Simulations (e.g. of future scenarios) help gathering deeper insights on the behaviour of complex systems. Advanced computing concepts like grid computing enable large scale simulations to scale with real world requirements. A wide range of different techniques is required: genetic algorithms, financial models, high quality-random number generators, ...

Members of the Approximity team contributed to the following publications:

  • Simulation of the Yield Curve: Checking a Cox-Ingersoll-Ross Model
    Tom Fischer, A. May and B. Walther
    preprint, TU Darmstadt
    We give a complete description of a simulation of future bond prices by a one-factor Cox-Ingersoll-Ross (CIR) interest rate model. Explicit methods and formulas are provided, the time series service of the German Federal Reserve is used as data source. Several model checks are developed and applied to the CIR model. As a result, the model has to be rejected for the German debt securities market.
  • Anpassung eines CIR-k-Modells mit Hilfe der Kalman-Filter-Methode
    Tom Fischer, Angelika May, Brigitte Walther
    preprint, TU Darmstadt
    (German article for practitioners in German life insurance companies). In dieser Arbeit wird erlaeutert, wie die Theorie des Kalman-Filters fuer die Parameterschaetzung eines Cox-Ingersoll-Ross-Models mit k Faktoren genutzt werden kann. Die zunaechst theoretische Ausfuehrung der Vorgehensweise wird an Hand des Deutschen Rentenmarkts konkretisiert.
  • Fondsgebundene Lebensversicherungen - Ein finanzmathematisches Simulationstool zur Tarifkalkulation in Versicherungsunternehmen Download
    Prof. Dr. Jürgen Lehn, Dr. Angelika May, Tom Fischer
    Projekt-Poster (PDF, 211KB) für das BMBF-Statusseminar BASF Ludwigshafen, 16.-17.12. 2002

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