Module manager: Georgios Aivaliotis
Email: G.Aivaliotis@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2026/27
None
This module is not approved as an Elective
Risk management is considered vital for individuals as well as companies that are exposed to financial risk. Badly managed risk easily can lead to bankruptcy as history can attest. This module aims to develop the mathematical methods and models to quantify, control and manage risk. Students will carry out some basic numerical simulations using the programming language R.
This module covers the different types of risk to which financial investments are exposed, Value-at-Risk and other risk measures, credit risks and credit derivatives and stress-testing of risky investment portfolios. Particular attention is paid to dependence between risks.
The module consists of Lectures, where the theory is introduced, seminars where students practice problem solving and computer practical sessions that deliver the computational tools for risk management.
Subject specific learning outcomes:
On completion of this module, students will be able to:
describe the main sources of financial risk and their mathematical modelling. In particular:
Appreciate the importance financial risk management through case studies.
Demonstrate an understanding of basic risk measures and the methods for computing those.
Explain in detail the concepts of Value-at-Risk and Expected Shortfall.
Demonstrate an understanding of credit risks and credit derivatives.
Describe the dependence between risk sources using copulas.
Carry out stress-testing of simple portfolios.
Skills learning outcomes:
On successful completion of the module students will be able to:
Apply problem-solving and analytical skills to risk quantification and management problems through risk models, simulations and stress-testing, including dependence modelling.
Make financial decisions based on solid understanding of capabilities and limitations of financial risk management models as well as data uncertainties.
Communicate risk results and decisions clearly and concisely in a structured written form supported by evidence.
Manage time effectively to balance analytical, computational, and written tasks, meeting academic deadlines.
Demonstrate initiative and active learning strategies through searching for information and data.
Maintain academic integrity and use appropriate referencing when engaging with financial mathematics literature.
-Introduction to financial risk and types of financial risks
-Risk measurement, coherence.
-Dependence and copulas.
-Credit Risk models, credit rating.
Additional topics that build on these may be covered as time allows. Such topics may be drawn from the following, or similar:
-Credit risk derivatives.
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Lecture | 22 | 1 | 22 |
| Practical | 3 | 1 | 3 |
| Seminar | 11 | 1 | 11 |
| Private study hours | 114 | ||
| Total Contact hours | 36 | ||
| Total hours (100hr per 10 credits) | 150 | ||
114
Feedback on problem sheets will be provided orally to students during lectures/seminars. Individual feedback will be provided during office hours as required.
Check the module area in Minerva for your reading list
Last updated: 30/04/2026
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