Asset pricing under smooth ambiguity in continuous time

Abstract We study asset pricing implications of a revealing and tractable formulation smooth ambiguity investor preferences in continuous-time environment. Investors do not observe hidden Markov state instead make inferences about this using past data. show that distribution alters decisions equilibrium prices. Our allows us to apply recursive filtering Hamilton–Jacobi–Bellman methods solve the modified decision problem. Using such methods, we how characterizations portfolio allocations local uncertainty-return tradeoffs change when investors are ambiguity-averse.