Corpus ID: 235790648

Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance

@article{Carmona2021DeepLF,
  title={Deep Learning for Mean Field Games and Mean Field Control with Applications to Finance},
  author={Ren{\'e} A. Carmona and Mathieu Lauri{\`e}re},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.04568}
}
Financial markets and more generally macro-economic models involve a large number of individuals interacting through variables such as prices resulting from the aggregate behavior of all the agents. Mean field games have been introduced to study Nash equilibria for such problems in the limit when the number of players is infinite. The theory has been extensively developed in the past decade, using both analytical and probabilistic tools, and a wide range of applications have been discovered… Expand

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