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Geopolitical risks and conflicts wield substantial influence on the global economy and financial markets, fostering uncertainty and volatility. This study investigates the intricate relationship between gold and representatives of green and sustainable stocks in the US and EU during the Russia-Ukraine conflict, employing multifractal detrended cross-correlation analysis (MF-DCCA) and nonlinear Granger causality. MF-DCCA reveals significant multifractal properties and nonlinear cross-correlations across all time series pairs. Notably, conflict weakened the multifractal cross-correlations between US stocks and gold, except for the TESLA/gold pair. A similar significant change in the EU market's multifractal properties was observed during the conflict. In conjunction with MF-DCCA, Granger causality tests indicate bidirectional nonlinear relationships between gold and green/sustainable stock markets in the USA and EU. Gold's past movements significantly influence changes in all the considered green and sustainable stocks, enabling predictions of their behavior. These findings shed light on multifractal dynamics during geopolitical crises and emphasize the bidirectional relationships between gold and green and sustainable stock markets. This comprehensive analysis informs investors and policy makers, enhancing their understanding of financial market behavior amid geopolitical instability. [ABSTRACT FROM AUTHOR]

In this study, we conduct a comparative analysis of the nonlinear dynamics of the time series data for green and conventional bond indices spanning the period from 2014 to 2023. Our research builds upon the existing limited studies conducted in this domain. To examine the inherent characteristics of the empirical data-generating process, we utilize a generalized chaos analysis framework. The findings indicate that both series exhibit a combination of quasi-periodic cycles and deterministic (chaotic) dynamics. Additionally, we employ reconstruction techniques to visualize the strange (fractal) system attractors for both series. Furthermore, we quantify and compare the dynamics that emerge from the data by employing recurrence quantification analysis and multifractal analysis with power-law distributional coherence tests. Consequently, we identify that both bond series exhibit multifractal characteristics. Finally, we conduct a comparative analysis of the distinct dynamical differences observed between the bond index series. Based on our results, we draw concluding remarks regarding the future evolution of the green bond market and discuss the potential implications of our findings in the context of climate change. • Generalized chaos analysis for green versus conventional bonds is conducted. • Underlying empirical DGP characteristics stated for green and conventional bonds. • Chaos and strange (fractal) attractors presented for green and conventional bonds. • Multifractality shown for both bond series. • Implications for climate change, hedging and save-havens are discussed. [ABSTRACT FROM AUTHOR]