The Real Dogs of the Dow

Abstract

Kahneman and Tversky argue that regression to the mean is a pervasive but subtle statistical principle that is often misunderstood or insufficiently appreciated. The authors investigate this phenomenon by looking at changes in the Dow Jones Industrial Average. Regression to the mean suggests that companies taken out of the Dow may not be as bad as their current predicaments indicate, and the companies that replace them may not be as terrific as their current records suggest. If investors are insufficiently aware of this statistical phenomenon, stock prices may be too low for the former and too high for the latter—mistakes that will be corrected when these companies regress to the mean. Thus, stocks taken out of the Dow may outperform the stocks that replace them. The authors test this hypothesis with the 50 substitutions made since the Dow expanded to 30 stocks in 1928.