COMPARISON OF MEAN VARIANCE LIKE STRATEGIES FOR OPTIMAL ASSET ALLOCATION PROBLEMS
J. Wang () and
P. A. Forsyth ()
Additional contact information J. Wang: David R. Cheriton School of Computer Science, University of Waterloo, Waterloo ON, N2L 3G1, Canada
P. A. Forsyth: David R. Cheriton School of Computer Science, University of Waterloo, Waterloo ON, N2L 3G1, Canada
We determine the optimal dynamic investment policy for a mean quadratic variation objective function by numerical solution of a nonlinear Hamilton-Jacobi-Bellman (HJB) partial differential equation (PDE). We compare the efficient frontiers and optimal investment policies for three mean variance like strategies: pre-commitment mean variance, time-consistent mean variance, and mean quadratic variation, assuming realistic investment constraints (e.g. no bankruptcy, finite shorting, borrowing). When the investment policy is constrained, the efficient frontiers for all three objective functions are similar, but the optimal policies are quite different.