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Mathematical Finance II - MAT00074M

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  • Department: Mathematics
  • Module co-ordinator: Dr. Alex Daletskii
  • Credit value: 10 credits
  • Credit level: M
  • Academic year of delivery: 2022-23

Related modules

Pre-requisite modules

  • None

Co-requisite modules

  • None

Prohibited combinations

Module will run

Occurrence Teaching cycle
A Spring Term 2022-23

Module aims

To present classical mathematical approaches to portfolio selection and asset pricing in discrete and continuous time.

Module learning outcomes

By the end of this module students should be able to know/understand/do


  • The martingale approach to asset pricing.

  • Cox-Ross-Rubinstein formula for option pricing in discrete time.

  • Black-Scholes formula for option pricing in continuous time.

  • Basic models of interest rates, and compounding methods.

Furthermore the students will have developed their capacity at an advanced level to


  • Critically compare the above theories, identifying relative strengths and weaknesses.
  • Reason and make predictions in the field of mathematical finance using the methodology of stochastic processes.
  • Combine their understanding of the fundamental approaches above together with supporting literature to complete a self-study of a specific area of mathematical finance

Module content

In addition to lectures, Masters students will be required to complete a directed self-study into a specific area of mathematical finance which draws on their knowledge and understanding from lectures, and supported by additional reading and the seminars, to be assessed by regular coursework.



Task Length % of module mark
N/A 25
Online Exam 24 hrs
Mathematical Finance II
N/A 75

Special assessment rules



Task Length % of module mark
Online Exam 24 hrs
Mathematical Finance II - Reassessment
N/A 100

Module feedback

  • Summative fortnightly coursework, to be returned in seminars.
  • Examination result delivered in Week 10 of Summer Term, with model solutions and examiner’s comments available earlier.

Indicative reading

M Capinski and T Zastawniak, Mathematics for Finance; An Introduction to Financial Engineering, Springer.

The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.