ST422      Half Unit
Time Series

This information is for the 2019/20 session.

Teacher responsible

Dr Wai-Fung Lam


This course is compulsory on the MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (LSE 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.


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.


20 hours of lectures and 10 hours of seminars in the MT.

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.


Exam (100%, duration: 2 hours) in the summer exam period.

Student performance results

(2015/16 - 2017/18 combined)

Classification % of students
Distinction 24
Merit 28.1
Pass 35.7
Fail 12.2

Key facts

Department: Statistics

Total students 2018/19: 66

Average class size 2018/19: 21

Controlled access 2018/19: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Application of information skills
  • Application of numeracy skills