This paper explores the interconnections among oil, artificial intelligence (AI), clean technology, and traditional markets. We apply a novel generalized quantile-on-quantile connectedness method that assesses variable cross-quantile interdependencies, analyzing data from 2018 to 2023. Our study provides a detailed examination of risk transmission dynamics between oil, AI, clean technology, and major markets including equity, debt, and currency. Our findings indicate that tail risk spillovers are more pronounced than median quantiles. In contrast, the analysis shows negative spillovers across these tails in markets for U.S. government debt, the U.S. dollar, and gold. The dynamic risk transmission analysis reveals that while the stock and AI markets generally act as net transmitters of risk across all quantiles, the crude oil and USD index markets consistently receive net risk spillovers, particularly in the right tail of the distribution. Our results suggest that, on average, AI, and clean technology markets, along with the stock markets, are more likely to transfer risk spillovers compared to debt, currency, or other commodity markets. This positions the USD and crude oil as potential buffers against extreme risk transmissions emanating from the AI and clean technology sectors. This study highlights the complex risk dynamics and the pivotal role of oil in the interplay between emerging technologies and traditional financial markets.

中文翻译：

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跨分位数风险评估：原油、人工智能、清洁技术和其他市场的相互作用


本文探讨了石油、人工智能 （AI）、清洁技术和传统市场之间的相互联系。我们应用了一种新的广义分位数对分位数连接性方法，该方法评估了可变的跨分位数相互依赖关系，分析了 2018 年至 2023 年的数据。我们的研究详细研究了石油、人工智能、清洁技术和主要市场（包括股票、债务和货币）之间的风险传递动态。我们的研究结果表明，尾部风险溢出比中位数分位数更明显。相比之下，分析显示，美国政府债务、美元和黄金市场对这些尾部的负面溢出效应。动态风险转移分析显示，虽然股票和 AI 市场通常充当所有分位数的风险净传递器，但原油和美元指数市场始终收到净风险溢出，尤其是在分布的右尾。我们的结果表明，平均而言，与债务、货币或其他商品市场相比，人工智能和清洁技术市场以及股票市场更有可能转移风险溢出效应。这使得美元和原油成为潜在的缓冲，以应对人工智能和清洁技术行业产生的极端风险传导。本研究强调了复杂的风险动态以及石油在新兴技术与传统金融市场之间相互作用中的关键作用。