This paper is intended to introduce students to the applications of Artificial Intelligence (AI) in finance. Standard Computational Finance problems such as index tracking, algorithmic trading, and corporate failure prediction will be investigated, and students will learn how to solve these problems using advanced computational techniques from the AI research literature, such as natural computing and data mining.
Either COMP316 Artificial Intelligence Techniques and Applications or
COMP321 Practical Data Mining and
a further 40 points at 300 level Computer Science
COMP556 Computational Finance
Official Timetable Information
Internal assessment/final examination ratio: 1:0
ALL assessment components are mandatory.
- Assignment 1: 15%
- Assignment 2: 15%
- Assignment 3: 15%
- Assignment 4: 40%
- Presentation: 15%
Class attendance is expected. The course notes provided are not comprehensive, additional material will be covered in class. You are responsible for all material covered in class.
Follow this link for Academic Integrity information.
Follow this link for information on Performance Impairment.
Student Concerns and Complaints
Follow this link for Student Concerns and Complaints information.
Application for Extension
Follow this link for information on applying for an Extension.
Review of Grade
Follow this link for information on applying for a Review of Grade.
Your attention is drawn to the following regulations and policies, which are published in the University Calendar: