A Study of Portfolio Investment Decision Method Based on Neural Network

In the paper, a multi-objective programming of portfolio is proposed according to the assumption that total risk loss can be measured by the maximum of risk loss in all securities. After analyzing the risk preference of the investor and taking transaction cost function's linear approximation, the multi-objective programming model is transformed into simple-objective linear programming model. Based on neural network, a differential dynamical system for solving linear programming is constructed, and optimal portfolio decision is obtained.