Developing an Agent AI for Quantitative Analysis
Project Description
This project aims to build an autonomous Agent AI specialized in quantitative analysis. The agent integrates multi source data from various sources, and uses machine learning and statistical models to conduct data cleaning, factor mining, and backtesting. It supports automated strategy generation, real time monitoring, and alerting, reducing manual intervention with modular design and API access. The goal is to improve analysis efficiency, lower technical barriers, and provide stable, interpretable decision support.
Supervisor
SU, Haibin
Quota
5
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP3200
UROP4100
Applicant's Roles
Data cleaning, factor mining, backtesting; reasoning unit; context engineering; action unit
Applicant's Learning Objectives
Hands-on experiences in Agent AI applications
Complexity of the project
Moderate