Numerical approximation algorithms for pension funding

Author: 
Date created: 
2021-08-04
Identifier: 
etd21495
Keywords: 
Numerical algorithm
Approximation
Optimal pension funding
Dynamic programming
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 type: 
Graduating extended essay / Research project
Rights: 
This thesis may be printed or downloaded for non-commercial research and scholarly purposes. Copyright remains with the author.
File(s): 
Supervisor(s): 
Jean-François Bégin
Barbara Sanders
Department: 
Science: Department of Statistics and Actuarial Science
Thesis type: 
(Project) M.Sc.
Statistics: