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This project presents an approach for implementing a policy iteration algorithm to solve the Hamilton–Jacobi–Bellman equation arising from the optimal mean–variance asset allocation problem for defined contribution pension plans, as studied by Wang and Forsyth (2008) (https://www.sciencedirect.com/science/article/abs/pii/S0165188909001602)

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Rik-17/Policy-Iteration-Algorithm-for-Mean-Variance-Asset-Allocation

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Policy-Iteration-Algorithm-for-Mean-Variance-Asset-Allocation

This project presents an approach for implementing a policy iteration algorithm to solve the Hamilton–Jacobi–Bellman equation arising from the optimal mean–variance asset allocation problem for defined contribution pension plans, as studied by Wang and Forsyth (2008) (https://www.sciencedirect.com/science/article/abs/pii/S0165188909001602).


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The repository contains one main file:

  • Policy_Iteration_Algorithm_Mean_Variance_Asset_Allocation.ipynb – Jupyter notebook containing the main code of the prject and a brief theoretical introduction to the mean-variance asset allocation problem for contribution pension plans in continuous time.

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This project presents an approach for implementing a policy iteration algorithm to solve the Hamilton–Jacobi–Bellman equation arising from the optimal mean–variance asset allocation problem for defined contribution pension plans, as studied by Wang and Forsyth (2008) (https://www.sciencedirect.com/science/article/abs/pii/S0165188909001602)

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