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

Jenny X. Li; Gary L. Mullen

doi:10.1016/S0167-8191(99)00124-6

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

Jenny X. Li, Gary L. Mullen

Research output: Contribution to journal › Article › peer-review

23 Scopus citations

Abstract

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 language	English (US)
Pages (from-to)	641-653
Number of pages	13
Journal	Parallel Computing
Volume	26
Issue number	5
DOIs	https://doi.org/10.1016/S0167-8191(99)00124-6
State	Published - Jan 1 2000
Externally published	Yes

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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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10.1016/S0167-8191(99)00124-6

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AB - 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.

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

Abstract

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ASJC Scopus subject areas

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