ST422 Half Unit
Time Series
This information is for the 2021/22 session.
Teacher responsible
Prof Wai-Fung Lam
Availability
This course is compulsory on the MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (ÐÓ°ÉÂÛ̳ and Fudan) and MSc in Statistics (Financial Statistics) (Research). This course is available on the MSc in Applicable Mathematics, MSc in Data Science, MSc in Econometrics and Mathematical Economics, MSc in Financial Mathematics, MSc in Marketing, MSc in Operations Research & Analytics, MSc in Quantitative Methods for Risk Management, MSc in Statistics and MSc in Statistics (Research). This course is available with permission as an outside option to students on other programmes where regulations permit.
This course has a limited number of places (it is controlled access). In previous years we have been able to provide places for all students that apply but that may not continue to be the case.
Pre-requisites
Good undergraduate knowledge of statistics and probability.
Course content
A broad introduction to statistical time series analysis for postgraduates: what time series analysis can be useful for; autocorrelation; stationarity; causality; basic time series models: AR, MA, ARMA; ARCH and GARCH models for financial time series; trend removal and seasonal adjustment; invertibility; spectral analysis; estimation; forecasting. We will also discuss nonstationarity and multivariate time series if time permits.
Teaching
This course will be delivered through a combination of classes, lectures and Q&A sessions totalling a minimum of 30 hours across Michaelmas Term. This year, some of this teaching may be delivered through a combination of classes and flipped-lectures delivered as short online videos. This course includes a reading week in Week 6 of Michaelmas. Exercises will be given out to do at home during Week 6.
Formative coursework
Weekly exercises will be given.
Indicative reading
Brockwell & Davis, Time Series: Theory and Methods; Brockwell & Davis, Introduction to Time Series and Forecasting; Box & Jenkins, Time Series Analysis, Forecasting and Control; Shumway & Stoffer, Time Series Analysis and Its Applications.
Assessment
Exam (80%, duration: 2 hours) in the summer exam period.
Coursework (20%) in the MT.
The course will be assessed by an examination (80%) and a coursework (20%) involving case studies which will be submitted in MT.
Course selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Student performance results
(2017/18 - 2019/20 combined)
| Classification | % of students |
|---|---|
| Distinction | 31.6 |
| Merit | 27.2 |
| Pass | 28.2 |
| Fail | 13.1 |
Important information in response to COVID-19
Please note that during 2021/22 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Key facts
Department: Statistics
Total students 2020/21: 81
Average class size 2020/21: 27
Controlled access 2020/21: Yes
Value: Half Unit
Personal development skills
- Application of information skills
- Application of numeracy skills
