On the Robustness of Least-Squares Monte Carlo (LSM) for Pricing American Derivatives
AbstractThis 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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Bibliographic InfoArticle provided by Springer in its journal Review of Derivatives Research.
Volume (Year): 6 (2003)
Issue (Month): 2 (May)
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Web page: http://www.springerlink.com/link.asp?id=102989
Least-Squares Monte Carlo; option pricing; American options;
Other versions of this item:
- Manuel Moreno & Javier R. Navas, 2001. "On the robustness of least-squares Monte Carlo (LSM) for pricing American derivatives," Economics Working Papers 543, Department of Economics and Business, Universitat Pompeu Fabra.
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
- G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
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