The Latest from Two Sigma Research: How Design Choices Impact Low Risk Factor Performance

When it comes to the construction of risk factors, the devil is in the details.¹ It is one thing to define a general theme for a risk factor, for example “Value” or “Momentum”, but when it comes to the design and actual construction of the factor, there are many specification choices that need consideration, and that is where the value can lie. For example, while the theme behind a Value² factor is generally well understood and documented in the academic literature, how one defines whether a stock is under– or overvalued is not necessarily straightforward. Our 2016 paper, “Risk Factors Are Not Generic,” demonstrated that Value factors with varying definitions of value were only 14% correlated on average—and that’s just definitional differences. There is also dispersion that can occur from different approaches to what data sets and techniques are utilized in factor construction. Long story short: when building factors for practical use cases, such as portfolio analysis and risk modeling, definitional and constructional choices matter.

A recent, stark example of how seemingly small specification details may have a surprisingly large impact is the performance of Low Risk during the COVID-19 equity market selloff in the first quarter of 2020. At a high level, “Low Risk” factors intend to capture the phenomenon that lower risk stocks tend to outperform higher risk stocks on a risk-adjusted basis. The performance of funds and long-short factors attempting to capture the same Low Risk phenomenon varied greatly over this period. In fact, performance was often directionally different depending on the factor provider or asset manager: some delivered positive returns, while others saw notable losses.

For example, as reflected in the chart below, on the positive side, the largest Low Risk factor-based ETF by assets, BlackRock’s iShares Edge MSCI Min Vol USA ETF (ticker USMV), delivered positive excess returns relative to the S&P 500 Index. The same can be said for Invesco’s S&P 500 Low Volatility ETF (ticker SPLV). Both USMV and SPLV are long-only U.S. funds, hence our comparison relative to the S&P 500 Index. Additionally, some asset managers’ Low Risk long-short factors, such as Northern Trust’s Low Volatility factor, posted meaningfully positive returns during the market rout, with top-quintile low volatility stocks outperforming their higher-risk counterparts by nearly 10%.³

This positive performance is in stark contrast to the very poor performance of other Low Risk factors over the same period. The long-short Betting Against Beta (BAB) factor, which was part of the original research on the Low Risk phenomenon, delivered double digit negative returns during the COVID market meltdown in the U.S. universe.⁴ Similarly, the Low Risk factor in Venn suffered even worse losses, down closer to -20%. 

Cumulative Returns of Various Low Risk Factors and ETFs

Time period: February 19, 2020 - March 17, 2020.

In a recent Street View, our colleagues on the Two Sigma Client Solutions Research team (the group responsible for developing new Venn factors and methodologies) walk through five different factor design choices and compare how they impacted the performance of the Low Risk factor during the COVID market crisis period and over the long-term. They demonstrate the implications for asset allocators, specifically those that outsource all or some of their investment management to external managers, where factor design specifications may not be as clear. While this group of investors may be less concerned with building their own factor portfolios, they may be impacted by the factor design choices of others to the extent they use factors to analyze whether their managers are delivering the factor exposures they expect.

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Visit Venn to analyze the performance of the Low Risk factor and its influence on the risk of your investments and portfolio(s).

REFERENCES

¹ For example, read “The Devil in HML’s Details” (Asness and Frazzini, 2013) in which the authors show the performance improvement of a simple book-to-price Value factor by updating the denominator (i.e., price) more frequently.

² The idea behind Value is that stocks that are priced cheaply, relative to some fundamental measure, tend to outperform those that are relatively expensively priced over time.

³ Source: Northern Trust.

⁴ Source: AQR Capital Management, LLC. https://www.aqr.com/Insights/Datasets/Betting-Against-Beta-Equity-Factors-Daily

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