This paper describes an extension of the traditional application of Genetic Programming in the domain of the prediction of daily currency exchange rates. In combination with trigonometric operators, we introduce a new set of high-order statistical functions in a unique representation and analyze each system performance using daily returns of the British Pound and Japanese Yen. We will demonstrate that the introduction of high-order statistical functions in combination with trigonometric functions will outperform other traditional models such as Genetic Programming with the basic function set and ARMA models. Performance will be measured on hit percentage, average percentage change, and profit.
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