Time-Frequency Dynamics and Cross-Market Integration among Metal, Energy, Carbon, and AI Sectors

This study examines the dynamic co-movement and interconnectedness of the Metal, Energy, ‎Carbon, and Artificial Intelligence (AI) markets to understand their evolving interactions in the ‎context of technological progress and sustainability transitions. The study employs wavelet coherence analysis to investigate the interactions between these markets across various time scales, encompassing both short-term variations and long-term trends. The results ‎demonstrate substantial long-term coherence, especially between Energy and Carbon, as well ‎as between Carbon and AI, signifying robust and enduring interdependencies. Medium-term ‎correlations demonstrate modest variability, likely influenced by market restrictions and ‎innovation cycles, whereas short-term linkages seem more unstable, reflecting acute shocks ‎and developing technologies. This paper presents new empirical evidence about the increasing ‎integration of financial and resource-based markets, highlighting the impact of AI ‎advancements and environmental issues on conventional sectors. The study enhances ‎comprehension of cross-market behavior, providing significant insights for investors, ‎policymakers, and researchers investigating market predictability, risk management, and ‎sustainable economic planning‎.