Optimizing investment strategies with the reconfigurable hardware platform RIVYERA

Authors:
Christoph Starke;Vasco Grossmann;Lars Wienbrandt;Sven Koschnicke;John Carstens;Manfred Schimmler
Affiliations:
Department of Computer Science, Christian-Albrechts-University of Kiel, Kiel, Germany;Department of Computer Science, Christian-Albrechts-University of Kiel, Kiel, Germany;Department of Computer Science, Christian-Albrechts-University of Kiel, Kiel, Germany;Department of Computer Science, Christian-Albrechts-University of Kiel, Kiel, Germany;Department of Computer Science, Christian-Albrechts-University of Kiel, Kiel, Germany;Department of Computer Science, Christian-Albrechts-University of Kiel, Kiel, Germany
Venue:
International Journal of Reconfigurable Computing - Special issue on High-Performance Reconfigurable Computing
Year:
2012

Citing 3
Cited 0

Mining the stock market (extended abstract): which measure is best?

Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
A Massively Parallel Architecture for Bioinformatics

ICCS '09 Proceedings of the 9th International Conference on Computational Science: Part I
Breaking Elliptic Curve Cryptosystems Using Reconfigurable Hardware

FPL '10 Proceedings of the 2010 International Conference on Field Programmable Logic and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

The hardware structure of a processing element used for optimization of an investment strategy for financial markets is presented. It is shown how this processing element can be multiply implemented on the massively parallel FPGA-machine RIVYERA. This leads to a speedup of a factor of about 17,000 in comparison to one single high-performance PC, while saving more than 99% of the consumed energy. Furthermore, it is shown for a special security and different time periods that the optimized investment strategy delivers an outperformance between 2 and 14 percent in relation to a buy and hold strategy.