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.
We provide practical, hands-on learning about how modern, highly computerised financial markets work, how assets should be priced, and how investors should construct a portfolio of assets. In addition to traditional topics in derivatives and asset pricing, we place a special emphasis on risk management in non-Gaussian environment with extreme events.
You master these areas through studying topics including: -Non-linear and evolutionary computational methods for derivatives pricing and portfolio management -Applications of calculus and statistical methods -Computational intelligence in finance and economics -Financial markets
You also graduate with an understanding of the use of artificial financial market environments for stress testing, and the design of auctions and other financial contracts.
Our Centre for Computational Finance and Economic Agents is 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.
Our research is geared towards real-world, practical applications, and many of our academic staff have experience of applying their findings in industry and in advising the UK government.
This course is also available on a part-time basis.
This degree is accredited by the Institution of Engineering and Technology (IET).This accreditation is increasingly sought by employers, and provides the first stage towards eventual professional registration as a Chartered Engineer (CEng).
Our expert staff
This course is taught by experts with both academic and industrial expertise in the financial and IT sectors. We bring together leading academics in the field from our departments of economics, computer science and business.
Our staff are currently researching the development of real-time trading platforms, new financial econometric models for real-time data, the use of artificially intelligent agents in the study of risk and market-based institutions, operational aspects of financial markets, financial engineering, portfolio and risk management.
We are one of the largest and best resourced computer science and electronic engineering schools in the UK. Our work is supported by extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment. -We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress -All computers run either Windows 7 or are dual boot with Linux -Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project -Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET) -We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors
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.
Our recent graduates have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including: -HSBC -Mitsubishi UFJ Securities -Old Mutual -Bank of England
We also work with the university’s Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.
-CCFEA MSc Dissertation -Financial Engineering and Risk Management -Introduction to Financial Market Analysis -Learning and Computational Intelligence in Economics and Finance -Professional Practice and Research Methodology -Quantitative Methods in Finance and Trading -Big-Data for Computational Finance (optional) -Industry Expert Lectures in Finance (optional) -Mathematical Research Techniques Using Matlab (optional) -Programming in Python (optional) -Artificial Neural Networks (optional) -High Frequency Finance and Empirical Market Microstructure (optional) -Machine Learning and Data Mining (optional) -Trading Global Financial Markets (optional) -Creating and Growing a New Business Venture (optional) -Evolutionary Computation and Genetic Programming (optional) -Constraint Satisfaction for Decision Making (optional)