ST304 Half Unit
Time Series and Forecasting
This information is for the 2025/26 session.
Course Convenor
Oliver Feng
Availability
This course is available on the BSc in Actuarial Science, BSc in Actuarial Science (with a Placement Year), BSc in Data Science, BSc in Mathematics with Data Science, BSc in Mathematics with Economics, BSc in Mathematics, Statistics and Business, Erasmus Reciprocal Programme of Study and Exchange Programme for Students from University of California, Berkeley. This course is freely available as an outside option to students on other programmes where regulations permit. It does not require permission. This course is freely available to General Course students. It does not require permission.
This course is not capped, any student that requests a place and meet the criteria will be given one.
Requisites
Additional requisites:
2nd year statistics and probability
Students who have no previous experience in R are required to complete an online pre-sessional R course from the Digital Skills Lab before the start of the course.
Course content
The course introduces the student to the statistical analysis of time series data and simple time series models, and showcase what time series analysis can be useful for. Topics include: autocorrelation; stationarity, trend removal and seasonal adjustment; AR, MA, ARMA, ARIMA; estimation; forecasting; model diagnostics; unit root test; introduction to financial time series and the ARCH/GARCH models; and if time permits, basic spectral analysis. The use of R for time series analysis will also be covered.
Teaching
10 hours of seminars and 20 hours of lectures in the Winter Term.
This course has a reading week in Week 6 of Winter Term.
Formative assessment
Written answers to set problems will be expected on a weekly basis.
Indicative reading
Peter J. Brockwell and Richard A. Davis, Introduction to Time Series and Forecasting
Robert H. Shumway and David S. Stoffer, Time Series Analysis and Its Applications: With R Examples
Christopher Chatfield, The Analysis of Time Series
Ruey S. Tsay, An Introduction to Analysis of Financial Data with R
Peter J. Brockwell and Richard A. Davis, Time Series: Theory and Methods
Christian Francq and Jean-Michel Zakoïan, GARCH Models: Structure, Statistical Inference and Financial Applications
Assessment
Exam (90%), duration: 120 Minutes in the Spring exam period
Project (10%)
Key facts
Department: Statistics
Course Study Period: Winter Term
Unit value: Half unit
FHEQ Level: Level 6
CEFR Level: Null
Total students 2024/25: 54
Average class size 2024/25: 14
Capped 2024/25: NoCourse selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Personal development skills
- Problem solving
- Application of information skills
- Communication
- Application of numeracy skills
- Commercial awareness
- Specialist skills