Among the many parallels we can draw between life’s macro issues and the world of finance, perhaps one of the most compelling is the tendency for people to think they know more than they do. While this can be costly in any context, it can break the bank when mixed with investing.
In the field of psychology, this tendency is known as the Dunning-Kruger effect, named after the Cornell University psychologists who studied it. David Dunning found that the main reason for such a bias was ignorance rather than arrogance–that is, that often people didn’t realize how much they didn’t know and, therefore, couldn’t accurately assess their own abilities.
If combined with emotionally-charged investment decisions, the result can be a toxic brew. The ease with which today’s investors tap into vast amounts of data and newsfeeds can leave them thinking they possess the knowledge and insight necessary to make sound investment decisions. While on a much larger scale, it harkens back to the words of eighteenth-century poet Alexander Pope who wrote, “A little learning is a dangerous thing.” A timelier context could be a (slightly brain-twisting) comment made in a 2002 news briefing by then Secretary of Defense Donald Rumsfeld regarding the government of Iraq’s relationship with terrorist groups:
“Reports that say that something hasn’t happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns – the ones we don’t know we don’t know. And if one looks throughout the history of our country and other free countries, it is the latter category that tend to be the difficult ones.”
This underscores a critical issue for investors—that unknown unknowns do exist. There is no possible way to predict the vagaries of the market on any given day or year, nor to fully understand what you fail to understand. Therefore, the best defense for investors is to stick to concrete data and the analysis of fundamentals—the “known knowns.”
In 2009, in the wake of the financial crisis, the Financial Industry Regulatory Authority (FINRA), in consultation with the U.S. Department of the Treasury, commissioned the first national study of the financial capability of American adults. The research was conducted through online surveys of over 25,000 American adults, and the study was updated in 2012 and 2015. Participants were asked to rate their level of financial knowledge and then answer questions to reflect that knowledge. The report states:
“In order to make sound financial decisions, individuals need to be equipped not only with at least a rudimentary level of financial knowledge, but also with the skills to apply what they know to actual financial decision-making situations. As the survey data demonstrate, all too often, a gap exists between self-reported knowledge and real-world behavior.”
When I created stock screening models based on the strategies of some of the most successful investors of all time, including Warren Buffett, Peter Lynch and James O’Shaughnessy (among others), I used the known knowns that they focused on—fundamental, straightforward, quantifiable criteria that were easy to collect and which served as strong indicators of a company’s underlying operating strength.
Using these models, I have identified the following high-scoring stocks:
Robert Half International Inc. (RHI) provides specialized staffing and risk consulting services and is favored by our Kenneth Fisher-based model in light of its price-sales ratio of 1.17, which falls comfortably within the preferred range of .75 and 1.5. The company also earns high marks from our Peter Lynch-inspired stock screening model based on its exceptionally low leverage (debt-equity ratio of 0.09%) and positive earnings-per-share of $2.65. Our Joel Greenblatt-based model likes the earnings yield of 9.30%.
Snap-on Incorporated (SNA) is a manufacturer and marketer of tools, equipment, diagnostics, repair information and systems solutions that earns solid scores from our Warren Buffett-based investment strategy due to its earnings predictability and its ability to pay off debt with earnings in less than two years. This model also likes management’s use of retained earnings, which reflects a return of 15.9%. Our Lynch-based model favors the earnings-per-share of $9.43 (based on 3, 4 and 5-year averages) and debt-equity ratio of 37%. Our Greenblatt-inspired investment strategy favors the earnings yield of 9.65%.
Owens Corning (OC) is engaged in the business of composite and buildings materials systems, with products ranging from glass fiber to insulation and roofing for residential, commercial and industrial applications. The company earns a perfect score from our James O’Shaughnessy-based investment methodology in light of its earnings persistence and price-sales ratio of 1.22 versus the maximum allowed level of 1.5. Our Lynch-based model favors the company’s earnings growth of 17.18%, which falls comfortably within the preferred range of between 10% and 19%, and its earnings-per-share of $3.81.
Wabash National Corporation (WNC) is a diversified industrial manufacturer and producer of semi-trailers and liquid transportation systems. The company scores well under our Lynch-based investment strategy due to the ratio of price-earnings to growth in earnings-per-share (PEG ratio) which, at 0.39, is considered exceptional by this model (anything under 1.0 passes the screen). Our Greenblatt-inspired screen favors the company’s earnings yield of 13.82% and return-on-total capital of 40.86%.
Thor Industries, Inc. (THO) manufactures a range of recreational vehicles in the U.S. to sell primarily in the U.S. and Canada. The company earns a perfect score under our O’Shaughnessy-based stock screening model given persistent growth in earnings-per-share and a price-sales ratio of 0.84 (based on trailing 12-month sales), well below the maximum level allowed of 1.5. Our Lynch-based strategy likes the company’s PEG ratio of 0.73 as well as its favorable level of debt (20% of equity. Our Greenblatt-based model gives high marks to the earnings yield (9.08%).