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Numerical approximation algorithms for pension funding

Thesis type
(Project) M.Sc.
Date created
2021-08-04
Authors/Contributors
Abstract
It is difficult to find closed-form optimal decisions in the context of pension plans. Therefore, we often need to rely on numerical algorithms to find approximate optimal decisions. In this report, we present two numerical algorithms that can be applied to solve optimal pension funding problems: the value function approximation and the grid value approximation. The value function approximation method applies to models with infinite time horizons and approximates the parameters of the value function by minimizing the difference between the true and approximate evaluations of the Hamilton–Jacobi–Bellman (HJB) equation. The grid value approximation method is used for models with finite time horizons. It works iteratively with backward and forward stages and approximates the optimal decisions directly without using the HJB equation. Numerical results are presented to compare approximate and true solutions for optimal contributions and share in risky assets for classic problems in the pension literature.
Document
Identifier
etd21495
Copyright statement
Copyright is held by the author(s).
Permissions
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Supervisor or Senior Supervisor
Thesis advisor: Bégin, Jean-François
Thesis advisor: Sanders, Barbara
Language
English
Download file Size
input_data\21539\etd21495.pdf 704.29 KB

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