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Quasi-Monte Carlo Algorithm for Pricing Options

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dc.contributor.author Li, Jenny X. es_CL
dc.date.accessioned 2014-07-31T21:25:05Z
dc.date.available 2014-07-31T21:25:05Z
dc.date.issued 2000 es_CL
dc.identifier.citation Revista de Análisis Económico 15(1): 2000, p. 111-119 es_CL
dc.identifier.issn 0716-5927 es_CL
dc.identifier.other eISSN 0718-8870 es_CL
dc.identifier.other es_CL
dc.identifier.uri http://repositorio.uahurtado.cl/handle/11242/1741
dc.description.abstract The purpose of this paper is to compare the use of Quasi-Monte Carlo methods, especially the use of recent developed (t; m; s)-nets, versus classical Monte Carlo method for valuing _nancial derivatives. Some research has indicate that under certain condition Quasi-Monte Carlo is superior than the traditional Monte Carlo in terms of rate of convergence and accuracy. In particular, theoretic results hinted that the so-called (t; m; s)-net suppose to be the most powerful one among all the Quasi-Monte Carlo methods when the problem is "smooth". However, the application of (t; m; s)-net was not included in the exist-ing simulation literatures. In this paper I will introduce the algorithms of generate the most common Quasi-Monte Carlo sequences, then im- plement these sequences in several path-dependent options. Our in- vestigation showed that Quasi-Monte Carlo methods outperform the traditional Monte Carlo. en_US
dc.language.iso eng en_US
dc.publisher ILADES; Georgetown University; Universidad Alberto Hurtado. Facultad de Economía y Negocios es_CL
dc.rights Attribution 3.0 Unported
dc.rights.uri http://creativecommons.org/licenses/by/3.0/
dc.subject.lcsh Método�de�Monte�Carlo es_CL
dc.title Quasi-Monte Carlo Algorithm for Pricing Options es_CL
dc.type Artículo es_CL

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