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Machine Learning Methods in Algorithmic Trading Strategy Optimization – Design and Time Efficiency

, 1993), when others, such as the Hill Climbing or evolutionary methods, are based on heuristic approach ( Juels and Wattenbergy, 1994 ). The commonly used methods and algorithms with application in scientific problems are discussed by Hastie et al . (2013) and Hastie et al . (2001) . The algorithmic strategies are widely used in the financial markets, but most of them are not discussed in papers, due to exclusive character. Nevertheless, some types of the quantitative strategies are widely known, and therefore, discussed in books and papers. The strategy based

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The Proportions and Rates of Economic Activities as a Factor of Gross Value Added Maximization in Transition Economy

References Akbari, R., and Ziarati, K., 2011. A multi level evolutionary algorithm for optimizing numerical functions. International Journal of Industrial Engineering Computations, 2, 419-430. doi: http://dx.doi.org/10.5267/j.ijiec.2010.03.002 Atencia, M., Joya, G., and Sandoval, F., 2005. Hopfield Neural Networks for Parametric Identification of Dynamical Systems. Neural Processing Letters, 21(2), 143-152. doi: http://dx.doi.org/10.1007/s11063-004-3424-3 Balakrishnan, S., Kannan, P. S., Aravindan, C., and

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