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.