Can the Low-Risk Anomaly Be Exploited?

For our ongoing Financial Analysts Journal author interview series, Dr. Benjamin R. Auer spent some time explaining the motivation and findings of his article “Liquid Betting against Beta in Dow Jones Industrial Average Stocks,” co-written with Frank Schuhmacher and published in the November/December 2015 issue.

Financial Analysts Journal: What was the practical issue or issues that motivated your research?

Dr. Benjamin R. Auer: The main motivation for our research was the fascinating nature of the low-risk anomaly. Recent research has shown that, in stock markets all over the world, low-beta stocks have consistently outperformed high-beta stocks. According to the Journal of Financial Economics article by Frazzini and Pedersen (2014), this effect holds among various asset classes (e.g., stock, bond, credit, and futures markets) and can be considered one of the greatest anomalies in finance because it challenges the basic notion of a risk–return trade-off. Furthermore, the limits-to-arbitrage explanation for the anomaly provided in the recent Financial Analysts Journal article by Baker, Bradley, and Wurgler (2011) suggests that as long as investment managers with fixed-benchmark contracts hold a large share of the market, “there is no reason to expect that the anomaly will go away any time soon.”

Given this strong evidence for the anomaly, the question arises whether it can be exploited in practice. Unfortunately, most of the literature on the anomaly cannot be used to answer this question because its main focus is on documenting the anomaly in very large stock universes and on constructing new asset pricing factors. The portfolios used in those studies do not reflect returns that can be realized by investors because they contain a large proportion of small, illiquid stocks that are known to be less desirable for trading purposes. This has led to the widespread belief that illiquidity and transaction costs may act as significant barriers that prevent investors from extracting the returns associated with the anomaly via typical long–short trading strategies.

In our article, we take the perspective of typical investors. They have the tendency to concentrate on building small stock portfolios composed of highly liquid stocks that ensure tradability and low transaction costs. Furthermore, they tend to select stocks from the constituents of well-known indexes. For example, the PowerShares S&P 500 Low Volatility Portfolio, an exchange-traded fund, contains only the 200 least volatile stocks of the S&P 500 Index. In the light of this typical investor behavior, we analyze two important questions: First, can the low-risk anomaly be observed in highly liquid portfolios? Second, if it exists, how can unconstrained investors (e.g., hedge funds) exploit this anomalous effect?

What was your approach to the issue?

Our approach is quite simple but powerful. We address the liquidity issue of the low-risk anomaly by focusing on the constituents of the Dow Jones Industrial Average (DJIA). This choice is motivated by several factors. First, the high liquidity of the index constituents allows the practical implementation of various portfolio formation strategies. Second, short-selling of DJIA stocks is almost unconstrained. Third, no other index of US stocks has been available for a longer period of time. Finally, detecting the low-risk anomaly within a small universe of only 30 representative stocks would make this anomaly even more astonishing because one would expect these well-known and actively traded stocks to be most efficiently priced.

In our study, we provide three substantive contributions. First, we analyze whether the low-risk anomaly can be detected within DJIA stocks, using beta as the relevant measure of risk. Second, we derive a trading strategy for effectively capturing the returns associated with the low-risk anomaly. To this end, we construct betting-against-beta portfolios that are long low-beta stocks and short high-beta stocks. Based on these trading portfolios, we then implement a strategy for exploiting the low-risk anomaly in DJIA stocks without sacrificing diversification. That is, we propose a core-satellite strategy, where the active betting-against-beta portfolio is combined with the passive stock market index S&P 500 by means of the Treynor and Black (1973) methodology. Finally, we explicitly account for transaction costs because they are known to affect a number of stock market anomalies and because they can significantly reduce trading performance.

Our main findings for the period 1926 to 2013 are that the low-risk anomaly exists in the highly liquid universe of DJIA stocks and that this phenomenon can be effectively exploited by our betting-against-beta portfolios and the corresponding core-satellite approaches. These results, and the fact that alphas cannot be explained by exposures to standard asset pricing factors, are robust in a variety of settings and provide important implications for practical portfolio management.

How do you expect your findings or results to influence practice?

We believe that our results seriously challenge the common perception that the low-risk anomaly cannot be exploited. We provide robust evidence on the existence and exploitability of the anomaly in the highly liquid stock universe of the DJIA. Because recent studies show that (1) transaction costs have become largely negligible for large institutional investors, (2) trading costs of short positions tend to be immaterially different from the costs of buying and selling stocks, and (3) market impact is unlikely to fully eliminate the profitability of strategies based on highly liquid stocks, our study directly suggests that DJIA stocks offer significant potential for the implementation of trading strategies exploiting the low-risk anomaly and related anomalies.

CFA Institute members can read the full article online. Explore the archives for more Financial Analysts Journal author interviews.

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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.

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