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Numerical solution of the Hamilton-Jacobi-Bellman formulation for continuous time mean variance asset allocation

  • Wang, J.
  • Forsyth, P.A.
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    We solve the optimal asset allocation problem using a mean variance approach. The original mean variance optimization problem can be embedded into a class of auxiliary stochastic linear-quadratic (LQ) problems using the method in Zhou and Li (2000) and Li and Ng (2000). We use a finite difference method with fully implicit timestepping to solve the resulting nonlinear Hamilton-Jacobi-Bellman (HJB) PDE, and present the solutions in terms of an efficient frontier and an optimal asset allocation strategy. The numerical scheme satisfies sufficient conditions to ensure convergence to the viscosity solution of the HJB PDE. We handle various constraints on the optimal policy. Numerical tests indicate that realistic constraints can have a dramatic effect on the optimal policy compared to the unconstrained solution.

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    Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

    Volume (Year): 34 (2010)
    Issue (Month): 2 (February)
    Pages: 207-230

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    Handle: RePEc:eee:dyncon:v:34:y:2010:i:2:p:207-230
    Contact details of provider: Web page: http://www.elsevier.com/locate/jedc

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    1. Markus LEIPPOLD & Fabio TROJANI & Paolo VANINI, 2002. "A Geometric Approach to Multiperiod Mean Variance Optimization of Assets and Liabilities," FAME Research Paper Series rp48, International Center for Financial Asset Management and Engineering.
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