Bergische Universität Wuppertal
Fachbereich Mathematik und Naturwissenschaften
Angewandte Mathematik - Numerische Analysis

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Numerical Evaluation of Complex Logarithms in the Cox-Ingersoll-Ross Model


Masterarbeit Mathematik



Supervision


Description

The Cox-Ingersoll-Ross (CIR) model has been a benchmark in finance for many years because of its analytical and structural tractability. The wide applications and extensions of the CIR model requires to evaluate the cumulative distribution function (CDF) of the integrated CIR process in financial modelling.

Usually the characteristic function of the integrated CIR process is known analytically and one can use the option pricing method of Carr and Madan to transform it into the corresponding CDF. This characteristic function is defined via complex logarithms which often leads to numerical instabilities when it is integrated using the inverse Fourier transform. Typically, this instability is expected to be apparent for wide ranges of model parameters.

In this thesis, we adapt the recent approach by Kahl and Jäckel for the Heston model to deal with such instability problems. Our new strategy allows to construct a very robust routine to determine numerically a highly accurate CDF of the integrated CIR process for almost any choices of parameters.

Keywords

Cox-Ingersoll-Ross model, interest-rate dynamics, Fourier inversion methods, complex logarithm, oscillatory integral, Gauss-Lobatto quadrature.

References:

  1. G. Bakshi, D. Madan, Spanning and derivative-security valuation, J. Fin. Econ. 55 (2000), 205-238.
  2. D. Brigo, K. Chourdakis, Counterparty Risk for Credit Default Swaps: Impact of spread volatility and default correlation, Int. J. Theoret. Appl. Fin. 12 (2009), 1007-1026.
  3. K. Chourdakis, Option Pricing using the Fractional FFT, J. Comput. Fin. 8 (2005), 1-18.
  4. P. Carr, D. Madan, Option Valuation using the Fast Fourier Transform, J. Comput. Fin. 2 (1999), 61-73.
  5. J. Cox, J. Ingersoll, S. Ross, A Theory of the Term Structure of Interest Rates, Econometrica 53 (1985), 385-408.
  6. R.J. Elliot, P.E. Kopp, Mathematics of Financial Markets, Springer, 2004.
  7. W. Gander, W. Gautschi, Adaptive Quadrature - Revisited, BIT 40 (2000), 84-101.
  8. C. Kahl, P. Jäckel, Not-so-complex Logarithms in the Heston Model, Wilmott Magazine, September 2005, 94-103.
  9. R. Lee, Option Pricing by Transform Methods: Extensions, Unification, and Error Control, J. Comput. Fin. 7 (2005), 51-86.
  10. R. Schöbel, J. Zhu, Stochastic Volatility With an Ornstein Uhlenbeck Process: An Extension, Europ. Fin. Rev. 3 (1999), 23-46.
  11. A. Sepp, Pricing European-Style Options under Jump Diffusion Processes with Stochastic Volatility: Application of Fourier Transform, Working paper, Institute of Mathematical Statistics, Faculty of Mathematics and Computer Science, University of Tartu, J. Liivi 2, 50409 Tartu, Estonia, September 2003.
  12. L. Teng, M. Ehrhardt, M. Günther, Numerical evaluation of complex logarithms in the Cox-Ingersoll-Ross model, Int. J. Comput. Math. 90 (2013), 1083-1095.


University of Wuppertal
Faculty of Mathematics and Natural Sciences
Department of Mathematics
Applied Mathematics & Numerical Analysis Group

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