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Knowledge-intensive genetic discovery in foreign exchange markets

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3 Author(s)
Bhattacharyya, S. ; Dept. of Inf. & Decision Sci., Illinois Univ., Chicago, IL, USA ; Pictet, O.V. ; Zumbach, G.

This paper considers the discovery of trading decision models from high-frequency foreign exchange (FX) markets data using genetic programming (GP). It presents a domain-related structuring of the representation and incorporation of semantic restrictions for GP-based searching of trading decision models. A defined symmetry property provides a basis for the semantics of FX trading models. The symmetry properties of basic indicator types useful in formulating trading models are defined, together with semantic restrictions governing their use in trading model specification. The semantics for trading model specification have been defined with respect to regular arithmetic, comparison and logical operators. This study also explores the use of two fitness criteria for optimization, showing more robust performance with a risk-adjusted measure of returns

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Evolutionary Computation, IEEE Transactions on  (Volume:6 ,  Issue: 2 )