This is an archived handbook for a previous year. The current undergraduate and postgraduate handbooks can be viewed using the links above.
Postgraduate Handbook 2022-2023 (archived)
Module MATH40920: Mathematical Finance
Department: Mathematical Sciences
MATH40920: Mathematical Finance
| Type | Level | Credits | Availability | Module Cap | Location |
|---|---|---|---|---|---|
| Tied | 4 | 20 | Available in 2022/2023 | None. | Durham |
Tied To
Pre-requisites
- Probability
Corequisites
- None
Excluded Combinations
- None
Aims
- Mathematical Finance.
Content
- An introduction to options and markets.
- Asset price random walks.
- The Black-Scholes model.
- Partial Differential Equations.
- The Black-Scholes formulae.
- Variations on the Black-Scholes model.
- Reading material on a topic related to: American options (obstacle problems, free boundary problems), Exotic options, Historical volatility.
Learning Outcomes
Subject-specific Knowledge
- By the end of the module students will: have an understanding of basic option theory and Black-Scholes models.
- Will have an advanced understanding in one of the following areas: American options, Exotic options or Historical Volatility.
Subject-specific Skills
- Students will have skills in Partial Differential Equations and Finance.
Key Skills
- Students will have developed an appreciation of, and ability in, mathematical modelling in the financial world. Students will also have developed independent learning of an advanced topic.
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Teaching is by lectures through which the main body of knowledge is made available.
- Subject material assigned for independent study develops the ability to acquire knowledge and understanding without dependence on lectures.
- Students do regular formative work solving problems to gain insight into the details of relevant theories and procedures.
- Summative examination assesses acquired knowledge, problem-solving skills and a range of modellig and computational skills. The subject material assigned for independent study will form part of the examined material.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total Hours | Attendance Monitored |
|---|---|---|---|---|---|
| Lectures | 42 | 2 per week for 20 weeks and 2 in term 3 | 1 Hour | 42 | |
| Problems Classes | 8 | Four in each of terms 1 and 2 | 1 Hour | 8 | |
| Preperation and Reading | 150 | ||||
| Total | 200 |
Summative Assessment
| Component | Component Weighting | Element | Length/Duration | Element Weighting | Resit Opportunity |
|---|---|---|---|---|---|
| Examination | 100% | Written examination | 3 Hours | 100% |
Formative Assessment
Eight written or electronic assignments to be assessed and returned. Other assignments are set for self-study and complete solutions are made available to students.
Students who do not attend monitored activities shown under Teaching Methods
and Learning Hours, or who fail to complete the summative or formative
assessment(s) specified above, may be subject to the Academic Progress
procedures defined in the University's General Regulation V, and may be
required to leave the University.