MFIN7037B - Quantitative trading

Semester 2, 2022-23

Professor
Alan Kwan
Syllabus This course provides a foundation for advanced quantitative trading in financial markets. The course has two parts. First, the course reviews stylised facts and methods used for time-series predictability, cross-sectional asset pricing and strategy performance evaluation. The second part of the course uses these tools to study recent advances in investment strategies sourcing from academic and practitioner literature. For example, the course will discuss new theories on risk premia, intermediation-based asset pricing, and quantifiable soft information and alternative data. The primary method of learning will be a combination of problem sets and projects. Subject to availability, learning will be supplemented with exposure to industry speakers from the local financial industry.
Course Objectives
  1. Gain fluency for analytical methods involved in performance evaluation and investment strategy design.
  2. Give students a working understanding of quantitative trading.
  3. Gain proficiency in programming and performing basic data cleaning, custodianship and data manipulation.
  4. Give students practice designing their own investment strategy.
Learning Outcomes
Course Learning Outcomes
CLO1. Students will learn to store and access data efficiently using modern database storage methods.
CLO2. Students will gain an overview of analytical methods used in finance and their typical application, and demonstrate understanding of how to apply the methods through highly-supervised programming assignments.
CLO3. Students will demonstrate strong fluency in one analytical method of their own choice through course projects.
CLO4. Students will be encouraged to creatively apply methods or data to generate trading strategies.
CLO5. Students will be encouraged to communicate ideas.
 
Pre-requisites Prerequisite: MFIN7002 Investment Analysis and Portfolio Management
Compatibility Nil
Assessment
Description Type Weighting * Tentative Assessment Period /
Examination Period ^		 Course Learning Outcomes
Group projects and class participation Continuous Assessment 100% - CLO1, 2, 3, 4, 5
* The weighting of coursework and examination marks is subject to approval
^ The exact examination date uses to be released when all enrolments are confirmed after add/drop period by the Examinations Office.  Students must oblige to the examination schedule. Students should NOT enrol in the course if they are not certain that they will be in Hong Kong during the examination period.  Absent from examination may result in failure in the course. There is no supplementary examination for all MSc curriculums in the Faculty of Engineering.
Course materials Selected course materials will be posted on the Moodle
Session dates
Date Time Venue Remark
Session 1 8 Feb 2023 (Wed) 6:30pm - 10:00pm Rm EFG, Cyberport 4 Face-to-face
Session 2 11 Feb 2023 (Sat) 2:00pm - 5:30pm Rm EFG, Cyberport 4 Face-to-face
Session 3 15 Feb 2023 (Wed) 6:30pm - 10:00pm Rm EFG, Cyberport 4 Face-to-face
Session 4 18 Feb 2023 (Sat) 2:00pm - 5:30pm Rm EFG, Cyberport 4 Face-to-face
Session 5 22 Feb 2023 (Wed) 6:30pm - 10:00pm Rm EFG, Cyberport 4 Face-to-face
Session 6 25 Feb 2023 (Sat) 2:00pm - 5:30pm Rm EFG, Cyberport 4 Face-to-face
Session 7 1 Mar 2023 (Wed) 6:30pm - 10:00pm Rm EFG, Cyberport 4 Face-to-face
Session 8 4 Mar 2023 (Sat) 2:00pm - 5:30pm Rm EFG, Cyberport 4 Face-to-face
Session 9 8 Mar 2023 (Wed) 6:30pm - 10:00pm Rm EFG, Cyberport 4 Face-to-face
Session 10 11 Mar 2023 (Sat) 2:00pm - 5:30pm Rm EFG, Cyberport 4 Face-to-face
Add/drop 16 January, 2023 - 11 February, 2023
Back