Sensitivity of functionals of McKean-Vlasov SDEs with respect to the initial distribution

We examine the sensitivity at the origin of the distributional robust optimization problem in the context of a model generated by a mean field stochastic differential equation. We adapt the finite dimensional argument developed by Bartl, Drapeau, Obloj, & Wiesel to our framework involving the infinite dimensional gradient of the solution of the mean field SDE with respect to its initial data. We revisit the derivation of this gradient process as previously introduced by Buckdahn, Li, Peng, & Rainer and we complement the existing properties so as to satisfy the requirement of our main result. We use the theory developed in the context of a mean-field systemic risk model by evaluating the sensitivity with respect to the initial distribution for the variance of the log-monetary reserve of a representative bank.