Incorporating environmental and social considerations into the portfolio optimization process

Over the last years, more and more companies face increased pressure by the public to provide information on how they perform on environmental, social and governance (ESG) issues. However, so far a very small number of studies have investigated optimal ways to construct socially responsible portfolios, either in the sense of the screening criteria used to narrow the investment universe, or the optimization process employed to determine the asset proportions. This study covers this gap by introducing an algorithm that first performs a screening to eliminate stocks from the investment universe that do not respect the imposed ESG constraint and then on the ESG compliant universe the portfolio optimization is performed. The novelty of the proposed approach lies in the fact that all underlying functionality of the algorithm, including the screening procedure and the imposed constraints, is facilitated seamlessly through a novel solution representation. Three multiobjective evolutionary algorithms have been adapted to work well with the proposed solution representation and the imposed constraints. The study by utilizing data from the FTSE-100 corporate social responsibility index finds that investors that are concerned about the environmental and social impact of their investments that must be ready to sacrifice a part of their welfare by selecting combinations of assets that provide subordinate return and risk combinations, compared to the available investment opportunities.