Research dating back to 1972 has persistently found that low-volatility (or low beta) stocks have systematically provided higher risk-adjusted returns than high-risk stocks. Today, many leading equity risk model providers (such as MSCI, Axioma, Factset, Bloomberg and Style Analytics) include low volatility as a distinct factor. Despite the strong academic evidence and popularity in the industry, the low-volatility factor is not included in well-known asset pricing models.
Amar Soebhag, Guido Baltussen, and Pim van Vliet, authors of the June 2025 paper “Factoring in the Low Volatility Factor,” examined why low-volatility stocks have historically outperformed their higher-volatility counterparts. This phenomenon challenges traditional finance theory. The authors investigated whether this “low-volatility premium” can be explained by known risk factors or if it represents a persistent anomaly, and, thus, should be included in standard asset pricing models. Their data covered U.S. stocks and spanned the period 1972-2023. They constructed portfolios that go long low-volatility stocks and short high-volatility stocks, similar to the methodology used in Fama-French factor research. Then, they compared factor models using the maximum Sharpe ratio as the primary criterion to assess a model’s asset pricing power. To address the concern that many anomalies are heavily influenced by microcap stocks that are not easily accessible, they excluded stocks below the 20th NYSE size percentile. Their analysis included:
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Measuring the performance of the low volatility factor over a long historical period.
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Testing whether this performance could be explained by established risk factors, including market, size, value, momentum, profitability and bond sensitivity.
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Assessing the persistence and statistical significance of the low volatility premium.
Key Findings
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High Volatility Resembles “Junk.” High-volatility stocks exhibited strong correlations with low profitability and high investment stocks. However, low volatility is not simply the opposite of junk, nor is it identical to quality or value. This nuance is central to their findings.
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Persistent Outperformance. The low volatility factor produced an annualized premium of 6.4% with a near-zero beta, and a CAPM alpha of 6.3% per annum—a highly significant result.
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Not Fully Explained by Traditional Models. Spanning regressions showed that all factor models showed significant improvements at the 1% significance level when factoring in low volatility.
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Survives Transaction Costs. After accounting for the frictions of implementation costs and shorting constraints, the low-volatility factor was not only robust but also increased. This was true for both the long and the short sides. In addition, for most factors, the hedged (short the market) long returns were higher than the hedged (long the market) short returns.
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Tests of Robustness. Results over extended samples starting in January 1930 or July 1963 for the factors that could be constructed across those periods showed that the low-volatility factor provided added value once accounting for factor asymmetry and investment frictions. In addition, it has persisted in recent periods marked by the rise of passive investing and changing market structures.
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Sharpe Ratios: The low-volatility factor significantly improved all major factor models, increasing Sharpe ratios by 13–17%.
Key Takeaways for Investors
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Low Volatility Works. Over long periods, portfolios of low-volatility stocks have outperformed those of high-volatility stocks on both an absolute and risk-adjusted basis.
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Not Just a Risk Story. The outperformance is not fully explained by traditional risk factors or sector exposures, suggesting that investors may systematically overpay for volatile stocks or underappreciate the compounding benefits of lower volatility.
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Potential for Alpha. The low volatility factor generates statistically significant alpha, even after accounting for market, size, value, and bond factors.
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Practical Implications. Investors can potentially improve portfolio risk-adjusted returns by incorporating low-volatility strategies but should be mindful of sector concentrations and the possibility of changing market dynamics.
Their findings led Soebhag, Baltussen, and van Vliet to conclude: “A low-volatility factor substantially improves performance of factor models once accounting for these dimensions in various in-sample and out-of-sample exercises, across different low-risk measures and methodological choices. We advocate integrating the low-volatility factor into asset pricing models, accounting for the asymmetry and frictions.”
Before summarizing, it’s important to discuss some other interesting findings from empirical research on the low volatility factor.
Other Research Findings
In his 2012 paper, “Enhancing a Low-Volatility Strategy is Particularly Helpful When Generic Low Volatility is Expensive,” Pim van Vliet found that while, on average, low-volatility strategies tend to have exposure to the value factor, that exposure was time-varying. The low-volatility factor spent about 62% of the time in a value regime and 38% in a growth regime. The regime-shifting behavior affected the performance of low-volatility strategies—when low-volatility stocks had value exposure, they, on average, outperformed the market by 2%. However, on average, when they had growth exposure, they underperformed by 1.4%. Providing further evidence, the authors of the 2015 study “Low-Volatility Cycles: The Influence of Valuation and Momentum on Low-Volatility Portfolios,” found that there was no alpha in a four-factor model except in extremely cheap, low volatility environments.
As of the end June 2025, Morningstar reports that Invesco’s S&P 500® Low Volatility ETF (SPLV)—a single factor strategy that tracks the S&P 500 Low Volatility Index (the 100 stocks from the S&P 500 with the lowest realized volatility over the past 12 months)—had a P/E ratio of 22.3, virtually the same as that of Vanguard’s 500 ETF (VOO). Low volatility is not in the value regime where it has provided portfolio benefits. The P/E ratio of Dimensional’s Large Value ETF (DFLV) was just 14.2.
Summary
The authors of “Factoring in the Low Volatility Factor” provide compelling evidence that the low volatility premium is genuine, persistent, and not fully explained by existing risk models. For investors, low-volatility strategies can be a valuable addition to a diversified portfolio, offering the potential for higher risk-adjusted returns without simply taking on more risk. However, investors should be aware that the valuations of single-factor, low volatility strategies are not in the value regime, where they have provided portfolio benefits. As legendary investor Howard Marks noted: “No asset is so good that it can’t become a bad investment if bought at too high a price.” If you are considering a low-volatility strategy, it should be one that is multi-factor, combining low volatility with value, momentum, and quality, as combining it with other factors helps avoid periods when it might be expensive or have bad quality/momentum.
Postscript
For investors looking to dive deeper into the research on the low volatility factor I recommend my October 2024 Alpha Architect article “Improving Low Volatility Strategies.”
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