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    Stock market statistical data analysis for prices forecasting and trading decision support
    (Dana, Italy, 2021) Грінберг, Галина Леонідівна; Grinberg, Galina
    A general problems and methods for stock market statistical analysis are analyzed. A new method for stock price forecasting problem is considered based on a time series structural decomposition approach realized in special assignment of wave component auto-regression model as a superposition of harmonics with tuning frequencies. Computer simulation has been fulfilled in order to evaluate the performance of proposed method and algorithms.