Syllabus for Computational Finance: Calibration and Estimation

Finansiella beräkningsmetoder - kalibrering och parameterskattning


  • 5 credits
  • Course code: 1TD188
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Computer Science A1N, Computational Science A1N, Financial Mathematics A1N
  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2014-03-13
  • Established by:
  • Revised: 2018-08-30
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: week 24, 2019
  • Entry requirements: Scientific Computing II or Scientific Computing, Bridging Course, 5 credits, and one course in mathematical statistics (at least 5 credits). Financial Derivatives is recommended.
    English language proficiency that corresponds to English studies at upper secondary (high school) level in Sweden ("English 6").
  • Responsible department: Department of Information Technology

Learning outcomes

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

  • describe and implement solution methodologies and optimisation methods for calibration of interest rate models and calibration of a single underlier model;
  • describe and implement solution methodologies for filtering and parameter estimation in financial models;
  • use advanced software for calibration of models and parameter estimation for financial applications;
  • appraise, interpret and discuss computational results orally and in a written report;
  • summarise a scientific paper in the area.


The course contains areas which are essential when practically dealing with computational methods in finance in engineering and research. The content includes methods for calibration of stochastic models for financial applications, optimisation methods for calibration, filtering, maximum likelihood-estimation and Kalman-filter. 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.


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


Projects/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.

Reading list

Reading list

Applies from: week 24, 2019

  • Hirsa, Ali Computational methods in finance

    Boca Raton, FL: CRC Press, 2013

    Find in the library