| Unit convenor and teaching staff |
Unit convenor and teaching staff
Shuping Shi
Tutor
Rerotlhe Basele
Tutor
Fazeel Mohamed Jaleel
Tutor
Alex Berger
Tutor
Md Arafat Rahman
|
|---|---|
| Credit points |
Credit points
10
|
| Prerequisites |
Prerequisites
ECON2041 or STAT2372 or AFIN2070
|
| Corequisites |
Corequisites
|
| Co-badged status |
Co-badged status
|
| Unit description |
Unit description
This unit examines econometric techniques that are used in portfolio management, risk management and securities analysis. It provides students with the tools necessary for financial applications in these and other areas. Statistical techniques are developed in the context of particular financial applications. Recent empirical evidence is also discussed. |
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Late Submission Penalties
If you submit your assessment late, 5% of the total possible marks will be deducted for each day (including weekends), up to 7 days. Submissions more than 7 days late will receive a mark of 0.
Example 1 (out of 100):
If you score 85/100 but submit 20 hours late, you will lose 5 marks and receive 80/100.
Example 2 (out of 30):
If you score 27/30 but submit 20 hours late, you will lose 1.5 marks and receive 25.5/30.
Extensions
Automatic short extension: Some assessments are eligible for automatic short extension. You can only apply for an automatic short extension before the due date.
Special Consideration: If you need more time due to serious issues and for any assessments that are not eligible for Short Extension, you must apply for Special Consideration. Need help? Review the Special Consideration page for further details.
| Name | Weighting | Hurdle | Due | Groupwork/Individual | Short Extension | AI Approach |
|---|---|---|---|---|---|---|
| Skills development: Financial econometrics quiz | 30% | No | Week 7 (during lecture time & in person) | Individual | No | Observed |
| Skills development: Data analysis task | 30% | No | 13/05/2026 | Individual | Yes | Open |
| Formal examination | 40% | No | University Examination Period | Individual | No | Observed |
Assessment Type 1: Problem-based task
Indicative Time on Task 2: 15 hours
Due: Week 7 (during lecture time & in person)
Weighting: 30%
Groupwork/Individual: Individual
Short extension 3: No
AI Approach: Observed
Assessment Type 1: Professional task
Indicative Time on Task 2: 25 hours
Due: 13/05/2026
Weighting: 30%
Groupwork/Individual: Individual
Short extension 3: Yes
AI Approach: Open
Assessment Type 1: Examination
Indicative Time on Task 2: 30 hours
Due: University Examination Period
Weighting: 40%
Groupwork/Individual: Individual
Short extension 3: No
AI Approach: Observed
1 If you need help with your assignment, please contact:
2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation.
3 An automatic short extension is available for some assessments. Apply through the Service Connect Portal.
Delivery
The intended delivery mode is as per the timetable: https://publish.mq.edu.au/.
Resources
The prescribed textbook for the unit is:
In addition to the textbook, the following references are useful but are not required.
Material such as lecture slides, examples, and tutorial questions will be available on the unit home page. The text and lecture notes, together with the lectures and additional references will provide students with a clear indication of the basic content of the unit.
It is recommended that students attend all lectures and tutorials for several reasons including:
Technology Used and Required
Students are required to use a computer to carry out certain tasks of the course, such as tutorials and assignments.
Unit Web Page
• Course material is available on the learning management system (iLearn), which can be found at: http://ilearn.mq.edu.au.
The list below is a proposed study plan, but this may be modified as we progress through the semester to allow us to take more or less time with different sections of the course as required.
|
Week No. |
Lecture Topic |
Tutorials |
|
1 |
Characteristics of Financial Data; Revision of Basic Mathematical and Statistical Concepts Textbook: Chapter 1 and Chapter 2, all sections; 4th or 3rd Edition. Lecture Notes. |
|
|
2 |
Correlation and Basic Regression Methods Textbook: Chapter 3, all sections, excluding the appendix; 4th or 3rd Edition. Lecture Notes. |
Tutorial Week 2 |
|
3 |
Multiple Linear Regression Model Textbook: 4th Edition Chapter 4, Sections 4.1 to 4.7 inclusive, Section 4.9. Lecture Notes; or Textbook: 3rd Edition Chapter 4, Sections 4.1 to 4.8 inclusive, Section 4.10. Lecture Notes. |
Tutorial Week 3 |
|
4 |
Regression Model Diagnostics Textbook: Chapter 5, all sections. Chapter 10, Sections 10.1 to 10.3 inclusive; 4th or 3rd Edition. Lecture Notes. |
Tutorial Week 4 |
|
5 |
Time Series Models Textbook: Chapter 6, Sections 6.1 to 6.5; 4th or 3rd Edition. Lecture Notes. |
Tutorial Week 5 |
|
6 |
Identification of Time Series Models Textbook: Chapter 6, Sections 6.1 to 6.5; 4th or 3rd Edition. Lecture Notes. |
Tutorial Week 6 |
|
|
Mid-semester Break |
|
|
7 |
Class Test |
Tutorial Week 7 |
|
8 |
Forecasting with Time Series Models Textbook: 4th Edition, Chapter 6, Sections 6.10. Lecture Notes; or Textbook: 3rd Edition, Chapter 6, Sections 6.11 and 6.12. Lecture Notes. |
Tutorial Week 8 |
|
9 |
Modeling Volatility: Specification and Estimation of ARCH and GARCH Models Textbook: Chapter 9, Sections 9.1 to 9.4 inclusive, Sections 9.6 to 9.9 inclusive; 4th or 3rd Edition. Lecture Notes. |
Tutorial Week 9 |
|
10 |
Modeling Volatility (Extensions of GARCH Models) and Forecasting Volatility Textbook: 4th Edition, Chapter 9, Sections 9.10 to 9.18 inclusive, Lecture Notes; or Textbook: 3rd Edition, Chapter 9, Sections 9.10 to 9.19 inclusive, Lecture Notes.
Assignment due Wednesday @ 11:55pm (Sydney time). |
Tutorial Week 10 |
|
11 |
Nonstationarity in Financial Time Series Textbook: 4th Edition, Chapter 8, Sections 8.1. Lecture Notes; or Textbook: 3rd Edition, Chapter 8, Sections 8.1 & 8.3. Lecture Notes |
Tutorial Week 11 |
|
12 |
Long-Run Relationships in Finance Textbook: 4th Edition, Chapter 8, Sections 8.3 to 8.6.1 inclusive. Lecture Notes; or Textbook: 3rd Edition, Chapter 8, Sections 8.3 to 8.7.1 inclusive. Lecture Notes. |
Tutorial Week 12 |
|
13 |
Revision |
Tutorial Week 13 |
Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:
Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.
To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct
Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au
At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Academic Success provides resources to develop your English language proficiency, academic writing, and communication skills.
The Library provides online and face to face support to help you find and use relevant information resources.
Macquarie University offers a range of Student Support Services including:
Got a question? Ask us via the Service Connect Portal, or contact Service Connect.
For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/.
When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.
Unit information based on version 2026.04 of the Handbook