Dr Hao Xing COL 7.12

This course is available on the MSc in Financial Mathematics, MSc in Management, MSc in Management (CEMS MIM), MSc in Management, Organisations and Governance, MSc in Risk and Stochastics and MSc in Statistics (Financial Statistics). This course is available as an outside option to students on other programmes where regulations permit.

A self-contained introduction to probabilistic and statistical methods in risk management. This course starts with risk factors models and loss distributions, which are illustrated via examples in stocks, derivatives, and bonds portfolios. Axioms of coherent risk measures are introduced. Value at risk and other risk measures are introduced and their relation with coherent risk measures is discussed. Multivariate factor models are introduced and analysed: covariance and correlation estimations, multivariate normal distributions and their testing, normal mixture distributions and their fitting to data. The theory of copulas is introduced: meta distributions, tail dependence, fitting copulas to data. Some limitations of copulas are also discussed. The extreme value theory is introduced: generalized extreme value distribution, threshold exceedances and generalized Pareto distribution, modelling and measures of tail risk. Applications to insurance with large loss are also discussed. Students will be exposed to financial data via sets of computer-based classes and exercises.

20 hours of lectures and 10 hours of seminars in the LT.

An informal 'open book' mid-term practice examination will take place in Week 6.

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.

A.McNeil, R.Frey, P.Embrechts, Quantitative Risk Management: Concepts, Techniques, Tools; Princeton Series in Finance

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