Stock-market investing and trading system

Computers have been applied to the stock market for decades. Consequently, a significant portion of this project will be to examine and evaluate existing systems.  As of right now, the most interesting new use of computing for stock-market investing and trading will be the application of machine learning (ML) techniques—and in particular techniques such as transformers, used in the production of natural language texts. 

The goal of this project is to explore the use of consumer-level computing systems for stock-market investing and trading. The primary deliverables will be (a) a report on findings and (b) executable code.

Student Team
  • Fardeen Abir
  • Nathan Campos
  • Anthony Edeza
  • Jose Flores De Santiago
  • Edward Kim
  • Kenneth Lieu
  • Kevin Mateo
  • Michael Nguyen
  • Roberto Reyes
  • Maggie Yang
Project Sponsor
Computer Science
Project Liaisons
  • Russ Abbott
Faculty Advisors
  • Yuqing Zhu