AI, Green Resources and Semiconductor Markets Form a Tightly Linked Financial Network

An analysis of financial-market data from 1 June 2018 to 30 March 2026 found that green-resource, artificial intelligence and semiconductor markets behaved as a closely integrated network. The study reported a Total Connectedness Index of 83.46%, indicating extensive cross-market spillovers, and decomposed that linkage into contemporaneous and lagged components using the R²-decomposed connectedness framework. It also evaluated connectedness-based portfolio strategies for diversification.

Most of the measured interdependence occurred within the same trading period rather than through delayed adjustments. Contemporaneous spillovers accounted for 81.04% of total connectedness, while lagged effects represented 2.42%. This pattern suggests that information affecting one part of the innovation ecosystem was quickly incorporated into prices across related markets, leaving comparatively little scope for subsequent delayed adjustment. The result concerns statistical transmission among selected market proxies; it does not by itself establish that any particular technology, policy or event caused price movements in another market.

The directional analysis distinguished markets according to whether they generally transmitted or received shocks. Hydrogen and water were identified as net receivers, consistent with their sensitivity to developments involving technology-driven markets. AI and robotics emerged as net transmitters, indicating their expanding influence within the connected system. Semiconductors played an intermediate but prominent role: they both transmitted and received substantial shocks, positioning the market as an interface between artificial intelligence, automation and clean-energy development. These labels describe the direction of connectedness in the study’s selected assets, not direct measures of the physical dependence of industries on one another.

The strength of the relationship varied over time and increased during periods of global stress, including the COVID-19 pandemic, geopolitical conflicts, trade tensions and financial disruptions. The researchers interpreted these episodes as conditions in which cross-market transmission became more intense. Their dynamic analysis also tested portfolio approaches based on the connectedness structure and reported that a Minimum Connectedness Portfolio outperformed the standard strategies considered. That finding offers a market-based rationale for diversification, although the evidence is limited to the study’s particular assets, sample period and methodology.

The authors argue that the findings support closer coordination among semiconductor supply-chain, industrial, digital and climate policy, alongside real-time monitoring of interconnected markets and prompt use of macroprudential tools where warranted. They also identify important boundaries: the analysis relies on selected market proxies and does not capture every feature of the global innovation economy. Future work could examine additional innovation sectors, firm-level and cross-country data, nonlinear or regime-switching relationships, frequency-domain effects and quantile connectedness. The central measured result is therefore a financial one: during the studied period, shocks moved swiftly through a highly connected network linking AI, robotics, semiconductor, hydrogen and water markets, with implications for portfolio resilience and financial oversight.

Subject of Research: Financial spillovers among AI, semiconductor and green-resource markets

Article Title: Dynamic interdependence between green resources, AI and semiconductor market

Article References: Talha, M., Zygiaris, S., Panwar, K., & Tabassum, S. (2026). Dynamic interdependence between green resources, AI and semiconductor market. Discover Sustainability. https://doi.org/10.1007/s43621-026-04798-y

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04798-y

Keywords: market connectedness, artificial intelligence, semiconductors, hydrogen markets, water markets, financial spillovers, portfolio diversification, green resources, robotics, Dynamic, interdependence, between