ObjectivesThis innovative programme is offered by Nottingham University Business School and the School of Computer Science. It is designed to develop the combination of computational and financial skills now demanded by most careers in finance. The programme aims to develop analysts capable of designing and writing high quality computer code for finance applications. This course encourages the development and combination of quantitative and programming skills to support the solution of problems in financial analysis, financial management, and the pricing of financial instruments. Modules in financial reporting and corporate finance provide key concepts and background in semester 1. These are accompanied by modules which develop advanced quantitative methods relevant to finance and also the programming skills necessary for the implementation of these methods. Semester 2 modules provide further technical development in the area of Artificial Intelligence and Intelligent Systems, as well as dealing with the major groups of financial instruments: equity, debt and derivatives. The degree mixes modules which are offered across a range of Masters degrees in each School with others developed exclusively for this programme. These tailored modules include Quantitative Methods for Finance, Computational Methods for Finance, and Artificial Intelligence Applications in Finance. The programme concludes with a supervised project, which will be jointly supervised by the two participating schools and will emphasise the computational solution of a significant real world problem.
Entry requirementsTo apply you must have a good degree in a quantitative subject. Students without an accounting or finance based first degree are encouraged to apply. All accepted applicants will be advised about pre-course reading and given the opportunity to attend top-up lectures in accounting and finance during the programme induction process
Academic titleMSc Computational Finance
Course descriptionKey facts
-The Business School is a leading UK centre for management education, and is ranked seventh in the UK in the 2007 Times Good University Guide.
-We regularly review and update our MSc programmes to ensure that their content is relevant to the changing global business environment
Course Content
Modules in financial reporting and corporate finance provide key concepts and background in semester one. These are accompanied by modules which develop advanced quantitative methods relevant to finance and also the programming skills necessary for the implementation of these methods.
Semester two modules provide further technical development in the area of Artificial Intelligence and Intelligent Systems, as well as dealing with the major groups of financial instruments: equity, debt and derivatives.
You will study the following core modules in order to develop your knowledge and skills relating to Computational Finance:
-Quantitative Methods for Finance
-Introduction to Computer Programming
-Foundations of Artificial Intelligence
-Computational Programming Methods for Finance
-Financial Reporting
-Corporate Financial Strategy
-In addition, you will be able to choose from a broad range of elective modules:
One from:
-Artificial Intelligence Applications in Finance
-New module offered by Computer Sciences
Please note that all module details are subject to change.
Over the summer period towards the end of the course, you will undertake a 60-credit supervised dissertation on a subject of your choice relating to Computational Finance – this is an opportunity to concentrate in depth on an international topic according to your individual interests and career requirements.
You will have two project supervisors – one from each School – to ensure that the project emphasises the computational solution of a significant real world problem.
Course Structure
The MSc in Computational Finance is taught on a full-time basis over one year.
During this time, you must accumulate 180 credits to qualify for the award of MSc.
120 credits come from modules taught and examined during two 15 week semesters.
Each taught module typically consists of ten 2 or 3 hour sessions. Assessment is a combination of individual essay or group project and written examination.
The remaining 60 credits of this course are allocated to an independent dissertation/project which is completed over the summer period for submission in September.