HPCwire: High Frequency Trading Benefits from Fermi Architecture

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May 06, 2010

High Frequency Trading Benefits from Fermi Architecture

Early CUDA results on Fermi

May 6 -- More and more financial market participants are focussed on high-frequency trading. They are submitting buy or sell orders on time scales of few milliseconds to an exchange located, for example, in New York, London, Tokyo, or Frankfurt. On these time scales, not only the access to the stock exchange is of crucial importance. Decisions have to be made in fractions of a second. Statistically-driven market participants are using historical stock data sets in order to generate automatically buy or sell orders which are then routed to the exchange with the velocity of light.

Thus, they have to perform time series analyses in a very short period of time. It was shown that simple concepts of time series analyses -- especially the analysis of financial market data -- can be accelerated on NVIDIA GPUs using CUDA. A more sophisticated analysis approach makes it possible to detect financial patterns on a transaction-by-transaction level. This approach quantifies pattern-based complex short-time correlations of time series. In context of financial market time series, the existence of complex correlations implies that reactions of market participants to a given time series pattern are related to comparable patterns in the past. Thus, the aim is to compare a current pattern of a certain time interval length ?t- with all possible previous patterns of the time series.

With the release of NVIDIA's new Fermi architecture, it is possible to use promising high-end graphics cards for benchmark tests -- we use a GTX 480 with CUDA 3.0. Simple methods, such as autocorrelation functions and scaling exponents, can be achieved 50 percent to 60 percent faster than on one chip of a GTX 295.

However, the detection of financial trading patterns benefits not only from the highly increased number of processing cores -- now 480 stream processor cores can be used on a single chip. "The new cache structure in combination with the huge number of processor cores provides excellent resources for high-frequency trading," says Tobias Preis, managing director of Artemis Capital Asset Management.

The calculation of pattern-based correlations can be accelerated by a factor of 2.3 in comparison to the previous GPU generation. The pattern conformity is the most accurate measure to characterize the short-term correlations of a general time series. It is essentially given by the comparison of subsequences of the time series. Subsequences of various lengths are compared with historical sequences in order to extract similar reactions on similar patterns.

More information can be found on www.tobiaspreis.de.

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Source: Tobias Preis

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