Dr Xiaolin Zhu

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 Financial Statistics and MSc in 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. For information on controlled access courses, including eligibility, application processes, deadlines, and departmental contact details, please refer to the Controlled Access Courses webpage.

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.

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 9:30am on Thursday 24 September 2026.

Course lecturers will aim to make initial offers to students on LSE For You by Thursday 24 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.

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).

This course introduces the quantitative methods used in financial risk management. The course begins with the analysis of portfolio losses, covering key risk measures including Value at Risk and Expected Shortfall, and their theoretical foundations.

A central theme is the modelling of dependence among risks. The course covers multivariate models and copula theory — including Sklar's theorem, fundamental and Archimedean copulas, and dependence measures — providing tools for analysing the joint distribution of portfolio losses. Dimension reduction techniques, particularly principal component analysis, are also introduced.

The course concludes with an examination of tail behaviour and extreme value theory, equipping students with methods for modelling rare but severe loss events.

Theoretical concepts are complemented by computational implementation in R throughout the course.

9 hours of seminars, 20 hours of lectures and 5 hours of workshops in the Autumn Term.

This course has no reading week in Autumn Term.

Problem sets similar to exam questions will be assigned. Coding exercises for computer workshops will also be assigned.

McNeil, A. J., Frey, R., & Embrechts, P. (2015). Quantitative risk management: concepts, techniques and tools. Princeton university press.

Exam (75%), duration: 120 Minutes in the January exam period.

Project (25%) in December.