ST422      Half Unit
Time Series

This information is for the 2016/17 session.

Teacher responsible

Dr Yining Chen


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 Econometrics and Mathematical Economics, MSc in Financial Mathematics, MSc in Management Science (Operational Research), MSc in Risk and Stochastics, 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.


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

Exercises will be given out to do at home during Week 6.

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 main exam period.

Student performance results

(2012/13 - 2014/15 combined)

Classification % of students
Distinction 42.6
Merit 21.5
Pass 20.1
Fail 15.8

Key facts

Department: Statistics

Total students 2015/16: 70

Average class size 2015/16: 1

Controlled access 2015/16: No

Lecture capture used 2015/16: Yes (MT)

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Application of information skills
  • Application of numeracy skills