Computational Finance
5 credits
Syllabus, Master's level, 1TD185
This course has been discontinued.
A revised version of the syllabus is available.
- Code
- 1TD185
- Education cycle
- Second cycle
- Main field(s) of study and in-depth level
- Computational Science A1F, Computer Science A1F, Financial Mathematics A1F
- Grading system
- Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Finalised by
- The Faculty Board of Science and Technology, 15 April 2010
- Responsible department
- Department of Information Technology
Entry requirements
Financial Mathematics II and Scientific Computing II or Scientific Computing, Bridging Course, 10 credits.
Learning outcomes
After the course, the student should be able to
- describe solution methodologies based on Finite differences, Monte Carlo methods and Lattice methods;
- implement solvers based on Monte Carlo and Finite differences for European financial derivatives in one space dimension;
- describe similarities and differences in efficiency, convergence rate and complexity for the methods in previous item;
- describe how solvers for more complex types of financial derivatives can be developed, and for higher grades implement these solvers;
- use advanced software for pricing of financial derivatives;
- appraise, interpret and discuss computational results both orally and in a written report;
- read and summarise a scientific paper in the computational finance area.
Content
The course contains areas which are essential when practically dealing with computational finance in engineering and research. The content include Monte Carlo- and Monte Carlo-like methods, finite difference methods and the use of advanced software in the field. The course contains general parts, which all participants take, as well as a number of eligible modules. Thus, the course can partly be individually adjusted.
Assessment
Approved projects/assignments presented in written reports and orally in seminars.