Asymmetric Shock Transmission Between Artificial Intelligence Stocks and Carbon Markets: A Quantile-on-Quantile Connectedness Approach

Abstract

The primary objective of this study is to examine the financial interaction between artificial intelligence (AI) indices and the carbon market and to reveal how shock transmission between the two markets varies according to market conditions. In this regard, the study analyzes the dynamics between two carbon indices, ICE EUA Carbon Futures Excess Return Index (ICEEUA) and S&P Global Carbon Credit Index (GLCARB), and two AI indices, Nasdaq CTA Artificial Intelligence & Robotics Index (NQROBO) and ROBO Global Artificial Intelligence Index (THNQ), using daily data covering the period from February 18, 2022 to June 27, 2025. Findings from the Quantile-on-Quantile Connectedness analysis reveal that the carbon market serves as a net shock transmitter across most quantile combinations; however, this role exhibits significant asymmetry, with transmission intensifying during extreme market conditions. Put differently, in certain periods characterized by heightened technological momentum, the AI indices also generate a meaningful feedback effect toward the carbon market. These interactions intensify in extreme quantile regimes, indicating stronger market integration during periods of stress. The results demonstrate that the financial structure of carbon pricing and the AI sector is becoming increasingly intertwined, and that sustainability policies need to be reconsidered in a manner that appropriately accounts for developments in technology markets.