Conventional macroeconomic indicators are released with a time lag and may therefore provide limited information about rapidly changing market expectations, creating a need for complementary high-frequency indicators capable of capturing the informational content of financial narratives. This study examines whether sentiment extracted from unstructured financial text contains incremental predictive information for short-horizon market dynamics in the context of Eastern Europe’s green and digital transition. Using financial news and discourse collected between May 2025 and May 2026, a FinBERT-based Daily Sentiment Index (DSI) is constructed for selected technology, energy, and sustainability-related narratives and linked to market indicators and representative assets, including the DAX, UiPath, and OMV Petrom. The empirical strategy combines Granger predictability tests, vector autoregression (VAR), GARCH(1,1) models with sentiment effects, lead–lag analysis, Bai–Perron structural-break tests, and Markov-switching specifications to assess predictive temporal relationships, volatility dynamics, and time variation in sentiment–market interactions. Forecasting utility is further evaluated through an expanding-window out-of-sample exercise in which a sentiment-augmented VAR is compared with a benchmark autoregressive specification using one-day-ahead DAX returns, with relative predictive accuracy evaluated via the Diebold–Mariano test. The results indicate that lagged sentiment contains statistically significant predictive information for subsequent market returns and that incorporating the DSI significantly improves out-of-sample forecast accuracy relative to the benchmark specification. The evidence also reveals heterogeneous and time-varying responses across the selected cases: technology-related assets exhibit comparatively differentiated sensitivity to macro-sentiment conditions, whereas the energy case displays stronger exposure to transition-related narratives. Structural-break and regime-dependent estimates further suggest instability in the relationship between ESG sentiment and market performance over the sample period, but do not establish a permanent structural transformation in investor preferences. The study contributes to the narrative-economics and computational-finance literature by providing applied evidence that domain-specific textual sentiment contains incremental short-horizon information beyond conventional market dynamics and can complement lagged macroeconomic indicators in financial forecasting and risk-monitoring applications.

This study investigates the role of higher education in improving the employability of young graduates in the NorthEast region of Romania, highlighting its contribution to bridging the gap between academic training and labor market demands. The research aims to identify the determinants of graduates' success in securing and maintaining employment relevant to their fields of study, while analyzing discrepancies between academic curricula and employer expectations. Using a mixed-methods approach, the study combines quantitative and qualitative methodologies to provide comprehensive insights. A structured survey was conducted with 200 graduates across disciplines and 11 employers in the region. Survey questions explored educational experiences, job search strategies, and the applicability of skills in professional settings. The data were analyzed using the Statistical Package for the Social Sciences (SPSS), employing Principal Component Analysis (PCA) to identify key factors influencing employability. These determinants include career advancement opportunities, salary competitiveness, and practical application of academic training. Additionally, semi-structured interviews with employers offered nuanced perspectives on essential competencies such as communication skills, technical expertise, digital literacy, and adaptability. Results indicate that 82.5% of graduates secured employment post-graduation, but 60% were employed outside their academic specialization, underscoring a mismatch between training and labor market needs. Employers emphasized the importance of internships, university-business collaborations, and experiential learning to better prepare graduates for professional challenges. This study underscores the need for higher education institutions to align curricula with labor market requirements by fostering university-employer partnerships, incorporating practical learning experiences, and developing transversal skills.