- UCAS course code
- G1N3
- UCAS institution code
- M20
Bachelor of Science (BSc)
BSc Mathematics with Finance
Duration: 3 years
Year of entry: 2025
UCAS course code: G1N3 / Institution code: M20
- Key features:
Scholarships available
Accredited course
- Typical A-level offer: A*AA including specific subjects
- Typical contextual A-level offer: A*AB including specific subjects
- Refugee/care-experienced offer: A*BB including specific subjects
- Typical International Baccalaureate offer: 37 points overall with 7,6,6 at HL, including specific requirements
Course unit details:
Tools for Risk Management
| Unit code | MATH37542 |
|---|---|
| Credit rating | 10 |
| Unit level | Level 3 |
| Teaching period(s) | Semester 2 |
| Available as a free choice unit? | No |
Overview
A “risk” is any future gain/loss of uncertain size, and obviously we would like to be able to “manage” such risks. From a mathematical perspective that entails: model and analyse the risk, in order to understand the situation and make sensible decisions. The uncertainty involved means that random variables and more generally probability theory are very important fundamentals. Building on these, many tools and techniques for risk management have been developed over time, and in this course we will discuss some of the most prominent ones. Although the focus will mainly be on examples from/applications in finance, insurance and related, the possible applications are much more diverse. This course also contains some light use of the software package R.
Note: this course does not consider (investing in) financial markets, there are several other courses dedicated to that topic.
Pre/co-requisites
| Unit title | Unit code | Requirement type | Description |
|---|---|---|---|
| Probability and Statistics 2 | MATH27720 | Pre-Requisite | Compulsory |
Aims
The unit aims to: introduce students to a number of (mathematical) risk management tools prominent in finance, insurance and elsewhere.
Learning outcomes
On the successful completion of the course, students will be able to:
- Implement and use Monte Carlo simulations to analyse various characteristics of random quantities
- Discuss and evaluate dependence between random variables using copulas and related concepts
- Apply risk measures to random quantities and interpret the result
- Build and evaluate appropriate models for risks, including parameter dependence and risk sharing
Syllabus
1. Monte Carlo simulations [2 weeks]
2. Copulas [4 weeks]
3. Risk measures [2 weeks]
4. Loss Models [3 weeks]
Teaching and learning methods
Initially, each week a two hour lecture in which the materials are discussed followed by a one hour tutorial in which exercises are discussed. Later, when the course materials are fully developed and tested, we will move to a “flipped classroom” approach.
Assessment methods
| Method | Weight |
|---|---|
| Other | 20% |
| Written exam | 80% |
End of semester exam - 80% weighting
In-class test (computer cluster) - 20% weighting
Feedback methods
Individual feedback for in-class test after marking completed.
Group level feedback for exam after marking completed.
Recommended reading
Extensive typeset notes to be provided.
Study hours
| Scheduled activity hours | |
|---|---|
| eAssessment | 1 |
| Lectures | 22 |
| Tutorials | 11 |
| Independent study hours | |
|---|---|
| Independent study | 66 |
Teaching staff
| Staff member | Role |
|---|---|
| Kees Van Schaik | Unit coordinator |