Abstract
In this paper, the authors present an investment strategy based on moving averages (MA). The strategy on the basis of the relationship between two moving averages classifies events of opening long and short position. To gain desirable results it was enriched by extra filtering mechanisms, such as: StopLoss, first derivative of the difference of moving averages, and additional buffers within the classification rules—these parameters constitute the parameters space. The whole concept is based on machine learning principles. According to these principles, the values of the parameters are computed during the learning phase and applied in simulated trading during the testing phase. The experiments conducted showed that the strategy is effective for EURUSD 1 h currency pair.
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Wiliński, A., Zabłocki, M. (2015). The Investment Strategy Based on the Difference of Moving Averages with Parameters Adapted by Machine Learning. In: Wiliński, A., Fray, I., Pejaś, J. (eds) Soft Computing in Computer and Information Science. Advances in Intelligent Systems and Computing, vol 342. Springer, Cham. https://doi.org/10.1007/978-3-319-15147-2_18
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DOI: https://doi.org/10.1007/978-3-319-15147-2_18
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