When Artificial Intelligence Meets Sustainable Investment Assets: Quantile‐on‐Quantile Connectedness Analysis

ABSTRACT With the intensive development in Artificial Intelligence and sustainable financial assets, the link between these two domains has received limited attention in existing literature. To shed light on this issue, the present study examines the dynamic spillover effects between the AI stock index and three sustainable investment stock indices such as Energy Efficiency Index (EEI), Pollution Mitigation Index (PMI), and Renewable Energy Index (REI). To account for different market conditions of the two types of assets simultaneously, we used the newly developed Quantile‐on‐Quantile connectedness (QQC) approach, which is based on a bivariate VAR model. Results show high connectedness when AI and sustainable assets are directly related, while weak links emerge when the two markets are in opposite states. Moreover, a time‐varying analysis shows a substantial surge in connectedness attributed to the COVID‐19 pandemic as well as to some episodes characterized by technological acceleration, energy market stress, and policy uncertainty. These findings are useful for policymakers and investors in the context of policy design and portfolio management, emphasizing the need for adaptive asset allocation in AI‐driven and sustainability‐focused financial markets.