The Natural Language Processing (NLP) for Financial Markets team works on the development and application of NLP models for Financial Markets Including but not limited to Equity Market, Bond Market, and Cryptocurrency Market. Modern techniques help to better understand and predict financial market movements for investment in various financial markets through state-of-the-art NLP like FLANG-BERT, ChatGPT, etc.
Issues Involved or Addressed
With the application of NLP in financial markets comes the natural challenge of the need to collect and clean large datasets before applying any model. Many projects under the team require substantial data scraping, data cleaning, data labeling, and data wrangling. We try to optimize all data-related tasks using the latest ideas for example data labeling tasks can be optimized by employing weak-supervision techniques. Once we convert unstructured data to a more structured machine-readable form, we apply the latest ML/NLP models to answer essential questions about economics, and various financial markets. In the past students in our team worked on a wide range of problems including, “Using ChatGPT-based Sentiment Analysis on Consumer Reviews to Predict Price Changes of Products on Amazon”, “Investor Insight: Exploring Companies’ Annual SEC Reports through Knowledge Graphs”, “How Automobile Companies Change Narrative Based on EV Policy Change”, “Understanding Effect of Inflation on Real Estate Industry through NLP”, etc.
Methods and Technologies
Academic Majors of Interest
- Computing›Algorithms, Combinatorics and Optimization
- Computing›Computational Science and Engineering
- Computing›Computer Science
Preferred Interests and Preparation
Motivated and interested in learning novel approaches in finance and machine learning. Strong motivation and passion to learn or work in the Finance and FinTech industry. Effective communication skills. Have solid ground in programming in python. Familiarity with basic SDE tools like Git and GitHub (if not, you will be required to attend workshop offered by PACE). Driven and committed, self-motivation and eagerness to become familiar with new concepts. Ability to work well with others across teams with varied strengths.
Meeting Schedule & Location
- Scheller College of Business
- Computational Science and Engineering