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Do ESG investments improve portfolio diversification and risk management during times of uncertainty

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  • Ben Ameur, Hachmi
  • Ftiti, Zied
  • Louhichi, Wael

Abstract

This study aims to assess whether the statistical properties of ESG assets contribute to portfolio resilience, mitigate market volatility, and enhance diversification. Specifically, we focus on variations in the tails of the return distribution, highlighting potential asymmetries in risk exposure. We use weekly ESG and conventional indicesacross various regions from January 2017 to May 2023. Empirically, we augment themean-conditional value at risk (CVaR) optimisation technique, by introducing geopolitical risk as an exogenous factor. First,ESG indices enhance portfolio diversification while reducing exposure to extreme market movements and geopolitical uncertainty.Second, incorporating ESG assets is advantageous for both sustainable investment and effective financial risk management, presenting a viable option for investors pursuing both financial and sustainability objectives. Moreover, our results remainrobust under incremental CVaR approachand align with thetime-varying sensitivity of ESG and conventional indices to geopolitical risk, as shown bybeta dynamics analysis. Our findings offer several insights for investors diversifying their portfolio.

Suggested Citation

  • Ben Ameur, Hachmi & Ftiti, Zied & Louhichi, Wael, 2025. "Do ESG investments improve portfolio diversification and risk management during times of uncertainty," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 103(C).
    • Handle: RePEc:eee:intfin:v:103:y:2025:i:c:s1042443125000897
    DOI: 10.1016/j.intfin.2025.102199
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    Cited by:

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    2. Duong, An Thi Thuy, 2026. "ESG as a conditional risk buffer: Idiosyncratic volatility and tail losses across market regimes," Finance Research Letters, Elsevier, vol. 92(C).
    3. Trotta, Annarita & Piluso, Fabio & Strano, Eugenia & Ceraso, Danilo, 2026. "Exploring the climate resilience of ESG and conventional ETFs: Evidence from the European region," Research in International Business and Finance, Elsevier, vol. 84(C).

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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G01 - Financial Economics - - General - - - Financial Crises
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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