HANDBOOK
MSc Financial Engineering
2004 – 2005
Birkbeck College
School of Economics, Mathematics & Statistics
http://www.ems.bbk.ac.uk
SCHOOL OF ECONOMICS, MATHEMATICS & STATISTICS
ACADEMIC STAFF
Anne Sibert, PhD(Carnegie Mellon) - Head of School
Professor in International Finance
Andris Abakuks, PhD(Lond)
Yunus Aksoy, Phd(Leuven)
Lecturer in Statistics
Lecturer in Economics
Fiona Atkins, PhD(Lond)
Parimal Bag, PhD (Cornell)
Lecturer in Economics
Senior Lecturer in Economics
Brad Baxter, PhD(Cantab)
Andrew Bowler, PhD(Lond)
Lecturer in Financial Mathematics
Lecturer in Mathematics
Anthony Brooms, PhD(Brist)
Lecturer in Statistics
Raymond Brummelhuis, PhD(Amst)
Alvaro Cartea, DPhil(Oxon)
Jerry Coakley, PhD(OU)
Arupratan Daripa, PhD(Princeton)
Professor of Mathematical Finance
Lecturer in Financial Mathematics
Associate Professor in Economics
Lecturer in Financial Economics
John Driffill, PhD(Princeton)
Suzanne Evans, PhD(Lond)
Professor of Economics
Lecturer in Statistics
Anthony Garratt, PhD(Lond)
Senior Lecturer in Economics
Clemens Grafe, PhD(Lond)
Kenjiro Hori, MPhil(Cantab)
Lecturer in Economics
Lecturer in Economics
Simon Hubbert, PhD(Lond)
Anthony Humm, PhD(Lond)
Lecturer in Mathematical Finance
Associate Lecturer in Economics
Sandeep Kapur, PhD(Cantab)
Marika Karanassou, Phd(Lond)
Senior Lecturer in Economics
Teaching Fellow
Jihong Lee, PhD(Cantab)
Lecturer in Economics
Sarah Perkins, PhD(UMIST)
Zacharias Psaradakis, PhD(So'ton)
Lecturer in Mathematics
Professor of Econometrics
Hamid Sabourian, PhD(Cantab)
Stephen Satchell, PhD(Lond)
Visiting Professor
Visiting Fellow
Ron Smith, PhD(Cantab)
Martin Sola, PhD(So'ton)
Professor of Applied Economics
Professor of Economics
Stephen Wright, MA(Cantab)
Lecturer in Economics
Gylfi Zoega, PhD(Columbia)
Senior Lecturer in Economics
ADMINISTRATIVE STAFF
Jan O'Brien, BA(Hons)
Department Administrator
020 7631 6401
Barbara Rye, MSc(Lond)
Beverley Downton, BA(Hons)
Financial Economics Admin.
Mathematics & Statistics Admin.
020 7631 6403
020 7631 6442
Vanesa Ho
Tim Byne
Economic & Social Policy Secretary
Postgraduate Admissions Administrator
020 7631 6432
020 7631 6429
CONTENTS
1 MSC FINANCIAL ENGINEERING: GENERAL PROGRAMME
INFORMATION 1
1.1
Aim of Handbook .................................................................................................. 1
1.2
Staff Responsible for the MSc Financial Engineering ....................................... 1
1.3
Other Sources of Information for Students ........................................................ 2
1.4
Fees and Enrolment .............................................................................................. 2
1.5
Important Dates .................................................................................................... 2
1.6
Programme Aims and Objectives ........................................................................ 2
1.7
Programme Structure ........................................................................................... 3
1.8
Brief Descriptions of Courses .............................................................................. 3
1.9
Allocation of Marks .............................................................................................. 5
1.10
A Brief Guide to the Marking System................................................................. 5
1.11
Results .................................................................................................................... 6
2
MSC FINANCIAL ENGINEERING COURSE UNITS .................................... 7
2.1
September Statistics
2.2
September Mathematics
2.3
September Introduction to Finance
2.4
Mathematical Methods FT and PT1 ................................................................ 10
2.5
Financial Econometrics FT and PT1 ................................................................ 12
2.6
Pricing FT and PT2 ........................................................................................... 13
2.7
Risk Management FT and PT2 ......................................................................... 14
2.8
Dissertation FT and PT2 ................................................................................... 15
3
FT and PT1 ........................................................... 7
FT ......................................................................... 8
FT and PT1 ................................... 9
TEACHING AND ASSESSMENT................................................................ 17
3.1
Course Assessment .............................................................................................. 17
3.2
Feedback on Coursework ................................................................................... 17
3.3
Examination Regulations ................................................................................... 18
3.4
Examination Registration .................................................................................. 18
3.5
Examination Deferment ..................................................................................... 18
3.6
Policy on Plagiarism ........................................................................................... 19
i
4
PROVISIONAL TIMETABLES .................................................................... 21
4.1
September Statistics, Mathematics & Introduction to Finance ...................... 21
4.2
MSc Financial Engineering Full-time AUTUMN TERM ............................... 22
4.3
MSc Financial Engineering Full-time SPRING TERM .................................. 23
4.4
MSc Financial Engineering Part-time Year 1 AUTUMN TERM .................. 24
4.5
MSc Financial Engineering Part-time Year 1 SPRING TERM ..................... 25
4.6
MSc Financial Engineering Part-time Year 2 AUTUMN TERM .................. 26
4.7
MSc Financial Engineering Part-time Year 2 SPRING TERM ..................... 27
ii
MSc Financial Engineering: General Programme Information
1 MSc Financial Engineering: General Programme
Information
Welcome to the School of Economics, Mathematics and Statistics. We hope that
taking your degree will be an enjoyable experience both academically and
personally.
1.1
Aim of Handbook
This handbook has several aims:

to help you understand the structure of the degree programme;

to introduce you to the Departmental staff and their roles within the Department
and the College;

to provide details of procedures, rules and regulations etc. for the degree
programme.
1.2
Staff Responsible for the MSc Financial Engineering
Programme Director
Raymond Brummelhuis
Email: r.brummelhuis@bbk.ac.uk
Programme Administrator
Barbara Rye
Room: 716
Tel:
020 7631 6403
Fax: 020 7631 6416
Email: b.rye@bbk.ac.uk
Personal Tutors
At the beginning of the Autumn term a list is posted on the main noticeboard (seventh
floor) indicating Personal Tutor allocations for each course.
School Computer Representative
Nigel Foster
Room 759
Tel:
020 7631 6402
Email: n.foster@bbk.ac.uk
Lecturers
Generally members of staff are available at certain times during normal office hours
each week. These 'office hours' are posted on the noticeboards on the seventh floor.
It is best to meet the staff members during these hours. Outside these hours you may
leave a note for them in the School Office specifying the nature of the problem, and
your contact number, etc. This procedure is especially useful for routine
communication. If the matter is urgent you could call them to seek an appointment
1
MSc Financial Engineering: General Programme Information
outside their office hours. We also encourage students to contact us by email. The
email address of staff members is initial.surname@bbk.ac.uk.
1.3
Other Sources of Information for Students
Much information can be obtained from the College web site. School-specific
information is found at http://www.bbk.ac.uk/ems, and College information at
http://www.bbk.ac.uk/.
You can also get a copy of the current University Regulations for Internal Students if
you present your College membership card at the Academic Enquiries Desk in the
reception area of Senate House (in Malet Street, to the South of the main College
building).
1.4
Fees and Enrolment
You should receive enrolment/registration papers before you start the course. You
will not be able to use the College facilities, such as the library, without a College
membership card issued at enrolment.
The sessional fee is due in full by the first day of the Autumn term. Self-financing
students are offered the facility of paying by instalments either by direct debit or
termly cheque, but only if this is arranged at the beginning of October. Queries on
fee issues should be addressed to the Registry.
Students who wish to withdraw from the programme must give immediate notice in
writing or email to the School.
1.5
Important Dates
September Quantitative Techniques (Statistics and Mathematics) Lectures: 6
September - 23 September, Revision classes 27 September.
September QT Examinations: Wednesday 29 September (Mathematics); Thursday
30 September (Statistics)
September Introduction to Finance: 8, 15 and 22 September.
Term Dates 2004 – 2005
Autumn:
Spring:
Revision:
Examinations:
4 October – 17 December 2004 (Reading week 8-12 November)
10 January – 18 March 2005
25 April – 27 May 2005
June
First Meeting
6 September, full-time: 2pm, part-time: 6pm, Malet St. building.
Part-time 2 start on the first Tuesday of term, 5 October.
1.6
Programme Aims and Objectives
The entry requirement is a 2.1 or above from an established UK university or an
equivalent qualification. A candidate’s first degree should normally be in a
quantitative discipline such as physics, engineering, statistics or mathematics.
Students who have completed highly quantitative economics degrees will also be
eligible. Substantial relevant work experience may also be taken in to account.
Students who complete the programme will be:
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MSc Financial Engineering: General Programme Information

trained in applicable areas of finance and in quantitative methods, as well as in
specialist areas that fit their interests;

competent in the fields of pricing and risk management as practiced by financial
institutions;

able to read and provide a critical interpretation of the scientific literature in
finance;

able to formulate propositions, test them using quantitative techniques and report
the conclusions;

able to conduct an independent research project and report on it;

able to become professional specialists in finance for industry, the financial
sector, the public sector or higher education;

familiar with research at the frontier of the subject and be able (should they wish
to do so) to undertake independent research for a PhD.
1.7
Programme Structure
Throughout, the material is approached in a rigorous fashion. Having completed the
programme, students have a solid grasp of a broad sweep of advanced applicable
finance and are ready to work as quantitative analysts in financial markets or to study
for a doctorate. Lectures are held between 6 and 9 in the evening. In addition to
lectures, some courses involve classes. These provide opportunities to review
material related to the lectures and to discuss solutions to problem sets. For full-time
students, classes are sometimes held in the afternoon. Classes for part-time students
are always in the evening.
The structure of the degree is as follows. Students complete four compulsory
courses, which are assessed through examinations in June. For some courses,
problem sets also count towards the final grade. Full-time (FT) students are normally
expected to complete the programme in one academic year, while part-time (PT)
students normally take two years. Following their successful completion of four
courses, students also complete a dissertation on a subject related to material
covered in the programme. This dissertation has the same weight as one course in
the final evaluation of a student’s performance.
Private study
Lectures and classes are only part of your overall learning experience. Private study
is equally important. You are expected to spend at least as long in private study reading material on the reading lists, working through problems and exercises,
writing essays, completing other assignments, revising for examinations - as you
spend in lectures and classes. You must devote enough time each week to keeping
up with the programme.
1.8
Brief Descriptions of Courses
1. a) September Statistics
Full-time and Part-time 1
b) September Mathematics
Full-time
Prior to the start of the MSc programme, there are preliminary quantitative
techniques courses in September, at the end of which qualifying examinations are
held in each subject. Resits are not held. Full-time students with very strong
mathematical backgrounds may apply to omit the mathematics preliminary course.
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MSc Financial Engineering: General Programme Information
c) September Introduction to Finance
Full-Time and Part-time 1
This course is intended for students who have not had an academic background in
Finance.
2. Mathematical Methods
a) Stochastic Processes for Finance
After an introduction to Matlab, the course will treat the basic stochastic calculus
needed for modern finance: Brownian motion, Ito calculus, filtrations and martingales,
culminating in the Feynman-Kac theorem. Simple Matlab exercises will be used to
illustrate the material numerically, where appropriate.
b) Theoretical Numerical Methods for Finance
The course will provide rigorous analysis of the numerical methods required to solve
parabolic differential equations of the Black-Scholes style, including a treatment of
the Cox-Ross-Rubinstein binomial method.
Some more general numerical methods will also be treated briefly, including (i) Monte
Carlo simulation and its algorithmic efficiency, (ii) numerical methods for solving
nonlinear equations and some basic optimization techniques, and (iii) more general
numerical methods, such as data fitting.
3. Financial Econometrics
This course develops students’ theoretical and practical grasp of important statistical
and econometric techniques commonly applied in analysing financial data. The first
part of the course consists of foundational material on regression analysis and
estimation techniques such as Maximum Likelihood and Generalised Least Squares.
The second part consists of more advanced topics and modelling approaches used
specifically in financial applications.
The course is assessed through a three-hour examination in June.
4. Pricing
This course covers continuous time price theory. It comprises two modules. The first
provides a basic treatment of non-measure-theoretic pricing theory applied to
financial options, default-free bonds and defaultable debt. The second introduces
students to matingale theory techniques (Girsanov’s theorem and representation
theorems) and then shows them how to price derivative securities using martingale
methods in an arbitrage-free market setting. Changing numeraire techniques will also
be covered in connection with option pricing in both defaultable and non-defaultable
term structure models (HJM and LIBOR). Applicaions to interest rate and credit
derivatives will be given.
The two modules are assessed via coursework and a three-hour examination in
June.
5. Risk Management
This course introduces students to the modern theory of risk management as
practiced by banks and other financial institutions. The first part of the course covers
risk measures such as Value at Risk based on loss distribution tails. Modelsused to
analyse market, credit and operational risk in bank portfolios are examined. The
second section of the course deals with risk management techniques employed by
investment funds. Topics covered include capital asset pricing models, asset
allocation and performance assessment.
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MSc Financial Engineering: General Programme Information
The course is assessed through a three-hour examination in June and a take-home
problem set in the Easter vacation.
6. Dissertation
After the June examinations, students complete a project under the supervision of a
faculty member. The project offers students an opportunity to pursue a topic of their
own choosing and to apply in a practical way the knowledge they have acquired in
the courses. All students are required to submit a dissertation by the last Friday of
August of their last year of study.
Full-time students
Full-time students do September Statistics and Mathematics, with qualifying exams in
each at the end of September. They then take five units –Mathematical Methods,
Financial Econometrics, Pricing, Risk Management and the dissertation - in one year.
Part-time students
First-year part-time students do September Statistics, with a qualifying exam at the
end of September. They then take Mathematical Methods and Financial
Econometrics. Second-year part-time students Pricing and Risk Management, and
produce the dissertation.
1.9
Allocation of Marks
The marking scheme for the course units is as follows:
Mathematical Methods
80% June exam + 20% for coursework
Financial Econometrics
June exam
Pricing
80% June exam + 20% for coursework
Risk Management
80% June exam + 20% for coursework
Dissertation
Coursework
1.10 A Brief Guide to the Marking System
For each course unit, the following classification applies:
The final degree classification is made from the five course units. The mark for each
unit is interpreted as follows:
 70
Distinction
60 - 69
Merit
50 - 59
Pass
49
Marginal Pass
< 49
Fail
Students who receive a Distinction for at least three course units (and no less than a
Merit in the other two) are awarded an overall mark of Distinction. Students who
receive a Merit for at least four units (and no less than a Pass in the other) receive a
Merit overall. Students who receive a Pass for at least four units (and no less than a
Marginal Pass in the other), receive a Pass overall.
Candidates who fail any one of the courses are allowed one resit for each course that
they fail, which will normally be taken the following June. You cannot resit in order to
improve a pass mark.
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MSc Financial Engineering: General Programme Information
The earliest you can take a resit is the next academic year. When you resit a course,
the Examiners may permit you to carry over the mark for the coursework component.
However, you are advised to do the coursework even if you do not submit it for
evaluation. Also, when resitting the examination, it is your responsibility to keep track
of any alterations in the syllabus.
(Fuller details of the marking scheme are given in the Assessment of Course and
Award of Degrees Booklet.)
1.11 Results
The examination scripts are marked by two internal examiners and then a large
selection of scripts are sent to our external examiners. All this takes time. The
Examiners' Meeting usually takes place towards the end of the first week of July, and
letters are sent to students indicating how well they have performed. At this stage,
the School gives an indication to the broad degree classification, that is Distinction,
Merit, Pass or Fail, dependent on successful completion of the dissertation.
University Regulations do not allow us to tell you the marks, or even give any
indication of them. The marks are notified routinely by the University in
October/November.
6
MSc Financial Engineering Course Units
2 MSc Financial Engineering Course Units
2.1
September Statistics
FT and PT1
Lecturer: Ali Tasiran
Course Objectives
This course is intended to provide the necessary statistical background for the
Financial Econometrics course. At the beginning, it covers basic facts about random
variables and their distributions. It then provides an introduction to statistical
inference.
At the end of the course a qualifying examination is held. You are required to pass
this examination to continue on the MSc programme. No resits are held
Textbook
D. Wackerly, W. Mendenhall and R. Scheaffer, Mathematical Statistics with
Applications, 5th edition, Duxbury Press, 1996. ISBN 0-534-20916-5.
Outline of Topics
Probability and Distribution Theory

Random variables

Moments of a random variable

Some specific probability distributions

The distribution of a function of a random variable

Joint distributions

Conditioning in a bivariate distribution

The bivariate normal distribution

Multivariate distributions
Statistical Inference

Samples and sampling distributions

Point estimation of parameters

Interval estimation

Hypothesis testing
7
MSc Financial Engineering Course Units
2.2
September Mathematics
FT
Lecturers: Arup Daripa and Sandeep Kapur
Course Objectives
This is an introductory course in mathematical techniques which are needed for the
courses of the MSc. It involves revision of material that you should have covered as
part of your earlier training in economics and finance. While we start with the basics,
the material covers some advanced topics.
At the end of the course a qualifying examination is held. You are required to pass
this examination to continue on the MSc programme. No resits are held.
Outline of Topics

Introductory calculus and basic linear algebra

Linear algebra, and something on sets

Advanced calculus and introduction to optimisation

Optimisation
Recommended Texts

Hoy, M et al., Mathematics for Economics, Addison-Wesley, 1996.

A. C. Chiang, Fundamental Methods of Mathematical Economics, 3rd edition,
McGraw-Hill.
Pre-Course Reading
If you think you need to prepare for the course over the summer, use the above text
(or indeed one that you have already used) to revise:

basic calculus: differentiation and integration (functions of one variable);

basic matrix operations: matrix addition, multiplication, determinants.
8
MSc Financial Engineering Course Units
2.3
September Introduction to Finance
FT and PT1
September
Lecturer: Stephen Wright
Aims
This short optional course of three lectures is intended to give a broad brush outline
of the key ideas in finance. It is aimed at students coming on to the MSc programmes
with little or no prior training in finance or economics.
Objectives
By the end of the course, students should be familiar with the following key concepts
and their applications in finance.

No arbitrage pricing conditions, in particular as applied to bond and option prices

Risk-return tradeoffs and the Capital Asset Pricing Model

Inter-temporal choice as a basis for asset pricing.
Teaching Arrangements
The course is taught over 3 weeks. There is a double lecture on Wednesday
evenings starting 8 September. Some lectures will involve a degree of student
interaction in problem solving to test understanding of core ideas.
Course Assessment
Since the course is optional it is not examined formally.
Textbooks
There is no set text, and no required reading. Handouts will be provided that cover
key ideas. Those wishing for additional background on some topics may also find the
following texts useful (but not essential):

Copeland, Thomas E & JF Weston, Financial Theory and Corporate Policy,
Addison Wesley

Hull J, Options, Futures and Other Derivative Securities, Prentice-Hall

Cochrane, J, Asset Pricing
9
MSc Financial Engineering Course Units
2.4
Mathematical Methods
FT and PT1
Autumn and Spring Terms
Lecturers: Raymond Brummelhuis and Brad Baxter
Aims

To introduce the student to the main mathematical and numerical techniques
used in present-day quantitative finance. The course is divided into three submodules and illustrated by examples drawn from this subject area.

To become acquainted with suitable languages and computer packages for
financial applications (C++ and Matlab).
a) Stochastic Processes for Finance
Objectives

To understand the basic concepts of stochastic calculus, in particular Brownian
motion and stochastic integrals.

To understand Ito calculus and its applications to stochastic differential equations
(SDEs).

To understand the numerical solution of an SDE.

To appreciate the connections between probability theory and partial differential
equations via the Feynman-Kac formula.
b) Theoretical Numerical Methods for Finance
Objectives

To obtain basic fluency in Matlab.

To solve SDEs using Monte Carlo simulation.

To understand the fundamental algorithms for the numerical solution of parabolic
partial differential equations (PDEs).

To understand the binomial method for option pricing as a finite difference
method, particularly its disadvantages.

To appreciate the importance of stability in numerical algorithms for PDEs.

To understand numerical methods for the solution of nonlinear equations and
some basic optimization techniques.

To know the basics of more general relevant numerical methods, such as data
fitting.

To illustrate the above by examples and exercises in Matlab.
c) Programming in C++
Objectives

To understand the language fundamentals of C and C++.

To know the basic use of arrays, dynamic memory allocation and data
input/output.
10
MSc Financial Engineering Course Units

To understand and construct classes, illustrated by classes for complex numbers
and matrix algebra.

To use numerical libraries.
Teaching Arrangements
The course is taught over 20 weeks, divided into two terms. There are extra tutorial
sessions (approximately 12 hours) for Matlab and C++.
Course Assessment
The material presented in 2.4 (a) and 2.4 (b) will be assessed via coursework (20%)
and a three-hour examination in June (80%). Students will be strongly encouraged to
apply their knowledge of C++ in their final-year dissertation.
Textbooks
The courses will be based on fairly extensive lecture notes. Detailed reading lists will
be provided during term.
11
MSc Financial Engineering Course Units
2.5
Financial Econometrics
FT and PT1
Autumn and Spring Terms
Lecturers: Zacharias Psaradakis and Martin Sola
Aims
The course provides an introduction to the modern econometric techniques used in
the analysis of financial time series. The interaction between theory and econometric
analysis is emphasised, and students will be trained in formulating and testing
financial models.
Objectives
At the end of the course, students will be able to demonstrate that they can:

derive standard estimators (OLS, GLS, GIVE, ML, GMM) and establish their
finite-sample and asymptotic properties;

develop exact and/or asymptotic specification and misspecification tests;

develop and analyse models for stationary univariate and multivariate time series;

develop and analyse models for nonstationary and long-memory time series;

develop and analyse nonlinear time-series models;

understand and explain empirical articles in the literature of the sort that appear in
the main economics and finance journals.
Topics









Least squares theory
Maximum likelihood theory
Hypothesis testing and model evaluation
Instrumental variables and GMM
Univariate time-series models
Multivariate time-series models
Nonstationary time series and cointegration
Switching models
Applications
Teaching Arrangements
The course is taught over 20 weeks. There is a double lecture a week and one class.
Course Assessment
The final grade is determined through a three-hour exam in June.
Recommended Textbooks
W. H. Greene, Econometric Analysis, 4th edition, Prentice-Hall, London, 2000.
J. D. Hamilton, Time Series Analysis, Princeton University Press, 1994.
12
MSc Financial Engineering Course Units
2.6
Pricing
FT and PT2
Autumn and Spring Terms
Lecturers: Alvaro Cartea and Raymond Brummelhuis
Aims
To understand and be able to implement contingent claim and bond pricing by a
variety of methods: binomial, PDE and martingale pricing methods.
Objectives

To develop problem-solving abilities to value derivative securities.

To become acquainted with standard derivative and bond pricing models.

To understand equivalent martingale measures and their role in pricing.

To understand the concepts of complete and incomplete markets.

To understand techniques based on change of numeraire.

To apply martingale pricing to a variety of contexts: option pricing and term
structure models (defaultable and non-defaultable).
Teaching Arrangements
The course is taught over 20 weeks, divided into two terms.
Course Assessment
The material will be assessed via coursework (20%) and a three-hour examination in
June (80%).
Textbooks
The courses will be based on fairly extensive lecture notes. Detailed reading lists will
be provided during term.
13
MSc Financial Engineering Course Units
2.7
Risk Management
FT and PT2
Autumn and Spring Terms
Lecturers: Simon Hubbert, Steve Satchell and John Knight
Aims
The course provides an introduction to modern risk management theory and practice.
Students will develop problem-solving skills in risk management applications and
become conversant with up-to-date techniques employed by financial institutions.
Objectives

To develop knowledge of statistical techniques applicable to measuring risk in
portfolios.

To learn how to apply these techniques in practice.

To become acquainted with standard risk models and to have a thorough critical
understanding of the strengths and weaknesses of these models.
Topics













Loss distribution risk measures such as VaR and TVaR
Market risk modelling
VaR with derivative portfolios
Extreme Value Theory techniques applied to VaR measurement
Credit risk modelling
Copula techniques
Models for operational risk
The Basel proposals for bank capital requirements
Capital Asset Pricing
Arbitrage Pricing Theory
Strategic Asset Allocation
Tactical asset allocation
Performance measurement
Teaching Arrangements
The course is taught over 20 weeks. There is a double lecture a week. Problem sets
will be distributed and reviewed in the lectures.
Course Assessment
The final grade is determined through a three-hour exam in June and a take-home
exercise in the Easter vacation.
Textbooks
Lecture notes will be distributed.
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MSc Financial Engineering Course Units
2.8
Dissertation
FT and PT2
Summer term
Supervisors: members of the School
Aims
The summer projects provide students with the opportunity to apply the techniques
and knowledge they have acquired from the rest of the programme. The dissertation
should provide an in depth analysis of a specific financial issue. Students either
perform a statistical or numerical analysis or, less commonly, examine a question
using a theoretical model.
Objectives
Students should:

show that they have a good knowledge of the relevant literature on their chosen
topic;

identify an interesting question associated with that topic and analyse this
question either in a new way or with new data;

demonstrate they have a good grasp of techniques (statistical, numerical or
theoretical) relevant for analysing the question;

show they can exposit the results of their analysis in a clear and convincing
manner.
Teaching Arrangements
Supervision by member of the School is provided for work on the dissertation from
the end of the examinations in June to the end of August. Students should plan to
see their supervisors several times during this period.
Course Assessment
The dissertations are marked in September.
Guidance Notes for MSc Financial Engineering Dissertations
Students should prepare a single-page proposal that they should hand in on or
before the first day of the summer term. This proposal should state succinctly the
basic idea of the project, what data and computing facilities will be required and
whether or not these are known to be available. The School will allocate a supervisor
to each student within a few days. The project (which has a word limit of 8000 words)
must be completed by the last Friday in August.
Students are strongly advised to keep in touch with their supervisor while working on
the project. An initial meeting to obtain advice on data, techniques and overall
direction is essential. In addition, students should see their supervisor two or three
times in the course of the research to discuss results and receive further guidance.
As a general rule, it is very important that the project contain an interesting question
or issue to be analysed. Simply applying a well-known statistical technique to a new
dataset will not generally earn a good mark. Any subject that relates to material
covered in the course is admissible, but it is generally sensible to stick to projects
15
MSc Financial Engineering Course Units
which contain some substantial element of statistical or numerical analysis.
Theoretical projects are difficult although occasionally students have produced good
work of this type. Purely institutional topics are not permitted.
On data, it is important not to be too ambitious. Often students spend inordinate
amounts of time collecting large datasets and then find they have no time to perform
analysis. Interesting analysis motivated by some genuine, substantive question earns
high marks. Whatever is done, it is important that students time their work
realistically. Going away on holiday and expecting to be able to complete in the last
fortnight before the deadline is a recipe for trouble. If you are unfamiliar with
econometric packages (as most of you will be) then everything takes longer than you
expect.
A good source of financial data is Datastream, which can be accessed using a
computer in the Library. The principal databases cover equities, bonds, company
accounts, economic series, international market indices, interest and exchange rates
and financial and commodity futures and traded options.
16
Teaching and Assessment
3 Teaching and Assessment
3.1
Course Assessment
For most course units, you will do coursework and sit exams (further information on
written exams is found below and in the relevant Assessment Handbook). The
relative weights of these components toward your mark for the course unit will vary
from unit to unit and you will be given this information on the individual unit
syllabus/reading list. You should also take care to note the deadlines for submission
of coursework and realise that there are penalties for late submission.
There are several types of coursework that you will be asked to produce in your
degree. The particular type of coursework assignments will vary from unit to unit, so
you will need to pay close attention to the instructions given by the lecturer. Some
examples of the types of coursework assignments that you will be expected to
produce are given below.
Essays
You may be asked to write brief essays on particular questions. The marking criteria
are given in the Assessment Handbook.
Problem Solving
Technical course units are likely to give exercises to test your ability to use concepts
and techniques.
Mid-Term Tests
These may be provided by lecturers where necessary.
3.2
Feedback on Coursework
Coursework can constitute a significant proportion of the expected workload for a
course unit. If coursework is an integral part of the examination for a unit, this means
that it is absolutely NOT optional. You MUST attempt all coursework for a course
unit, otherwise you will obtain zero for the coursework.
It will always be requested that you submit coursework on or before a certain
deadline. This deadline is an integral part of the assignment rather than an arbitrary
date conjured to annoy and/or penalise students. This rationalisation notwithstanding,
we do attach penalties for breaking submission deadlines as late submission of work
disrupts the marking and feedback procedures and can confer an unfair advantage
on students who delay submitting work.
For each piece of marked coursework, the lecturer will be the first marker and a
second member of staff will act as moderator of the marks, to ensure that they have
been of the correct standard. The mark will be provisional since it will only finally be
confirmed by the Degree Board.
Coursework will be returned with comments and your provisional mark. In some
cases, individual lecturers may offer additional feedback devices: for example, a
general commentary addressed to the entire class, or an additional form that
addresses a specific assignment directly.
17
Teaching and Assessment
3.3
Examination Regulations
When you start the course, you will be issued with an Assessment Handbook
outlining the principal University of London Examination Regulations and Procedures.
It is important to note requirements on entry and withdrawal from examinations.
Students are deemed to have failed an examination if they do not notify the
appropriate authorities of their withdrawal.
3.4
Examination Registration
The registration process for the June examinations is controlled by the University
Examinations Office and it is your responsibility to ensure that things go right. During
the Spring Term, the College Registry sends entry forms to all degree students at
their home address. If you do not receive an entry form (and other students have got
theirs') you should contact the Examinations Office. You must fill these in promptly
and as accurately as possible. Once you have made your entry, some flexibility
exists for subsequent alteration, but given the administrative difficulty of making such
changes, try not to.
The examination entry tickets are sent to the candidates between April and May.
These contain your examination number and the examination dates etc. Check it
immediately to make sure that you have been entered for the right examination.
3.5
Examination Deferment
Permission to defer the examination or any part of the examination, including
submission of an essay, project, dissertation or other written work, may only be
granted for reasons judged adequate in the particular case at the discretion of the
College.
Application for permission to defer examination(s) shall be made in the case of
summer examinations at least 14 days in advance of the first examination or by 1
May whichever is the earlier, or in the case of September examinations by 1 August.
Application must be made in writing to the Programme Director of the programme for
the degree or diploma for which the student is registered. The Programme Director
shall exercise on behalf of the College the discretion to grant or refuse such
applications and may consult as necessary before doing so and may require the
submission of documentary evidence in support of the application.
In cases where permission is granted to defer the examination until the following
year the relevant examination entries shall be designated as ‘withdrawn’ and the
candidate will be required to submit entries for the examination(s) on an examination
entry form in the following year. All other candidates will be regarded as having made
an entry or re-entry, except that in the case of illness or other adequate cause for
which certification must be provided a candidate may be permitted at the discretion of
the College to withdraw his/her entry to the examination in the week before the
commencement of the examination and up to and including the date of his/her first
paper provided that (s)he has not entered the examination hall. Candidates who do
not attend an examination or who do not submit written work without being granted
permission to defer or withdraw their examination entry shall be deemed to have
failed the examination on that occasion.
Deferment is not a right, and each case is judged on its merit. The earliest you can
resit the examination is the next summer. Note also that deferment is not a very
sensible option - the courses change slightly from one year to the next, if only in
emphasis on particular topics, and students who defer may end up being at a slight
disadvantage. Do not consider this route unless you have to.
18
Teaching and Assessment
3.6
Policy on Plagiarism

You are reminded that all work submitted as part of the requirements for any
course must be expressed in your own words and incorporate your own ideas
and judgements.

Plagiarism – that is, the presentation of another person’s thoughts or words as
though they were your own – must be avoided, particularly in coursework essays
and reports written in your own time.

Direct quotations from published and unpublished work or from web sites must
always be identified as such by being placed inside quotation marks, and a full
reference to the source must be provided in the proper form.

Remember that a series of short quotations from several different sources, if not
clearly identified as such, constitutes plagiarism just as much as does a single
unacknowledged quotation from a single source.

If you summarise another person’s ideas or judgements, you must refer to that
person in the text and include the work referred to in your bibliography.

Failure to observe these rules may result in an allegation of cheating.

Copying another student’s work is also a form of plagiarism.

You must consult your tutor or course co-ordinator if you in doubt over what is
permissible.
Remember, the marker of your assignment requires evidence of your understanding
and effort. Borrowed material that is unacknowledged attracts no marks.
Unacknowledged copying of text and/or ideas is called plagiarism, and YOU MUST
NOT PLAGIARISE.
You must ensure that all work you submit is entirely your own, unless you
declare otherwise. Plagiarism will incur severe penalties, which may include
exclusion from your degree programme!
There are two situations in which plagiarism commonly occurs:

Fraud. This applies when a student submits the written work of another person
(who might be a fellow student), in whole or part, as his/her own. Such fraud may
occur with or without the author’s consent, but having obtained the author’s
consent does not excuse the crime! Deception of this kind devalues the
coursework of the perpetrator and is grossly unfair to his/her peers. Markers find
this easy to spot as they keep some record of the coursework of past and present
students.

Pirated text. This refers to copying (sometimes word for word) from a publication.
Pirated text is not difficult to detect, for even if the marker does not know the
source of the text (but often he/she will), the style of the plagiarised text betrays
the fraud. The cohesiveness of argument, the structure of the text (formal
scientific writing has a form seldom found in student essays) and English usage
differ substantially from the usual output of the plagiariser.
Group work is an area where students may be unsure, justifiably, about whether
their submitted work constitutes plagiarism. The key to dealing with group work is to
ensure that your coursework assignment has a content that is distinctively your own.
For example, if you are collecting and commenting on data, even where the data are
the same, your work will have different introductory sections, different tabular or
graphic presentation and different discussion. Such elements must be your own effort
and not be copied from others.
19
Teaching and Assessment
Recourse to the services of “ghost-writing” agencies (for example in the preparation
of essays or reports) or of outside word-processing agencies which offer
“correction/improvement of English” is strictly forbidden, and students who make use
of the services of such agencies render themselves liable for an academic penalty.
20
Provisional Timetables
4 Provisional Timetables
4.1
September Statistics, Mathematics & Introduction to Finance
The September quantitative courses begin with lectures on Monday 6 September,
three days per week for three weeks. Full-time students attend mathematics during
the afternoon and statistics in the evening. Part-time students (Year 1) take statistics
in the evening.
There are also three Introduction to Finance lectures on Wednesdays, starting 8
November. These are for students who have not had an academic background in
Finance.
Revision classes:
Monday 27 September
Examinations:
Mathematics
Wednesday 29 September, 6-8 pm
Statistics
Thursday 30 September, 6-8 pm
Room locations will be posted in the reception.
Monday
Tuesday
Wednesday
Full-time only
Full-time only
Full-time only
2-4.30pm
2-4.30pm
3.30-5pm
Mathematics
Mathematics
Mathematics
Full-time and
Year 1
Full-time and
Year 1
Full-time and
Year 1
Full-time and
Year 1
6-8pm
6-8pm
6-8pm
6-8pm
Statistics
Statistics
Introduction to
Finance
Statistics
21
Thursday
Provisional Timetables
4.2
MSc Financial Engineering Full-time AUTUMN TERM
4 October - 17 December 2004
Reading week: 8-12 November
L: Lecture
C: Class
Monday
Tuesday
Wednesday
Thurs
Friday
3-4 pm
Financial
Econometrics
C: K Ait Chabane
Starts week 2
Room
6-7.30pm
6-7.30pm
6-7.30pm
6-7.30pm
6-7pm
Mathematical
Methods
Pricing
Financial
Econometrics
Risk
Management
Pricing
L: R Brummelhuis
L: Z Psaradakis
L: S Hubbert
(weeks 1-8)
Room
(weeks 1-7)
(Starts week
2)
L: B Baxter
L: S Satchell
Room
(weeks 9-11)
(weeks 8-11)
Room
Room
L: A Cartea
Room
7.30-9pm
7.30-9pm
7.30-9pm
7.30-9pm
Mathematical
Methods
Pricing
Financial
Econometrics
Risk
Management
L: Z Psaradakis
L: S Hubbert
Room
(weeks 1-7)
L: A Cartea
L: R Brummelhuis
(weeks 1-8)
Room
L: B Baxter
L: S Satchell
(weeks 9-11)
(weeks 8-11)
Room
Room
22
C: M Figuera
Provisional Timetables
4.3
MSc Financial Engineering Full-time SPRING TERM
10 January - 18 March 2005
L: Lecture
Monday
C: Class
Tuesday
Wednesday
Thursday
Friday
3-4pm
Financial
Econometrics
C: K Ait Chabane
(Starts week 2)
Room
6-7.30pm
6-7.30pm
Mathematical Pricing
Methods
L: R Brummelhuis
L: B Baxter
Room
6-7.30pm
6-7.30pm
6-7pm
Financial
Econometrics
Risk Management
Pricing
L: J Knight
C: M Figuera
(weeks 1-7)
(Starts week 2)
L: S Satchell
Room
L: M Sola
Room
Room
(weeks 8-10)
Room
7.30-9pm
7.30-9pm
Mathematical Pricing
Methods
L: R Brummelhuis
L: B Baxter
Room
7.30-9pm
7.30-9pm
Financial
Econometrics
Risk Management
L: M Sola
Room
Room
L: J Knight
(weeks 1-7)
L: S Satchell
(weeks 8-10)
Room
23
Provisional Timetables
4.4
MSc Financial Engineering Part-time Year 1 AUTUMN TERM
4 October - 17 December 2004
Reading week: 8-12 November
L: Lecture
C: Class
Monday
Tuesday
Wednesday
Thursday
6-7.30pm
6-7.30pm
6-7.30pm
Mathematical
Methods
Financial
Econometrics
Financial
Econometrics
L: R Brummelhuis
L: Z Psaradakis
C: K Ait Chabane
(weeks 1-8)
Room
(Starts week 2)
L: B Baxter
Room
(weeks 9-11)
Room
7.30-9pm
7.30-9pm
Mathematical
Methods
Financial
Econometrics
L: R Brummelhuis
L: Z Psaradakis
(weeks 1-8)
Room
L: B Baxter
(weeks 9-11)
Room
24
Friday
Provisional Timetables
4.5
MSc Financial Engineering Part-time Year 1 SPRING TERM
10 January - 18 March 2005
L: Lecture
Monday
C: Class
Tuesday
Wednesday
Thursday
6-7.30pm
6-7.30pm
6-7.30pm
Mathematical
Methods
Financial
Econometrics
Financial
Econometrics
L: B Baxter
L: Z Psaradakis
C: K Ait
Chabane
Room
(Starts week 2)
Room
Room
7.30-9pm
7.30-9pm
Mathematical
Methods
Financial
Econometrics
L: B Baxter
L: Z Psaradakis
Room
Room
25
Friday
Provisional Timetables
4.6
MSc Financial Engineering Part-time Year 2 AUTUMN TERM
4 October - 17 December 2004
Reading week: 8-12 November
L: Lecture
Monday
C: Class
Tuesday
Wednesday
Thursday
Friday
6-7.30pm
6-7.30pm
6-7pm
Pricing
Risk Management
Pricing
L: A Cartea
L: S Hubbert
C: M Figuera
(weeks 1-7)
(Starts week 2)
L: S Satchell
Room
Room
(weeks 8-11)
Room
7.30-9pm
7.30-9pm
Pricing
Risk Management
L: A Cartea
L: S Hubbert
(weeks 1-7)
Room
L: S Satchell
(weeks 8-11)
Room
26
4.7
MSc Financial Engineering Part-time Year 2 SPRING TERM
10 January - 18 March 2005
L: Lecture C: Class
Monday
Tuesday
Wed
Thursday
Friday
6-7.30pm
6-7.30pm
6-7pm
Pricing
Risk Management
Pricing
L: R Brummelhuis
L: J Knight
C: M Figuera
(weeks 1-7)
(Starts week 2)
L: S Satchell
Room
Room
(weeks 8-10)
Room
7.30-9pm
7.30-9pm
Pricing
Risk Management
L: R Brummelhuis
L: J Knight
(weeks 1-7)
Room
L: S Satchell
(weeks 8-10)
Room
27