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

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) c...

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Main Authors: Nicolás Magner, Jaime F. Lavín, Mauricio A. Valle
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/10/19/3598
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author Nicolás Magner
Jaime F. Lavín
Mauricio A. Valle
author_facet Nicolás Magner
Jaime F. Lavín
Mauricio A. Valle
author_sort Nicolás Magner
collection DOAJ
description 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.
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spelling doaj.art-c57e01a71ec84e9fb53eb8235fe2be652023-11-23T21:04:18ZengMDPI AGMathematics2227-73902022-10-011019359810.3390/math10193598Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis ApproachNicolás Magner0Jaime F. Lavín1Mauricio A. Valle2Facultad de Administración y Economía, Universidad Diego Portales, Santiago 8370109, ChileEscuela de Negocios, Universidad Adolfo Ibáñez, Santiago 7941169, ChileFacultad de Economía y Negocios, Universidad Finis Terrae, Santiago 7501015, ChileWe 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.https://www.mdpi.com/2227-7390/10/19/3598ETFESG ratingsrisk managementeconometric modelingnetwork analysisvolatility shocks
spellingShingle Nicolás Magner
Jaime F. Lavín
Mauricio A. Valle
Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach
Mathematics
ETF
ESG ratings
risk management
econometric modeling
network analysis
volatility shocks
title Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach
title_full Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach
title_fullStr Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach
title_full_unstemmed Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach
title_short Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach
title_sort modeling synchronization risk among sustainable exchange trade funds a statistical and network analysis approach
topic ETF
ESG ratings
risk management
econometric modeling
network analysis
volatility shocks
url https://www.mdpi.com/2227-7390/10/19/3598
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AT jaimeflavin modelingsynchronizationriskamongsustainableexchangetradefundsastatisticalandnetworkanalysisapproach
AT mauricioavalle modelingsynchronizationriskamongsustainableexchangetradefundsastatisticalandnetworkanalysisapproach