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|Title:||Wasserstein distance estimates for stochastic integrals by forward-backward stochastic calculus||Authors:||Breton, Jean-Christophe
|Keywords:||Science::Mathematics||Issue Date:||2022||Source:||Breton, J. & Privault, N. (2022). Wasserstein distance estimates for stochastic integrals by forward-backward stochastic calculus. Potential Analysis, 56(1), 1-20. https://dx.doi.org/10.1007/s11118-020-09874-0||Project:||MOE2016-T2-1-036||Journal:||Potential Analysis||Abstract:||We prove Wasserstein distance bounds between the probability distributions of stochastic integrals with jumps, based on the integrands appearing in their stochastic integral representations. Our approach does not rely on the Stein equation or on the propagation of convexity property for Markovian semigroups, and makes use instead of forward-backward stochastic calculus arguments. This allows us to consider a large class of target distributions constructed using Brownian stochastic integrals and pure jump martingales, which can be specialized to infinitely divisible target distributions with finite Lévy measure and Gaussian components.||URI:||https://hdl.handle.net/10356/160989||ISSN:||0926-2601||DOI:||10.1007/s11118-020-09874-0||Schools:||School of Physical and Mathematical Sciences||Rights:||© 2020 Springer Nature B.V. All rights reserved.||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||SPMS Journal Articles|
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