In an environment where real-time information flows increasingly shape financial markets, this study investigates the impact of financial news sentiment on the daily returns of the Euro Stoxx 50 index from January 2022 to March 2024. The aim of this study is to examine whether sentiment derived from Bloomberg articles can predict stock returns and how this relationship is conditioned by market volatility and lagged performance.
Sentiment scores were computed using the Loughran–McDonald Lexicon applied to Bloomberg news headlines. These sentiment metrics were matched with daily Euro Stoxx 50 returns and market volatility indicators (VIX). A panel data framework was adopted using both fixed and random effects estimators, with the Hausman test guiding model selection. Additionally, year-by-year ordinary least squares regressions were conducted to capture temporal variation in sentiment effects across the post-COVID period.
The results indicate that financial news sentiment exerted a significant positive influence on Euro Stoxx 50 returns, particularly in periods of heightened market volatility. The predictive power of sentiment appears stronger during uncertain conditions, highlighting the role of investor psychology in shaping short-term market movements. However, the effect is not uniform over time, suggesting it is sensitive to prevailing market conditions.
From a managerial perspective, findings carry important implications for corporate communication practices. In fact, the measurable effect of news tone on market valuation underscores the power of language in shaping investor perception. Firms may be tempted to use optimistic wording in press releases or earnings announcements to elicit favorable short-term market reactions, even when underlying fundamentals are unchanged.
This study contributes to the growing literature on behavioral finance by offering new evidence on the conditional impact of sentiment on equity returns in a post-pandemic context. It highlights the limitations of traditional asset pricing models in explaining price formation under uncertainty and supports the integration of sentiment analytics into investment decision-making and risk assessment.
