A significant multi-stage financial planning problem is posed as a stochastic program with decision rules. The decision rule - called dynamically balanced - requires the purchase and sale of assets at each time stage so as to keep constant asset proportions in the portfolio composition. It leads to a nonconvex objective function. We show that the rule performs well as compared with other dynamic investment strategies. We specialize a global optimization algorithm for this problem class - guaranteeing finite ε-optimal convergence. Computational results demonstrate the procedure's efficiency on a real-world financial planning problem. The tests confirm that local optimizers are prone to erroneously underestimate the efficient frontier. The concepts can be readily extended for other classes of long-term investment strategies.
All Science Journal Classification (ASJC) codes
- Economics and Econometrics
- Control and Optimization
- Applied Mathematics