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)

Associate Professor Kais Hamza

Unit Coordinator(s)

Associate Professor Kais Hamza

Notes

IMPORTANT NOTICE:
Scheduled teaching activities and/or workload information are subject to change in response to COVID-19, please check your Unit timetable and Unit Moodle site for more details.

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 - In-semester assessment
2 - Examination (3 hours and 10 minutes)

Scheduled and non-scheduled teaching activities

Applied sessions
Lectures

Workload requirements

Workload

Other unit costs

Costs are indicative and subject to change.
Miscellaneous Items Required (Printing, Stationery) - $100.