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.