7 papers
Neural feedback approximation for stochastic control with degenerate diffusions: error estimates and numerical analysis
Olivier Bokanowski, Jean-François Chassagneux, Marco Scaratti +1
We study finite-horizon stochastic optimal control problems and approximate the resulting time-discrete formulation by a direct policy-learning problem over neural-network feedback…
Numerical Approximation for Path-Dependent McKean-Vlasov Control with Non-Asymptotic Error Estimates
Olivier Bokanowski, Jean-Francois Chassagneux, Xinyu Li +1
Path-dependent McKean--Vlasov (MKV) control models large interacting populations with history-dependent dynamics and costs. This paper develops a unified approximation-and-learning…
A note on the -convergence rate of the empirical measure of an ergodic -valued diffusion
Jean-Francois Chassagneux, Gilles Pagès
In this note, we consider a Stochastic Differential Equation under a strong confluence and Lipschitz continuity assumption of the coefficients. For the unique stationary solution,…
Stochastic Policy Gradient Methods in the Uncertain Volatility Model
Lokman A Abbas-Turki, Jean-François Chassagneux, Jean-Philippe Lemor +2
The multidimensional Uncertain Volatility Model leads to robust option pricing problems under joint volatility and correlation uncertainty. Their numerical resolution quickly becom…
Martingales On A Euclidean Manifold With A Boundary And Reflected BSDES In Non-Convex Domains
Marc Arnaudon, Jean-François Chassagneux, Sergey Nadtochiy +1
The purpose of this paper is twofold. First, we introduce the notion of a -martingale on a Euclidean manifold with a boundary (i.e., the closure of an open connected domain in…
Computing the invariant distribution of McKean-Vlasov SDEs by ergodic simulation
Jean-François Chassagneux, Gilles Pagès
We design a fully implementable scheme to compute the invariant distribution of ergodic McKean-Vlasov SDE satisfying a uniform confluence property. Under natural conditions, we pro…