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Systemic risk contagion of green and Islamic markets with conventional markets

Systemic risk contagion of green and Islamic markets with conventional markets
Systemic risk contagion of green and Islamic markets with conventional markets
Financial markets are exposed to extreme uncertain circumstances escalating their tail risk. Sustainable, religious, and conventional markets represent three different markets with various characteristics. Motivated with this, the current study measures the tail connectedness between sustainable, religious, and conventional investments by employing a neural network quantile regression approach from December 1, 2008 to May 10, 2021. The neural network recognized religious and conventional investments with maximum exposure to tail risk following the crisis periods reflecting strong diversification benefits of sustainable assets. The Systematic Network Risk Index spots Global Financial Crisis, European Debt Crisis, and COVID-19 pandemic as intensive events yielding high tail risk. The Systematic Fragility Index ranks the stock market in the pre-COVID period and Islamic stocks during the COVID sample as the most susceptible markets. Conversely, the Systematic Hazard Index nominates Islamic stocks as the chief risk contributor in the system. Given these, we portray various implications for policymakers, regulatory bodies, investors, financial market participants, and portfolio managers to diversify their risk using sustainable/green investments.
COVID-19, CoVaR, Neural networks, Religious investments, Sustainable Investments
0254-5330
Naeem, Muhammad Abubakr
959d6cc4-53d1-47dc-8c3c-0354a08633d7
Karim, Sitara
1f712808-acf8-4b84-b157-0464f326704c
Yarovaya, Larisa
2bd189e8-3bad-48b0-9d09-5d96a4132889
Lucey, Brian
ea62416d-8886-4acd-b160-f653aea6c319
Naeem, Muhammad Abubakr
959d6cc4-53d1-47dc-8c3c-0354a08633d7
Karim, Sitara
1f712808-acf8-4b84-b157-0464f326704c
Yarovaya, Larisa
2bd189e8-3bad-48b0-9d09-5d96a4132889
Lucey, Brian
ea62416d-8886-4acd-b160-f653aea6c319

Naeem, Muhammad Abubakr, Karim, Sitara, Yarovaya, Larisa and Lucey, Brian (2023) Systemic risk contagion of green and Islamic markets with conventional markets. Annals of Operations Research.

Record type: Article

Abstract

Financial markets are exposed to extreme uncertain circumstances escalating their tail risk. Sustainable, religious, and conventional markets represent three different markets with various characteristics. Motivated with this, the current study measures the tail connectedness between sustainable, religious, and conventional investments by employing a neural network quantile regression approach from December 1, 2008 to May 10, 2021. The neural network recognized religious and conventional investments with maximum exposure to tail risk following the crisis periods reflecting strong diversification benefits of sustainable assets. The Systematic Network Risk Index spots Global Financial Crisis, European Debt Crisis, and COVID-19 pandemic as intensive events yielding high tail risk. The Systematic Fragility Index ranks the stock market in the pre-COVID period and Islamic stocks during the COVID sample as the most susceptible markets. Conversely, the Systematic Hazard Index nominates Islamic stocks as the chief risk contributor in the system. Given these, we portray various implications for policymakers, regulatory bodies, investors, financial market participants, and portfolio managers to diversify their risk using sustainable/green investments.

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Accepted/In Press date: 30 March 2023
e-pub ahead of print date: 18 April 2023
Published date: 18 April 2023
Keywords: COVID-19, CoVaR, Neural networks, Religious investments, Sustainable Investments

Identifiers

Local EPrints ID: 478440
URI: http://eprints.soton.ac.uk/id/eprint/478440
ISSN: 0254-5330
PURE UUID: 4d321b3b-a49e-4467-b547-9a3e218b8b65
ORCID for Larisa Yarovaya: ORCID iD orcid.org/0000-0002-9638-2917

Catalogue record

Date deposited: 30 Jun 2023 16:53
Last modified: 10 Apr 2024 04:01

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Contributors

Author: Muhammad Abubakr Naeem
Author: Sitara Karim
Author: Larisa Yarovaya ORCID iD
Author: Brian Lucey

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