Differences of Opinion and the Cross Section of Stock Returns

TLDR: In this paper, the authors examine the role of dispersion in analysts' earnings forecasts in predicting the cross-section of future stock returns and find that stocks with higher dispersion have significantly lower future returns than similarly similar stocks.

Abstract: We provide evidence that stocks with higher dispersion in analysts’ earnings forecasts earn lower future returns than otherwise similar stocks. This effect is most pronounced in small stocks and stocks that have performed poorly over the past year. Interpreting dispersion in analysts’ forecasts as a proxy for differences in opinion about a stock, we show that this evidence is consistent with the hypothesis that prices will ref lect the optimistic view whenever investors with the lowest valuations do not trade. By contrast, our evidence is inconsistent with a view that dispersion in analysts’ forecasts proxies for risk. IN THIS PAPER WE ANALYZE THE ROLE of dispersion in analysts’ earnings forecasts in predicting the cross section of future stock returns. We find that stocks with higher dispersion in analysts’ earnings forecasts earn significantly lower future returns than otherwise similar stocks. In particular, a portfolio of stocks in the highest quintile of dispersion underperforms a portfolio of stocks in the lowest quintile of dispersion by 9.48 percent per year. This effect is strongest in small stocks, and stocks that have performed poorly over the past year. Our results are robust to various risk-adjustment techniques, and are inconsistent with an interpretation of dispersion in analysts’ forecasts as a proxy for risk. We postulate that dispersion in analysts’ earnings forecasts can be viewed as a proxy for differences of opinion among investors. Differences of opinion are typically modeled via dogmatic beliefs or asymmetric information sets, and have been included in numerous models that relax the standard