A Low Beta Offering: Scientific Beta
Investors usually want to participate in bull markets while mitigating their downside risk during bear periods. Many are implementing strategies like Low Volatility or Minimum Volatility that seek such results. But using the ‘Low Vol’ factor alone can lead to poor diversification, exposing investors to company-specific and sector-specific risks, as well as to certain macro drivers. A multi-factor framework, however, allows investors to potentially benefit from the defensive attributes of the Low Volatility factor, while also capturing the risk premias associated with other historically rewarded risk factors, like Value, Size, and Momentum. In this piece, we’ll discuss the shortcomings of stand-alone Low Volatility strategies and offer empirical evidence of improved risk-adjusted profiles of certain multi-factor approaches.
Investors Getting Defensive
Despite recently improving sentiment, not too long ago, the probability of a recession in the US reached a 12.5 year-high fueled by weakening PMI data, yield curve inversion, and declining corporate profit margins.1 After more than a decade-long bull market, caution is common these days, with investors looking to more defensive equity strategies to mitigate their downside risk while participating in the bull market.
Low Vol Presents Certain Drawbacks
While certain defensive strategies can reduce volatility and outperform broad indexes during bear markets, investors must take into account the concentration risks they can introduce. For example, looking at just a subset of stocks that historically exhibited lower volatility than the market means that Low Vol strategies can be heavily concentrated in certain sectors, like Utilities and Consumer Staples.
Given this sector-level concentration, Low Vol strategies can have increased sensitivities to certain macro-economic drivers. Utilities are characterized by higher sensitivity to interest rates. During low interest rate environments, Utilities stocks benefit by offering an attractive high-dividend paying profile. But when rates increase, investors tend to leave the sectors due to their high debt and less necessity to chase yield. During the 2018 rising rate environment, Utilities exhibited a 34% negative correlation with the 2 Year Treasury Yield at the lowest point.
Another drawback of standalone Low Volatility strategies is that they often have negative exposure to other historically well-rewarded factors. Over the last five years, Low Volatility exhibited negative exposure to Size, Value, and Profitability. Given that factor leadership rotates unpredictably, we believe investors ought to maintain positive exposure to multiple factor simultaneously to increase potential performance robustness.
A Robust Approach with the Sci Beta Multi-Factor Framework
Rather than isolating exposure to just the Low Vol factor, multi-factor strategies can blend the defensive characteristics of Low Vol with other factors with their own unique characteristics such as Momentum, Size, and Value. Sci Beta, for example, blends the aforementioned four factors together in an effort to deliver more robust returns over the long term and across different market environments.
- The case for Size:2 The Size effect is well established in the finance literature. Stocks with smaller market capitalization have outperformed large stocks over the long term.
- The case for Momentum:3 A hypothesis that lies behind momentum investing is that a stock that has performed well in the recent past will continue to perform well on a short- to medium-term horizon, and that one that has performed poorly will also continue to perform poorly. The momentum effect is often associated with the herding behavior of investors, who tend to invest in the same stocks at the same time and induce a momentum effect over short- to medium-term horizons.
- The case for Value:4 Book-to-market (P/B) based stock selection attempts to increase exposure lower-priced stocks within a given index universe. The book-to-market ratio has been identified as a key driver of stock returns by Fama and French, who found that low book-to-market stocks outperformed high book-to-market stocks over the long term.
Gaining exposure to additional factors can also help diversify company and sector specific risks by broadening the number of securities held in the strategy. The Sci Beta US ETF (SCIU) that seeks to have an equal risk contribution from each factor, for example, has resulted in a positive factor score to Size, Value, Momentum, Low Vol and Investment.
While defensive strategies that promise outperformance in bear markets are attractive to investors, they can introduce unwanted risks into a portfolio. We believe a better long-term approach is to diversify exposure across multiple factors that are well-rewarded over the long run. Such an approach can still introduce the defensive properties of the Low Vol factor, while also offering the potential benefits and unique characteristics of other factors, in an attempt to create a smoother ride for investors across market regimes.
Volatility: Volatility, defined as the standard deviation of returns, measures the dispersion of strategy returns around their mean.
Beta: Coefficient the measures the volatility of an individual factor in comparison to the unsystematic risk of the entire market, defined by the S&P 500 Index.
Correlation: Statistic that measures the degree to which two securities move in relation to each other.
SciBeta United States Low-Volatility Diversified Multi-Strategy Index – Live Date: 21-Dec 2012:
The objective of the Scientific Beta United States Low-Volatility Diversified Multi-Strategy Index is to represent the performance of large and medium capitalization companies from the United States universe that exhibit Low-Volatility characteristics, while ensuring a high degree of diversification.
SCIU: The Global X Scientific Beta U.S. ETF (SCIU) seeks to outperform cap weighted indexes with similar volatility through a multi-factor investment strategy rooted in academic research.
SCID: The Global X Scientific Beta Europe ETF (SCID) seeks to outperform cap weighted indexes with similar volatility through a multi-factor investment strategy rooted in academic research.
SCIJ: The Global X Scientific Beta Japan ETF (SCIJ) seeks to outperform cap weighted indexes with similar volatility through a multi-factor investment strategy rooted in academic research.
SCIX: The Global X Scientific Beta Asia ex-Japan ETF (SCIX) seeks to outperform cap weighted indexes with similar volatility through a multi-factor investment strategy rooted in academic research.