10 citations · 35 across the 17 of their papers we have counts for
20 papers
Simultaneous upper and lower bounds of American-style option prices with hedging via neural networks
Ivan Guo, Nicolas Langrené, Jiahao Wu
In this paper, we introduce two novel methods to solve the American-style option pricing problem and its dual form at the same time using neural networks. Without applying nested M…
Superhedging duality for multi-action options under model uncertainty with information delay
Anna Aksamit, Ivan Guo, Shidan Liu +1
We consider the superhedging price of an exotic option under nondominated model uncertainty in discrete time in which the option buyer chooses some action from an (uncountable) act…
Optimal transport for model calibration
Ivan Guo, Gregoire Loeper, Jan Obloj +1
We provide a survey of recent results on model calibration by Optimal Transport. We present the general framework and then discuss the calibration of local, and local-stochastic, v…
On Stochastic Partial Differential Equations and their applications to Derivative Pricing through a conditional Feynman-Kac formula
Kaustav Das, Ivan Guo, Grégoire Loeper
The price of a financial derivative can be expressed as an iterated conditional expectation, where the inner term conditions on the future of an auxiliary process. We show that thi…
Deep Semi-Martingale Optimal Transport
Ivan Guo, Nicolas Langrené, Grégoire Loeper +1
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 cons…
Portfolio optimization with a prescribed terminal wealth distribution
Ivan Guo, Nicolas Langrené, Grégoire Loeper +1
This paper studies a portfolio allocation problem, where the goal is to prescribe the wealth distribution at the final time. We study this problem with the tools of optimal mass tr…