Many academics and practitioners rely on standard, relatively basic methods to estimate and manage portfolio risk. This can affect an investment manager’s ability to accurately target lower volatility stocks designed to exploit the well-documented low-risk anomaly. This article finds a hybrid risk estimate that mixes short-, medium-, and long-term variances leads to superior ex post information ratios and alphas by properly aligning securities in the correct order (low risk to high risk). This risk estimate may be worth between $420 million and $1.9 billion annually, calculated from the overall size ($75 billion) of the market. The significance of this estimate survives transaction costs, various time periods, and risk factor exposures. TOPICS: Factors, risk premia, factor-based models, passive strategies, portfolio construction, risk management Key Findings • We propose an alternative way to built portfolios designed to exploit the low-risk anomaly. • The alpha due to this alternative method alone is anywhere from $420 million to $1.9 billion annually, given the current size ($75 billion) of this market. • The significance of this approach survives transaction costs, various time periods, and risk factor exposures.

中文翻译：

---

低风险异常：一个好的风险估计值多少钱？

许多学者和从业人员依靠标准的相对基本的方法来评估和管理投资组合风险。这可能会影响投资经理准确瞄准旨在利用有据可查的低风险异常现象的较低波动性股票的能力。本文发现了一种混合风险估计，该风险混合了短期，中期和长期方差，可以通过按正确的顺序正确排列证券（从低风险到高风险）来获得更高的事后信息比率和Alpha。根据市场的整体规模（750亿美元）计算，该风险估计每年可能价值4.2亿美元至19亿美元。此估计的意义在于交易成本，各个时间段和风险因素敞口。主题：因素，风险溢价，基于因素的模型，被动策略，投资组合构建，风险管理主要发现•我们提出了另一种方法来构建旨在利用低风险异常现象的投资组合。•考虑到该市场的当前规模（750亿美元），仅由于这种替代方法而产生的阿尔法（Alpha）每年约为4.2亿美元至19亿美元。•这种方法的重要性在于可以承受交易成本，各种时间段和风险因素的影响。