量价因子有所回暖，1000 指增强势 2025 年 9 月 28 日│中国内地 量化投资周报 证券研究报告 本月以来换手率因子多空收益领跑 从因子多空组合收益的平均水平来看，本月以来换手率因子多空收益领跑， 在中证 1000 和全 A 股股票池中表现尤为突出；预期净利润增速因子次之， 整体呈现较可观的多空收益。盈利和成长因子同样呈现正向的平均多空收 益，但较前者有较大差距。其余因子均呈现负向的平均多空收益，其中反转、 估值和小市值因子多空收益较为落后。 本月以来中证 1000 指增基金超额收益保持领先 我们重点跟踪以沪深 300、中证 500、中证 1000 和中证 A500 指数为基准 的量化指数增强基金。基于公募指增基金的复权净值曲线表现来看，本月以 来各类指增基金超额收益呈现分化。从中位数层面来看，中证 1000 指增基 金表现保持领先，呈现较明显的正超额；其余指增基金的超额收益中位数均 呈现负值，整体表现平淡。从今年以来的整体表现来看，中证 1000 指增基 金超额领先，中证 A500 指增基金次之。 风险提示：量化基金的业绩受到多种因素影响，包括环境、政策、基金管理 人变化等，过去业绩好的基金不代表 ...

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].