Time Series Analysis and Forecasting

Subject ECOM30004 (2015)

Note: This is an archived Handbook entry from 2015.

Credit Points: 12.5
Level: 3 (Undergraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2015:

Semester 2, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 27-Jul-2015 to 25-Oct-2015
Assessment Period End 20-Nov-2015
Last date to Self-Enrol 07-Aug-2015
Census Date 31-Aug-2015
Last date to Withdraw without fail 25-Sep-2015


Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: Two 1-hour lectures and a 1-hour tutorial/practice class per week
Total Time Commitment:

An estimated total time commitment of at least 170 hours.
Prerequisites:

One of:

Subject
Study Period Commencement:
Credit Points:
Semester 1
12.50
Semester 1
12.50

OR both of the following:

Subject
Study Period Commencement:
Credit Points:
Semester 1
12.50
Semester 2
12.50
Corequisites:

None
Recommended Background Knowledge:

Please refer to Prerequisites and Corequisites.
Non Allowed Subjects:

None
Core Participation Requirements:

For the purposes of considering requests for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements for this entry.

The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website: http://www.services.unimelb.edu.au/disability/

Coordinator

Dr Matthew Greenwood-Nimmo

Contact

matthew.greenwood@unimelb.edu.au

Subject Overview:

Normally topics will include current techniques used in forecasting in finance, accounting and economics such as regression models, Box-Jenkins, ARIMA models, vector autoregression, causality analysis, cointegration and forecast evaluation, and ARCH models. The computer software used is Eviews.
Learning Outcomes:

On successful completion of this subject students should be able to:

  • Apply the Box-Jenkins methodology for identifying stationary and non-stationary univariate forecasting models,
  • Apply VAR/VECM models to analyse relationships between economic and financial time series,
  • Apply ARCH models to analyse and forecast the volatility of financial time series.
Assessment:

A 2-hour end-of-semester examination (60%) and four assignments of no more than 1000 words each due in weeks 3, 6, 9 and 12 (40% - 10% each).
Prescribed Texts:

You will be advised of prescribed texts by your lecturer.
Breadth Options:

This subject potentially can be taken as a breadth subject component for the following courses:

You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

On successful completion of this subject, students should have improved the following generic skills:

  • Evaluation of ideas, views and evidence
  • Synthesis of ideas, views and evidence
  • Strategic thinking
  • Critical thinking
  • Accessing economic and other information
  • Summary and interpretation of information
  • Application of Windows software
  • Statistical reasoning
  • Problem solving skills
  • Written communication
Related Course(s): Master of Accounting
Related Majors/Minors/Specialisations: Economics

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