The present paper attempts to examine the relationship between investor sentiment and the price dynamics of ESG-compliant cryptocurrencies (ESG coins). The author has investigated the potential impact of macroeconomic and monetary policy factors on the dynamic correlations between ESG coins and the Fear and Greed Index (FGI).
Using a daily data set from 2021 to 2025, the study uses both QVAR and QQR connectedness approaches to examine the distributional relationship between investor sentiment and ESG coins. The author uses DCC M-GARCH and reverses MIDAS models to consider the impact of macroeconomic and monetary policy variables.
The findings confirm that the sentiment index is a strong predictor of ESG coin market performance, and reveal heterogeneous investor perceptions of these cryptocurrencies. Solana shows a stronger correlation with overall market sentiment compared to Polkadot and Cardano. The results show that industrial production positively influences the correlation for Polkadot and Cardano, while negatively impacting Solana. The US Leading Index and Federal Funds Rate also have significant, albeit different, impacts across the three ESG coins, highlighting their distinct responses to macroeconomic conditions and monetary policy.
The empirical findings suggest important policy implications and demonstrate the imperative of integrating both investor sentiment and macroeconomic conditions into risk–return assessments of ESG-compliant cryptocurrencies.
To the best of the author’s knowledge, this study represents the first investigation into the influence of macroeconomic variables on the correlation between ESG coin prices and investor sentiment. Furthermore, it provides an in-depth analysis of the nexus between these variables by using quantile-on-quantile connectedness.
