No Cover Image

Journal article 767 views 35 downloads

Singular McKean-Vlasov (reflecting) SDEs with distribution dependent noise

Xing Huang, Feng-yu Wang

Journal of Mathematical Analysis and Applications, Volume: 514, Issue: 1, Start page: 126301

Swansea University Author: Feng-yu Wang

  • 21HWc.pdf

    PDF | Accepted Manuscript

    ©2022 All rights reserved. All article content, except where otherwise noted, is licensed under a Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND)

    Download (311.65KB)

Check full text

DOI (Published version): 10.1016/j.jmaa.2022.126301

Abstract

By using Zvonkin's transformation and a two-step fixed point argument in distributions, the well-posedness and regularity estimates are derived for singular McKean-Vlasov SDEs with distribution dependent noise, where the drift contains a term growing linearly in space and distribution and a loc...

Full description

Published in: Journal of Mathematical Analysis and Applications
ISSN: 0022-247X
Published: Elsevier BV 2022
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa59935
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract: By using Zvonkin's transformation and a two-step fixed point argument in distributions, the well-posedness and regularity estimates are derived for singular McKean-Vlasov SDEs with distribution dependent noise, where the drift contains a term growing linearly in space and distribution and a locally integrable term independent of distribution, while the noise coefficient is weakly differentiable in space and Lipschitz continuous in distribution with respect to the sum of Wasserstein and weighted variation distances. The main results extend existing ones derived for noise coefficients either independent of distribution, or having nice linear functional derivatives in distribution. Singular reflecting SDEs with distribution dependent noise are also studied.
Keywords: McKean-Vlasov SDEs; Wasserstein distance; Two-step fixed point argument; Weighted variation distance
College: Faculty of Science and Engineering
Issue: 1
Start Page: 126301

Similar Items