ST422 Half Unit
This information is for the 2018/19 session.
Dr Wai-Fung Lam
This course is compulsory on the MSc in Statistics (Financial Statistics) 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.
Good undergraduate knowledge of statistics and probability.
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.
20 hours of lectures and 10 hours of seminars in the MT.
Exercises will be given out to do at home during Week 6.
Weekly exercises will be given.
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.
Exam (100%, duration: 2 hours) in the summer exam period.
Student performance results
(2014/15 - 2016/17 combined)
|Classification||% of students|
Total students 2017/18: 71
Average class size 2017/18: 18
Controlled access 2017/18: No
Lecture capture used 2017/18: Yes (MT)
Value: Half Unit
Personal development skills
- Application of information skills
- Application of numeracy skills
Course survey results
(2014/15 - 2016/17 combined)1 = "best" score, 5 = "worst" score
The scores below are average responses.
Response rate: 100%
Reading list (Q2.1)
Course satisfied (Q2.4)