The Low-Volatility Anomaly: Market Evidence on Systematic Risk vs. Mispricing

The authors explored whether the well-publicized anomalous returns associated with low-volatility stocks can be attributed to market mispricing or to compensation for higher systematic factor risk. The results of their study, covering a 46-year period, indicate that the relatively high returns of low-volatility portfolios cannot be viewed solely as compensation for systematic factor risk. The results from their cross-sectional analyses indicate that average returns to low-volatility portfolios are determined by common variations associated with the idiosyncratic-volatility characteristic rather than factor loadings. This finding suggests that the excess returns are more likely driven by market mispricing connected with volatility as a stock characteristic.The summary was prepared by Priyank Singhvi, CFA, India.What’s Inside?Low-volatility portfolios, both in the United States and international markets, tend to outperform high-volatility portfolios, which contradicts the CAPM. The authors look at the empirical data for the period of January 1966–December 2011 and find that this outperformance is not related to compensation for some hidden systematic (undiversifiable) risk factor but is likely driven by market mispricing and/or limits to arbitrage.How Is This Research Useful to Practitioners?The outperformance of previously low-return-volatility portfolios relative to previously high-return-volatility portfolios is inconsistent with the conventional theory that higher expected returns compensate for higher risk as predicated by the CAPM. There are two possible explanations for this anomaly: (1) There is some pervasive systematic risk factor directly associated with volatility, or (2) investors prefer high-volatility stocks over low-volatility stocks because of behavioral considerations and/or limitations on arbitraging away any mispricing.The authors’ empirical evidence suggests that market mispricing best characterizes the link between low volatility and future returns and that the low-volatility anomaly cannot be viewed as compensation for some pervasive systematic risk factor.This work adds to the research into the source of abnormal returns across companies and over time, which can enable investors to improve portfolio construction and risk management. Low-volatility strategies have the potential to add diversification to portfolios and lead to higher Sharpe ratios, but those strategies also tend to increase tracking errors relative to index-based benchmarks.How Did the Authors Conduct This Research?The authors investigate whether the low-risk anomaly can be attributed to compensation for higher systematic risk or market mispricing. To carry out this investigation, they rely on the methodologies previously used in research examining other well-known anomalies, such as size, book to market, and momentum. To identify whether the returns on high- and low-volatility stocks can be attributed to factor loadings (systematic risk) or to company characteristics (mispricing), the authors test whether variations in the loading on a factor created on the basis of volatility can explain future stock returns after controlling for actual return variability. In line with previous studies, the authors focus on idiosyncratic volatility (IVOL), which has been shown to be negatively associated with subsequent stock returns. They measure IVOL each month as the standard deviation of the residual returns from the Fama–French three-factor model by regressing the daily returns of individual stocks in excess of the one-month T-bill rate on the returns to the common factors related to size and book to market. To estimate factor loadings (betas) on the IVOL factor, the authors conduct rolling regressions of monthly excess stock returns on the three Fama–French factors plus the IVOL factor over the previous 36 months. They obtain IVOL factor loadings for 552 months for the period of January 1966–December 2011. The authors separate low-IVOL stocks with high and low loadings on the IVOL factor. If the systematic risk explanation is correct, a low-IVOL stock with a low-IVOL factor loading should have a low average return. In contrast, if the characteristics, rather than factor loadings, determine prices, a low-IVOL stock should have a high return regardless of its loading on the IVOL factor. Because the results show that loadings on the IVOL factor cannot explain cross-sectional stock returns, the authors conclude that the low-volatility anomaly is inconsistent with the systematic risk explanation but consistent with market mispricing.The results indicate that the IVOL characteristic can predict subsequent stock returns at the 1% significance level with the inclusion of control variables. The IVOL effect was very strong from 1966 to 1989, but it disappeared after 1990. Thus, there is no evidence to support the view that the IVOL effect will continue to explain stock returns.Abstractor’s ViewpointThe low-volatility anomaly is often considered one of the greatest anomalies of the CAPM, which is part of the foundation of modern portfolio theory. The anomaly was first pointed out by Haugen and Heins in the early 1970s (working paper 1972), and since then, it has been an area of interest for both academics and practitioners. This work provides additional support to the conjecture that the market mispricing related to the low-risk anomaly may be related to behavioral considerations and/or to limitations to arbitrage. Thus, it is related to the works of Baker, Bradley, and Wurgler (Financial Analysts Journal 2011), Frazzini and Pedersen (Journal of Financial Economics 2014), and Li, Sullivan, and Garcia-Feijóo (Financial Analysts Journal 2014). As explained by the delegated asset management model by Baker et al., large investors may not be able to arbitrage away the mispricing because of index benchmarking, thus explaining why the low-volatility anomaly has persisted for a long period of time. Further research is necessary to disentangle the underlying sources of abnormal returns.Editor’s note: Rodney N. Sullivan, CFA, was the editor and Luis Garcia-Feijóo, CFA, CIPM, was an associate editor of the Financial Analysts Journal at the time this article was submitted. Mr. Sullivan and Dr. Garcia-Feijóo were both recused from the peer-review and acceptance processes, and the reviewers were unaware of their identities. The article was accepted in June 2013; it is published in this issue to abide by the FAJ conflict-of-interest policies then in place, which stipulated that, should the paper be accepted, the editor is allowed to publish one research article or Perspectives piece per calendar year. For information about the current conflict-of-interest policies, see www.cfapubs.org/page/faj/policies.Editor’s note: The authors may have a commercial interest in the topics discussed in this article.Editor’s note: This article was reviewed and accepted by Executive Editor Robert Litterman.Authors’ note: The views and opinions expressed herein are those of the authors and do not necessarily reflect the views of AQR Capital Management, LLC, its affiliates, or its employees.