One of the most popular and successful strategies over the last decade has been low-risk (i.e., low-beta or low-volatility) investing. New research shows that those strategies have persisted even after the publication of the research documenting their existence, and that they can be pursued in low-cost, low-turnover portfolios.

One of the big problems for the first formal asset pricing model developed by financial economists, the capital asset pricing model (CAPM), was that it predicts a positive relationship between risk and return. However, the historical evidence demonstrates that the slope of the security market line is flatter than the CAPM suggests. Most importantly, the quintile of stocks with the highest beta meaningfully underperform those in the lowest-beta quintile – high-beta stocks provide the lowest returns while experiencing much higher volatility. The publication of research findings led to low-risk (low-beta and low-volatility) investing receiving a tremendous amount of attention, especially since the financial crisis that began in late 2007.

Three economic theories explain the low-risk anomaly:

  1. Many investors are either constrained against the use of leverage or have an aversion to its use. Such investors who seek higher returns do so by investing in high-beta stocks despite the fact that the evidence shows they have delivered poor risk-adjusted returns. Limits to arbitrage and aversion to shorting, as well as the high cost of shorting such stocks, prevent arbitrageurs from correcting the pricing mistake.
  1. Some individual investors have a “taste” for lottery-like investments. This leads them to “irrationally” invest in high-volatility stocks (which have lottery-like distributions) despite their poor returns. They pay a premium to gamble.
  1. Mutual fund managers who are judged against benchmarks have an incentive to own higher-beta stocks. In addition, managers’ bonuses are options on the performance of invested stocks and thus are more valuable for high-volatility stocks.

Those three theories provide reasons to believe that the low-risk premium not only exists but is also likely to persist.

AQR Capital Management’s Ron Alquist, Andrea Frazzini, Antti Ilmanen and Lasse Pedersen contribute to our understanding of the low-risk anomaly with their February 2020 paper, Fact and Fiction about Low-Risk Investing. Their analysis uses metrics created by ranking U.S. stocks each month since 1931 for six statistical risk metrics, or since 1957 for four fundamental risk measures that have later data availability. The six statistical risk metrics are: the betting-against-beta (BAB) factor – buying stocks with low beta and selling stocks with high beta; the stable-minus-risky (SMR) factor, which ranks stocks using betas but weights them in a dollar-neutral rather than a market-neutral way, resulting in a negative exposure to beta; SMRMN, the market-neutral version of SMR; the betting-against-correlation (BAC) factor; idiosyncratic volatility (VOL); and maximum recent daily return (MAX). The four fundamental risk measures are quality-minus-junk (QMJ), which is based on 16 single metrics, and its subgroups profitability, growth and safety.