Parallel computing of a quasi-Monte Carlo algorithm for valuing derivatives

Jenny X. Li, Gary L. Mullen

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


The performance the standard Monte Carlo method is compared with the performance obtained through the use of (t,m,s)-nets in base b in the approximation of several high dimensional integral problems in valuing derivatives and other securities. The (t,m,s)-nets are generated by a parallel algorithm, where particular considerations are given to scalability of dynamic adaptive routing and load balancing in the design and implementation of the algorithm. From the numerical evidence it appears that such nets can be powerful tools for valuing such securities.
Original languageEnglish (US)
Pages (from-to)641-653
Number of pages13
JournalParallel Computing
Issue number5
StatePublished - Jan 1 2000
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-09-23

ASJC Scopus subject areas

  • Artificial Intelligence
  • Hardware and Architecture
  • Theoretical Computer Science
  • Computer Graphics and Computer-Aided Design
  • Software
  • Computer Networks and Communications


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