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Accelerating the least-square Monte Carlo method with parallel computing.

Authors :
Chen, Ching-Wen
Huang, Kuan-Lin
Lyuu, Yuh-Dauh
Source :
Journal of Supercomputing. Sep2015, Vol. 71 Issue 9, p3593-3608. 16p.
Publication Year :
2015

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09208542
Volume :
71
Issue :
9
Database :
Academic Search Index
Journal :
Journal of Supercomputing
Publication Type :
Academic Journal
Accession number :
109115974
Full Text :
https://doi.org/10.1007/s11227-015-1451-7