Risk-averse optimal stopping under ambiguity and partial information

Randall Martyr, John Moriarty

Published 2019-10-09Version 1

We obtain structural results for non-Markovian optimal stopping problems in discrete time when the decision maker is risk averse and has partial information about the stochastic sequences generating the costs. Time consistency is ensured in the problem by the aggregation of a sequence of conditional risk mappings, and the framework allows for model ambiguity. A reflected backward stochastic difference equation is used to characterise the value function and optimal stopping times.