We propose a decomposition method for the solution of a dynamic portfolio optimization problem formulated as a multistage stochastic programming problem. The method leads to the problem time and nodal decomposition in its arborescent formulation applying a discrete version of the Pontryagin Maximum Principle. The solution of the decomposed problems is coordinated through a weighted fixed-point iterative scheme. The introduction of an optimization step in the weights choice at each iteration leads to a very efficient solution algorithm.
Time and nodal decomposition with implicit non-anticipativity constraints in dynamic portfolio optimization
BARRO, Diana;CANESTRELLI, Elio
2006-01-01
Abstract
We propose a decomposition method for the solution of a dynamic portfolio optimization problem formulated as a multistage stochastic programming problem. The method leads to the problem time and nodal decomposition in its arborescent formulation applying a discrete version of the Pontryagin Maximum Principle. The solution of the decomposed problems is coordinated through a weighted fixed-point iterative scheme. The introduction of an optimization step in the weights choice at each iteration leads to a very efficient solution algorithm.File in questo prodotto:
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