This paper studies sequential information acquisition by an ambiguity-averse decision maker (DM), who decides how long to collect information before taking an irreversible action. The agent optimizes against the worst-case belief and updates prior by prior. We show that the consideration of...

We consider optimal stopping problems for ambiguity averse decision makers with multiple priors. In general, backward induction fails. If, however, the class of priors is time-consistent, we establish a generalization of the classical theory of optimal stopping. To this end, we develop first...

We analyze several exotic options of American style in a multiple prior setting and study the optimal exercise strategy from the perspective of an ambiguity averse buyer in a discrete time model of Cox-Ross-Rubinstein style. The multiple prior model relaxes the assumption of a known distribution...

We develop a theory of optimal stopping problems under ambiguity in continuous time. Using results from (backward) stochastic calculus, we characterize the value function as the smallest (nonlinear) supermartingale dominating the payoff process. For Markovian models, we derive an adjusted...

We investigate American options in a multiple prior setting of continuous time and determine optimal exercise strategies form the perspective of an ambiguity averse buyer. The multiple prior setting relaxes the presumption of a known distribution of the stock price process and captures the idea...

This paper explicitly solves, in closed form, the optimal consumption and port folio choice for an ambiguity averse investor in a Merton-type two assets economy where a risk premium follows a mean-reverting process. The investor's preferences are represented by the recursive multiple priors...

We propose a novel one-sector stochastic growth model, where producitivity growth follows a Markov-switching process with two regimes, and where households have generalized recursive smooth ambiguity preferences. The adopted class of preferences permits a three-way separation of risk aversion,...

I develop a stochastic growth model with production where there is a hidden state governing productivity growth regimes, and the hidden state evolves according to a Markov chain. Economic agents learn about the hidden state and display ambiguity aversion in the spirit of Klibanoff et al. (2005)....

We propose a model of hedging and investment with ambiguity aversion in an incomplete financial market. We show that the agent's worst-case belief depends upon the payoff of the derivative to be hedged. Thus, we identify situations where one can distinguish ambiguity averse agents from...

We examine a production-based asset pricing model with an unobservable mean growth rate ollowing a two-state Markov chain and with an ambiguity averse representative agent. Our model requires a low coefficient of relative risk aversion to produce: (i) a high equity premium and volatile equity...