Entry requirements

Scientific Computing II or Scientific Computing, Bridging Course, 5 credits. Financial Derivatives is recommended.

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.

The software that is used is Front Arena and MATLAB.

Instruction

Recorded web-based lectures, lectures, guest lectures, seminars, group supervision and laboratory work. Participants work in groups as well as on individual basis.

Assessment

Projects/assignments presented in written reports and orally in seminars.