All activities that form part of this course will be delivered remotely
The course offers an introduction to modern stochastic processes, including Brownian motion, continuous-time martingales, stochastic integration and Ito's calculus, Markov processes, stochastic differential equations, point processes and their applications. The course will include some applications but will emphasise setting up a solid theoretical foundation for the subject.
The course will provide a sound basis for progression to other honours and post-graduate courses including mathematical finance, stochastic analysis and statistics, and actuarial sciences.
The course aims to round off the rigorous introduction to probabilistic reasoning initiated in STAT3004, as well as to substantially enhance students' depth of knowledge in the mathematical underpinning of stochastic process theory.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Explain the fundamental concepts of stochastic processes in continuous time and their position in modern statistical and mathematical sciences and applied contexts;
- Demonstrate accurate and efficient use of stochastic calculus techniques;
- Demonstrate mathematical reasoning through analysing, proving and explaining concepts from stochastic analysis; and,
- Apply problem-solving techniques using stochastic analysis methods in various situations.
Indicative Assessment
- Typical assessment may include, but is not restricted to: exams, assignments, quizzes, presentations and other assessment as appropriate (100) [LO 1,2,3,4]
In response to COVID-19: Please note that Semester 2 Class Summary information (available under the classes tab) is as up to date as possible. Changes to Class Summaries not captured by this publication will be available to enrolled students via Wattle.
The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Workload
Students are expected to commit 130 hours of work in completing this course. This includes time spent in scheduled classes and self-directed study time.
Inherent Requirements
Not applicable
Requisite and Incompatibility
Prescribed Texts
Information about the prescribed textbook will be available via the Class Summary.
Assumed Knowledge
Students will require a good background in elementary stochastic processes and probability theory such as introduced in STAT2005 and STAT3004.
Fees
Tuition fees are for the academic year indicated at the top of the page.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- 2
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2020 | $4050 |
- International fee paying students
| Year | Fee |
|---|---|
| 2020 | $5760 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
Second Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 8252 | 27 Jul 2020 | 03 Aug 2020 | 31 Aug 2020 | 30 Oct 2020 | In Person | View |
