How do FinTech impact China's traditional and clean energy markets? A time-frequency quantile analysis

This paper employs time-frequency quantile methods to explore the interrelationships between financial technology (FinTech), traditional energy markets, and clean energy markets. The results indicate that, both in the short and long term, clean energy is the primary net contributor, while FinTech and traditional energy act as net receivers. However, in the short term, nuclear energy (Nuclear) contributes the most, followed by hydrogen (Hydrogen), making them the main contributors in this system. In the long term, all indicators of clean energy are net contributors, with hydrogen (Hydrogen) being the largest contributor, followed by wind energy (Wind), while the contribution of nuclear energy (Nuclear) decreases, and solar energy (Solar) ranks last. The quantile analysis shows that the dependency relationships under extreme market conditions differ from those under normal market conditions. Notably, under extreme market conditions, FinTech is more closely linked to the clean energy market, especially nuclear energy (Nuclear). Moreover, as the lag period increases, the dependencies between markets evolve, highlighting the importance of considering dynamic market changes in the analysis. Finally, robustness checks confirm the robustness of the study's findings. The study provides recommendations for investors to manage risk in energy asset portfolios, as well as policy recommendations for policymakers on market risk spillovers.