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Risk-based strategies: the social responsibility of investment universes does matter

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  • Philippe Bertrand

    (CERGAM - Centre d'Études et de Recherche en Gestion d'Aix-Marseille - AMU - Aix Marseille Université - UTLN - Université de Toulon)

  • Vincent Lapointe

Abstract

In this article we extend the research on risk-based asset allocation strategies by exploring how using an SRI universe modifies properties of risk-based portfolios. We focus on four risk-based asset allocation strategies: the equally weighted, the most diversified portfolio, the minimum variance and the equal risk contribution. Using different estimators of the matrix of covariances, we apply these strategies to the EuroStoxx universe of stocks, the Advanced Sustainability Performance Index (ASPI) and the complement of the ASPI in the EuroStoxx universe from March 15, 2002 to May 1, 2012. We observe several impacts but one is particularly important in our mind. We observe that risk-based asset allocation strategies built on the entire universe, concentrate their solution on non-SRI stocks. Such risk-based portfolios are therefore under-weighted in socially responsible firms.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Philippe Bertrand & Vincent Lapointe, 2018. "Risk-based strategies: the social responsibility of investment universes does matter," Post-Print hal-01833080, HAL.
    • Handle: RePEc:hal:journl:hal-01833080
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    References listed on IDEAS

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    1. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    2. Bertrand, Philippe & Lapointe, Vincent, 2015. "How performance of risk-based strategies is modified by socially responsible investment universe?," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 175-190.
    3. Beck, Nathaniel & Katz, Jonathan N., 1995. "What To Do (and Not to Do) with Time-Series Cross-Section Data," American Political Science Review, Cambridge University Press, vol. 89(3), pages 634-647, September.
    4. Maillet, Bertrand & Tokpavi, Sessi & Vaucher, Benoit, 2015. "Global minimum variance portfolio optimisation under some model risk: A robust regression-based approach," European Journal of Operational Research, Elsevier, vol. 244(1), pages 289-299.
    5. Renneboog, Luc & Ter Horst, Jenke & Zhang, Chendi, 2008. "Socially responsible investments: Institutional aspects, performance, and investor behavior," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1723-1742, September.
    6. Hong, Harrison & Kacperczyk, Marcin, 2009. "The price of sin: The effects of social norms on markets," Journal of Financial Economics, Elsevier, vol. 93(1), pages 15-36, July.
    7. repec:dau:papers:123456789/4688 is not listed on IDEAS
    8. Maillet, Bertrand & Tokpavi, Sessi & Vaucher, Benoit, 2015. "Global minimum variance portfolio optimisation under some model risk: A robust regression-based approach," European Journal of Operational Research, Elsevier, vol. 244(1), pages 289-299.
    9. repec:dau:papers:123456789/14735 is not listed on IDEAS
    10. Markus Kitzmueller & Jay Shimshack, 2012. "Economic Perspectives on Corporate Social Responsibility," Journal of Economic Literature, American Economic Association, vol. 50(1), pages 51-84, March.
    11. Bertrand Maillet & Sessi Tokpavi & Benoît Vaucher, 2015. "Global minimum variance portfolio optimisation under some model risk : A robust regression-based approach," Post-Print hal-02312329, HAL.
    12. Scherer, Bernd, 2011. "A note on the returns from minimum variance investing," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 652-660, September.
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    Cited by:

    1. Gallucci, Carmen & Santulli, Rosalia & Lagasio, Valentina, 2022. "The conceptualization of environmental, social and governance risks in portfolio studies A systematic literature review," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    2. Prayut Jain & Shashi Jain, 2019. "Can Machine Learning-Based Portfolios Outperform Traditional Risk-Based Portfolios? The Need to Account for Covariance Misspecification," Risks, MDPI, vol. 7(3), pages 1-27, July.
    3. David Ardia & Guido Bolliger & Kris Boudt & Jean-Philippe Gagnon-Fleury, 2017. "The impact of covariance misspecification in risk-based portfolios," Annals of Operations Research, Springer, vol. 254(1), pages 1-16, July.
    4. 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.
    5. Rubesam, Alexandre, 2022. "Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market," Emerging Markets Review, Elsevier, vol. 51(PB).
    6. Chinnadurai Kathiravan & Murugesan Selvam & Sankaran Venkateswar & S. Balakrishnan, 2021. "Investor behavior and weather factors: evidences from Asian region," Annals of Operations Research, Springer, vol. 299(1), pages 349-373, April.

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