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Online course materials for MATH38191

Statistical Modelling in Finance


Unit code: MATH38191
Credit Rating: 10
Unit level: Level 3
Teaching period(s): Semester 1
Offered by School of Mathematics
Available as a free choice unit?: N

Requisites

Prerequisite

Additional Requirements

Please note.

Students are not permitted to take more than one of MATH38191 or MATH48191 for credit in the same or different undergraduate year.

 

Students are not permitted to take MATH48191 and MATH68191 for credit in an undergraduate programme and then a postgraduate programme.

 

Note that MATH68191 is an example of an enhanced level 3 module as it includes all the material from MATH38191

 

When a student has taken level 3 modules which are enhanced to produce level 6 modules on an MSc programme taken within the School of Mathematics, then they are limited to a maximum of two such modules (with no alternative arrangements available otherwise)

Aims

Students should gain an insight into statistical models and methods to fit financial data and assess risk. As a result they should be able to analyse financial data using statistical methods.

Overview

This course unit is set up to support the finance pathway of the BSc in Mathematics and Statistics. No previous knowledge of finance is required.

Learning outcomes

On successful completion of the course, students will be able to analyse economic and financial data using statistical models. Emphasis will be placed on model fitting and interpretation.

Assessment methods

  • Other - 20%
  • Written exam - 80%

Assessment Further Information

End of semester examination: two hours weighting 80% plus 20% coursework.

Syllabus

  • Characteristics of financial data. Mean, variance, skewness, kurtosis, heavy tails. [2]
  • Distributions with Pareto tails. Maximum likelihood estimation and inference. [2]
  • Correlation and dependence. Regression methods. [2]
  • Asset returns. The random walk model. Market efficiency and tests. [3]
  • Portfolio Theory. Risk versus expected return. The minimum variance portfolio. Efficient portfolios. [5]
  • The Capital Asset Pricing Model. Estimation of Beta and testing of CAPM. Factor Models. [5]
  • Value at risk. [3]

Recommended reading

  • Lai TL and H Xing (2008). Statistical Models and Methods for Financial Markets. Springer. Available at http://rylibweb.man.ac.uk/cgi-bin/doip.pl?10.1007+978-0-387-77827-3.
  • Ruppert D (2004). Statistics and Finance: An Introduction. Springer.

Feedback methods

Feedback tutorials will provide an opportunity for students' work to be discussed and provide feedback on their understanding.  Coursework or in-class tests (where applicable) also provide an opportunity for students to receive feedback.  Students can also get feedback on their understanding directly from the lecturer, for example during the lecturer's office hour.
 

Study hours

  • Lectures - 22 hours
  • Tutorials - 11 hours
  • Independent study hours - 67 hours

Teaching staff

Jingsong Yuan - Unit coordinator

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