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A Class of Finite-Dimensional Numerically Solvable McKean-Vlasov Control Problems

Abstract : 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.
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Preprints, Working Papers, ...
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Contributor : Côme Huré <>
Submitted on : Wednesday, September 26, 2018 - 7:12:22 PM
Last modification on : Friday, April 10, 2020 - 5:13:33 PM
Document(s) archivé(s) le : Thursday, December 27, 2018 - 3:42:18 PM


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  • HAL Id : hal-01718751, version 2
  • ARXIV : 1803.00445


Alessandro Balata, Côme Huré, Mathieu Laurière, Huyên Pham, Isaque Pimentel. A Class of Finite-Dimensional Numerically Solvable McKean-Vlasov Control Problems. 2018. ⟨hal-01718751v2⟩



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