Beat the Street: Stock Analysts, Credit Risk, and the Lack of Negative Earnings Forecasts
August 7, 2020 | By Michael Adkison
Researcher: Samar Ashour
In March 2001, a Fortune magazine reporter published an article that would contribute to the largest corporate scandal the world had ever seen. “Is Enron Overpriced?” Bethany McLean asked, noting that analysts seemed to have no clue what they were doing when it came to Enron, a billion-dollar energy company that claimed it was worth $126 a share at the time. “Analysts don’t seem to have a clue what’s in Assets and Investments, or, more to the point, what sort of earnings it will generate,” she wrote. Eight months later, Enron shares would plummet to less than $1; by December, the Wall Street-darling filed for bankruptcy.
While a number of factors contributed to the downfall of Enron, one of the most significant aspects is the lack of stock analyst integrity. McLean wrote in her original article that “13 of Enron’s 18 analysts rate the stock a buy” at a time when Enron had hundreds of millions of dollars in debt. After the Enron scandal, the Securities and Exchange Commission and the rest of Wall Street implemented new policies and precautions to prevent another fallout like that of Enron. But research shows that nearly two decades later, stock analysts suffer from “anchoring bias,” leading to faulty reporting.
“When analysts have negative opinions of the stocks that they have been covering, they tend to stop issuing forecasts instead of issuing low earnings per share (EPS) forecasts,” write Samar Ashour and Grace Qing Hao in their article “Do analysts really anchor? Evidence from credit risk and suppressed negative information.”
Rather than negatively report on the stocks they cover, analysts tend to report nothing at all, leaving investors with over-confident analyses of these stocks. “However,” the researchers write, “we know little about what type of firms have more negative information suppressed by analysts.” Ashour and Hao conducted a massive survey of stocks, analysts’ earnings forecasts, and future returns across nearly three decades to uncover what types of firms are most susceptible to this analysis skew.
Beat the Street
Playing the stock exchange game boils down, more or less, to one goal — beat the street. That is, knowing what the Wall Street market will look like, when to buy, when to sell, and everything in between. It’s been the subject of articles, books and even movies. As Robert Leahy wrote in a 2016 Forbes article, there is an easy way and a hard way to beat the street: the easy way is to stop investing and quit Wall Street; the hard way is to “outperform the markets.” But devoting the level of time and attention to the stock markets necessary to outperform them borders on impossible. That’s where stock analysts come into play.
Stock analysts literally make it their business to predict “the future activity of an instrument, sector, or market.” These analysts, often, have studied and trained at business colleges and universities, including the Sam M. Walton College of Business, and work for business and firms to analyze the stocks to invest in. They issue earnings per share forecasts, or EPS, to predict how much money a single share in a stock will return. But, as noted, research by Ling Cen, Gilles Hilary, and K. C. John Wei revealed that many stock analysts have an anchoring bias in their predictions, meaning that analysts rely greatly on early information for long-term predictions.
“Specifically, [they] construct a measure of cross-sectional anchoring in analysts’ earnings forecasts, which they refer to as CAF, as an individual firm’s mean consensus forecasted earnings per share minus the industry median forecasted earnings per share.” Essentially, Cen, Hilary, and Wei tested the firm’s EPS predictions against the industry median EPS prediction and test its accuracy. “They find that CAF is positively related to analyst forecast errors, earnings surprises, and future stock returns suggesting that analysts anchor their EPS forecasts on the industry norms without sufficient adjustments.” And with analysts providing crucial roles to investors, accuracy, or as close to it as possible, is vital. The question remains, though, which firms are most susceptible to anchoring bias?
Where Credit is Due
That’s where Ashour and Hao’s investigation comes in. They developed a sample of nearly 14,000 firms, based on data from January 1986 to December 2014 and find that a majority of the faulty predictions can be explained by credit rating. “We find that the profitability of anchoring bias-based trading strategies is concentrated in the worst rated firms around credit rating downgrades.” Just like you and I have credit scores, so do public firms, thanks to bond credit services such as Moody’s, Standard & Poor’s (S&P) and Fitch. These credit ratings allow investors to see how trustworthy, or how risky, it is to invest in those bonds.
“Each month,” the researchers say, “we divide stocks rated by the S&P into quintiles according to their credit rating. Within each credit rating quintile, we further divide stocks into quintiles according to their CAF.” They found that, while the prior research on CAF and EPS forecasts is accurate, it is especially true for high-credit risk stocks. “Analysts suppress more negative information for stocks with higher credit risk, especially around credit rating downgrade periods,” so much so, in fact, that once the researchers controlled for credit rating and suppressed negative information, “the ability of CAF to predict forecast errors, earnings surprises, and stock returns disappears.”
But the investigation doesn’t stop there—Ashour and Hao search for an answer as to why these risky firms tend to have more negative information suppressed by analysts. While correlation doesn’t necessarily mean causation, one notable factor is that “analysts who cover high credit risk stocks are younger, less experienced, and less reputable.” Experienced, reputable analysts may avoid these risky stocks so that they “protect their reputation” or simply they may just avoid such risky investments. Meanwhile, younger analysts “may be less skillful at uncovering all the negative information about high credit risk stocks. However, once they ascertain this negative information, they also suppress it by dropping the coverage.”
Risky Business: Investing Wisely
So, do you really have to quit the stock exchange game in order to beat the street? Not necessarily, but it goes without saying that it takes time, energy, and, pun intended, investment in market analysis to win big on Wall Street. Stock analysts, whether within a firm or not, take much of that burden off your shoulders. But Ashour and Hao’s article offers some sound advice for investors to know what to look for in an investment — and what to avoid.
It’s always a good idea to consider the credit scores of the firms you may be considering investing in, and not just for evaluating trustworthiness. As the researchers note, stock analysts tend to, whether consciously or not, suppress negative information about risky stocks. As a result, these analysts might not give you a full picture of what you’re investing in. On the other hand, you might consider thoroughly vetting the stock analysts you trust and listen to. As the researchers write, rookie analysts tend to suppress more information because they cover riskier stocks. That doesn’t mean you should only trust older professionals who’ve done this for years, but it does mean you should take the wisdom of a younger, inexperienced stock analyst with a grain of salt. You may have to spend money to make money, but it never hurts to make sure you see the whole picture.