Optimum Constrained Portfolio Rules in a Diffusion Market

Fernando Durrell

Applied Mathematical Finance, 2006, vol. 13, issue 4, 285-307

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.

Keywords: Utility; stochastic dynamic programming; Hamilton-Jacobi-Bellman equation; constraints (search for similar items in EconPapers)
Date: 2006
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DOI: 10.1080/13504860600840061

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