25573 Time Series Econometrics
Warning: The information on this page is indicative. The subject outline for a
particular session, location and mode of offering is the authoritative source
of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.
Subject handbook information prior to 2016 is available in the Archives.
Credit points: 6 cp
Subject level:
Undergraduate
Result type: Grade and marksRequisite(s): 25503 Investment Analysis OR 25571 Introductory Econometrics OR 23571 Introductory Econometrics
These requisites may not apply to students in certain courses.
There are course requisites for this subject. See access conditions.
Description
This subject equips students with a general knowledge of model building, which stands them in good stead for basic empirical work in business environments. It provides the analytic tools required for further study in time series econometrics. The approach to modelling, and the reasoning about multi-variable empirical relationships, strengthens students' analytic skills.
Subject objectives
| 1. | apply techniques to model, estimate and forecast univariate time series |
|---|---|
| 2. | apply techniques to model, estimate and forecast multivariate time series |
| 3. | apply techniques to model, estimate and forecast time series of higher order moments. |
Contribution to the development of graduate attributes
The subject contributes to the aim of preparing students to commence a fulfilling and effective career in business, especially in finance professions. The subject makes its contribution by examining the special statistical characteristics that arise when modelling time series data, such as unemployment rates, inflation rates, commodity prices, interest rates and exchange rate data, that have been collected at a regular frequency (such as daily, weekly, monthly or quarterly intervals). The subject will make use of an advanced econometrics package for the purpose of analysing data.
Content
- Basic regression analysis with time series data
- Issues in using OLS with time series data
- Serial correlation in time series regressions
- Advanced time series topics
- ARIMA models and forecasting
- Vector autoregressive models and forecasting
- Models of second moments
- Empirical projects.
Assessment
Assessment task 1: Assignment (Individual)
| Objective(s): | This addresses subject learning objective(s): 1, 2 and 3 |
|---|---|
| Weight: | 20% |
Assessment task 2: Assignment (Group)
| Objective(s): | This addresses subject learning objective(s): 1, 2 and 3 |
|---|---|
| Weight: | 30% |
Assessment task 3: Final Exam (Individual)
| Objective(s): | This addresses subject learning objective(s): 1, 2 and 3 |
|---|---|
| Weight: | 50% |
Minimum requirements
Students must achieve at least 50% of the subject’s total marks.
Required texts
James H. Stock and Mark W. Watson, Introduction to Econometrics, Pearson, 3rd Edition, 2015
Chris Brooks, Introductory Econometrics for Finance, Cambridge, 3rd Edition, 2014
Recommended texts
Walter Enders, Applied Econometric Time Series, Wiley, 3rd Edition, 2009
R. Carter Hill, William E. Griffiths and George G. Judge, Undergraduate Econometrics, Wiley, 2nd Edition, 2001
Quantitative Micro Software, EViews 8 User's Guide, 2014
Jeffrey M. Wooldridge, Introductory Econometrics, 5th Edition, Thomson South-Western. 2013.
References
UTS Business School's Guide to Writing Assignments, 2014.
Other resources
Lecture materials will be posted to UTS-Online each week. Note that the subject slides are not a substitute for the recommended textbooks.
