Portfolio Optimization with Position Constraints : an Approximate Dynamic Programming Approach

We analyze dynamic portfolio choice problems using an approximate dynamic programming (ADP) algorithm. We extend the algorithm to the case of constraints on borrowing and implement a duality-based simulation procedure for estimating bounds on the true value function. We demonstrate that the ADP solution exhibits a high degree of accuracy in the considered examples, indicating that this is a promising approach to tackling challenging practical problems in the area of asset allocation and portfolio choice. We present additional evidence on the performance of the duality-based method for estimating performance of approximate portfolio rules, showing that it provides a valuable tool in conjunction with ADP-style algorithms. Subject Classifications: Finance: portfolio optimization. Dynamic Programming: optimal control, duality theory.

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