AI market swings track technology stocks more than clean energy

A new open-access study published in Discover Sustainability on 25 October 2026 reports that the market performance of artificial intelligence is far more tightly linked to the global technology market than to clean-energy equities. Seyed Alireza Athari and colleagues analysed daily data spanning 6 March 2020 to 5 June 2026, a window that covers the pandemic shock, the subsequent inflation surge and the recent AI investment boom. To separate the AI signal from broad financial conditions, the authors incorporated oil-price returns and changes in the CBOE Volatility Index (VIX) as control variables, allowing them to distinguish the AI–market association from general energy-price movements and financial-risk sentiment.

The empirical design relies on wavelet quantile-based approaches, a combination that lets researchers examine associations both across time horizons and across different market states. Quantiles matter because markets behave differently under stress: the lowest quantiles correspond to severe downside conditions, while central and upper quantiles reflect calm or bullish phases. Wavelet decomposition adds a second dimension, revealing whether relationships hold over short, medium or long horizons. This dual lens is particularly useful for a period in which AI stocks, clean-energy shares and oil prices all experienced dramatic swings.

For the clean-energy market, the results are notably state dependent. The association between AI market performance and clean-energy equities is weak and occasionally negative at the lowest quantiles, especially over medium and long horizons. In other words, when clean-energy stocks are under extreme downside pressure, AI-market innovations do not move in step with them. Across most central and upper quantiles, however, the relationship turns positive. The positive long-horizon association proves especially persistent: it remains evident after controlling for oil-price returns and VIX changes, after varying the lag length, and after altering the set of control variables, suggesting the linkage is not an artefact of energy-price conditions or general market fear.

The picture for the global technology market is strikingly different. AI exhibits a consistently strong and positive association with technology equities across nearly all quantiles and horizons, with the largest coefficients generally concentrated in the medium horizon. This robustness across market states and time scales indicates that AI-market innovations are more deeply integrated with the wider technology sector than with clean-energy stocks, whose AI linkage appears contingent on prevailing conditions.

The authors interpret these patterns as evidence that the AI–clean-energy relationship is more sensitive to extreme downside conditions than the AI–technology relationship. Clean-energy markets, which depend heavily on policy support, interest-rate expectations and commodity prices, appear to decouple from AI-driven sentiment precisely when they are weakest. Based on the findings, the study proposes policy recommendations, although the analysis is an association study of market data rather than a demonstration of causal effects, and its scope is limited to the 2020–2026 sample period and the specific market indices examined.

Subject of Research: Associations between artificial-intelligence market performance, the clean-energy market and the global-technology market

Article Title: Artificial intelligence and the evolving behaviour of clean energy and green technology market

Article References: Athari, S. A., Uzun, B., Henni, M. D., Kirikkaleli, D., Olanrewaju, V. O., & Taiwo, T. S. (2026). Artificial intelligence and the evolving behaviour of clean energy and green technology market. Discover Sustainability. https://doi.org/10.1007/s43621-026-05119-z

Image Credits: AI Generated

DOI: 10.1007/s43621-026-05119-z

Keywords: artificial intelligence, clean energy, green technology, wavelet quantile analysis, financial markets, CBOE Volatility Index, oil prices, Discover Sustainability, Artificial, intelligence, evolving, behaviour