A class of finite-dimensional numerically solvable McKean-Vlasov control problems.

Authors
  • BALATA Alessandro
  • HURE Come
  • LAURIERE Mathieu
  • PHAM Huyen
  • PIMENTEL Isaque
Publication date
2019
Publication type
Journal Article
Summary We address a class of McKean-Vlasov (MKV) control problems with common noise, called polynomial conditional MKV, and extending the known class of linear quadratic stochastic MKV control problems. We show how this polynomial class can be reduced by suitable Markov embedding to finite-dimensional stochastic control problems, and provide a discussion and comparison of three probabilistic numerical methods for solving the reduced control problem: quantization, regression by control randomization, and regress later methods. Our numerical results are illustrated on various examples from portfolio selection and liquidation under drift uncertainty, and a model of interbank systemic risk with partial observation.
Publisher
EDP Sciences
Topics of the publication
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