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A level-set approach to the control of state-constrained McKean-Vlasov equations: application to renewable energy storage and portfolio selection
Huyên Pham / Maximilien Germain / Xavier Warin
machine learning / numerical methodsResource overview

A level-set approach to the control of state-constrained McKean-Vlasov equations: application to renewable energy storage and portfolio selection

Paper2022

by Huyên Pham, Maximilien Germain, Xavier Warin

Tags
machine learningnumerical methodsoptimizationportfolio managementportfolio optimizationstochastic processes

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Suggested foundations for portfolio construction and optimisation and numerical methods. Specialist prerequisites vary by paper.

Before you read

  1. Eigenvalues and Covariance Matrices

    Understand the covariance structure of portfolio risk.

  2. Constrained and Convex Optimisation

    Identify the objective, constraints and conditions for an optimum.

  3. Vectors, Matrices and Linear Systems

    Read the linear algebra used to define a numerical problem.

Go further

  1. Mean-Variance Optimisation

    Construct allocations and examine sensitivity to estimated inputs.

  2. Portfolio Constraints

    Turn mathematical weights into feasible portfolio decisions.

  3. Calibration as an Inverse Problem

    Understand identifiability and fitted model parameters.

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