Xiangjing Zhou

Guangxi University of Finance and Economics

Papers

Total Citations

H-Index

About

Xiangjing Zhou is a leading researcher at the intersection of artificial intelligence and sustainable energy systems, with a primary focus on understanding the complex financial and technological linkages between AI-driven markets and clean energy indices. Their most cited work, "Measuring the extreme linkages and time-frequency co-movements among artificial intelligence and clean energy indices" (2024, 73 citations), provides a groundbreaking empirical analysis of how AI and renewable energy sectors interact under extreme market conditions. This study, which has quickly become a cornerstone reference in the field, introduces novel time-frequency methodologies to capture the dynamic co-movements and risk transmission between these two critical industries. Zhou’s research is particularly impactful for policymakers and investors seeking to understand the financial interdependencies that shape the green transition. By quantifying the extreme linkages between AI and clean energy, their work offers actionable insights for portfolio diversification and systemic risk management. With their paper already garnering significant attention, Zhou is establishing themselves as a key voice in the emerging field of AI-energy finance, bridging computational methods with real-world sustainability challenges. Their contributions are essential reading for anyone exploring the financial architecture of the low-carbon economy.