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Generating Tempered Stable Random Variates from Mixture Representation

Author

Listed:
  • Piotr Jelonek

Abstract

The paper presents a new method of random number generation for tempered stable distribution. This method is easy to implement, faster than other available approaches when tempering is moderate and more accurate than the benchmark. All the results are given as parametric formulas that may be directly used by practitioners.

Suggested Citation

  • Piotr Jelonek, 2012. "Generating Tempered Stable Random Variates from Mixture Representation," Discussion Papers in Economics 12/14, Division of Economics, School of Business, University of Leicester.
    • Handle: RePEc:lec:leecon:12/14
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    File URL: https://www.le.ac.uk/economics/research/RePEc/lec/leecon/dp12-14.pdf
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    References listed on IDEAS

    as
    1. Karen J. Palmer & Martin S. Ridout & Byron J. T. Morgan, 2008. "Modelling cell generation times by using the tempered stable distribution," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(4), pages 379-397, September.
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    Cited by:

    1. Michele Leonardo Bianchi & Svetlozar T. Rachev & Frank J. Fabozzi, 2013. "Tempered stable Ornstein-Uhlenbeck processes: a practical view," Temi di discussione (Economic working papers) 912, Bank of Italy, Economic Research and International Relations Area.
    2. Michele Bianchi & Frank Fabozzi, 2014. "Discussion of ‘on simulation and properties of the stable law’ by Devroye and James," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(3), pages 353-357, August.
    3. Hasan Fallahgoul & Gregoire Loeper, 2021. "Modelling tail risk with tempered stable distributions: an overview," Annals of Operations Research, Springer, vol. 299(1), pages 1253-1280, April.

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    More about this item

    Keywords

    heavy tails; random number generation; tempered stable distribution;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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