FM457     
Applied Computational Finance

This information is for the 2016/17 session.

Teacher responsible

Mr Lorenz Bretscher

Availability

FM457A is intended for students taking FM442 Quantitative Methods for Finance and Risk Analysis and FM404 Forecasting Financial Time Series. There may be limited availability to other students not taking these courses, however, priority will be given to those who are registered for FM404 and FM442.

FM457B is available to students on the MSc Finance (Full-time), MSc Finance and Private Equity, MSc Finance and Economics and MSc Risk and Finance programmes.

Course content

This course is an introduction to computational methods in finance; the course mainly focuses on Matlab but then introduces other programming languages. We will begin with an introduction to basic Matlab. We will then learn how to simulate individual securities, with a special focus on the predictability and fat tails features of volatility. Simultaneously we will examine the data to test how well our models approximate the real world. Next we will move onto modeling portfolios of multiple securities and test the CAPM and the Fama-French three factor model; we will also test for long term predictability in asset prices. Finally we will use numerical techniques to price options and to construct a yield curve.

Teaching

FM457A: 10 hours of seminars in the MT.

FM457B: Students can take the course either in the MT or LT. 10 hours of seminars in the MT. 10 hours of seminars in the LT.

Indicative reading

Teaching notes will be distributed.

Assessment

This is an additional, non-assessed computer course to supplement MSc level courses in the Department of Finance.

Key facts

Department: Finance

Total students 2015/16: Unavailable

Average class size 2015/16: Unavailable

Controlled access 2015/16: No

Value: Non-assessed

Guidelines for interpreting course guide information

Personal development skills

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