Authors
Anthony Brabazon, Michael O'Neill
Publication date
2003/6/23
Conference
IC-AI
Pages
492-498
Description
Evolution to uncover a series of useful technical trading rules which can be used to trade foreign exchange markets. In this study, each of the evolved programs represents a market trading system and implicitly, a predictive model. The form of these programs is not specified ex-ante but emerges by means of an evolutionary process. Daily US Dollar-DM exchange rates for the period 9/3/93 to 13/10/97 are used to train and test the model. The preliminary findings suggest that the developed rules earn positive returns in hold-out sample test periods after allowing for trading and slippage costs. This suggests potential for future research to determine whether further refinement of the methodology adopted in this study could improve the returns earned by the developed rules.
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