A computational intelligence method for solving a class of portfolio optimization problems

摘要

In this paper,we revisit themean-variance model of Markowitz and the construction of the risk-return efficient frontier. A few other models, such as themean absolute deviation, the minimax and maximin, and models with diagonal quadratic form as objectives, which use alternative metrics for risk are also introduced. Then we present a neurodynamic model for solving these kinds of problems. By employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact optimal solution of the original problem. The validity and transient behavior of the neural network are demonstrated by using several examples of portfolio selection.