Exploring the Low Volatility Anomaly

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We are taught to assume that there is a linear relationship between risk and return. In other words, for a greater reward you have to take greater risk. And from an investment perspective, we’re taught this concept of the capital asset pricing model or CAPM, which states the expected return of an asset is a function of risk.

Subsequent to the findings of CAPM the world of academia shed light on the concept known as a low volatility anomaly which states the exact opposite. And that over longer periods of time, it is, in fact, lower risk stocks that provide a greater return than higher risk stocks.

Here’s what I mean. If you’re to take the Russell 1000 universe and break it out into five equally-weighted buckets sorted from low risk to high risk, you would find that on average low risk stocks outperform high risk stocks.

This happens for a number of reasons. Some behavioral such as the tendency of investors to overpay for glamour stocks, some structural such as limitations on borrowing or constraints on long-only exposures.

As investors have embraced the benefits of low volatility equities, there’s been a proliferation of product, with the low volatility equity universe exceeding $400 billion. However, not all low volatility strategies are created equal. When it comes to reducing portfolio volatility, there are many different approaches, which can yield different results.

One must ask, how does a strategy measure risk? What constraints are put into place? And probably the most important question today’s market environment: Valuations. How does this strategy consider the price you pay for a company?

Fears of an economic slowdown or recession aren’t going away. While equities are near all-time highs, market volatility has increased significantly because of this. We expect the popularity of low volatility strategies to continue. However, it is important to understand the different approaches in this space and ask the question, is my low volatility strategy really low volatility?

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