Abstract
In the last five years, extreme events such
as the COVID-19 pandemic and the Ukrainian crisis have highlighted the
importance of corporate social responsibility and sustainable principles.
Consequently, the investment process is changing toward more ethical choices.
In this context, we extend the classical optimization framework under the
cumulative prospect theory (CPT) in two directions. We first consider an agent
who maximizes a financial CPT-value function preselecting the assets to be
included in the portfolio based on their environmental, social, and governance
(ESG) scores. Then, we develop a bi-objective model that optimizes financial
and sustainable CPT-value functions at the same time. Numerical results
obtained on an investable universe from the constituents of the STOXX Europe
600 show that introducing ESG information improves the portfolio’s financial
performance.
JEL classification numbers: C63, G11, G17.
Keywords: Cumulative prospect theory, ESG scores, portfolio
optimization, genetic algorithm, European stock exchange.