In this paper, I propose a novel way to model sentiments in asset prices. Under this new representation, sentiments, or animal spirits, are sparked by exogenous shocks to beliefs, but feed on the uncertainty generated by imperfect information. Sentiments cause expec-tations to deviate from optimal, information-based estimates, with their magnitude de-pending on the amount of uncertainty: the higher the uncertainty, the larger the scope for psychological attitudes to affect expectations.Armed with this framework, I investigate the role of uncertainty on the transmission chan-nel from sentiment shocks to prices in a market with imperfect information and Bayesian agents. The main result that emerges is that the source of noise generating uncertainty, whether fundamental or informational, has important consequences for the effect of sen-timents. Specifically, while more informational noise always amplifies the impact of psy-chological shocks on prices, more fundamental noise can actually reduce such impact, de-pending on the elasticity of sentiments to uncertainty. This result implies that, for example, noise traders in stock markets can actually reduce the relevance of animal spirits for asset prices.(c) 2022 The Author. Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )
