current students
Teaching @ CCFEA
MSc in Computational Finance
Aims and objectives of the scheme
The MSc aims to equip students with the core concepts and mathematical principles of modern quantitative
finance along with the operational skills to use computational packages (mainly Matlab) for financial
modelling. In addition to traditional topics in derivatives and asset pricing, there will be special emphasis
on risk management in non-Gaussian environment with extreme events. Further, the student has the opportunity to
study methods of non-linear and evolutionary computational methods for derivatives pricing and portfolio
management. The use of artificial financial market environments for stress testing, design of auctions and
other financial contracts will also be covered.
Duration of the scheme
The MSc is a 12 month programme with a project in the summer that is oriented toward the computational
implementation of financial models. The MSc consists of 185/190 credits with each 10-week lecture module
constituting 15 credits (unless otherwise stated).
Target students
Students should have a good 2.1 or First class first degree, with a quantitative background such as in
Physics, Computer Science, Mathematics, Statistics or mathematical Economics/Finance. However, no finance or
computing background is assumed.
Our expertise and reputation
Computational Finance at University of Essex has established its international reputation as a centre that
closely integrates finance and computing. A search on "Computational Finance + UK" in Google and
many Internet search engines will find us amongst the top two entries. The recent high quality workshops and
international conferences hosted by CCFEA give a good measure of our national and international standing.
The market
The CCFEA MSc can be viewed as a high powered degree scheme combining computing and finance. The MSc will be
a unique experience for students in that it will be run at a multi-disciplinary centre where students will get
exposure to cutting edge research, seminars and workshops. CCFEA students have gained sought after City internships.
The course modules
The MSc consists of 185/190 credits. There are 8 taught course modules of which
6 are compulsory and 2 are
optional and a MSc project in the summer oriented toward the computational implementation of financial models.
Compulsory modules
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BE351
Derivatives Securities
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CE885
Mathematical Research Techniques using Matlab
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CF961
Introduction to Financial Market Analysis or
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CF962
Quantitative Finance and Market Analysis
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CF963
Learning and Computational Intelligence in
Economics and Finance
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CF966
Financial Engineering and Risk Management
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CF968
Industry Expert Lectures in Finance
Optional modules
Two optional modules to be taken from the following (the lists are not exhaustive):
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BE352 Asset Pricing
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BE354 Portfolio Management
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BE356 Financial Modelling
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BE953 Research Methods in Finance: Empirical Methods in Finance
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BE954 Research Methods in Finance: Foundations in Finance
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CE802 Machine Learning and Data Mining
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CE804 Digital Signal Processing
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CE883 Heuristic and Evolutionary Computation
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CE884 Constraint Satisfaction for Decision Making
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CF964 Introduction to Java and Agent Based Economic Platforms
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CF965 High Frequency Finance and Empirical Market-Micro Structure
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CF967 Agent Based Economics and Financial Market Modelling
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EC907 Economics of Financial Markets
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EC965 Time Series Econometrics
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EC967 Empirical Methods of Economics and Finance
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MA311 Mathematics of Potfolios
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MA333 Mathematical Biology
Note: some of these CE optional modules require previous experience and students should refer to the
University's online module directory for full module descriptions.
Further information
Applying