Comments about MSc Numerical Techniques for Finance - At the institution - Nottingham - Nottinghamshire
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Objectives
Scientific computing is a new and growing discipline in its own right. It is concerned with harnessing the power of modern computers to carry out calculations relevant to science and engineering. By its very nature, scientific computing is a fundamentally multidisciplinary subject. The various application areas give rise to mathematical models of the phenomena being studied. Examples range in scale from the behaviour of cells in biology, to flow and combustion processes in a jet engine, to the formation and development of galaxies. Mathematics is used to formulate and analyse numerical methods for solving the equations that come from these applications. Implementing the methods on modern, high performance computers requires good algorithm design to produce efficient and robust computer programs. Competence in scientific computing thus requires familiarity with a range of academic disciplines. The practitioner must, of course, be familiar with the application area of interest, but it is also necessary to understand something of the mathematics and computer science involved. Whether you are interested in fundamental science, or a technical career in business or industry, it is clear that having expertise in scientific computing would be a valuable, if not essential asset. The question is: how does one acquire such expertise? This course is one of a suite of new MScs in Scientific Computation that are genuinely multidisciplinary in nature. These new courses will be taught by internationally leading experts in various application areas and in the core areas of mathematics and computing science, fully reflecting the multidisciplinary nature of the subject. The courses have been carefully designed to be accessible to anyone with a good first degree in science or engineering. They are excellent preparation either for research in an area where computational techniques play a significant role, or for a career in business or industry
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Academic title
MSc Numerical Techniques for Finance
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Course description
Numerical Techniques for Finance (MSc)
Duration: 1 year full-time
Course Content
This course aims to help you develop your ability to think logically and critically, to acquire problem-solving skills, to become competent users of relevant software, and to communicate results effectively.
You will be required to take the following core modules:
Variational Methods
Computational Linear Algebra
Algorithm Design and Operational Research
Quantitative Methods for Finance
Corporate Financial Strategy
Derivative Investment
In addition, you will be able to choose a number of optional modules that place an emphasis on finance and include:
Stochastic Financial Modelling
Capital Market Analysis
Fixed Interest Investment
Quantitative Risk Management
Financial Econometrics
Please note that all module details are subject to change.
Over the summer period towards the end of the course, you will undertake a research project in Scientific Computation with specific emphasis on finance. This research will be of some depth and will form the basis of your dissertation; it will be carried out under the supervision of a member of academic staff.
This project will develop your ability to engage in independent learning, and will prepare you for postgraduate research or careers in industry.
Course Structure
The MSc in Numerical Techniques for Finance is offered on a full-time basis over one year.
The course comprises 180 credits, split across 120 credits’ worth of core and optional modules and a 60-credit research project.
Modules are usually taught in small groups by experts in the field of Scientific Computation.
Written and oral presentations will be undertaken at various stages of the course.
During the summer period, you will conduct an independent research project under the supervision of academic staff.
Key facts
This particular course is offered in collaboration with the School of Computer Science and Information Technology and Nottingham University Business School.
The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 50 full-time academic staff.
In the 2001 Research Assessment Exercise, the School was awarded a grade of 5 for each of the areas of Pure Mathematics, Applied Mathematics and Statistics.
In the most recent Quality Assurance Agency Subject Review (2004/05), the School of Mathematical Sciences scored 23 out of 24 for the quality of its teaching.
