It is known that there is a duality relation between risk-averse and distributionally robust approaches to stochastic programming. An extension from the static to dynamic (multistage) settings is not straightforward. This involves such basic concepts as conditional counterparts of risk-averse/distributionally robust functionals, dynamic equations and time consistency of nested formulations of multistage stochastic programs. In this talk we present a point of view on these topics in the frameworks of Stochastic Programming, Stochastic Optimal Control and MDP.