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
收藏
页码：1246 / 1253
页数：8
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