Novel GPU Approach in Predicting the Directional Trend of the S&P 500

Our goal is development of an algorithm capable of
predicting the directional trend of the Standard and Poor’s 500 index
(S&P 500). Extensive research has been published attempting to
predict different financial markets using historical data testing on an
in-sample and trend basis, with many authors employing excessively
complex mathematical techniques. In reviewing and evaluating these
in-sample methodologies, it became evident that this approach was
unable to achieve sufficiently reliable prediction performance for
commercial exploitation. For these reasons, we moved to an out-ofsample
strategy based on linear regression analysis of an extensive
set of financial data correlated with historical closing prices of the
S&P 500. We are pleased to report a directional trend accuracy of
greater than 55% for tomorrow (t+1) in predicting the S&P 500.

• A. J. Regan
• F. J. Lidgey
• M. Betteridge
• P. Georgiou
• C. Toumazou
• K. Hayatleh
• J. R. Dibble

• Financial algorithm
• GPU
• S&P 500
• stock market prediction.

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