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The Journal of Supercomputing

Erschienen in:

01.09.2015

Accelerating the least-square Monte Carlo method with parallel computing

verfasst von: Ching-Wen Chen, Kuan-Lin Huang, Yuh-Dauh Lyuu

Erschienen in: The Journal of Supercomputing | Ausgabe 9/2015

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Abstract

This paper accelerates the critically important least-squares Monte Carlo method (LSM) in financial derivatives pricing with parallel computing. We parallelize LSM with space decomposition, turning it into an embarrassingly parallel algorithm. The program is implemented with Parallel Virtual Machine and ALGLIB. Our method gives accurate option prices with excellent speedup. Although this paper focuses on the pricing of options, the methodology is applicable to much more complex financial derivatives.

Vorheriger Artikel Design space exploration of hardware task superscalar architecture

Nächster Artikel Synchronization algorithm for predictors for SDRAM memories

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Titel: Accelerating the least-square Monte Carlo method with parallel computing
verfasst von: Ching-Wen Chen
Kuan-Lin Huang
Yuh-Dauh Lyuu
Publikationsdatum: 01.09.2015
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 9/2015
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-015-1451-7

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