Clean energy and fintech: A scientometric study on spillovers and hedging in investment portfolios

This scientometric study delves into the integration of clean energy and fintech within investment portfolios, emphasising their role in sustainable development and Environmental, Social, and Governance (ESG) objectives. Through a systematic literature review (SLR) and advanced bibliometric analyses, including co-citation, bibliographic coupling, co-word analysis, and thematic mapping, this body of research identifies key thematic clusters and methodological advancements. It highlights the role of clean energy in diversified and resilient portfolios, the dynamic interplay between energy markets and fintech innovations, and the significance of global crises, such as COVID-19, in reshaping research priorities. Novel methodologies, including time-varying parameter vector autoregressive models (TVP-VAR), time-frequency connectedness frameworks, wavelet quantile correlation (WQC), nonparametric causality in quantile approaches, the tail event driven network technique (TENET), empirical mode decomposition-windowed-cross-correlation (EMD-WCC), wavelet-windowed-cross-correlations and the cross-quantilogram approach are showcased as critical tools for understanding interconnected market dynamics. The findings underscore the evolving relationship between green bonds, ESG assets, and traditional financial instruments, with an emphasis on their hedging potential and systemic risk implications. Furthermore, the study explores the impacts of regional energy transitions, particularly in Europe, on economic stability and competitiveness. By integrating bibliometric tools with cutting-edge methodological insights, this paper offers actionable strategies for policymakers, investors, and researchers wishing to align financial practices with global sustainability goals, by fostering resilience in increasingly volatile markets.