Students

ECON3034 – Financial Econometrics

2022 – Session 1, In person/Online-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Unit Convenor
Lance Fisher
4 Eastern Road, Room 410
Credit points Credit points
10
Prerequisites Prerequisites
90cp at 1000 level or above including ECON241 or ECON2041 or STAT272 or STAT2372
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This unit is highly recommended for students majoring in economics and finance. Finance professionals use econometric techniques in portfolio management, risk management and securities analysis. This unit is intended to provide students with the tools necessary for financial applications. Statistical techniques are developed within the context of particular financial applications. Recent empirical evidence is also discussed. Although ECON2032 is not a prerequisite, it is highly recommended.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Apply econometric methods to modelling, analysing and forecasting financial data.
  • ULO2: Demonstrate and explain different estimation methodologies.
  • ULO3: Critically evaluate empirical econometric work.
  • ULO4: Present results based on financial econometric analysis, to a non-technical audience, in a clear and understandable manner.

General Assessment Information

Late submissions of assessments

Unless a Special Consideration request has been submitted and approved, no extensions will be granted. There will be a deduction of 10% of the total available assessment-task marks made from the total awarded mark for each 24-hour period or part thereof that the submission is late. Late submissions will only be accepted up to 96 hours after the due date and time.

No late submissions will be accepted for timed assessments – e.g., quizzes, online tests.

Table 1: Penalty calculation based on submission time

Submission time after the due date (including weekends)

Penalty (% of available assessment task mark)

Example: for a non-timed assessment task marked out of 30

<24 hours

10%

10% x 30 marks = 3-mark deduction

24-48 hours

20%

20% x 30 marks = 6-mark deduction

48-72 hours

30%

30% x 30 marks = 9-mark deduction

72 – 96 hours

40%

40% x 30 marks = 12-mark deduction

>96 hours

100%

Assignment won’t be accepted

 

Special Consideration

To request an extension on the due date/time for a timed or non-timed assessment task, you must submit a Special Consideration application. An application for Special Consideration does not guarantee approval.

The approved extension date for a student becomes the new due date for that student. The late submission penalties above then apply as of the new due date.

Assessment Tasks

Name Weighting Hurdle Due
Class test 30% No Week 7 (during lecture time)
Assignment 30% No Week 10, Thursday 4pm (Sydney time)
Final examination 40% No University examination period

Class test

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 15 hours
Due: Week 7 (during lecture time)
Weighting: 30%

 

The class test will be held online during the week 7 lecture time. The test will consist of multiple-choice questions, and will cover all material up to and including Week 5.

 


On successful completion you will be able to:
  • Apply econometric methods to modelling, analysing and forecasting financial data.
  • Demonstrate and explain different estimation methodologies.

Assignment

Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 25 hours
Due: Week 10, Thursday 4pm (Sydney time)
Weighting: 30%

 

A series of short answer questions exploring various aspects of Financial Econometrics.

 


On successful completion you will be able to:
  • Critically evaluate empirical econometric work.
  • Present results based on financial econometric analysis, to a non-technical audience, in a clear and understandable manner.

Final examination

Assessment Type 1: Examination
Indicative Time on Task 2: 30 hours
Due: University examination period
Weighting: 40%

 

A two-hour open book examination will be held during the University Examination Period, and will consist of multiple-choice and short-answer questions. Computer outputs and statistical tables will be provided.

 


On successful completion you will be able to:
  • Demonstrate and explain different estimation methodologies.
  • Critically evaluate empirical econometric work.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

Delivery 

The intended delivery mode may need to change after the start of the session due to the evolving covid situation and students need to ensure they keep up with iLearn Announcements made during the session accordingly.

Resources

The prescribed textbook for the unit is:

Brooks, C. (2019) Introductory Econometrics for Finance, 4th Edition, Cambridge University Press. The 4th Edition of the textbook has been recently published. You can use the 3rd Edition of the textbook (2014) instead if you prefer.  

In addition to the textbook, the following references are useful but are not required.

(i) Campbell, J., Lo, A., and Mackinlay, C. (1997) The Econometrics of Financial Markets, Princeton University Press. (This book is too advanced for our class, but contains a lot of interesting material).

(ii) Diebold, F. (2007) Elements of Forecasting, 4th Edition, South-Western College

(iii) Enders, W. (2014) Applied Econometric Time Series, 4th Edition, Wiley.

• 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:

• Not all the material in the text is included in the unit, and not all the material in the unit is covered in the text. In some places the text deals with issues in greater depth than is necessary for the unit, and in other places it doesn’t go far enough. The lectures contain all the unit material taught at the level required for the assessment tasks, and are your guide to the unit content.

• The approaches to some problems that are recommended by the lecturer are different to those in the text.

• The lectures will include guidance about the style and content of the final exam and recommendation about study technique.

•  It is difficult (and often impossible) for staff to provide meaningful assistance to students outside class times on topics for which they did not attend the relevant lectures and tutorials.

Technology Used and Required

Students are required to use a computer to carry out certain tasks of the course, such as tutorials and assignments. The software programs used in this course include EViews 10 and Microsoft Excel. 

Unit Web Page

• Course material is available on the learning management system (iLearn), which can be found at: http://ilearn.mq.edu.au.

Unit Schedule

Unit Schedule

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. 

No tutorial this week.

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: 4th Edition Chapter 5, all sections. Chapter 10, Sections 10.1 to 10.3 inclusive. Lecture Notes; or

Textbook: 3rd Edition Chapter 5, all sections. Chapter 10, Sections 10.1 to 10.3 inclusive. Lecture Notes.

Tutorial Week 4

5

Time Series Models

Textbook: 4th Edition, Chapter 6, Sections 6.1 to 6.5. Lecture Notes; or

Textbook: 3rd Edition, Chapter 6, Sections 6.1 to 6.5. Lecture Notes.

Tutorial Week 5

6

Identification of Time Series Models

Textbook: 4th Edition, Chapter 6, Sections 6.6 to 6.8. Lecture Notes; or

Textbook: 3rd Edition, Chapter 6, Sections 6.6 to 6.9. Lecture Notes.

Tutorial Week 6

7

Class Test

Tutorial Week 7
 

Mid-semester Break

 

8

Forecasting with Time Series Models (Pre-recorded lecture due to public holiday)

Textbook: 4th Edition, Chapter 6, Sections 6.10. Lecture Notes; or

Textbook: 3rd Edition, Chapter 6, Sections 6.11 and 6.12. Lecture Notes.

Lecture is pre-recorded this week ONLY

Tutorial Week 8

9

Modeling Volatility: Specification and Estimation of ARCH and GARCH Models

Textbook: 4th Edition, Chapter 9, Sections 9.1 to 9.4 inclusive, Sections 9.6 to 9.9 inclusive. Lecture Notes; or

Textbook: 3rd Edition, Chapter 9, Sections 9.1 to 9.4 inclusive, Sections 9.6 to 9.9 inclusive. Lecture Notes.

Tutorial Week 9

10

Modeling Volatility: Extensions of ARCH and GARCH Models. 

Textbook: 4th Edition, Chapter 9, Sections 9.10 to 9.17 inclusive, Lecture Notes; or

Textbook: 3rd Edition, Chapter 9, Sections 9.10 to 9.18 inclusive, Lecture Notes.

Assignment due Thursday 4pm.

Tutorial Week 10

11

Forecasting Volatility.

Textbook: 4th Edition, Chapter 9, Sections 9.18. Lecture Notes; or

Textbook: 3rd Edition, Chapter 9, Sections 9.17, 9.19. Lecture Notes.

Tutorial Week 11

12

Long-Run Relationships in Finance

Textbook: 4th Edition, Chapter 8, Sections 8.1, 8.3 to 8.6.1 inclusive. Lecture Notes; or

Textbook: 3rd Edition, Chapter 8, Sections 8.1, 8.3 to 8.7.1 inclusive. Lecture Notes.

Tutorial Week 12

13

Bivariate Autoregressive Models

Textbook: 4th Edition, Chapter 7, Sections 7.10, 7.12. Lecture Notes; or

Textbook: 3rd Edition, Chapter 7, Sections 7.11, 7.13. Lecture Notes. 

Policies and Procedures

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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.

Student Code of Conduct

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

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 ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

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.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

The Writing Centre

The Writing Centre 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. 

Student Services and Support

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Student Enquiries

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IT Help

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