Start with a basic method for valuing stocks. To grossly oversimplify, what you pay for a share in a company is based (in large part) on a formula called “earnings multiple.” How much you should pay today is a function of how much the company is likely to earn next year. The Wall Street analysts who create those earnings forecasts put a multiple on it, lets say 15X and — voila! — we get a fair estimate for what prices stocks should be next year.
What could possibly go wrong with that? Plenty. Three major things: estimates, multiples and forecasting error.
Estimates: Not only can they be wrong, they often are very wrong — and in a consistent and predictable way. According to a study by McKinsey & Co., Wall Street’s analysts are nearly always too bullish. The authors noted that analysts have been “persistently over-optimistic for the past 25 years.” Their earnings estimates ranged from 10 to 12 percent a year. Actual earnings growth was half of that, about 6 percent annually. “On average, analysts’ forecasts have been almost 100 percent too high.” The only exceptions are during recessions, when they are (surprise!) too bearish.
Multiples: We could use an earnings multiple of 15x — about the average over the past century. However, at times this multiple swings to extremes, sometimes wildly so. Sometimes, investors think markets are worth more than usual — 20x, 25x, even 30x. Other times, they are willing to pay much less for a dollar of earnings — 12x, 10x even 7x earnings. History teaches us that these multiples eventually revert to the mean.
That is for the overall market. Different sectors command different multiples, and even companies within the same sector can trade at different earnings multiples. That multiple can be a function of popularity, media coverage, a celebrity CEO or a hot new product. But buzz and other trendy factors are not the best basis for determining the intrinsic value of equities.
So we see the first two legs of our “simple formula” are not so simple after all. Earnings estimates are not very reliable, while multiples vary widely. What else could go wrong? One big thing, and it could be the source of your queasiness.
Forecasting error: As it turns out, whenever the economy slips into a recession, these earnings estimates have their greatest error factor. In other words, those estimates that were not so great in the first place turn out to be simply terrible as the economy turns. Wall Street gets it most wrong at precisely the worst possible time.