  Sustainable finance, which integrates environmental, social and governance
(ESG) criteria on financial decisions rests on the fact that money should be
used for good purposes. Thus, the financial sector is also expected to play a
more important role to decarbonise the global economy. To align financial flows
with a pathway towards a low-carbon economy, investors should be able to
integrate in their financial decisions additional criteria beyond return and
risk to manage climate risk. We propose a tri-criterion portfolio selection
model to extend the classical Markowitz mean-variance approach in order to
include investors preferences on the portfolio carbon risk exposure as an
additional criterion. To approximate the 3D Pareto front we apply an efficient
multi-objective genetic algorithm called ev-MOGA which is based on the concept
of e-dominance. Furthermore, we introduce an a posteriori approach to
incorporate the investor's preferences into the solution process regarding
their sustainability preferences measured by the carbon risk exposure and
his/her loss-adverse attitude. We test the performance of the proposed
algorithm in a cross section of European SRI open-end funds to assess the
extent to which climate related risk could be embedded in the portfolio
according to the investor's preferences.
