Purpose This study examines the potential for diverse information flows between traditional and green energy markets, focusing on three key financial instruments that represent various dimensions of the global energy transition, with the moderating roles of economic policy uncertainty (EPU) and monetary policy intervention (MPI). Accordingly, three key financial instruments analysed in this study are the iShares USD Green Bond ETF (BGRN), the iShares Global Clean Energy ETF (ICLN), and the S&P 500 Energy Index (SP500EN). Design/methodology/approach Employing the recently developed quantile-on-quantile transfer entropy (QQTE) method introduced by Yao et al. (2025), we analyse data spanning from January 4, 2019, to April 25, 2025. Findings Empirical analysis revealed that information flow from the clean energy market to both green bond and traditional energy markets persists in the lower and median quantiles when the effects of policy regimes (EPU and MPI) were ignored. However, the connection between the two alternative markets diminishes in the presence of EPU and MPI. Further, the traditional energy market remains a main shock transmitter even after controlling for EPU and MPI. Research limitations/implications The robust linkage between the traditional (oil) market and the clean energy market, especially in the absence of policy uncertainty or intervention, suggests that the conventional energy market can complement the clean energy market during the energy transition period, provided policy stability and non-intervention prevail. However, the weak contagion between the two alternative markets implies that portfolio diversification benefits exist between green fixed-income and conventional energy equities, particularly during policy intervention and climatic policy uncertainty, as well as between portfolios sensitive to sector-specific shocks. Originality/value To the best of our knowledge, none of the previous studies have used the newly proposed quantile-on-quantile transfer entropy (QQTE) method by Yao et al. (2025) to examine interactions between the two alternative energy markets. Compared to the various approaches employed in previous studies, the newly proposed QQTE method, based on the QTE of Zhang and Zhao (2022), can detect nonlinear feedback connections across quantiles.
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Marco Tedeschi
Adeolu O. Adewuyi
Aviral Kumar Tiwari
China Accounting and Finance Review
Marche Polytechnic University
University of Ibadan
Indian Institute of Management Indore
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Tedeschi et al. (Thu,) studied this question.
www.synapsesocial.com/papers/69a75cd1c6e9836116a2602f — DOI: https://doi.org/10.1108/cafr-07-2025-0125