Introduction to Algorithmic Trading – Financial Data and Modeling

MATH 585

This course explores the complexity of financial data and the challenges in modeling them.  Increasing portions of trading and investment activities are now fully automated. Many key decisions are driven by computer algorithms and models built on top of ever-larger financial data sets. Students will learn a variety of financial data sets, perform research and analysis on these data, and develop mathematical and risk management models for profitable trading and investment strategies.

David Ye received his PhD in Mathematics from Duke University.  After a career in academia he moved to finance, where he has been a chief risk officer for banking, insurance and trading firms.  He is currently the founder and CEO of TriLeaf Technologies.

Prerequisite:  Knowledge of linear algebra, probability, and a basic understanding of programing (preferably in Python).  Some understanding of finance is preferred; exposure to linear regression is also preferred.

Topics in mathematics suitable for advanced undergraduates or graduate students. Topics vary per semester. Instructor:  Dr. David Ye

** available as of 2021-08-15
Algorithmic Trading
Typically Offered
Fall and/or Spring