Cluster analysis for ethical portfolio optimization problem using fuzzy chance constrained programming

Choosing the greatest investment possibilities to maximize the value of one’s stock investment has always been one of the primary concerns of investors. However, issues like human rights, and business ethics, are at the forefront of the public and political conversation in today’s world of globalization and interdependence. Many financial experts, policymakers, and economic and social researchers view Islamic finance as a potential solution to prevent future crises. Consequently, there is a need for new models to facilitate this investment approach. In this study, we propose a new hybrid approach to portfolio selection which combines multiple methodologies like investor topology, cluster analysis, preference modeling and fuzzy multi-objective programming strategy. The proposed model is applied on 9 Tunisian mutual funds including conventional and ethical/Islamic funds in Tunisian financial market. The findings reveal that higher expected losses and greater proportions of ethical or Islamic stocks in a portfolio translate into better portfolio performance as measured by the Sharpe ratio. These findings confirm our hypothesis that ethical investments should be taken into account when developing investment strategies for conventional investors.