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On a Wasserstein-type distance between solutions to stochastic differential equations

Jocelyne Bion-Nadal 1 Denis Talay 2 
2 TOSCA - TO Simulate and CAlibrate stochastic models
CRISAM - Inria Sophia Antipolis - Méditerranée , IECL - Institut Élie Cartan de Lorraine : UMR7502
Abstract : In this paper, we introduce a Wasserstein-type distance on the set of the probability distributions of strong solutions to stochastic differential equations. This new distance is defined by restricting the set of possible coupling measures. We prove that it may also be defined by means of the value function of a stochastic control problem whose Hamilton–Jacobi–Bellman equation has a smooth solution, which allows one to deduce a priori estimates or to obtain numerical evaluations. We exhibit an optimal coupling measure and characterize it as a weak solution to an explicit stochastic differential equation, and we finally describe procedures to approximate this optimal coupling measure. A notable application concerns the following modeling issue: given an exact diffusion model, how to select a simplified diffusion model within a class of admissible models under the constraint that the probability distribution of the exact model is preserved as much as possible?
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Contributor : Denis Talay Connect in order to contact the contributor
Submitted on : Tuesday, December 4, 2018 - 11:13:25 AM
Last modification on : Friday, July 8, 2022 - 10:08:05 AM


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Jocelyne Bion-Nadal, Denis Talay. On a Wasserstein-type distance between solutions to stochastic differential equations. Annals of Applied Probability, Institute of Mathematical Statistics (IMS), 2019, 29 (3), pp.1609-1639. ⟨10.1214/18-AAP1423⟩. ⟨hal-01943863⟩



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