Master’s studies

Syllabus for Computational Finance: Calibration and Estimation

Finansiella beräkningsmetoder - kalibrering och parameterskattning

Syllabus

  • 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), 3, 4, 5
  • Established: 2014-03-13
  • Established by: The Faculty Board of Science and Technology
  • Revised: 2014-03-13
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: week 50, 2014
  • 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.
  • Responsible department: Department of Information Technology

Learning outcomes

After 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.

Content

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.

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.

Reading list

Reading list

Applies from: week 14, 2015

  • Hirsa, Ali Computational methods in finance

    Boca Raton, FL: CRC Press, 2013

    Find in the library

    Mandatory