AI for Financial Markets (NLP for Financial Markets)

Goals

The Artificial Intelligence for Financial Markets team explores applications of AI in finance, a rapidly growing field with emerging challenges and opportunities. A key aspect of our work involves creating high-quality datasets and benchmarking models for underexplored areas of finance. Students also learn to apply modern ML tools to better understand, analyze, and predict financial market behavior.

Issues Involved or Addressed

With the application of machine learning and natural language processing in finance comes the natural challenge of collecting and cleaning large datasets before applying any model. Students gain hands-on experience in data scraping, cleaning, labeling, and wrangling which are essential steps for building reliable datasets used in financial modeling. Once the data is prepared, students apply state-of-the-art ML and NLP models to explore questions in economics and financial markets. Past projects have included measuring subjectivity in earnings call transcripts, developing Text2SQL systems for financial databases, analyzing sentiment in financial news, exploring companies’ annual SEC reports through knowledge graphs, analyzing IPO filings, and using large language models to study corporate narratives and investor behavior. 

Partners/Sponsors

Center for Finance and Technology, Master of Science in Quantitative and Computational Finance (MS-QCF)