ST326 Half Unit
Financial Statistics
This information is for the 2025/26 session.
Course Convenor
Prof Clifford Lam
Availability
This course is compulsory on the BSc in Financial Mathematics and Statistics. This course is available on the BSc in Actuarial Science, BSc in Actuarial Science (with a Placement Year), BSc in Data Science, BSc in Mathematics with Data Science, BSc in Mathematics, Statistics and Business, Erasmus Reciprocal Programme of Study and Exchange Programme for Students from University of California, Berkeley. This course is available with permission as an outside option to students on other programmes where regulations permit. This course is available with permission to General Course students.
Requisites
Pre-requisites:
Before taking this course, students must have completed: ST202 or (ST206 and ST211)
Additional requisites:
Previous programming experience is not required but students who have no previous experience in R must complete an online R pre-sessional course from the Digital Skills Lab before the start of the course (https://moodle.lse.ac.uk/course/view.php?id=8714)
Course content
The course covers key statistical methods and data analytic techniques most relevant to finance. Hands-on experience in analysing financial data in the “R” environment is an essential part of the course. Basic time series analysis will be introduced at the start. The course includes a selection of the following topics: obtaining financial data, low- and high-frequency financial time series, ARCH-type models for low-frequency volatilities and their simple alternatives, Markowitz portfolio theory and the Capital Asset Pricing Model, concepts and practices in machine learning as applied in financial forecasting, Value at Risk. Will cover classification techniques using random forests and simple trading strategies if time permits.
Teaching
20 hours of lectures and 10 hours of classes in the Autumn Term.
This course has a reading week in Week 6 of Autumn Term.
Formative assessment
Students will be expected to produce 9 problem sets in the AT.
Indicative reading
Lecture notes will be provided
Lai, T.L. And Xing H. (2008) Statistical Models and Methods for Financial Markets. Springer.
Tsay, R. S. (2005) Analysis of Financial Time Series. Wiley.
Ruppert, D. (2004) Statistics and Finance – an introduction. Springer.
Fan, Yao (2003) Nonlinear Time Series.
Hastie, Tibshirani, Friedman (2009) The Elements of Statistical Learning.
Haerdle, Simar (2007) Applied Multivariate Statistical Analysis.
Assessment
Exam (80%), duration: 120 Minutes in the January exam period
Project (20%)
The course will be assessed by an examination (80%) and a coursework (20%) involving case studies which will be submitted in AT.
Key facts
Department: Statistics
Course Study Period: Autumn Term
Unit value: Half unit
FHEQ Level: Level 6
CEFR Level: Null
Total students 2024/25: 70
Average class size 2024/25: 35
Capped 2024/25: NoCourse selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Personal development skills
- Self-management
- Problem solving
- Communication
- Application of numeracy skills
- Specialist skills