msc in financial modelling and optimization - school of

MSc in Financial Modelling and Optimization

Programme Information

2013-2014

MSc in Financial Modelling and Optimization – Student Guide 2

Contents 1 Introduction ......................................................................................................................................... 4

2 Programme aims .................................................................................................................................. 4

3 Administration ..................................................................................................................................... 5

3.1 Programme Director ...................................................................................................................................5

3.2 Programme Secretary .................................................................................................................................5

3.3 Personal Tutors ...........................................................................................................................................5

3.4 Representation and feedback ....................................................................................................................6

4 Teaching and learning approach ........................................................................................................... 6

4.1 Core courses ...............................................................................................................................................6

4.2 Optional courses .........................................................................................................................................6

4.3 Dissertation.................................................................................................................................................7

4.4 Attendance .................................................................................................................................................8

4.5 Combining work and study .........................................................................................................................8

4.6 Coursework, cover sheets and group assignments ....................................................................................8

4.7 Plagiarism ...................................................................................................................................................9

4.8 Electronic submission and self-checking for plagiarism .......................................................................... 10

4.9 Special Circumstances ............................................................................................................................. 11

5 Dissertation ........................................................................................................................................ 11

5.1 Role of the academic supervisor ............................................................................................................. 12

5.2 Assessment criteria.................................................................................................................................. 12

5.3 Dissertation format ........................................................................................................................... 13

6 Programme Structure ......................................................................................................................... 13

6.1 Programme dates .................................................................................................................................... 13

6.2 Examinations ........................................................................................................................................... 14

7 Assessment requirements ................................................................................................................... 14

7.1 Unsatisfactory performance .................................................................................................................... 15

7.2 Appeals .................................................................................................................................................... 15

7.3 Complaints .............................................................................................................................................. 15

8 Individual course details ..................................................................................................................... 16

8.1 Core courses ............................................................................................................................................ 16

8.2 .................................................................................................................................................................. 20

Optional courses ............................................................................................................................................ 20

9 Facilities ............................................................................................................................................. 26


9.1 James Clerk Maxwell Building ................................................................................................................. 26

9.2 University Library ..................................................................................................................................... 26

9.3 MSc Workroom ........................................................................................................................................ 26

9.4 Careers service ........................................................................................................................................ 26

9.5 Computer facilities .................................................................................................................................. 27

9.6 Travel ....................................................................................................................................................... 27


1 Introduction

This handbook is a guide to what is expected of you on this MSc in Financial Modelling and Optimization

programme, and the academic and pastoral support available to you. Please read it carefully. It will help you

to make the most of your time on the Programme. Throughout this document references to the ``MSc in

Financial Modelling and Optimization programme'', ``FMO MSc'', or simply the ``Programme'' refer to the

degree programme in Financial Modelling and Optimization unless stated otherwise.

Some important general aspects covered in this handbook are amplified in the University of Edinburgh Code

of Practice for Taught Postgraduate Programmes, which you are expected to read and is available from

http://www.docs.sasg.ed.ac.uk/AcademicServices/Codes/CoPTaughtPGProgrammes.pdf

This handbook does not supersede the University of Edinburgh Regulations, which are available from

http://www.ed.ac.uk/schools-departments/academic-services/policies-regulations

Disclaimer: Every effort has been made to ensure the contents of this booklet are accurate at the time of

printing. Unforeseen circumstances, however, may necessitate changes to the procedures, curricula and

syllabuses described. The School of Mathematics undertakes to operate within the rules and regulations as

set out in the University Calendar and the Assessment Regulations. It will also honour undertakings made in

writing to individual classes, insofar as these do not conflict with the University's regulations.

Large print: Large print version of this Guide and other documents issued to students by the School of

Mathematics can be made available. Students requiring these should contact the Mathematical Teaching

Organisation (MTO). (Telephone 0131 650 6427)

2 Programme aims

The aims of the MSc in Financial Modelling and Optimization are:

provide a flexible syllabus of study relevant to the needs of employers today in areas such as the

financial sector, energy markets and those that use modern financial tools and optimization

techniques;

facilitate the professional development of students (with a strong mathematical background) in the

theory and practice of financial mathematics and optimization and lay the foundations for a

successful career to the benefit of the economy and society;

provide a sound knowledge base in the fields studied and develop the wider process skills of

Problem Solving (through the application of advanced mathematical techniques from the areas of

Modern Probability Theory, Stochastic Analysis and Optimization), Team Working and Time/Task

Management;


http://www.ed.ac.uk/schools-departments/academic-services/policies-regulations


3 Administration

3.1 Programme Director

Dr Sotirios Sabanis

School of Mathematics

Room 4610

James Clerk Maxwell Building

The King’s Buildings

The University of Edinburgh

Edinburgh EH3 9BW

Tel: +44 (0)131 650 5084

Email: [email protected]

The Programme Director is responsible for the smooth running of the programme, including promotion and

admission, plus coordination of teaching delivery, examinations, programme evaluation, and curriculum

development. It is also the Programme Director's role to act as arbitrator in the case of requests for deadline

extensions and any other academic issues relating to individual courses that cannot be resolved between the

student and the course lecturer.

3.2 Programme Secretary

Dr Jenna Mann/ Mrs Katy McPhail,

School of Mathematics

Room 5211

James Clerk Maxwell Building

The King’s Buildings

The University of Edinburgh

Edinburgh EH3 9BW

Tel: +44 (0)131 650 4885

Email: [email protected] or [email protected]

3.3 Personal Tutors

Each student will be assigned to a Personal Tutor (PT). Your Personal Tutor is available as a first line of advice

for any academic issues which may arise whilst you are on the Programme. He/she is charged with

facilitating your orientation and smooth progression through the degree, from initial induction to

subsequent course choice, and the transition into the project/dissertation stage to successful completion.

He/she is also available to provide first line pastoral support. You are strongly advised to inform your

Personal Tutor immediately of any problems that are interfering with your coursework or progress through

the Programme, including any religious or medical requirements that might affect your participation in any

aspect of the Programme.

Other sources of specialist academic and pastoral support are listed in Appendix IV of the Code of Practice

for Taught Postgraduate Programmes.

mailto:[email protected]




3.4 Representation and feedback

Student feedback and evaluation is a valued input to curriculum and programme review and development of

the University of Edinburgh. Formally, students are asked to complete evaluation forms for each course they

take, and to attend (or select representatives for) Staff-Student Liaison Committee meetings.

Representatives are also welcome to participate in the Edinburgh University Students' Association. Informal

feedback is welcome at any time.

4 Teaching and learning approach

The study programme for the FMO MSc consists of:

9 compulsory courses including 2 full year course,

12 optional courses,

1 project.

4.1 Core courses

The core courses deal with the technical knowledge and practical skills that are essential for anyone who is

to graduate with an MSc in Financial Modelling and Optimization. There are nine core courses:

Semester 1

Discrete-Time Finance (15 points)

Stochastic Analysis in Finance I (7.5 points)

Fundamentals of Optimization (10 points)

Finance, Risk and Uncertainty (10 points)

Semester 2

Risk-Neutral Asset Pricing (15 points)

Stochastic Analysis in Finance II (7.5 points )

Simulation (10 points)

Optimization Methods in Finance (15 points)

Full Year

Research-Linked Topics (5 points)

Brief descriptions of these courses and links to the Degree Regulations and Programmes of Study (DRPS) can

be found in Section 8.1.

4.2 Optional courses

The optional courses allow each student to specialise in a range of skills that suits his/her own career

development. Your Personal Tutor will discuss with you the appropriate choice of optional courses based on

your background and progress on the Programme to date. You will be asked to make a provisional choice of

MSc in Financial Modelling and Optimization – Student Guide 7 optional courses for both Semesters at the start of the year. You can sign up for more than 120 credits at this

stage. You will not be allowed to sign up for new Semester 1 courses after 25 September 2013 or Semester 2

courses after 22 January 2014. We will ask you to confirm course cancellations for Semester 1 by 18 October

2013 and by 14 February 2014 for Semester 2 courses. A student is allowed to withdraw from a course, at

any time up to the end of week six of the Semester, providing that the student has not taken any

assessment on that course.

The list of optional courses is given below. The list is provisional at this stage as optional courses will not

normally run with fewer than 5 students.

Semester 1

o Computing for Operational Research and Finance (10 points)

o Programming Skills (10 points)

Semester 2

o Advanced Time Series Econometrics (10 points)

o Combinatorial Optimization (5 points)

o Credit Scoring and Data Mining (10 points)

o Financial Risk Management (10 points)

o Fundamentals of Operational Research (10 points)

o Microeconomics 2 (10 points)

o Nonlinear Optimization (10 points)

o Risk Analysis (5 points)

o Stochastic Modelling (10 points)

o Stochastic Optimization (5 points)

Brief descriptions and links to the DRPS of these courses can be found in Section 8.2.

4.3 Dissertation

During the period from June to August, candidates for the MSc work on a project on an approved topic and

write a dissertation based on this work. The project gives the student the opportunity to apply skills

developed earlier in the programme to real problems in Financial Mathematics and Optimization. Projects

often take the form of a consultancy exercise for a sponsoring organisation.

Students are strongly encouraged to seek the opportunity to do their project in collaboration with an outside

partner in a bank, financial institution or an organisation which has a requirement for consultation by a

Financial Mathematics analyst with specialisation in Optimization. A wide variety of organisations provide

project topics and assist with their supervision. Projects need to be accepted by the Project Coordinator, Dr

Lukasz Szpruch, to ensure they are suitable for an MSc.

Here is a list of different types of dissertations. This list is not exhaustive, nor are its members mutually

exclusive; it is just meant to give some ideas about what makes an acceptable dissertation.


A subject review surveys a chosen area, summarising the research literature and providing an

overview of its development, importance, methodology and outstanding problems.

A theoretical essay describes, in considerable depth, some piece of mathematical theory relevant to

finance. Papers in research journals are often very terse and assume a lot of prior knowledge on the

part of the reader; and acceptable project could be to explain a recent paper, making its results

more accessible and putting them in context.

A numerical project would describe and implement one or more numerical methods for pricing,

hedging or reserving for derivatives or portfolios, and perhaps aim to measure how well it

performed using real or simulated data.

A data-based project would analyse market or other data, fitting them to suitable models and

drawing conclusions.

4.4 Attendance

Lecture attendance is compulsory. The Programme Director must be notified in writing, or by e-mail, of

absence of more than a week from lectures for medical, personal, or other reasons. During the project

period you will have meeting with your supervisor. These are also compulsory.

4.5 Combining work and study

It should be stressed that the programme is full-time. You should expect to spend 40 hours per week

attending classes, working on the delivered material and preparing assignments for submission. Unless you

manage your time well, there will be weeks (particularly towards the end of Semester 2) when you will have

to work significantly more than 40 hours. As a consequence, it is recommended that students do not take

any employment. The University recommends a full time student not to work more than 16 hours per week

during term or during the summer months when the MSc dissertation is prepared. Students can take a part-

time job only under the condition that such an activity will not adversely affect their performance on the

MSc. Any part-time job which would exceed 16 hours per week needs special permission from the

Programme Director.

4.6 Coursework, cover sheets and group assignments

The coursework requirements---case studies, essays, and other projects---vary between courses, as does the

balance of the methods of assessment. The weighting of coursework and examinations for individual courses

is given in the information for each course.

All coursework must be submitted with a completed cover sheet, stapled in the top left corner, and handed

to the Programme Secretary, JCMB Room 5211. Completed work must not be handed directly to any other

member of staff or submitted by any other means. Cover sheets are available in JCMB 5211 (and on-line) and

have a number of functions.

They provide fields for a clear statement of the student's name and matriculation number

They contain an “own work declaration” that may be used in cases of suspected plagiarism

They allow comments on the coursework to be communicated to the lecturer


They enable the coursework mark and written feedback to be returned to the student

Until a completed cover sheet has been provided, the work will not be considered to have been

submitted.

All students must adhere to deadlines for the submission of work. Work handed in late will incur a penalty.

The penalty for late submission is a reduction of the mark by 5% of the maximum obtainable mark per

calendar day (e.g. a mark of 65% on the common marking scale would be reduced to 60% up to 24 hours

later). This applies for up to five calendar days (or to the time when feedback is given, if this is sooner), after

which a mark of zero will be given. Note that the reference to “calendar days” includes weekends and public

holidays. Students may not, for example, submit work on a Monday morning for a Friday deadline in the

expectation that no late penalty will be applied. If there is likely to be a delay due to illness or other crisis,

the Programme Director must be informed in writing so that an extension may be considered.

4.7 Plagiarism

The following is based on an extract from the guidelines for Colleges on the avoidance of plagiarism:

The University's degrees and other academic awards are given in recognition of the candidate's

personal achievement. Plagiarism (that is to say the action of including or copying, without adequate

acknowledgement, the work of another in one's own work) is academically fraudulent, and an

occurrence against University discipline.

Plagiarism, at whatever stage of the candidate's course, whether discovered before or after

graduation, will be investigated and dealt with appropriately by the University. If after investigation it

is established that work submitted has been plagiarised to a significant extent, that will be

permanently noted on a candidate's record.

Cheating and plagiarism are academic occurrences. Plagiarism can be defined as the act of including or

copying, without adequate acknowledgement, the work of another in one's own work as if it were one's

own.

The University's procedures used in case of a presumed plagiarism can be found in the University's Code of

Practice for Taught Postgraduate Programmes and the University Regulations.

The University's full information on plagiarism

http://www.ed.ac.uk/schools-departments/academic-services/students/postgraduate-

taught/discipline/plagiarism

includes specific guidance for undergraduate/postgraduate taught students

http://www.docs.sasg.ed.ac.uk/AcademicServices/Discipline/StudentGuidanceUGPGT.pdf

This includes the University's procedures for dealing with different kinds of plagiarism and advice about what

to do if you are accused of plagiarism. If you are still unsure how to avoid plagiarism, having read these

guidance notes, then you should approach the Programme Director for further advice.

The University of Edinburgh encourages discussion in the preparation of all work and cooperation in finding

sources of material. This is essential in group work, but any work submitted in an individual's name must be

http://www.ed.ac.uk/schools-departments/academic-services/students/postgraduate-taught/discipline/plagiarism

http://www.ed.ac.uk/schools-departments/academic-services/students/postgraduate-taught/discipline/plagiarism

http://www.docs.sasg.ed.ac.uk/AcademicServices/Discipline/StudentGuidanceUGPGT.pdf

MSc in Financial Modelling and Optimization – Student Guide 10 prepared solely by that person. Using any published source whether private, public or from the internet

without providing a full reference, or using other students' work are disciplinary occurrences which could

lead to reduced or no marks being awarded for the work, and in extreme cases to immediate termination of

studies. Students should therefore make sure that they are quite clear about the status of every piece of

work they submit, including computer based material such as spreadsheets and computer programs. An

individual assignment must be wholly and exclusively the work of the student submitting the assignment.

Any common material found in such assignments may be treated as plagiarism, with serious consequences

for the students concerned.

The definition of plagiarism varies from educational system to educational system, and this can be a source

of misunderstandings. However, it must be absolutely clear that students must not copy another person's

work or claim another person's work as their own. Students must be aware of possible dangers in this area.

For this reason:

Always ensure the references for quotations are provided.

Do not take an extract from any text without placing quotation marks around it and referencing the

source.

If a diagram is used or adapted, give a reference to the source.

If, in an assignment, a student draws upon work performed by him/her-self outside the programme

or prior to attendance on the programme, this must be clearly indicated in the assignment.

If in doubt, check with the Programme Director.

Past experience shows that specific procedures are required to prevent, deter and detect plagiarism. To

prevent plagiarism of certain important handwritten assignments in core courses, they will be written up

under supervision. To detect plagiarism in typeset work, all the submissions will analysed using the

plagiarism detection software “Turnitin”.

4.8 Electronic submission and self-checking for plagiarism

In addition to the hard copy, most assignments requiring typeset work (and the dissertation project) must be

submitted electronically. This is done via “Learn”, from “MyEd”. Independently, students will also be able to

perform a self-check for plagiarism using “Turnitin”. This is also available from “MyEd”. This will compare the

text of your submission against the following sources

Turnitin's student paper repository

Current and archived internet

Periodicals, journals and publications

What you self-check for plagiarism will not be compared with submissions from other students on the

Programme, nor will it be retained in Turnitin's student paper repository. The final, formal submission that

you make via Learn will be checked for plagiarism against the sources above and submissions from other

students on the Programme. It will also be retained in Turnitin's student paper repository.

It is hoped that these procedures, together with the sanctions that can be applied if plagiarism is detected,

will deter the members of the FMO MSc class who might, otherwise, cheat in order to get higher marks.


4.9 Special Circumstances

You should let either the Programme Director or your Personal Tutor know if you feel an illness, or other

circumstances out-with your control, is either impacting on your studies, or may impact on your examination

performance. For formal consideration of your case by the School, you will be required to supply appropriate

supporting documentation and/or medical evidence to your Personal Tutor and give your permission for

them to submit your case. The School will consider all submitted cases and make its recommendations to the

Board of Examiners for approval.

For more information on what circumstances are deemed appropriate, see the College of Science and

Engineering guidelines:

https://www.wiki.ed.ac.uk/download/attachments/174590921/Student+Guide+to+College+Special+Circums

tances+Policy+20130901DW.pdf?version=1

5 Dissertation

The dissertation gives students the opportunity to make use of the knowledge and skills developed on the

programme, frequently by working on a real mathematical finance problem within an organisation, although

dissertation projects may also be desk/library based.

Prior to the final assessment of the taught component of the MSc programme, all students are considered as

MSc candidates. Following the Board of Examiners meeting in June, students who complete the taught

component at MSc level proceed to the dissertation stage of the MSc programme. The award of the MSc

degree thereafter depends solely on the achievement of a dissertation mark of at least 50%.

It is the responsibility of each MSc candidate to prepare a dissertation on a subject chosen by agreement

with a member of staff who will act as an Academic Supervisor. Dissertation topics will be agreed by mid-

May. Detailed work will be carried out during the months of June, July and August, with sufficient time being

allocated to writing up the dissertation. In many cases the research for the dissertation will involve working

with an outside organisation for at least part of the summer months.

University regulations require full-time postgraduate students to be in Edinburgh for the duration of the

Programme, unless specifically granted a leave of absence. This will not be given to enable the student to

submit a dissertation early in order to return home prior to the end of the programme. Completing a

dissertation in less than the time available is also extremely unwise as early completion may adversely affect

the standard of work and presentation.

Two typeset copies of the dissertation must be submitted to the Programme Secretary (JCMB Room 5211) by

11.00am on 18 August 2014. An electronic version of the dissertation must also be submitted via “Learn” by

this deadline. If commercial confidentiality requires that a dissertation be treated as confidential, this can be

arranged by informing the office at the time of submission. Confidential dissertations will be read by the

Academic Supervisor and examiners, and will not be available for reference.

Dissertations are read by two internal examiners before being reviewed by the External Examiner. A copy of

the dissertation can be collected by the student after the final Board of Examiners meeting in

September/October.

https://www.wiki.ed.ac.uk/download/attachments/174590921/Student+Guide+to+College+Special+Circumstances+Policy+20130901DW.pdf?version=1

https://www.wiki.ed.ac.uk/download/attachments/174590921/Student+Guide+to+College+Special+Circumstances+Policy+20130901DW.pdf?version=1

MSc in Financial Modelling and Optimization – Student Guide 12 You are strongly advised to keep a back-up draft of your dissertation and not to use a USB pendrive for this

purpose since they are easily lost or damaged. No compensation or extension will be given for work or data

lost by students.

5.1 Role of the academic supervisor

The Academic Supervisor will give advice on the subject area, relevant literature, presentation

format, methodology, structure of the dissertation, and scheduling of the work to be done. The final

responsibility for the dissertation always lies with the student. Advisers are not expected to read and

amend chapters, but they may require periodic progress reports and sample chapters. The

responsibility for the quality and content of a dissertation lies with the author of the dissertation.

Academic staff acting as Academic Supervisors cannot be expected to be available at all times,

especially during the summer period, although staff will provide back-up facilities during their

absence. Meetings should be arranged between Academic Supervisors and students at regular

intervals, as appropriate. These meetings are primarily the initiative of the student. The frequency of

contact with Academic Supervisors depends on the wishes of the individual student and Academic

Supervisor, but students should try to discuss progress with their Academic Supervisors at least once

every 2 or 3 weeks, with more frequent discussions in the early stages.

In the case of projects based in an outside organisation, Academic Supervisors may visit the students

in the organisation.

Students may ask their Academic Supervisors to read a draft of part of the dissertation, but it is up to

the Academic Supervisor's professional judgement as to how much of the dissertation he or she is

willing to read. Clearly, an Academic Supervisor cannot examine a dissertation before it is formally

submitted and any comments which an Academic Supervisor makes on a draft are provisional in that

the Board of Examiners may come to a decision which differs from that of the Academic Supervisor.

5.2 Assessment criteria

All dissertations are expected to conform to the following standards:

The dissertation must add to the understanding of the dissertation subject.

The dissertation must show awareness of the relevant literature.

The dissertation must contain relevant analysis: an informed description of a problem is not

sufficient.

The dissertation must be presented using a satisfactory standard of English.

Students should inform their Academic Supervisor and the Programme Director of any factors that will

adversely affect their ability to work on their dissertation topic. Extenuating circumstances will be taken into

account by the Board of Examiners, but this information must be available prior to the meeting of the Board.

Exceptionally, it is possible for extensions to be granted if justified by illness or other personal problems. This

can be done if relevant information is given to the Academic Supervisor or the Programme Director.


5.3 Dissertation format

Dissertations should consist of the following:

- Title page with your NAME, MATRIC NUMBER, PROGRAMME TITLE, DISSERTATION TITLE and YEAR

- Abstract

- Acknowledgements

- Own work declaration (signed and dated)

- Table of contents

- Main text (including introductory chapter and final chapter on conclusions and/or recommendations)

- Appendices (optional)

- Bibliography

The main text of the dissertation must not exceed 35 pages, based upon a 12-point font size and 1.0-line

spacing. The main text referred to here, does not include such things as tables, graphs, figures, appendices

and computer code.

Dissertations must be type set on one side of white A4 paper only. The following minimum margins must be

observed.

Left 30mm Right 15mm Top 15mm Bottom 20mm

The pages in the main text, appendices and bibliography must be numbered consecutively.

6 Programme Structure

6.1 Programme dates

Induction Week: 9 - 13 September 2013

Semester 1

o Teaching period: 16 September - 6 December 2013

o December exams: 9 December - 20 December 2013

o Winter break: 23 December 2013 - 10 January 2014

The School of Mathematics will be closed during the period 23 December - 10 January (inclusive)

and (for security reasons) students will not be able to gain admittance.

Semester 2

o Teaching period: 13 January - 4 April 2014

o Spring break: 7 April - 18 April 2014


o April/May exams: 21 April - 23 May 2014

o Summer break: 26 May - 30 May 2014

MSc Project (dissertation): 2 June - 18 August 2014

MSc dissertations are to be submitted by 11.am on 18 August 2014. Late submissions are penalised.

See Item 4.6 for details of the penalty for late submission.

6.2 Examinations

Students must attend all examinations. Students who do not attend an examination will be deemed to have

failed. If there are special circumstances relating to the non-attendance, a Special Circumstances form and

appropriate documentation must be submitted no later than two days after the last affected assignment.

Students will not be excused from the examinations because of holiday plans.

The Registry will give details of the location of each examination once this is known. Information on the form

of the examination will be given for each course. There are no resit examinations for any of the courses on

the programme.

6.2.1 Dictionaries in Examinations

No student is permitted to take any dictionary into an examination without written permission. Please

consult the programme secretary Mrs Katy McPhail.

6.2.2 Calculators

Only a calculator from the following list (specified by the College of Science and Engineering) may be used in

examinations.

Make Model

Casio fx85 (any version, e.g. fx85WA, fx85MS)

Casio fx83 (any version)

Casio fx82 (any version)

7 Assessment requirements

To determine the overall assessment of the taught component on the University Common Marking Scale

(UCMS), courses are weighted. Each core course worth 15 points has a weighting of 1/8 (or 15/120), each

core course worth 10 points has a weighting of 1/12 (or 10/120) and each core course worth 7.5 points has a

weighting of 1/16 (or 7.5/120). The total weight of core courses is 3/4.

Similarly, each optional course worth 15 points has a weighting of 1/8 each optional course worth 10 points

has a weighting of 1/12 and each optional course worth 7.5 points has a weighting of 1/16. Students must

choose optional courses having a total weight of 1/4.

MSc in Financial Modelling and Optimization – Student Guide 15 The UCMS mark for the taught component of the Programme is the weighted average over courses (core

and optional courses). Sufficient conditions for the various awards that can be made are set out in Table 1.

The University’s Taught Assessment Regulations (specifically Regulation 51-54 for 2013-14) state the

minimum requirements for each award and can be found at

http://www.docs.sasg.ed.ac.uk/AcademicServices/Regulations/TaughtAssessmentRegulations.PDF

Upon completion of the taught component of the Programme, any student satisfying the conditions set out

in the penultimate column of Table 1, will be permitted to proceed to the dissertation. Note that candidates

are not allowed to re-sit a paper in order to be considered for the award of MSc.

Diploma Dip with Distinction MSc MSc with Distinction

All courses average 40% 70% 50% 70%

80 points at 50% No No Yes Yes

80 points at 40% Yes Yes Yes Yes

Project/Dissertations No No 50% or above 70% or above

Table 1: Sufficient conditions for a given award. Percentages are UCMS. Students should note that in order

to be eligible for an MSc with Distinction, all courses must be passed at 40% or above (Regulation 54.5).

7.1 Unsatisfactory performance

Under the rules drawn up by the University, the Head of the School of Mathematics can, on the advice of the

Programme Director, formally request a student who is not performing adequately, or has otherwise

breached University discipline, to withdraw from the programme at any time during the programme.

7.2 Appeals

The University regulations for postgraduate appeals can be found in the University's Code of Practice for

Taught Postgraduate Programmes and Academic Services Appeals.


http://www.ed.ac.uk/schools-departments/academic-services/students/postgraduate-taught/academic-

appeals

7.3 Complaints

We would encourage students to raise any problems (either academic or personal) as quickly as possible by

approaching their Student Representative, Personal Tutor, course staff and the Advice Place, as appropriate.

When such matters cannot be resolved informally, the University has a formal student complaints procedure

which can be found at

http://www.ed.ac.uk/schools-departments/student-academic-services/student-complaint-procedure

http://www.docs.sasg.ed.ac.uk/AcademicServices/Regulations/TaughtAssessmentRegulations.PDF


http://www.ed.ac.uk/schools-departments/academic-services/students/postgraduate-taught/academic-appeals

http://www.ed.ac.uk/schools-departments/academic-services/students/postgraduate-taught/academic-appeals

http://www.ed.ac.uk/schools-departments/student-academic-services/student-complaint-procedure


8 Individual course details

8.1 Core courses

Brief details for the core courses are listed below, including the number of teaching hours and delivery

period. For details of the syllabus and recommended texts for a particular course, please use the link to the

DRPS for that course.

Discrete-Time Finance

(30+ hours, semester 1)

Lecturer: Dr Sotirios Sabanis

Aims

To introduce, in a discrete time setting, the basic probabilistic ideas and results needed for the later

stochastic process and derivative pricing courses. By the end of the course students will be expected to

understand discrete martingale theory and its relationship with financial concepts such as arbitrage.

Assessment

Discrete-Time Finance will be assessed by 100% exam.

http://www.drps.ed.ac.uk/13-14/dpt/cxmath11075.htm

Finance, Risk and Uncertainty

(30 hours, semester 1)

Lecturers: Prof John Davies

Aims

To provide key concepts in Finance which are integral part of the theory of Financial Math-

ematics.

Assessment

Finance, Risk and Uncertainty will be assessed by 30% coursework and 70% exam.





Fundamentals of Optimization


Lecturer: Prof Jacek Gondzio

Aims

Many management decision problems can be formulated as Linear Programming problems. This core course

introduces the theory and application of this important optimization technique. Syllabus: Convexity; Linear

Programming: model formulation, simplex method: tableau form, revised SM, geometric interpretation,

sensitivity analysis; Extensions and applications of LP: goal programming, data envelopment analysis (DEA),

transportation problems, piecewise linear objective, cutting plane methods; Duality in LP, Lagrangian

Relaxation; Solving LP problems using commercial mathematical programming software; Public domain

software for optimization, NEOS.

Assessment

Fundamentals of Optimization will be assessed by 20% coursework and 80% exam.


Optimization Methods in Finance


Lecturer: Dr Peter Richtarik

Aims

This course will demonstrate how recent advances in optimization modelling, algorithms and software can

be applied to solve practical problems in computational finance. Previous exposure to optimization theory

and methods is not assumed.

Assessment

Optimization Methods in Finance will be assessed by 50% coursework and 50% exam.





Research-Linked Topics

(18 hours, full year)

Lecturer: Dr Sotirios Sabanis

Aims:

Research linked material presented to the students so as to allow them to work on a particular active

problem in financial mathematics.

The Research-Linked Topics consist of two short courses with a grand total of 5 points. They are taken as

guided reading courses in weeks 10-13 of semester 1 and in weeks 7-12 of semester 2. In each semester,

students choose 1 topic from a list which may vary from year to year. The topics are assessed by either oral

presentation and/or short written essay. A topic is assessed in week 13 of semester 1, and another topic is

assessed in week 11 of semester 2. The combined weight of the topics is 5 points, that is, each is worth 2.5

points.

Assessment

Research-Linked Topics will be assessed by 100% coursework.


Risk-Neutral Asset Pricing


Lecturer: Dr Miklos Rasonyi

Aims

To provide solid mathematical foundations for pricing derivative products in financial markets, highlighting

the points where the idealized and the realistic diverge.

Assessment

Risk-Neutral Asset Pricing will be assessed by 100% exam.





Simulation


Lecturer: Dr Lukasz Szpruch

Aims

Introduction to Monte Carlo methods and random number generation. Use of simulation for option pricing.

Variance reduction methods. Stochastic programming, coherent risk measures and value at risk.

Assessment

Simulation will be assessed by 5% coursework and 95% exam.


Stochastic Analysis in Finance I & II

(20 hours, semester 1; 20 hours, semester 2)

Lecturers: Prof Istvan Gyongy and Dr Sotirios Sabanis

Aim

This course will provide and develop the key mathematical ideas which are used in derivative pricing. By

spending a significant proportion of time on this particular topic it is hoped that the students develop a good

understanding of the mathematics. This will provide a rigorous framework for the derivative pricing course

enabling students to understand where the assumptions in the models break down.

Assessment

Stochastic Analysis in Finance I and II will be assessed together by one examination.







8.2 Optional courses

Brief details for optional courses are listed below, including the number of teaching hours and delivery

period. For details of the syllabus and recommended texts for a particular course, please use the link to the

DRPS for that course. The list of optional courses below is provisional at this stage. Some courses may not be

available in a specific year.

Advanced Time Series Econometrics


Course Organiser: Prof Jonathan Thomas (Economics)

Aims

This module explores further topics in time series econometrics. Students will be introduced to various tools

that are part of the basic econometric training of professional economists. **Students must seek permission

from their PT and email [email protected] in advance to request permission**

Assessment

Advanced Time Series Econometrics will be assessed by 100% exam.

http://www.drps.ed.ac.uk/13-14/dpt/cxecnm11049.htm

Combinatorial Optimization


Lecturer: Prof Jonathan Thomas (Economics)

Aims

This course will discuss both mathematical programming and heuristic approaches to solving combinatorial

optimization problems.

Assessment

Combinatorial Optimization will be assessed by 100% coursework.





Computing for Operational Research and Finance


Lecturer: Dr Andreas Grothey and Chaman Kumar

Aims

This course gives an introduction to several packages, including LaTeX, Matlab and Excel, via applications

relevant to OR and Finance, then develops basic skills in java programming.

Assessment

Computing for Operational Research and Finance will be assessed by 100% coursework.


Credit Scoring and Data Mining


Lecturers: David Edelman and Prof Nick Radcliffe

Aims

Understanding how large data sets can be used to model customer behaviour. How such data is gathered,

stored and interrogated and its use to cluster, segment and score individuals. The aim is to look at the largest

applications in more detail. Credit scoring is the process of deciding, whether or not to grant or extend a

loan. Sophisticated mathematical and statistical models have been developed to assist in such decision

problems.

Assessment

Credit Scoring and Data Mining will be assessed by 100% coursework.





Financial Risk Management


Lecturer: Emmanuel Fragniere

Aims

Risk is a key factor in many financial decisions. The ability to assess risk and hedge the decision against it

needs to be translated into quantitative measures.

Assessment

Financial Risk Management will be assessed by 100% coursework.


Fundamentals of Operational Research


Lecturer: Dr Andreas Grothey

Aims

Dynamic programming is a neat way of solving sequential decision optimization problems. Integer

Programming provides a general method of solving problems with logical constraints. Game theory is

concerned with mathematical modelling of behaviour in competitive strategic situations in which the success

of strategic choices of one individual (person, company, server, ...) depends on the choices of others.

Assessment

Fundamentals of Optimization will be assessed by 20% coursework and 80% exam.





Microeconomics 2


Course Organiser: Prof Jonathan Thomas (Economics)

Aims

To give students a command of the main tools of microeconomic analysis, so that they can undertake

advanced work in areas such as industrial economics, public economics, labour economics, environmental

economics, international economics and finance; and to show how such microeconomic analysis can be

applied in making the transition from theoretical models to empirical/policy models. An introduction to

models of information and incentives, including adverse selection, signalling and screening. **Students must

seek permission from their PT and email [email protected] in advance to request permission**

Assessment

Microeconomics will be assessed by 100% exam.


Nonlinear Optimization


Lecturer: Sergio Garcia-Quiles

Aims

To introduce students to the analysis of nonlinear optimization problems and to present the classical

methods for solving nonlinear optimization problems with and without constraints, and nonlinear equations.

Assessment

Nonlinear Optimization will be assessed by 5% coursework and 95% exam.





Programming Skills


Lecturer: Dr Mike Jackson

Aims

This course aims to provide students with practical experience of tools and techniques which will help

students to become a more effective programmer, to do more, to a higher degree of quality in less time and

with less effort. These fundamentals of good programming are applicable to any programming language.

Assessment

Programming Skills will be assessed by 100% coursework.

http://www.drps.ed.ac.uk/13-14/dpt/cxpgph11079.htm

Risk Analysis


Lecturers: Prof Ken McKinnon

Aims

Risk analysis deals with the assessment and management of the risk form unlikely but costly events. This

course will introduce the risk analysis methodology.

Assessment

Risk Analysis will be assessed by 100% coursework.


http://www.drps.ed.ac.uk/13-14/dpt/cxpgph11079.htm



Stochastic Modelling


Lecturer: Dr Burak Buke

Aims

Uncertainty and randomness serve to make decision problems encountered in industry non-trivial.

Uncertainty is quantified through the study of probability. This course aims to cover an important area of

Applied Probability, namely Markov Processes. The second part of the course deals with continuous time

processes, including the application to queueing problems which form the subject of many OR investigations.

Assessment

Stochastic Modelling will be assessed by 20% coursework and 80% exam.


Stochastic Optimization


Lecturer: Dr Roberto Rossi

Aims

Stochastic optimization deals with the optimization problems with uncertain data. The modelling objective is

to find the best way to hedge against the resulting risk. The applications considered are: portfolio analysis,

strategic planning, sequential sampling and production problems.

Assessment

Stochastic Optimization will be assessed by 20% coursework and 80% exam.





9 Facilities

9.1 James Clerk Maxwell Building

Your right to be in the building and means of access are as follows

08:00 - 18:00 Monday-Friday: No restriction on access

18:00 - 21:00 Monday-Friday and 09:00 - 17:00 Saturday and Sunday: You are allowed in the building

and your student card will give you access.

At all other times you are not permitted to be in the building and your student card (even with the

PIN) should not give you access.

If you are found in the building when you are not permitted to be then you must leave when asked to do so.

9.2 University Library

The University of Edinburgh has excellent library facilities. The libraries which are most likely to be relevant

for this programme are:

Noreen and Kenneth Murray Library, King's Buildings, West Mains Road, Edinburgh EH9 3JF. Tel:

0131 650 5784

Main Library, George Square, Edinburgh, EH8 9LJ, tel: 0131 650 3409.

For the opening hours see:

http://www.ed.ac.uk/schools-departments/information-services/library-museum-gallery/using-libraries

9.3 MSc Workroom

The MSc workroom is 5210 in JCMB. Near 5210 is the “kitchen area" of the School of Mathematics with a

sink, fridge, microwave, cupboards and kettle for the use of all occupants of the 5210 room.

9.4 Careers service

The University of Edinburgh Careers Service offers advice, information and practical help in all matters

relating to the development of students' future work or study plans. The Careers Service offices are at:

Weir Building, West Mains Road, Edinburgh EH9 3JY Tel: 0131 650 5773 Fax: 0131 650 6704 Email:

[email protected].

33 Buccleuch Place, Edinburgh, EH8 9JS Tel: 0131 650 4670 Fax: 0131 650 4479 Email:

[email protected].

For the opening hours see the Careers Service web site: http://www.careers.ed.ac.uk/

http://www.ed.ac.uk/schools-departments/information-services/library-museum-gallery/using-libraries

http://www.careers.ed.ac.uk/


9.5 Computer facilities

All students have a University email address that allows them to be contacted from anywhere in the world.

Students are required to check regularly for email sent to this address, since this is the formal means of

communication with students.

The University of Edinburgh provides free wireless internet (WiFi) in most buildings. You need to register

before you can use it with your wireless-enabled device. Further information will be distributed during

Induction Week.

Students should use the MSc computing room (5205). An introduction to computing facilities will be

provided during Induction Week when the full range of facilities will be explained. Any general

hardware/software problems should be reported to [email protected]

9.6 Travel

A shuttle bus runs at regular times between the George Square campus and the Kings Buildings campus of

the University of Edinburgh.

http://www.ed.ac.uk/staff-students/students/shuttlebus

There are several scheduled bus services which run from the city centre to the Kings Buildings campus:

The number 42 runs every 20 minutes from George IV Bridge to Kings Buildings.

Other buses (3, 7, 8, 31) run along a parallel route from North Bridge and Nicholson Street to Craigmillar Park

and Cameron Toll. From there it is a 5 minute walk to the Kings Buildings campus.

For more info about Lothian buses see http://lothianbuses.com/


http://www.ed.ac.uk/staff-students/students/shuttlebus

http://lothianbuses.com/

msc in financial modelling and optimization - school of

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