ST302      Half Unit
Stochastic Processes

This information is for the 2019/20 session.

Teacher responsible

Prof Umut Cetin COL.6.08


This course is compulsory on the BSc in Actuarial Science. This course is available on the BSc in Business Mathematics and Statistics, BSc in Financial Mathematics and Statistics, BSc in Mathematics with Economics, BSc in Mathematics, Statistics, and Business and BSc in Statistics with Finance. This course is available as an outside option to students on other programmes where regulations permit and to General Course students.


Students must have completed either Probability, Distribution Theory and Inference (ST202) or Probability and Distribution Theory (ST206).

Course content

A second course in stochastic processes and applications to insurance. Markov chains (discrete and continuous time), processes with jumps; Brownian motion and diffusions; Martingales; stochastic calculus; applications in insurance and finance. Content: Stochastic processes in discrete and continuous time; Markov chains: Markov property, Chapman-Kolmogorov equation, classification of states, stationary distribution, examples of infinite state space; filtrations and conditional expectation; discrete time martingales: martingale property, basic examples, exponential martingales, stopping theorem, applications to random walks; Poisson processes: counting processes, definition as counting process with independent and stationary increments, compensated Poisson process as martingale, distribution of number of events in a given time interval as well as inter-event times, compound Poisson process, application to ruin problem for the classical risk process via Gerber's martingale approach; Markov processes: Kolmogorov equations, solution of those in simple cases, stochastic semigroups, birth and death chains, health/sickness models, stationary distribution; Brownian motion: definition and basic properties, martingales related to Brownian motion, reflection principle, Ito-integral, Ito's formula with simple applications, linear stochastic differential equations for geometric Brownian motion and the Ornstein-Uhlenbeck process, first approach to change of measure techniques, application to Black-Scholes model. The items in the course content that also appear in the content of ST227 are covered here at greater depth. However, ST227 is not a pre-requisite for this course.


20 hours of lectures and 9 hours of seminars in the MT.

Week 6 will be a reading week left free for students to revise by themselves. 

Formative coursework

Compulsory written answers to two sets of problems.

Indicative reading

R Durrett, Essentials of Stochastic Processes; T Mikosch, Elementary Stochastic Calculus with Finance in View; Institute of Actuaries core reading notes.


Exam (100%, duration: 3 hours) in the January exam period.

Key facts

Department: Statistics

Total students 2018/19: 94

Average class size 2018/19: 31

Capped 2018/19: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Problem solving
  • Application of numeracy skills
  • Specialist skills