Syllabus for Computational Finance: Pricing and Valuation

Learning outcomes

On completion of the course, the student should be able to:

• describe solution methodologies based on Finite differences, Monte Carlo methods and Lattice methods;
• describe similarities and differences in efficiency, convergence rate and complexity for the methods in previous item;
• implement solvers based on Monte Carlo and Finite differences for European financial derivatives in one space dimension;
• 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;
• 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

Assignments presented in written reports and orally in seminars.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.