The Expectations Game

The most notable development in the stock market over the last couple of weeks may be the fact that investors finally appear to be paying attention to the dramatic slowdown in corporate earnings growth. You can still find people who insist that liquidity will continue to drive this market higher–one CNBC guest said on Friday “I don’t care a rap for earnings.” But the mainstream business press has been giving increased (and long overdue) coverage to investor concern about weak profits.

Still, the serious news about slowing earnings growth–profits for the S&P 500 are up just 3.7 percent from last year–continues to be occluded by that most annoying of bugbears, namely analysts’ estimates. Because U.S. companies have become so adept at managing their earnings and at guiding analysts’ expectations, they’re often able to meet those expectations even during difficult times. In the quarter just ended, for instance, First Call reports that 59 percent of the corporations it follows beat estimates, 23 percent matched estimates, and just 18 percent came in below estimates. If the criterion you’re using to judge corporate performance is whether it was better or worse than expected, then, corporate performance in the second quarter was not bad at all.

This is what seems to be behind the still-sanguine forecasts offered by prominent market strategists, including Lehman Bros.’ Jeffrey Applegate and Goldman Sachs legend Abby Joseph Cohen. Cohen, whose market forecasts have been uncannily accurate for much of this market, wrote two weeks ago, in a note to clients, that corporate earnings were “so far, so good,” and pointed specifically to the fact that almost 60 percent of earnings reports had beaten estimates.

The problem here is that whether a company’s earnings are better than expected has nothing to do with whether a company’s earnings are good enough to justify its stock price. If a company beats estimates, or falls short of estimates, that may tell us something important about the accuracy of the analysts, but it can’t tell us anything about the company itself. The validity or lack thereof of a forecast is relevant to an evaluation of the forecaster, but not to whatever is being forecast.

Think of it in terms of the weather. If the weatherman predicts that the temperature will soar to 95 degrees tomorrow, and instead the thermometer never climbs above 80, you don’t feel cooler because the temperature fell short of expectations. And if the weatherman predicts a 100-degree day, and the temperature is 100 degrees, you don’t feel any better about how hot it is because the temperature performance was in line with expectations. What matters is how hot or cool it is, not how accurate the weatherman is.

You can extend the analogy to think about temperature change over time. Let’s accept, for the moment, that this is the hottest summer of the decade. Let’s also accept that weathermen have been fairly accurate in predicting these record-breaking temperatures. Does that mean the dramatic rise in temperature is less important? Should we be saying: “It’s a lot hotter than it was last year, but the temperatures are right in line with expectations?”

What an observer thinks is going to happen, then, has nothing to do with what actually happens. (Let’s set the Hawthorne Effect aside, please.) And while there are lots of things to look at in evaluating a company–year-over-year earnings growth, sequential quarterly earnings growth, return on capital, and operating margins–its performance relative to expectations is simply not one of them. It’s not just that the less we hear about beating estimates, the better. It’s that we shouldn’t ever hear about beating, or missing, or matching estimates again.