ST429 Half Unit
Statistical Methods for Risk Management
This information is for the 2025/26 session.
Course Convenor
Dr Xiaolin Zhu
Availability
This course is compulsory on the MSc in Quantitative Methods for Risk Management. This course is available on the Global MSc in Management, Global MSc in Management (CEMS MIM), Global MSc in Management (MBA Exchange), MSc in Data Science, MSc in Financial Mathematics, MSc in Statistics (Financial Statistics) and MSc in Statistics (Financial Statistics) (Research). This course is freely available as an outside option to students on other programmes where regulations permit. It does not require permission. This course uses controlled access as part of the course selection process.
How to apply: Compulsory on the MSc Quantitative Methods for Risk Management.
Students from any other programmes should check that they meet the pre-requisites in the course guide before applying and submit their transcript: a) indicating which courses are equivalent to the pre-requisites, and b) including brief information on such courses and syllabus. Providing this information will not aid a student’s chances of being accepted onto the course.
Priority is given to Department of Statistics students and those with the course listed in their programme regulations.
Deadline for application: Due to the nature of the method of application, interested students should apply as soon as possible after the opening selection and no later than 10.00am on Friday 26 September 2025.
Course lecturers will aim to make initial offers to students on LSE For You by Friday 26 September.
For queries contact: Stats-Msc@lse.ac.uk.
This course has a limited number of places (it is controlled access) and demand is typically very high. Priority is given to students on the MSc in Quantitative Methods for Risk Management programme, students from outside this programme may not get a place.
Requisites
Pre-requisites:
Students must have completed ST202 and ST302 before taking this course.
Additional requisites:
Previous programming experience would be helpful and students who have no previous experience in R must complete an online pre-sessional R course from the Digital Skills Lab before the start of the course (https://moodle.lse.ac.uk/course/info.php?id=8714).
Course content
This course covers fundamental concepts of loss functions, including risk factors and changes in risk factors. These concepts will be illustrated with examples of different value functions. For the quantitative analysis of portfolio losses, we introduce risk measures, providing a general overview ranging from variance to expected shortfall. We focus on highly important risk measures: Value at Risk (VaR) and Expected Shortfall (ES).
Considering a portfolio, we analyse the (joint) distribution and dependence among different risks. We cover multivariate models and copula models, including Sklar's theorem, fundamental copulas, Archimedean copulas and dependence measures. As part of dimension reduction, we also study principal component analysis. Finally, we examine the tail distributions and study the extreme value theory.
Teaching
9 hours of seminars, 20 hours of lectures and 5 hours of workshops in the Autumn Term.
This course has a reading week in Week 6 of Autumn Term.
Formative assessment
A set of exercises which are similar to problems appearing in the exam will be assigned. A set of coding exercises which are similar to examples in computer lab sessions will be assigned.
Indicative reading
A.McNeil, R.Frey, P.Embrechts, Quantitative Risk Management: Concepts, Techniques, Tools; Princeton Series in Finance
Assessment
Exam (75%), duration: 120 Minutes in the January exam period
Project (25%) in December
Key facts
Department: Statistics
Course Study Period: Autumn Term
Unit value: Half unit
FHEQ Level: Level 7
CEFR Level: Null
Total students 2024/25: 42
Average class size 2024/25: 21
Controlled access 2024/25: YesCourse selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Personal development skills
- Team working
- Application of information skills
- Application of numeracy skills
- Commercial awareness