Financial Technology and ESG market: A Wavelet-DCC GARCH approach

This paper examines the co-movement between FinTech and ESG markets from a time-frequency domain perspective. We use an approach suggested by Vacha and Barunik (2012) and include wavelet coherence analysis and dynamic conditional correlation from a multivariate GARCH model (DCC GARCH). We find a significant bi-directional positive relationship between the FinTech and ESG indices. We also find the DCC GARCH process to be mean reverting. The correlations between FinTech and ESG indices, based on both the wavelet coherence and DCC GARCH models, are found to fluctuate over time with the one based on DCC GARCH being higher on the average compared to the one based on wavelet coherence. Finally, we find that the correlations are significant for almost all frequencies except for the 256-day frequency. For the lower frequencies, such as 512-day (approximately 2-year frequency), the correlation increases.