This study investigates the dynamic connectivity between non-renewable and renewable energy markets using a Time-Varying Parameter Vector Autoregression (TVP-VAR) model. The analysis encompasses eight principal indices: WTI crude oil, natural gas, gasoline, and carbon emissions futures for non-renewables, alongside four clean energy ETFs—ICLN, QCLN, PBW, and SPGTCLNT—symbolizing renewables. The study extends from November 30, 2015, to February 29, 2024, and is categorized into pre- and post-COVID-19 stages. The results indicate a notable change following the onset of the pandemic. The Total Connectedness Index (TCI) increased from 50.95 to 54.69 post-COVID, indicating a slight rise in systemic spillovers. WTI underwent a slight net receipt of shocks, whereas renewable energy indices—specifically ICLN and QCLN—functioned as notable net transmitters. The Net Pairwise Directional Connectedness (NPDC) underscores the increasing significance of renewables in bilateral return shocks, signifying a transformation in inter-market dynamics and volatility hierarchy. Robustness assessments were performed utilizing two supplementary methodologies. Initially, alternative forecast horizons within the GFEVD framework validated the consistency of the findings. Secondly, re-evaluating the model across the entire sample, without segmenting it into COVID phases, yielded a comparable connectedness network, so further substantiating the durability of the principal findings. This study provides a high-frequency, asset-level analysis of the evolving energy-finance relationships and highlights the increasing systemic importance of renewable energy. The findings contain important implications for investors and regulators functioning within a highly interconnected energy environment in the post-COVID period.

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