Mean-Entropy Models for Fuzzy Portfolio Selection

This short paper proposes two types of credibility-based fuzzy mean-entropy models. In the short paper, entropy is used as the measure of risk. The smaller the entropy value is, the less uncertainty the portfolio return contains, and thus, the safer the portfolio is. Furthermore, as a measure of risk, entropy is free from reliance on symmetrical distributions of security returns and can be computed from nonmetric data. In addition, the short paper compares the fuzzy mean-variance model with the fuzzy mean-entropy model in two special cases and presents a hybrid intelligent algorithm for solving the proposed models in general cases. To illustrate the effectiveness of the proposed algorithm, the short paper also provides two numerical examples.