Optimal trading rules at hourly frequency in the foreign exchange markets

An accurate measure of profitability of Technical Analysis, free of "data snooping", requires the separation of the Training Set (where the parameters of the technical filter are obtained) from the Trading Set (where the profit results of this technical filter are studied, using parameters obtained in the former). The next task is how to obtain the "best" parameters for high profits. Following the suggestions of the literature, we used a Genetic Algorithm (GA) to spot the "best" parameters in the Training Set to be used, separately and independently, in the Trading Set. This paper presents quantitative results in the use of one GA applied to the Dual Moving Average Crossover rule (DMAC) applied to hourly data of the Euro-Dollar exchange rate between 1999 and 2006. One important feature of the paper is the use of a GA in an unconstrained and constrained optimization set-up. The first optimization aims at obtaining the highest profit rates. The second one looks for smoother profit rates. We study the impact of these two techniques on a kind of mean-variance relationship of profit rates. Unconstrained optimization yields an yearly average profits of 16.8%; the constrained one gets 13.4% (but with much lower volatility of cumulative profits overtime). © Springer-Verlag Italia 2012.