Postgraduate Prospectus

Computational Finance | www.essex.ac.uk/ccfea
Why study
computational
finance at Essex?
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Cross-disciplinary syllabus
incorporating the latest research
from agent-based modelling,
computational-intelligence in
finance, high frequency finance and
computational risk management
Practical hands-on instruction
across all our programmes
Strong emphasis on the skills
required by industry
Excellent links with industry
and government bodies
Approachable and friendly
lecturers, who are leaders in
their fields
Career prospects
Graduates of our Centre have
gone on to become quantitative
analysts, portfolio managers and
software engineers at various
institutions, including major
investment banks like HSBC
and Mitsubishi UFJ Securities.
We have an extensive network
of industrial contacts through our
City Associates Board and our
alumni, while our expert seminar
series gives you the opportunity
to work with leading figures from
industry. A number of our students
have held internships with
prestigious City institutions, such
as HSBC, Old Mutual and the Bank
of England.
About our Centre
We are an innovative and laboratory-based
teaching and research centre, with an
international reputation for leading-edge,
interdisciplinary work combining economic
and financial modelling with computational
implementation. We are supported by
Essex’s highly rated Department of
Economics, School of Computer Science
and Electronic Engineering, and Essex
Business School.
Our research falls into four
inter-related areas: agent-based
modelling of financial markets, the use
of computational-intelligence methods
for investment decision making,
high frequency finance, and computational
risk management. Our research is geared
towards practical applications, and many
of our academic staff have experience
of applying their findings both in industry
and in advising the UK government.
We place a strong emphasis on empirical
work and make use of high frequency
data both in our research and teaching.
High frequency data is defined as the full
real-time record of all trading activities and
their associated characteristics observed
in an electronic exchange system. These
financial ‘tick-by-tick’ data sets provide
deeper insights into the price formation
process at the micro-level and have been
widely used to study various (theoretical
and empirical) market microstructure
issues, such as price discovery, order
choice behaviour of market participants
and optimal order placement strategy.
We host advanced workshops and
seminars by experts in the area of
computational finance and economics,
so you have the opportunity to attend
lectures given by practitioners, including
senior staff from HSBC, Olsen Ltd, Royal
Bank of Scotland and the Financial
Services Authority.
Taught courses
If you are a high calibre and creative
student from a quantitative discipline (for
example, engineering, physics, computer
science, statistics, mathematics or
quantitative economics/finance), then you
will enjoy our intellectually challenging and
socially vibrant atmosphere. You receive
practical hands-on instruction, with a focus
on problem solving skills, that equips you
for high flying careers.
Our taught courses run for one year on
a full-time basis and consist of taught
modules for the first two semesters,
followed by a dissertation in the summer.
We ensure your study is highly practical
and involves both lectures and hands-on
laboratory sessions in which you have
the opportunity to analyse and model
real-world financial data.
Each of our taught courses is highly
cross-disciplinary and involves some
elements of programming, statistics and
mathematics, with the particular focus
depending on the course you choose.
However we do not assume that you
have prior formal training in finance or
economics, so run an optional pre-sessional
course that provides all your required
foundational material.
MSc Computational Finance•
Our MSc Computational Finance
equips you with the core concepts
and mathematical principles of modern
quantitative finance, plus the operational
skills to use computational packages
(mainly Matlab) for financial modelling.
In addition to traditional topics in
derivatives and asset pricing, we place
a special emphasis on risk management
in a non-Gaussian environment with
extreme events. You have the opportunity
to study methods of non-linear and
evolutionary computational methods
for derivatives pricing and portfolio
management. You graduate with an
understanding of the use of artificial
financial market environments for stress
testing, and the design of auctions and
other financial contracts.
MSc Financial Software Engineering•
This course allows you to attain a high
degree of competence in software
76 | Postgraduate Prospectus 2012