Marc Arnaudon, Jean-Christophe Breton, Nicolas Privault
Published 2008-01-30Version 1
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.
On Weak Tail Domination of Random Vectors
Balancing sums of random vectors
Efficient simulation of density and probability of large deviations of sum of random vectors using saddle point representations
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