Postgraduate Course: Financial Risk Theory (MATH11132)
|School||School of Mathematics
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Not available to visiting students
|Summary||This course presents approaches to model various financial risks. The
purpose is to learn the basic underlying mathematical concepts, to understand the economic rationale behind them through simple examples and to get an idea about how these methods can be implemented in practice.
- Mean and variance. A quick look at Markowitz portfolio theory.
- Utility functions, certainty equivalent.
- Value-at-risk, calculation methods (historical, Monte Carlo). Drawbacks.
- Convex and coherent risk measures, examples.
- Measures of dependence: from covariance to copulas.
- Some statistical techniques (dimension reduction, factor analysis).
Entry Requirements (not applicable to Visiting Students)
|| Students MUST have passed:
Probability, Measure & Finance (MATH10024) OR
Stochastic Analysis in Finance (MATH11154)
||Other requirements|| The central point of this course (FRT) is built around risk measures. It is thus required that anyone taking this course needs to have a solid understanding of the concept of Equivalent Martingale Measures (and of the associated theory - Girsanov theorem; Radon-Nikodym derivative; Lebesgue integration).
At UG level, the above topics are taught in MATH10024 Probability, Measure and Finance. At PGT level, they are taught in MATH11154 Stochastic Analysis in Finance.
Course Delivery Information
|Academic year 2023/24, Not available to visiting students (SS1)
|Learning and Teaching activities (Further Info)
Lecture Hours 18,
Seminar/Tutorial Hours 4,
Summative Assessment Hours 3,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||Hours & Minutes
|Main Exam Diet S2 (April/May)||Financial Risk Theory (MATH11132)||2:00|
On completion of this course, the student will be able to:
- Demonstrate knowledge of, and a critical understanding of, Markowitz portfolio theory.
- Demonstrate knowledge of, and a critical understanding of, the utility functions theory.
- Demonstrate knowledge of, and a critical understanding of, the Value-at-risk approach.
- Demonstrate understanding of, and critical assessment of, different convex and coherent risk measures.
- Demonstrate understanding of, and critical assessment of, different measures of dependence.
|- Follmer-Schied: Stochastic finance, Walter de Gruyter, 2004.|
- Embrechts-Frey-McNeil: Quantitative risk management, Princeton University
|Graduate Attributes and Skills
||MSc Financial Modelling and Optimization, MSc Computational Mathematical Finance and MMaths students only.
|Course organiser||Prof Sotirios Sabanis
Tel: (0131 6)50 5084
|Course secretary||Miss Gemma Aitchison
Tel: (0131 6)50 9268