Ambiguity in the Cross-Section of Expected Returns: An Empirical Assessment
This paper estimates and tests the smooth ambiguity model of Klibanoff, Marinacci, and Mukerji (2005, 2009) based on stock market data. We introduce a novel methodology to estimate the conditional expectation which characterizes the impact of a decision maker's ambiguity attitude on asset prices. Our point estimates of the ambiguity parameter are between 25 and 40, whereas our risk aversion estimates are considerably lower. The substantial difference indicates that market participants are ambiguity averse. Furthermore, we evaluate if ambiguity aversion helps explaining the cross-section of expected returns. Compared with Epstein and Zin (1989) preferences, we find that incorporating ambiguity into the decision model improves the fit to the data while keeping relative risk aversion at more reasonable levels.