Convex concentration inequalities and forward-backward stochastic calculus

Given (Mt)t∈R+ and (M ∗ t )t∈R+ respectively a forward and a backward martingale with jumps and continuous parts, we prove that E[φ(Mt + M ∗ t )] is nonincreasing in t when φ is a convex function, provided the local characteristics of (Mt)t∈R+ and (M ∗ t )t∈R+ satisfy some comparison inequalities. We deduce convex concentration inequalities and deviation bounds for random variables admitting a predictable representation in terms of a Brownian motion and a non-necessarily independent jump component.