ST409      Half Unit
Stochastic Processes

This information is for the 2017/18 session.

Teacher responsible

Prof Kostas Kardaras COL 6.07


This course is compulsory on the MSc in Financial Mathematics and MSc in Quantitative Methods for Risk Management. This course is available on the MSc in Applicable Mathematics, MSc in Econometrics and Mathematical Economics, MSc in Operations Research & Analytics, MSc in Risk and Finance, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (Research) and MSc in Statistics (Research). This course is available with permission as an outside option to students on other programmes where regulations permit.


Students must have completed Further Mathematical Methods (MA212).

Good undergraduate knowledge of distribution theory

Course content

A broad introduction to stochastic processes for postgraduates with an emphasis on financial and actuarial applications. The course examines Martingales, Poisson Processes, Brownian motion, stochastic differential equations and diffusion processes. Applications in Finance. Actuarial applications.


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

Week 6 will be used as a reading week.

Indicative reading

T Bjork, Arbitrage Theory in Continuous Time; T Mikosch, Elementary Stochastic Calculus; S I Resnick, Adventures in Stochastic Processes; B K Oksendal, Stochastic Differential Equations: An Introduction with Applications, D Williams, Probability with Martingales.


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

Student performance results

(2013/14 - 2015/16 combined)

Classification % of students
Distinction 11.5
Merit 17.2
Pass 44
Fail 27.3

Key facts

Department: Statistics

Total students 2016/17: 70

Average class size 2016/17: 35

Controlled access 2016/17: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Team working
  • Problem solving
  • Application of information skills
  • Application of numeracy skills
  • Specialist skills