FM321      Half Unit
Risk Management and Modelling

This information is for the 2023/24 session.

Teacher responsible

Dr Linyan Zhu

Availability

This course is compulsory on the BSc in Finance and BSc in Financial Mathematics and Statistics. This course is available on the BSc in Accounting and Finance, BSc in Econometrics and Mathematical Economics, BSc in Economics, BSc in Mathematics and Economics, BSc in Mathematics, Statistics and Business and Diploma in Accounting and Finance. This course is available with permission as an outside option to students on other programmes where regulations permit and to General Course students.

This course is not capped, any eligible student that requests a place will be given one.

Pre-requisites

Students must have completed Principles of Finance (FM212 or FM213) and Statistical Methods (Elementary Statistical Theory (ST102) or Econometrics II (EC2C1) or (Econometrics I (EC2C3) or Statistical Models and Data Analysis (ST201))). Mathematical Methods (MA100) is desirable but not required. Students who have not taken Principles of Finance (FM212 or FM213), but have an excellent quantitative background, may be allowed to take this course at the discretion of the course leader.

Course content

This course is intended for third-year undergraduates and builds upon FM212/FM213 Principles of Finance. The main topics covered are financial risk analysis and financial risk. The course provides students with a thorough understanding of market risk from both a practical and technical point of view. A representative list of topics covered includes:

  • empirical properties of market prices (fat tails, volatility clusters) and forecasting of conditional volatility
  • concepts of financial risk (volatility, Value-at-Risk)
  • univariate and multivariate volatility models (ARCH, GARCH)
  • implementation and evaluation of risk forecasts
  • endogenous risk

Students apply the models to real financial data using Matlab/Python/R, a programming environment widely used in industry and academia. No prior knowledge of programming is assumed: students will learn-by-doing in class. Students will at times use data and software for classwork assignments.

Teaching

20 hours of lectures and 10 hours of classes in the AT.

Formative coursework

Students will be expected to produce written work for classes and to make positive contributions to class discussion

Indicative reading

J Danielsson, Financial Risk Forecasting: The Theory and Practice of Forecasting Market Risk will be the required textbook for the course.  Additional readings may be assigned as needed.

Assessment

Coursework (100%) in the AT.

Key facts

Department: Finance

Total students 2022/23: 168

Average class size 2022/23: 34

Capped 2022/23: No

Lecture capture used 2022/23: Yes (MT)

Value: Half Unit

Guidelines for interpreting course guide information

Course 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

  • Problem solving
  • Application of information skills
  • Application of numeracy skills
  • Commercial awareness