Not available in 2017/18
ST326 Half Unit
Financial Statistics
This information is for the 2017/18 session.
Teacher responsible
Prof Pauline Barrieu COL.6.03
Availability
This course is compulsory on the BSc in Financial Mathematics and Statistics. This course is available with permission as an outside option to students on other programmes where regulations permit and to General Course students.
Pre-requisites
ST202 Probability, Distribution Theory and Inference.
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, statistics and machine learning in financial forecasting, Value at Risk, simple trading strategies, statistics of fixed income finance, derivative instruments from the statistical viewpoint.
Teaching
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.
Assessment
Exam (100%, duration: 2 hours) in the main exam period.
Key facts
Department: Statistics
Total students 2016/17: Unavailable
Average class size 2016/17: Unavailable
Capped 2016/17: No
Value: Half Unit
PDAM skills
- Self-management
- Problem solving
- Communication
- Application of numeracy skills
- Specialist skills