Large Deviation Principle for Neutral Type Mckean-Vlasov Stochastic Differential Equations

Fuente: arXiv
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Autores principales: Wang, Zhaohang, Hu, Junhao, Yuan, Chenggui
Formato: Preprint
Publicado: 2025
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author Wang, Zhaohang
Hu, Junhao
Yuan, Chenggui
author_facet Wang, Zhaohang
Hu, Junhao
Yuan, Chenggui
contents This paper investigates neutral-type McKean-Vlasov stochastic differential equations in which the drift and diffusion coefficients depend on both the segment process and its distribution. Under a one-sided Lipschitz condition on the drift coefficient, we establish a Freidlin-Wentzell-type large deviation principle for the solution process by using the extended contraction principle combined with an exponential approximation technique. Our results extend existing large deviation principles for McKean-Vlasov equations to the neutral case.
format Preprint
id arxiv_https___arxiv_org_abs_2511_19181
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Large Deviation Principle for Neutral Type Mckean-Vlasov Stochastic Differential Equations
Wang, Zhaohang
Hu, Junhao
Yuan, Chenggui
Probability
This paper investigates neutral-type McKean-Vlasov stochastic differential equations in which the drift and diffusion coefficients depend on both the segment process and its distribution. Under a one-sided Lipschitz condition on the drift coefficient, we establish a Freidlin-Wentzell-type large deviation principle for the solution process by using the extended contraction principle combined with an exponential approximation technique. Our results extend existing large deviation principles for McKean-Vlasov equations to the neutral case.
title Large Deviation Principle for Neutral Type Mckean-Vlasov Stochastic Differential Equations
topic Probability
url https://arxiv.org/abs/2511.19181