Fuzzy Data Decision Support in Portfolio Selection: a Possibilistic Safety-first Model

Vast pools of historical financial information are available on economies, industry, and individual companies that affect investors’ selection of appropriate portfolios. Fuzzy data provides a good tool to reflect investors’ opinions based on this information. A possibilistic mean variance safety-first portfolio selection model is developed to support investors’ decision making, to take into consideration this fuzzy information. The possibilistic-programming problem can be transformed into a linear optimal problem with an additional quadratic constraint using possibilistic theory. We propose a cutting plane algorithm to solve the programming problem. A numerical example is given to illustrate our approach.