Algorithmic Trading Strategies
Project Description

This project incorporates new factors such as qualitative and behavioral factors into trading strategies.

Supervisor
CHEN Yanzhen
Quota
10
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP4100
Applicant's Roles

Students are expected to assist in reviewing literature, processing data, and/or analyzing results.

Applicant's Learning Objectives

Students should gain insights into algorithmic trading and backtesting. In addition, students would obtain relevant research experience.

Complexity of the project
Challenging