Investment Analysis with Machine Learning
Project Description

In this project, we will investigate the usefulness of machine learning in investment analysis. In particular, we will investigate what factors drive asset returns and whether machine learning algorithms can better capture the predictability of security returns. Students are required to have good python programming skills and knowledge about capital markets to be eligible for the project.

Supervisor
YOU Haifeng
Quota
3
Course type
UROP1000
UROP1100
Applicant's Roles

Students will be required to:
1) Review the literature on investment analysis and machine learning
2) Collect and process relevant structured and unstructured data
3) Conduct tests on investment theories using machine learning algorithms
4) Write up research report

Applicant's Learning Objectives

After the completion of the project, students should be familiar with:
1) the role of the macroeconomic, industry- and asset-specific information in driving security returns,
2) how to test theoretical predictions through empirical analysis,
3) how to apply machine learning algorithms in modeling securities prices/returns.

Complexity of the project
Challenging