Accelerating the least-square Monte Carlo method with parallel computing

被引：4

作者：

Chen, Ching-Wen ^{[1
]}

Huang, Kuan-Lin ^{[1
]}

Lyuu, Yuh-Dauh ^{[2
]}

机构：

[1] Natl Taiwan Univ, Dept Comp Sci & Informat Engn, Taipei 10617, Taiwan

[2] Natl Taiwan Univ, Dept Comp Sci & Informat Engn, Dept Finance, Taipei 10617, Taiwan

来源：

JOURNAL OF SUPERCOMPUTING | 2015年 / 71卷 / 09期

关键词：

Least-squares Monte Carlo; Parallel computing; Option pricing; PVM; OPTIONS;

D O I：

10.1007/s11227-015-1451-7

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：3593 / 3608

页数：16

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