Dynamic spillover effects and connectedness among climate change, technological innovation, and uncertainty: Evidence from a quantile VAR network and wavelet coherence

• QVAR and multiple wavelet coherence frameworks were applied. • The frameworks report a strong connectedness between climate change indexes. • Climate change markets are impacted by technical innovation and uncertainty. • Such markets were subject to a switching effect during the COVID-19 pandemic. This study investigated time-frequency transmission and connectedness among green indexes dealing with clean energy, environmental preservation, and technological innovation and information uncertainty related to economics news, the COVID-19 pandemic, and Twitter usage. First, by employing a quantile vector autoregression framework, we assessed how the static and dynamic connectedness between markets switched across a broad spectrum of market conditions, particularly bear, normal, and bull markets. Second, we examined the dynamics of the co-movement between green financial markets and the level of uncertainty in the time-frequency domain using novel vector wavelet coherence analysis. Our analysis yielded the following major findings: Statically, high spillover and volatility effects existed among the indexes; dynamically, evidence of very strong connectedness between climate change indexes was reported at extreme lower and extreme upper quantiles. The findings further exhibit the switching of climate change between net contributing/net receiving shock behavior during the pandemic. Technological innovation, the COVID-19 pandemic, and uncertainty have strong effects on climate change markets as revealed by multiple, quadruple, and vector wavelet analysis. Implications for both environmental investors and policymakers were revealed.