Programme Specification
MSc Industrial Mathematical Modelling/ MSc Mathematical Finance
Academic Year: 2020/21
This specification provides a concise summary of the main features of the programme and the learning outcomes that a typical student might reasonably be expected to achieve and demonstrate if full advantage is taken of the learning opportunities that are provided.
This specification applies to delivery of the programme in the Academic Year indicated above. Prospective students reviewing this information for a later year of study should be aware that these details are subject to change as outlined in our Terms and Conditions of Study.
This specification should be read in conjunction with:
- Reg. XXI (Postgraduate Awards) (see University Regulations)
- Module Specifications
- Summary
- Aims
- Learning outcomes
- Structure
- Progression & weighting
Programme summary
| Awarding body/institution | º¬Ðß²ÝÊÓƵ |
| Teaching institution (if different) | |
| Owning school/department | Department of Mathematical Sciences |
| Details of accreditation by a professional/statutory body | |
| Final award | MSc/PGDip/PGCert |
| Programme title | Industrial Mathematical Modelling/ Mathematical Finance |
| Programme code | See Programme Structure |
| Length of programme | |
| UCAS code | n/a |
| Admissions criteria | MSc Industrial Mathematical Modelling - http://www.lboro.ac.uk/MAPT30 MSc Mathematical Finance - http://www.lboro.ac.uk/MAPT31 |
| Date at which the programme specification was published | Wed, 05 Aug 2020 09:56:45 BST |
1. Programme Aims
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IMM |
MF |
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To deliver a postgraduate curriculum which provides a solid foundation in the core areas of mathematics relevant to industry and stimulates students to meet their own aspirations, interests and educational needs. |
x |
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To equip students with certain general skills and thus help them prepare for future employment. |
x |
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To provide a mathematically based intellectual education appropriate to the needs of industry. |
x |
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To provide students with an environment which enables them to fulfil their potential in industrial mathematical modelling by providing access to appropriate opportunities, support and educational experiences. |
x |
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To develop students’ understanding in a particular area of interest by undertaking a research based project. |
x |
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To introduce students to the theoretical background of measure and integration theory, martingales and stochastic processes, and their applications in finance, derivatives industry, option pricing and hedging. |
x |
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To prepare graduates with strong mathematical skills, necessary computational techniques and the finance background necessary for employment in areas of the financial sector such as banks, hedge funds and insurance companies or for research careers in relevant subject areas. |
x |
2. Relevant subject benchmark statements and other external reference points used to inform programme outcomes:
- The Benchmark Statement for Mathematics, Statistics and Operational Research (MSOR)
- Framework for Higher Education Qualifications
- º¬Ðß²ÝÊÓƵ Learning and Teaching Strategy
- School Assessment Policy and Assessment Strategy
- Annual and Periodic Programme Review
- External Examiner’s Reports
- School Industrial Steering Committee
- Staff/Student Committees
- School staff specialisms
3. Programme Learning Outcomes
3.1 Knowledge and Understanding
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Students will gain knowledge and understanding in the following areas: |
IMM |
MF |
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K1 |
The relevance of mathematics in the analysis of problems of concern to industry |
x |
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K2 |
The core discipline of mathematical modelling |
x |
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K3 |
A range of analytical, numerical and qualitative techniques |
x |
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K4 |
The application of computer software to the solution of mathematical problems |
x |
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K5 |
The mathematical techniques that can be employed to model the kinds of stochastic processes that arise in financial markets |
x |
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K6 |
A range of analytical, numerical and qualitative techniques that are relevant to problems which arise in the financial sector |
x |
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3.2 Skills and other attributes
a. Subject-specific cognitive skills:
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Students should gain the ability to: |
IMM |
MF |
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C1 |
Construct logical mathematical arguments in the context of industrial mathematical modelling |
x |
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C2 |
Relate mathematics to problems within an industrial context in order to obtain quantitative and qualitative information about the underlying physical processes |
x |
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C3 |
Express certain problems which arise in the financial sector in mathematical terms |
|
x |
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C4 |
Identify appropriate mathematical techniques that can be applied to such problems |
|
x |
b. Subject-specific practical skills:
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Students should gain the ability to: |
IMM |
MF |
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|
P1 |
Select and apply appropriate mathematical tools for a specific problem |
x |
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P2 |
Use a range of mathematical techniques to obtain quantitative and qualitative information about financial processes |
|
x |
c. Key transferable skills:
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Students should gain the ability to: |
IMM |
MF |
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|
T1 |
Possess general study skills, including the ability to learn independently using a variety of media |
x |
x |
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T2 |
Have good time management and organisational skills |
x |
x |
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T3 |
Be logical and analytical, and possess skills in IT, communication, presentation and problem solving |
x |
x |
4. Programme structure
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Programme title and code |
|||
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Programme Code |
Title |
Award |
Abbreviation |
|
MAPT30 |
Industrial Mathematical Modelling |
MSc |
IMM |
|
MAPT31 |
Mathematical Finance |
MSc |
MF |
Programme structure
Key
x = Compulsory Module
o = Optional Module
|
Code |
Title |
Cred |
Sem |
IMM |
MF |
|
MAD102 |
Regular and Chaotic Dynamics |
15 |
1 |
x |
o |
|
MAD103 |
Lie Groups and Lie Algebras |
15 |
1 |
o |
|
|
MAP102 |
Programming and Numerical Methods |
15 |
1 |
x |
o |
|
MAP103 |
Statistics for Large Data |
15 |
1 |
o |
o |
|
MAP104 |
Brownian Motion |
15 |
1 |
|
x |
|
MAP111 |
Mathematical Modelling I |
15 |
1 |
x |
|
|
MAP114 |
Stochastic Models in Finance |
15 |
1 |
|
x |
|
MAD203 |
Functional Analysis |
15 |
2 |
|
o |
|
MAP201 |
Elements of PDEs |
15 |
2 |
x |
o |
|
MAP203 |
Computational Methods in Finance |
15 |
2 |
o |
x |
|
MAP202 |
Static and Dynamic Optimisation |
15 |
2 |
x |
o |
|
MAP204 |
Stochastic Calculus and Theory of Pricing |
15 |
2 |
|
x |
|
MAP211 |
Mathematical Modelling II |
15 |
2 |
x |
|
|
MAP213 |
Fluid Mechanics |
15 |
2 |
x |
|
|
MAP300 |
Industrial Modelling Research Project |
60 |
3 |
x |
|
|
MAP301 |
Mathematical Finance Research project |
60 |
3 |
x |
|
|
PHP100 |
Mathematical Methods for Interdisciplinary Sciences |
15 |
1 |
o |
|
|
ECP201 |
The Financial System |
15 |
1 |
o |
|
|
ECP202 |
Financial Economics |
15 |
1 |
|
o |
|
ECP255 |
Corporate Finance |
15 |
2 |
|
o |
5. Criteria for Progression and Degree Award
In order to be eligible for the award, candidates must satisfy the requirements of Regulation XXI.
Students who fail the assessment at their first attempt are allowed the opportunity for reassessment. This may take place at the Special Assessment Period (if available) or when the module is offered in the following year.
