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

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 stoc...

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Main Authors: Balata Alessandro, Huré Côme, Laurière Mathieu, Pham Huyên, Pimentel Isaque
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:ESAIM: Proceedings and Surveys
Subjects:
Online Access:https://www.esaim-proc.org/articles/proc/pdf/2019/01/proc196506.pdf
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author Balata Alessandro
Huré Côme
Laurière Mathieu
Pham Huyên
Pimentel Isaque
author_facet Balata Alessandro
Huré Côme
Laurière Mathieu
Pham Huyên
Pimentel Isaque
author_sort Balata Alessandro
collection DOAJ
description 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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spelling doaj.art-df30f085c95a478ca0699f052fc777732023-01-02T09:09:22ZengEDP SciencesESAIM: Proceedings and Surveys2267-30592019-01-016511414410.1051/proc/201965114proc196506A class of finite-dimensional numerically solvable McKean-Vlasov control problemsBalata AlessandroHuré CômeLaurière MathieuPham HuyênPimentel IsaqueWe 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.https://www.esaim-proc.org/articles/proc/pdf/2019/01/proc196506.pdfmckean-vlasov controlpolynomial classquantizationregress-latercontrol randomization
spellingShingle Balata Alessandro
Huré Côme
Laurière Mathieu
Pham Huyên
Pimentel Isaque
A class of finite-dimensional numerically solvable McKean-Vlasov control problems
ESAIM: Proceedings and Surveys
mckean-vlasov control
polynomial class
quantization
regress-later
control randomization
title A class of finite-dimensional numerically solvable McKean-Vlasov control problems
title_full A class of finite-dimensional numerically solvable McKean-Vlasov control problems
title_fullStr A class of finite-dimensional numerically solvable McKean-Vlasov control problems
title_full_unstemmed A class of finite-dimensional numerically solvable McKean-Vlasov control problems
title_short A class of finite-dimensional numerically solvable McKean-Vlasov control problems
title_sort class of finite dimensional numerically solvable mckean vlasov control problems
topic mckean-vlasov control
polynomial class
quantization
regress-later
control randomization
url https://www.esaim-proc.org/articles/proc/pdf/2019/01/proc196506.pdf
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