Getting Paid to Reduce Risk: The Low-Risk Anomaly

by Larry Swedroe, 9/23/19

New research on the low-risk anomaly – the fact that less risky stocks have had higher risk-adjusted returns – reveals exactly which types of stocks are likely to perform poorly over time, especially in a bear market. If the funds and ETFs you own lack construction rules to screen out those stocks, you will be exposed to unnecessary risks.

In addition to momentum, one of the great challenges to the efficient markets hypothesis is the low-risk anomaly – the highest risk stocks have lower returns, not just lower risk-adjusted returns, than the lowest risk stocks. This is true whether we consider volatility as the measure of risk, market beta, or broader measures such as quality (the QMJ factor). This is a real problem, as some investors seem able to enjoy a free lunch – higher return with less risk.

Nishad Kapadia, Barbara Ostdiek, James Weston and Morad Zekhnini (KOWZ) contribute to the literature on the low-risk anomaly with their study “Getting Paid to Hedge: Why Don’t Investors Pay a Premium to Hedge Downturns?” which was published in the June 2019 issue of the Journal of Financial and Quantitative Analysis. They began by noting: “At the heart of most rational asset pricing models is a concept of ‘bad times,’ when the marginal utility of consumption is high. Stocks that do well in bad times should have low expected returns because of the insurance they provide.” They tested this hypothesis using an intuitive measure of bad times: bear markets (periods from peak to trough in Standard & Poor’s (S&P) 500 levels at the business-cycle frequency).

To perform their test, they first identified stocks that performed particularly poorly in bear markets. They then constructed tradable portfolios that hedge bear market risk (long safe stocks and short risky stocks, creating an SMR, or safe minus risky, factor) and tested whether they do, in fact, earn low average returns. They identified nine bear markets between 1966 and 2015, with an average duration of 14 months and an average loss of about 30%. They excluded financials and microcap stocks.

Following is a summary of their findings:

It is possible to identify stocks ex-ante with differing sensitivities to bear markets.

The risky (the R in SMR) small-growth stocks with high short-term debt, high capital expenditures and low dividend yields suffer the most during downturns. Investors seeking to avoid the worst outcomes during bear markets should shun stocks with those characteristics.

Large, profitable, dividend-paying value stocks that make smaller investments with limited debt (the S in SMR) suffer the least during downturns.

Safe stocks are in the highest decile of predicted bear market returns, and risky stocks are in the lowest decile.

SMR has out-of-sample average monthly returns of 3.6% in bear markets – risky stocks lose 5.5% a month versus the 1.9% a month loss for safe stocks.

The unconditional average returns of safe stocks are much greater than those of risky stocks – the safe portfolio outperforms the market (by about 0.2% per month), and the risky portfolio underperforms U.S. Treasury securities. The results are not due to small illiquid stocks, but are pervasive patterns across the market.

From May 1967 through December 2015, SMR generated a four-factor (beta, size, value and momentum) alpha of 0.85% per month. It’s an anomaly for asset pricing models.

The high returns for SMR were robust to a battery of tests (such as value weighting and equal weighting, including financials and microcaps) and cannot be explained by co-skewness, idiosyncratic skewness or the betting-against-beta anomaly.

KOWZ also found that the returns for SMR in bull markets were essentially zero. Thus, you receive a premium during bear markets (when premiums are most valued) and don’t pay any price for the hedge during bull markets. At least historically, investors in safer stocks have enjoyed a free lunch, while investors in the riskiest stocks have earned below-market returns while taking on much greater risk. In fact, they concluded: “Stocks that are predicted to do the worst in bear markets do not unconditionally outperform the risk-free asset”—one-month Treasury bills!

These results are certainly puzzling for classical finance theory because they suggest that insuring against bad times is not valuable to investors. Bear markets are correlated with lower consumption, GDP and investment growth, and also predict lower economic growth up to a year ahead. And assets that perform well in bad times should have lower overall returns, as investors are, on average, highly risk averse. Yet, the data demonstrates the reverse to be true. What explanations do we have for the anomaly? A look at the performance of the safe and risky stocks in the late 1990s and early 2000s provides us with a clue to the answer.

Explaining the anomaly

The risky leg of the SMR portfolio performed exceptionally well in the internet boom in the late 1990s, then suffered severe losses in the subsequent crash, suggesting that stocks that are the most overvalued before a bear market perform the worst during the bear market, when their prices correct sharply as investor sentiment falls. The research, including the study “The Short of It: Investor Sentiment and Anomalies,” by Robert F. Stambaugh, Jianfeng Yu and Yu Yuan, demonstrated that short-sale constraints (which prevent pessimists from expressing their views and correcting overvaluations) and high investor sentiment can lead to overvaluation.

To test this finding, KOWZ used the Baker and Wurgler sentiment index. They found that risky portfolios constructed using Baker and Wurgler’s characteristics-based model earned average excess returns of -0.87% (0.33%) per month if the prior month’s sentiment was above (below) the median. The difference of 1.2% a month is statistically significant (t-stat = 2.3). On the other hand, they found that investor sentiment does not predict differences in the next month’s average returns for the safe stock portfolio.

KOWZ concluded: “Simple intuitive measures of risk such as firm size, leverage, book-to-market ratio, investment and indebtedness are good predictors of bad performance during severe market downturns.” They added: “Our results support behavioral explanations for differences in the cross-section of stock returns and raise the bar for rational explanations. Rational asset pricing models should explain why bear market risk earns a negative risk premium.”

The takeaway is to make sure you understand the nature of the risks in the stocks in your portfolio. Make sure you, or the funds you own, aren’t holding small-growth stocks with high short-term debt, high capital expenditures and low dividend yields. Those risky stocks have performed very poorly over time, especially during bear markets. On the other hand, there are funds whose construction rules screen out stocks with those characteristics from their eligible universe.

Larry Swedroe is the director of research for The BAM Alliance, a community of more than 130 independent registered investment advisors throughout the country.

Getting Paid to Reduce Risk: The Low-Risk Anomaly

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