Ambiguity, Investor Disagreement, and Expected Stock Returns

Abstract

I set up a model in which two types of ambiguity-averse traders disagree on how to interpret a public signal. When traders first observe contradicting interpretations of the signal, they don't know whether to attribute the clash of opinions to different information processing or to information asymmetry, and thus treat the other type's interpretation as an ambiguous signal. This ambiguity decreases over time as traders gradually learn or form beliefs about the other type's interpretation. The model predicts a positive relation between investor disagreement (ID) and expected stock return, given that the public signal is very imprecise. Also, ID can be measured using the negative correlation coefficient between trading volume and absolute price change. I find that stocks in the highest ID decile outperform stocks in the lowest ID decile by 8.7 percent annually, adjusted for exposures to the market return as well as size, value, momentum, and liquidity factors. In addition, stocks with high ID prior to the earnings announcement experience significantly higher returns around the earnings announcement compared to stocks with low ID.