We analyze a problem of optimal control of the Fokker-Planck equation with state constraints
in the Wasserstein space of probability measures. We give first-order necessary conditions …

Stochastic optimal control problems with constraints on the probability distribution of the final
output are considered. Necessary conditions for optimality in the form of a coupled system of …

Goal-based investing is concerned with reaching a monetary investment goal by a given
finite deadline, which differs from mean-variance optimization in modern portfolio theory. In …

Risk parity is an approach to investing that aims to balance risk evenly across assets within
a given universe. The aim of this study is to unify the most commonly-used approaches to …

We analyse mean-field stochastic control problems under constraints in law. The goal is to
characterize optimal solutions thanks to a mean-field game system of partial differential …

We analyse mean-field stochastic control problems under constraints in law. The goal is to
characterize optimal solutions thanks to a mean-field game system of partial differential …

Portfolio optimization is a key challenge in finance with the aim of creating portfolios
matching the investors' preference. The target distribution approach relying on the Kullback …

We propose two deep neural network-based methods for solving semi-martingale optimal
transport problems. The first method is based on a relaxation/penalization of the terminal …

The treatment of uncertainties is a fundamental problem in the financial context, and more
precisely in portfolio optimisation. The variables studied are often time dependent, with …

The present work is devoted to investigating portfolio optimization from different
perspectives. We consider continuous-time investment on a finite time horizon. In the first …