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

Mostra el registre parcial de l'element Moreno, Manuel Navas, Javier R.
dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa 2017-07-26T12:08:03Z 2017-07-26T12:08:03Z 2001-04-01
dc.identifier.citation Review of Derivatives Research, 6 (2003), 2 (May), pp. 107-128
dc.description.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.
dc.language.iso eng
dc.relation.ispartofseries Economics and Business Working Papers Series; 543
dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
dc.title On the robustness of least-squares Monte Carlo (LSM) for pricing American derivatives
dc.type info:eu-repo/semantics/workingPaper 2017-07-23T02:06:05Z
dc.subject.keyword least-squares monte carlo
dc.subject.keyword option pricing
dc.subject.keyword american options
dc.subject.keyword Finance and Accounting
dc.rights.accessRights info:eu-repo/semantics/openAccess

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