  We formulate a probabilistic Markov property in discrete time under a dynamic
risk framework with minimal assumptions. This is useful for recursive solutions
to risk-sensitive versions of dynamic optimisation problems such as optimal
prediction, where at each stage the recursion depends on the whole future. The
property holds for standard measures of risk used in practice, and is
formulated in several equivalent versions including a representation via
acceptance sets, a strong version, and a dual representation.
