Overview
Homogeneous Markov chains in finite and countable state space. Foster-Lyapunov criterion for recurrence and transience. Random walks in one and more dimensions. Polya theorem. Limit theorems: law of iterated logarithms, functional central limit theorem. Connections with the Brownian motion and the heat equation. Applications of random walks to finance and … For more content click the Read More button below.
Offerings
S2-01-CLAYTON-ON-CAMPUS
Rules
Enrolment Rule
Contacts
Chief Examiner(s)
Dr Ivan Guo
Unit Coordinator(s)
Dr Ivan Guo
Learning outcomes
On successful completion of this unit, you should be able to:
1.
Develop specialised mathematical knowledge and skills within the theories of markov chains and random walks.
2.
Apply sophisticated stochastic modelling skills within a variety of contexts, from a wide range of scientific areas of knowledge.
3.
Apply critical thinking to problems in Markov chains in general, and in the theory of random walks in particular.
4.
Formulate expert solutions to practical financial, engineering or scientific problems using specialised cognitive and technical skills within the theories of markov chains and random walks.
Teaching approach
Active learning
Assessment
1 - Continuous assessment
2 - Final assessment - Exam (3 hours and 10 minutes)
Scheduled and non-scheduled teaching activities
Applied sessions
Seminars
Workload requirements
Workload
Other unit costs
Costs are indicative and subject to change.
Miscellaneous items required (Printing, Stationery) - $100.