Accelerating the least-square Monte Carlo method with parallel computing

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...

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Bibliographic Details
Published in:The Journal of supercomputing 2015-09, Vol.71 (9), p.3593-3608
Main Authors: Chen, Ching-Wen, Huang, Kuan-Lin, Lyuu, Yuh-Dauh
Format: Article
Language:English
Subjects:
Compilers
Computer Science
Interpreters
Processor Architectures
Programming Languages
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Summary: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.
ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-015-1451-7