Do climate policy uncertainty and investor sentiment drive the dynamic spillovers among green finance markets?

Green finance is an essential instrument for improving the environment and addressing climate change. This study investigates the dynamic spillovers among green finance markets using time-varying parameter vector autoregression (TVP-VAR) spillover indices, and further investigates the impact of climate policy uncertainty and investor sentiment on spillovers based on the generalised autoregressive conditional heteroscedasticity mixed data sampling (GARCH-MIDAS) model. The results indicate that: (i) environmental, social and governance (ESG), clean energy and water markets are information transmitters in the green finance system, whereas green building, green transportation, green bond and carbon markets are mainly information receivers; (ii) green stock markets including clean energy, non-energy and ESG markets transmit and receive greater information in the green finance system, while green bond and carbon markets do less; (iii) the green bond market is more interconnected with other green finance markets after the COVID-19 outbreak; (iv) investor sentiment contributes more to the net total directional spillovers of green resource markets (water and clean energy), while climate policy uncertainty contributes more to total spillovers and the net total directional spillovers of other green finance markets. These findings offer invaluable guidance for both policymakers and environmental investors. [Display omitted] •We quantify the dynamic spillovers among green finance markets.•We reveal the role of climate policy uncertainty and investor sentiment on spillovers.•We employed the GARCH-MIDAS model, which is used to analyze mixed-frequency data.•Green stock markets transmit and receive greater information in the system.•Investor sentiment contributes more to the spillovers of green resource markets.