5 papers
Deep kernel hedging
Jean-Loup Dupret, Donatien Hainaut, Edouard Motte
We introduce a deep kernel hedging framework that combines the flexibility of deep learning with the structural inductive bias of kernel methods. The hedging functional is restrict…
INEUS: Iterative Neural Solver for High-Dimensional PIDEs
Jean-Loup Dupret, Davide Gallon, Patrick Cheridito
In this paper, we introduce INEUS, a meshfree iterative neural solver for partial integro-differential equations (PIDEs). The method replaces the explicit evaluation of nonlocal ju…
General bounds on functionals of the lifetime under life table constraints in a joint actuarial-financial framework
Jean-Loup Dupret, Edouard Motte
In life insurance, life tables provide survival probabilities at integer ages but leave the distribution of deaths within each year unspecified. This incompleteness is particularly…
ABIDES-MARL: A Multi-Agent Reinforcement Learning Environment for Optimal Execution with Endogenous Liquidity
Patrick Cheridito, Jean-Loup Dupret, Zhexin Wu
Classical optimal execution models treat market impact as a pre-specified, exogenous process. However, when market makers adapt strategically, this assumption becomes a structural…
Deep Learning for Continuous-Time Stochastic Control with Jumps
Patrick Cheridito, Jean-Loup Dupret, Donatien Hainaut
In this paper, we introduce a model-based deep-learning approach to solve finite-horizon continuous-time stochastic control problems with jumps. We iteratively train two neural net…