Optimal Investment Strategies

A major challenge for portfolio managers is that it is hard for them to predict the future. In practice, they would settle for being able to identify which stocks are likely to perform well and which are likely to perform badly in the next month. This project will include the investigation of algorithms for using specific collections of research data about a family of stocks to do just this, and will also be concerned with ways of assessing how best to compare the quality of alternative algorithms.

Greg Orosi
Faculty Supervisor: 
Drs. Len Bos & Tony Ware