  We prove convex ordering results for random vectors admitting a predictable
representation in terms of a Brownian motion and a non-necessarily independent
jump component. Our method uses forward-backward stochastic calculus and
extends previous results in the one-dimensional case. We also study a geometric
interpretation of convex ordering for discrete measures in connection with the
conditions set on the jump heights and intensities of the considered processes.
