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

Abstract

Climate 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.

Divisions: College of Business and Social Sciences > Aston Business School > Economics, Finance & Entrepreneurship
?? RG1022 ??
College of Business and Social Sciences > Aston Business School
Additional Information: Copyright © 2023 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
Publication ISSN: 1539-6924
Last Modified: 29 Nov 2023 13:38
Date Deposited: 24 Jul 2023 08:22
Full Text Link: 10.1111/risa.14195
Related URLs: https://onlinel ... 1111/risa.14195 (Publisher URL)
PURE Output Type: Article
Published Date: 2023-07-21
Published Online Date: 2023-07-21
Accepted Date: 2023-07-02
Submitted Date: 2023-01-30
Authors: Chaudhry, Sajid M.
Chen, Xihui Haviour
Ahmed, Rizwan
Nasir, Muhammad Ali

Download

Export / Share Citation


Statistics

Additional statistics for this record