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Finding socially responsible portfolios close to conventional ones

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  • Calvo, Clara
  • Ivorra, Carlos
  • Liern, Vicente

Abstract

An increasing number of investors are interested in sustainable, responsible and impact investment (SRI). However, there is a concern about the possible financial sacrifice associated to this kind of investments. The design of Decision Support Systems assisting socially responsible investors in their investment decisions can contribute to stimulate SRI. In this paper the financial content of a portfolio selection model is discussed in order to justify that it can be integrated into a Decision Support System designed for investors interested in socially responsible investment but initially reluctant to pay a financial cost in exchange for increasing the social responsibility of their portfolios. Investor's preferences are incorporated by means of adequate parameters of a utility function designed for handling subjective criteria in a reliable way. We show that these parameters can be determined by means of a non-technical questionnaire addressed to the investor, and that they can faithfully reflect his/her preferences about achieving an SRI performance as good as possible without going too far from the financial efficient frontier or even from an initial choice of an efficient pair of financial risk and return. The proposed procedure is illustrated by means of two examples. A first small example illustrates the decision making process followed in order to obtain the required parameters from the investor. The second example is intended to show how the proposed procedure can be applied to real world problems including financial constraints which are hard from a computational point of view.

Suggested Citation

  • Calvo, Clara & Ivorra, Carlos & Liern, Vicente, 2015. "Finding socially responsible portfolios close to conventional ones," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 52-63.
  • Handle: RePEc:eee:finana:v:40:y:2015:i:c:p:52-63
    DOI: 10.1016/j.irfa.2015.03.014
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    2. Bilbao-Terol, Amelia & Álvarez-Otero, Susana & Bilbao-Terol, Celia & Cañal-Fernández, Verónica, 2017. "Hedonic evaluation of the SRI label of mutual funds using matching methodology," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 213-227.
    3. K. Liagkouras & K. Metaxiotis & G. Tsihrintzis, 2022. "Incorporating environmental and social considerations into the portfolio optimization process," Annals of Operations Research, Springer, vol. 316(2), pages 1493-1518, September.
    4. Eduardo C. Garrido-Merch'an & Gabriel Gonz'alez Piris & Maria Coronado Vaca, 2023. "Bayesian Optimization of ESG Financial Investments," Papers 2303.01485, arXiv.org.
    5. Nicholas Apergis & Vassilios Babalos & Christina Christou & Rangan Gupta, 2015. "Identifying Asymmetries between Socially Responsible and Conventional Investments," Working Papers 201537, University of Pretoria, Department of Economics.
    6. Contreras-Pacheco, Orlando E. & Barbosa, Alejandra E., 2016. "Financiación al Desarrollo Sostenible a través de Inversiones de Impacto - Hacia la Construcción de un Framework Teórico [Financing Sustainable Development through Impact Investments - Towards a Th," MPRA Paper 88139, University Library of Munich, Germany.
    7. Yahya Hanine & Youssef Lamrani Alaoui & Mohamed Tkiouat & Younes Lahrichi, 2021. "Socially Responsible Portfolio Selection: An Interactive Intuitionistic Fuzzy Approach," Mathematics, MDPI, vol. 9(23), pages 1-13, November.
    8. Ming-Lang Tseng & Phan Anh Tan & Shiou-Yun Jeng & Chun-Wei Remen Lin & Yeneneh Tamirat Negash & Susilo Nur Aji Cokro Darsono, 2019. "Sustainable Investment: Interrelated among Corporate Governance, Economic Performance and Market Risks Using Investor Preference Approach," Sustainability, MDPI, vol. 11(7), pages 1-15, April.
    9. Panos Xidonas & Eric Essner, 2024. "On ESG Portfolio Construction: A Multi-Objective Optimization Approach," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 21-45, January.

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