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Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach

Author

Listed:
  • Nicolás Magner

    (Facultad de Administración y Economía, Universidad Diego Portales, Santiago 8370109, Chile)

  • Jaime F. Lavín

    (Escuela de Negocios, Universidad Adolfo Ibáñez, Santiago 7941169, Chile)

  • Mauricio A. Valle

    (Facultad de Economía y Negocios, Universidad Finis Terrae, Santiago 7501015, Chile)

Abstract

We evaluate the environment, society, and corporate governance rating (ESG rating) contribution from a new perspective; the highest ESG rating mitigates the impact of unexpected change in the implied volatility on the systemic stock market risk. For this purpose, we use exchange-traded funds (ETF) classified by their ESG rating into quartiles to estimate the synchronization as a proxy by systemic risk. Then, for each ETF quartile, we study the effect of the implied volatility over the synchronization. Our study is the first to model sustainable ETFs’ synchronization by combining econometric modeling and network methods, including 100 ETFs representing 80% of the global ETF market size between 2013 and 2021. First, we find that a higher ESG rating mitigates the effect of implied volatility over ETF synchronization. Surprisingly, the effect is the opposite in the case of ETFs with lower ESG ratings, where an increase in the volatility expectation increases the synchronization. Our study depicts the effect of sustainable ETFs on lessening the systemic risk due to returns synchronization, this being a novel contribution of this asset class. Finally, this paper offers extensions to deepen the contribution of other asset classes of ETFs in terms of their synchronization behavior and impact on risk management and financial performance.

Suggested Citation

  • Nicolás Magner & Jaime F. Lavín & Mauricio A. Valle, 2022. "Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach," Mathematics, MDPI, vol. 10(19), pages 1-30, October.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:19:p:3598-:d:931712
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