  We consider three different types of global uncertainty models for
discrete-time stochastic processes: measure-theoretic upper expectations,
game-theoretic upper expectations and axiomatic upper expectations. The last
two are known to be identical. We show that they coincide with
measure-theoretic upper expectations on two distinct domains: monotone
pointwise limits of finitary gambles, and bounded below Borel-measurable
variables. We argue that these domains cover most practical inferences, and
that therefore, in practice, it does not matter which model is used.

Probability