Role of ESG cryptocurrencies and AI assets in promoting sustainable investing: insights from multiscale volatility

Purpose This study investigates the multiscale volatility transmissions and diversification opportunities among artificial intelligence (AI) tokens, environmental, social and governance (ESG) cryptocurrencies and AI equity stocks, with a focus on their implications for sustainable finance. This study aims to uncover how connectedness dynamics evolve across different market conditions and frequencies, providing insights into risk management and sustainability-driven investment strategies. Design/methodology/approach Using a quantile time–frequency approach, the study captures both static and dynamic spillovers across time and frequency domains at the median, upper and lower quantiles. This framework enables a comprehensive assessment of volatility connectedness under varying market states, from normal to extreme conditions. Findings The results reveal that volatility interlinkages are relatively weak under normal conditions but intensify significantly during market extremes, particularly in the upper quantile. ESG cryptocurrencies consistently act as net transmitters of volatility across all quantiles and frequencies, underscoring their systemic role in sustainability-oriented digital finance. In contrast, AI equity stocks exhibit heterogeneous spillover patterns, suggesting diversification potential, while AI tokens demonstrate mixed transmitter–receiver behaviors that vary with market sentiment. Overall, volatility connectedness is highly time-varying and sensitive to macroeconomic events and policy reforms. Originality/value To the best of the authors’ knowledge, this study is among the first to jointly examine AI tokens, ESG cryptocurrencies and AI equity stocks, bridging the rapidly growing fields of AI and sustainable finance. By uncovering the multiscale and state-dependent nature of volatility transmissions, it advances the theoretical understanding of interconnected digital asset markets. Furthermore, by estimating optimal portfolio weights and hedging ratios, the study provides practical insights that support sustainable financial integration. Overall, it offers novel evidence on the structure and dynamics of the AI–ESG financial ecosystem.