A Multi-Factor Strategy for Index Alpha Enhancement

Q4 Economics, Econometrics and Finance Journal of Index Investing Pub Date : 2019-03-31 DOI:10.3905/jii.2019.9.4.067
Roy. Henriksson, J. Livnat, P. Pfeifer, M. Stumpp
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引用次数: 1

Abstract

Empirical studies suggest that the so-called “low volatility anomaly” is actually an artifact of skewness preferences—a tendency of investors to prefer stocks offering upside potential with low likelihood of loss. The authors argue that if skewness preferences underlie the low volatility anomaly, then a naïve low volatility strategy should be dominated by one that explicitly targets expected return skew. This article provides empirical evidence to that effect. It recommends a multi-factor alpha strategy that is based on avoiding index constituents that are perceived to have ex ante high relative skew. These findings have important implications for investors. Specifically, the authors demonstrate that portfolios constructed to avoid high expected skew stocks outperform both low volatility strategies and several widely used US and global capitalization-weighted indices.
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指数Alpha增强的多因素策略
实证研究表明,所谓的“低波动异常”实际上是偏态偏好的产物——投资者倾向于选择具有上行潜力且亏损可能性较低的股票。作者认为,如果偏态偏好是低波动性异常的基础,那么天真的低波动性策略应该由明确针对预期回报偏态的策略主导。这篇文章提供了这方面的经验证据。它建议采用多因素阿尔法策略,该策略基于避免被认为具有事前高相对偏斜的指数成分。这些发现对投资者具有重要意义。具体而言,作者证明,为避免高预期偏斜股票而构建的投资组合表现优于低波动性策略和几个广泛使用的美国和全球资本化加权指数。
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来源期刊
Journal of Index Investing
Journal of Index Investing Economics, Econometrics and Finance-Finance
CiteScore
0.70
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