Dynamic Programming for Stochastic Control Problems with Expectation Constraints
par Chao Zhou

Abstract: We prove a dynamic programming principle for stochastic optimal control problems with expectation constraints by measurable selection approach. Since target problems, state constraints problems, quantile hedging and efficient hedging can all be reformulated into expectation constraints, we apply our results to prove the corresponding dynamic programming principle for these classes of stochastic control problems in a continuous but non-Markovian setting. This is a joint work with Yulong ZHOU.

An adverse selection approach to power pricing
par Nicolas Hernandez

Abstract : In this work, we study an optimal tarification problem for an electricity provider facing a distribution of clients having different appetences for electricity consumption. We formulate the problem in a non-standard problem of calculus of variations, which we solve explicitly in several cases. This is a joint work with Clémence Alasseur (EDF), Ivar Ekeland (Université Paris Dauphine), Romuald Elie (Université Marne-la-Vallée) and Dylan Possamaï (Université Paris Dauphine)