ESG investing, Systemic risk, Market impact, Network, Indirect contagion
We consider a network of equity mutual funds characterized by different levels of compliance with Environmental, Social, and Governance (ESG) aspects. We measure the impact of portfolio liquidation in a stress scenario on funds with different ESG ratings. Fire-sales spillover from portfolio liquidation propagates from one fund to another through indirect contagion mediated by common asset holdings. The analysis is conducted quarterly from March 2016 through June 2018 using daily data from different sources at the fund and firm levels. Our estimation strategy relies on a network analysis where funds are not taken as stand- alone entities but are interconnected components of a unified system. We find evidence that the relative market value loss of the High ESG ranked funds is lower than the loss experienced by the Low ESG ranked counterparts in the time span with lower volatility. In the higher-volatility period there is not always a clear dominance of one class over another. Results are robust when controlling for size and for feedback effects, and for different model specifications. Our analysis offers new insights to both asset managers and policymakers to exploit the aggregate effect of portfolio diversification related to the system as a whole.
Cerqueti, R., Ciciretti, R., Dalo, A., Nicolosi, M. (2021). ESG investing: A chance to reduce systemic risk. JOURNAL OF FINANCIAL STABILITY, 54 [10.1016/j.jfs.2021.100887].
ESG investing: A chance to reduce systemic risk
Ciciretti R.;
2021-05-18
Abstract
We consider a network of equity mutual funds characterized by different levels of compliance with Environmental, Social, and Governance (ESG) aspects. We measure the impact of portfolio liquidation in a stress scenario on funds with different ESG ratings. Fire-sales spillover from portfolio liquidation propagates from one fund to another through indirect contagion mediated by common asset holdings. The analysis is conducted quarterly from March 2016 through June 2018 using daily data from different sources at the fund and firm levels. Our estimation strategy relies on a network analysis where funds are not taken as stand- alone entities but are interconnected components of a unified system. We find evidence that the relative market value loss of the High ESG ranked funds is lower than the loss experienced by the Low ESG ranked counterparts in the time span with lower volatility. In the higher-volatility period there is not always a clear dominance of one class over another. Results are robust when controlling for size and for feedback effects, and for different model specifications. Our analysis offers new insights to both asset managers and policymakers to exploit the aggregate effect of portfolio diversification related to the system as a whole.File | Dimensione | Formato | |
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