近期，博道基金量化投资总监杨梦在接受中国证券报记者采访时表示，尽管公募量化行业已取得长足进 步，但未来发展空间依然广阔。无论是因子挖掘、策略迭代，还是人工智能（AI）技术的深化应用， 都蕴藏着巨大潜力。她表示，博道基金量化团队的核心目标并非追求短期爆发力，而是致力于寻找能够 穿越不同市场周期的、可持续的超额收益来源。"均衡"是团队重要的指导思想，通过方法论与因子来源 的均衡配置，力求让投资者获得波动更小的持有体验，帮助投资者真正"拿得住、赚到钱"。 杨梦，经济学硕士。专注量化领域14年，其中4年量化研究、10年量化投资管理经验。现任博道基金量 化投资总监兼量化投资部总经理。 从AI量价到AI全流程的进化之路 博道基金对AI量化的探索起步很早，2017年就开始使用GP算法去挖掘因子，2019年，受彼时私募领域 对AI应用的启发，博道基金量化团队开始研究AI量价因子，这一前瞻性的布局在2020年得以实盘落 地，并为博道基金"指数+"产品在2020年和2021年带来了相对亮眼的业绩。 然而，量化团队并未止步于此。随着AI技术在量化领域的普及，杨梦敏锐地意识到，要想保持领先， 必须进行更深层次的变革。2023年一季度 ...

□本报记者 魏昭宇 2018年8月，博道基金发行了首只公募量化产品——博道启航，标志着其正式进军公募量化领域。截至 2025年11月14日，该产品成立七年多来的累计回报率已超过144%，年化回报率超13%，展现了稳健的 长期盈利能力。在此期间，中国公募量化行业实现了快速发展。数据显示，截至2025年三季度末，公募 量化产品总规模已突破4000亿元。其中，博道基金的量化管理规模约达270亿元，成功跻身行业前三。 近期，博道基金量化投资总监杨梦在接受中国证券报记者采访时表示，尽管公募量化行业已取得长足进 步，但未来发展空间依然广阔。无论是因子挖掘、策略迭代，还是人工智能（AI）技术的深化应用， 都蕴藏着巨大潜力。她表示，博道基金量化团队的核心目标并非追求短期爆发力，而是致力于寻找能够 穿越不同市场周期的、可持续的超额收益来源。"均衡"是团队重要的指导思想，通过方法论与因子来源 的均衡配置，力求让投资者获得波动更小的持有体验，帮助投资者真正"拿得住、赚到钱"。 从AI量价到AI全流程的进化之路 博道基金对AI量化的探索起步很早，2017年就开始使用GP算法去挖掘因子，2019年，受彼时私募领域 对AI应用的启发，博 ...

然而，量化团队并未止步于此。随着AI技术在量化领域的普及，杨梦敏锐地意识到，要想保持领先， 必须进行更深层次的变革。2023年一季度，基于过往多年的积累，博道基金量化团队决定将原有的AI 量价框架，拓展升级为"AI全流程投资框架"。杨梦告诉中国证券报记者，这意味着，团队从此进入 了"传统框架多因子模型"与"AI框架多因子模型"双轮驱动、并行实盘的新阶段。 不同于现在公募领域广泛使用AI的场景，比如仅仅在某个环节使用AI，AI全流程框架是从原始数据输 入开始，经过特征工程处理后，直接交由复杂的神经网络模型进行端到端的学习和预测，统一训练，并 直接输出最终的预测结果。 AI方法论绝对拓宽了量化投资的边界，并且使得不同团队之间的策略差异性显著增强。"我自己觉得还 是有很大的挖掘空间，迭代永无止境。"她透露，团队在AI模型上已经进行了数以千计的尝试，实盘应 用的子策略模型有十几套，待探索的清单越测越多。 值得一提的是，这种持续进化、迅速落地实盘的能力，根植于博道基金量化团队独特的人才培养和投研 模式。杨梦介绍，博道基金量化团队实行"分工协作、投研一体化"的模式，每位成员都有主攻的研究方 向，达标的研究成果会上线成为参 ...

博道基金杨梦： 打造公募量化"指数+" 特色矩阵 ◎记者 聂林浩 指数化投资大浪潮下，公募量化赛道逐步获得市场青睐，一些中小型公募基金公司则凭借先发优势在量 化管理规模上"弯道超车"。数据显示，截至三季度末，博道基金主动量化管理规模超270亿元，在这一 领域的行业排名跃居前三。 事实上，早在2013年，还是私募形态的博道已开启量化实盘，其量化投资的发展历程与国内量化行业的 成熟过程高度契合。如今是博道基金量化投资总监的杨梦，2011年从浙江大学毕业后即进入公募体系从 事量化研究，早期便因对编程与数理的兴趣而建立起模型化思维，这段经历为她后来主导博道量化体系 建设打下基础。 "我热爱这份工作，投身于市场和量化投研，每次攻克难题和模型迭代，对我来说都充满乐趣。"杨梦 说。 传统多因子与AI全流程"双框架并行" 杨梦于2014年加入博道投资，当年12月，银行、券商等市场权重股集体大涨，这被视作中国量化史上首 次大级别"黑天鹅"。彼时，一些量化策略依靠小市值暴露获取超额收益，在极端行情中遭遇巨大压力。 而博道量化在早期即采用基于Barra风险模型的多因子组合体系，风险暴露更为均衡，其核心的市场中 性产品经受住考验，并 ...

Core Viewpoint - The article discusses the recent performance and strategy shifts of small-cap investment strategies, particularly focusing on the招商量化精选 fund and its manager, Wang Ping, who has expressed caution regarding small-cap investments in the second quarter report [3][9]. Group 1: Fund Performance Analysis - The招商量化精选 fund's holdings in沪深300 increased from 2.48% in mid-2024 to 10.85% in mid-2025, indicating a significant shift towards larger market cap stocks [5][6]. - Conversely, the allocation to "other" small-cap stocks, which are smaller than中证2000, decreased from 16.24% to 10.37% during the same period [5][6]. - The fund's performance has been relatively strong compared to国证2000, especially during periods when国证2000 showed weakness [10]. Group 2: Investment Strategy Insights - Wang Ping mentioned that the招商量化精选 fund employs a PB-ROE strategy, which does not specifically target small-cap stocks, but the selection process tends to favor them [7][8]. - The article raises questions about whether the observed market cap shift is a result of active selection or a consequence of the underlying model used by the fund [7][8]. Group 3: Comparison with Other Funds - The博道远航 fund, managed by Yang Meng, shows a significant downshift in market cap distribution, but its performance is closely tied to the万得偏股混合型基金指数 [12][14]. - The国泰君安量化选股 fund has shifted its holdings from large-cap to small-cap stocks, particularly中证2000, achieving a 31.30% return in the first eight months of the year [15]. - The华夏智胜先锋 fund maintains a focus on中证1000 and below, with a notable increase in small-cap allocations [19][21].

Group 1 - The report identifies six main categories of public quantitative products, totaling 919 products with a combined scale of 386.87 billion yuan, with the largest categories being index enhancement, active quantitative, and absolute return funds [4][10][11] - Active quantitative funds have shown a higher correlation with quality, growth, and small-cap factors in 2020, shifting to a stronger correlation with small-cap factors after 2022 [4][22] - The report outlines four main strategies for active quantitative funds, including equity fund enhancement, SmartBeta style strategies, industry rotation/all-industry quantitative stock selection strategies, and quantitative strategies from active equity teams [4][12][17] Group 2 - The report details the distribution of public quantitative products by strategy, highlighting that index enhancement funds account for 374 products with a scale of 194.32 billion yuan, while active quantitative funds consist of 343 products totaling 91.39 billion yuan [10][11] - The active quantitative fund strategies include equity fund enhancement represented by products like Baodao Qihang and Baodao Yuhang, SmartBeta strategies focusing on small-cap and dividend strategies, and industry rotation products like Huashan Event-Driven Quantitative Strategy [4][12][17] - The report emphasizes the differences in active quantitative product layouts among various fund companies, with specific companies focusing on different strategies such as full-industry quantitative stock selection or style funds [13][14] Group 3 - The report lists the top 20 active quantitative products by scale, with notable products including Zhao Shang Quantitative Selection A and Guojin Quantitative Multi-Factor A, highlighting their respective strategies and performance metrics [15][24] - It notes that many of the top-performing active quantitative products in 2025 have a tendency to invest in small-cap stocks, indicating a market trend towards smaller market capitalization [25][26] - The report also discusses the environmental adaptability of different strategies within active quantitative funds, indicating varying performance based on market conditions [26]

Quantitative Models and Construction Methods 1. Model Name: 博道远航 (Bodao Yuanhang) - **Model Construction Idea**: The product employs an enhanced model based on the average performance index of偏股混合型基金 (partial equity hybrid funds). The fund manager uses quantitative methods to replicate the underlying stock holdings of the 885001 index and then enhances it further [43][43]. - **Model Construction Process**: - The model first replicates the stock holdings of the 885001 index using quantitative techniques. - Enhancements are applied to the replicated portfolio to achieve superior performance while maintaining a controlled deviation from the benchmark [43][43]. - **Model Evaluation**: The model demonstrates significant and stable excess returns over the 885001 index, with a high information ratio and low relative drawdowns [43][43]. 2. Model Name: 兴业聚利 (Xingye Juli) - **Model Construction Idea**: The product adopts a "process-to-result management" approach, setting偏股基准 (partial equity benchmark) and enhancing it while keeping deviations under control [57][57]. - **Model Construction Process**: - The benchmark is first established based on the偏股基准. - Enhancements are applied to the benchmark portfolio, with a focus on maintaining a relatively low deviation and incorporating moderate timing strategies [57][57]. - **Model Evaluation**: The model achieves stable excess returns over the 885001 index, though its lower average position results in occasional underperformance during strong market uptrends [57][57]. 3. Model Name: 信澳宁隽智选 (Xinao Ningjun Zhixuan) - **Model Construction Idea**: This product belongs to the "Index Plus" series, aiming to achieve higher excess returns with relatively loose deviation constraints. It targets the 885001 index as its benchmark [70][70]. - **Model Construction Process**: - The model allows for a certain degree of deviation from the benchmark to capture higher excess returns. - It incorporates港股 (Hong Kong stocks) allocation, which is particularly relevant in the current environment where active equity funds are increasing their exposure to Hong Kong stocks [70][70]. - **Model Evaluation**: The model demonstrates high and stable excess returns over the 885001 index, though it experiences relatively higher maximum relative drawdowns during sharp market uptrends [70][70]. --- Model Backtesting Results 1. 博道远航 (Bodao Yuanhang) - **Excess Return**: 12.65% over the 885001 index [43][43] - **Information Ratio (IR)**: 1.46 [43][43] - **Maximum Relative Drawdown**: -3.41% [43][43] 2. 兴业聚利 (Xingye Juli) - **Excess Return**: 9.24% over the 885001 index [57][57] - **Information Ratio (IR)**: 0.95 [57][57] - **Maximum Relative Drawdown**: -4.84% [57][57] 3. 信澳宁隽智选 (Xinao Ningjun Zhixuan) - **Excess Return**: 11.26% over the 885001 index [70][70] - **Information Ratio (IR)**: 1.07 [70][70] - **Maximum Relative Drawdown**: -7.29% [70][70]