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Computational Aspects: Inversion Techniques

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Queues and Lévy Fluctuation Theory

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Abstract

In this chapter it is pointed out how to numerically evaluate fluctuation-theoretic quantities. Many results presented in this book are in terms of transforms, and fast and accurate algorithms are available to numerically invert these. We describe two intrinsically different approaches. In the first, jumps in one direction are approximated by a phase-type random variable, thus allowing (semi-)explicit evaluation of the Wiener–Hopf factors. The second approach numerically evaluates (by repeated inversion) the Wiener–Hopf factors.

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References

  1. Abate, J., Whitt, W.: Numerical inversion of Laplace transforms of probability distributions. ORSA J. Comput. 7, 36–43 (1995)

    Article  MATH  Google Scholar 

  2. Asghari, N., den Iseger, P., Mandjes, M.: Numerical techniques in Lévy fluctuation theory. Methodol. Comput. Appl. Probab. 16, 31–52 (2014)

    MathSciNet  MATH  Google Scholar 

  3. Asghari, N., Mandjes, M.: Transform-based evaluation of prices and Greeks of lookback options driven by Lévy processes. J. Comput. Financ. (accepted)

    Google Scholar 

  4. Asmussen, S.: Applied Probability and Queues, 2nd edn. Springer, New York (2003)

    MATH  Google Scholar 

  5. Asmussen, S., Nerman, O., Olsson, M.: Fitting phase-type distributions via the EM algorithm. Scand. J. Stat. 23, 419–441 (1996)

    MATH  Google Scholar 

  6. Carolan, C., Dykstra, R.: Characterization of the least concave majorant of Brownian motion, conditional on a vertex point, with application to construction. Ann. Inst. Stat. Math. 55, 487–497 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  7. Cooley, J., Tukey, J.: An algorithm for the machine calculation of complex Fourier series. Math. Comput. 19, 297–301 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  8. den Iseger, P.: Numerical transform inversion using Gaussian quadrature. Probab. Eng. Inf. Sci. 20, 1–44 (2006)

    MATH  Google Scholar 

  9. den Iseger, P., Oldenkamp, E.: Pricing guaranteed return rate products and discretely sampled Asian options. J. Comput. Financ. 9, 1–39 (2006)

    Google Scholar 

  10. Dubner, H., Abate, J.: Numerical inversion of Laplace transforms by relating them to the finite Fourier cosine transform. J. ACM 15, 115–123 (1968)

    Article  MathSciNet  MATH  Google Scholar 

  11. Feldmann, A., Whitt, W.: Fitting mixtures of exponentials to long-tail distributions to analyze network performance models. Perform. Eval. 31, 245–279 (1998)

    Article  Google Scholar 

  12. Fu, M.: Variance-Gamma and Monte Carlo. In: Fu, M., Jarrow, R., Yen, J., Elliott, R. (eds.) Advances in Mathematical Finance, pp. 21–35. Birkhäuser, Boston (2007)

    Chapter  Google Scholar 

  13. Groeneboom, P.: The concave majorant of Brownian motion. Ann. Probab. 11, 1016–1027 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  14. Gruntjes, P., den Iseger, P., Mandjes, M.: A Wiener–Hopf based approach to numerical computations in fluctuation theory for Lévy processes. Math. Methods Oper. Res. 78, 101–118 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  15. Horváth, A., Telek, M.: Approximating heavy tailed behavior with phase type distributions. In: Proceedings of 3rd International Conference on Matrix-Analytic Methods in Stochastic Models, Leuven (2000)

    Google Scholar 

  16. Lewis, A., Mordecki, E.: Wiener–Hopf factorization for Lévy processes having positive jumps with rational transforms. J. Appl. Probab. 45, 118–134 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  17. Thümmler, A., Buchholz, P., Telek, M.: A novel approach for phase-type fitting with the EM Algorithm. IEEE Trans. Dependable Sec. Comput. 3, 245–258 (2006)

    Article  Google Scholar 

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Dębicki, K., Mandjes, M. (2015). Computational Aspects: Inversion Techniques. In: Queues and Lévy Fluctuation Theory. Universitext. Springer, Cham. https://doi.org/10.1007/978-3-319-20693-6_16

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