ST409      Half Unit
Stochastic Processes

This information is for the 2018/19 session.

Teacher responsible

Prof Kostas Kardaras COL 6.07

Availability

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.

Pre-requisites

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.

Teaching

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.

Assessment

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

Student performance results

(2014/15 - 2016/17 combined)

Classification % of students
Distinction 17.6
Merit 15.7
Pass 44.8
Fail 21.9

Key facts

Department: Statistics

Total students 2017/18: 72

Average class size 2017/18: 35

Controlled access 2017/18: 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