A Socially Responsible Portfolio Selection Strategy

Author(s):  
Stefano Herzel ◽  
Marco Nicolosi
2005 ◽  
Vol 166 (1) ◽  
pp. 278-292 ◽  
Author(s):  
Xiao-Tie Deng ◽  
Zhong-Fei Li ◽  
Shou-Yang Wang

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
A. Garcia-Bernabeu ◽  
J. V. Salcedo ◽  
A. Hilario ◽  
D. Pla-Santamaria ◽  
Juan M. Herrero

Despite the widespread use of the classical bicriteria Markowitz mean-variance framework, a broad consensus is emerging on the need to include more criteria for complex portfolio selection problems. Sustainable investing, also called socially responsible investment, is becoming a mainstream investment practice. In recent years, some scholars have attempted to include sustainability as a third criterion to better reflect the individual preferences of those ethical or green investors who are willing to combine strong financial performance with social benefits. For this purpose, new computational methods for optimizing this complex multiobjective problem are needed. Multiobjective evolutionary algorithms (MOEAs) have been recently used for portfolio selection, thus extending the mean-variance methodology to obtain a mean-variance-sustainability nondominated surface. In this paper, we apply a recent multiobjective genetic algorithm based on the concept of ε-dominance called ev-MOGA. This algorithm tries to ensure convergence towards the Pareto set in a smart distributed manner with limited memory resources. It also adjusts the limits of the Pareto front dynamically and prevents solutions belonging to the ends of the front from being lost. Moreover, the individual preferences of socially responsible investors could be visualised using a novel tool, known as level diagrams, which helps investors better understand the range of values attainable and the tradeoff between return, risk, and sustainability.


2019 ◽  
Vol 11 (23) ◽  
pp. 6812 ◽  
Author(s):  
Tizian M. Fritz ◽  
Georg von Schnurbein

In their pursuit of value creation, charitable foundations are mission- rather than profit-driven. Therefore, foundations are also mission-driven investors. We explore the effects of mission-driven portfolio selection based on three model foundations, representing common fields of activity in Switzerland. Employing a moving block bootstrap approach, we simulate time series. Based on these model foundations and under the integration of qualitative company rating data, such as environmental, social, and governance-related characteristics (ESG), we find both negative and no significant financial effects of portfolio screening. However, screening portfolios substantially increases mission-driven portfolio quality. Additionally, screening reduces reputational risks and even leptokurtic return characteristics under special consideration of governance issues. After a joint analysis of financial and qualitative factors for portfolios with equity shares of 25% and 50%, we did find strong enough evidence to encourage foundations to implement negative and positive screening criteria. Additionally, we argue that without the integration of mission-based qualitative criteria, for instance, the involvement in business activities contradicting the foundation’s mission, an adequate evaluation of investment opportunities’ desirability is not feasible.


2016 ◽  
Vol 260 (1-2) ◽  
pp. 395-415 ◽  
Author(s):  
Sergio Ortobelli ◽  
Sebastiano Vitali ◽  
Marco Cassader ◽  
Tomáš Tichý

2012 ◽  
Vol 216 (2) ◽  
pp. 487-494 ◽  
Author(s):  
Enrique Ballestero ◽  
Mila Bravo ◽  
Blanca Pérez-Gladish ◽  
Mar Arenas-Parra ◽  
David Plà-Santamaria

Mathematics ◽  
2021 ◽  
Vol 9 (23) ◽  
pp. 3023
Author(s):  
Yahya Hanine ◽  
Youssef Lamrani Alaoui ◽  
Mohamed Tkiouat ◽  
Younes Lahrichi

In this study, we address the topic of sustainable and responsible portfolio investments (SRI). The selection of such portfolios is based, in addition to traditional financial variables, on environmental, social, and governance (ESG) criteria. The interest of our approach resides in allowing socially responsible (SR) portfolio investors to select their optimal portfolios by considering their individual preferences for each objective and simultaneous definition of the degrees of acceptance and rejection. In particular, we consider socially responsible portfolio selection as an optimization problem with multiple objectives before applying interactive intuitionistic fuzzy method to solve the portfolio optimization. The robustness of our approach is tested through an empirical study on the top 10 Stocks for ESG values worldwide.


2014 ◽  
Vol 52 (3) ◽  
pp. 126-137 ◽  
Author(s):  
José Manuel Cabello González ◽  
Francisco Ruiz ◽  
Méndez-Rodríguez Paz ◽  
Pérez Gladish Blanca

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