Sustainability and ESG. Optimization of portfolio capital allocation through ε-dominance and multi objective evolutionary genetic algorithm.

Abstract

In recent years, a new wave of sustainability has spread through the financial world and an increasing demand for virtuous investment have been raised to wealth managers, private equity and venture capitalist. After reviewing scientific literature and a brief introduction of ESG and sustainability factor into finance, the thesis explores the methodologies applied to efficiency optimization and portfolio capital allocation in MATLAB, 2020a. The aim of this research is to improve an existing algorithm, called ε-dominance, using parallelization and to introduce a third dimensional criteria into portfolio allocation, namely ESG, to align investors preferences and environmental, social and governance issues reduction.