Valuing American options by weighted least-squares Quasi-Monte Carlo

  • Yang Haijun*
  • , Lei Yang
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

American options pricing has the backward nature of iterative search feature. Based on the least-squares Monte Carlo(LSM), this paper employs Faure sequences and doubles the sample's number by antithetic variate method to decrease the variance of simulation. Then, underling assets are valued. Thus, weighted least-squares quasi-Monte Carlo (WLSQM) is proposed by weighted least-squares regression. Comparing the two methods with option value, standard error and computation cost, WLSQM is better than LSM, which validates WLSQM is efficient on pricing American options.

Original languageEnglish
Title of host publication2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008
DOIs
StatePublished - 2008
Event2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008 - Dalian, China
Duration: 12 Oct 200814 Oct 2008

Publication series

Name2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008

Conference

Conference2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008
Country/TerritoryChina
CityDalian
Period12/10/0814/10/08

Keywords

  • American-style options
  • Antithetic variates method
  • Weighted least-squares quasi-Monte Carlo

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