The contagion effect of artificial intelligence across innovative industries: From blockchain and metaverse to cleantech and beyond
The contagion effect of artificial intelligence across innovative industries: From blockchain and metaverse to cleantech and beyond
Artificial Intelligence (AI) stands as a transformative force across business, technology, and science, yet its comprehensive impact on innovative industries remains relatively unexplored. This study delves into the interconnectedness between AI and pivotal sectors such as cryptocurrency, blockchain, metaverse, democratized banking, and Cleantech, among others. Employing the conditional autoregressive value-at-risk (CAViaR) and time-varying parameters vector autoregressions (TVP-VAR) methods, we scrutinize daily data spanning from June 1, 2018, to October 11, 2023, encompassing 12 stock indices representing each industry. Our findings unveil a strong contagion effect from AI to other innovative sectors, with the exception of Cleantech, which appears to have decoupled from the AI surge. Notably, democratized banking and the metaverse emerge as key recipients of this contagion. Examination of tail-risk spillovers highlights AI as one of the most influential risk transmitters during market tumult, while cryptocurrency and blockchain consistently function as net risk receivers throughout the sample period. The implications of these findings are multifaceted, offering substantive insights into the risk profiles of these critical innovative sectors. Investors and regulatory bodies stand to benefit significantly from this analysis, as it illuminates potential avenues for portfolio diversification and deepens understanding of contagion mechanisms within these evolving industries.
Artificial Intelligence, CAViaR, Cryptocurrency, Metaverse, TVP-VAR, Artificial intelligence
Naeem, Muhammad Abubakr
959d6cc4-53d1-47dc-8c3c-0354a08633d7
Arfaoui, Nadia
74231397-dfab-4de4-87ad-eadfcc5f6519
Yarovaya, Larisa
2bd189e8-3bad-48b0-9d09-5d96a4132889
16 November 2024
Naeem, Muhammad Abubakr
959d6cc4-53d1-47dc-8c3c-0354a08633d7
Arfaoui, Nadia
74231397-dfab-4de4-87ad-eadfcc5f6519
Yarovaya, Larisa
2bd189e8-3bad-48b0-9d09-5d96a4132889
Naeem, Muhammad Abubakr, Arfaoui, Nadia and Yarovaya, Larisa
(2024)
The contagion effect of artificial intelligence across innovative industries: From blockchain and metaverse to cleantech and beyond.
Technological Forecasting and Social Change, 210, [123822].
(doi:10.1016/j.techfore.2024.123822).
Abstract
Artificial Intelligence (AI) stands as a transformative force across business, technology, and science, yet its comprehensive impact on innovative industries remains relatively unexplored. This study delves into the interconnectedness between AI and pivotal sectors such as cryptocurrency, blockchain, metaverse, democratized banking, and Cleantech, among others. Employing the conditional autoregressive value-at-risk (CAViaR) and time-varying parameters vector autoregressions (TVP-VAR) methods, we scrutinize daily data spanning from June 1, 2018, to October 11, 2023, encompassing 12 stock indices representing each industry. Our findings unveil a strong contagion effect from AI to other innovative sectors, with the exception of Cleantech, which appears to have decoupled from the AI surge. Notably, democratized banking and the metaverse emerge as key recipients of this contagion. Examination of tail-risk spillovers highlights AI as one of the most influential risk transmitters during market tumult, while cryptocurrency and blockchain consistently function as net risk receivers throughout the sample period. The implications of these findings are multifaceted, offering substantive insights into the risk profiles of these critical innovative sectors. Investors and regulatory bodies stand to benefit significantly from this analysis, as it illuminates potential avenues for portfolio diversification and deepens understanding of contagion mechanisms within these evolving industries.
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The contagion effect of artificial intelligence across innovative industries
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1-s2.0-S0040162524006206-main
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Accepted/In Press date: 7 October 2024
e-pub ahead of print date: 16 November 2024
Published date: 16 November 2024
Keywords:
Artificial Intelligence, CAViaR, Cryptocurrency, Metaverse, TVP-VAR, Artificial intelligence
Identifiers
Local EPrints ID: 495839
URI: http://eprints.soton.ac.uk/id/eprint/495839
ISSN: 0040-1625
PURE UUID: 85ce209c-d7e9-46c5-be9f-40c80e8f7acc
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Date deposited: 25 Nov 2024 17:44
Last modified: 22 Aug 2025 02:26
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Author:
Muhammad Abubakr Naeem
Author:
Nadia Arfaoui
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