Actuarial science

Project portfolio management

Financial market

Portfolio

Selection (genetic algorithm)

Economics

Computer science

Mathematical optimization

Market liquidity

Modern portfolio theory

Application portfolio management

Operations research

Mathematics

Management

Stock exchange

Fuzzy logic

Project management

Artificial intelligence

Portfolio optimization

Finance

Goal programming

Order (exchange)

Expert Systems with Applications

In the financial portfolio selection (FPS) problem, the investor usually considers several conflicting objectives such as return, risk, and liquidity. The values of these objectives are often provided by the investor who keeps inaccurate information and states his/her considerations subjectively. In order to deal with such a situation, we will propose a combined possibility theory and goal programming model (GP) allowing to consider tradeoffs between investor's preferences regarding several incommensurable objectives in an imprecise environment. The aim of this paper is to formulate a multi-objective FPS approach involving fuzzy parameters, where possibility distributions are given by fuzzy numbers from the information supplied by the decision-making environment (investor, analyst, financial market environment, etc.). Moreover, the investor's preferences will be explicitly incorporated through the concept of satisfaction functions. The proposed model is applied to FPS within the Tunisian stock exchange market and discussed in comparison with other portfolio selection procedures.

Multi-objective imprecise programming for financial portfolio selection with fuzzy returns