STAT6013A - Financial data analysis

Semester 1, 2022-23

Professor
K.C. Yuen
Teaching assistant
N/A
Syllabus This course aims at introducing statistical methodologies in analysing financial data.  Financial applications and statistical methodologies are intertwined in all lectures.  Contents include: recent advances in modern portfolio theory, Copula, market microstructure, stochastic volatility models and high frequency data analysis.
Course Objectives

This course takes a quantitative approach to investment analysis. Students who successfully complete this course will be able to:

  • apply modern techniques to construct the optimal investment portfolios;
  • understand market microstructure;
  • model high frequency data
Learning Outcomes
Course Learning Outcomes
CLO1. Upon successful completion of the course, students should be able to understand classical and modern portfolio theory such as factor-based models
CLO2. Upon successful completion of the course, students should be able to understand robust estimation and robust portfolio selection.
CLO3. Upon successful completion of the course, students should be able to understand stylized facts about market microstructure.
CLO4. Upon successful completion of the course, students should be able to understand modelling of high frequency financial data that takes into account market microstructure.
 
Prior knowledge expected Preliminary knowledge of probability and statistics is required.
Compatibility Nil
Topics covered
Course Content
1. Classical Portfolio Theory
2. Portfolio Selection in Practice
3. Factor-Based Portfolio Analysis
4. Robust Parameter Estimation
5. Robust Portfolio Selection
6. Market Microstructure
7. Volatility Modelling
8. Models for High Frequency Data
 
Assessment
Description Type Weighting * Tentative Assessment Period /
Examination Period ^
Written Assignments & Project Continuous Assessment 40% -
Written exam covers all taught content in the course. Written Examination 60% 8 - 23 December 2022
* 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 3 Sep 2022 (Sat) 2:30pm - 5:20pm LE-1  
Session 2 10 Sep 2022 (Sat) 2:30pm - 5:20pm LE-1  
Session 3 17 Sep 2022 (Sat) 2:30pm - 5:20pm LE-1  
Session 4 24 Sep 2022 (Sat) 2:30pm - 5:20pm LE-1  
Session 5 8 Oct 2022 (Sat) 2:30pm - 5:20pm LE-1  
Session 6 15 Oct 2022 (Sat) 2:30pm - 5:20pm LE-1  
Session 7 22 Oct 2022 (Sat) 2:30pm - 5:20pm LE-1  
Session 8 29 Oct 2022 (Sat) 2:30pm - 5:20pm TT-404  
Session 9 5 Nov 2022 (Sat) 2:30pm - 5:20pm LE-1  
Session 10 12 Nov 2022 (Sat) 2:30pm - 5:20pm LE-1
Session 11 19 Nov 2022 (Sat) 2:30pm - 5:20pm LE-1  
Session 12 26 Nov 2022 (Sat) 2:30pm - 5:20pm LE-1  
LE - Library Extension Building
TT - T. T. Tsui Building
Add/drop 1 September 2022 - 10 September 2022
Quota 100   [Priority to MSTAT & MDASC students]
Back