TY - JOUR

T1 - Modeling Synchronization Risk among Sustainable Exchange Trade Funds

T2 - A Statistical and Network Analysis Approach

AU - Magner, Nicolás

AU - Lavín, Jaime F.

AU - Valle, Mauricio A.

N1 - Publisher Copyright:
© 2022 by the authors.

PY - 2022/10

Y1 - 2022/10

N2 - 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.

AB - 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.

KW - ESG ratings

KW - ETF

KW - econometric modeling

KW - financial market synchronization

KW - network analysis

KW - risk management

KW - volatility shocks

UR - http://www.scopus.com/inward/record.url?scp=85139752314&partnerID=8YFLogxK

U2 - 10.3390/math10193598

DO - 10.3390/math10193598

M3 - Article

AN - SCOPUS:85139752314

SN - 2227-7390

VL - 10

JO - Mathematics

JF - Mathematics

IS - 19

M1 - 3598

ER -