ST429      Half Unit
Statistical Methods for Risk Management

This information is for the 2020/21 session.

Teacher responsible

Daniela Escobar


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), MSc in Statistics (Financial Statistics) (LSE and Fudan) and MSc in Statistics (Financial Statistics) (Research). This course is available as an outside option to students on other programmes where regulations permit.


Students must have completed Probability, Distribution Theory and Inference (ST202) and Stochastic Processes (ST302).

ST202, ST302, or equivalent

Course content

This course covers fundamental definitions of loss functions involving risk factors and risk factor changes. These concepts will be illustrated with examples of different value functions. For the quantitative analysis of the losses of a portfolio we introduce risk measures: General overview from variance to expected shortfall. We concentrate in highly important risk measures: Value at Risk (VaR) and Expected Shortfall (ES).

Considering a portfolio we analyse the distribution and dependence between different risks. We cover multivariate models and Copula models: Sklar's Theorem, Fundamental copulas, Clayton copulas, Archimedean copulas, Dependence measures. As part of dimension reduction we also study Principal component analysis. Finally, we also look at the tail of the distributions and study extreme value theory.


This course will be delivered through a combination of classes and lectures totalling a minimum of 300 hours across Michaelmas Term. This year, some or all of this teaching may be delivered through a combination of virtual classes and flipped-lectures delivered as short online videos. This course includes a reading week in Week 6 of MichaelmasTerm.

Formative coursework

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


Exam (75%, duration: 2 hours) in the January exam period.
Project (25%, 2000 words).

Student performance results

(2016/17 - 2018/19 combined)

Classification % of students
Distinction 32.4
Merit 33.8
Pass 23.2
Fail 10.6

Important information in response to COVID-19

Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.

Key facts

Department: Statistics

Total students 2019/20: 30

Average class size 2019/20: 20

Controlled access 2019/20: Yes

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Team working
  • Application of information skills
  • Application of numeracy skills
  • Commercial awareness