ST326      Half Unit
Financial Statistics

This information is for the 2019/20 session.

Teacher responsible

Dr Wai-Fung Lam COL.6.09


This course is compulsory on the BSc in Financial Mathematics and Statistics. This course is available on the BSc in Actuarial Science and BSc in Mathematics, Statistics, and Business. This course is available with permission as an outside option to students on other programmes where regulations permit and to General Course students.


Either ST202, or ST206 and ST211.

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. 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, simple trading strategies, statistics of fixed income finance, derivative instruments from the statistical viewpoint.


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

Formative coursework

Students will be expected to produce 9 problem sets in the MT.

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.


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

Key facts

Department: Statistics

Total students 2018/19: Unavailable

Average class size 2018/19: Unavailable

Capped 2018/19: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Self-management
  • Problem solving
  • Communication
  • Application of numeracy skills
  • Specialist skills