Zeng YaWen
Papers
1
Total Citations
10
H-Index
1
About
Zeng YaWen is a rising researcher at the intersection of natural language processing and financial technology, with a primary focus on explainable AI for stock market analysis. Her most notable contribution is the development of "FinReport," a novel framework introduced in her 2024 paper that leverages large language models to automatically mine financial factors from news articles and generate transparent, explainable stock earnings forecasts. This work addresses a critical gap for ordinary investors who lack the resources of financial institutions, making sophisticated market analysis more accessible. Although early in her career, with her flagship paper already garnering 10 citations, Zeng's work represents a significant step toward democratizing financial intelligence. Her research uniquely combines factor modeling with news sentiment analysis, offering both predictive power and interpretability—a rare combination in quantitative finance. By bridging the gap between complex financial models and user-friendly explanations, Zeng YaWen is pioneering a new paradigm in AI-assisted investment decision-making, with potential implications for retail investors and financial analysts alike.
Research Focus
Key Achievements
Top Papers
- 1