Geopolitical risk, artificial intelligence, and clean energy markets: Nonlinear effects and dynamic connectedness

This study examines the dynamic relationships among geopolitical risk, artificial intelligence (AI), and clean energy markets. The Geopolitical Risk Index (GPR) is used to represent geopolitical risk; the STOXX Global Artificial Intelligence Index, Indxx Global Robotics & Artificial Intelligence Index, and Nasdaq CTA Artificial Intelligence & Robotics Index represent AI markets; and the FTSE Environmental Opportunities Renewable & Alternative Energy Index, NASDAQ Clean Edge Green Energy Index, and S&P Global Clean Energy Index represent clean energy markets. Using daily data from December 18, 2017 to May 1, 2026, the study employs Wavelet Quantile-on-Quantile Regression (WQQR), Quantile-on-Quantile Connectedness (QQCON), and Frequency Quantile Connectedness (FQCON) approaches. The findings reveal that the effects of geopolitical risk on AI and clean energy markets are nonlinear, heterogeneous, and dependent on market regimes and time horizons. Moreover, AI and clean energy markets exhibit asymmetric connectedness, while their net transmitter and receiver roles vary across quantiles and over time. These findings provide important implications for investors, portfolio managers, and policymakers regarding risk management, portfolio diversification, and the coordination of green and digital transformation policies.