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On the Robustness of Least-Squares Monte Carlo (LSM) for Pricing American Derivatives

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Abstract

This paper analyses the robustness of Least-Squares Monte Carlo, a technique proposed by Longstaff and Schwartz (2001) for pricing American options. This method is based on least-squares regressions in which the explanatory variables are certain polynomial functions. We analyze the impact of different basis functions on option prices. Numerical results for American put options show that this approach is quite robust to the choice of basis functions. For more complex derivatives, this choice can slightly affect option prices.

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Authors and Affiliations

  1. Department of Economics and Business, Universitat Pompeu Fabra, Carrer Ramón Trias Fargas 25-27, 08005, Barcelona, Spain

    Manuel Moreno

  2. Department of Finance, Instituto de Empresa, María de Molina 13, 28006, Madrid, Spain

    Javier F. Navas

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  1. Manuel Moreno
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  2. Javier F. Navas
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Moreno, M., Navas, J.F. On the Robustness of Least-Squares Monte Carlo (LSM) for Pricing American Derivatives. Review of Derivatives Research 6, 107–128 (2003). https://doi.org/10.1023/A:1027340210935

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