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On the Robustness of Least-Squares Monte Carlo (LSM) for Pricing American Derivatives Author info | Abstract | Publisher info | Download info | Related research | Statistics Manuel Moreno ()
Javier Navas ()
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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. Copyright Kluwer Academic Publishers 2003
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Article provided by Springer in its journal Review of Derivatives Research .
Volume (Year): 6 (2003)
Issue (Month): 2 (May)
Pages: 107-128
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Handle: RePEc:kap:revdev:v:6:y:2003:i:2:p:107-128Contact details of provider: Web page: http://www.springerlink.com/link.asp?id=102989
For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).
Keywords: Least-Squares Monte Carlo ; option pricing ; American options ; Other versions of this item:
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references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
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