Imagine a spectrum of stocks that represents an index. On the left-hand side are the losers, and on the right-hand side are the winners. If I were to ask a portfolio manager how to beat the index, which side of the spectrum would you expect him or her to pick from? For most portfolio managers, trying to pick winners is instinctual. But the alternative, which is to simply avoid picking the losers, may in fact be a more reliable strategy.
By trying to pick winners, many portfolio managers end up chasing “sexy” names. “Unsexy,” though, is better than “sexy” when it comes to stocks. These stocks have high prices, and in order to justify those high prices, investors must have lofty expectations regarding what the future holds.
In order to value a stock, analysts and active managers make guesses about future cash flows and, based on those guesses, arrive at an intrinsic value for the stock. At best, this intrinsic value is grossly inaccurate, for the mere fact that the future is unknowable. At worst, this intrinsic value is biased because of the systematic behavioral biases that all humans have. Indeed, research in the field of behavioral finance has shown that both analysts and active managers have trouble controlling their emotions, leading them to become overconfident, rely on heuristics rather than rigorous analysis or fall victim to any number of other psychological influences.
It makes sense to focus on the unequivocal—the facts that aren’t in dispute. The most important such fact is the stock price itself. Rather than making guesses about the future and arriving at an intrinsic value, it makes much more sense to reverse the process, determining what performance is implied by the current stock price, whatever that price happens to be.
The result of this process is a number that represents the implicit assumptions of analysts and active managers who trade in the stock at the market price. I then ask myself, can management deliver this performance? To answer that question, I need to consider the company’s historical ability to deliver this performance.
By fitting the company’s past to a statistical distribution, I am able to calculate a probability that the company’s required business performance can be delivered. This probability, called the RBP probability, represents the likelihood that a company can deliver revenue growth sufficient to support the current stock price. Just as important, however, is the probability that management will not deliver the required revenue growth. I call this the behavioral risk indicator because to the extent a stock price is not supported by management’s historical ability to deliver performance, there are implicit assumptions of growth in excess of what management has shown it can deliver. It is assumptions like these in which behavioral biases manifest themselves.
As investors suffering from behavioral biases become willing to trade the stock at ever more irrational levels, the probability that management can deliver the performance to support the price falls and the behavioral risk indicator rises. By avoiding the stocks with the most behavioral risk, an investor can avoid the most losers.
Currently, stocks have generally high RBP probabilities and relatively low behavioral risk indicators. Among the S&P 500, for example, the average RBP probability and behavioral risk indicator (weighted by market capitalization) are 65% and 35% respectively. This means that, on average, a stock in the S&P 500 has a 65% chance of delivering the performance that its current stock price implies. This is rather high by historical standards. As recently as the spring of 2011, the weighted average RBP probability of the S&P 500 was only 42%.
Although broad market averages such as these are interesting, the strength of RBP probability and the behavioral risk indicator lies in its ability to distinguish between those stocks most likely to be winners and those most likely to be losers. If we can just avoid the losers, we are already in a position to beat the index, which is, after all, the goal of most active managers.