Mean-field stochastic differential equations driven by <i>G</i>-Brownian motion

This paper introduces a novel formulation of mean-field stochastic differential equations driven by G-Brownian motion. The proposed formulation generalises existing approaches within the G-framework and enables the study of Fréchet differentiability. Under non-Lipschitz conditions on the coefficients, we establish the existence and uniqueness of a solution for square-integrable stochastic initial data.

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Publication Details

Journal
Probability Uncertainty and Quantitative Risk
Published
2025-01-01
DOI
https://doi.org/10.3934/puqr.2025011
Citations
2
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
4.42
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article

Mean-field stochastic differential equations driven by G-Brownian motion

Thilo Meyer‐Brandis, K. Bollweg
2 citations
Probability Uncertainty and Quantitative Risk
Stochastic processes and financial applications
4.42
article

Mean-field stochastic differential equations driven by G-Brownian motion

Thilo Meyer‐Brandis, K. Bollweg
article en
2 citations

Abstract

This paper introduces a novel formulation of mean-field stochastic differential equations driven by G-Brownian motion. The proposed formulation generalises existing approaches within the G-framework and enables the study of Fréchet differentiability. Under non-Lipschitz conditions on the coefficients, we establish the existence and uniqueness of a solution for square-integrable stochastic initial data.

Probability Uncertainty and Quantitative RiskVol. 10(2)
LMU Klinikum (DE), Ludwig-Maximilians-Universität München (DE)
Openalex Percentile: Top 7%
Stochastic processes and financial applications
4.42
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