3 papers
stat.ML2024
A new Input Convex Neural Network with application to options pricing
Vincent Lemaire, Gilles Pagès, Christian Yeo
We introduce a new class of neural networks designed to be convex functions of their inputs, leveraging the principle that any convex function can be represented as the supremum of…
q-fin.MF2024
Convex ordering for stochastic control: the (path dependent) swing contracts case
Gilles Pagès, Christian Yeo
We investigate propagation of convexity and convex ordering on a typical discrete-time stochastic optimal control problem, namely the pricing of swing option. The dynamics of the u…
stat.ML2024
Deep multitask neural networks for solving some stochastic optimal control problems
Christian Yeo
Most existing neural network-based approaches for solving stochastic optimal control problems using the associated backward dynamic programming principle rely on the ability to sim…