On the robustness of least-squares Monte Carlo (LSM) for pricing American derivatives

Manuel Moreno and Javier Navas

Economics Working Papers from Department of Economics and Business, Universitat Pompeu Fabra

Abstract: This paper analyses the robustness of Least-Squares Monte Carlo, a technique recently 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 provide evidence that a) this approach is very robust to the choice of different alternative polynomials and b) few basis functions are required. However, these conclusions are not reached when analyzing more complex derivatives.

Keywords: Least-Squares Monte Carlo; option pricing; American options (search for similar items in EconPapers)
JEL-codes: C15 C60 G13 (search for similar items in EconPapers)
Date: 2001-04
New Economics Papers: this item is included in nep-cmp and nep-fin
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Related works:
Journal Article: On the Robustness of Least-Squares Monte Carlo (LSM) for Pricing American Derivatives (2003)
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Persistent link: https://EconPapers.repec.org/RePEc:upf:upfgen:543

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