| dc.creator | Li, Jenny X. | |
| dc.date | 2014-07-31T21:25:05Z | |
| dc.date | 2014-07-31T21:25:05Z | |
| dc.date | 2000 | |
| dc.date.accessioned | 2018-04-19T21:04:05Z | |
| dc.date.available | 2018-04-19T21:04:05Z | |
| dc.identifier | Revista de Análisis Económico 15(1): 2000, p. 111-119 | |
| dc.identifier | 0716-5927 | |
| dc.identifier | eISSN 0718-8870 | |
| dc.identifier | | |
| dc.identifier | http://repositorio.uahurtado.cl/handle/11242/1741 | |
| dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/1370765 | |
| dc.description | 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. | |
| dc.language | eng | |
| dc.publisher | ILADES; Georgetown University; Universidad Alberto Hurtado. Facultad de Economía y Negocios | |
| dc.rights | Attribution 3.0 Unported | |
| dc.rights | http://creativecommons.org/licenses/by/3.0/ | |
| dc.subject | Método�de�Monte�Carlo | |
| dc.title | Quasi-Monte Carlo Algorithm for Pricing Options | |
| dc.type | Artículos de revistas | |
