Information Aggregation Under Ambiguity: Theory and Experimental Evidence

We study information aggregation in a dynamic trading model with partially informed and ambiguity averse traders. We show theoretically that separable securities, introduced by Ostrovsky (2012) in the context of Subjective Expected Utility, no longeraggregate information if some traders have imprecise beliefs and are ambiguity averse. Moreover, these securities are prone to manipulation, as the degree of information aggregation can be influenced by the initial price, set by the uninformed market maker. These observations are also confirmed in our experiment, using prediction markets. We define a new class of strongly separable securities which are robust to the above considerations, and show that they characterize information aggregation in both strategic and non-strategic environments. We derive several theoretical predictions, which we are able to confirm in the lab.