Well-posedness and averaging principle for non-Gaussian McKean–Vlasov stochastic differential equations with locally Lipschitz coefficients

Abstract In this paper, we investigate a class of McKean–Vlasov stochastic differential equations (SDEs) with Lévy-type perturbations. We first establish the existence and uniqueness theorem for the solutions of the McKean–Vlasov SDEs by utilizing an Eulerlike approximation. Then, under suitable conditions, we demonstrate that the solutions of the McKean–Vlasov SDEs can be approximated by the solutions of the associated averaged McKean–Vlasov SDEs in the sense of mean square convergence. In contrast to existing work, a novel feature of this study is the use of a much weaker condition, locally Lipschitz continuity in the state variables, allowing for possibly superlinearly growing drift, while maintaining linearly growing diffusion and jump coefficients. Therefore, our results apply to a broader class of McKean–Vlasov SDEs.

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Publication Details

Journal
Advances in Applied Probability
Published
2025-09-09
DOI
https://doi.org/10.1017/apr.2025.10024
Primary Topic
Stochastic processes and financial applications
Type
article
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article

Well-posedness and averaging principle for non-Gaussian McKean–Vlasov stochastic differential equations with locally Lipschitz coefficients

Ying Chao, Jinqiao Duan, Pingyuan Wei, Ting Gao
Advances in Applied Probability
Stochastic processes and financial applications
article

Well-posedness and averaging principle for non-Gaussian McKean–Vlasov stochastic differential equations with locally Lipschitz coefficients

Ying Chao, Jinqiao Duan, Pingyuan Wei, Ting Gao
article en

Abstract

Abstract In this paper, we investigate a class of McKean–Vlasov stochastic differential equations (SDEs) with Lévy-type perturbations. We first establish the existence and uniqueness theorem for the solutions of the McKean–Vlasov SDEs by utilizing an Eulerlike approximation. Then, under suitable conditions, we demonstrate that the solutions of the McKean–Vlasov SDEs can be approximated by the solutions of the associated averaged McKean–Vlasov SDEs in the sense of mean square convergence. In contrast to existing work, a novel feature of this study is the use of a much weaker condition, locally Lipschitz continuity in the state variables, allowing for possibly superlinearly growing drift, while maintaining linearly growing diffusion and jump coefficients. Therefore, our results apply to a broader class of McKean–Vlasov SDEs.

Advances in Applied Probability
Southeast University (BD), Great Bay University, Huazhong University of Science and Technology (CN), Xi'an Jiaotong University (CN)
Openalex Percentile: Top 68%
Stochastic processes and financial applications
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