STAT6015A - Advanced quantitative risk management

Semester 2, 2022-23

Professor
Zhiqiang Zhang
Syllabus This course covers statistical methods and models of risk management, specially of Value-at-Risk (VaR). Contents include: Value-at-risk (VaR) and Expected Shortfall (ES); univariate models (normal model, log-normal model and stochastic process model) for VaR and ES; models for portfolio VaR; time series models for VaR; extreme value approach to VaR; back-testing and stress testing.
Course Objectives

On successful completion of the course, the students should be able to:

  1. apply Monte Carlo methods to determine the value of certain options and other derivative securities;
  2. predict volatility of a set of securities using appropriate volatility models;
  3. estimate the value at risk and expected shortfall of an investment portfolio;
  4. perform stress testing for value at risk models;
  5. estimate the probability of occurrence of rare events using extreme value theory.
Learning Outcomes
Course Learning Outcomes
CLO1. Upon successful completion of the course, students should be able to apply Monte Carlo methods to determine the value of certain options and other derivative securities.
CLO2. Upon successful completion of the course, students should be able to predict volatility of a set of securities using appropriate volatility models.
CLO3. Upon successful completion of the course, students should be able to estimate the value at risk and expected shortfall of an investment portfolio.
CLO4. Upon successful completion of the course, students should be able to perform stress testing for value at risk models.
CLO5. Upon successful completion of the course, students should be able to estimate the probability of occurrence of rare events using extreme value theory.
 
Prior knowledge expected Preliminary knowledge of probability and statistics is required.
Compatibility Nil
Topics covered
Course Content
1. Basic Monte Carlo Method
2. Variance Reduction Techniques
3. Simulating the Value of Options and the Value-at-Risk for Risk Management
4. Review of Univariate Volatility Models
5. Multivariate Volatility Models
6. Modeling High-Frequency Transactions Data
7. Extreme Value Theory for Risk Management
 
Assessment
Description Type Weighting * Tentative Assessment Period /
Examination Period ^
Written Assignments Continuous Assessment 40% -
Written exam covers all taught content in the course Written Examination 60% 3 - 23 May 2023
* 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 19 Jan 2023 (Thu) 7:00pm - 10:00pm KK-202 Face-to-face
Session 2 2 Feb 2023 (Thu) 7:00pm - 10:00pm KK-202 Face-to-face
Session 3 9 Feb 2023 (Thu) 7:00pm - 10:00pm KK-202 Face-to-face
Session 4 16 Feb 2023 (Thu) 7:00pm - 10:00pm KK-202 Face-to-face
Session 5 23 Feb 2023 (Thu) 7:00pm - 10:00pm KK-202 Face-to-face
Session 6 2 Mar 2023 (Thu) 7:00pm - 10:00pm KK-202 Face-to-face
Session 7 23 Mar 2023 (Thu) 7:00pm - 10:00pm KK-202 Face-to-face
Session 8 30 Mar 2023 (Thu) 7:00pm - 10:00pm KK-202 Face-to-face
Session 9 6 Apr 2023 (Thu) 7:00pm - 10:00pm KK-202 Face-to-face
Session 10 13 Apr 2023 (Thu) 7:00pm - 10:00pm KK-202 Face-to-face
Session 11 20 Apr 2023 (Thu) 7:00pm - 10:00pm KK-202 Face-to-face
Session 12 27 Apr 2023 (Thu) 7:00pm - 10:00pm KK-202 Face-to-face
KK - K.K. Leung Building
Add/drop 16 January, 2023 - 4 February, 2023
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