3 citations · 3 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
An analysis of linear regression and neural networks approximation for the pricing of swing options
Christian Yeo
Linear regression, firstly introduced for the pricing of American-style options, has since been expanded to include swing options pricing. Swing options price may be viewed as the…
Swing contract pricing: with and without Neural Networks
Vincent Lemaire, Gilles Pagès, Christian Yeo
We propose two parametric approaches to evaluate swing contracts with firm constraints. Our objective is to define approximations for the optimal control, which represents the amou…