Lili LIU
Department of Information Systems and Analytics, School of Computing, National University of Singapo, Singapore
Publications
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Review Article
Empowering Stock Trading through Macroeconomic Events: A Deep Learning-Based NLP Framework
Author(s): Yaoyi Duan and Lili LIU*
Macroeconomic announcements—such as central bank policy decisions, employment statistics, and inflation reports—have a profound impact on equity markets. However, extracting actionable insights from such textual disclosures remains a significant challenge due to the complexity, ambiguity, and temporally dynamic nature of economic language. In this paper, we propose a novel deep learning-based Natural Language Processing (NLP) framework designed to empower stock trading strategies through automated interpretation of macroeconomic events. Our approach integrates FinBERT—a transformer-based language model pretrained on financial corpora—with Long Short- Term Memory (LSTM) networks to capture both the semantic and sequential characteristics of economic news. We construct a large-scale dataset comprising over 5,000 timestamped macroeconomic headlines linke.. Read More»