Topics on mean-field and McKean-Vlasov backward stochastic differential equations, and the backward propagation of chaos
Abstract
Backward propagation of chaos is referring to the phenomenon where the behavior of interactive agents (or particles), described from a system of backward stochastic differential equations (BSDEs), progressively resembles the one as if they where independent, while the number of agents increases to infinity. This thesis aims to study backward propagation of chaos in a setting as general as possible, and also to introduce the notion of stability of backward propagation of chaos. Here stability is understood as the continuity property of backward propagation of chaos with respect to the data sets. The interaction between the different agents is expressed through their empirical measure. In order to identify the asymptotic behaviour of the mean-field systems of BSDEs we are going to use the McKean–Vlasov BSDE. We consider two instances of backward propagation of chaos, when we have path dependence in the generator and when we have the usual instantaneous dependence. So, we begin by establi ...
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