<![CDATA[The rapid expansion of digital financial information has increased the influence of news-driven narratives on capital market behavior in emerging ASEAN economies. This study examines how financial news sentiment affects stock returns and conditional volatility in Indonesia, Malaysia, and Singapore during 2015–2024. A daily sentiment index was constructed from Reuters, Bloomberg, Factiva, and LexisNexis articles using a hybrid Natural Language Processing (NLP) approach combining lexicon-based methods and FinBERT classification. The sentiment measures were integrated into panel regression, correlated random effects (CRE), Granger causality, and GARCH(1,1) models. The results show that sentiment significantly affects both returns and volatility across ASEAN markets. A one-standard-deviation decline in sentiment increases conditional volatility by approximately 10.3% in Indonesia (p < 0.01), with weaker effects observed in Malaysia and Singapore. The return estimations indicate that a one-unit increase in sentiment raises next-day returns by approximately 0.084 percentage points. Negative sentiment generates stronger volatility responses than positive sentiment, supporting behavioral asymmetry and loss-aversion interpretations. Cross-country findings further show that sentiment sensitivity is strongest in Indonesia and weakest in Singapore, suggesting that institutional development moderates the transmission of digital information into market outcomes. The study contributes by integrating FinBERT-based sentiment analysis with comparative ASEAN financial econometrics and demonstrates the growing importance of narrative-driven risk in emerging capital markets. Keywords: Financial news sentiment; Market stability; Indonesia; ASEAN equity markets JEL Classification: G14; G15; C58]]>
Copyrights © 2026
