Accelerated Fluctuation Analysis by Graphic Cards and Complex Pattern Formation in Financial Markets

September 22nd, 2009


The compute unified device architecture is an almost conventional programming approach for managing computations on a graphics processing unit (GPU) as a data-parallel computing device. With a maximum number of 240 cores in combination with a high memory bandwidth, a recent GPU offers resources for computational physics. We apply this technology to methods of fluctuation analysis, which includes determination of the scaling behavior of a stochastic process and the equilibrium autocorrelation function. Additionally, the recently introduced pattern formation conformity (Preis T et al 2008 Europhys. Lett. 82 68005), which quantifies pattern-based complex short-time correlations of a time series, is calculated on a GPU and analyzed in detail. Results are obtained up to 84 times faster than on a current central processing unit core. When we apply this method to high-frequency time series of the German BUND future, we find significant pattern-based correlations on short time scales. Furthermore, an anti-persistent behavior can be found on short time scales. Additionally, we compare the recent GPU generation, which provides a theoretical peak performance of up to roughly 1012 [ed. should be 1 Trillion] floating point operations per second with the previous one.

(Tobias Preis et al., Accelerated fluctuation analysis by graphic cards and complex pattern formation in financial markets, New J. Phys. 11 093024 (21pp) doi: 10.1088/1367-2630/11/9/093024)