What REALLY drives clean energy stocks - Fear or Fundamentals?

This study investigates the relationship between the S&P Global Clean Energy Index and novel factors based on the GDELT Database, such as global news confidence levels, environmental sentiment, media coverage preferences in the US and China, and the ratio of environmental to overall reporting. We identify variables sourced from recent literature. Using the Isolation Forest method to select potential explanatory variables, Extreme Bounds Analysis reveals that “Fear” factors such as media sentiment and confidence show consistent and significant correlations with the S&P Global Clean Energy Index. These findings highlight the influential role of media sentiment in driving market confidence and industry growth. In contrast, some traditionally popular “Fundamental” factors, such as the Global Financial Stress Indicator, Green Bond Index, and US Dollar Index, lack robustness. While they appear reliable under normal distribution models, they exhibit substantial uncertainty under alternative models, limiting their explanatory power. • Media sentiment and confidence significantly influence the S&P Global Clean Energy Index more than traditional market factors. • Extreme Bounds Analysis (EBA) confirms that media-driven variables have robust impacts, while some conventional economic indicators lack consistency. • The GDELT database provides global media sentiment data, enabling comprehensive analysis of clean energy market influences. • Isolation Forest method effectively identifies key drivers of clean energy stock movements, enhancing the robustness of the analysis. • U.S.-China media sentiment plays a major role in shaping clean energy stock performance, reflecting geopolitical and economic trends. • Future research should further explore sentiment-driven market dynamics using advanced AI-driven media analysis techniques.