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 .
We obtain structural results for non-Markovian optimal switching problems in discrete time on an infinite horizon, when the decision maker is risk averse and has partial information about the stochastic sequences generating the costs , and establish existence and uniqueness of solutions for the associated reflected backward stochastic difference equations. An example illustrates the interaction between partial information and risk aversion in the special case of optimal stopping problems .
R
stopping
switching
A
on an infinite horizon,
R
. 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
, and establish existence and uniqueness of solutions for the associated
R
equation is used to characterise the value function and optimal stopping times
equations. An example illustrates the interaction between partial information and risk aversion in the special case of optimal stopping problems