Computational Finance

5 credits

Syllabus, Master's level, 1TD185

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, 27 August 2009
Responsible department
Department of Information Technology

Entry requirements

Financial Mathematics II and Scientific Computing II (1TD395) or Scientific Computing, Bridging Course, 10 credits.

Learning outcomes

After the course, the student should be able to

  • solve stochastic differential equations within the field using Monte Carlo- och Monte Carlo-like methods
  • solve partial differential equations within the field using finite difference methods,
  • handle advanced software within the field,
  • evaluate numerical results,
  • interpret computed results

Content

The course contains different moments which are essential when practically working 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 within 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.

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