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

Moreno, ManuelNavas, Javier R.Universitat Pompeu Fabra. Departament d'Economia i Empresa2017-07-262017-07-262001-04-01Review of Derivatives Research, 6 (2003), 2 (May), pp. 107-128http://hdl.handle.net/10230/951This 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.application/pdfengL'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative CommonsOn the robustness of least-squares Monte Carlo (LSM) for pricing American derivativesinfo:eu-repo/semantics/workingPaperleast-squares monte carlooption pricingamerican optionsFinance and Accountinginfo:eu-repo/semantics/openAccess