Now that volatility has returned to the market, we thought we’d revisit some basics about low volatility equity strategies. These strategies all have a common objective: less volatility, lower drawdowns, and market-like or -better returns. But since the last major equity market drawdown, the category of low volatility equity strategies has matured – both in magnitude and in the variety of investment approaches.

What’s in a Name?

Recall the quote from Romeo and Juliet, "That which we call a rose by any other name would smell as sweet." Shakespeare touched on a universal truth in this play – one that is still relevant even today – when Juliet laments on the fact that the Montague name is meaningless – the name did not make the man. Similarly, the label of low volatility strategies is arbitrary compared to their intrinsic qualities. Focus on the strategies’ key characteristics and you can start to see where they're alike and different.

Quantitative vs. Fundamental

Most defensive equity strategies are quantitative, with differing inputs, models, objectives, and limitations. Nevertheless, the residual outcomes of fundamental approaches could improve equity allocations by providing diversification and a defensive posture. Although they may be categorized as dividend-focused or value strategies, they share some characteristics with low volatility strategies, including lower beta, defensive stock and sector exposure, and downside protection. However, for our purposes, the remaining differentiators and analysis will mostly apply to quantitative strategies that explicitly set risk reduction as their central objective.

Rules-based vs. Optimized

The portfolio construction process is likely where the line in the sand for quantitative approaches is most frequently discovered. In particular, whether a strategy a) constructs its portfolio by ranking names in a universe according to some measure of risk, establishing a cut-off, and implementing a weighting scheme, or b) mathematically optimizes holdings for lower portfolio-level volatility, using estimates of volatility and correlation for each stock.

The former rules-based, or rank-based, method is easier to understand and less opaque, but it may be more vulnerable to concentration risk since it implicitly excludes higher volatility equities and relies too much on the companies with the lowest volatility. The latter optimization approach offers the potential for narrower outcomes and higher risk reduction, but it is more complex and only as good as its covariance estimates. Due to the inclusion of companies that aren't strictly low volatility due to their attractive correlations with others, the portfolio-optimized approach may also be better equipped to avoid valuation or overcrowding risks.

Both methods need well-conceived and carefully applied constraints, especially the portfolio optimization approach. Optimized strategies require a deft touch to exploit stock correlations for risk reduction while avoiding overexposure to particular sectors or countries, liquidity traps, and high turnover.

Return Expectations

The most typical expectation is for long-term returns to match a cap-weighted index. Outperformance in market downturns is always a part of the performance contours for low volatility strategies. Typically, this is exchanged for trailing cap-weighted index returns during bullish periods. There are some low volatility strategies, however, that also attempt to outperform capitalization-weighted indexes in up markets.

Risk Expectations

The assumption that a strategy's "risk" is lower than a cap-weighted equity benchmark is likely obvious, but the magnitude and terms of their risk-reduction claims are important to uncover. The projected risk characteristics of a low volatility strategy are frequently described as a percentage of benchmark volatility (for example, 60–90%) or, alternatively, as a percentage of reduced volatility compared to the benchmark (for example, 20–30%). A beta expectation, which reflects the percentage of reduction in benchmark-driven volatility, may be stated less frequently (e.g., 0.60-0.75). For some strategies, volatility reduction and beta may naturally occupy a narrow range over an entire market cycle, but others may have a wider range and exhibit more variability depending on the market environment.

Stock- and Portfolio-level Risk

Low volatility investing methods often incorporate some input to gauge stock-level. This input could be statistical (e.g., standard deviation, beta), fundamental (e.g., measures of quality or value), or a combination of both. Stock volatility predictions must strike a balance between being out of date and favoring recent history. You may think of these estimations as the true "secret sauce" of these models because it is difficult to build a successful defensive portfolio without accurate estimates of a stock's future volatility.

Heuristic strategies may assume a decrease in risk at the portfolio level as a natural residual based on the low volatility stocks they include, despite defining an objective function for it in their models. Optimized strategies advertise the use of proprietary algorithms intended to reduce portfolio-level volatility, but it's essential to discover what this actually means. Do they only limit stock-level weights for diversification in accordance with their selection model screen? Do they actually take into account stock correlation, or is their optimization just an improved weighting system on top of a ranking approach? Is the screening step already doing the heavy lifting to the extent that there are so few stocks left to truly benefit from a covariance matrix?

Appetite for Alpha

Many managers aren't satisfied to rely on the low volatility "anomaly" to match or outperform the market over the long run, even when there are many more naive, passive-appearing smart beta solutions available. They might choose to include an alpha source in the mix, which is frequently their own return forecast model that is based on valuation, momentum, or other unusual combinations of variables.

Need More Than Basics?

Intech has been managing low volatility equity portfolios for over a decade now. We offer a range of resources on the subject, including how to evaluate low volatility equity strategies and their role in portfolio construction. Our recent paper, “Low Volatility Investing: Assess, Analyze, and Act” is a quick primer on these topics. Download it to learn more.