Abstract
The paper presents a combined approach of using machine learning methods to select an effective trading strategy on the currency exchange. The presented approach uses the calculation of the linear regression angle coefficient by log return indicators and determination of the currency pair quotes trend in the next period based on the calculated coefficient sign. The multilayer feed-forward neural network predicts the angular coefficient value in the next 10-min period for the current 20-min period. The research contains practical experiments that estimate the ratio of effective strategies to non-effective ones based on the linear regression coefficients predicted values.
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This work was supported by the Russian Foundation for Basic Research under Grant No 18-01-00910.
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Alymova, E., Kudryavtsev, O. (2021). The Application of a Neural Network and Elements of Regression Analysis in the Development of a Methodology for Effective Foreign Exchange Trading. In: Shiryaev, A.N., Samouylov, K.E., Kozyrev, D.V. (eds) Recent Developments in Stochastic Methods and Applications. ICSM-5 2020. Springer Proceedings in Mathematics & Statistics, vol 371. Springer, Cham. https://doi.org/10.1007/978-3-030-83266-7_23
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DOI: https://doi.org/10.1007/978-3-030-83266-7_23
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