Fitting Financial Models to Market Data Using Kriging
Eelse-jan Stutvoet
Site of the project:
Delft University of Technology
start of the project:
October 2006
For working address etc. we refer to our
alumnipage.
Summary of the master project:
To obtain an optimal parameter set for various financial models, we
minimize the distance of a set to the market data in the least square
sense. We use a Kriging model, which approximates the surface of model
from sample points. These sample points are treated as realizations of
a
random variable. This way we obtain a mean and a variance for each
parameter set. Using a genetic algorithm we search for the point which
is expected to improve the model the most and include this point in
the
approximation. We repeat this process until the optimal parameter set
is
found.
Contact information:
Kees
Vuik
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