Fuzzy Multi-Objective Chance-Constrained Portfolio Optimization Under Uncertainty Considering Investment Return, Investment Risk, and Sustainability

Abstract

Effective portfolio management can increase business value by maximizing investment return, reducing possible risk and, making the best use of limited resources. Achieving this goal is constrained by multiple conflicting objectives and uncertainty, which are inherent in all projects. The investment return, investment risk, and sustainability have been simultaneously evaluated in this study by fuzzy multi-objective chance-constrained portfolio optimization, aligned with an organization’s strategic direction. Through the fuzzy chance-constrained programming, the obtained portfolio under uncertainties can be optimized with a specified confidence level imposed by decision makers. With such an NP-hard problem, a Genetic Algorithm (GA) is embedded in the developed decision support tool for sustainable investment portfolio selection and optimization. The applicability of the proposed approach and the constructed tool are illustrated through an example.