> q` YibjbjqPqP _::`$~~~P)hbb:w%<a ((((((($+hs-T(uwwuu((6ux(u(V!ej~Vd+)x)`-q-0-XZ@4O&((EX)uuuudVvZ$uVZ A. NATURE OF THE AWARD
Awarding Institution: Kingston University
Programme Accredited by:
Final Award(s): BSc (Hons)
Intermediate Awards: CertHE, DipHE, Ordinary Degree
Field Title: Financial Mathematics
FHEQ Level: Honours
Credit rating by level:
Major field: 75 credits @ level 4, 75 credits @ level 5 and 75 credits @ level 6
JACS code: G100
QAA Benchmark Statement(s): The Financial Mathematics Field described below complies with the MSOR Subject Benchmark Statement (QAA 2002).
Minimum Registration: 3 years or 4 years with placement
Maximum Registration: 9 years
Faculty: Computing Information Systems & Mathematics
School: N/A
Location: Penrhyn Road
Date Specification Produced May 2007
Date Specification Revised:
B. FEATURES OF THE FIELD
Title:
The field is available in the following forms:
- BSc (Hons) Financial Mathematics with x
where x is a second subject.
2. Modes of Delivery
The field may be studied in the following alternative patterns
- Full time
- Sandwich
- Part time
Financial Mathematics (FMA) is offered as a three year full time course (4 years with placement), although it is possible for students to switch between full time and part time mode attendance.
3. Features of the Field
The major field in Financial Mathematics is offered within the Joint Honours programme of the Undergraduate Modular Scheme (UMS). The field can be combined with minors in Computing, Economics, Web Development and Business.
C. EDUCATIONAL AIMS OF THE FIELD
In keeping with the ethos of the mathematics based fields within the joint honours portfolio, the field will cover the fundamental mathematical and statistical methods that students interested in solving problems in mathematical finance require, together with the development of the necessary computing and analytical skills. The field will constitute a coherent, academically sound programme of study which will assist students in their general personal development and produce graduates suited for employment in careers where financial, mathematical, statistical or computing skills are used, or to go onto postgraduate studies. Embedded within the provision is the opportunity for the development of a range of key skills.
There will be three main strands to the core of the field, these being:
use of probability, statistics and stochastic methods;
use of analytical and numerical methods;
the approach of mathematical modelling in finance.
The Financial Mathematics field aims to develop students abilities to:
a. apply confidently the appropriate techniques and models of mathematics, probability and statistics to obtain the fair price of a variety of financial instruments and apply them to related fields.
b. attain a body of knowledge and skills in the mathematical sciences and finance in order to understand the basic principles and methods of the subject and also to apply these skills to a range of problems;
c. identify relationships between the various subject areas in finance and the mathematical sciences they have studied;
d seek, use and communicate relevant information effectively in oral, visual and written forms;
e. work in groups and individually, and to work for and with non-mathematicians;
f. extend their knowledge in finance and the mathematical sciences by further formal study (for academic or professional qualifications) or by effective use of published work.
Specific aims for each module within the field are given in the module descriptions.
D. LEARNING OUTCOMES (OBJECTIVES) OF THE FIELD
The learning outcomes of the Financial Mathematics field are to produce graduates who are able to:
1. Knowledge and Understanding
demonstrate a suitable level of the mastery of techniques of financial mathematics and be able to apply them also to a variety of problems in business, industrial or professional areas.
2. Cognitive (thinking) Skills
formulate problem solutions;
identify appropriate mathematical methods and any relevant computer applications, to assist in the solution of problems;
demonstrate research skills;
3. Practical Skills
All students develop practical skills at level 4 in a core computing module. These skills are subsequently used in those MA and ST modules which have computing packages embedded as tools.
4. Key Skills
On completion of the field students will have acquired transferable skills to:
a. Communication Skills
receive and respond to a variety of information e.g. taking part in discussions; selecting, extracting and collating information from appropriate sources; presenting information in a variety of formats/media;
b. Numeracy
apply numerical skills and techniques to quantitative situations e.g. collecting data (where appropriate); evaluating quantitative data; performing basic calculations;
c. Information, Communication and Technology
make effective use of computer systems to aid data manipulation and presentation e.g. presenting different forms of information; searching for and storing information; on-line communication;
d. Teamwork
work effectively as a member of a team, appreciating the value of their own and others contributions;
e. Independent Learning
display self management and organisation leading to attainment of objectives within timelines and personal development e.g. developing research and information handling skills; developing self awareness; monitoring and reviewing own progress.
Table 1 below identifies the key skills associated with summative assessment components for core modules and options from the subject areas of Mathematics, Statistics and Computing. It should be recognised that, in addition, students will be developing these skills extensively away from these summative assessment exercises: in classes, in formative assessment exercises, in private study and in extra-curricula activities. Modules shown in bold text are core.
The learning and teaching strategies of the field seek to ensure that students learn actively and effectively, thus laying the foundation for future careers and/or further study.
CommunicationNumeracyICTTeamworkIndependent LearningLevel 4MA1010Mathematical Science IC, GC, G, T, EGG, EMA1020Mathematical Science IICC, T, ECEMA1030Introduction to Linear AlgebraC, T, ECEMA1261Mathematical Studies ICC, TCC, TMA1271Mathematical Studies IIC, IC, T, I, EC, T, I, EMA1031Mathematical Studies IIIC, T, ECEST1210Introduction to Probability and StatisticsC, T, ECECO1000Fundamental Programming Concepts I, LCI, L, TI, L, TLevel 5MA2010Mathematical Methods IC, EEMA2020Ordinary Differential EquationsC, EEST2210Regression ModellingGG(R) TG(R)G(R)EST2220Statistical DistributionsCC, EEST2353Operational Research TechniquesCC, ECEMA2401Actuarial Methods ,Planning and ControlCCCMA2402ContingenciesCC,EC,ELevel 6MA3010Partial Differential Equations & Approximation TheoryCC, ECC, EMA3402Mathematical FinanceCC, ECC, EST3361Stochastic FinanceC, I(R)C, ECCEFE3148Financial Risk ManagementC,RC,RI,L,TEMA3401Advanced ContingenciesCC,EEST3320Time Series and ForecastingG(R)I(R), C, EI(R)I(R), C,EMA3980ProjectC, D, O, RC, D, O, RC, D, O, RDC, D, O, R
Table 1 - Key Skills Summary
Key:
C - Coursework Assignment,
D - Project Development,
E Examination,
I - Individual Case Study or Self-Study/Research Exercise,
G - Group Case Study or Self-Study,
L - Library Workbook,
O - Oral Presentation/Interview,
R Report,
T - In-class Test.
E. FIELD STRUCTURE
The FMA field structure aligns with the specifications of the UMS. It is offered as a major field with an optional work placement year between levels 5 and 6.The modules at each level total to a credit value of 120 points.
The sandwich year is an optional element in the programme, taken between levels 5 and 6. Students who opt for the sandwich mode will spend a minimum period of 36 weeks in an approved placement in industry or commerce.
Level 1
At Level 4, students will be introduced to a wide variety of topics, laying the necessary foundation for further work in this field. The study of mathematical methods will include calculus, linear algebra, ordinary differential equations, an introduction to numerical methods and exposure to symbolic algebra and linear algebra packages. Core statistics and computing modules are included to underpin those subjects and to provide pre-requisites for later options.
In the first semester a significant proportion of the content of Mathematical Science I is designed to overlap selected A-level material to ensure consolidation of a firm uniform base on which to build further knowledge structures.
Applicants entering the Field without A-level mathematics will take Mathematical Studies I, II and III instead of Mathematical Science I and II and Introduction to Linear Algebra. This trio of modules (MA1261, MA1271 and MA1031) covers the same material as the trio MA1010, MA1020 and MA1030 but with a slightly different treatment and with a different ordering of material. Provision of these alternate routes with equivalent end-points is in accordance with the aim of widening participation.
The level 4 modules contributing to the field are:
Semester A
Module TitleCodeCore/OptionMathematical Science IMA1010CoreMathematical Studies IMA1261Alternative CoreIntroduction to Probability & StatisticsST1210CoreFundamental Programming ConceptsCO1000Core
Semester B
Module TitleCodeCore/OptionMathematical Science IIMA1020CoreIntroduction to Linear AlgebraMA1030CoreMathematical Studies IIMA1271Alternative CoreMathematical Studies IIIMA1031Alternative Core
Level 5
There are three core modules at Level 5. Mathematical Methods will build on the Level 4 work, introducing additional techniques and providing a foundation for numerical and analytical treatments of ordinary and partial differential equations later in the field. Then, in semester 2, the study of ordinary differential equations is extended to systems where a symbolic algebra package will be used to assist qualitative understanding with graphical representations. In Regression Modelling, studied in semester 1, students gain experience of an industry standard statistical package as well as the statistical techniques involved.
Students choose either ST2220 and one of the second semester options or two of the second semester options. The options are either OR Techniques which will complement the Business minor field , Actuarial Methods, Planning and Control which will give experience in assessing risk or Contingencies which is concerned with the pricing of insurance and financial products.
The level 5 modules contributing to the field are:
Semester A
Module TitleCodeCore/OptionMathematical Methods MA2010CoreRegression ModellingST2210CoreStatistical DistributionsST2220Option
Semester B
Module TitleCodeCore/OptionOrdinary Differential Equations: Analytical and Computational MethodsMA2020CoreActuarial Methods, Planning and Control MA2401Option ContingenciesMA2402Option Operational Research TechniquesST2353BOption
Level 6
The core taught module in the first semester of the field at Level 6 will extend the students study to partial differential equations and approximation theory. The core modules in the second semester develop from previous modules the stochastic and the PDE approaches to Financial Mathematics. As with all joint honours fields, there is a project module, usually occupying 2 of the 8 level 6 modules (MA3980), although Financial Mathematics with Business students may opt for an additional taught Business module and undertake a single semester project (MA3990).
The level 6 modules contributing to the field are:
Semester A
Module TitleCodeCore/OptionPartial Differential Equations and Approximation TheoryMA3010ACoreFinancial Risk ManagementFE3148Option Advanced ContingenciesMA3401OptionTime Series & Forecasting MethodsST3320Option
Semester B
Module TitleCodeCore/OptionMathematical FinanceMA3402CoreStochastic FinanceST3361Core
F. FIELD REFERENCE POINTS
The Field has been designed to take account of QAA Subject Benchmark Statements for MSOR (QAA 2002).
The awards made to students who complete the field or who are awarded intermediate qualifications comply fully with the National Qualifications Framework.
All of the procedures associated with the field comply with the QAA Codes of Practice for Higher Education.
Module content, especially at level 6, is informed by staff research expertise, and other scholastic activities and employment experience.
G. LEARNING AND TEACHING STRATEGIES
The learning and teaching strategies reflect the field aims and learning outcomes, student background, potential employer requirements and the need to develop a broad range of technical skills, with the ability to apply them appropriately. The strategies ensure that students have a sound understanding of some important areas in mathematics and statistics and have acquired the transferable skills expected of modern-day undergraduates.
150 hours of study time is allocated to each module. Typically, this includes 55 hours of contact time per module at level 4 and 44 hours at levels 5 and 6, leaving the remainders for self-directed or guided study time. There is more contact at level 4 to provide initial academic support and students are encouraged to develop as independent learners as they progress through their degree course. Contact time can consist of lectures, tutorials, problems classes, practicals or PAL sessions, dependent on individual module requirements. Generally, subject material and corresponding techniques will be introduced in lectures; for many modules, practical activities are regarded as essential to the understanding of the material and the development of relevant skills. In problems classes students typically work through formative exercises under guidance and in PAL sessions second year students help those at level 1 to develop their study skills.
Some Level 4 MA modules have associated study guides containing core material and formative exercises. The latter, and worksheets in computing practical sessions, help develop self-paced learning and independent study. Most modules have lecture notes available in hard-copy or on BLACKBOARD, which is the universitys learning management system.
Students will be expected to develop their skills, knowledge and understanding through independent and group learning, in the form of both guided and self-directed study. In most modules students will be given regular formative exercises or practical work through which they can develop learning skills, knowledge and techniques. Further they will have the opportunity to work individually and in groups on assignments, practicals, case studies and projects. These activities and their assessment are designed to enable students to meet the specific learning outcomes of the field.
A particularly important component of the degree is the project, which develops the students confidence and ability to carry out individual and/or group pieces of scholarship or research and then communicate their results in both written and oral forms. The project may be solely mathematics-based or, preferably of an interdisciplinary nature, on a topic which draws on the integration of both fields studied.
H. ASSESSMENT STRATEGIES
Assessment enables students abilities to be measured in relation to the aims of the field; assessment also serves as a means for students to monitor their own progress at prescribed stages and enhance the learning process.
The assessment strategy has been devised to reflect the aims of the field and to complement the learning and teaching strategies described above. Throughout the field students are exposed to a range of assessment methods, thus allowing them to develop technical and key skills and enabling the effectiveness of the learning and teaching strategies to be evaluated.
The methods of assessment have been selected so as to be most appropriate for the nature of the subject material, teaching style and learning outcomes in each module. Some modules are assessed entirely by in-course work, while others have, in addition an end-of-module examination. No module is assessed by an end-of-module examination alone. In particular, the balance between the various assessment methods for each module reflects the specified learning outcomes.
The assessments are designed so that students achievements of the field learning outcomes can be measured. A wide range of assessment techniques will be used to review as accurately and comprehensively as possible the students attainments in acquiring sound factual knowledge together with the appropriate technical competence and understanding, so that they can tackle various types of problems.
Components of Assessment
In the field as a whole, the following components may be used in the assessment of the various modules:
- Multiple choice or short answer in-class tests: to assess competence in basic techniques and understanding of concepts
- Long answered structured questions in coursework assignments: to assess ability to apply learned techniques to solve simple to medium problems and which may include a limited investigative component
- Long answer structured questions in end-of-module examinations: to assess overall breadth of knowledge and technical competence to provide concise and accurate solutions within restricted time
- Practical exercises: to assess students understanding and technical competence
- Individual case studies: to assess ability to understand requirements and to provide solutions to realistic problems. The outcomes can be:
- Written report, where the ability to communicate the relevant concepts, methods, results and conclusions effectively will be assessed.
- Oral presentation, where the ability to summarise accurately and communicate clearly the key points from the work in a brief presentation will be assessed.
- Poster presentation where information and results must be succinct and eye-catching.
- Group-based case studies: contain all of the assessment objectives of individual case studies and in addition to assess ability to interact and work effectively with others as a contributing member of a team
- Project: The individual project module is similar to an extended case study. The problems tackled may be of a more open-ended nature, allowing students to increase their knowledge of mathematics or of the second field by studying a topic in greater depth and/or by applying techniques learned in a new situation. As such the assessment here will place a greater emphasis on ability to plan work, manage time effectively, and research background information, although students will also be expected to produce written reports and to be interviewed about their work.
In addition to any specific criteria, the following features are expected in work that is submitted for coursework assignments:
- Technical competence: the generated system or solution performs the requirements stated in the best possible implementation.
- Completeness: all aspects of the work are attempted and full explanations of all reasoning are given.
- Clarity: all explanations are clear and concise. Arguments follow a logical sequence and are laid out in a clear format.
- Neatness: all reports are produced using a word-processor. Tables, graphs and diagrams are neat and suitably labelled. Assignments with a high mathematical content may be submitted in neat handwriting.
Assessment Procedures
It is the Faculty policy that in-course work is returned to students within three working weeks. Feedback can be model solutions and/or comments on the work. All examination papers, coursework and tests are internally moderated and those for levels 5 and 6 also externally. Projects are double-marked; examination scripts are checked to ensure that all work has been marked and scores correctly totalled.
The formal assessment procedure is specified in the general regulations of the UMS.
Assessment Summary
Table 2 indicates the methods of assessment to be used in all the field modules. Core modules are given in bold text. Further details are given in the module descriptions.
Module TitleCodeTestsWritten
AssignmentsPractical/
Case StudyExaminationLevel 4Mathematical Science IMA1010**Mathematical Science IIMA1020***Introduction to Linear AlgebraMA1030***Mathematical Studies IMA1261**Mathematical Studies IIMA1271****Mathematical Studies IIIMA1031***Introduction to Probability & StatisticsST1210***Fundamental Programming ConceptsCO1000**Level 5Mathematical Methods IMA2010**Ordinary Differential Equations: Analytical and Computational MethodsMA2020**Regression ModellingST2210**(Group)Statistical DistributionsST2220***Operational Research TechniquesST2353**Level 6Partial Differential Equations and Approximation TheoryMA3010**Mathematical FinanceMA3402***Stochastic FinanceST3361***Time Series & Forecasting MethodsST3320*(Group)*Financial Risk ManagementFE3148**Advanced ContingenciesMA3401**ProjectMA3980**
Table 2 - Assessment Summary (Indicative)
I. ENTRY QUALIFICATIONS
1. The minimum entry qualifications for the field are:
The general entry requirements for the field are those applicable to all programmes within the UMS.
2. Typical entry qualifications set for entrants to the field are:
For the FMA field a minimum of 260 points, including two 6-unit awards, with an A-Level in mathematics are normally required.
Qualified applicants who have studied mathematics beyond GCSE level but who are without a full A-level in mathematics, or equivalent, will be considered individually and appropriate steps will be taken to asses their potential to succeed in this field.
A foundation year is available for students without formal entry qualifications. Mature applicants and those with qualifications not specified above will be considered individually.
J. CAREER OPPORTUNITIES
In addition to providing a route to studying for higher degrees, the Financial Mathematics field graduate will be equipped for employment, for example, as:
Traders and dealers in, and analysts of, financial instruments such as options, forwards and futures
Commercial, industrial and public sector managers
Other business and finance associate professionals
Actuaries
Chartered accountants
Statisticians
Business analysts
Marketing, sales and advertising professionals
Teaching professionals.
K. INDICATORS OF QUALITY
Subject log, reviewed by Faculty Quality Assurance Committee (annual)
External examiners reports, reviewed by Faculty Quality Assurance Committee (annual)
QAA MSOR Subject Review (2000).
L. APPROVED VARIANTS FROM THE UMS/PCF
No variations from UMS required. In addition, approved Faculty progression regulations apply.
BSc (HONOURS) FINANCIAL MATHEMATICS - Major Field
LEVEL 4LEVEL 5OPTIONALLEVEL 6Mathematical Science I
MA1010A (D)
OR
Mathematical Studies I
MA1261 (D)Mathematical Science II
MA1020B (D) MA1010A
OR
Mathematical Studies II
MA1271 (D) ) MA1261Mathematical Methods
MA2010A (D)
MA1010, MA1020, MA1030/ MA1261, MA1271, MA1031Ordinary Differential Equations
MA2020 (C)
MA2010Industrial Placement YearPDEs & Approximation Theory
MA3010 (F)
MA2010, MA2020Stochastic Finance
ST3361 (E)
MA1020/,MA1261 & MA1271,
ST1210Introduction to Probability and Statistics
ST1210 (E)Introduction to Linear Algebra
MA1030B (A)
MA1010A
OR
Mathematical Studies III
MA1031 (A) MA1261Regression Modeling
ST2210 (B)
ST1210, MA1030/MA1031
Option 2B
Option 3AMathematical Finance
MA3402 (A)
ST1210, MA3010Fundamental Programming Concepts
CO1000 (B)
2nd Field ModuleStatistical Distributions
ST2220A(E)
ST1210, MA1010/MA1261&MA1271
or
2nd Field Module
2nd Field Module
or
Option 2B
2nd Field Module
2nd Field Module
2nd Field Module
2nd Field Module
2nd Field Module
2nd Field Module
Project
Project
Option 2B:
MA2401 Actuarial Methods, Planning and Control (G) MA2010
MA2042 Contingencies (A) MA2010
ST2353 OR Techniques (F) ST1210, MA1030, MA1031
Option 3A:
FE3148 Financial Risk Management (B)
MA3401 Advanced Contingencies (A) MA2042
ST3320 Time Series and Forecasting Methods (E) ST2210
FIELD SPECIFICATION
FILENAME Financial Mathematics major 20078-2008.doc
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