American options with multiple priors in continuous time

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 of incomplete information of the market data leading to model uncertainty. Using the theory of (reflected) backward stochastic differential equations we are able to solve the optimal stopping problem under multiple priors and identify the particular worst-case scenario in terms of the worst-case prior. By means of the analysis of exotic American options we highlight the main difference to classical single prior models. This is characterized by a resulting endogenous dynamic structure of the worst-case scenario generated by model adjustments of the agent due to particular occurring events that change the agent's beliefs.