人工智能在创新产业中的传染效应：从区块链和元宇宙到清洁技术及其他

IF 12.9 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change Pub Date : 2024-11-16 DOI:10.1016/j.techfore.2024.123822

Muhammad Abubakr Naeem , Nadia Arfaoui , Larisa Yarovaya

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引用次数: 0

摘要

人工智能（AI）是横跨商业、技术和科学领域的变革力量，但其对创新行业的全面影响仍相对欠缺。本研究深入探讨了人工智能与加密货币、区块链、元宇宙、民主化银行和清洁技术等关键行业之间的相互联系。我们采用条件自回归风险价值（CAViaR）和时变参数向量自回归（TVP-VAR）方法，仔细研究了从2018年6月1日到2023年10月11日的每日数据，涵盖了代表各行业的12个股票指数。我们的研究结果揭示了人工智能对其他创新行业的强烈传染效应，但清洁技术行业除外，该行业似乎已与人工智能浪潮脱钩。值得注意的是，民主化银行业和元宇宙成为这种传染效应的主要接受者。对尾部风险溢出效应的研究表明，人工智能是市场动荡期间最有影响力的风险传播者之一，而加密货币和区块链在整个样本期间始终是净风险接收者。这些发现的影响是多方面的，为这些关键创新领域的风险状况提供了实质性的见解。投资者和监管机构将从这一分析中获益匪浅，因为它揭示了投资组合多样化的潜在途径，并加深了对这些不断发展的行业内传染机制的理解。

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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.

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来源期刊

Technological Forecasting and Social Change Multiple-

CiteScore

21.30

自引率

10.80%

发文量

813

期刊介绍： Technological Forecasting and Social Change is a prominent platform for individuals engaged in the methodology and application of technological forecasting and future studies as planning tools, exploring the interconnectedness of social, environmental, and technological factors. In addition to serving as a key forum for these discussions, we offer numerous benefits for authors, including complimentary PDFs, a generous copyright policy, exclusive discounts on Elsevier publications, and more.