Journal of Pure and Applied Mathematics: Advances and ApplicationsAuthor's: Guohua Chen
Pages: [39] - [57]
Received Date: June 15, 2010
Submitted by:
Vast pools of historical financial information are available on economies, industries, and individual companies that affect investor’s selection of appropriate portfolios. Fuzzy data provides a good tool to reflect investor’s opinions based on this information. A possibilistic mean variance safety-first portfolio selection model is developed to support investor’s 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 by using possibilistic theory. We propose a cutting plane algorithm to solve the programming problem. Two numerical examples are given to illustrate our approach.
portfolio selection, fuzzy data, safety-first, possibility theory, cutting plane algorithm.
