FA 631 Investment, Portfolio Construction, and Trading Analytics

The significant amount of information available in any field requires a systematic and analytical approach to select the most important information and anticipate major events. Machine learning algorithms facilitate this process understanding, modeling and forecasting the behavior of major social or economic systems and their variables. This is an applied research course that explores how to apply fundamental machine learning models to predict financial time series and solve financial problems. Some of the financial applications explored are algorithmic trading, model calibration, portfolio optimization, and risk management.




BIA 610, BIA 656, CS 559, FE 590, FE 690, MIS 637 or Instructor Permission.


School of Business

Typically Offered Periods

Fall Semester