MA420      Half Unit
Quantifying Risk and Modelling Alternative Markets

This information is for the 2013/14 session.

Teacher responsible

Dr Pavel Gapeev


This course is available on the MSc in Applicable Mathematics, MSc in Financial Mathematics, MSc in Risk and Stochastics, MSc in Statistics (Financial Statistics) and MSc in Statistics (Financial Statistics) (Research). This course is available with permission as an outside option to students on other programmes where regulations permit.


Students must have completed Stochastic Processes (ST409).

Course content

This course is concerned with various issues arising in the context of investment risk specification as well as with the mathematical theory of so-called alternative markets, such as commodity and energy markets. In particular, the course considers the structural credit risk models and the quantification of risk by means of copulas and risk measures. Also, the course expands on the modeling of alternative markets and addresses the problem of valuation of investments in real assets.


20 hours of lectures and 10 hours of seminars in the MT. 2 hours of lectures in the ST.

Formative coursework

Two sets of written homework will be marked with feedback provided.

Indicative reading

F.Benth, J.Benth, S.Koekebakker, Stochastic Modelling of Energy and Related Markets, World Scientific 2008.
H.Föllmer and A.Schied, Stochastic Finance, 3rd edition, De Gruyter, 2011.
A.McNeil, R.Frey and P.Embrechts, Quantitative Risk Management, Princeton University Press, 2005.
A.K.Dixit and R.S.Pindyck, Investment under Uncertainty, Princeton University Press, 1994.


Exam (100%, duration: 2 hours) in the main exam period.

Key facts

Department: Mathematics

Total students 2012/13: Unavailable

Average class size 2012/13: Unavailable

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Self-management
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills