The performance of stochastic dynamic and fixed mix portfolio models

The purpose of this paper is to demonstrate how to evaluate stochastic programming models, and more specifically to compare two different approaches to asset liability management. The first uses multistage stochastic programming, while the other is astatic approach based on the so-called constant rebalancing or fixed mix. Particular attention is paid to the methodology used for the comparison. The two alternatives are tested over a large number of realistic scenarios created by means of simulation. We find that due to the ability of the stochastic programming model to adapt to the information in the scenario tree, it dominates the fixed mix approach.