Abstract
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.
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© 2005 Springer-Verlag Berlin Heidelberg
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Barua, S., Thulasiram, R.K., Thulasiraman, P. (2005). High Performance Computing for a Financial Application Using Fast Fourier Transform. In: Cunha, J.C., Medeiros, P.D. (eds) Euro-Par 2005 Parallel Processing. Euro-Par 2005. Lecture Notes in Computer Science, vol 3648. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11549468_136
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DOI: https://doi.org/10.1007/11549468_136
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28700-1
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