Studying at York
Financial and Time Series Econometrics - ECO00055H
- Department: Economics and Related Studies
- Credit value: 20 credits
- Credit level: H
- Academic year of delivery: 2023-24
- See module specification for other years: 2024-25
Module summary
The aim of the module is to introduce advanced econometric techniques that are used both in the applied literature and in the professional analysis of economic or financial data and to provide critical empirical discussion of some important financial models
Related modules
Pre-requisite modules
Co-requisite modules
- None
Prohibited combinations
Additional information
Prerequisite modules: Econometric Theory, [For Department of Mathematics Student: Statistics I (MAT00010I) and Linear Algebra (MAT00008I)]
Prohibited Combination: Applied Econometrics
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Semester 1 2023-24 |
Module aims
-
To introduce advanced econometric techniques that are used both in the applied literature and in the professional analysis of economic or financial data.
-
To provide critical empirical discussion of some important financial models
Module learning outcomes
Have a working knowledge of the main models for analysing a stationary or nonstationary time series
-
Read empirical macro and financial literature
-
Apply econometric methods for time series using standard software (EViews)
-
Use the information in the term structure of interest rates to forecast future rates
-
Evaluate market efficiency and the scope for higher than market profits, and estimate the Value at Risk of a portfolio
-
Model and analyse asset returns using one-factor and multi-factor models
-
Apply principal component analysis to model portfolio returns and analyse portfolio risk
Module content
Techniques will include: ARMA models for scalar time series, unit root testing and cointegration, ARCH models.
Topics will include: the theoretical and empirical investigation of market returns; the use of (G)ARCH models for the evaluation of the Value at Risk of a portfolio; the evaluation of the information content in the term structure of interest rates for the purpose of forecasting future short term rates; one-factor and multi-factor models of asset returns; principal component analysis with applications to portfolio returns modeling and risk assessment.
Indicative assessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 90 |
| Essay/coursework | 5 |
| Essay/coursework | 5 |
Special assessment rules
None
Indicative reassessment
| Task | % of module mark |
|---|---|
| Closed/in-person Exam (Centrally scheduled) | 90 |
Module feedback
Marking and feedback within twenty-five working days of the coursework assignment.
Marking and cohort feedback within twenty-five working days of the 2-hour unseen examination.
Indicative reading
The course material will be based (selectively) on the following texts:
Hamilton, J. (1994). Time Series Analysis. Princeton University Press.
Carol Alexander (2008) Vol I, Quantitative Methods in Finance. Wiley, UK.
Carol Alexander (2008) Vol II, Practical Financial Econometrics. Wiley, UK.
Additional learning material will be made available as the course progresses. (This too will be part of the syllabus.)
Other recommended texts include:
Brockwell, P.J. & Davis, R. (2002). Introduction to Time Series and Forecasting. Springer.
Brooks, C. (2008). Introductory Econometrics for Finance. 2nd ed. CUP.
Cuthbertson, K. & Nitzsche, D. (2005). Quantitative Financial Economics. Wiley.