High performance computing for a financial application using Fast Fourier Transform

被引：0

作者：

Barua, S ^{[1
]}

Thulasiram, RK ^{[1
]}

Thulasiraman, P ^{[1
]}

机构：

[1] Univ Manitoba, Dept Comp Sci, Winnipeg, MB R3T 2N2, Canada

来源：

EURO-PAR 2005 PARALLEL PROCESSING, PROCEEDINGS | 2005年 / 3648卷

关键词：

HPC for commercial application; option pricing; Fast Fourier Transform; mathematical modeling; parallel algorithm; data locality;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Fast Fourier Transform (FFT) has been used in many scientific and engineering applications. In the current study, we have applied the FFT for a novel application in finance. We have improved a recently proposed mathematical model of Fourier transform technique for pricing financial derivatives to help design and develop an effective parallel algorithm using a swapping technique that exploits data locality. We have implemented our algorithm on 20 node SunFire 6800 high performance computing system and compared the new algorithm with the traditional Cooley-Tukey algorithm We have presented the computed option values for various strike prices with a proper selection of strike-price spacing to ensure fine grid integration for FFT computation as well as to maximize the number of strikes lying in the desired region of the asset price.

引用

页码：1246 / 1253

页数：8

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