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Monte Carlo Pricing of American Options Using Nonparametric Regression

Author

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  • Pizzi Claudio

    (Universita' Ca' Foscari, Venice)

  • Pellizzari Paolo

    (universita' Ca' Foscari, Venice)

Abstract

This paper provides an introduction to Monte Carlo algorithms for pricing American options written on multiple assets, with special emphasis on methods that can be applied in a multi-dimensional setting. Simulated paths can be used to estimate by nonparametric regression the continuation value of the option or the optimal exercise policy and the value functions can then be computed by backward induction. The flexibility of nonparametric regression allows to obtain accurate price estimates with remarkable speed. For illustrative purposes we price one- and two-dimensional American options.

Suggested Citation

  • Pizzi Claudio & Pellizzari Paolo, 2002. "Monte Carlo Pricing of American Options Using Nonparametric Regression," Finance 0207007, University Library of Munich, Germany, revised 04 Mar 2003.
    • Handle: RePEc:wpa:wuwpfi:0207007
    Note: Type of Document - pdf; prepared on OzTeX on Macintosh; to print on Laser printer; pages: 345,395,4323247 ; figures: included
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    References listed on IDEAS

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    6. Boyle, Phelim P., 1988. "A Lattice Framework for Option Pricing with Two State Variables," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 23(1), pages 1-12, March.
    7. Barone-Adesi, Giovanni & Whaley, Robert E, 1987. "Efficient Analytic Approximation of American Option Values," Journal of Finance, American Finance Association, vol. 42(2), pages 301-320, June.
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    Cited by:

    1. Maximilian Mair & Jan Maruhn, 2013. "On the primal-dual algorithm for callable Bermudan options," Review of Derivatives Research, Springer, vol. 16(1), pages 79-110, April.

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    More about this item

    Keywords

    Option pricing; American options; Monte Carlo; nonparametric regression;
    All these keywords.

    JEL classification:

    • G - Financial Economics

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