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Minimum Variance Importance Sampling via Population Monte Carlo

Author

Listed:
  • Randal Douc

    (Crest)

  • Arnaud Guillin

    (Crest)

  • Jean-Michel Marin

    (Crest)

  • Christian P, Robert

    (Crest)

Abstract

Variance reduction has always been a central issue in Monte Carlo experiments.Population Monte Carlo can be used to this effect, in that a mixture of importancefunctions, called a D-kernel, can be iteratively optimised to achieve the minimumasymptotic variance for a function of interest among all possible mixtures. Theimplementation of this iterative scheme is illustrated for the computation of theprice of a European option in the Cox-Ingersoll-Ross model,

Suggested Citation

  • Randal Douc & Arnaud Guillin & Jean-Michel Marin & Christian P, Robert, 2005. "Minimum Variance Importance Sampling via Population Monte Carlo," Working Papers 2005-09, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:2005-09
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    References listed on IDEAS

    as
    1. Cox, John C. & Ingersoll Junior, Jonathan E. & Ross, Stephen A., 2007. "A theory of the term structure of interest rates," RAE - Revista de Administração de Empresas, FGV-EAESP Escola de Administração de Empresas de São Paulo (Brazil), vol. 47(2), April.
    2. repec:dau:papers:123456789/6072 is not listed on IDEAS
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