In line with achieving the objectives of COP27 and SDG7, this paper examines the interdependence of the Artificial Intelligence market, clean energy, and conventional energy markets from 19th December 2017 to 5th May 2023 by using Cross-Quantilogram (CQ) and Wavelet Locale Multiple correlations (WLMC) techniques. Heatmaps of CQ show a bidirectional relationship between the AI market and clean energy at lag one with negative cross-quantile dependence evident throughout most quantiles, especially in normal market conditions. It also indicates a positive relationship between AI return rates and the clean energy market, but only when both datasets are in the same extreme quantiles (10th and 90th). Additionally, WMLC results reveal that time, scale, and investment horizons influence the interaction between AI and clean and non-clean energy industries. A considerable positive association exists between the AI market and traditional energy markets, ranging from 0.6 to 0.8. However, during the pandemic, this dependency turned negative, and it has since been minor, with an uptick in co-movement during Russia – Ukraine conflict. Several policy implications are suggested for the clean energy and conventional energy markets in line with AI.

中文翻译：

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人工智能、清洁能源和传统能源市场之间的联系：CQ 和 WLMC 技术的新发现


为实现 COP27 和 SDG7 的目标，本文使用交叉量子图 （CQ） 和小波区域多相关 （WLMC） 技术，研究了 2017 年 12 月 19 日至 2023 年 5 月 5 日人工智能市场、清洁能源和传统能源市场的相互依存关系。CQ 的热图显示 AI 市场和清洁能源之间存在双向关系，滞后为 1，在大多数分位数中都存在明显的负交叉分位数依赖性，尤其是在正常的市场条件下。它还表明 AI 回报率与清洁能源市场之间存在正相关关系，但前提是两个数据集都处于相同的极端分位数（第 10 个和第 90 个）。此外，WMLC 结果表明，时间、规模和投资期限会影响 AI 与清洁和非清洁能源行业之间的互动。人工智能市场与传统能源市场之间存在相当大的正相关，范围从 0.6 到 0.8 不等。然而，在大流行期间，这种依赖性变成了负数，此后一直很轻微，在俄乌冲突期间，共同行动有所增加。根据人工智能，对清洁能源和传统能源市场提出了一些政策影响。