Risk modelling of ESG (environmental, social, and governance), healthcare, and financial sectors

Author:

Chaudhry Sajid M.1,Chen Xihui Haviour2,Ahmed Rizwan3,Nasir Muhammad Ali45ORCID

Affiliation:

1. Economics Finance & Entrepreneurship Department, Aston Business School Aston University Birmingham UK

2. Edinburgh Business School, The Centre for Social and Economic Data Analytics (CSEDA) Heriot‐Watt University Edinburgh UK

3. Kent Business School University of Kent Canterbury UK

4. Department of Economics University of Leeds Leeds UK

5. Department of Land Economy University of Cambridge Cambridge UK

Abstract

AbstractClimate change poses enormous ecological, socio‐economic, health, and financial challenges. A novel extreme value theory is employed in this study to model the risk to environmental, social, and governance (ESG), healthcare, and financial sectors and assess their downside risk, extreme systemic risk, and extreme spillover risk. We use a rich set of global daily data of exchange‐traded funds (ETFs) from 1 July 1999 to 30 June 2022 in the case of healthcare and financial sectors and from 1 July 2007 to 30 June 2022 in the case of ESG sector. We find that the financial sector is the riskiest when we consider the tail index, tail quantile, and tail expected shortfall. However, the ESG sector exhibits the highest tail risk in the extreme environment when we consider a shock in the form of an ETF drop of 25% or 50%. The ESG sector poses the highest extreme systemic risk when a shock comes from China. Finally, we find that ESG and healthcare sectors have lower extreme spillover risk (contagion risk) compared to the financial sector. Our study seeks to provide valuable insights for developing sustainable economic, business, and financial strategies. To achieve this, we conduct a comprehensive risk assessment of the ESG, healthcare, and financial sectors, employing an innovative approach to risk modelling in response to ecological challenges.

Publisher

Wiley

Subject

Physiology (medical),Safety, Risk, Reliability and Quality

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