Prof Luitgard Veraart

Dr Christoph Czichowsky

This course is available on the MPhil/PhD in Mathematics, MSc in Financial Mathematics and MSc in Quantitative Methods for Risk Management. This course is available with permission as an outside option to students on other programmes where regulations permit. This course uses controlled access as part of the course selection process. For information on controlled access courses, including eligibility, application processes, deadlines, and departmental contact details, please refer to the Controlled Access Courses webpage.

All MSc Financial Mathematics and MPhil/PhD Mathematics students will be guaranteed a place if they select the course by the course selection deadline in Autumn Term. All other students to which this course is available will be selected based on a first come first served basis. 

The only programmes to which this course is available as an outside option are MSc in Statistics, MSc in Statistics (Research), MSc in Financial Statistics, MSc in Financial Statistics (Research). 

Assumed prior knowledge:

Previous or current MSc level education in financial mathematics.

Recommended pre-requisites:

Programming experience in Python.

This course bridges the gap between theory and practice and shows how financial mathematics is used in the financial industry. It is taught by experts from the financial industry who share their experience and insights and discuss case studies and hands-on examples on a selection of application areas. The course will focus on 1-3 topics per year which can include financial risk management, algorithmic trading, portfolio optimisation, derivatives pricing and hedging, valuation adjustments (XVAs), market making, financial regulation, programming applications etc. 

10 hours of seminars in the Autumn Term.
20 hours of seminars in the Winter Term.

This course is delivered through seminars totalling normally between 10 and 30 hours across Autumn Term and Winter Term.  The seminars combine lectures and example classes and include case studies. 

Homework concerned with applications of financial mathematics and case studies is set.   

This course is not assessed.