Abstract
We present a robust multi-market optimization methodology for technical trading strategies, whereby robustness is incorporated via the environmental variables of the problem. The search for the optimum parameters is conducted over several markets, in the hope of exposing the GA to differing conditions, increasing the robustness of the solutions produced. Our results show an improvement in terms of performance for the solutions generated under this robust method when compared to those offered by single-market optimization.
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