ÃÛèÖÊÓÆµ

Department of Mathematics

Mathematics with Finance

(MMath) Mathematics with Finance

Entry for 2023

FHEQ level

This course is set at Level 7 (Masters) in the national Framework for Higher Education Qualifications.

Course Aims

The Mathematics with Finance (MMath) degree programme aims to provide:
1. teaching in the mathematical and financial sciences that is advanced and broad-based and, where appropriate, informed by a research base of international standard;
2. a programme structure which allows transfer between certain programmes at appropriate stages, and a guided choice of courses to meet students' developing interests;
3. a coherent set of courses grouped for intellectual and vocational reasons, based on a mathematics, statistics and finance core building progressively on advanced skills and knowledge acquired during the programme;
4. a sound preparation for further training and research and for a career requiring advanced mathematical, statistical or financial science knowledge and understanding;
5. an admissions policy which gives access to students with special needs and to mature and other prospective students who may have unconventional academic backgrounds;
6. provision for students to develop personal, transferable and intellectual skills, enabling them to compete successfully on the employment market.

Course learning outcomes

Knowledge and Understanding: By the end of the programme a successful student is expected to be able to: demonstrate in depth knowledge and understanding of a core of analysis, algebra, applied mathematics, probability and statistics, much of which is at (or is informed by) the forefront of the discipline; demonstrate knowledge and understanding of advanced topics, depending on his or her own choice to enable the student to progress either in professional work or to PhD research.

Knowledge and Understanding: By the end of the programme a successful student is expected to master the core principles of finance, including common knowledge in financial institutions, products and markets, as well as understanding of advanced topics in finance.

Intellectual Skills: By the end of the programme a successful student is expected to be able to demonstrate ability to understand and use mathematical argument and deductive reasoning; demonstrate awareness of the importance of mathematical and statistical assumptions and awareness of their use.

Intellectual Skills: By the end of the programme a successful student is expected to be able to analyse a finance or industrial problem using an appropriate theoretical framework with strong mathematics content and present ideas, concepts and information using means appropriate to the audience and the problem at issue.

Intellectual Skill: By the end of the programme a successful student is expected to be able to understand and critically evaluate current research and, where appropriate, to suggest new ideas.

Practical Skills: By the end of the programme a successful student is expected to be able to: explore and solve advanced mathematical problems, by selecting appropriate techniques; demonstrate knowledge and understanding of the process of mathematical or statistical modelling; exhibit advanced skills of numeracy, involving use of quantitative concepts and arguments, where appropriate, at all stages of work.

Practical Skills: By the end of the programme a successful student is expected to be able to demonstrate an understanding of appropriate concepts in finance that may be of wider use in a decision-making context (e.g. discounting and interest rate markets) and demonstrate competence in the use of mathematical methods and techniques in problem solving and modelling, in particular in finance.

Transferable Skills: By the end of the programme a successful student is expected to be able to: take decisions in complex and unpredictable contexts; apply a range of mathematical, computational, numerical, statistical and financial skills; communicate scientific/financial information orally and in writing; work and learn independently, including taking responsibility for their own learning, time-management and organisation.

Full-time course composition

YearTermStatusModuleCreditsFHEQ level
1Autumn SemesterCoreAnalysis 1 (G5135)154
  CoreFundamentals of Mathematics (G5133)154
  CoreLinear Algebra 1 (G5134)154
  CorePrinciples of Finance (N1560)154
 Spring SemesterCoreAnalysis 2 (G5139)154
  CoreComputational Mathematics (G5137)154
  CoreFinancial Institutions and Markets (N1634)154
  CoreLinear Algebra 2 (G5138)154
YearTermStatusModuleCreditsFHEQ level
2Autumn SemesterCoreCalculus of Several Variables (G5141)155
  CoreIntroduction to Probability (G5143)155
  CoreOrdinary Differential Equations (G5142)155
  CoreTheory of Investments (N1553)155
 Spring SemesterCoreCorporate and International Finance (N1563)155
  CoreNumerical Analysis (G5147)155
  CoreProbability and Statistics (G5146)155
  CoreReal Analysis (G5145)155
YearTermStatusModuleCreditsFHEQ level
3Autumn SemesterOptionApplied Numerical Analysis (L.6) (G1110)156
  Computing for Data Analytics and Finance (L6) (G5219)156
  Data Science Research Methods (L6) (G5222)156
  Financial Risk Management (N1569)156
  Functional Analysis (L.6) (G1029)156
  Introduction to Mathematical Biology (L6) (G5106)156
  Linear Statistical Models (L6) (G1107)156
  Partial Differential Equations (G1114)156
  Probability Models (L6) (G1100)156
  Valuation of Companies and Cash Flow Generating Assets (N1591)156
 Spring SemesterOptionComplex Analysis (L6) (G5261)156
  Cryptography (L.6) (G1032)156
  Dynamical Systems (L6) (G5126)156
  Financial Derivatives (N1559)156
  International Financial Management (N1548)156
  Machine Learning and Statistics for Health (L6) (G5221)156
  Monte Carlo Simulations (L6) (G5220)156
  Numerical Solution of Partial Differential Equations (L.6) (G5217)156
  Statistical Inference (L.6) (G5216)156
YearTermStatusModuleCreditsFHEQ level
4Autumn SemesterCoreFinancial Mathematics (L.7) (G5078)157
  OptionApplied Numerical Analysis (L.7) (852G1)157
  Functional Analysis (L.7) (851G1)157
  Linear Statistical Models (L7) (971G1)157
  Probability Models (L7) (973G1)157
 Autumn & Spring TeachingCoreMMath Project (846G1)457
 Spring SemesterCoreFinancial Portfolio Analysis (849G1)157
  OptionFinancial Invest & Corp Risk Analysis (861G1)157
  Machine Learning and Statistics for Health (L7) (974G1)157
  Monte Carlo Simulations (L7) (865G1)157
  Numerical Solution of Partial Differential Equations (L.7) (845G1)157
  Statistical Inference (L.7) (867G1)157

Please note that the University will use all reasonable endeavours to deliver courses and modules in accordance with the descriptions set out here. However, the University keeps its courses and modules under review with the aim of enhancing quality. Some changes may therefore be made to the form or content of courses or modules shown as part of the normal process of curriculum management.

The University reserves the right to make changes to the contents or methods of delivery of, or to discontinue, merge or combine modules, if such action is reasonably considered necessary by the University. If there are not sufficient student numbers to make a module viable, the University reserves the right to cancel such a module. If the University withdraws or discontinues a module, it will use its reasonable endeavours to provide a suitable alternative module.