- Department: Economics and Related Studies
- Module co-ordinator: Dr. Fabrizio Iacone
- Credit value: 10 credits
- Credit level: H
- Academic year of delivery: 2022-23
- See module specification for other years: 2021-22
Occurrence | Teaching period |
---|---|
A | Autumn Term 2022-23 |
To provide a careful introduction to the statistical techniques used in the analysis of data observed chronologically. This data arises in a wide range of situations of interest in economics, finance, science and elsewhere
On completing the module a student will be able to:
Have a working knowledge of the main models for analysing a stationary or nonstationary time series
Fit and interpret these models for themselves
Have the capability to read applied literature where these techniques are applied
Be equipped to undertake more advanced study in time series analysis
Task | Length | % of module mark |
---|---|---|
Closed/in-person Exam (Centrally scheduled) Introduction to Time Series |
2 hours | 100 |
None
Task | Length | % of module mark |
---|---|---|
Closed/in-person Exam (Centrally scheduled) Introduction to Time Series |
2 hours | 100 |
Information currently unavailable
The course material will be based (selectively) on the following preferred texts:
Brockwell, P. & Davis, R. (2002). Introduction to Time Series and Forecasting. 2nd ed. Springer Verlag.
Hamilton, J. (1994). Time Series analysis. Princeton University Press.