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Study of new rare event simulation schemes and their application to extreme scenario generation

Author

Listed:
  • Agarwal, Ankush
  • De Marco, Stefano
  • Gobet, Emmanuel
  • Liu, Gang

Abstract

This is a companion paper based on our previous work on rare event simulation methods. In this paper, we provide an alternative proof for the ergodicity of shaking transformation in the Gaussian case and propose two variants of the existing methods with comparisons of numerical performance. In numerical tests, we also illustrate the idea of extreme scenario generation based on the convergence of marginal distributions of the underlying Markov chains and show the impact of the discretization of continuous time models on rare event probability estimation.

Suggested Citation

  • Agarwal, Ankush & De Marco, Stefano & Gobet, Emmanuel & Liu, Gang, 2018. "Study of new rare event simulation schemes and their application to extreme scenario generation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 143(C), pages 89-98.
    • Handle: RePEc:eee:matcom:v:143:y:2018:i:c:p:89-98
    DOI: 10.1016/j.matcom.2017.05.004
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    References listed on IDEAS

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    1. Breuer, Thomas & Csiszár, Imre, 2013. "Systematic stress tests with entropic plausibility constraints," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1552-1559.
    2. René Carmona & Jean-Pierre Fouque & Douglas Vestal, 2009. "Interacting particle systems for the computation of rare credit portfolio losses," Finance and Stochastics, Springer, vol. 13(4), pages 613-633, September.
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