AQR资本管理 · 2026/08/19

学术阿尔法

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完整中文译文

学术阿尔法

构建良好的另类风险溢价（ARP）或风格溢价策略，长期以来以适度的费用提供了正收益且不相关的回报。在 2010 年代，这些策略因其学术基础、分散化特性、透明度和低费用而广受欢迎，但在 2018 至 2020 年的“量化寒冬”期间，该类别面临了挑战。尽管一些投资者对这一概念失去了信心，许多策略随后经历了强劲复苏，我们仍然相信风格溢价可以为投资者组合做出宝贵贡献。

在本文中，我们通过“学术阿尔法”的视角重新审视风格溢价投资的概念和收益——即基于成熟学术研究的回报来源。我们讨论了为什么在所谓的“因子动物园”中识别稳健且可实施的因子需要大量管理人技能，以及实践者如何通过改进信号测量、拓宽资产类别应用、优化组合构建和风险管理来改进和扩展学术理念。

我们还探讨了持续创新——包括新信号和技术、扩展投资范围以及组合实施方面的进步——如何使学术与专有量化策略之间的界限日益模糊。更复杂的学术阿尔法策略可能为投资者提供具有流动性、透明度和不相关回报来源的强力分散工具。

本文档不旨在也不涉及AQR提供的任何特定投资策略或产品。提供本文档仅为协助投资者自行分析和形成对本讨论主题的观点提供框架。

完整英文原文

Well-constructed alternative risk premia (ARP), or style premia, strategies have delivered positive, uncorrelated returns at modest fees over the long run. After gaining popularity in the 2010s for their academic grounding, diversification properties, transparency, and low fees, the category faced a challenging period during the "Quant Winter" of 2018–2020. While some investors lost faith in the concept, many strategies subsequently experienced a strong recovery, and we continue to believe style premia can make a valuable contribution to investor portfolios.

In this paper, we revisit the concept and benefits of style premia investing through the lens of "academic alpha"—sources of return grounded in well-established academic research. We discuss why identifying robust and implementable factors within the so-called "factor zoo" requires substantial manager skill, and how practitioners can improve and expand upon academic ideas through better signal measurement, broader asset-class applications, portfolio construction and risk management.

We also explore how continued innovation—including new signals and techniques, expanded investment universes, and advances in portfolio implementation—is making the boundary between academic and proprietary quantitative strategies increasingly blurred. More sophisticated academic alpha strategies may offer investors a powerful diversifier with liquidity, transparency and a source of uncorrelated returns.

This document is not intended to, and does not relate specifically to any investment strategy or product that AQR offers. It is being provided merely to provide a framework to assist in the implementation of an investor’s own analysis and an investor’s own view on the topic discussed herein.

机构免责声明

This document has been provided to you solely for information purposes and does not constitute an offer or solicitation of an offer or any advice or recommendation to purchase any securities or other financial instruments and may not be construed as such. The factual information set forth herein has been obtained or derived from sources believed by the author and AQR Capital Management, LLC (“AQR”) to be reliable but it is not necessarily all-inclusive and is not guaranteed as to its accuracy and is not to be regarded as a representation or warranty, express or implied, as to the information’s accuracy or completeness, nor should the attached information serve as the basis of any investment decision. This document is not to be reproduced or redistributed to any other person. The information set forth herein has been provided to you as secondary information and should not be the primary source for any investment or allocation decision. Past performance is not a guarantee of future performance. Diversification does not eliminate the risk of experiencing investment losses. This material is not research and should not be treated as research. This paper does not represent valuation judgments with respect to any financial instrument, issuer, security or sector that may be described or referenced herein and does not represent a formal or official view of AQR. The views expressed reflect the current views as of the date hereof and neither the author nor AQR undertakes to advise you of any changes in the views expressed herein. The information contained herein is only as current as of the date indicated, and may be superseded by subsequent market events or for other reasons. Charts and graphs provided herein are for illustrative purposes only. The information in this presentation has been developed internally and/or obtained from sources believed to be reliable; however, neither AQR nor the author guarantees the accuracy, adequacy or completeness of such information. Nothing contained herein constitutes investment, legal, tax or other advice nor is it to be relied on in making an investment or other decision. There can be no assurance that an investment strategy will be successful. Historic market trends are not reliable indicators of actual future market behavior or future performance of any particular investment which may differ materially, and should not be relied upon as such. Diversification does not eliminate the risk of experiencing investment losses. The information in this paper may contain projections or other forward-looking statements regarding future events, targets, forecasts or expectations regarding the strategies described herein, and is only current as of the date indicated. There is no assurance that such events or targets will be achieved, and may be significantly different from that shown here. The information in this document, including statements concerning financial market trends, is based on current market conditions, which will fluctuate and may be superseded by subsequent market events or for other reasons.

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关键论点

精心构建的替代风险溢价策略在长期内以适度费用提供了正、不相关的回报。
在“因子动物园”中识别稳健且可实施的因子需要大量的管理者技能。
从业者可以通过更好的信号测量、更广泛的资产类别应用、投资组合构建和风险管理来改进学术观点。
持续创新正在模糊学术与专有量化策略之间的界限。
复杂的学术alpha策略可能为投资者提供具有流动性、透明度和不相关回报的强大分散工具。

风险

2018-2020年的“量化冬天”对该类别构成挑战，导致部分投资者失去信心。
如果管理不当，因子动物园的复杂性可能导致错误发现。
在某些市场条件下，风格溢价策略可能表现不佳。