确观点 - US high - performing active equity products in different styles (large - cap core, large - cap growth, large - cap value) still maintain distinct active management characteristics. They deviate from the benchmark in industries while keeping clear style features and express clear views on individual stocks, with individual stock deviations generally reaching 3% [36][56]. - For example, Fidelity Contrafund has significant over - allocation in communication services and finance and under - allocation in technology and consumption. It over - allocates Meta by more than 10% and Berkshire by more than 8% [42].

Core Viewpoint - The rapid growth of index-enhanced funds in the market is driven by the evolution of market conditions and the increasing demand from investors for more sophisticated investment tools [1] Group 1: Market Overview - As of the end of Q1 2025, there are 327 index-enhanced funds with a total scale exceeding 200 billion yuan, representing an increase of over 80% since the end of 2020 [1] - The demand for index-enhanced strategies is rising due to the maturation of investors and the deepening of capital markets [1] Group 2: Definition and Strategy - Quantitative index enhancement involves tracking benchmark indices while optimizing stock selection through quantitative models to pursue excess returns (Alpha) [2] - Index-enhanced funds combine passive tracking of indices with active management strategies, such as multi-factor models and AI stock selection, to achieve superior performance [3][4] Group 3: Performance Comparison - Over the past decade, index-enhanced funds have demonstrated significant excess returns, with the Wind index-enhanced fund index achieving a 24.88% increase, while the CSI 300 index and stock index funds saw returns of -18.05% and 2.26%, respectively [3][4] - As of May 12, 2025, the average return of CSI 300 index-enhanced funds is 25.48%, compared to 6.07% for regular CSI 300 index funds, indicating the effectiveness of the index enhancement strategy [7] Group 4: Mechanisms of Enhancement - Quantitative index enhancement typically involves two core components: modeling stock returns and optimizing the portfolio relative to the benchmark index [9] - The three main methods for achieving index enhancement include: 1. Multi-factor stock selection models that assess various factors such as value, momentum, and quality [10] 2. AI stock selection techniques that utilize machine learning and deep learning to identify patterns in historical data [11] 3. Fundamental enhancement strategies that analyze a company's financial health to optimize the investment portfolio [12] Group 5: Key Indicators for Selection - When selecting index-enhanced funds, important indicators to consider include annualized excess returns, tracking error, information ratio, maximum drawdown, and win rates [13]