Studies of the Performance of High-Quality, Low-Volatility Stocks

A Bibliography with Excerpts

Quality as an investment factor has been studied extensively and the research papers and articles summarized below detail the results. While approaches to identifying quality vary, the common thread through all of these studies is that high-quality companies are systematically undervalued relative to their future potential. As noted in the paper on the Nifty Fifty, even many of that group of high-flying stocks in the 1970s actually turned out to warrant their then-lofty valuations over the long run. The bottom line: assembling a portfolio of high-quality companies can give you an intrinsic edge over the rest of the market chasing volatility and beta.

This article provides global evidence supporting the Low Volatility Anomaly: that low risk stocks consistently provide higher returns than high risk stocks. This study covers 33 different markets during the time period from 1990 – 2011. (Two previous studies by Haugen & Heins (1972) and Haugen & Baker (1991) show the same negative payoff to risk in time periods 1926 – 1970 and 1970 – 1990.) The procedure for our study is intentionally simple, transparent and easily replicable. Our samples include non-survivors.

We look at an international universe of stocks beginning with the first month of 1990 until December 2011; we compute the volatility of total return for each company in each country over the previous 24 months. Stocks in each country are ranked by volatility and formed into deciles. In the total universe and in each individual country low risk stocks outperform, the relationship with respect to Sharpe ratios is even more impressive.

We believe this anomaly is caused primarily by agency issues, namely the compensation structures and internal stock selection processes at asset management firms which lead institutional investors on average to hold more volatile stocks. The article also addresses the implications for how corporate finance managers make capital investment decision in light of this evidence. The evidence presented here dethrones both CAPM and the Efficient Market Hypothesis.

Abstract: We define a quality security as one that has characteristics that, all else equal, an investor should be willing to pay a higher price for: stocks that are safe, profitable, growing, and well managed. High quality stocks do have higher prices on average, but not by a very large margin. Perhaps because of this puzzlingly modest impact of quality on price, high quality stocks have high risk adjusted returns. Indeed, a quality minus junk (QMJ) factor that goes long high quality stocks and shorts low quality stocks earns significant risk adjusted returns in the U.S. and globally across 24 countries. The price of quality – i.e., how much investors pay extra for higher quality stocks – varies over time, reaching a low during the internet bubble. Further, a low price of quality predicts a high future return of QMJ. Finally, controlling for quality resurrects the otherwise moribund size effect.

This article examines a group of high-flying growth stocks that soared in the early 1970s, only to come crashing to earth in the vicious 1973 –74 bear market. These stocks are often held up as examples of speculation based on unwarranted optimism about the ability of growth stocks to continue to generate rapid and sustained earnings growth. And it was not just the public, but large institutions as well that poured tens of billions of dollars into these stocks. After the 1973 –74 bear market slashed the value of most of the “Nifty Fifty,” many investors vowed never again to pay over 30 times earnings for a stock.

But is the conventional wisdom justified that the bull market of the early 1970s markedly overvalued these stocks? Or is it possible that investors were right to predict that the growth of these firms would eventually justify their lofty prices? To put it in more general terms: What premium should an investor pay for large, well-established growth stocks?

Buffett's returns appear to be neither luck nor magic, but, rather, reward for the use of leverage combined with a focus on cheap, safe, quality stocks. Decomposing Berkshires' portfolio into ownership in publicly traded stocks versus wholly-owned private companies, we find that the former performs the best, suggesting that Buffett's returns are more due to stock selection than to his effect on management. These results have broad implications for market efficiency and the implementability of academic factors.

Investing in quality companies is rooted in a thorough fundamental analysis of all aspects of a company’s financial strength, growth prospects, profit and income generation and overall stability. While various definitions of “quality” abound, we believe that most companies considered to be in this category possess similar attributes: consistent profit and income generation, reduced volatility, downside protection in bear markets, and superior risk adjusted returns as compared to a market index. Quality companies have historically demonstrated predictable periods of outperformance within a market cycle as well as above average returns versus the S&P 500 over longer time periods.

Far from being an avant-garde technique, the practice of ranking stocks on the basis of a quality score is well established, and has been ingrained in the investment process of asset managers, especially those following a value strategy. Even as early as 1949, in his original publication of The Intelligent Investor, Benjamin Graham highlighted the importance of quality stocks by affirming: “The risk of paying too high a price for good quality stocks – while a real one – is not the chief hazard...the chief losses to investors come from the purchase of low quality stocks at times of favorable business conditions...”

In the last two decades, this truism took on renewed significance with the spectacular failure of sizeable companies such as WorldCom, whose market capitalization bore a scant relationship with their fundamentals. There is also growing recognition that high quality companies can be determined a priori and that their performance cannot be comprehensively explained by classical risk factors alone — namely size, momentum, volatility and value. This has therefore given credence to the idea that a fifth factor —quality — exists in its own right and, in combination with other risk premia, may act as a good diversifier in investment portfolios…

Broadly speaking, “high quality companies” share similar characteristics of seeking to generate higher revenue and cash, and enjoying more stable growth than the “average” company. Equally important, high quality companies seek to adopt a conservative, yet effective, capital structure that allows them to grow. Finally, high quality companies are run by managers who tend to exercise prudence in the administration of the companies’ affairs. Together, these propitious traits generally shield these companies from the vagaries of the economic cycle, making them slightly more immune to downturns.

Benjamin Graham spoke of hunting for quality stocks at a reasonable price, so quality investing isn’t new. But where quality fits into a trading strategy or even how it is defined differs among asset management and research firms. We can take a stab at it by describing quality investing as a framework for discerning a company’s potential for strong future profitability.

In some sports, coaches are fond of the maxim that the best offense is a good defense. The rationale, of course, is that even if a team’s offense is having a bad day, good defense can keep the score close. 

There’s an analogous argument in the investment world, since defensive strategies have often turned out to produce above average returns in the long run. For example, Fama and French famously identified value as a return-generating factor, and more recently, the so-called “low volatility anomaly” has generated considerable interest. If value and low volatility strategies produce long run excess returns, they could be good examples of how investors might win by playing defense—or, as some practitioners are fond of saying, how they might win by not losing.

The historical outperformance of low-risk stocks defies a central tenet of finance theory, which states that risk and return go hand in hand: accept more volatility and you’ll be paid with higher rewards over time. Yet, academic research confirms that the low-volatility anomaly has been observable for much of the past century. It also spans asset classes and geographies. 

We did our own research into this anomaly’s investment potential and found that explicitly targeting both low Volatility and measures of fundamental stability, and vetting for nearterm downside risks, produced even stronger results than passive low-volatility approaches.

Not only did they produce higher returns and lower risk, they actually did best in times of market turmoil. In other words, they offered you something close to a free insurance policy against meltdowns like 2008.

Buying high quality assets without paying premium prices is just as much value investing as buying average quality assets at discount prices. Strategies that exploit the quality dimension of value can be profitable on their own, and accounting for both dimensions of value yields dramatic performance improvements over traditional value strategies. Gross profitability is particularly powerful among popular quality notions, especially among large cap stocks and for long-only investors.

In an efficient market, investors earn a higher return only to the extent that they bear higher risk. Despite the intuitive appeal of a positive risk-return relationship, this pattern has been surprisingly hard to find in the data, dating at least to Black (1972). For example, sorting stocks using measures of market beta or volatility shows just the opposite. Panel A of Figure 1 shows that, from 1968 through 2012 in the U.S. equity market, portfolios of low risk stocks deliver on the promise of lower risk as planned, but with surprisingly higher average returns. A dollar invested in the lowest risk portfolio grew to $81.66 while a dollar invested in the highest risk portfolio grew to only $9.76. A similar inverse relationship between risk and return appears from 1989 through 2012 in a sample of up to 31 developed equity markets shown in Panel B of Figure 1. A dollar invested in the lowest risk portfolio of global equities grew to $7.23. Meanwhile a dollar invested in the highest risk portfolio of global equities grew to only $1.20 at the end of the period. This so-called low risk anomaly suggests a very basic form of market inefficiency.

We present a model with leverage and margin constraints that vary across investors and time. We find evidence consistent with each of the model's five central predictions:

(1) Because constrained investors bid up high-beta assets, high beta is associated with low alpha, as we find empirically for US equities, 20 international equity markets, Treasury bonds, corporate bonds, and futures. 

(2) A betting against beta (BAB) factor, which is long leveraged low-beta assets and short high-beta assets, produces significant positive riskadjusted returns. (3) When funding constraints tighten, the return of the BAB factor is low.

(4) Increased funding liquidity risk compresses betas toward one. (5) More constrained investors hold riskier assets.

BOOKS

The above cited papers and articles do not constitute an offer of any securities or investment advisory services. Hutner Capital Management, Inc. does not represent that the information contained in these third-party resources is accurate, true or complete, makes no warranty, express or implied, regarding the information herein and shall not be liable for any losses, damages, costs or expenses relating to its adequacy, accuracy, truth, completeness or use. None of these sources contains all the information necessary to make an investment decision.