Socially responsible investing (SRI) has gained significant popularity, with investors and institutions increasingly prioritizing sustainability and ethical considerations. However, during crises such as the COVID-19 pandemic and the Russia–Ukraine conflict, investor preferences often shift toward conventional assets, raising the question of whether SRI is a true priority or a luxury for stable markets. This paper investigates the relationship between socially responsible funds (SRFs) and conventional indices (CIs) across different market conditions, assessing whether SRFsmaintain their appeal during financial distress. Using data from 2014 to 2024, we identify two volatility regimes via a Hidden Markov model and exploit copula models to assess tail dependence, cointegration tests to examine long-term price relationships, fuzzy clustering to classify assets by risk dynamics, and spillover analysis to measure asset interconnectedness. Our findings showthat SRF and CI performance converge in performance during market turmoil, suggesting that SRI loses prominence in unstable conditions. Moreover, systemic, geographic, and issuer-specific risks overshadow ESG-related factors, challenging the notion of SRI as a resilient investment strategy in turbulent markets.
Socially responsible investing: a fair-weather commitment / Stefanelli, Kevyn; Storani, Saverio. - In: ANNALS OF OPERATIONS RESEARCH. - ISSN 1572-9338. - (2025).
Socially responsible investing: a fair-weather commitment
Kevyn Stefanelli
;Saverio Storani
2025
Abstract
Socially responsible investing (SRI) has gained significant popularity, with investors and institutions increasingly prioritizing sustainability and ethical considerations. However, during crises such as the COVID-19 pandemic and the Russia–Ukraine conflict, investor preferences often shift toward conventional assets, raising the question of whether SRI is a true priority or a luxury for stable markets. This paper investigates the relationship between socially responsible funds (SRFs) and conventional indices (CIs) across different market conditions, assessing whether SRFsmaintain their appeal during financial distress. Using data from 2014 to 2024, we identify two volatility regimes via a Hidden Markov model and exploit copula models to assess tail dependence, cointegration tests to examine long-term price relationships, fuzzy clustering to classify assets by risk dynamics, and spillover analysis to measure asset interconnectedness. Our findings showthat SRF and CI performance converge in performance during market turmoil, suggesting that SRI loses prominence in unstable conditions. Moreover, systemic, geographic, and issuer-specific risks overshadow ESG-related factors, challenging the notion of SRI as a resilient investment strategy in turbulent markets.| File | Dimensione | Formato | |
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