MA416      Half Unit
The Foundations of Interest Rate and Credit Risk Theory

This information is for the 2024/25 session.

Teacher responsible

Dr Christoph Czichowsky

Availability

This course is compulsory on the MSc in Financial Mathematics. This course is available on the MSc in Quantitative Methods for Risk Management, MSc in Statistics (Financial Statistics) and MSc in Statistics (Financial Statistics) (Research). This course is available with permission as an outside option to students on other programmes where regulations permit.

Pre-requisites

Students must have completed Stochastic Processes (ST409).

Course content

This course studies the mathematical foundations of interest rate and credit risk theory. The course starts with a development of the multi-dimensional Black & Scholes theory with stochastic market data. This is then used to show how discount bond dynamics modelling can be approached by (a) the modelling of the short-rate process and the market price of risk, which underlies the family of short-rate models, or (b) the modelling of the market price of risk and the discount bond volatility structure, which gives rise to the Heath-Jarrow-Morton (HJM) framework. The course then expands on the theory of interest rate market models and credit risk.

Teaching

This course is delivered through a combination of seminars and lectures totalling a minimum of 30 hours across Winter Term.

Formative coursework

The main formative assessment will be in the form of weekly exercise sets, which will be discussed in the seminars. Some of the topics of these will be similar to what is expected in the summative assessment (exam).

Indicative reading

T R Bielecki and M Rutkowski, Credit Risk Modeling, Valuation and Hedging, Springer; M Musiela and M Rutkowski, Martingale Methods in Financial Engineering, Springer; R Rebonato, Modern Pricing of Interest-rate Derivatives: The LIBOR Market Model and Beyond, Princeton.

Assessment

Exam (100%, duration: 2 hours) in the spring exam period.

Key facts

Department: Mathematics

Total students 2023/24: 30

Average class size 2023/24: 30

Controlled access 2023/24: No

Value: Half Unit

Guidelines for interpreting course guide information

Course selection videos

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Personal development skills

  • Self-management
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills