Mean field game of mutual holding

We introduce a mean field model for optimal holding of a representative agent of her peers as a natural expected scaling limit from the corresponding N-agent model. The induced mean field dynamics appear naturally in a form which is not covered by standard McKean–Vlasov stochastic differential equations. We study the corresponding mean field game of mutual holding in the absence of common noise. Our first main result provides an explicit equilibrium of this mean field game, defined by a bang-bang control consisting in holding those competitors with positive drift coefficient of their dynamic value. We next use this mean field game equilibrium to construct (approximate) Nash equilibria for the corresponding N-player game. We also provide some numerical illustrations of our mean field game equilibrium which highlight some unexpected effects induced by our results.

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Publication Details

Journal
The Annals of Applied Probability
Published
2024-12-01
DOI
https://doi.org/10.1214/23-aap1993
Citations
3
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
1.62
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article

Mean field game of mutual holding

Mao Fabrice Djete, Nizar Touzi
3 citations
The Annals of Applied Probability
Stochastic processes and financial applications
1.62
article

Mean field game of mutual holding

Mao Fabrice Djete, Nizar Touzi
article en
3 citations

Abstract

We introduce a mean field model for optimal holding of a representative agent of her peers as a natural expected scaling limit from the corresponding N-agent model. The induced mean field dynamics appear naturally in a form which is not covered by standard McKean–Vlasov stochastic differential equations. We study the corresponding mean field game of mutual holding in the absence of common noise. Our first main result provides an explicit equilibrium of this mean field game, defined by a bang-bang control consisting in holding those competitors with positive drift coefficient of their dynamic value. We next use this mean field game equilibrium to construct (approximate) Nash equilibria for the corresponding N-player game. We also provide some numerical illustrations of our mean field game equilibrium which highlight some unexpected effects induced by our results.

The Annals of Applied ProbabilityVol. 34(6)
École Polytechnique (FR), Centre de Mathématiques Appliquées de l'École polytechnique (FR)
Openalex Percentile: Top 19%
Stochastic processes and financial applications
1.62
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