Optimal asset–liability management with constraints: A dynamic programming approach

This paper is devoted to the analysis of a discrete-time dynamic programming algorithm for the numerical solution of an optimal asset–liability management model with transaction costs and in presence of constraints. By exploiting the financial properties of the model, we propose an approximation method based on the classical dynamic programming algorithm, which reduces significantly the computational and storage requirements of the algorithm and avoids any artificial boundary condition. The regularity of the value function is used to estimate the global error introduced by the numerical procedure and to prove a convergence result.