ST304 Half Unit
Time Series and Forecasting
This information is for the 2022/23 session.
Dr Yining Chen COL 7.06
This course is available on the BSc in Actuarial Science, BSc in Business Mathematics and Statistics, BSc in Data Science, BSc in Mathematics with Economics and BSc in Mathematics, Statistics and Business. This course is available as an outside option to students on other programmes where regulations permit and to General Course students.
This course is not capped, any student that requests a place and meet the criteria will be given one.
2nd year statistics and probability
Students who have no previous experience in R are required to complete an online pre-sessional R course from the Digital Skills Lab before the start of the course (https://moodle.lse.ac.uk/course/view.php?id=7745)
The course introduces the student to the statistical analysis of time series data and simple time series models, and showcase what time series analysis can be useful for. Topics include: autocorrelation; stationarity, trend removal and seasonal adjustment; AR, MA, ARMA, ARIMA; estimation; forecasting; unit root test; introduction to financial time series and the ARCH/GARCH models; basic spectral analysis. The use of R for time series analysis will also be covered.
This course will be delivered through a combination of classes, lectures and Q&A sessions totalling a minimum of 30 hours across Lent Term. This course includes a reading week in Week 6 of Lent Term.
Written answers to set problems will be expected on a weekly basis.
Peter J. Brockwell and Richard A. Davis, Introduction to Time Series and Forecasting
Robert H. Shumway and David S. Stoffer, Time Series Analysis and Its Applications: With R Examples
Christopher Chatfield, The Analysis of Time Series
Ruey S. Tsay, An Introduction to Analysis of Financial Data with R
Peter J. Brockwell and Richard A. Davis, Time Series: Theory and Methods
Christian Francq and Jean-Michel ZakoÃ¯an, GARCH Models: Structure, Statistical Inference and Financial Applications
Exam (90%, duration: 2 hours) in the summer exam period.
Student performance results
(2019/20 - 2021/22 combined)
|Classification||% of students|
Total students 2021/22: 43
Average class size 2021/22: 11
Capped 2021/22: No
Value: Half Unit
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