Optimum Constrained Portfolio Rules in a Diffusion Market
Author:
Fernando J. Durrell a
| Affiliation: | a Department of Mathematics and Applied Mathematics, University of Cape Town, South Africa |
DOI:
10.1080/13504860600840061
Publication Frequency:
6 issues per year
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Abstract
A portfolio selection model is derived for diffusions where inequality constraints are imposed on portfolio security weights. Using the method of stochastic dynamic programming Hamilton-Jacobi-Bellman (HJB) equations are obtained for the problem of maximizing the expected utility of terminal wealth over a finite time horizon. Optimal portfolio weights are given in feedback form in terms of the solution of the HJB equations and its partial derivatives. An analysis of the no-constraining (NC) region of a portfolio is also conducted.
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| Keywords: Utility; stochastic dynamic programming; Hamilton-Jacobi-Bellman equation; constraints |
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