  The present study deals with the analysis and mapping of Swiss franc interest
rates. Interest rates depend on time and maturity, defining term structure of
the interest rate curves (IRC). In the present study IRC are considered in a
two-dimensional feature space - time and maturity. Geostatistical models and
machine learning algorithms (multilayer perceptron and Support Vector Machines)
were applied to produce interest rate maps. IR maps can be used for the
visualisation and patterns perception purposes, to develop and to explore
economical hypotheses, to produce dynamic asses-liability simulations and for
the financial risk assessments. The feasibility of an application of interest
rates mapping approach for the IRC forecasting is considered as well.
